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Received: 25 October 2021
Revised: 23 February 2022
Accepted: 25 April 2022
DOI: 10.1111/iji.12576
ORIGINAL ARTICLE
Differential distribution of vitamin D receptor (VDR) gene
variants and its expression in systemic lupus erythematosus
Thiago Sotero Fragoso3
Suelen Cristina de Lima2
Jaqueline De Azevêdo Silva1
Catarina Addobbati Jordão Cavalcanti1
Alexandre Domingues Barbosa4
Maria Eduarda de Albuquerque Borborema5
Thays Maria Costa de Lucena5
Angela Luzia Branco Pinto Duarte4
Sergio Crovella6
Paula Sandrin-Garcia7
1
Departamento de Genética, Universidade
Federal de Pernambuco, Recife, Brazil
2
Laboratório de Imunopatologia Keizo Asami,
Universidade Federal de Pernambuco, Recife,
Brazil
3
Serviço de Reumatologia do Hospital das
Clínicas, Universidade Federal de Alagoas,
Maceió, Brazil
4
Ambulatório de Reumatologia do Hospital
das Clínicas, Universidade Federal de
Pernambuco, Recife, Brazil
5
Laboratório de Genética e Biologia Molecular
Humana, Departamento de Genética,
Universidade Federal de Pernambuco, Recife,
Brazil
6
Department of Biological and Environmental
Sciences, College of Arts and Sciences, Qatar
University, Doha, State of Qatar
7
Departamento de Genética / Laboratório de
Imunopatologia Keizo Asami, Universidade
Federal de Pernambuco, Recife, Brazil
Abstract
Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disorder that displays an important genetic background. Vitamin D3 (VD3 ) through its receptor (VDR)
plays an important immunomodulatory role in autoimmune misbalance, being capable of modulating immune responses. Genetic alterations in VDR gene may contribute
to an altered risk in SLE development and clinical manifestations. We investigated
VDR SNPs (single nucleotide polymorphisms) frequencies in 128 SLE patients and 138
healthy controls (HC) and mRNA differential expression in 29 patients and 17 HC
regarding SLE susceptibility as well as clinical features. We observed that rs11168268
G allele (OR = 1.55, p = .01) and G/G genotype (OR = 2.69, p = .008) were associated
with increased SLE susceptibility. The rs2248098 G allele and A/G and G/G genotypes
were associated to lower SLE susceptibility (OR = 0.66, p = .01; OR = 0.46, p = .01;
OR = 0.44, p = .02, respectively). Regarding clinical features, we observed lower risk
for: rs11168268 A/G genotype and nephritis (OR = 0.31, p = .01); rs4760648 T/T genotype and photosensitivity (OR = 0.24, p = .02); rs1540339 T/T genotype and antibody
anti-dsDNA (OR = 0.19, p = .015); rs3890733 T/T genotype and serositis (OR = 0.10,
Correspondence
Paula Sandrin-Garcia, Departamento de
Genética / Universidade Federal de
Pernambuco (UFPE), Av. Prof. Moraes Rego,
1235, Recife CEP 50760–90, Brazil.
Email: paula.sandrin@ufpe.br
p = .01). We identified a significant downregulation in VDR expression levels when
compared patients and controls overall (p = 1.04e–7 ), in Cdx-2 A/G and G/G (p = .008
and p = .014, respectively) and in patients with nephritis (p = .016)
Our results suggested that VDR SNPs influence upon SLE susceptibility and in particular clinical features, acting on mRNA expression in SLE patients overall and the ones
Funding information
Coordenação de Aperfeiçoamento de Pessoal
de Nível Superior (Capes); Conselho Nacional
de Desenvolvimento Científico e
Tecnológico (CNPq); Fundação de Amparo à
Ciência e Tecnologia do Estado de Pernambuco
(FACEPE), Grant/Award Number:
APQ-0952-2.02/15
Int J Immunogenet. 2022;49:181–192.
with nephritis.
KEYWORDS
genetic variants, nephritis, SLE, VDR
wileyonlinelibrary.com/journal/iji
© 2022 John Wiley & Sons Ltd.
181
1
DE AZEVÊDO SILVA ET AL .
INTRODUCTION
rs11568820 (Cdx-2) (Figure 1a), in SLE Northeast Brazilian patients in
order to understand their consequence in our studied subject group,
Systemic lupus erythematosus (SLE) is a complex autoimmune disorder
since associations were previously described with different conse-
featured by different clinical manifestations (Mok & Lau, 2003). Indeed,
quences in other populations (Table 1). We also assessed VDR mRNA
SLE clinical heterogeneity led to the establishment of 11 criteria by
levels in order to evaluated gene expression profile in these patients,
the American College of Rheumatology (ACR), in which 4 are simul-
according its clinical manifestations (LN, photosensitivity, antibody
taneously needed for the disease’s formal diagnosis (Hochberg, 1997;
anti-dsDNA and serositis) and also comparing different genotypes
Tsokos, 2011). SLE hallmark is the over production of autoantibodies,
from rs11568820 SNP (Cdx2).
which leads to deposition of antibody-containing immune complexes
throughout the body featuring tissue and organ damage (Silva et al.,
2013). Additionally, a common feature in most of autoimmune diseases
2
MATERIAL AND METHODS
is a strong sex bias and especially in SLE this discrepancy is increased
towards woman in childbearing age (Yan et al., 2012). According to
2.1
Study design, location and subjects
the Brazilian Society of Rheumatology, epidemiology data in Brazil,
estimates around 65,000 people with lupus, the majority being women
We performed a case-control study to perform a genetic association
with 1 affected in every 1700 (Sociedade Brasileira de Reumatologia,
analysis and an experimental study with a quantitative case-control
2020).
approach to expression analysis. Genotyping patient group was
Several clinical complications are observed in patients with SLE,
composed by 128 females SLE patients (mean age 37.1 years ±
with emphasis on lupus nephritis (LN), one of the most severe mani-
10.5) diagnosed according to the ACR (Hochberg, 1997). All patients
festations of this disease that results in a glomerulonephritis caused
were selected from the Division of Rheumatology from a hospital
by an inflammatory response to endogenous immunogenic chromatin
in the metropolitan region of Recife, Pernambuco, Brazil. Patients
(Anders et al., 2020).
were classified according to the criteria of the American College
As a multifactorial disease, SLE presents an active interplay from
of Rheumatology (ACR) (Hochberg, 1997) and SLICC (cumulative
many altered genes, particularly the ones involved with immune
organic damage index (SLICC/ACR) or SLEDAI (disease activity index)
response regulation, responsible for disease’s establishment and main-
according to patient status. For clinical and laboratory evaluation of
tenance (Iruretagoyena et al., 2015; Mok & Lau, 2003). The steroid
SLE patients was collected the following data: photosensitivity, malar
hormone vitamin D (VD3 ) has as primary function calcium homeostasis
or discoid rashes, oral ulcers, serositis (pleuritis, pericarditis), arthritis,
and bone metabolism (Veldurthy et al., 2016), however recent studies
neuropsychiatric disorder (seizures, headache, psychosis), haema-
have been reported as a pleiotropic regulator of human physiology
tological alterations (haemolytic anaemia, leucopenia, lymphopenia,
and immune system modulation (Di Rosa et al., 2011). In fact, VD3 has
thrombocytopenia), presence of anti-double-strand DNA antibody
emerged as a potent immunosuppressive hormone, interfering with
(anti-ds-DNA), presence of antinuclear antibodies (ANA) and nephritic
T regulatory (Th) cell functions and modulation which may be a key
disorder. Nephritic disease was evaluated on laboratory parameters,
mechanism in SLE’s development (Kamen & Tangpricha, 2010). Besides
specifically changes in urine summary and 24 h proteinuria, as follows:
that, SLE Brazilian patients present overall low levels of vitamin D (Eloi
persistent proteinuria (>0.5 g/day or 3+) or abnormal cylindruria. The
et al., 2017).
health control (HC) group consisted by 138 healthy females (mean
VD3 exerts its actions through interaction with its specific receptor
age 33.5 years ± 13.4). The exclusion criteria were autoimmune,
named Vitamin D Receptor (VDR), which is widely spread throughout
renal, chronic inflammatory disease or infection diseases. Subjects
several organs, tissues and noteworthy, in all immune cells (Wang et al.,
were chosen randomly in the population and matched for sex, age,
2012). VDR is located on chromosome 12 (12q13.11) and encloses
ethnic group and same geographical area of the patients. Clinical and
several single nucleotide polymorphisms (SNPs), which can modulate
laboratorial characteristics are available at Table 2.
VDR levels and activity (Silva et al., 2013). The SNPs described in the
For assessing VDR gene expression levels we sampled 29 SLE
VDR are mainly in the promoter regions close to the f and c sites of
patients (clinical and laboratorial confirmation) and 17 individuals as
exon 1, between exons 2 and 9 and in the 3′UTR region (Figure 1). The
controls randomly selected. The inclusion and exclusion criteria were
most frequently VDR polymorphisms in the literature are: Cdx2 (G > A),
the same of genotyping study. SLE patients and healthy controls also
FokI (C > T), BsmI (A > G), EcoRV (G > A), ApaI (G > T) and TaqI (T > C)
denied any calcium or vitamin D replacement in the past two years.
(Uitterlinden et al., 2004). Polymorphisms in the VDR gene can alter
To evaluate the correlation of VDR mRNA levels and SLE activity, we
both gene function and expression, thus leading to altered VD action.
assessed the SLEDAI mean to obtain the activity profile of SLE group.
Since vitamin D levels has already been associated to inflammatory
diseases including SLE (Wöbke et al., 2014), attention in its role on
disease’s pathogenesis has dramatically grown.
2.2
VDR association study
Therefore, considering VD3 a key regulator in immune system, we
aimed to evaluated the TagSNPs: rs11168268, rs2248098, rs1540339,
Genomic DNA was isolated from peripheral blood samples using
rs4760648 and rs3890733 and functional SNPs: rs2228570 (FokI) and
DNA Wizard Genomic DNA Purification Kit (Promega, Madison, WI)
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182
F I G U R E 1 a) VDR gene schematic structure. The arrows indicate the position of all the assessed SNPs and the doted boxes indicate all the
tagged SNPs. (b) Haplotype graphical representation. Linkage Disequilibrium (LD) plot among the studied polymorphisms, whereas in a D’ values.
The marked red box represents the LD shows (D’ = 0.86) between the rs11168268 and rs2248098, demonstrating a strong linkage disequilibrium.
Graph from Haploview Software
according to manufacturer’s protocol. Polymorphisms were selected
2.3
VDR gene expression study
using the SNPBrowser software 4.0 (Applied Biosystems, Foster
City, CA) and HapMap database (http://hapmap.ncbi.nlm.nih.gov/). We
RNA isolation was performed using the Qiagen Whole Blood RNAse
selected TagSNPs: rs11168268, rs2248098, rs1540339, rs4760648,
kit, as described in manufacturer’s instructions. The RNA integrity was
rs3890733 (TagSNPs are representative SNPs in a gene region by
performed by agarose gel electrophoresis and quantification by Nan-
linkage disequilibrium) (LD) (Stram, 2004) and rs2228579 (Fok1) and
odrop 2000 (Thermo Scientific USA). SuperScript III First-Strand Syn-
rs11568820 (Cdx-2), SNPs with functional impact. All selected SNPs
thesis System for RT-PCR kit (Invitrogen, USA) was performed for
presented at least 10% Minimum Allele Frequency (MAF) in CEU and
cDNA synthesis using for each sample a standard input of 500 ng from
YRI populations and covered most of VDR gene (Figure 1a).
total RNA for reaction of 20 μl of cDNA. Oligo(dT) was used as primers
Genotyping was evaluated by Taqman Probes® (Applied Biosys-
in all samples.
tems, Foster City, CA) using the ABI7500 Real-Time PCR platform
The mRNA levels were determined for the target gene VDR and
(Applied Biosystems, Foster City, CA). Allelic discrimination followed
the reference genes GAPDH and β-Actin was used for data normal-
as recommended by the manufacturer and analysed using the SDS soft-
ization (VDR: Hs00172113_m1, GAPDH: Hs02758991_g1, ACTB: Hs
ware 2.3 (Applied Biosystems, Foster City, CA).
99999903_M1). Expression assays were performed on ABI 7500
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183
DE AZEVÊDO SILVA ET AL .
TA B L E 1
DE AZEVÊDO SILVA ET AL .
Most frequents SNPs assessed according populations
VDR SNP
Function
Author (reference)
Country (ethnicity)
Population
(cases/controls)
rs1544410
(BsmI)
Located on intron 8 (A > G or B > b).
Could affect mRNA stability and
VDR gene expression. Could
generate an alteration in the splice
sites for mRNA transcription or a
change in the intron regulatory
elements of VDR.
Ozaki et al., 2000
Japan (Asian)
58/87
SLE and allele B
(p < .0001)
Nephritis and
allele b (p = .03)
Huang et al., 2002
Taiwan (Asian)
47/90
SLE and allele B
(p < .0001)
Luo et al., 2012
China (Han Chinese)
337/239
SLE and allele B
(p = .031)
Nephritis and
allele B (p = .027)
Luo et al., 2011
China (Han Chinese)
271/130
SLE and allele F
(p = .001)
Carvalho et al., 2015
Portugal (Caucasian)
170/192
CT genotype and
higher SLICC value
(p = .031)
Salimi et al., 2019
Southeast Iranian
1027/139
CT genotype and
higher SLE
susceptibility
(p = .02)
Salimi et al., 2019
Southeast Iranian
1027/139
No association
Portugal (Caucasian)
170/192
TT genotype and
higher SLICC value
(p = .046)
Salimi et al., 2019
Southeast Iranian
1027/139
Tt genotype and
higher SLE
susceptibility
(p = .0002)
Silva et al., 2013
Brazil (Southeast)
158/190
Cutaneous
alterations
(p = .036)
rs2228570
(FokI)
Located on exon 2, generates a
non-synonymous polymorphism
with a change of C > T (also called
F > f), resulting in a change of
threonine to methionine. The
presence of the restriction site
FokI C allele (F allele), generates a
new start codon (ATG) 9 bp after
the common starting site, which
translates to a shorter truncated
VDR protein of 424 amino acids
with more transactivation
capacity as a transcription factor
than the wild type full-length VDR
A isoform (VDRA) with 427 amino
acids.
rs7975232
(ApaI)
Located on intron 8 (A > C also
called A > a), does not change the
amino acid sequence of the VDR
protein, therefore could affect
mRNA stability and the gene
expression of VDR;
rs731236
(TaqI)
Located on the exon 9 (C > T also
Carvalho et al., 2015
called T > t) and generates a
synonymous change of the
isoleucine amino acid in the coding
sequence, therefore it does not
change the encoded protein, but it
could influence the stability of the
mRNA.
rs11168268
TagSNP
Relevant results
(Continues)
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184
TA B L E 1
(Continued)
VDR SNP
Function
Author (reference)
Country (ethnicity)
Population
(cases/controls)
Relevant results
rs3890733
TagSNP
Silva et al., 2013
Brazil (Southeast)
158/190
Arthritis (p = .001)
rs2248098
TagSNP
Silva et al., 2013
Brazil (Southeast)
158/190
Immunological
alterations
(p = .040)
rs4760648
TagSNP
Silva et al., 2013
Brazil (Southeast)
158/190
Antibody
anti-dsDNA
(p = .036)
platform (Applied Biosystems, Foster City, CA, USA). Relative quantity
(RQ) of VDR mRNA was measured by quantification cycle (Cq) values
obtained for VDR and each of the endogenous reference genes from all
samples. Then, the mean value for each gene in each group was used
to calculate VDR mRNA levels using ΔCq as quantification method
TA B L E 2
studied
Clinical and laboratorial features from the SLE patients
Clinical/laboratorial characteristics
n (%)
Photosensitivity
80 (62.5%)
Malar Rash
77 (60.16%)
(Livak & Schmittgen, 2001). We performed all qPCR assays in technical
triplicates.
2.4
Statistical analysis
Discoid Rash
22 (17.19%)
Oral ulcers
27 (21%)
Serositis
28 (21.88%)
Arthritis
92 (71.8%)
Neuropsychiatric disorder
11 (8.5%)
SNPStats tool (http://bioinfo.iconcologia.net/SNPstats) was used for
Nephritic disorder
65 (50.7%)
calculate allele and genotype frequencies and Hardy–Weinberg equi-
Haematological alterations
87 (67.9%)
Antinuclear factor positive (FAN)
128 (100%)
Antibody anti DNA (anti ds-DNA)
33 (25.7%)
librium, and Fisher’s exact test was used to the statistical significance
of difference in allele and genotype frequencies. After Bonferroni’s
Correction, a p < .071 was considerate statistically significant for SNP
association study. For haplotype associations and linkage disequilibrium analysis (LD) was used Haploview Software (version 4.2). The
multivariate analysis logistic regression was performed to investigate
the association between the qualitative variables and dependent vari-
for rs2248098 (A > G) SNP, the G allele (OR = 0.66, CI = 0.46–0.94,
able binary: SLE risk and ACR clinical phenotypes. The open-source R
p = .01) and A/G (OR = 0.46, CI = 0.24–0.86, p = .01) and G/G
Studio 4.1.2 (www.r-project.org) was used for all statistical analyses.
(OR = 0.44, CI = 0.20–0.93, p = .02) genotypes were associated to
The post hoc power analysis was performed in the G*Power 3.1.9.4
lower SLE susceptibility, as shown in Table 3. For the rs2228570 (C > T)
software and the results were included at Table 2.
SNP, the frequency of C allele, C/T and C/C genotypes was increased
The statistical tests applied to gene expression analyses were:
in controls when compared to patients (OR = 0.19, p = 2.7 × 10−16 ;
Shapiro–Wilk, to verify the sample’s distribution, and Student’s t-test
OR = 0.14, p = 1.55 × 10−7 ; OR = 0.05, p = 1.77 × 10−13 , respectively),
and one-way ANOVA for analysis of variance, considering as statisti-
as shown in Table 3. However, this last result regarding rs2228570 is
cally significant in both p < .05 in a 95% confidence interval (95% CI).
biased once the patient’s group did not present H-W equilibrium.
For the SNPs rs4760648, rs1540339 and rs11568820, no significant difference in allelic and genotypic distribution was observed
3
RESULTS
(Table 3).
Regarding VDR polymorphisms and clinical and laboratorial char-
The VDR allelic and genotypic frequencies from all assessed SNPs
acteristics we report association between following SNPs and clini-
were in Hardy–Weinberg equilibrium in SLE patients and HC, except
cal features: rs11168268 A/G genotype (OR = 0.31, CI = 0.11–0.8,
for patients’ group in rs2228570 (FokI). The frequencies distribution
p = .01) with lower nephritis susceptibility; rs4760648 T/T genotype
presented significantly differed between SLE patients and HC in three
(OR = 0.24, CI = 0.05–0.9, p = .02) with diminished photosensitivity;
out of the seven assessed SNPs namely: rs11168268, rs2248098 and
rs1540339 T/T genotype (OR = 0.19, CI = 0.04–0.78, p = .015) with
rs2228570 as shown in Table 3.
less frequency of antibody anti-dsDNA and rs3890733 T/T genotype
For the rs11168268 (A > G) SNP, the G allele (OR = 1.55, CI = 1.08–
(OR = 0.10, CI = 0.002–0.81, p = .01) with lesser serositis develop-
2.23, p = .01) and G/G genotype (OR = 2.69, CI = 1.24–6.01, p = .008)
ment, as seen in Table 4. Multivariate analysis results are demonstrated
were associated to increased SLE susceptibility. In the other hand
at Table 5.
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185
DE AZEVÊDO SILVA ET AL .
DE AZEVÊDO SILVA ET AL .
Haplotype analysis was performed to assess linkage disequilibrium among the tested TagSNPs. We observed LD between TagSNPs
rs11168268 and rs2248048 (Dt’ = 0.86) as shown in Figure 1b. Even
though we identified a haplotype combination, no association was
observed to SLE or its clinical features susceptibility (data not shown).
We performed a relative gene expression assay to evaluate the
mRNA levels from VDR in SLE patients as well as in healthy controls.
We observed that overall VDR gene expression was downregulated in
patients (−10.51 FC, p = 1.04e−7 ) when compared to HC (Figure 2a).
We also analysed whether the Cdx-2 (rs11568820) genotypes (A/GG/G) influence VDR gene expression in SLE patients. Our analyses
indicated that the A/G and G/G genotypes decrease VDR mRNA levels
(−9.6, p = .008 and −12.6 FC, p = .014, respectively) when compared
to A/A genotype (Figure 2b).
When assessing VDR gene expression and altered risk for SLE clinical manifestations, we found a differential expression in patients with
nephritis (−5.7 FC, p = .016; Figure 2c). We also found a differential
expression in patients with skin alterations (+1.3 FC, p = .587), but the
data comparison is not statistically significant. The differential expression reported with mRNA levels from VDR and clinical manifestations
are showed in Figure 2a–c. Other clinical features were analysed, but
they did not present enough sampling power to be included in the
expression analyses.
4
DISCUSSION
In present study, we observed an association between rs11168268 and
rs2248098 and SLE development, where rs11168268 (A > G) SNP,
the G allele and G/G genotype conferred risk for SLE; and rs2248098
(A > G) SNP, the G allele, as well the A/G and G/G genotypes conferring
lower susceptibility to SLE. Interestingly, although these SNPs were not
associated with SLE itself, it had already been previously reported as
associated to clinical features in a southeast Brazilian population study
(Silva et al., 2013).
In our study, a strong linkage disequilibrium was observed between
rs11168268 and rs2248098. Interesting, Cavalcanti et al. (2016) also
verified significant linkage disequilibrium between these same SNPs
(D’ = 0.91, r2 = .72), corroborating our data (D’ = 0.86).
VDR plays a key role regulating vitamin D pathway and its physiological importance in immune modulation relates it to several immune
disorders, including SLE (Kamen et al., 2006; Wöbke et al., 2014). In our
study the presence of C allele as well C/T and C/C genotypes from FokI
SNP indicated a lower risk of SLE susceptibility. FokI display a cytosine
to thymine change (C > T) creating a methionine codon three codons
latter, which in turn, leads to a final protein with 424 amino acids (aa)
shorter than the one with the T allele, with 427aa. In fact, the shorter
F I G U R E 2 a) VDR expression graph comparing SLE patients and
HC. (b) VDR expression graph of SLE patients among from Cdx-2 SNP
genotypes (A/A n = 6; A/G n = 10; G/G n = 5). (c) VDR expression
graph of SLE patients or SLE nephritis (SLEN). The results were
normalized using GAPDH and ACTB as endogenous references. SLE:
patients with Systemic lupus erythematosus (n = 29); HC: Healthy
controls (n = 17); SLEN: patients with SLE and nephritis (n = 12); FC:
fold-change. * p < .05
variant (C) seems to interact more strongly to the transcription factor II
B (TFIIB) compared to the longer one. Therefore, it seems that the VDR
Two previous VDR association studies were performed in Brazil-
shorter protein may be more efficient than the longer one in activating
ian populations. The first one, by Monticielo et al. (2012), was per-
vitamin D pathway (Dzhebir et al., 2016). Besides the statistical associ-
formed in a south Brazilian population and included, amongst others,
ation, it is important to mention that in our population for this SNP, the
the two most studied VDR SNPs: BsmI and FokI. However, the authors
patient’s group was out of Hardy–Weinberg equilibrium.
did not find statistically significant differences in genotype and allelic
1744313x, 2022, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12576 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
186
TA B L E 3
Allelic and genotypic VDR SNPs and TagSNPs frequencies from all assessed SLE patients and HC
OR (95%CI)
p Value
SNP ID
HC
SLE patients
rs3890733
N = 138
N = 127
C
194 (70%)
169 (67%)
1.00
T
82 (30%)
85 (33%)
1.18 (0.81–1.74)
CC
69 (50%)
63 (49.6%)
1.00
CT
56 (40.6%)
43 (33.9%)
0.84 (0.48–1.46)
.84
1.76 (0.76–4.17)
.17
0.97 (0.66–1.44)
.92
Allele
.39
Genotype
TT
13 (9.4%)
21 (16.5%)
rs11568820
N =109
N = 115
G
124 (57%)
132 (57%)
A
94 (43%)
98 (43%)
GG
33 (30.3%)
40 (34.8%)
AG
58 (53.2%)
52 (45.2%)
0.74 (0.39–1.39)
.36
AA
18 (16.5%)
23 (20%)
1.05 (0.45–2.45)
1.00
rs2228570
N = 108
N = 107
T
71 (33%)
154 (72%)
1.00
C
145 (67%)
60 (28%)
0.19 (0.12–0.30)
TT
12 (11.1%)
60 (56.1%)
1.00
CT
47 (43.5%)
34 (31.8%)
0.14 (0.06 - 0.32)
1.55 × 10–7*
CC
49 (45.5%)
13 (12.2%)
0.05 (0.02–0.13)
1.77 × 10–13*
rs4760648
N = 138
N = 127
C
151 (55%)
132 (52%)
1.00
T
125 (45%)
122 (48%)
1.11 (0.78–1.59)
CC
37 (26.8%)
31 (24.4%)
1.00
CT
77 (55.8%)
70 (55.1%)
1.08 (0.58–2.0)
.88
TT
24 (17.4%)
26 (20.5%)
1.29 (0.58–2.86)
.57
rs1540339
N = 138
N = 128
C
193 (70%)
176 (69%)
1.00
T
83 (30%)
80 (31%)
1.05 (0.71–1.55)
CC
63 (45.6%)
62 (48.4%)
1.00
CT
67 (48.5%)
52 (40.6%)
0.78 (0.46–1.34)
.37
TT
8 (5.8%)
14 (10.9%)
1.77 (0.63–5.24)
.25
Allele
Genotype
Allelea
2.7 × 10–16*
Genotypea
Allele
.54
Genotype
Allele
.77
Genotype
(Continues)
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187
DE AZEVÊDO SILVA ET AL .
DE AZEVÊDO SILVA ET AL .
TA B L E 3
(Continued)
SNP ID
HC
SLE patients
rs2248098
N = 138
N = 127
OR (95%CI)
p Value
Allelea
A
127 (46%)
143 (56%)
1.00
G
149 (54%)
111 (44%)
0.66 (0.46–0.94)
AA
26 (18.8%)
43 (33.9%)
1.00
AG
75 (54.4%)
57 (44.9%)
0.46 (0.24–0.86)
.01*
GG
37 (26.8%)
27 (21.3%)
0.44 (0.20–0.93)
.02*
rs11168268
N = 138
N = 127
A
176 (64%)
135 (53%)
1.00
G
100 (36%)
119 (47%)
1.55 (1.08–2.23)
AA
54 (39.1%)
41 (32.3%)
1.00
AG
68 (49.3%)
53 (41.7%)
1.02 (0.57–1.83)
1.00
GG
16 (11.6%)
33 (26%)
2.69 (1.24–6.01)
.008*
.01*
Genotypea
Allelea
.01*
Genotypea
*p < .05; Values in bold are the results with association (significant p). The SNPs used in the study are in italics.
a
Power > 0.8.
frequencies between SLE patients and healthy individuals. The other
The most frequent and severe clinical finding in SLE patients is LN
study performed by our research group in a southeast Brazilian cohort
(Tang et al., 2017). LN is an important condition and major risk factor
and even though we did not find any association to SLE itself, we
for morbidity and mortality in SLE patients (Almaani et al., 2017). In our
reported association to cutaneous manifestations, arthritis, immuno-
study, we found a significant association between LN and the A/G geno-
logical alterations and antibody anti-dsDNA (Silva et al., 2013).
type of rs11168269 SNP. Corroborating with our findings, the TagSNP
In relation to VDR SNPs and clinical manifestations, the study
rs11168269 tags the BsmI, already reported as associated to LN lower
found statistically significant association with antibody anti-dsDNA
susceptibility. Located on intron 8, BsmI represents the change of ade-
(rs1540339), photosensitivity (rs4760648), nephritis (rs11168268)
nine for guanine (A > G), also called for B > b (BB, Bb and bb genotypes).
and serositis (rs3890733).
The SNP BsmI may affect mRNA stability and VDR gene expression,
In our study, the presence of T/T genotype of rs1540339 SNP is
altering in the splice sites in mRNA transcription or a change in intronic
associated with lower frequency of antibody anti-dsDNA presence.
regulatory elements of VDR (Luo et al., 2011; Luo et al., 2012). The LN
Corroborating with our findings, anti-dsDNA is an important marker to
pathogenesis is not completely elucidated. Low levels of Vitamin D may
evaluate the disease activity in SLE patients. Studies have shown that
play a role in SLE progression and nephritis development. On the other
SLE patients present vitamin D deficiency when compared to the gen-
hand, VD3 supplementation may prevent renal involvement by lessen-
eral population. SLE patients with VD3 deficiency presents increased
ing proteinuria risk, a frequent condition in LN patients (Yu et al., 2019).
disease’s activity and raised anti-dsDNA levels, which strengthen VD3
We also found an association between rs3890733 T/T genotype
role as an immune modulator in autoimmune diseases (Mok et al.,
and lower susceptibility to serositis. Serositis is an inflammation of
2012).
serous membranes and a significant cause of morbidity in SLE patients
Our results showed that the presence of rs4760648 T/T genotype
(Liang et al., 2017). Located at promoter region, rs3090733 is a TagSNP
confers a lower susceptibility to photosensitivity development and
that tags another six SNPs by linkage disequilibrium. The rs4334089
are in agreement with Silva et al (2013) that identified in southeast
is tagged by rs3090733 and its variant genotype A/A is associated
Brazilian population the same association. Photosensitivity is an
to lower risk to upper respiratory infection (URI) development. It is
important clinical manifestation in SLE patients and contributes to
hypothesized that the presence of this variant would improve the
poor life quality of these individuals (Klein et al., 2011). Lesions caused
inflammatory response performed by the VD3 /VDR complex (Jolliffe
by photosensitivity in SLE patients are characterized by increased epi-
et al., 2018). Although the literature lacks association studies correlat-
dermal apoptosis and infiltrate of inflammatory cells like dendritic cells
ing VDR and clinical features in SLE such as serositis, a study conducted
in the dermis (Kim & Chong, 2013). The immunoregulation promoted
by Luo et al. (2012), with SLE patients from Chinese population and
by VD3 in immune cells recruitment and cytokine liberation may play
VDR SNPs found a relation between ApaI and BsmI polymorphisms with
a crucial role in SLE patient response to lesions caused by ultraviolet
serositis and also an increased risk to SLE development considering
(UV) exposure (Correa-Rodríguez et al., 2021).
combined genotype Aa-bb.
1744313x, 2022, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12576 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
188
TA B L E 4
Genotypes from VDR SNVs and TagSNVs associated with SLE clinical manifestations
SNV
Clinical Feature
Genotype
OR
95%CI
p Value
rs1540339 (C > T)
Anti-dsDNA
TT
0.19
0.04–0.78
.015
rs3890733 (C > T)
Serositis
TT
0.10
0.002–0.81
.01
rs11168268 (A > G)
Nephritis
AG
0.31
0.11–0.8
.01
rs4760648 (C > T)
Photosensitivity
TT
0.24
0.05–0.9
.02
TA B L E 5 Multivariate analysis using as dependent variables SLE susceptibility and ACR clinical phenotypes and as independent variables
seven the SNPs analysed
Genotype
Dependent variables
rs2228570
C/T
SLE susceptibility
3.06 × 105
6.92 × 10−11
T/T
SLE susceptibility
4.45 × 10
.00584
C/T
Serositis
0.086
.009
Neurological alterations
0.179
.0316
0.082
.0123
0.121
.0208
rs4760648
Exponential value
p Value
SNP
T/T
4
rs11168268
A/G
Antibody anti-dsDNA
rs1540339
C/T
Discoid rash
−3.663
.0313
Photosensitivity
rs3890733
rs11568820
C/T
−6.495
.0408
Nephritis
0.204
.0402
Antibody anti-dsDNA
0.184
.0276
Neurological alterations
0.1705
.0214
Antibody anti-dsDNA
0.121
.014
G/G
Arthritis
−32.402
.0014
A/G
Nephritis
0.149
.045
Complex diseases as SLE presents several variants in specific
are deficient or insufficient in vitamin D levels compared with healthy
genes, as VDR, which provides diverse clinical phenotypes, rais-
controls, where 1,25(OH)2 D3 serum levels and VDR mRNA expression
ing a challenge in identifying genetic variations associated simul-
in peripheral blood were decreased in SLE patients and it could inhibit
taneously with correlated traits. Multivariate analysis should be
the activation of CD4+ T cells and suppress the immune response in
done to detect independent predictors of different clinical pheno-
SLE (Xiao et al., 2016). VD3 inhibits the action of activated B cells and
types. The multivariate analysis performed in the present study
induces their apoptosis. B cells, on the other hand, express mRNAs for
(Table 5) found statistically significant association with SLE suscep-
proteins involved in VD3 activity, including VDR, which consequently is
tibility and rs2228570 SNP (FokI). The analysis was also performed
regulated by vitamin D levels (Chen et al., 2007), in concordance with
using ACR clinical characteristics directly related to the accumulation
our results.
of immune complexes such as photosensitivity (rs1540339), serositis
In addition, when VDR gene expression was analysed in SLE patients
(rs4760648), neurological alterations (rs4760648, rs3890733), anti-
according rs11568820 (Cdx-2), a downregulation was observed in
body anti-dsDNA (rs11168268, rs1540339, rs3890733), discoid rash
patients with the genotype G/A and G/G, when compared to A/A
(rs1540339), nephritis (rs1540339, rs11568820/Cdx-2) and arthritis
genotype, indicating that, the G allele decreases VDR mRNA levels in
(rs11568820/Cdx-2). Inflammatory process is one of the most impor-
these individuals. The Cdx-2 polymorphism is located at VDR promoter
tant roles on SLE’s pathogenesis, and vitamin D levels has already been
region and consists in change of adenine to guanine, potentiating the
associated to its modulation (Iruretagoyena et al., 2015; Wöbke et al.,
binding strength between VDR and its transcriptional complex (Ralston
2014). In addition, a recent study shows vitamin D levels are associated
& Rossant, 2008; Savory et al., 2009).
with SLE activity and DNA damage growth (Correa-Rodríguez et al.,
2021).
When assessing VDR expression and risk for SLE clinical manifestations our analyses showed that patients with skin alterations as malar
Accessing VDR expression levels, we found a downregulation
rash, discoid rash and photosensitivity presents an upregulation of VDR
(−10.51 FC) in SLE patients comparing with HC group. VD3 /VDR
mRNA levels (+1.3 FC), however this data was not statistically signifi-
complex plays an important role in immune cells as monocytes,
cant. Individuals with SLE show increased cutaneous manifestations in
macrophages, dendritic, T and B cells (Wang et al., 2012). SLE patients
response to UV light exposure that induces apoptosis with subsequent
1744313x, 2022, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12576 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
189
DE AZEVÊDO SILVA ET AL .
DE AZEVÊDO SILVA ET AL .
immune complexes formation, justifying inflammation and skin lesions
Angela Luzia Branco Pinto Duarte
(Bijl & Kallenberg, 2006).
6434-9939
We also report a downregulation of VDR expression in patients that
present nephritis (−5.7 FC). Interestingly, several studies report signif-
Sergio Crovella
https://orcid.org/0000-0001-
https://orcid.org/0000-0001-8493-1168
Paula Sandrin-Garcia
https://orcid.org/0000-0003-4641-7429
icant associations of VDR SNPs with LN (Luo et al., 2012, Emerah & ElShal, 2013; Mostowska et al, 2013; Ozaki et al, 2000). Being ours the
first one to bring up an expression data from nephritis in SLE patients,
our results agree with the fact that 1,25(OH)2 D3 upregulates VDR gene
expression in kidney cells (Andress, 2006; Healy et al., 2003; Healy
et al., 2005) and since SLE patients with nephritic disorders have significantly lower vitamin D levels (Sumethkul et al., 2013), it justifies the
VDR downregulation detection. The kidney is one of the main organs
processing pro-forms of inactive vitamin D into active forms (1,25a-OH
vitamin D) (Veldurthy et al., 2016) when its function is impaired, it may
influence upon vitamin D levels, contributing to deficiency. Therefore,
due to our sample limitation we suggest that further studies needed to
be performed in other population to better elucidate the VDR role in
LN.
Our results support VDR polymorphisms and mRNA expression levels associated to SLE and some clinical features, particularly nephritis.
We also assessed in SLE patients according Cdx-2 genotype, which indicated a downregulation when compared to healthy individuals. To the
better of our knowledge, this was the first and only study to evaluate
almost the completed VDR gene SNPs by linkage disequilibrium. Our
main limitation is the relatively small sample size from SLE patients’
group and not following the functional analysis from the associations
detected, falling into the main gap of all genetic association studies.
Thus, these findings reinforce the VDR key role in SLE and its clinical
features.
ACKNOWLEDGEMENTS
This work was supported by the Brazilian funding agencies: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
and Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE) under Grant APQ-0952-2.02/15.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
ORCID
Jaqueline De Azevêdo Silva
https://orcid.org/0000-0003-1660-7299
Suelen Cristina de Lima
https://orcid.org/0000-0003-3793-5152
Thiago Sotero Fragoso
https://orcid.org/0000-0002-0192-0760
Catarina Addobbati Jordão Cavalcanti
https://orcid.org/0000-0001-
6598-0482
Alexandre Domingues Barbosa
https://orcid.org/0000-0002-8055-
0509
Maria Eduarda de Albuquerque Borborema
https://orcid.org/0000-
0002-6692-3356
Thays Maria Costa de Lucena
5833
https://orcid.org/0000-0002-1923-
REFERENCES
Almaani, S., Meara, A., & Rovin, B. H. (2017). Update on lupus nephritis.
Clinical Journal of the American Society of Nephrology, 12(5), 825–835.
https://doi.org/10.2215/CJN.05780616
Anders, H. - J., Saxena, R., Zhao, M., Parodis, I., Salmon, J. E., & Mohan, C.
(2020). Lupus nephritis. Nature Reviews Disease Primers, 6(1), 7. https://
doi.org/10.1038/s41572-019-0141-9
Andress, D. L. (2006). Vitamin D in chronic kidney disease: A systemic role
for selective vitamin D receptor activation. Kidney International, 69(1),
33–43. https://doi.org/10.1038/sj.ki.5000045
Bijl, M., & Kallenberg, C. G. (2006). Ultraviolet light and cutaneous lupus.
Lupus, 15(11), 724–727. https://doi.org/10.1177/09612033060717
05
Carvalho, C., Marinho, A., Leal, B., Bettencourt, A., Boleixa, D., Almeida, I.,
Farinha, F., Costa, P. P., Vasconcelos, C., & Silva, B. M. (2015). Association between vitamin D receptor ( VDR ) gene polymorphisms and systemic lupus erythematosus in Portuguese patients. Lupus, 24(8), 846–
853. https://doi.org/10.1177/0961203314566636
Cavalcanti, C. A. J., De Azevêdo Silva, J., De Barros Pita, W., Veit, T. D.,
Monticielo, O. A., Xavier, R. M., Brenol, J. C. T., Brenol, C. V., Fragoso, T.
S., Barbosa, A. D., Duarte, Â. L. B. P., Oliveira, R. D. R., Louzada-Júnior,
P., Donadi, E. A., Crovella, S., Chies, J. A. B., & Sandrin-Garcia, P. (2016).
Vitamin D receptor polymorphisms and expression profile in rheumatoid arthritis brazilian patients. Molecular Biology Reports, 43(1), 41–51.
https://doi.org/10.1007/s11033-015-3937-z
Chen, S., Sims, G. P., Chen, X. X., Gu, Y. Y., Chen, S., & Lipsky, P. E. (2007). Modulatory effects of 1,25-dihydroxyvitamin D3 on human B cell differentiation. The Journal of Immunology, 179(3), 1634–1647. https://doi.org/10.
4049/jimmunol.179.3.1634
Correa-Rodríguez, M., Pocovi-Gerardino, G., Callejas-Rubio, J. -L., RíosFernández, R., Martín-Amada, M., Cruz-Caparrós, M. -G., DelOlmoRomero, S., Ortego-Centeno, N., & Rueda-Medina, B. (2021). Vitamin D
levels are associated with disease activity and damage accrual in systemic lupus erythematosus patients. Biological Research for Nursing, 23(3),
455–463. https://doi.org/10.1177/1099800420983596
Di Rosa, M., Malaguarnera, M., Nicoletti, F., & Malaguarnera, L. (2011). Vitamin D3: A helpful immuno-modulator. Immunology, 134(2), 123–139.
https://doi.org/10.1111/j.1365-2567.2011.03482.x
Dzhebir, G., Kamenarska, Z., Hristova, M., Savov, A., Vinkov, A., Kaneva, R.,
Mitev, V., & Dourmishev, L. (2016). Association of vitamin D receptor
gene BsmI B/b and FokI F/f polymorphisms with adult dermatomyositis
and systemic lupus erythematosus. International Journal of Dermatology,
55(8), e465–e468. https://doi.org/10.1111/ijd.13263
Eloi, M., Horvath, D. V., Ortega, J. C., Prado, M. S., Andrade, L. E. C., Szejnfeld,
V. L., & de Moura Castro, C. H. (2017). 25-Hydroxivitamin D serum concentration, not free and bioavailable vitamin D, is associated with disease activity in systemic lupus erythematosus patients. PLoS One, 12(1),
e0170323. https://doi.org/10.1371/journal.pone.0170323
Emerah, A. A., & El-Shal, A. S. (2013). Role of vitamin D receptor gene
polymorphisms and serum 25-hydroxyvitamin D level in Egyptian
female patients with systemic lupus erythematosus. Molecular Biology
Reports, 40(11), 6151–6162. https://doi.org/10.1007/s11033-013-272
6-9
Healy, K. D., Frahm, M. A., & DeLuca, H. F. (2005). 1,25-Dihydroxyvitamin
D3 up-regulates the renal vitamin D receptor through indirect gene activation and receptor stabilization. Archives of Biochemistry and Biophysics,
433(2), 466–473. https://doi.org/10.1016/j.abb.2004.10.001
1744313x, 2022, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12576 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
190
Healy, K. D., Zella, J. B., Prahl, J. M., & DeLuca, H. F. (2003). Regulation of
the murine renal vitamin D receptor by 1,25-dihydroxyvitamin D3 and
calcium. Proceedings of the National Academy of Sciences, 100(17), 9733–
9737. https://doi.org/10.1073/pnas.1633774100
Huang, C. -M., Wu, M. -C., Wu, J. -Y., & Tsai, F. -J. (2002). Association of
vitamin D receptor gene BsmI polymorphisms in Chinese patients with
systemic lupus erythematosus. Lupus, 11(1), 31–34. https://doi.org/10.
1191/0961203302lu143oa
Iruretagoyena, M., Hirigoyen, D., Naves, R., & Burgos, P. I. (2015). Immune
response modulation by Vitamin D: Role in systemic lupus erythematosus. Frontiers in Immunology, 6, 1–7. https://doi.org/10.3389/fimmu.
2015.00513
Jolliffe, D. A., Greiller, C. L., Mein, C. A., Hoti, M., Bakhsoliani, E., Telcian,
A. G., Simpson, A., Barnes, N. C., Curtin, J. A., Custovic, A., Johnston,
S. L., Griffiths, C. J., Walton, R. T., & Martineau, A. R. (2018). Vitamin D receptor genotype influences risk of upper respiratory infection.
British Journal of Nutrition, 120(8), 891–900. https://doi.org/10.1017/
S000711451800209X
Kamen, D. L., Cooper, G. S., Bouali, H., Shaftman, S. R., Hollis, B. W., &
Gilkeson, G. S. (2006). Vitamin D deficiency in systemic lupus erythematosus. Autoimmunity Reviews, 5(2), 114–117. https://doi.org/10.1016/
j.autrev.2005.05.009
Kamen, D. L., & Tangpricha, V. (2010). Vitamin D and molecular actions on
the immune system: Modulation of innate and autoimmunity. Journal
of Molecular Medicine, 88(5), 441–450. https://doi.org/10.1007/s00109010-0590-9
Kim, A., & Chong, B. F. (2013). Photosensitivity in cutaneous lupus erythematosus. Photodermatology, Photoimmunology & Photomedicine, 29(1), 4–
11. https://doi.org/10.1111/phpp.12018
Klein, R., Moghadam-Kia, S., Taylor, L., Coley, C., Okawa, J., LoMonico, J.,
Chren, M. - M., & Werth, V. P. (2011). Quality of life in cutaneous lupus
erythematosus. Journal of the American Academy of Dermatology, 64(5),
849–858. https://doi.org/10.1016/j.jaad.2010.02.008
Liang, Y., Leng, R. - X., Pan, H. - F., & Ye, D. - Q. (2017). The prevalence
and risk factors for serositis in patients with systemic lupus erythematosus: A cross-sectional study. Rheumatology International, 37(2), 305–311.
https://doi.org/10.1007/s00296-016-3630-0
Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression
data using real-time quantitative PCR and. Methods (San Diego, Calif.), 25,
402–408. https://doi.org/10.1006/meth.2001.1262
Luo, X., Wu, L., Yang, M., Liu, N., Liao, T., Tang, Z., Zeng, X. - F., & Yuan,
G. (2011). Relationship of vitamin D receptor gene Fok I polymorphism with systemic lupus erythematosus. Xi Bao Yu Fen Zi Mian Yi Xue
Za Zhi = Chinese Journal of Cellular and Molecular Immunology, 27(8),
901–905. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/218068
92
Luo, X. Y., Wu, L. J., Chen, L., Yang, M. H., Liao, T., Liu, N. T., & Zhao, Y.
(2012). The association of vitamin D receptor gene ApaI and BsmI polymorphism with systemic lupus erythematosus. Zhonghua Nei Ke Za Zhi
[Chinese Journal of Internal Medicine], 51(2), 131–135. https://doi.org/10.
1016/j.atherosclerosis.2015.12.030
Luo, X. -Y., Yang, M. -H., Wu, F. -X., Wu, L. -J., Chen, L., Tang, Z., Liu, N. -T., Zeng,
X. -F., Guan, J. -L., & Yuan, G. -H. (2012). Vitamin D receptor gene BsmI
polymorphism B allele, but not BB genotype, is associated with systemic
lupus erythematosus in a Han Chinese population. Lupus, 21(1), 53–59.
https://doi.org/10.1177/0961203311422709
Hochberg, M. C. (1997). Updating the American College of Rheumatology
revised criteria for the classification of systemic lupus erythematosus.
Arthritis and Rheumatism, 40(9), 1725.
Mok, C., Birmingham, D., Ho, L., Hebert, L., Song, H., & Rovin, B. (2012).
Vitamin D deficiency as marker for disease activity and damage in systemic lupus erythematosus: A comparison with anti-dsDNA and antiC1q. Lupus, 21(1), 36–42. https://doi.org/10.1177/09612033114220
94
191
Mok, C. C., & Lau, C. S. (2003). Pathogenesis of systemic lupus erythematosus. Journal of Clinical Pathology, 56(7), 481–490. https://doi.org/10.
1016/j.jaut.2011.05.004
Monticielo, O. A., Teixeira, T. D. M., Chies, J. A. B., Brenol, J. C. T., & Xavier,
R. M. (2012). Vitamin D and polymorphisms of VDR gene in patients
with systemic lupus erythematosus. Clinical Rheumatology, 25, . https://
doi.org/10.1007/s10067-012-2021-5
Mostowska, A., Lianeri, M., Wudarski, M., Olesińska, M., & Jagodziński, P.
P. (2013). Vitamin D receptor gene BsmI, FokI, ApaI and TaqI polymorphisms and the risk of systemic lupus erythematosus. Molecular Biology Reports, 40(2), 803–810. https://doi.org/10.1007/s11033-012-211
8-6
Ozaki, Y., Nomura, S., Nagahama, M., Yoshimura, C., Kagawa, H., & Fukuhara,
S. (2000). Vitamin-D receptor genotype and renal disorder in japanese
patients with systemic lupus erythematosus. Nephron, 85(1), 86–91.
https://doi.org/10.1159/000045635
Ralston, A., & Rossant, J. (2008). Cdx2 acts downstream of cell polarization to cell-autonomously promote trophectoderm fate in the early
mouse embryo. Developmental Biology, 313(2), 614–629. https://doi.org/
10.1016/j.ydbio.2007.10.054
Salimi, S., Eskandari, F., Rezaei, M., & Sandoughi, M. (2019). Vitamin D receptor rs2228570 and rs731236 polymorphisms are susceptible factors for
systemic lupus erythematosus. Advanced Biomedical Research, 8(1), 48.
https://doi.org/10.4103/abr.abr_19_19
Savory, J. G. A., Bouchard, N., Pierre, V., Rijli, F. M., De Repentigny, Y.,
Kothary, R., & Lohnes, D. (2009). Cdx2 regulation of posterior development through non-Hox targets. Development (Cambridge, England), 136,
4099–4110. https://doi.org/10.1242/dev.041582
Silva, J. D. A., Fernandes, K. M., Pancotto, J. T., Fragoso, T. S., Donadi, E.,
Crovella, S., & Sandrin-Garcia, P. (2013). Vitamin D receptor (VDR) gene
polymorphisms and susceptibility to systemic lupus erythematosus clinical manifestations. Lupus, 21(1), 1110–1117. https://doi.org/10.1177/
0961203313500549
Sociedade Brasileira de Reumatologia. (2020). Lúpus Eritematoso Sistêmico
(LES). Retrieved December 6, 2021, from https://www.reumatologia.org.
br/doencas-reumaticas/lupus-eritematoso-sistemico-les/
Stram, D. O. (2004). Tag SNP selection for association studies. Genetic
Epidemiology, 27(4), 365–374. https://doi.org/10.1002/gepi.200
28
Sumethkul, K., Boonyaratavej, S., Kitumnuaypong, T., Angthararuk, S.,
Cheewasat, P., Manadee, N., & Sumethkul, V. (2013). AB0682 Lupus
nephritis is a significant predictor of vitamin D deficiency in SLE patients.
Annals of the Rheumatic Diseases, 71(Suppl 3), 677.14–677. https://doi.
org/10.1136/annrheumdis-2012-eular.682
Tang, Y., Qin, W., Peng, W., & Tao, Y. (2017). Development and validation of a
prediction score system in lupus nephritis. Medicine, 93(37), e8024.
Tsokos, G. C. (2011). Systemic lupus erythematosus. The New England Journal of Medicine, 365(22), 2110–2121. https://doi.org/10.1056/
NEJMra1100359
Uitterlinden, A. G., Fang, Y., van Meurs, J. B. J., Pols, H. A. P., & van Leeuwen,
J. P. T. M. (2004). Genetics and biology of vitamin D receptor polymorphisms. Gene, 338(2), 143–156. https://doi.org/10.1016/j.gene.2004.05.
014
Veldurthy, V., Wei, R., Oz, L., Dhawan, P., Jeon, Y. H., & Christakos, S. (2016).
Vitamin D, calcium homeostasis and aging. Bone Research, 4, 16041.
https://doi.org/10.1038/boneres.2016.41
Wang, Y., Zhu, J., & DeLuca, H. F. (2012). Where is the vitamin D receptor?
Archives of Biochemistry and Biophysics, 523(1), 123–133. https://doi.org/
10.1016/j.abb.2012.04.001
Wöbke, T. K., Sorg, B. L., & Steinhilber, D. (2014). Vitamin D in inflammatory
diseases. Frontiers in Physiology, 5, 1–20. https://doi.org/10.3389/fphys.
2014.00244
Xiao, X., Wang, Y., Hou, Y., Han, F., Ren, J., & Hu, Z. (2016). Vitamin D deficiency and related risk factors in patients with diabetic nephropathy.
1744313x, 2022, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12576 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
DE AZEVÊDO SILVA ET AL .
Journal of International Medical Research, 44(3), 673–684. https://doi.org/
10.1177/0300060515593765
Yan, S., Zheng, C., Chen, Z., Liu, R., Li, G., Hu, W., Pei, H., & Li, B. (2012).
Expression of endoplasmic reticulum stress-related factors in the retinas of diabetic rats. Experimental Diabetes Research, 2012, 1–11. https://
doi.org/10.1155/2012/743780
Yu, Q., Qiao, Y., Liu, D., Liu, F., Gao, C., Duan, J., Liang, L., Di, X., Yuan,
Y., Gao, Y., Cui, S., Qin, Y., Li, T., Zheng, Z., & Liu, Z. (2019). Vitamin D
protects podocytes from autoantibodies induced injury in lupus nephritis by reducing aberrant autophagy. Arthritis Research & Therapy, 21(1),
19. https://doi.org/10.1186/s13075-018-1803-9
DE AZEVÊDO SILVA ET AL .
How to cite this article: De Azevêdo Silva, J., De Lima, S. C.,
Fragoso, T. S., Cavalcanti, C. A. J., Barbosa, A. D., Borborema, M.
E. D. A., De Lucena, T. M. C., Duarte, A. L. B. P., Crovella, S., &
Sandrin-Garcia, P. (2022). Differential distribution of vitamin D
receptor (VDR) gene variants and its expression in systemic
lupus erythematosus. International Journal of Immunogenetics,
49, 181–192. https://doi.org/10.1111/iji.12576
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192
Received: 22 July 2022
Revised: 29 December 2022
Accepted: 19 January 2023
DOI: 10.1111/iji.12613
ORIGINAL ARTICLE
Vitamin D receptor gene polymorphisms influence on clinical
profile and bone mineral density at different skeletal sites in
postmenopausal osteoporotic women
Jaqueline de Azevêdo Silva1
Werbson Lima Guaraná2,3
Camilla Albertina Dantas de Lima2
Alexandre Domingues Barbosa4
Thiago Sotero Fragoso5
Ângela Luzia Branco Pinto Duarte4
Sergio Crovella6
Paula Sandrin-Garcia1,2
1
Department of Genetics, Federal University
of Pernambuco, Recife, Pernambuco, Brazil
2
Keizo Asami Institute (iLIKA), Federal
University of Pernambuco, Recife,
Pernambuco, Brazil
3
Genetics Postgraduate Program, Federal
University of Pernambuco, Recife,
Pernambuco, Brazil
4
Division of Rheumatology, Clinical Hospital,
Federal University of Pernambuco (UFPE),
Recife, Pernambuco, Brazil
5
Division of Rheumatology, University
Hospital, Federal University of Alagoas (UFAL),
Maceió, Alagoas, Brazil
6
Biological Sciences Program, Department of
Biological and Environmental Sciences, College
of Arts and Sciences, Qatar University, Doha,
Qatar
Correspondence
Werbson Lima Guaraná, Genetics
Postgraduate Program/Federal University of
Pernambuco, Av. Moraes Rego, 1235,
Recife/CEP 50760-901, Brazil.
Email: werbson.guarana@ufpe.br
Funding information
Brazilian research agencies: CNPq; CAPES;
FACEPE
Abstract
Bone remodeling is marked by bone synthesis and absorption balance, and any altered
dynamic in this process leads to osteoporosis (OP). The interaction of hormonal,
environmental and genetic factors regulate bone metabolism. Since vitamin D displays a classic role in bone metabolism regulation, acting through vitamin D receptor
(VDR), the genetic variants within VDR were the first ones associated with bone
density and remodelling. Therefore, we investigated whether three single nucleotide
polymorphisms (SNPs) within VDR were associated with OP differential susceptibility and clinical profile from postmenopausal versus healthy women from Northeast
Brazil. Genetic association study enrolling 146 postmenopausal osteoporotic women
as the patient group and 95 healthy age-matched women as the control group. We
assessed three SNPs within VDR (rs11168268, rs1540339 and rs3890733), considering the clinical profile of all patients. Our results showed an association of
rs11168268 G/G genotype with higher bone mineral density (BMD) mean for the total
hip (A/A = 0.828 ± 0.09; A/G = 0.081 ± 0.13; G/G = 0.876 ± 0.12, p = .039), and the
rs3890733 T/T genotype was associated with increased OP risk in patients below 60
years old (odds ratio [OR] = 5.12, 95% confidence interval [CI ]= 1.13–23.27, p = .012).
The rs1540339 T/T genotype was associated with protection for individuals with low
melanin deposition when compared to the high melanin deposition group (OR = 0.24,
95%CI = 0.06–0.94, p = .029). Additionally, 61% of patients presented deficient vitamin D serum levels. The SNP rs11168268 G/G was associated with a significantly
increased mean total hip BMD in patients OP, highlighting this SNP and its relationship
with BMD.
KEYWORDS
osteoporosis, SNP, VDR, vitamin D
1
INTRODUCTION
The condition results from bone synthesis and reabsorption misbalance, regulated by endocrine, environmental and genetic factors (Brent
Osteoporosis (OP) is an essential skeletal condition characterized by
Richards et al., 2012; Chandra & Rajawat, 2021). The multiple aeti-
low bone mass, reduced bone strength and increased risk of fractures.
ologies of decreased bone mineral density (BMD) and metabolic bone
Int J Immunogenet. 2023;50:75–81.
wileyonlinelibrary.com/journal/iji
© 2023 John Wiley & Sons Ltd.
75
DE AZEVÊDO SILVA ET AL .
diseases development create major confounding factors, leaving the
Menopause was defined according to the World Health Organization
exact aetiology of OP poorly understood (He et al., 2015).
(WHO) criteria as amenorrhea for at least 1 year in women over 45
OP is a current concern in public health worldwide, and its preva-
years old without any other pathological or physiological cause.
lence increases as people live longer. Additionally, it affects both
Since Brazilian populations are ancestrally genetically heteroge-
genders and displays bias towards postmenopausal women. The con-
neous, it is not appropriate to divide them into different groups, such
dition presents a genetic background characterized by the polygenic
as Caucasian or African-derived (Coelho et al., 2015). However, skin
influence and many gene variations associated with low BMD and
melanin deposition is essential to evaluate vitamin D levels and their
possibly facilitating fractures (Conti et al., 2015; Lovšin et al., 2018).
consequences. Therefore, we arbitrarily divided the OP patients into
Different endocrine pathways involved in skeletal ageing with BMD
two main groups: group I—patients with moderate to high melanin
loss process have been described, leading to new possibilities for prog-
deposition (dark to very dark skin) and group II—patients with very low
nosis and effectiveness in disease therapies (Chandra & Rajawat, 2021;
and low melanin deposition (fair and fair light skin tone).
Larsson & Fazzalari, 2014; Y. Zhang et al., 2014).
In the control group, 95 postmenopausal non-osteoporotic age-
Vitamin D is a secosteroid hormone with a major source in the
matched (mean age 57, SD ± 3.96, ranging from 49 to 64) women were
skin, synthesized when 7-dehydrocolesterol reacts with ultraviolet B
enrolled. All individuals from the control group presented no medical
(UVB) light. The active form of vitamin D, known as D3 , acts through its
history of secondary OP on physical examination and laboratory tests.
receptor—vitamin D receptor (VDR)—and has a significant function in
Additionally, no subjects from the study were on hormone replacement
calcium (Ca) absorption and equilibrium, being the natural modulator
therapy. In the absence of a fragility fracture, BMD by dual-energy
of bone homeostasis (Goltzman, 2018; Holick, 2004; Y. Y. Zhang et al.,
x-ray absorptiometry was used to diagnose OP or osteopenia accord-
2003). VDR, located at chromosome 12 (12q12–q14) and displaying
ing to the WHO classification (Kanis & Kanis, 1994). In addition, plain
14 exons, is a member of the nuclear receptor family of transcription
x-rays of the dorsal-lumbar spine (LS) and hip were performed to
factors, regulating essential bone metabolism genes such as osteocal-
diagnose osteoporotic fractures. All information was obtained directly
cin, osteopontin and factor nuclear kappa B (NF-κB) receptor (Haussler
from the patient’s assessment and medical records.
et al., 2010; He et al., 2015). VDR is a highly polymorphic gene with
All the participants provided written informed consent approved
several polymorphisms described and the first gene known to be asso-
by the local Research Ethics Committee (CEP/CCS/UFPE No. 513/11),
ciated with bone density, remodelling and turnover (Conti et al., 2015;
according to the 1964 Helsinki Declaration.
He et al., 2015).
VDR polymorphisms were first associated with OP because vitamin D and its metabolites play a significant role in the Ca absorption
pathway and bone metabolism. However, most of the studied single
nucleotide polymorphisms (SNPs; TaqI, BmsI and ApaI) within VDR are
in non-coding regions or with no known function, except for FokI and
Cdx-2 (Mohammadi et al., 2014; Yang et al., 2020). Nevertheless, they
have been associated with several pathologies from systemic autoimmune disorders, such as systemic lupus erythematosus to cancer, such
as melanoma (Carvalho et al., 2015; Shahbazi et al., 2013; Zeljic et al.,
2014).
For its role in bone metabolism and homeostasis, we evaluated
whether the TagSNPs rs1168268, rs1540339 and rs3890733, covered
by linkage disequilibrium in most VDR genes, were associated with
postmenopausal OP in women. Additionally, we assessed all patients’
vitamin D serum levels, BMD, clinical features and their relation to the
VDR SNPs investigated.
2.2
Measurement of 25-hydroxyvitamin D3
(25(OH)D) serum levels and BMD
25(OH)D were determined by LIAISON Chemiluminescent Immunoassay (CLIA) (DiaSorin, Stillwater, MN, USA). Normal 25(OH)D serum
levels were defined as values ≥ 30 ng/mL, insufficiency as values 20–
30 ng/mL and deficiency as values < 20 ng/mL, according to Yamada
et al. (2001).
Measurement by the Dual Energy X-ray Absorptiometry (Lunar Corporation, Madison, WI, USA) was performed at the LS from L1 to L4
anteroposteriorly and the total hip, including the femoral neck, Ward’s
triangle and trochanter. The results are expressed in g/cm2 and T-score.
We used a local database (reference population aged 20 to 29 years)
to calculate the T-score. The mean (± SD) of normal values for women
was 1.085 g/cm2 (± 0.1) at the LS, 0.913 g/cm2 (± 0.12) at the femoral
neck and 0.316 g/cm2 (± 0.07) at the distal radius. The in vivo precision
error of the equipment employed in the study expressed in percentage
2
2.1
METHODS AND SUBJECTS
Subjects
In this study, 146 osteoporotic women were enrolled based on clinical
coefficient of variation (%CV = SD + mean BMD of repeated measurements) was 0.9% for the LS on the anteroposterior view and 1.2% for
the femoral neck.
2.3
SNPs selection and VDR genotyping
and laboratory diagnosis, all postmenopausal (mean age at diagnosis
59, SD ± 3.91, ranging from 50 to 65 years old). All patients were
Genomic DNA was isolated from 5 mL of whole blood using the
recruited from the Rheumatology Division at Clinical Hospital, Fed-
Wizard genomic DNA purification kit (Promega, Madison, WI,
eral University of Pernambuco (UFPE), Recife, Pernambuco, Brazil.
USA), following the protocol according to the manufacturer’s
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76
guidelines. Polymorphisms were selected using the SNPBrowser
software version 4.0 (Applied Biosystems, Foster City, CA, USA) and
TA B L E 1 Clinical features from all assessed osteoporotic
postmenopausal women.
the HapMap database (http://hapmap.ncbi.nlm.nih.gov/). We selected
Characteristic
three TagSNPs rs11168268, rs1540339 and rs3890733, tagging some
of the most studied polymorphisms, namely, Taq-I, Bsm-I, Apa-I, and
N (%)
Moderate to high skin melanin deposition
84 (57.5)
Low to very low skin melanin deposition
62 (42.5)
Age (range)
59 (50–65)
considering the 10% minimum allele frequency in Caucasian (Nothen
European from Utah-CEU) and African-derived (Yoruba in Ibadan-
Mean of years since menopause (range)
YRI) subpopulation according to National Center for Biotechnology
11 (2–27)
Information. A TagSNP is a representative SNP in a particular genome
Mean of body mass index mean (range)
region, presenting high linkage disequilibrium with other polymor-
Obesity (%)
phisms within or not a gene (Stram, 2004). The list of all tagged SNPs by
Present
87 (59.6)
the ones assessed herein is shown in Supporting Information Data 1.
Absent
59 (40.4)
Smoking (%)
55 (37.7)
Genotyping was performed with commercially available fluorogenic
allele-specific Taqman Probes (Applied Biosystems, Foster City, CA,
Smoking duration, years, mean (range)
USA) using the ABI7500 Real-Time PCR system (Thermo Fisher, Madi-
20 (5–45)
Mean bone mineral density in g/cm2 (range)
son, WI, USA). Allelic discrimination was followed as recommended
by the manufacturer and analysed using the SDS software version 2.3
(Applied Biosystems, Foster City, CA, USA).
2.4
26.24 (18.37–41.65)
Femoral neck
0.739 (0.482–0.987)
Total hip
0.828 (0.518–1.182)
Lumbar spine (LS)
0.768 (0.484–0.923)
Site of osteoporosis (OP)a (%)
Statistical analysis
Femoral neck
26 (17.8)
Allelic and genotypic frequencies and Hardy–Weinberg equilibrium
Total hip
16 (10.96)
were performed using the SNPStats tool (available online: http://
LS
142 (97.26)
Osteoporotic fractures (%)
bioinfo.iconcologia.net/SNPstats). The exact Fisher test was applied
to determine the statistical significance of all comparisons. Haploview
Present
9 (6.2)
Software version 4.2 was used for haplotype associations. ‘SNPassoc’
Absent
137 (93.8)
R software package version 2.12.2, developed for genetic studies, was
Vitamin D serum levels (%)
used for evaluating the association between SNPs and postmenopausal
OP susceptibility and all clinical features (González et al., 2007). The
multivariate analysis logistic regression was performed to investigate
the association between the variables and dependent variables binary:
SNPs and Ca, vitamin D and BMD of total hip and femoral neck in IBM
a
Low serum level of 25-hydroxyvitamin D3
89 (60.95)
Vitamin D insufficiency
21 (14.38)
Vitamin D deficiency
68 (45.58)
Some patients presented OP in more than one site.
SPSS statistic software version 18.0 (IBM Corp, Armonk, NY, USA).
p-values < .05 were considered statistically significant.
all assessed frequencies are shown in Table 2. No association was identified when assessing the patients and control groups overall. However,
3
3.1
RESULTS
Clinical characterization of the OP patients
In total, 146 patients with postmenopausal OP were included in our
analysis. Additionally, all the clinical and laboratory findings and antiOP therapy from the patients’ group are depicted in Table 1, with a
we identified associations by subgroups when stratifying the patient’s
group by clinical features and SNPs presence.
When comparing patients below and above 60 years old, the SNP
rs3890733 T/T genotype was associated with the group of individuals
below 60 years old (odds ratio [OR] = 5.16, 95% confidence interval
[CI] = 1.1–24.1, p = .043 and OR = 5.12, 95%CI = 1.13–23.27, p = .012)
in the codominant and recessive model, respectively (Table 3).
mean level of 25(OH)D of 27.99 ng/mL. Low serum levels of 25(OH)D
were observed in 89/146 (60.95%) and vitamin D deficiency in 68/146
(45.58%). Furthermore, 9/146 (6.2%) presented historical fractures,
3.3
VDR SNPs and clinical features from
postmenopausal osteoporotic patients
whereas 137/146 (93.8%) patients had no fractures (Table 1).
Moreover, no association was found between VDR polymorphisms and
vitamin D levels. Regarding BMD, we observed a statistically significant
3.2
VDR allelic and genotyping frequencies
higher BMD mean of total hip among patients for the SNP rs11168268
G/G genotype when compared with A/G genotype (A/A = 0.828 ± 0.09;
VDR allelic and genotypic frequencies from the selected SNPs were in
A/G = 0.081 ± 0.13; G/G = 0.876 ± 0.12, p = .039; Supporting
Hardy–Weinberg equilibrium in OP patients and healthy controls, and
Information Data 2).
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77
DE AZEVÊDO SILVA ET AL .
DE AZEVÊDO SILVA ET AL .
TA B L E 2
Allelic and genotypic distribution from all TagSNPs assessed within vitamin D receptor OP patients and controls.
Polymorphism
Patients N (%)
Controls N (%)
OR (95% CI)
p-value
.33
rs11168268
Allele
140
92
A
159 (57%)
113 (61%)
G
121 (43%)
71 (39%)
1.21 (0.81–1.80)
A/A
48 (34.28%)
35 (38.04%)
1.00
A/G
63 (45%)
43 (46.74%)
1.07 (0.57–1.99)
.88
G/G
29 (20.72%)
14 (15.22%)
1.52 (0.65–3.56)
.33
.83
Genotype
rs1540339
Allele
142
84
C
204 (72%)
119 (71%)
T
80 (28%)
49 (29%)
0.95 (0.61–1.48)
73 (51.41%)
41 (48.81%)
1.00
C/T
58 (40.85%)
37 (44.05%)
0.88 (0.48–1.60)
.66
T/T
11 (7.74%)
6 (7.14%)
1.03 (0.32–3.65)
1.00
.75
Genotype
C/C
rs3890733
Allele
141
88
C
197 (70%)
126 (72)
T
85 (30%)
50 (28%)
1.08 (0.70–1.68)
74 (52.48%)
47 (53.41%)
1.00
C/T
49 (34.75%)
32 (36.36%)
0.97 (0.52–1.80)
1.00
T/T
18 (12.77%)
9 (10.23%)
1.27 (0.49–3.48)
.66
Genotype
C/C
Abbreviations: CI, 95% confidence interval; OR, odds ratio; p-value.
TA B L E 3
Patient stratification analysis according to age: Above and below 60 years old and genotype distribution.
>60 years
<60 years
N = 50 (%)
N = 91(%)
OR, CI and p-value
C/C
29 (58%)
45 (49.5%)
OR = 1
C/T
19 (38%)
30 (33%)
OR = 1.02,CI = 0.49–2.13
T/T
02 (4%)
16 (17.5%)
OR = 5.16,CI = 1.1–24.10, p = .043a
C/C + C/T
48(96%)
75(82.4%)
OR = 1
T/T
02(4%)
16(17.6%)
OR = 5.12,CI = 1.13–23.27, p = .012a
rs3890733
Codominant
Recessive
Abbreviations: CI, 95% confidence interval; OR, odds ratio; p-value.
a
Statistically significant p-value.
We also evaluated haplotype combinations in our data, but no asso-
in both codominant and recessive models (OR = 0.2, 95%CI = 0.05–
ciation either to OP susceptibility or gene–gene interactions (epistasis)
0.8, p = .043 and OR = 0.24, 95%CI = 0.06–0.94, p = .029; Supporting
was detected in this study (Supporting Information Data 3). However,
Information Data 4).
when considering the VDR SNPs and skin deposition melanin in the
Multivariate analysis of genotypes with clinical features such as Ca,
patients’ group, SNP rs1540339 T/T genotype was associated with low
vitamin D and BMD of total hip and femoral neck has not presented
susceptibility for individuals from group II (fair and fair light skin tone)
statistically significant results (data not shown).
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78
4
DISCUSSION
and has no precise function, has previously been associated by our
research group with Type I Diabetes (De Azevêdo Silva et al., 2013)
This study assessed the TagSNPs rs3890733, rs11168268 and
and tags three other SNPs rs2239181, rs2239179 and rs886441. At
rs1540339 within VDR and their role in OP susceptibility and its traits.
the same time, the rs2239179 has been associated with lower suscep-
VDR polymorphisms have been associated with both OP susceptibility
tibility to melanoma in a Caucasian-derived population (Ogbah et al.,
and BMD in several populations (Horst-Sikorska et al., 2013; Moham-
2013). Melanoma is a type of cancer strongly influenced by sun expo-
madi et al., 2014; Pouresmaeili et al., 2013; Singh et al., 2013; Wang
sure, and melanin is known to act as a biological protector against UV
et al., 2021).
light damage to DNA (Böhm et al., 2005). Therefore, Caucasian-derived
Age-related bone loss is usually asymptomatic, with different
individuals with less melanin than African-derived with moderate to
genetic and environmental influences on BMD in several sites through-
high melanin may display advantages in vitamin D production but with
out the skeleton (Pouresmaeili et al., 2013). However, we identified
increased UV light exposure consequences (Lupsa & Insogna, 2015).
TagSNP rs3890733 T/T genotype association with an increased risk
In this study, we observed that 61% of all patients presented low
of presenting OP at a younger age (< 60 years old) in both codomi-
vitamin D levels, which agrees with most studies showing that low
nant and dominant analysis, which could relate to a more intense loss
vitamin D status is a risk factor for BMD loss in postmenopausal
in bone turnover over the years due to the fact that in the first 10 years
women (Chang & Lee, 2019; van der Wielen et al., 1995). Estrogen
after menopause, women show a marked loss of bone mass (Finkelstein
has an essential role in increasing the activity of the enzyme respon-
et al., 2008). Estrogen is one of the main elements in physiological bone
sible for activating vitamin D; therefore, declining estrogen levels
remodelling. Its deficiency after menopause causes increased produc-
during menopause could lead to vitamin D deficiency (LeBlanc et al.,
tion of cytokines such as interleukin-1 (IL-1), IL-6 and tumor necrosis
2014). Furthermore, even though 25-hydroxyvitamin D serum level of
factor (TNF), which increase the half-life of the osteoclast and the dif-
20 ng/mL seems to be enough for homeostasis of bone metabolism, it is
ferentiation of pre-osteoclastic cells in mature osteoclasts. The lack of
considered low for the non-classical roles of vitamin D, leading to other
the hormone also decreases the number of osteoblasts and osteocytes,
pathologies (Lupsa & Insogna, 2015).
which impairs the detection of microdamage and immediate repair of
bone mass (Pacifici, 1996; Rahnama et al., 2013).
Low vitamin D levels are known to contribute to reducing BMD,
increasing the risk of fractures and falls in the elderly. However, in
The SNP rs1168268 G/G was associated with increased BMD in
this study, the absence of fractures was more prevalent (93.8%) than
this study. Noteworthy, this particular SNP tags the extensively studied
its presence. In addition, the patient recruitment was carefully carried
SNP BsmI (rs1544410). The BsmI is an intronic variant with unknown
out to age-matched healthy controls. Therefore, it is probable that the
protein consequence; however, it is in strong linkage disequilibrium
younger the OP patient, the lower the risk of falling with subsequent
with the polyA variable number of tandem repeats in the 3′ untrans-
fractures. Nevertheless, low vitamin D levels were still inversely asso-
lated region (3’UTR) (Ingles et al., 1997). Therefore, it may influence
ciated with increased parathyroid hormone, alkaline phosphatase and
VDR transcript (Uitterlinden et al., 2004), which in turn enhances
osteocalcin levels in postmenopausal women leading to accelerated
vitamin D proper function and leads to increased BMD. So, the G/G
bone mass loss and low BMD (Capatina et al., 2014; Lips et al., 2001).
genotype could be an attenuating factor for patients with hip OP.
In summary, our data show that VDR variants are associated with
Therefore, this TagSNP could improve the BMD in these patients. Fur-
higher BMD and increased susceptibility to OP in patients under 60
thermore, it covers three well-recognized SNPs (Apa-I, Bsm-I and Taq-I)
years old. Although this study has a limited number of samples and a
that may potentially influence the stability of RNAm at the VDR gene
‘p-value’ close to borderline statistical significance, it is the first study
(Chen et al., 2020). Some studies observed an association between
that evaluated SNPs in linkage disequilibrium in a Brazilian population,
the presence of these restriction sites (Apa-I, Bsm-I and Taq-I) with
which emphasizes the role of VDR in the clinical features of the disease
increased BMD, higher peak bone mass and even a decrease of bone
in this population.
loss in Iranian, Turkish, Chinese and Dutch populations (Creatsa et al.,
2011; Jakubowska-Pietkiewicz et al., 2012; Li et al., 2012; Özaydin
ACKNOWLEDGEMENTS
et al., 2010; Pouresmaeili et al., 2013; Qin et al., 2004). However, the
This work was funded by the following Brazilian research agencies:
finding of this study is unusual in the Brazilian population.
CNPq (Conselho Nacional de Pesquisa), CAPES (Coordenação de Aper-
The TagSNP rs1540339 T/T genotype was associated with lower
susceptibility to OP in group II (very low to low melanin skin deposi-
feiçoamento de Pessoal de Nível Superior) and FACEPE (Fundação de
Amparo à Ciência e Tecnologia do Estado de Pernambuco).
tion), compared to group I (moderate to high melanin skin deposition).
Our data disagree with those of Horst-Sikorska, which show that
CONFLICT OF INTEREST STATEMENT
decreased susceptibility to OP and its fractures are substantially lower
The authors declare no conflict of interest.
in African-derived subjects—which usually present moderately high
melanin when compared to Caucasian and Asian-derived origin, with
ORCID
very low to low melanin skin deposition (Horst-Sikorska et al., 2013).
Werbson Lima Guaraná
This particular TagSNP rs1540339, located in the intron 4 within VDR
Paula Sandrin-Garcia
https://orcid.org/0000-0003-1806-5219
https://orcid.org/0000-0003-4641-7429
1744313x, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12613 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
79
DE AZEVÊDO SILVA ET AL .
REFERENCES
Böhm, M., Wolff, I., Scholzen, T. E., Robinson, S. J., Healy, E., Luger, T. A.,
Schwarz, T., & Schwarz, A. (2005). α-melanocyte-stimulating hormone
protects from ultraviolet radiation-induced apoptosis and DNA damage. Journal of Biological Chemistry, 280(7), 5795–5802. https://doi.org/
10.1074/jbc.M406334200
Brent Richards, J., Zheng, H. F., & Spector, T. D. (2012). Genetics of
osteoporosis from genome-wide association studies: Advances and
challenges. Nature Reviews Genetics, 13(8), 576–588. https://doi.org/10.
1038/nrg3228
Capatina, C., Carsote, M., Caragheorgheopol, A., Poiana, C., & Berteanu, M.
(2014). Vitamin D deficiency in postmenopausal women–biological correlates. Maedica, 9(4), 316–322. http://www.ncbi.nlm.nih.gov/pubmed/
25705298%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?
artid=PMC4316873
Carvalho, C., Marinho, A., Leal, B., Bettencourt, A., Boleixa, D., Almeida, I.,
Farinha, F., Costa, P. P., Vasconcelos, C., & Silva, B. M. (2015). Association
between vitamin D receptor (VDR) gene polymorphisms and systemic
lupus erythematosus in Portuguese patients. Lupus, 24(8), 846–853.
https://doi.org/10.1177/0961203314566636
Chandra, A., & Rajawat, J. (2021). Skeletal aging and osteoporosis: Mechanisms and therapeutics. International Journal of Molecular Sciences, 22(7),
3553. https://doi.org/10.3390/ijms22073553
Chang, S. W., & Lee, H. C. (2019). Vitamin D and health—The missing vitamin in humans. Pediatrics and Neonatology, 60(3), 237–244. https://doi.
org/10.1016/j.pedneo.2019.04.007
Chen, G., Hu, C., Song, Y., Xiu, M., Liang, W., Ou, N., Liu, X., & Huang, P.
(2020). Relationship between the Apal (rs7975232), Bsml (rs1544410),
Fokl (rs2228570), and Taql (rs731236) variants in the vitamin D receptor gene and urolithiasis susceptibility: An updated meta-analysis and
trial sequential analysis. Frontiers in Genetics, 11, 234. https://doi.org/10.
3389/fgene.2020.00234
Coelho, A., Moura, R. R., Cavalcanti, C., Guimarães, R. L., Sandrin-Garcia,
P., Crovella, S., & Brandão, L. A. C. (2015). A rapid screening of ancestry
for genetic association studies in an admixed population from Pernambuco, Brazil. Genetics and Molecular Research, 14(1), 2876–2884. https://
doi.org/10.4238/2015.March.31.18
Conti, V., Russomanno, G., Corbi, G., Toro, G., Simeon, V., Filippelli, W.,
Ferrara, N., Grimaldi, M., D’Argenio, V., Maffulli, N., & Filippelli, A.
(2015). A polymorphism at the translation start site of the vitamin
D receptor gene is associated with the response to anti-osteoporotic
therapy in postmenopausal women from Southern Italy. International
Journal of Molecular Sciences, 16(3), 5452–5466. https://doi.org/10.3390/
ijms16035452
Creatsa, M., Pliatsika, P., Kaparos, G., Antoniou, A., Armeni, E., Tsakonas,
E., Panoulis, C., Alexandrou, A., Dimitraki, E., Christodoulakos, G., &
Lambrinoudaki, I. (2011). The effect of vitamin D receptor Bsml genotype
on the response to osteoporosis treatment in postmenopausal women:
a pilot study. The Journal of Obstetrics and Gynaecology Research, 37(10),
1415–1422. https://doi.org/10.1111/j.1447-0756.2011.01557.x
De Azevêdo Silva, J., Guimarães, R. L., Brandão, L. A. C., Araujo, J., Segat, L.,
Crovella, S., & Sandrin-Garcia, P. (2013). Vitamin D receptor (VDR) gene
polymorphisms and age onset in type 1 diabetes mellitus. Autoimmunity,
46(6), 382–387. https://doi.org/10.3109/08916934.2013.795952
Finkelstein, J. S., Brockwell, S. E., Mehta, V., Greendale, G. A., Sowers, M. R.,
Ettinger, B., Lo, J. C., Johnston, J. M., Cauley, J. A., Danielson, M. E., & Neer,
R. M. (2008). Bone mineral density changes during the menopause transition in a multiethnic cohort of women. Journal of Clinical Endocrinology
and Metabolism, 93(3), 861–868. https://doi.org/10.1210/jc.2007-1876
Goltzman, D. (2018). Functions of vitamin D in bone. Histochemistry and Cell
Biology, 149(4), 305–312. https://doi.org/10.1007/s00418-018-1648-y
González, J. R., Armengol, L., Solé, X., Guinó, E., Mercader, J. M., Estivill,
X., & Moreno, V. (2007). SNPassoc: An R package to perform whole
genome association studies. Bioinformatics, 23(5), 654–55. https://doi.
org/10.1093/bioinformatics/btm025
DE AZEVÊDO SILVA ET AL .
Haussler, M. R., Haussler, C. A., Whitfield, G. K., Hsieh, J. C., Thompson, P.
D., Barthel, T. K., Bartik, L., Egan, J. B., Wu, Y., Kubicek, J. L., Lowmiller, C.
L., Moffet, E. W., Forster, R. E., & Jurutka, P. W. (2010). The nuclear vitamin D receptor controls the expression of genes encoding factors which
feed the “Fountain of Youth” to mediate healthful aging. Journal of Steroid
Biochemistry and Molecular Biology, 121(1–2), 88–97. https://doi.org/10.
1016/j.jsbmb.2010.03.019
He, W., Liu, M., Huang, X., Qing, Z., & Gao, W. (2015). The influence of vitamin
D receptor genetic variants on bone mineral density and osteoporosis in
chinese postmenopausal women. Disease Markers, 2015, 1–7. https://doi.
org/10.1155/2015/760313
Holick, M. F. (2004). Sunlight and vitamin D for bone health and prevention
of autoimmune diseases, cancers, and cardiovascular disease. The American Journal of Clinical Nutrition, 1678S–88S, 80(6), 1678S–88S. https://
doi.org/10.1093/ajcn/80.6.1678S
Horst-Sikorska, W., Dytfeld, J., Wawrzyniak, A., Marcinkowska, M.,
Michalak, M., Franek, E., Napiórkowska, L., Drwęska, N., & Słomski, R.
(2013). Vitamin D receptor gene polymorphisms, bone mineral density
and fractures in postmenopausal women with osteoporosis. Molecular
Biology Reports, 40(1), 383–390. https://doi.org/10.1007/s11033-0122072-3
Ingles, S. A., Haile, R. W., Henderson, B. E., Kolonel, L. N., Nakaichi, G.,
Shi, C. Y., Yu, M. C., Ross, R. K., & Coetzee, G. A. (1997). Strength of
linkage disequilibrium between two vitamin D receptor markers in five
ethnic groups: Implications for association studies. Cancer Epidemiology
Biomarkers and Prevention, 6(2), 93–98.
Jakubowska-Pietkiewicz, E., Młynarski, W., Klich, I., Fendler, W., & ChlebnaSokół, D. (2012). Vitamin D receptor gene variability as a factor influencing bone mineral density in pediatric patients. Molecular Biology Reports,
39(5), 6243–6250. https://doi.org/10.1007/s11033-012-1444-z
Kanis, J. A., & Kanis, J. A. (1994). Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: Synopsis of a
WHO report. Osteoporosis International, 4(6), 368–381. https://doi.org/
10.1007/BF01622200
Larsson, S., & Fazzalari, N. L. (2014). Anti-osteoporosis therapy and fracture
healing. Archives of Orthopaedic and Trauma Surgery, 134(2), 291–297.
https://doi.org/10.1007/s00402-012-1558-8
LeBlanc, E. S., Desai, M., Perrin, N., Wactawski-Wende, J., Manson, J. A. E.,
Cauley, J. A., Michael, Y. L., Tang, J., Womack, C., Song, Y., Johnson, K.
C., O’Sullivan, M. J., Woods, N., & Stefanick, M. L. (2014). Vitamin D levels and menopause-related symptoms. Menopause, 21(11), 1197–1203.
https://doi.org/10.1097/GME.0000000000000238
Li, Y., Xi, B., Li, K., & Wang, C. (2012). Association between vitamin D receptor gene polymorphisms and bone mineral density in Chinese women.
Molecular Biology Reports, 39(5), 5709–5717. https://doi.org/10.1007/
s11033-011-1380-3
Lips, P., Duong, T., Oleksik, A., Black, D., Cummings, S., Cox, D., & Nickelsen,
T. (2001). A global study of vitamin D status and parathyroid function
in postmenopausal women with osteoporosis: Baseline data from the
multiple outcomes of Raloxifene Evaluation clinical trial. Journal of Clinical Endocrinology and Metabolism, 86(3), 1212–1221. https://doi.org/10.
1210/jcem.86.3.7327
Lovšin, N., Zupan, J., & Marc, J. (2018). Genetic effects on bone health.
Current Opinion in Clinical Nutrition and Metabolic Care, 21(4), 233–239.
https://doi.org/10.1097/MCO.0000000000000482
Lupsa, B. C., & Insogna, K. (2015). Bone health and osteoporosis. Endocrinology and Metabolism Clinics of North America, 44(3), 517–530. https://doi.
org/10.1016/j.ecl.2015.05.002
Mohammadi, Z., Fayyazbakhsh, F., Ebrahimi, M., Amoli, M. M., Khashayar,
P., Dini, M., Zadeh, R. N., Keshtkar, A., & Barikani, H. R. (2014). Association between vitamin D receptor gene polymorphisms (Fok1 and Bsm1)
and osteoporosis: A systematic review. Journal of Diabetes and Metabolic
Disorders, 13(1), 98. https://doi.org/10.1186/s40200-014-0098-x
Ogbah, Z., Visa, L., Badenas, C., Ríos, J., Puig-Butille, J. A., Bonifaci, N., Guino,
E., Augé, J. M., Kolm, I., Carrera, C., Pujana, M. Á., Malvehy, J., & Puig, S.
1744313x, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/iji.12613 by UFAL - Universidade Federal de Alagoas, Wiley Online Library on [20/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
80
(2013). Serum 25-hydroxyvitamin D3 levels and vitamin D receptor variants in melanoma patients from the Mediterranean area of Barcelona.
BMC Medical Genetics, 14(1), Article 26. https://doi.org/10.1186/14712350-14-26
Özaydin, E., Dayangac-Erden, D., Erdem-Yurter, H., Derman, O., & Coşkun,
T. (2010). The relationship between vitamin D receptor gene polymorphisms and bone density, osteocalcin level and growth in adolescents.
Journal of Pediatric Endocrinology and Metabolism, 23(5), 491–496. https://
doi.org/10.1515/jpem.2010.080
Pacifici, R. (1996). Estrogen, cytokines, and pathogenesis of postmenopausal osteoporosis. Journal of Bone and Mineral Research, 11(8),
1043–1051. https://doi.org/10.1002/jbmr.5650110802
Pouresmaeili, F., Jamshidi, J., Azargashb, E., & Samangouee, S. (2013). Association between vitamin D receptor gene BsmI polymorphism and bone
mineral density in a population of 146 Iranian women. Cell Journal, 15(1),
75–82.
Qin, Y. J., Zhang, Z. L., Huang, Q. R., He, J. W., Hu, Y. Q., Zhou, Q., Lu, J. H.,
Li, M., & Liu, Y. J. (2004). Association of vitamin D receptor and estrogen receptor-α gene polymorphism with peak bone mass and bone size
in Chinese women. Acta Pharmacologica Sinica, 25(4), 462–468. http://
www.chinaphar.com/article/view/8070
Rahnama, M., Jastrzebska, I., Jamrogiewicz, R., & Kocki, J. (2013). IL-1α
and IL-1β levels in blood serum and saliva of menopausal women.
Endocrine Research, 38(2), 69–76. https://doi.org/10.3109/07435800.
2012.713425
Shahbazi, S., Alavi, S., Majidzadeh-A, K., Ghaffarpour, M., Soleimani, A., &
Mahdian, R. (2013). BsmI but not FokI polymorphism of VDR gene is contributed in breast cancer. Medical Oncology, 30(1), Article 393. https://
doi.org/10.1007/s12032-012-0393-7
Singh, M., Singh, P., Singh, S., Juneja, P. K., & Kaur, T. (2013). Vitamin D
receptor (VDR) gene polymorphism influences the risk of osteoporosis
in postmenopausal women of Northwest India. Archives of Osteoporosis,
8(1–2), 1–8. https://doi.org/10.1007/s11657-013-0147-y
Stram, D. O. (2004). Tag SNP selection for association studies. Genetic
Epidemiology, 27(4), 365–374. https://doi.org/10.1002/gepi.20028
Uitterlinden, A. G., Fang, Y., Van Meurs, J. B. J., Pols, H. A. P., & Van Leeuwen,
J. P. T. M. (2004). Genetics and biology of vitamin D receptor polymorphisms. Gene, 338(2), 143–156. https://doi.org/10.1016/j.gene.2004.05.
014
van der Wielen, R. P. J., de Groot, L. C. P. G. M., van Staveren, W. A.,
Löwik, M. R. H., van den Berg, H., Haller, J., & Moreiras, O. (1995).
Serum vitamin D concentrations among elderly people in Europe. The
Lancet, 346(8969), 207–210. https://doi.org/10.1016/S0140-6736(95)
91266-5
Wang, S., Ai, Z., Song, M., Yan, P., & Li, J. (2021). The association between
vitamin D receptor FokI gene polymorphism and osteoporosis in postmenopausal women: A meta-analysis. Climacteric, 24(1), 74–79. https://
doi.org/10.1080/13697137.2020.1775806
Yamada, S., Yamamoto, K., Masuno, H., & Choi, M. (2001). Threedimensional structure-function relationship of vitamin D and vitamin
D receptor model. Steroids, 66(3–5), 177–187. https://doi.org/10.1016/
S0039-128X(00)00145-8
Yang, T. L., Shen, H., Liu, A., Dong, S. S., Zhang, L., Deng, F. Y., Zhao, Q., &
Deng, H. W. (2020). A road map for understanding molecular and genetic
determinants of osteoporosis. Nature Reviews. Endocrinology, 16(2), 91.
https://doi.org/10.1038/s41574-019-0282-7
Zeljic, K., Kandolf-Sekulovic, L., Supic, G., Pejovic, J., Novakovic, M.,
Mijuskovic, Z., & Magic, Z. (2014). Melanoma risk is associated with
vitamin D receptor gene polymorphisms. Melanoma Research, 24(3),
273–279. https://doi.org/10.1097/CMR.0000000000000065
Zhang, Y., Bradley, A. D., Wang, D., & Reinhardt, R. A. (2014). Statins, bone
metabolism and treatment of bone catabolic diseases. Pharmacological
Research, 88, 53–61. https://doi.org/10.1016/j.phrs.2013.12.009
Zhang, Y. Y., Long, J. R., Liu, P. Y., Liu, Y. J., Shen, H., Zhao, L. J., & Deng,
H. W. (2003). Estrogen receptor α and vitamin D receptor gene polymorphisms and bone mineral density: Association study of healthy
pre- and postmenopausal Chinese women. Biochemical and Biophysical Research Communications, 308(4), 777–783. https://doi.org/10.1016/
S0006-291X(03)01479-7
SUPPORTING INFORMATION
Additional supporting information can be found online in the Supporting Information section at the end of this article.
How to cite this article: de Azevêdo Silva, J., de Lima, C. A. D.,
Guaraná, W. L., Barbosa, A. D., Fragoso, T. S., Duarte, Â. L. B. P.,
Crovella, S., & Sandrin-Garcia, P. (2023). Vitamin D receptor
gene polymorphisms influence on clinical profile and bone
mineral density at different skeletal sites in postmenopausal
osteoporotic women. International Journal of Immunogenetics,
50, 75–81. https://doi.org/10.1111/iji.12613
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81
DE AZEVÊDO SILVA ET AL .
Inflammation Research (2018) 67:255–264
https://doi.org/10.1007/s00011-017-1119-2
Inflammation Research
ORIGINAL RESEARCH PAPER
Polymorphisms and expression of inflammasome genes are associated
with the development and severity of rheumatoid arthritis in Brazilian
patients
Catarina Addobbati1,2 · Heidi Lacerda Alves da Cruz2 · José Eduardo Adelino1,2 ·
Amanda Luíze Melo Tavares Ramos2 · Thiago Sotero Fragoso3 · Alexandre Domingues4 ·
Ângela Luiza Branco Pinto Duarte4 · Renê Donizeti Ribeiro Oliveira5 · Paulo Louzada‑Júnior5 ·
Eduardo Antônio Donadi5 · Alessandra Pontillo6 · Jaqueline de Azevêdo Silva1,2 · Sergio Crovella1,2 ·
Paula Sandrin‑Garcia1,2
Received: 1 July 2017 / Revised: 22 October 2017 / Accepted: 21 November 2017 / Published online: 11 December 2017
© Springer International Publishing AG, part of Springer Nature 2017
Abstract
Objective In the present study, we analyzed the possible association of inflammasome gene variants and expression to
rheumatoid arthritis (RA)’s development and severity in the Brazilian population.
Materials and methods Thirteen single nucleotide polymorphisms within six inflammasome genes (NLRP1, NLRP3, NLRC4,
AIM2, CARD8, CASP1) as well as IL1B and IL18 genes in two different Brazilian populations (from Northeast and Southeast
Brazil) were analyzed. We also evaluated inflammasome gene expression profile in resting and LPS + ATP-treated monocytes from RA patients and healthy individuals. For genetic association study, 218 patients and 307 healthy controls were
genotyped. For gene expression study, inflammasome genes mRNA levels of 12 patients and ten healthy individuals were
assessed by qPCR.
Results Our results showed that rs10754558 NLRP3 and rs2043211 CARD8 polymorphisms are associated with RA development (p value = 0.044, OR = 1.77, statistical power = 0.999) and severity measured by Health Assessment Questionnaire
(HAQ) (p value = 0.03), respectively. Gene expression analyses showed that RA patients display activation of CASP1, IL1B
and IL1R genes independently of LPS + ATP activation. In LPS + ATP-treated monocytes, NLRP3 and NLRC4 expressions
were also significantly higher in patients compared with controls.
Conclusions The first reported results in Brazilian populations support the role of inflammasome in the development of RA.
Keywords SNPs · Autoimmunity · Prognostic and monocytes
Responsible Editor: Jason J. McDougall.
Electronic supplementary material The online version of this
article (https://doi.org/10.1007/s00011-017-1119-2) contains
supplementary material, which is available to authorized users.
* Catarina Addobbati
catarinaaddobbati@hotmail.com
1
Department of Genetics, Federal University
of Pernambuco, Av. Moraes Rego, 1235, Recife,
Pernambuco CEP 50760‑901, Brazil
2
Laboratory of Immunopathology Keizo Asami (LIKA),
Federal University of Pernambuco, Recife, Pernambuco,
Brazil
3
Rheumatology Service, Clinical Hospital, Federal University
of Alagoas, Maceió, Alagoas, Brazil
4
Rheumatology Division, Clinical Hospital, Federal
University of Pernambuco, Recife, Pernambuco, Brazil
5
Clinical Immunology Division, Department of Medicine,
Medicine Faculty of Ribeirão Preto, University of São Paulo,
Ribeirão Preto, São Paulo, Brazil
6
Laboratory of Immunognetics, Department of Immunology,
Institute of Biomedical Sciences, University of São Paulo,
São Paulo, São Paulo, Brazil
13
Vol.:(0123456789)
256
Introduction
Rheumatoid arthritis (RA) is a complex and chronic
inflammatory disease associated with progressive joint
destruction, disabling and systemic complications. It is
characterized by proliferation of synovial tissue, autoantibody production and systemic alterations such as cardiovascular, pulmonary and dermatological [1, 2]. RA is
a disorder with an important sex bias, substantially more
affecting women from 30 to 50 years old [2, 3]. Even
though RA etiology remains unclear, it depends upon the
interaction between genetic and environmental factors.
The genetic component has a pivotal role in RA etiology
with several genes contributing in disease´s triggering [2,
4]. The majority of genetic variations associated with RA
development are within immune response-related genes,
with the human leukocyte antigen (HLA) variants being
the most well-known genetic risk factors [4].
The pathogenesis of RA encompasses abnormal innate
and adaptive immune responses, being tumor necrosis
factor and interleukin (IL)-6 the main pro-inflammatory
cytokines involved in RA pathogenesis [5, 6]. High levels
of IL-1β, secreted by monocytes, macrophages and dendritic cells, have also been involved in RA, revealing an
important role in bone resorption and cartilage destruction [7]. Indeed, the therapeutic inhibition of IL-1 reduces
signs and symptoms of RA as well as radiological damage.
Animal models of RA, such as collagen-induced arthritis
and antigen-induced arthritis, also respond to IL-1 inhibition [8, 9], underlining the importance of this cytokine in
disease’s development.
IL-1β secretion is induced by the activation of inflammasomes, which are multiprotein complexes capable
of promoting the processing and maturation of IL-1β.
Assembly of inflammasomes depends upon the activation
of intracellular receptors belonging to Nod-like receptors
and PHIN receptors families, such as NLR family pyrin
domain-containing 1 (NLRP1), NLR family pyrin domaincontaining 3 (NLRP3), NLR family CARD domain-containing protein 4 (NLRC4) and absent in melanoma 2
(AIM2), the adaptor molecule apoptosis-associated specklike protein containing a CARD (ASC) and the effector
protein caspase-1. When sensing pathogen-associated
molecular pattern (PAMP) or danger-associated molecular pattern (DAMP), the intracellular receptors recruit the
adaptor protein ASC, which triggers the cleavage of procaspase-1 into caspase-1. Activated caspase-1 processes
pro-IL-1β and pro-IL-18 cytokines into their mature and
secreted form. Inflammasome activation is strictly regulated by transcriptional mechanisms (i.e., NF-kB-dependent transcription of NLRP3, AIM2, IL1B), post-transductional modifications (i.e., ubiquitination, nitrosylation), as
13
C. Addobbati et al.
well as by endogenous proteins, such as caspase recruitment domain-containing protein 8 (CARD8), which specifically inhibit NLRP3-inflammasome activation. Pro-IL-1β
production is dependent on NF-kB role, being the cytokine
secretion a two-stage process [10–12].
Mutations in inflammasome genes may cause rare autoinflammatory disorders characterized by constitutively
elevated level of IL-1β contributing to the systemic inflammatory presentation [13]. Polymorphisms in inflammasome
genes have been associated to more common chronic inflammatory disorders, such as systemic lupus erythematosus
[14], psoriasis [15], Crohn´s disease [16, 17], celiac disease
[18, 19], type 1 diabetes [18, 20] and vitiligo [21]. Previous studies reported the association between NLRP3 and/or
CARD8 and RA in different populations [22–27], and despite
their heterogeneity, the results pointed out a major role of
NLRP3-inflammasome dysregulation in RA pathogenesis.
Herein, we first performed in Brazilian populations a
genetic association study to assess inflammasome and also
IL1B and IL18 gene polymorphisms and the susceptibility to
RA and its clinical manifestations. Moreover, we analyzed
inflammasome components genes as well as IL1B and IL1R
expression profile in peripheral blood-derived monocytes
from RA subjects with and without inflammasome activation in vitro.
Methods
Genotyping study
Subjects
For this study, a total of 218 RA patients and 307 healthy
individuals, all from Brazil, were enrolled. The Northeastern
sample comprised 128 patients (mean age 51.3 ± 11.7 years;
mean age at diagnosis 42.1 ± 11.7 years; 122 females and 6
males) and 149 healthy individuals (mean age 39.2 ± 14.2
years; 122 females and 27 males) from the state of Pernambuco, Northeastern Brazil. The Southeast sample comprised
90 patients (mean age 55.7 ± 10.8 years; mean age at diagnosis 44.8 ± 13.2 years; 83 females and 7 males) and 158
healthy controls (mean age 37.4 ± 11.3 years; 76 females
and 82 males) from state of São Paulo, Southeast Brazil.
Patients from Northeastern Brazil were under care of the
Division of Rheumatology of Hospital das Clínicas from
Federal University of Pernambuco, whereas patients from
Southeast Brazil were recruited from Division of Clinical
Immunology of University Hospital of the School of Medicine of Ribeirão Preto, University of São Paulo. All RA
patients were diagnosed according to the American College
of Rheumatology (ACR) criteria [28]; control individuals
were healthy blood donors without previous family history
Polymorphisms and expression of inflammasome genes are associated with the development and…
of autoimmune diseases, as reported in appropriate questionnaire. The patients were evaluated for the presence of rheumatoid factor and bone erosions. Disease activity score in 28
joints (DAS28) [29, 30] and Health Assessment Questionnaire (HAQ) [31] were applied to patients as a measurement
of disease activity and functional disability, respectively.
Aiming to maintain a good statistical power, and also
to report the results as from the Brazilian population as a
whole, we joined the two groups into one, and then correct
the analysis by geographical origin and demographic data.
The demographic and clinical features from all assessed RA
patients and controls are shown in Supplementary data 1.
All procedures involving human participants were in
accordance with the 1964 Helsinki declaration and its later
amendments or comparable ethical standards. All the participants provided a written informed consent approved by
the local Research Ethics Committee (Southeast: HCRP
2981/2009 and Northeast: CAAE 03065312.3.0000.5208).
DNA isolation
Genomic DNA was isolated from whole blood samples,
using DNA Wizard Genomic DNA Purification Kit (Promega, USA) according manufacturer’s protocol or using a
salting out method [32].
SNPs selection and genotyping
Thirteen SNPs within IL1B, IL18, NLRP1, NLRP3, NLRC4,
AIM2, CARD8 and CASP1 genes were selected according to
previously reported association studies [18, 19] and/or their
functional effect on protein activity [16] or mRNA stability
[33]. More details about all assessed SNPs are reported in
Supplementary data 2.
SNPs genotyping was performed using fluorogenic allelespecific probes (Taqman Probes, Applied Biosystems, USA)
on an ABI7500 sequence detection system (Applied Biosystems, USA).
Statistical analysis
Genotype distribution was compared for Hardy–Weinberg
(HW) equilibrium using genotype transposer [34]. At a first
sight, considering RA patients and controls independently
of their geographical origin, the allele and genotype frequencies of controls and RA patients were compared using Chisquare test. Binary logistic regression was used to confirm
the association between the polymorphisms and RA, adjusting for origin of sample and gender. Bonferroni’s correction
for multiple comparisons was applied (pBonf = observed p
value x N, N = number of studied polymorphisms within
the same gene). The possible association of the assessed
polymorphisms with DAS28 and HAQ in RA patients was
257
analyzed using the likelihood ratio test. The significance
level was set at α = 0.05 (two tailed). All statistical analyses
were performed with SPSS 16.0 (SPSS, Inc., Chicago, IL,
USA). The eventual presence of linkage disequilibrium (LD)
between polymorphisms within the same gene and the association of haplotypes with RA susceptibility were evaluated
using the online software SNPStats [35]. The power was
verified using G*Power software 3.1.9.2 [36].
Inflammasome genes expression profile
in peripheral blood monocytes
Heparinized whole blood samples were obtained from
twelve post-menopausal RA female patients (mean age
50.42 ± 13.91 years) and ten healthy post-menopausal female
controls (HC) (mean age 57.5 ± 8.14 years) from metropolitan area of state of Pernambuco. None of the patients or controls had received systemic treatment recently, as corticosteroids drugs. To evaluate the correlation of inflammasome
mRNA levels and RA activity, measured by DAS28, patients
were stratified as high disease activity (DAS28 > 5.1),
moderate disease activity (3.2 < DAS28 < 5.1), low disease activity (2.6 < DAS28 < 3.2) or disease in remission
(DAS28 < 2.6) [29, 30].
Peripheral blood monocytes were isolated by adherence
from PBMCs obtained by centrifugation over Ficoll–Paque
(Sigma-Aldrich, USA) gradient. An amount of 5 × 10 6
PBMCs/well was cultured in RPMI 1640 containing 10%
fetal bovine serum in 24-wells microplate (Invitrogen, Life
Technology, USA). For this assay, we performed biological replicates. Monocytes were stimulated with 1 µg/ml
lipopolysaccharide (LPS; Sigma-Aldrich) for 4 h and 1 mM
adenosine triphosphate (ATP; Sigma-Aldrich) for 15′. After
incubation supernatants were collected for cytokines measurement, cells were lysed for mRNA isolation and gene
expression analysis. RNA isolation from monocytes was performed using the RNAqueous micro kit (Ambion, Life Technologies, USA), following the manufacturer’s instructions.
The RNA samples were stored at − 80 °C until used and
RNA integrity analysis was performed by gel electrophoresis
and quantification by Nanodrop 2000 (Thermo Scientific,
USA). cDNA synthesis was performed with SuperScript III
First-Strand Synthesis System for RT-PCR kit (Invitrogen,
Life Technology, USA).
The major inflammasome genes, NLRP1, NLRP3,
NLRC4, AIM2, ASC/PYCARD and CASP1, and IL1B and
IL1R genes were amplified with specific TaqMan Gene
Expression Assays using the ABI 7500 SDS platform
(Applied Biosystems, USA). GAPDH was the reference
gene used for normalization. Relative quantitative expression was calculated comparing RA and healthy individuals
cells (fold change (FC) = RA 2−ΔCq/HC 2−ΔCq) following the
13
258
indications by Schmittgen and Livak, 2008 [37]. Student’s t
test was applied to compare different groups.
IL‑1β measurement
The IL-1β secreted by monocytes was measured with ELISA
kit (R&D systems, USA) following manufacturer’s protocols
and results were expressed in picograms per milliliter. Oneway ANOVA test with Bonferroni post-test was applied to
compare IL-1β secretion in RA and healthy controls cells as
well as stimulated and resting cells.
Results
Genetic association study
Genotype distributions were in Hardy–Weinberg equilibrium
for the assessed SNPs with exception of NLRP3 rs35829419
and IL1B rs1143643 SNPs in the controls (p value = 0.0001
and 0.0419, respectively). No association was observed
among polymorphisms within NLRP1, NLRC4, AIM2,
CASP1, IL1B and IL18 genes and RA in studied population.
Genotype and allele frequencies are shown in Table 1.
Considering RA patients and controls independently of
their geographical origin, it showed a significant association
between the NLRP3 rs10754558 SNP [C > G] and RA susceptibility with a statistical power = 0.999. The C allele and
C/C genotype were significantly more frequent in patients
than in controls (67 vs 56%, p value = 0.005, OR = 1.59, 95%
CI = 1.23–2.05; and 47 vs 32%, p value = 0.0036, OR = 2.23,
95% CI = 1.32–3.75, respectively). After applying Bonferroni’s correction, the association remained statistically significant (pBonf = 0.01 and 0.007, respectively).
When we performed a binary logistic regression adjusting for gender and geographical origin of sample, the association of C/C genotype for NLRP3 rs10754558 SNP with
susceptibility to RA remained statistically significant (p
value = 0.044, OR = 1.77, 95% CI = 1.23–3.09) (Table 1),
suggesting that the association is not affected by gender or
origin.
The association of the studied SNPs with Rheumatoid
Factor production and bone erosions development was evaluated and no significant association was observed. Also, the
association between SNPs and disease activity, measured by
DAS28, was not detected (data not shown).
When we assessed the influence of the studied polymorphisms on disease activity (DAS28) and patient’s functional disability (HAQ), the association between CARD8
rs2043211 SNP [A > T] and a higher mean for HAQ was
observed. Patients homozygous for T allele presented a
higher functional disability (HAQ mean = 2.13 ± 0.20)
when compared to homozygous for A allele (HAQ
13
C. Addobbati et al.
mean = 1.32 ± 0.11) and heterozygous patients (HAQ
mean = 1.41 ± 0.10). This association was observed in both
codominant [p value = 0.03, Akaike Information Criterion (AIC) = 309.2] and recessive model (p value = 0.01,
AIC = 307.5) (Table 2).
Linkage disequilibrium was found for polymorphisms
rs12150220 [A > T] and rs2670660 [A > G] within NLRP1
(D′ = 87), rs455060 [A > G] and rs212713 [T > C] within
NLRC4 (D′ = 0.94) and also for polymorphisms rs1143643
[C > T] and rs1143634 [G > A] in IL1B gene (D′ = 0.82).
However, the observed haplotypes were not differentially
distributed between RA patients and healthy individuals
(Data not shown).
Inflammasome expression analyses
We evaluated the expression of major inflammasome genes
(NLRP1, NLRP3, NLRC4, AIM2, ASC and CASP1) and of
IL-1β cytokine and its receptor genes (IL1B and IL1R) in
non-stimulated/resting and LPS + ATP-stimulated monocytes from twelve RA patients and ten healthy controls.
First, basal as well as LPS + ATP-stimulated expression was
evaluated comparing RA patients with controls. We found
a statistical significant increase in the basal expression of
CASP1 (+ 499.02-fold, p value = 0.01), IL1B (+ 2.976-fold,
p value = 0.003) and IL1R (+ 216.6-fold, p value = 0.013)
genes in untreated monocytes from RA patients when compared with untreated monocytes from healthy individuals
(Fig. 1a). In LPS + ATP-treated monocytes, NLRP3 (+ 14.5fold, p value = 0.002), NLRC4 (+ 53.88-fold, p value = 0.04),
CASP1 (+ 19.1-fold, p value = 0.004), IL1B (+ 19.7-fold, p
value = 0.004) and IL1R (+ 14.1-fold, p value = 0.007) genes
were statistical significantly upregulated in monocytes from
RA patients compared to monocytes from control individuals (Fig. 1b).
LPS + ATP-induced IL-1β secretion in monocytes from
RA (LPS + ATP versus ATP: p = 0.007; LPS + ATP versus resting: p = 0.006) as well as from healthy individuals
(LPS + ATP versus ATP: p = 0.002; LPS + ATP versus resting, p = 0.006). The stimulation with LPS induced a small
increase in IL-1β secretion in controls; however, a greater
augmentation was observed in LPS + ATP cells. In RA cells,
LPS as well LPS + ATP were able to induce a similar increment in IL-1β secretion.
IL-1β secretion was incremented in RA patients compared
to controls in resting (mean = 6.12 ± 10.8 vs. 2.13 ± 2.98 pg/
ml), +ATP (12.6 ± 19.1 vs. 2.65 ± 3.26 pg/ml), +LPS
(124.2 ± 129.7 vs. 16.12 ± 8.8 pg/ml) and in LPS + ATP
cells (287.75 ± 175.63 vs. 273.7 ± 174 pg/ml, respectively).
However, no statistical significance was observed between
RA and healthy individuals (Fig. 2).
When we evaluated the correlation of inflammasome
components and IL1B and IL18 mRNA levels with RA
NLRP1 rs12150220
A
T
AA
AT
TT
NLRP1 rs2670660
A
G
AA
AG
GG
NLRP3 rs35829419
C
A
CC
CA
AA
NLRP3 rs10754558
G
C
GG
GC
CC
AIM2 rs35130877
T
G
TT
TG
GG
AIM2 rs2276405
C
T
CC
CT
TT
SNPs
288 (67)
144 (33)
96 (44)
96 (44)
24 (12)
231 (55)
187 (45)
62 (30)
107 (51)
40 (19)
427 (98)
9 (2)
209 (96)
9 (4)
0 (0)
144 (33)
288 (67)
29 (13)
86 (40)
101 (47)
436 (100)
0 (0)
218 (100)
0 (0)
0 (0)
431 (99)
5 (1)
213 (98)
5 (2)
0 (0)
346 (58)
248 (42)
97 (33)
152 (51)
48 (16)
585 (96)
23 (4)
284 (93)
17 (6)
3 (1)
269 (44)
339 (56)
62 (20)
145 (48)
97 (32)
614 (100)
0 (0)
307 (100)
0 (0)
0 (0)
597 (98)
11 (2)
293 (96)
11 (4)
0 (0)
RA, n (%)
383 (66)
201 (34)
132 (45)
119 (41)
41 (14)
Controls, n (%)
0.54
ND
0.55
ND
ND
ND
0.43
0.0036b, c
0.005 a
0.56
0.37
0.16
0.71
0.39
0.38
0.66
0.54
0.77
p
Table 1 Allele and genotype frequencies from RA patients and controls
1
0.63
1
0.63
ND
1
ND
1
ND
ND
1
1.59
1
1.27
2.23
1
0.54
1
0.72
ND
1
1.13
1
1.1
1.3
1
0.95
1
1.11
0.8
OR
0.17–1.99
ND
0.22–1.83
ND
ND
ND
0.38–0.85
1.32–3.75
1.23–2.05
0.28–1.75
ND
0.25–1.17
0.72–1.68
0.77–2.21
0.88–1.45
0.75–1.64
0.46–1.42
0.73–1.24
95% CI
CASP1 rs572687
G
A
GG
GA
AA
IL1B rs1143643
C
T
CC
CT
TT
IL1B rs1143634
G
A
GG
GA
AA
IL18 rs1946519
C
A
CC
AC
AA
NLRC4 rs212713
T
C
TT
CT
CC
NLRC4 rs455060
A
G
AA
AG
GG
SNPs
403 (66)
211 (34)
138 (45)
127 (41)
42 (14)
324 (53)
290 (47)
84 (27)
156 (51)
67 (22)
165 (57)
125 (43)
51 (35)
63 (44)
31 (21)
489 (81)
115 (19)
198 (65)
93 (31)
11 (4)
390 (65)
214 (35)
134 (44)
122 (41)
46 (15)
493 (82)
109 (18)
200 (66)
93 (31)
8 (3)
Controls, n (%)
271 (62)
163 (38)
87 (40)
97 (45)
33 (15)
234 (54)
200 (46)
63 (29)
108 (50)
46 (21)
237 (54)
199 (46)
66 (30)
105 (48)
47 (22)
347 (80)
85 (20)
144 (67)
59 (27)
13 (6)
307 (71)
127 (29)
111 (51)
85 (39)
21 (10)
359 (82)
77 (18)
148 (68)
63 (29)
7 (3)
RA, n (%)
0.37
0.49
0.32
0.75
0.8
0.75
0.33
0.66
0.54
0.56
0.35
0.86
0.39
0.05
0.05
0.72
0.96
0.92
p
1
1.15
1
1.21
1.25
1
0.95
1
0.92
0.92
1
1.1
1
1.29
1.17
1
1.04
1
0.87
1.63
0.84
0.55
1
0.75
1
0.97
1
0.92
1.18
OR
0.82–1.79
0.73–2.12
0.89–1.48
0.60–1.42
0.54–1.55
0.74–1.23
0.77–2.14
0.63–2.19
0.81–1.51
0.58–1.31
0.71–3.73
0.76–1.42
0.57–1.24
0.29–1.01
0.57–0.99
0.61–1.37
0.42–3.33
0.7–1.34
95% CI
Polymorphisms and expression of inflammasome genes are associated with the development and…
259
13
260
C. Addobbati et al.
95% CI
activity, measured by DAS28, no statistical significance was
observed (Data not show).
13
Binary logistic regression, adjusted by sex and origin of sample: p = 0.044, OR = 1.77, 95% CI = 1.23–3.09
p value after Bonferroni correction = 0.007
c
p value after Bonferroni correction = 0.01
b
*Due to technical issues, only 145 healthy individuals were genotyped for SNP rs1946519
a
RA rheumatoid arthritis, p Chi-square test p value, OR odds ratio, CI confidence interval, ND not determined
0.94–1.94
0.57–2.2
0.13
0.87
434 (72)
168 (28)
157 (52)
120 (40)
24 (8)
CARD8 rs2043211
A
T
AA
AT
TT
300 (69)
136 (31)
99 (45)
102 (47)
17 (8)
Controls, n (%)
SNPs
Table 1 (continued)
RA, n (%)
p
0.28
OR
1
1.17
1
1.35
1.12
95% CI
0.89–1.53
SNPs
Controls, n (%)
RA, n (%)
p
OR
Discussion
In the last years, substantial information has emerged connecting deregulated inflammasome signaling to inflammatory diseases. In this study, we evidenced for the first time
the association between SNPs in inflammasome genes and
RA development in the Brazilian population. In addition, we
demonstrated a dysregulated expression of some inflammasome components as well as IL-1β cytokine and its receptor
genes (IL1B and IL1R) in RA patients.
The NLRP3 rs10754558 [C > G] C allele seems to confer an augmented risk for the development of RA when in
homozygosis (OR = 1.77) with a power up to 99.9%; the
moderate value of OR suggest that being RA a multifactorial trait NLRP3 SNP gives a partial contribution to diseases susceptibility. This SNP is located within the 3′UTR of
NLRP3 gene and according to the PolymiRTS Database 2.0
(http://compbio.uthsc.edu/miRSNP/) its occurrence affects
the binding of miRNAs. In the presence of G allele, there is
a binding site for miR-3529-3p and miR-549a, while the C
allele abrogates such site, but gives rise to a binding site for
miR-146a-5p, miR-146b-5p, miR-589-5p and miR-7153-5p.
If and how rs10754558 SNP interferes with the binding of
these miRNAs in vivo remains to be further elucidated.
According to Hitomi et al., 2009, functional analyses of
NLRP3 rs10754558 SNP showed that allele G influences
higher NLRP3 expression (1.4-fold) by altering mRNA stability (34). The eventual effect of this 1.4-fold increasing
in NLRP3 expression on the inflammasome activation has
not been investigated. The C allele was also associated to
type 1 diabetes mellitus susceptibility [18] and to systemic
lupus erythematosus development (personal communication,
manuscript submitted), suggesting a role of this polymorphism in autoimmunity development.
When considering inflammasome SNPs in RA clinical manifestations, we observed the association between
CARD8 rs2043211 SNP [A > T] (p.C10X) and disease’s
severity. Patients homozygous for T allele presented a higher
functional disability measured by HAQ. CARD8 interacts
physically with caspase-1 and negatively regulates caspase1-dependent IL-1β expression and nuclear factor NFĸB activation [38–41]. The rs2043211 polymorphism introduces
a premature stop codon (Cys > Stop), which results in the
expression of a severely truncated protein [42]. The exact
role of CARD8 in inflammasome biology is still unclear.
It has been proposed that CARD8 acts as a modulator of
NLRP3 activation or it exerts an inflammasome independent
role, as NF-kB inductor [43]. CARD8 C10X variation leads
to an increased secretion of IL-1β, especially in combination
261
Polymorphisms and expression of inflammasome genes are associated with the development and…
Table 2 Association between
CARD8 rs2043211 SNP and a
higher functional disability
n
Codominant model
A/A
61
A/T
58
T/T
8
Recessive model
A/A–A/T
119
T/T
8
HAQ mean ± SD
dif
95% CI
p
AIC
1.32 ± 0.11
1.41 ± 0.10
2.13 ± 0.20
0
0.09
0.80
− 0.20 to 0.37
0.21 to 1.39
0.03
309.2
1.36 ± 0.07
2.13 ± 0.20
0
0.76
0.19 to 1.33
0.01
307.5
dif HAQ mean difference in relation to A/A genotype, CI confidence interval, p p value, AIC Akaike information criterion
Fig. 2 IL-1β secretion in healthy controls (HC) and RA patients in
non-stimulated monocytes (R); ATP-stimulated monocytes (ATP);
LPS-stimulated monocytes (LPS); and LPS + ATP-stimulated monocytes (LPS + ATP). *p < 0.05
Fig. 1 NLRP3, NLRP1, AIM2, CASP1, NLRC4, IL1B, IL1R and
PYCARD gene expressions in RA patients compared with healthy
controls (HC). The results were normalized to GAPDH expression.
Target gene expression in healthy controls was normalized to 1 (not
reported in the graph) and fold change (FC) is reported as RA 2−ΔCT/
HC 2−ΔCT. a Expression in non-stimulated monocytes. b Expression
in LPS + ATP-stimulated monocytes. *p value < 0.05
with NLRP3 Q705K [16]. Moreover, this variation was associated to an increased induction of NFĸB activity and its
translocation to the nucleus [44], which leads to high constitutive levels of pro-IL-1β and tumor necrosis factor α,
mediators of inflammation in RA [45]. Furthermore, NF-ĸB
has been reported to contribute to the proliferation of synovial cells, and consequently, to bone and cartilage destruction [46, 47].
Kastbom et al., 2010 [27] and Fontalba et al., 2007 [44]
also described an association between CARD8 p.C10X
polymorphism and RA severity in Swedish and Spanish
patients, respectively. Different from our study, both studies
assessed RA severity through cumulative amount DAS28
over 2 years, while we have chosen to measure the severity of the disease by the HAQ due to the fluctuation of the
DAS28 during the course of the disease. However, our study
corroborates the involvement of CARD8 p.C10X polymorphism in RA severity and then its possible use as a genetic
prognostic marker for RA.
The combination between the minor alleles for NLRP3
rs35829419 (Q705K) and CARD8 rs2043211 (p.C10X)
polymorphisms was described as associated with delayed
apoptosis of neutrophils [48] and RA susceptibility and
severity [22]. However, it was not possible to confirm this
association in our population, as the NLRP3 A/A genotype
was not found in our patients group. When we tested the
13
262
combination between the other genotypes for those polymorphisms, no significant association was observed.
Moreover, our results corroborate the findings from
García-Bermúdez et al., 2013 [26], Hamad et al., 2011
[24] and Kastbom et al., 2010 [27], which demonstrated
the lack of association of CARD8 rs2043211 with RA susceptibility when individually analyzed in Spanish, French,
Tunisian and Swedish populations. Despite the association
between the rs2043211 SNP and RA severity, this SNP
was not associated to bone erosions and rheumatoid factor
in our population.
When we assessed the gene expression profile for RA
patients, we found a statistical significant upregulation
of CASP1, IL1B and IL1R genes in untreated monocytes
from RA patients when compared with healthy individuals. This result suggests that RA patients are characterized
by a chronic expression of CASP1, IL1B and IL1R genes.
In LPS + ATP-treated monocytes from RA patients, the
same genes were upregulated but accompanied by NLRP3
and NLRC4 genes. This increased expression of CASP1,
IL1B and IL1R in stimulated monocytes from patients
may be consequence of the previous upregulation in resting monocytes. The observed augmented expression of
NLRP3 and NLRC4 genes in patients after stimulus prompt
us to hypothesize that NLRP3 and NLRC4 transcriptions
are dysregulated in RA patients, contributing to the establishment of the exacerbated inflammation observed in the
disease. When we compared the gene expression between
patients with disease in remission and patients with high
disease activity, no statistical difference was observed,
suggesting that the treatment of patients is efficient to control the disease symptoms but may be not able to control
the deregulation of inflammasome.
Being aware that other mechanisms may influence upon
IL-1β production overall, the observed differences in inflammasome components and IL-1β and its receptor genes
expression between patients and healthy controls are accompanied by IL-1β secretion ex vivo monocytes. In all studied
conditions, the RA monocytes secreted higher amounts of
IL-1β. Basal secretion of IL-1β in RA monocytes was higher
compared to healthy ones, indicating a constitutive secretion
of pro-inflammatory cytokine.
The exact mechanisms responsible for the production and
secretion of IL-1β remain unclear, but two signals are traditionally required. The first signal, in our case LPS, induces
the transcription of pro-IL-1β and inflammasome subunits;
the second signal promotes rapid activation of caspase-1 and
then secretion of mature IL-1β [49, 50]. This second signal
is provided by reduction of intracellular K + generated by
ATP stimulus. Of note in both LPS-stimulated and ATPstimulated RA monocyte, the signals individually are sufficient to induce an augment of IL-1β secretion, without the
common first or second signal mediation (Fig. 2), suggesting
13
C. Addobbati et al.
an inflammasome complex more prone to activation in RA
monocytes than in healthy ones.
Mathews et al., 2014 [23] also showed a higher NLRP3
and CASP1 expression in RA patients. However, in this
study, the gene expression was characterized directly in
peripheral blood mononuclear cells of patients. Thereby,
the upregulation of these inflammasome components could
be due to the abundant release of DAMPs upon tissue damage, typical in RA pathogenesis [51–53]. Differently, our
study evaluated the inflammasome gene expression in RA
and control individual’s monocytes under the same conditions, proving indeed the dysregulated transcription of these
inflammasome components.
The importance of NLRP3 in RA pathogenesis is confirmed by the findings of increased NLRP3 mRNA in the
synovium of RA patients compared to individuals suffering from non-autoimmune osteoarthritis [25]. The NLRP3inflammasome was described as an activator of both apoptotic and pyroptotic cell death [54]. Therefore, besides the
excessive IL-1β secretion, the deregulated activation of this
complex may exacerbate the cell death, contributing to the
inflammatory process and its maintenance in RA disease.
Conclusion
In conclusion, herein, we provide enough data to infer that
CASP1, IL1B and IL1R are activated in RA patients as well
as NLRP3 and NLRC4 genes are dysregulated transcript
upon stimulus. We also demonstrated that NLRP3 and
CARD8 polymorphisms are associated to RA susceptibility and severity in our studied populations. These results
are useful to help understanding the role of inflammasome
complex in RA.
Acknowledgements This work was supported by the following Brazilian funding agencies: CAPES (Coordenação de Aperfeiçoamento
de Pessoal de Nível Superior), CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), FAPESP (Fundação Amparo à
Pesquisa do Estado de São Paulo) and FACEPE (Fundação de Amparo
à Ciência e Tecnologia de Pernambuco).
Author contributions CAJC conducted experiments, wrote the manuscript and prepared the tables and figures; HLAC, JEA and ALMTR
helped conducting the experiments and provided insightful suggestions to the manuscript; PSG, JAS, AP and SC assisted in the study
design and coordination, and read, corrected and provided major suggestions to this manuscript; TSF, AD, LFRJ, ALBPD, RDRO, PLJ
and EAD recruited patients and participated in data acquisition. All
authors addressed important intellectual content and approved the final
manuscript for publication.
Compliance with ethical standards
Conflict of interest The authors have declared no conflicts of interest.
Polymorphisms and expression of inflammasome genes are associated with the development and…
References
1. Hitchon CA, El-Gabalawy HS. The synovium in rheumatoid
arthritis. Open Rheumatol J. 2011;5:107–14.
2. Tobón GJ, Youinou P, Saraux A. The environment, geo-epidemiology, and autoimmune disease: rheumatoid arthritis. Autoimmun
Rev. 2010;9(5):A288–A92.
3. Alamanos Y, Drosos AA. Epidemiology of adult rheumatoid
arthritis. Autoimmun Rev. 2005;4(3):130–6.
4. Jacob N, Jacob CO. Genetics of rheumatoid arthritis: an impressionist perspective. Rheum Dis Clin N Am. 2012;38(2):243–57.
5. Firestein GS. Evolving concepts of rheumatoid arthritis. Nature.
2003;423:356–61.
6. Gierut A, Perlman H, Pope RM. Innate immunity and rheumatoid
arthritis. Rheum Dis Clin N Am. 2010;36(2):271–96.
7. Joosten LA, Helsen MM, Saxne T, et al. IL-1 alpha beta blockade
prevents cartilage and bone destruction in murine type II collageninduced arthritis, whereas TNF-alpha blockade only ameliorates
joint inflammation. J Immunol. 1999;163:5049–55.
8. Bresnihan B, Alvaro-Gracia JM, Cobby M, et al. Treatment of
rheumatoid arthritis with recombinant human interleukin-1 receptor antagonist. Arthritis Rheum. 1998;41:2196–204.
9. Alten R, Gram H, Joosten LA, et al. The human anti-IL-1 beta
monoclonal antibody ACZ885 is effective in joint inflammation
models in mice and in a proof-of-concept study in patients with
rheumatoid arthritis. Arthritis Res Ther. 2008;10:R67.
10. Shaw PJ, McDermott MF, Kanneganti TD. Inflammasomes and
autoimmunity. Trends Mol Med. 2011;17(2):57–64.
11. Man SM, Kanneganti TD. Regulation of inflammasome activation.
Immunol Rev. 2015;265(1):6–21.
12. Ito S, Hara Y, Kubota T. CARD8 is a negative regulator for
NLRP3 inflammasome, but mutant NLRP3 in cryopyrin-associated periodic syndromes escapes the restriction. Arthritis Res
Ther. 2014;16(1):R52. 16(.
13. Neven B, Prieur AM. Quartier dit Maire P. Cryopyrinopathies:
update on pathogenesis and treatment. Nat Clin Pract Rheumatol.
2008;4:481–9.
14. Pontillo A, Girardelli M, Kamada AJ, et al. Polimorphisms in
inflammasome genes are involved in the predisposition to systemic lupus erythematosus. Autoimmunity. 2012;45(4):271–8.
15. Carlström M, Ekman AK, Petersson S, et al. Genetic support for
the role of the NLRP3 inflammasome in psoriasis susceptibility.
Exp Dermatol. 2012;21(12):932–7.
16. Roberts RL, Topless RK, Phipps-Green AJ, et al. Evidence of
interaction of CARD8 rs2043211 with NALP3 rs35829419 in
Crohn’s disease. Genes Immun. 2010;11(4):351–6.
17. Schoultz I, Verma D, Halfvarsson J, et al. Combined polymorphisms in genes encoding the inflammasome components NALP3
and CARD8 confer susceptibility to Crohn’s disease in Swedish
men. Am J Gastroenterol. 2009;104(5):1180–8.
18. Pontillo A, Brandao L, Guimaraes R, et al. Two SNPs in NLRP3
gene are involved in the predisposition to type-1 diabetes and
celiac disease in a pediatric population from northeast Brazil.
Autoimmunity. 2010;43(8):583–9.
19. Pontillo A, Vendramin A, Catamo E, et al. The missense variation Q705K in CIAS1/NALP3/NLRP3 gene and an NLRP1 haplotype are associated with celiac disease. Am J Gastroenterol.
2011;106(3):539 – 44.
20. Magitta NF, Bøe Wolff AS, Johansson S, et al. A coding polymorphism in NALP1 confers risk for autoimmune Addison’s disease
and type 1 diabetes. Genes Immun. 2009;10:120–4.
21. Levandowski CB, Mailloux CM, Ferrara TM, et al. NLRP1
haplotypes associated with vitiligo and autoimmunity increase
interleukin-1β processing via the NLRP1 inflammasome. Proc
Natl Acad Sci USA. 2013;110(8):2952–6.
263
22. Kastbom A, Verma D, Eriksson P, et al. Genetic variation in
proteins of the cryopyrin inflammasome influences susceptibility and severity of rheumatoid arthritis (the Swedish TIRA
project). Rheumatology (Oxford). 2008;47(4):415–7.
23. Mathews RJ, Robinson JI, Battellino M, et al. Evidence of
NLRP3-inflammasome activation in rheumatoid arthritis (RA);
genetic variants within the NLRP3-inflammasome complex in
relation to susceptibility to RA and response to anti-TNF treatment. Ann Rheum Dis. 2014;73(6):1202–10.
24. Ben Hamad M, Cornelis F, Marzouk S, et al. Association study
of CARD8 (p.C10X) and NLRP3 (p.Q705K) variants with
rheumatoid arthritis in French and Tunisian populations. Int J
Immunogenet. 2012;39(2):131–6.
25. Rosengren S, Hoffman HM, Bugbee W, et al. Expression and
regulation of cryopyrin and related proteins in rheumatoid
arthritis synovium. Ann Rheum Dis. 2005;64(5):708 – 14.
26. García-Bermúdez M, López-Mejías R, González-Juanatey
C, et al. CARD8 rs2043211 (p.C10X) polymorphism is not
associated with disease susceptibility or cardiovascular events
in Spanish rheumatoid arthritis patients. DNA Cell Biol.
2013;32(1):28–33.
27. Kastbom A, Johansson M, Verma D, et al. CARD8 p.C10X
polymorphism is associated with inflammatory activity in early
rheumatoid arthritis. Ann Rheum Dis. 2010;69(4):723–6.
28. Kay J, Upchurch KS. ACR/EULAR 2010 rheumatoid arthritis
classification criteria. Rheumatology (Oxford) 2012; 51Suppl
6:vi5–9.
29. Prevoo ML, van’t Hof MA, Kuper HH, et al. Modified disease activity scores that include twenty-eight-joint counts.
Development and validation in a prospective longitudinal
study of patients with rheumatoid arthritis. Arthritis Rheum.
1995;38:44–8.
30. Van Gestel AM, Haagsma CJ, van Riel PL. Validation of rheumatoid arthritis improvement criteria that include simplified joint
counts. Arthritis Rheum. 1998;41:1845–50.
31. Ramey DR, Fries JF, Singh G. The health assessment questionnaire 1995—Status and review. In: Spilker B, editor. Quality of
life and pharmacoleconomics in clinical trials. 2nd ed. Philadelphia: Lippincott-Raven Publishers; 1996.
32. Lahiri DK, Nurnberger JI. A rapid non-enzymatic method for the
preparation of HMW DNA from blood for RFLP studies. Nucleic
Acids Res. 1991;19:5444.
33. Hitomi Y, Ebisawa M, Tomikawa M, et al. Associations of functional NLRP3 polymorphisms with susceptibility to food-induced
anaphylaxis and aspirin-induced asthma. J Allergy Clin Immunol.
2009;124(4):779–85e6.
34. Cox DG, Canzian F. Genotype transposer: automated genotype
manipulation for linkage disequilibrium analysis. Bioinformatics.
2001;17(8):738–9.
35. Solé X, Guinó E, Valls J, Iniesta R, Moreno V. SNPStats: a
web tool for the analysis of association studies. Bioinformatics.
2006;22(15):1928–9.
36. Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149–60.
37. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the
comparative C(T) method. Nat Protoc. 2008;3(6):1101–8.
38. Razmara M, Srinivasula SM, Wang L, et al. CARD-8 protein, a
new CARD family member that regulates caspase-1 activation and
apoptosis. J Biol Chem. 2002;277:13952–8.
39. Bouchier-Hayes L, Conroy H, Egan H, et al. CARDINAL, a novel
caspase recruitment domain protein, is an inhibitor of multiple
NF-κB activation pathways. J Biol Chem. 2001;276:44069–77.
40. Stilo R, Leonardi A, Formisano L, et al. TUCAN/CARDINAL
and DRAL participate in a common pathway for modulation of
NF-κB activation. FEBS Lett. 2002;521:165–9.
13
264
41. von Kampen O, Lipinski S, Till A, et al. Caspase recruitment
domain-containing protein 8 (CARD8) negatively regulates
NOD2-mediated signaling. J Biol Chem. 2010;285:19921–6.
42. Bagnall RD, Roberts RG, Mirza MM, et al. Novel isoforms of the
CARD8 (TUCAN) gene evade a nonsense mutation. Eur J Hum
Genet. 2008;16:619–25.
43. Paramel GV, Sirsjö A, Fransén K. Role of genetic alterations in
the NLRP3 and CARD8 genes in health and disease. Mediators
Inflamm. 2015:846782.
44. Fontalba A, Martinez-Taboada V, Gutierrez O, et al. Deficiency
of the NF-kappaB inhibitor caspase activating and recruitment
domain 8 in patients with rheumatoid arthritis is associated with
disease severity. J Immunol. 2007;179:4867–73.
45. Moelants EA, Mortier A, Van Damme J, et al. Regulation of
TNF-α with a focus on rheumatoid arthritis. Immunol Cell Biol.
2013;91(6):393–401.
46. Makarov SS. NF-κB in rheumatoid arthritis: a pivotal regulator of
inflammation, hyperplasia, and tissue destruction. Arthritis Res.
2001;3:200–6.
47. Okamoto H, Cujec TP, Yamanaka H, et al. Molecular aspects
of rheumatoid arthritis: role of transcription factors. FEBS J.
2008;275(18):4463–70.
48. Blomgran R, Patcha Brodin V, Verma D, et al. Common genetic variations in the NALP3 inflammasome are
13
C. Addobbati et al.
49.
50.
51.
52.
53.
54.
associated with delayed apoptosis of human neutrophils. PLoS
One. 2012;7(3):e31326.
Perregaux DG, Gabel CA. Human monocyte stimulus-coupled
IL-1beta posttranslational processing: modulation via monovalent
cations. Am J Physiol. 1998;275:C1538–C1547.
Perregaux D, Gabel CA. Interleukin-1 beta maturation and release
in response to ATP and nigericin. Evidence that potassium depletion mediated by these agents is a necessary and common feature
of their activity. J Biol Chem. 1994;269:15195–203.
Shimada K, Crother TR, Karlin J, et al. Oxidized mitochondrial
DNA activates the NLRP3 inflammasome during apoptosis.
Immunity. 2012;36(3):401 – 14.
Pugin J. How tissue injury alarms the immune system and causes
a systemic inflammatory response syndrome. Ann Intensive Care.
2012;2(1):27.
Davis BK, Wen H, Ting JP. The inflammasome NLRs in immunity, inflammation, and associated diseases. Annu Rev Immunol.
2011; 29:707 – 35.
Sagulenko V, Thygesen SJ, Sester DP, et al. AIM2 and NLRP3
inflammasomes activate both apoptotic and pyroptotic death pathways via ASC. Cell Death Differ. 2013;20(9):1149–60.
Immunogenetics (2020) 72:217–224
https://doi.org/10.1007/s00251-020-01158-6
ORIGINAL ARTICLE
Differential expression of the inflammasome complex genes
in systemic lupus erythematosus
Heidi Lacerda Alves da Cruz 1 & Catarina Addobbati Jordão Cavalcanti 1,2 & Jaqueline de Azêvedo Silva 1 &
Camilla Albertina Dantas de Lima 1 & Thiago Sotero Fragoso 3 & Alexandre Domingues Barbosa 4 &
Andréa Tavares Dantas 4 & Henrique de Ataíde Mariz 4 & Angela Luzia Branco Pinto Duarte 4 & Alessandra Pontillo 5 &
Sergio Crovella 1,2 & Paula Sandrin-Garcia 1,2
Received: 3 September 2019 / Accepted: 29 January 2020 / Published online: 5 February 2020
# Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract
Systemic lupus erythematosus (SLE) is a complex autoimmune disorder involving heterogeneous clinical manifestations and
numerous susceptibility genes. Several findings evidence the critical role of inflammasomes in the predisposition to autoimmune
diseases and in SLE. We investigated whether inflammasome polymorphins could affect susceptibility to develop and/or severity
SLE. Moreover, differences in inflammasome activation in peripheral blood were also evaluated in SLE patients and controls.
The distribution of 13 SNPs in eight inflammasome genes was evaluated. To assess inflammasome priming in peripheral blood
monocytes of SLE and controls, differential expression of selected inflammasome genes and IL-1ß production was analyzed in
resting condition as well as after LPS and ATP stimulation. Results showed that the gain-of-function variant rs10754558
(NLRP3) was significantly more frequent in SLE patients with nephritis, reinforcing the concept of a key role of NLRP3
inflammasome not only in SLE but also especially in kidney disease. SLE monocytes in resting condition showed a higher level
of IL-1ß expression and produced higher levels of IL-1ß when stimulated with LPS+ATP comparing to controls. The stimulation
induced a significant expression of NLRP1, AIM2, CASP1, and IL1B genes, suggesting that the NLRP1 inflammasome is
responsible for the IL-1ß production observed in monocytes. These data emphasized once more the important contribution of
inflammasome in SLE-associated inflammation.
Keywords Systemic lupus erythematosus . Polymorphisms . Inflammasome . Gene expression . Nephritis
Introduction
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s00251-020-01158-6) contains supplementary
material, which is available to authorized users.
* Paula Sandrin-Garcia
paulasandrin27@gmail.com
1
Laboratory of Immunopathology Keizo Asami, Federal University of
Pernambuco, Recife, Pernambuco, Brazil
2
Department of Genetics, Federal University of Pernambuco,
Recife, Pernambuco, Brazil
3
Rheumatology Service, “Clinical Hospital”, Federal University of
Alagoas, Maceió, Alagoas, Brazil
4
Rheumatology Division, “Clinical Hospital”, Federal University of
Pernambuco, Recife, Pernambuco, Brazil
5
Laboratory of Immunogenetics, Department of Immunology,
Institute of Biomedical Sciences, University of São Paulo, São
Paulo, Brazil
Systemic lupus erythematosus (SLE) is a complex autoimmune disease that predominantly affects women of childbearing age. SLE hallmark is the generation of autoantibodies that
react with self-nuclear and cytoplasmic antigens, culminating
in immunocomplex deposition in several organs, inducing cell
death and organ failure (Davidson and Diamond 2001; Tsokos
et al. 2007). Although under intense investigations, the genetic
basis of human SLE is still not fully understood (GhodkePuranik and Niewold 2015; Tsao 2003; Croker and
Kimberly 2005).
Several studies indicate that abnormal activation of genes
related to the inflammatory response, resulting in an altered
activation of IL-1ß and/or NF-kB, may contribute to the pathogenesis of autoimmune disorders with a strong inflammatory
component, as observed in SLE (Shinkai and TH 2008; Shaw
et al. 2011a; Aksentijevich et al. 2007; Magitta et al. 2009;
Immunogenetics (2020) 72:217–224
218
Yang et al. 2015a; Kahlenberg and Kaplan 2014a). In the last
few years, the innate immune signaling complex, called
inflammasome, has garnered support for a role in triggering
and maintaining SLE (Kahlenberg and Kaplan 2014a).
Different innate immune cytoplasmic receptors, belonging to
Nod-like Receptors/NLRs (i.e., NLRP1, NLRP3, NLRC4) or
PYHIN (i.e., AIM2, IFI16) families, have been described as
able to assemble an inflammasome in response to pathogenor danger-associated molecular patterns (PAMPs or DAMPs)
leading to caspase-1 activation and consequent cleavage and
secretion of pro-inflammatory cytokines IL-1β and IL-18
(Shaw et al. 2011b; Man and Kanneganti 2015; Ito et al.
2014).
Several lupus-associated DAMPs (i.e., generation of
reactive oxygen species due to inefficient clearance of
cellular debris; impaired clearance of neutrophil extracellular trap (NET); accumulation of cytosolic self DNA)
could be recognized by inflammasome receptors consequently inducing an inflammatory response (Yang and
Chiang 2015).
NLRP3 inflammasome activation has been described as
increase in lupus macrophages (Kahlenberg et al. 2013) and
two recent studies suggested that this induction appeared to
be, at least partially, caused by lupus-specific autoantibodies
(Zhang et al. 2016; Shin et al. 2013a). NLRP3 inflammasome
plays an important role also for the progression of SLE, contributing to the development of nephritis (Ka et al. 2015; Li
et al. 2015).
Recently, it was demonstrated that the hyper-expression of
NLRP3 in myeloid cells induces a severe disease in an experimental model of lupus (Lu et al. 2017). Even if NLRP3 remains the first candidate DAMPs’ receptor involved in SLE
pathogenesis, other inflammasome components have been
pointed out as possible contributing factors. Our research
group demonstrated that gain-of-function polymorphisms in
the receptor NLRP1 gene were associated to SLE and SLEassociated nephritis, rash, and arthritis (Pontillo et al. 2012).
Accordingly, a deregulation not only of NLRP3 but also of
NLRP1 inflammasomes has been reported in patients with
SLE (Yang et al. 2014).
Accordingly, a deregulation not only of NLRP3 but also of
NLRP1 inflammasomes has been reported in patients with
SLE (Yang et al. 2014). Even though, the role of
inflammasome in the pathogenesis of SLE should be more
deeply elucidated (Yang et al. 2015b; Camargo et al. 2004;
Wang et al. 2013; Wen et al. 2014). So, to better understand
the possible impact of inflammasome gene disregulation in
SLE development and its clinical phenotype, we analyzed a
selected panel of single-nucleotide polymorphisms (SNPs) in
NLRP1, NLRP3, NLRC4, AIM2, CARD8, CASP1, IL1B, and
IL18 genes; moreover, inflammasome activation was evaluated in monocytes from SLE patients to further characterize
inflammasome profile in these individuals.
Materials and methods
Subject
We recruited 132 SLE patients (129 women/3 men, mean age
37.1 years ± 10.5) and 154 healthy controls (HC) (125
women/29 men, mean age 33.5 years ± 13.4) at the Clinical
Hospital of Federal University of Pernambuco (HC-UFPE),
from metropolitan region of Recife (Pernambuco, Brazil).
Patients were classified according to the criteria of the
American College of Rheumatology (ACR) (Hochberg
1997) and in the cumulative organic damage index (SLICC/
ACR) or disease activity index (SLEDAI). The control group
was composed of healthy volunteers without SLE or any other
autoimmune diseases, or other problems that may impair the
immune system. Subjects with diabetes mellitus, renal or hepatic dysfunction, acute or chronic inflammatory disease, cancer, and infection diseases were excluded from the study.
Subjects were chosen randomly in the population, sex-, age-,
and ethnicity-matched and from the same geographical area of
the patients (metropolitan Recife, PE). The demographic, clinical, and laboratory profiles of patients and controls are reported in Table 1.
The following laboratory and clinical data regarding the
SLE patients were collected: hematological alterations (hemolytic anemia, leucopenia, lymphopenia, thrombocytopenia),
immunological alterations (Anticardiolipin, Anti-Sm, Anti-
Table 1 Demographic, clinical, and laboratory data of Brazilian case/
control cohort of SLE. Data are expressed as number of individuals and
percentage or means ± standard deviation. ANA: antinuclear antibody test
Characteristic
SLE
(n = 132)
HC
(n = 154)
Sex, male/female; n (%)
Age, years; mean ±SD
Lupus blood tests
Anti-dsDNA positiveness
3 (2)/129 (98)
37.1 ± 10.5
n (%)
37 (27%)
29 (19)/125 (81)
33.5 ± 13.4
ANA positiveness
Immunologic alterationsa
Hematologic alterationsb
Clinical manifestations
Cutaneous manifestations
Photosensitivity
Lupus arthritis
Oral ulcers
Nephritic disorders
Neuropsychiatric disordersc
114 (82%)
44 (32%)
82 (59%)
n (%)
89 (64%)
85 (61%)
88 (63%)
29 (20%)
58 (42%)
12 (8%)
a
Anticardiolipin, anti-Sm, anti-RNP, anti-Ro/SSA, anti-La/SSB
b
Hemolytic anemia, leucopenia, lymphopenia, thrombocytopenia
c
Seizures, headache, psychosis
Immunogenetics (2020) 72:217–224
219
RNP, Anti-Ro/SSA, Anti-La/SSB), presence of antinuclear
antibodies (ANA), presence of anti-double-strand DNA antibody (anti-ds-DNA), antiphospholipid syndrome (APS), photosensitivity, serositis (pleuritis, pericarditis), Lupus arthritis,
cutaneous manifestations (malar or discoid rashes), oral ulcers, neuropsychiatric disorder (seizures, headache, psychosis), Raynaud phenomenon, and nephritic disorder. Patients
were classified as having nephritic disease based on laboratory
parameters, specifically changes in urine summary and 24-h
proteinuria, as follows: persistent proteinuria (> 0.5 g/day or
3+) or abnormal cylindrury. All the participants provided a
written informed consent approved by the local Research
Ethics Committee (CAAE 03065312.3.0000.5208).
genes in peripheral blood–derived monocytes among subjects
within the case/control study (10 SLE patients and 10 healthy
individuals) and if their expression differed between the basal
condition and after LPS+ATP stimulation.
All the patients selected for gene expression study had a
remission for SLE. The healthy individuals were sex-, age-,
and ethnicity-matched according to patients and did not present recent illness (autoimmune diseases, diabetes mellitus, renal or hepatic dysfunction, acute or chronic inflammatory disease, cancer, infection diseases) or any pharmacological treatment before blood collection.
DNA isolation and genotyping
Genomic DNA from SLE patients and controls was extracted
from peripheral blood using the DNA Wizard Genomic DNA
Purification Kit (Promega, Madison, WI, USA).
Thirteen SNPs were selected within NLRP1, NLRP3,
NLRC4, AIM2, CARD8, CASP1, IL1B, and IL18 genes according to previously reported association studies (Pontillo
et al. 2010; Pontillo et al. 2011) and/or their functional effect
on protein activity or mRNA stability (Roberts et al. 2010;
Hitomi et al. 2009), and minor allele frequency (MAF; >
5%) (Supplementary File 1).
SNPs were genotyped using allele-specific TaqMan assays
(ThermoFisher Scientific, California, USA) and qPCR in a
ABI7500 Real-Time PCR equipment (Thermo Fisher
Scientific, California, USA). SDS software v2.3 (Thermo
Fisher Scientific) was used for allelic discrimination.
Heparinized whole blood samples were obtained from ten
post-menopausal SLE female patients (mean age 42.6 ±
12 years) and ten healthy post-menopausal female controls
(HC) (mean age 57.5 ± 8.14 years). To establish a condition
where both patients and controls ex vivo cell cultures would
clear up from no reported inflammatory responses (in HC),
cells were cultured overnight and after this period medium
was changed. This procedure allowed cells to metabolize
any ex vivo conditions before initiate inflammasome stimuli.
To stimulate, we exposed 0.5 × 106 peripheral blood monocytes with 1 μg/ml lipopolysaccharide (LPS; Sigma-Aldrich)
for 4 h and then with 1 mM adenosine triphosphate (ATP;
Sigma-Aldrich) for 15′ in RPMI-1640 + 10% fetal bovine
serum/FBS (ThermoFisher Scientific). Inflammasome genes
modulation was evaluated in monocytes by real-time quantitative PCR and gene expression specific Taqman assays
(Thermo Fisher Scientific).
Statistical analysis
IL-1β measurement
SNPs distribution in case/control cohort as well as in SLE
groups (stratified according to clinical presentation) was analyzed by multivariate association based on general linear model (GLM) adjusted for confounders variables (age, sex, race)
using statistical program R package “SNP-association” version 1.5–2. Genetic analyses were performed taking into account co-dominant, dominant, recessive, and overdominant
models for all SNPs. The Haploview software was used to
investigate the linkage disequilibrium (LD) and to derive the
haplotypes. A significant threshold of p = 0.004 was assumed
after Bonferroni correction for multiple SNPs analysis (p =
0.05/n; n = 13 SNPs).
The secreted IL-1β was measured with ELISA (IL-1β assays,
R&D systems, USA). Results were expressed in picograms
per milliliter. Secretion differences between patients and controls were tested with Mann-Whitney U test with SPSS 15.0
(SPSS, Inc., Chicago, IL, USA).
Inflammasome gene expression assays
Subjects
We investigated the relative mRNA expression of IL-1β,
NLRP1, NLRP3, NLRC4, AIM2, ASC/PYCARD, and CASP1
Peripheral blood monocytes culture
Relative gene expression analysis
Total RNA was isolated using the RNAqueous micro kit
(Ambion, Thermofisher Scientific, USA). RNA integrity
was assessed by gel electrophoresis and quantification by
Nanodrop 2000 (ThermoScientific). After retro-transcription
of 0.5 μg total RNA (Super Script™ III Reverse Transcriptase
(Invitrogen, Thermoscientific)), IL1B and selected
inflammasome genes, namely NLRP1, NLRP3, NLRC4,
AIM2, ASC/PYCARD, and CASP1 were amplified with
TaqMan® gene-specific assays and ABI Prism 7500 RealTime PCR equipment. Gene modulation in SLE monocytes
compared to HC and stimulated (LPS) versus unstimulated
Immunogenetics (2020) 72:217–224
220
resting (R) monocytes were calculated as 2exp-ΔCt ± standard
deviation (fold change - FC). The SDS 2.3 software was used
to obtain cycle quantification (Cq) values for relative gene
expression analysis according to FC method (Schmittgen
and Livak 2008). GAPDH was the reference gene used for
normalization (ΔCt).
Statistical analysis
The comparison among expression levels of studied genes and
patients and healthy control group were calculated using
Student’s t or Mann-Whitney U tests as appropriate.
GraphPad Prism 6.0 (GraphPad Software Inc., San Diego,
CA) was used for statistical analyses and differences were
accepted as significant for p values < 0.05.
Results
Genotyping study
We genotyped 13 SNPs located at eight inflammasome genes
in 132 SLE unrelated patients and 154 healthy controls.
Genotypes distribution was in Hardy-Weinberg equilibrium
(p > 0.05). None of the studied polymorphisms resulted differently distributed in cases and controls (Table 2).
Linkage disequilibrium analysis revealed that IL1B
SNPs rs1143643 and rs1143634 were in strong LD
(D’ = 100), whereas NLRP1 rs12150220 and rs2670660,
as well as NLRP3 rs10754558 and rs35829419 in moderate LD (D´ = 78 and D’ = 0.86, respectively). The distribution of IL1B, NLRP1, and NLRP3 haplotypes was not
significantly different between cases and controls
(Supplementary File 2).
Then we analyzed SNPs distribution according to SLE
clinical presentation: none of the studied SNPs resulted
significantly associated to clinical features or laboratory
parameters after Bonferroni correction with the exception
of NLRP3 rs10754558 which correlated with lupus nephritis (Table 3).
SLE individuals carrying rs10754558 minor G allele
were significantly more frequent (p = 0.0004) in patients
with nephritis (0.68) than in patients without kidney involvement (0.36), according to a dominant model of inheritance (C/G + G/G; OR = 3.88; 95%CI = 1.80–8.40).
This result was poorly affected by confounders variables:
age, sex, and race, (padj = 0.0005; ORadj = 4.0; 95%CI =
1.79–8.92).
Of note, some SNPs resulted differently distributed according to clinical or laboratory data (p < 0.05), however,
the analysis did not reach the statistical significance after
Bonferroni correction (Table 3). NLRP1 rs2670660 was
less frequent in SLE patients positive for anti-DNA antibodies (0.08 versus 0.29) according to a recessive model
of inheritance (G/G; padj = 0.007; ORadj = 0.22). CARD8
rs2043211 resulted more frequent in SLE patients with
cutaneous manifestations (0.15 versus 0.02) according to
a recessive model of inheritance (T/T; p adj = 0.022;
ORadj = 7.34), and less frequent in SLE with hematologic
involvement (0.27 versus 0.49) according to an overdominant model of inheritance (A/T; p a d j = 0.024;
OR adj = 0.37). IL1B rs1143643 was more frequent in
SLE patients with photosensitivity (0.67 versus 0.44) according to a dominant model of inheritance (C/T + T/T;
padj = 0.009; ORadj = 2.76). NLRC4 rs455060 was more
Table 2 Association results for case/control analysis. Inflammasome
SNPs genotypes distribution in SLE patients (SLE) and healthy controls
(HC) was analyzed by general linear model (GLM). Genotypes
distribution in patients, p value and p value adjusted for sex, age, and
race are reported. p value < 0.05 are underlined
Gene
SNP ID
Genotypes
SLE
(n = 132)
HC
(n = 154)
p
padj
NLRP1
NLRP1
NLRP3
NLRP3
NLRC4
AIM2
AIM2
CARD8
CASP1
IL1B
IL1B
IL18
rs2670660
rs12150220
rs35829419
rs10754558
rs455060
rs2276405
rs35130877
rs2043211
rs572687
rs1143643
rs1143634
rs1946519
A/A-A/G-G/G
A/A-A/T-T/T
C/C-C/A-A/A
C/C-C/G-G/G
A/A-A/G-G/G
C/C-C/T-TT
T/T-G/T-T/T
A/A-A/T-T/T
G/G-A/G-A/A
C/C-C/T-T/T
G/G-A/G-A/A
C/C-A/C-A/A
43-62-19
68-47-9
126-6-0
61/60/11
58-51-16
112-5-0
126-0-0
58-51-6
89-32-5
60-58-8
79-28-7
41-53-20
47-66-22
75-55-16
143-9-2
60/64/30
59-69-21
117-6-0
152-0-0
84-59-7
95-44-3
67-58-14
87-41-6
46-60-27
0.985
0.607
0.609
0.012
0.526
1.0
1.0
0.681
0.439
0.496
0.555
0.876
0.940
0.860
0.633
0.074
Immunogenetics (2020) 72:217–224
221
Table 3 Association results stratified for clinical and laboratory data.
Inflammasome SNPs genotypes distribution in SLE patients was
analyzed according to clinical and laboratory variables by general linear
model (GLM). p value and p value adjusted for sex, age, and race are
reported. p value < 0.05 are underlined; p value < 0.004 are indicated in
bold characters. Adjusted p values are reported within brackets
ORadj = 0.25). Similarly, CARD8 rs2043211 was less frequent
between patients with immunological alterations (0.01 versus
0.13; padj = 0.013; ORadj = 0.10) (data not shown).
Gene
SNP ID
Clinical/laboratory data
p value
Inflammasome expression analysis
NLRP1
rs2670660
Anti-DNA antibodies
NLRP3
rs10754558
Nephritis
NLRC4
rs455060
Neurological presentation
CARD8
rs2043211
Cutaneous manifestations
CARD8
rs2043211
Hematological involvement
IL1B
rs1143643
Photosensitivity
0.008
(0.007)
0.0004
(0.0005)
0.122
(0.027)
0.022
(0.022)
0.036
(0.024)
0.009
(0.008)
Then, we questioned whether an inflammasome signature
characterizes SLE patients, as reported for other autoimmune
and chronic inflammatory diseases (Shin et al. 2012a). So, we
first evaluated the modulation of inflammasome genes expression in peripheral blood–derived monocytes of SLE and HC
individuals, and then the production of IL-1β in these cells.
To investigate the hypothesis that the threshold of NLRP
inflammasome responsiveness could be affected in SLE individuals, we evaluated the inflammasome genes modulation in
monocytes from SLE versus HC. In un-stimulated resting
monocytes we observed a higher expression of IL1B (fold
change: 50.79; p = 0.0212; t = 2.525; df = 18) in SLE patients
compared to HC (Fig. 1); however, we did not observe any
significant modulation in NLRP3, NLCR4, ASC/PYCARD,
AIM2, and CASP1 expression (p > 0.05).
Within each group, LPS+ATP stimulation induced a significant increased expression of NLRP1 (fold change 5.89; p =
0.0009, t = 4.205, df = 14), CASP1 (fold change 8.68; p =
0.0028, t = 3.427, df = 19), IL1B (fold change 6.37; p =
0.0051, t = 3.162, df = 19), and AIM2 (fold change 14.57;
p = 0.0009, t = 4.207, df = 14 (Fig. 2). These data are
frequent in SLE women with neurologic presentation
(0.56 versus 0.20) according to a dominant model of inheritance (A/G + G/G; padj = 0.027; ORadj = 5.16).
No significant association with antinuclear antibodies
(ANA) was evidenced, however, a different distribution of
NLRP1 rs2670220, CARD8 rs2043211 was observed.
NLRP1 rs2670220 was less frequent between patients with
immunological alterations (0.08 versus 0.26; padj = 0.011;
100
0
L
E
P
a
ti
C
H
e
n
ts
-1 0 0
S
( F o ld c h a n g e )
200
IL 1 B r e la tiv e q u a n tific a tio n
Fig. 1 Modulation of IL1B gene
in monocytes isolated from SLE
and HC individuals in a resting
condition. A total of three out of
10 SLE individuals displayed a
higher steady-state expression of
IL1B transcripts in relation to SLE
patients and HC individuals. IL1B
relative expression (2exp-ΔCt ±
standard deviation) between SLE
individuals (n = 10) and HC (n =
10) showed statistically significant difference (p = 0.0212; t =
2.525). SLE: Systemic Lupus
Erythematosus; HC: Healthy
Controls
Immunogenetics (2020) 72:217–224
222
50
40
30
( F o ld c h a n g e )
R e la tiv e g e n e e x p r e s s io n
Fig. 2 Modulation of IL1B and
inflammasome genes in
monocytes isolated from SLE
individuals and HC individuals
with LPS+ATP stimulation.
Relative expression (2exp-ΔCt ±
standard deviation) between SLE
individuals (n = 10) and HC (n =
10) showed statistically
significant for IL1B (p = 0.0051;
t = 3.162), AIM2 (p = 0.0009; t =
4.207), CASP1 (p = 0.0028; t =
3.427), and NLRP1 (p = 0.0009;
t = 4.205). SLE: Systemic Lupus
Erythematosus; HC: Healthy
Controls
20
10
0
S
C
H
N
L
L
E
R
P
P
a
1
ti
-
e
n
H
1
P
S
C
1
P
R
L
N
C
Discussion
compatible with the NLRP1 inflammasome being responsible
for the IL-1ß production observed in monocytes.
As expected, monocytes from SLE patients produced
higher levels of IL-1ß comparing to HC in LPS
(lipopolysaccharide) stimulated monocytes as well as in
LPS+ATP stimulated cells, however, only the last condition
was statistically different (p = 5.6 exp-4) (Fig. 3). Intriguingly,
this effect appeared to be emphasized in the presence of LPS+
ATP, suggesting that the inflammasomes respond actively to
LPS and ATP associated.
Recent studies have reported the association of NLRP1,
NLRP3, and IL1B genes with SLE in terms of susceptibility
factors and/or disease severity modulation (Magitta et al.
2009; Pontillo et al. 2012; Wang et al. 2013; Wen et al.
2014). Studies concerning specific polymorphisms in
inflammasome-related genes and the relationships with SLE
susceptibility are necessary to better understand the involvement of these molecules in SLE pathology. Here, we
600
400
200
0
C
E
H
L
L
S
P
L
P
S
+
+
A
A
T
T
P
P
S
H
S
P
L
S
P
L
A
+
R
C
E
S
H
P
T
P
T
A
+
R
L
C
E
L
S
H
R
S
L
C
E
-2 0 0
R
IL -1 β ( p g /m L )
Fig. 3 Production of IL-1ß in
monocytes isolated from SLE and
HC individuals. Concentration of
IL-1ß (pg/mL) in supernatants of
monocytes from SLE individuals
(n = 10) and HC (n = 10) in
unstimulated/resting condition or
stimulated with 1 μg/mL LPS for
4 h and 1 mM ATP for 15 min.
Only LPS+ATP condition
showed statistically significant
difference between groups (p =
5.6 exp-4). SLE: Systemic Lupus
Erythematosus; HC: Healthy
Controls; R: Resting condition;
LPS: stimulated with LPS; LPS+
ATP: stimulated with LPS and
ATP
ts
C
ts
A
E
S
1
P
S
A
A
IL
1
IM
B
2
-
-
S
S
L
L
L
E
A
P
IM
a
2
ti
-
e
n
H
C
ts
n
e
ti
a
P
1
IL
E
P
a
B
ti
-
e
n
H
C
ts
-1 0
Immunogenetics (2020) 72:217–224
demonstrated the relation between inflammasome SNPs and
SLE clinical manifestation as well as a chronic expression of
some inflammasome components in monocytes from SLE
patients.
The previously observed association between NLRP1 polymorphisms and SLE (Li et al. 2015) was not replicated in our
study performed on a different Brazilian group of patients and
controls, even if the frequency of the SNPs in the populations
was similarly distributed in the Southeast of Brazil when comparing to Northeast population in Brazil. On the other hand,
the NLRP3 rs10754558 gain-of-function variant associated
with augmented risk to development of lupus nephritis, which
apparently is sustained by NLRP3 inflammasome expression
findings in experimental model using LPS stimulated monocytes from SLE patients and HC (Shin et al. 2012a; Tsai et al.
2011; Zhao et al. 2013; Zhao et al. 2015; Kahlenberg et al.
2011; Huang et al. 2017; Fu et al. 2017).
The gene expression profile of SLE patients showed an
upregulation for IL1B gene in resting condition and for
IL1B, AIM2, CASP1, and NLRP1 genes in LPS+ATP-stimulated monocytes when comparing to healthy individuals, suggesting that cells are dramatically sensitized to ligands and
respond quickly for signs of stimulation.
Immune complexes formed secondary to antibody recognition of DNA or RNA antigens have been shown to
stimulate inflammasome activation through upregulation
of TLR-dependent activation of NF-kB and subsequent
activation of the NLRP1 and NLRP3 inflammasomes,
producing high amounts of IL-1β (Shin et al. 2012b,
2013b; Levandowski et al. 2013). Thereby, the upregulation of inflammasome components is expected since in
autoimmune diseases there are abundant releases of
DAMPs upon tissue damage, which may activate the
inflammasome (Shin et al. 2013b; Kahlenberg and
Kaplan 2014b). Therefore, besides the excessive IL-1β
secretion, the deregulated activation of these complexes
may exacerbate the cell death, contributing to the inflammatory process and its maintenance in SLE disease. Our
findings suggest that SLE monocytes may be dramatically
sensitized to ligands and respond faster for signs of stimulation, contributing to the establishment of the exacerbated inflammation observed in the disease.
These differences in inflammasome genes expression between patients and healthy controls are underlined by the results observed analyzing IL-1β secretion in monocytes supernatants. In all studied conditions, the SLE monocytes secreted
higher amounts of IL-1β. The exact mechanisms responsible
for the production and secretion of IL-1β remain unclear, but
two signals are traditionally required. The first signal, in our
case LPS, induces the transcription of pro-IL-1β and
inflammasome subunits (Shin et al. 2012b, 2013b). Onesecond signal is provided by reduction of intracellular K+
generated by ATP promoting a rapid activation of caspase-1
223
and then enhancing secretion of mature IL-1β (Perregaux and
Gabel 1998; Perregaux and Gabel 1994).
In conclusion, our results indicate that the inflammasome is
an important player in lupus pathogenesis. SNPs in genes of
inflammasome components are involved in the disease and a
chronic expression of some of them was observed, indicating
a dysfunction of this protein complex in SLE disease.
Acknowledgments We would like to thank patients and control individuals for their participation.
Funding information This work was supported by the following
Brazilian funding agencies: CAPES (Coordenação de Aperfeiçoamento
de Pessoal de Nível Superior), CNPq (Conselho Nacional de
Desenvolvimento Científico e Tecnológico) and FACEPE (Fundação de
Amparo à Ciência e Tecnologia de Pernambuco).
Compliance with ethical standards
Conflict of interest statement The authors declare that they have no
conflict of interest.
References
Aksentijevich I, D Putnam C, Remmers EF et al (2007) The clinical
continuum of cryopyrinopathies: novel CIAS1 mutations in North
American patients and a new cryopyrin model. Arthritis Rheum 56:
1273–1285
Camargo JF, Correa PA, Castiblanco J et al (2004) Interleukin-1beta
polymorphisms in Colombian patients with autoimmune rheumatic
diseases. Genes Immun 5(8):609e614
Croker JA, Kimberly RP (2005) Genetics of susceptibility and severity in
systemic lupus erythematosus. Curr Opin Rheumatol 17:529–537
Davidson A, Diamond B (2001) Autoimmune diseases. N Engl J Med
345:340–350
Fu R, Guo C, Wang S et al (2017) Podocyte activation of NLRP3
inflammasomes contributes to the development of proteinuria in
lupus nephritis. Arthritis Rheumatol 69(8):1636–1646
Ghodke-Puranik Y, Niewold TB (2015) Immunogenetics of systemic
lupus erythematosus: a comprehensive review. J Autoimmun 64:
125–136
Hitomi Y, Ebisawa M, Tomikawa M et al (2009) Associations of functional NLRP3 polymorphisms with susceptibility to food-induced
anaphylaxis and aspirin-induced asthma. J Allergy Clin Immunol
124(4):779–85.e6
Hochberg MC (1997) Updating the American College of Rheumatology
revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 40(9):1725
Huang F, Zhang RY, Song L (2017) Beneficial effect of magnolol on
lupus nephritis in MRL/lpr mice by attenuating the NLRP3
inflammasome and NFκB signaling pathway: a mechanistic analysis. Mol Med Rep 16:4817–4822
Ito S, Hara Y, Kubota T (2014) CARD8 is a negative regulator for
NLRP3 inflammasome, but mutant NLRP3 in cryopyrinassociated periodic syndromes escapes the restriction. Arthritis Res
Ther 16(1):R52
Ka SM, Lin JC, Lin TJ et al (2015) Citral alleviates an accelerated and
severe lupus nephritis model by inhibiting the activation signal of
NLRP3 inflammasome and enhancing Nrf2 activation. Arthritis Res
Ther 17:331
224
Kahlenberg JM, Kaplan MJ (2014a) The inflammasome and lupus: another innate immune mechanism contributing to disease pathogenesis? Curr Opin Rheumatol 26:475–481
Kahlenberg JM, Kaplan MJ (2014b) The inflammasome and lupus: another innate immune mechanism contributing to disease pathogenesis? Curr Opin Rheumatol 26(5):475–481
Kahlenberg JM, Thacker SG, Berthier CC et al (2011) Inflammasome
activation of IL-18 results in endothelial progenitor cell dysfunction
in systemic lupus erythematosus. J Immunol 187:6143–6156
Kahlenberg JM, Carmona-Rivera C, Smith CK, Kaplan MJ (2013)
Neutrophil extracellular trap–associated protein activation of the
NLRP3 Inflammasome is enhanced in lupus macrophages. J
Immunol 190(3):1217–1226
Levandowski CB, Mailloux CM, Ferrara TM, Gowan K, Ben S, Jin Y,
McFann K, Holland PJ, Fain PR, Dinarello CA, Spritz RA (2013)
NLRP1 haplotypes associated with vitiligo and autoimmunity increase interleukin-1beta processing via the NLRP1 inflammasome.
Proc Natl Acad Sci U S A 110(8):2952–2956
Li M, Shi X, Qian T, Li J, Tian Z, Ni B, Hao F (2015) A20 overexpression
alleviates pristine-induced lupus nephritis by inhibiting the NFkappaB and NLRP3 inflammasome activation in macrophages of
mice. Int J Clin Exp Med 8(10):17430–17440
Lu A, Li H, Niu J et al (2017) Hyperactivation of the NLRP3
inflammasome in myeloid cells leads to severe organ damage in
experimental lupus. J Immunol 198(3):1119–1129
Magitta NF, Bøe Wolff AS, Johansson S, Skinningsrud B, Lie BA, Myhr
KM, Undlien DE, Joner G, Njølstad PR, Kvien TK, Førre Ø,
Knappskog PM, Husebye ES (2009) A coding polymorphism in
NALP1 confers risk for autoimmune Addison's disease and type 1
diabetes. Genes Immun 10:120–124
Man SM, Kanneganti TD (2015) Regulation of inflammasome activation.
Immunol Rev 265(1):6–21
Perregaux D, Gabel CA (1994) Interleukin-1 beta maturation and release
in response to ATP and nigericin. Evidence that potassium depletion
mediated by these agents is a necessary and common feature of their
activity. J Biol Chem 269:15195–15203
Perregaux DG, Gabel CA (1998) Human monocyte stimulus-coupled IL1beta posttranslational processing: modulation via monovalent cations. Am J Phys 275:C1538–C1547
Pontillo A, Brandao L, Guimaraes R, Segat L, Araujo J, Crovella S
(2010) Two SNPs in NLRP3 gene are involved in the predisposition
to type-1 diabetes and celiac disease in a pediatric population from
Northeast Brazil. Autoimmunity 43(8):583–589
Pontillo A, Vendramin A, Catamo E, Fabris A, Crovella S (2011) The
missense variation Q705K in CIAS1/NALP3/NLRP3 gene and an
NLRP1 haplotype are associated with celiac disease. Am J
Gastroenterol 106(3):539–544
Pontillo A, Girardelli M, Kamada AJ, Pancotto JA, Donadi EA, Crovella
S, Sandrin-Garcia P (2012) Polimorphisms in inflammasome genes
are involved in the predisposition to systemic lupus erythematosus.
Autoimmunity. 45(4):271–278
Roberts RL, Topless RK, Phipps-Green AJ, Gearry RB, Barclay ML,
Merriman TR (2010) Evidence of interaction of CARD8
rs2043211 with NALP3 rs35829419 in Crohn’s disease. Genes
Immun 11(4):351–356
Schmittgen TD, Livak KJ (2008) Analyzing real-time PCR data by the
comparative C(T) method. Nat Protoc 3(6):1101–1108
Shaw PJ, Michael F, McDermott T-DK (2011a) Inflammasomes and autoimmunity trends. Mol Med 17:57–64
Shaw PJ, McDermott MF, Kanneganti TD (2011b) Inflammasomes and
autoimmunity. Trends Mol Med 17(2):57–64
Immunogenetics (2020) 72:217–224
Shin MS, Kang Y, Lee N et al (2012a) U1-small nuclear ribonucleoprotein activates the NLRP3 inflammasome in human monocytes. J
Immunol 188:4769–4775
Shin MS, Kang Y, Lee N et al (2012b) U1-small nuclear ribonucleoprotein activates the NLRP3 inflammasome in human monocytes. J
Immunol 188:4769–4775
Shin MS, Kang Y, Lee N et al. Self double-stranded (ds)DNA induces IL1β production from human monocytes by activating NLRP3
Inflammasome in the presence of anti–dsDNA antibodies. J
Immunol 2013a
Shin MS, Kang Y, Lee N et al (2013b) Self double-stranded (ds)DNA
induces IL-1b production from human monocytes by activating
NLRP3 inflammasome in the presence of anti-dsDNA antibodies.
J Immunol 190:1407–1415
Shinkai K, McCalmont TH, Leslie KS (2008) Cryopyrin-associated periodic syndromes and auto inflammation. Clin Exp Dermatol 33:1–9
Tsai PY, Ka SM, Chang JM, Chen HC, Shui HA, Li CY, Hua KF, Chang
WL, Huang JJ, Yang SS, Chen A (2011) Epigallocatechin-3-gallate
prevents lupus nephritis development in mice via enhancing the
Nrf2 antioxidant pathway and inhibiting NLRP3 inflammasome activation. Free Radic Biol Med 51:744–754
Tsao BP (2003) The genetics of human systemic lupus erythematosus.
Trends Immunol 24:595–602
Tsokos GC, Gordon C, Smolen JS (2007) Systemic lupus erythematosus:
a companion to rheumatology, 1st edn. Mosby-Elsevier,
Philadelphia
Wang B, Zhu JM, Fan YG, Feng CC, Chen GM, Chen H, Pan HF, Ye DQ
(2013) The association of IL1alpha and IL1beta polymorphisms
with susceptibility to systemic lupus erythematosus: a meta-analysis. Gene 527(1):95–101
Wen D, Liu J, Du X, Dong JZ, Ma CS (2014) Association of interleukin18 (−137G/C) polymorphism with rheumatoid arthritis and systemic
lupus erythematosus: a meta-analysis. Int Rev Immunol 33:34–44
Yang C-A, Chiang B-L (2015) Inflammasomes and human autoimmunity: a comprehensive review. J Autoimmun 61:1–8
Yang Q, Yu C, Yang Z, Wei Q, Mu K, Zhang Y, Zhao W, Wang X, Huai
W, Han L (2014) Deregulated NLRP3 and NLRP1 inflammasomes
and their correlations with disease activity in systemic lupus erythematosus. J Rheumatol 41:444–452
Yang CA, Huang ST, Chiang BL (2015a) Sex-dependent differential
activation of NLRP3 and AIM2 inflammasomes in SLE macrophages. Rheumatology 54(2):324–331
Yang CA, Huang ST, Chiang BL (2015b) Sex-dependent differential
activation of NLRP3 and AIM2 inflammasomes in SLE macrophages. Rheumatology 54(2):324–331
Zhang H, Fu R, Guo C et al (2016) Anti-dsDNA antibodies bind to TLR4
and activate NLRP3 inflammasome in lupus monocytes/macrophages. J Transl Med 14(1):15
Zhao J, Zhang H, Huang Y, Wang H, Wang S, Zhao C, Liang Y, Yang N
(2013) Bay11-7082 attenuates murine lupus nephritis via inhibiting
NLRP3 inflammasome and NF-kB activation. Int
Immunopharmacol 17:116–122
Zhao J, Wang H, Huang Y et al (2015) Lupus nephritis: glycogen synthase kinase 3β promotes renal damage through activation of
NLRP3 inflammasome in lupus-prone mice. Arthritis Rheumatol
67(4):1036–1044
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Autoimmunity
ISSN: 0891-6934 (Print) 1607-842X (Online) Journal homepage: https://www.tandfonline.com/loi/iaut20
T-cell specific upregulation of Sema4A as risk
factor for autoimmunity in systemic lupus
erythematosus and rheumatoid arthritis
Catarina Addobbati Jordão Cavalcanti, Vanessa Germoglio, Jaqueline de
Azevêdo Silva, Nadine Glesse, Priscila Vianna, Giovana Cechim, Odirlei Andre
Monticielo, Ricardo Machado Xavier, João Carlos Tavares Brenol, Claiton
Viegas Brenol, Thiago Sotero Fragoso, Alexandre Domingues Barbosa,
Ângela Luiza Branco Pinto Duarte, Renê Donizeti Ribeiro Oliveira, Paulo
Louzada-Júnior, Eduardo Antônio Donadi, José Artur Bogo Chies, Sergio
Crovella & Paula Sandrin-Garcia
To cite this article: Catarina Addobbati Jordão Cavalcanti, Vanessa Germoglio, Jaqueline de
Azevêdo Silva, Nadine Glesse, Priscila Vianna, Giovana Cechim, Odirlei Andre Monticielo,
Ricardo Machado Xavier, João Carlos Tavares Brenol, Claiton Viegas Brenol, Thiago Sotero
Fragoso, Alexandre Domingues Barbosa, Ângela Luiza Branco Pinto Duarte, Renê Donizeti
Ribeiro Oliveira, Paulo Louzada-Júnior, Eduardo Antônio Donadi, José Artur Bogo Chies, Sergio
Crovella & Paula Sandrin-Garcia (2020) T-cell specific upregulation of Sema4A as risk factor for
autoimmunity in systemic lupus erythematosus and rheumatoid arthritis, Autoimmunity, 53:2,
65-70, DOI: 10.1080/08916934.2019.1704273
To link to this article: https://doi.org/10.1080/08916934.2019.1704273
View supplementary material
Published online: 26 Dec 2019.
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https://www.tandfonline.com/action/journalInformation?journalCode=iaut20
AUTOIMMUNITY
2020, VOL. 53, NO. 2, 65–70
https://doi.org/10.1080/08916934.2019.1704273
ORIGINAL ARTICLE
T-cell specific upregulation of Sema4A as risk factor for autoimmunity in
systemic lupus erythematosus and rheumatoid arthritis
^do Silvaa,b, Nadine Glessec,
Catarina Addobbati Jord~ao Cavalcantia,b, Vanessa Germoglioa, Jaqueline de Azeve
c
c
d
Priscila Vianna , Giovana Cechim , Odirlei Andre Monticielo , Ricardo Machado Xavierd,
Jo~ao Carlos Tavares Brenold, Claiton Viegas Brenold, Thiago Sotero Fragosoe, Alexandre Domingues Barbosaf,
^
niorg,
Angela
Luiza Branco Pinto Duartef, Ren^e Donizeti Ribeiro Oliveirag, Paulo Louzada-Ju
g
c
a,b,h
^nio Donadi , Jose Artur Bogo Chies , Sergio Crovella
Eduardo Anto
and Paula Sandrin-Garciaa,b
a
Department of Genetics, Federal University of Pernambuco, Recife, Brazil; bLaboratory of Immunopathology Keizo Asami (LIKA), Federal
University of Pernambuco, Recife, Brazil; cDepartment of Genetics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil; dDivision of
Rheumatology, Clinical Hospital, Federal University of Rio Grande do Sul, Porto Alegre, Brazil; eRheumatology Service, Clinical Hospital,
Federal University of Alagoas, Maceio, Brazil; fRheumatology Division, Clinical Hospital, Federal University of Pernambuco, Recife, Brazil;
g
Department of Medicine, Clinical Immunology Division, Medicine Faculty of Ribeir~ao Preto, University of S~ao Paulo, Ribeir~ao Preto, Brazil;
h
Institute for Maternal, Child Health “Burlo Garofolo,” Trieste, Italy
ABSTRACT
The aim of the present study was to evaluate the impact of SEMA4A genetic variants on expression of
sema4A protein and its relation to autoimmunity development in Systemic Lupus Erythematosus and
Rheumatoid Arthritis patients. A total of 541 SLE patients, 390 RA patients and 607 healthy individuals
were genotyped. We also assessed SEMA4A mRNA expression from whole blood cells and the in vitro
protein production from resting and activated T lymphocytes as well as mature dendritic cells from
healthy individuals stratified according to their genotypes for SLE/RA associated SEMA4A variants. Our
results showed that T/T genotype for rs3738581 SNP is associated with both RA and SLE development
(p ¼ .000053, OR ¼ 2.35; p ¼ .0019, OR ¼ 2.07, respectively; statistical power ¼ 100%) and also to an
increased in vitro sema4A production in active T lymphocytes. Our findings are indicative of a T cellspecific upregulation of sema4A in the presence of T/T genotype, being a risk factor for SLE and RA.
1. Introduction
Semaphorins, first described as guidance factors that assist
axon pathfinding during neuronal development [1], have
been shown to play important roles in heart morphogenesis
[2,3], vascular growth [2,3], tumour progression [4,5], and
immunoregulation [6]. This group of proteins has been divided into different subclasses I to VII according to their
structure, being the classes III–VII expressed in vertebrates [7].
The Semaphorin 4 A (sema4A) is highly expressed on the
surface of mature dendritic cells (DC) and active T lymphocytes, but poorly expressed on B and resting T cells membrane [8]. DC-derived sema4A showed to be essential for T
cell priming as well as T-cell derived sema4A for T helper
type 1 (Th1) and 17 (Th17) differentiation [9].
Sandrin-Garcia et al. [10] evaluated the expression profile
of 4500 genes in patients with active and inactive systemic
lupus erythematosus (SLE): a total of 156 genes were differentially expressed between patients and healthy controls.
Within them, SEMA4A gene was upregulated (þ32-fold
change) in active SLE patients. Considering the imbalance
of T helper cell subsets in SLE pathogenesis and the
Received 26 July 2019
Revised 10 December 2019
Accepted 10 December 2019
KEYWORDS
SEMA4A; systemic lupus
erythematosus; rheumatoid
arthritis; polymorphism;
T cells
involvement of sema4A on the immune cell regulation [11],
we considered the SEMA4A gene as a potential target gene
in susceptibility to SLE and autoimmunity development.
In this study, we have investigated the hypothesis that
genetic variants in SEMA4A result in an altered expression
of sema4A and are involved in autoimmunity development.
Therefore, we investigated the impact of SEMA4A genetic
variants in SLE and rheumatoid arthritis (RA) development
in Brazilian populations. Following, to functionally understand the impact of the associated genetic variants, we
assessed SEMA4A mRNA expression in whole blood cells
and the in vitro protein production from resting and activated T lymphocytes as well as mature DC cells from
healthy individuals stratified according to their genotypes
for SLE and RA associated polymorphism.
2. Material and methods
2.1. SEMA4A genotyping study
2.1.1. Subjects
For this study, we enrolled patients and controls from three
Brazilian cohorts (a Northeastern cohort from state of
CONTACT Catarina Addobbati Jord~ao Cavalcanti
catarinaaddobbati@hotmail.com
50670-901, Brazil
Supplemental data for this article can be accessed here.
ß 2019 Informa UK Limited, trading as Taylor & Francis Group
ARTICLE HISTORY
Av. Prof. Moraes Rego, 1235—Cidade Universitaria, Recife—PE
66
C. A. J. CAVALCANTI ET AL.
Pernambuco, a Southeastern cohort from S~ao Paulo and a
South-Brazilian cohort from Rio Grande do Sul), comprising
541 SLE patients, 390 RA patients and 607 healthy controls.
The northeastern sample comprised 123 SLE patients, 118
RA patients and 158 healthy individuals from the state of
Pernambuco (Northeast of Brazil). The Southeastern sample
comprised 158 SLE patients, 89 RA patients and 189 healthy
controls from state of S~ao Paulo (Southeast of Brazil) and
the Southern sample comprised 260 SLE patients, 183 RA
patients and 260 healthy controls from state of Rio Grande
do Sul (South of Brazil). Patients from Northeast of Brazil
were under care of the Division of Rheumatology of Clinical
Hospital from Federal University of Pernambuco, whereas
patients from Southeast and South’s Brazil were recruited
from Division of Clinical Immunology of University
Hospital of the School of Medicine of Ribeir~ao Preto,
University of S~ao Paulo and Division of Rheumatology of
Clinical Hospital from Federal University of Rio Grande do
Sul, respectively. All patients were diagnosed according to
the American College of Rheumatology (ACR) criteria for
the classification of SLE [12] and RA [13]. As control group,
we enrolled healthy blood donors without previous family
history of autoimmune diseases, as reported in an appropriate questionnaire. Clinical and laboratory data from all
patients were collected from medical records and are shown
Table 1. Controls and patients’ characteristics.
Northeastern Southeastern
Southern
Controls (n ¼ 607)
n ¼ 158
n ¼ 189
n ¼ 260
Females
86.4%
51.6%
35.8%
Males
13.6%
48.4%
64.2%
40.8 ± 14.65
37.4 ± 11.31
42.1 ± 8.9
Agea
Rheumatoid arthritis (n ¼ 390)
n ¼ 118
n ¼ 89
n ¼ 183
Females
95.3%
92.2%
81.5%
Males
4.7%
7.8%
18.5%
51.2 ± 11.6
55.7 ± 10.8
64 ± 12.7
Agea
Age at diagnosisa
42.1 ± 11.7
44.8 ± 13.2
46 ± 13.7
Positive rheumatoid factor
71.2%
73.4%
89.7%
Bone erosions
75.8%
89.9%
86.1%
4.53 (0–7.84) 5.59 (2.87–7.89) 3.88 (0.84–7.45)
DAS28b
HAQb
1.42 (0–3)
NA
1.22 (0–3)
Systemic lupus
n ¼ 123
n ¼ 158
n ¼ 260
erythematosus (n ¼ 541)
Females
99%
94.4%
90.8%
Males
1%
5.6%
9.2%
a
37.5 ± 10.4
39.8 ± 11.9
49.7 ± 15.1
Age
a
31.2 ± 7.7
NA
33 ± 14
Age at diagnosis
Malar rash
58.9%
55%
56.7%
Discoid rash
17.8%
16%
13.5%
Photosensitivity
67.3%
29.4%
79.3%
Ulcers
19.6%
NA
36.5%
Arthritis
72%
42.6%
83.7%
Serositis
22.4%
25.2%
31.3%
Nephritis
50.5%
55.9%
39.9%
Neurological alterations
7.5%
20.3%
10.6%
Hematological alterations
68.2%
61.8%
70.7%
Positive ANA
93.5%
80.4%
99.5%
Anti-DNA
24.4%
19.6%
46.6%
Anti-Sm
8.42%
NA
17.8%
Antiphospholipid syndrome
5.6%
21%
6.3%
3.6 (0-16)
NA
3 (0-37)
SLEDAIb
b
0.9 (0-5)
NA
1 (0-7)
SLICC
a
Mean ± SD.
Mean (minimum–maximum).
DAS28: disease activity score in 28 joints; HAQ: health assessment questionnaire; ANA: antinuclear antibody; SLEDAI: systemic lupus erythematosus disease
activity index; SLICC: systemic lupus international collaborating clinics; NA:
not available.
b
in Table 1. All the participants provided a written informed
consent according to the Declaration of Helsinki and
approved by the local Research Ethics Committee
(Southeast: CAAE 34636013.9.3001.5440 (SLE and RA),
Northeast: CAAE 03065312.3.0000.5208 (SLE and RA) and
South: CAAE 01731012.0.0000.5327 (SLE) and HCPA 08366 (RA)).
2.1.2. DNA isolation
Genomic DNA was isolated from peripheral blood samples,
using DNA Wizard Genomic DNA Purification Kit
(Promega, Madison, WI) according to the standard protocol
from the manufacturer or using a salting out method [14].
2.1.3. SNPs selection and gene genotyping
Polymorphisms were selected crossing and merging data
from SNP Browser software 4.0 (Applied Biosystems, Foster
City, CA) and HapMap database (hapmap.ncbi.nlm.nih.gov)
in order to cover most of the SEMA4 gene (1q22). The
selected tag SNPs - rs3738581 (intronic region, near 30 UTR),
rs7695 (30 UTR), rs12401573 (exonic region) and rs3738582
(intronic region)—presented at least 10% minimum allele
frequency (MAF) (Figure 1).
Genotyping was performed with fluorogenic allele specific probes (Taqman Probes, Applied Biosystems, Foster
City, CA), using an ABI7500 sequence detection system
(Applied Biosystems, Foster City, CA). Initially, the four tag
SNPs were genotyped in SLE patients and controls and then
after analysis, the SLE-associated SNP (rs3738581) was genotyped in RA patients.
2.1.4. Statistical analysis
Genotype frequencies were compared for Hardy–Weinberg
(HW) expectations using Genotype Transposer [15]. In a
preliminary analysis, the allele and genotype frequencies
from healthy controls and RA and SLE patients were compared using chi-square test. Binary logistic regression was
used to evaluate the association between the polymorphisms
and SLE and RA, adjusting for origin of sample and sex.
Bonferroni’s correction for multiple comparisons was
applied when p-value was significant (N ¼ 4). The significance level was set at a ¼ .05 (two-tailed). All statistical analyses were performed with SPSS 15.0 (SPSS, Inc., Chicago,
IL). The eventual presence of linkage disequilibrium
between SEMA4A polymorphisms and the association of
haplotypes with SLE susceptibility were evaluated by using
the online tool SNPStats [16]. The power of the analyses
was verified using GPower software 3.1.9.2 (Kiel
University, Germany).
2.2. SEMA4 mRNA and protein expression assays
2.2.1. Subjects
We assessed the SEMA4A mRNA expression levels in whole
blood cells and the sema4A protein levels from resting and
stimulated T cell as well as mature DCs of 28 healthy
AUTOIMMUNITY
67
Figure 1. SEMA4 gene (1q22) structure and studied Tag SNPs; rs3738581 (intron, near 30 UTR), rs7695 (30 UTR), rs12401573 (exon 15) and rs3738582 (intron, near
50 UTR).
individuals stratified according to their genotypes for the
SLE/RA associated SEMA4A polymorphism.
2.2.2. Whole blood RNA extraction and cDNA synthesis
Peripheral blood samples were collected and immediately
used for RNA isolation, which was performed using the
Qiagen Whole Blood RNAse kit, following the manufacturer’s instructions. The samples were stored at –80 C until
used and RNA integrity analysis was performed by gel electrophoresis and quantification by Nanodrop 2000 (Thermo
Scientific USA).
For cDNA synthesis, we followed the SuperScript III
First-Strand Synthesis System for RT-PCR kit (Invitrogen,
USA) standard protocol, employing for each sample a standard RNA input of 500 ng for each reaction of 20 lL of
cDNA. Oligo(dT) was used as primers in all samples. cDNA
was stored at –20 C until qPCR assays.
2.2.3. mRNA expression analysis
Gene expression assays for SEMA4A cDNA was performed
using the ABI 7500 SDS platform (Applied Biosystems,
USA).
Glyceraldehyde-3-phosphate
dehydrogenase
(GAPDH) was the reference gene used for normalization
(SEMA4A: Hs00223617_m1 and GAPDH: Hs02758991_g1).
Gene expression analyses were performed with technical
triplicates. The calculation of 2–DCt was performed for each
subject [17]. Student’s t-test was applied to compare the
quantitative expression between different genotypes.
2.2.4. Cells culture and immunophenotype analysis
Peripheral blood (10 mL) was collected in EDTA tube by
venipuncture and isolated by density gradient using FicollPaque (Sigma-Aldrich, USA). After centrifugation, the
PBMCs ring was collected and washed twice in 1 PBS
saline. The cell pellet was suspended in 1 mL of RPMI-1640
(Sigma-Aldrich, St. Louis, MO) supplemented with 10% of
FBS (Fetal Bovine Serum, Sigma-Aldrich). Cells were
counted by means of microscopy in a Neubauer Chamber
and the viability always exceeded 95%, as judged from their
ability to exclude Trypan Blue (Sigma-Aldrich, St. Louis,
MO). PBMCs were culture on 96-well plate “U bottom” at a
concentration of the 200,000 cells/well for subsequent staining with antibodies.
T lymphocytes were cultured in nonstimulated and
stimulated conditions. For stimulation, T cells were cultured
with phytohemaglutinin 1%. Following 18 h, cells were harvested and analyzed by flow cytometry.
DCs were generated from monocytes isolated by adherence after 7 days of culture. The following cytokines were
used: 50 ng/mL of human granulocyte-macrophage colony
stimulating factor (GM-CSF) and recombinant human IL-4
(Sigma-Aldrich, USA) for 5 days. On day 5, the DCs were
maturated through 500 ng/ml of lipopolysaccharide (LPS;
Sigma-Aldrich). Following two days, DCs were harvested
and analyzed by light microscopy and by flow cytometry.
The phenotype of the cultured DC was confirmed by the
expression of HLA-DR, CD11c, CD80 and CD86, and low
levels of CD14 [18,19].
Cells were incubated with conjugated mAb or isotype
controls for 30 min protected from light at room temperature. The monoclonal antibodies used were: SEMA4A-FITC,
CD80—PE-CY7, CD86—APC, CD14—Texas Red, CD11c—
PE and HLA-DR—PerCP-Cy5.5 for DCs; CD3—APCH7
and CD4—PerCP-Cy5.5 for resting T cells; and CD3, CD4
and CD25—FITC for stimulated T lymphocytes. All purchased from BD Biosciences, San Diego, CA. The stained
cells were washed twice with PBS, fixed with 2% paraformaldehyde in PBS. Cells were kept at 4 C and protected
from light until analysis by flow cytometry. The frequency
of positive cells was calculated from lymphocyte gates from
PBMCs and 10,000 events were acquired by size (FSC) and
granularity (SSC) using the BD FACSAriaTM III cell-sorter
flow cytometer (BD Biosciences, San Diego, CA). For DC,
at least 20,000 events were acquired and analyzed.
Compensation was made with non-stained and single
68
C. A. J. CAVALCANTI ET AL.
Table 2. SEMA4A rs3738581 SNP allele and genotype frequencies in controls and SLE and RA patients.
SNPs
rs3738581
C
T
C/C
C/T
T/T
HWE
Controls
N (%)
SLE
N (%)
780 (64.3)
434 (35.7)
252 (41.5)
276 (45.5)
79 (13)
0.80
596 (55.1)
486 (44.9)
156 (28.8)
284 (52.5)
101 (18.7)
0.16
p
.000009
.0001a
.0007b
OR
OR ¼ 1
OR ¼ 1.47
OR ¼ 1
OR ¼ 1.66
OR ¼ 2.06
95% CI
1.23–1.73
1.27–2.17
1.42–2.99
RA
N (%)
434 (55.6)
346 (44.4)
121 (31.1)
192 (49.2)
77 (19.7)
0.95
p
.00014
.011c
.0003d
OR
OR ¼ 1
OR ¼ 1.43
OR ¼ 1
OR ¼ 1.45
OR ¼ 2.03
95% CI
1.19–1.72
1.1–1.95
1.36–3.03
Binary logistic regression, adjusted by gender and origin of sample: p ¼ .00018, OR ¼ 1.76, 95% CI ¼ 1.31–2.36; p-value after Bonferroni correction ¼ .0007.
Binary logistic regression, adjusted by gender and origin of sample: p ¼ .000053, OR ¼ 2.35, 95% CI ¼ 1.55–3.55; p-value after Bonferroni correction ¼ .0002.
c
Binary logistic regression, adjusted by gender and origin of sample: p ¼ .019, OR ¼ 1.49, 95% CI ¼ 1.1–2.09; p-value after Bonferroni correction ¼ .076.
d
Binary logistic regression, adjusted by gender and origin of sample: p ¼ .0019, OR ¼ 2.07, 95% CI ¼ 1.31–3.27; p-value after Bonferroni correction ¼ .0076.
SLE: systemic lupus erythematosus; RA: rheumatoid arthritis; p: chi-square test p-value; OR: odds ratio; CI: confidence interval; HWE: Hardy–Weinberg equilibrium.
a
b
Figure 2. SEMA4A gene expression in 28 healthy controls stratified by genotypes (T/T genotype: 7 individuals; C/T: 14; C/C:7). The results were normalized
to GAPDH expression. The calculation of 2–DCt was performed for each subject.
Student’s t-test was applied to compare the quantitative expression between
different genotypes.
stained controls. All analyzes were performed by FlowJo
7.5.5 (Tree Star Corporation, Ashland, OR).
All variables were tested for normality of distribution by
means with the Kolmogorov-Smirnov test. Statistical analysis of data was performed using One-way ANOVA.
Bonferroni’s correction was applied for multiple comparisons among individuals stratified by genotypes. Data are
presented as mean fluorescence intensity (MFI) of SEMA4A.
The significance level was set at a ¼ 0.05 (two-tailed).
Analyses of data were performed through the SPSS 15.0
Software Inc. (Chicago, IL).
3. Results
3.1. Genotyping study
Genotype distributions were in Hardy–Weinberg equilibrium for the assessed SNPs with exception of SEMA4A
rs12401573 in SLE group (p ¼ .04) (Supplementary Table 1).
Considering patients and controls independently of their
geographical origin, we found a significant association of
SEMA4A rs3738581 SNP [C > T] with RA and SLE susceptibility with a statistical power ¼ 1.0 for both groups. The T
allele and C/T and T/T genotypes were significantly more
frequent in SLE (44.9%, p value ¼ .000009, OR ¼ 1.47, 95%
CI ¼ 1.23–1.73; 52.5%, p-value ¼ .0001, OR ¼ 1.66, 95% CI
¼ 1.27–2.17; and 18.7%, p-value ¼ .0007, OR ¼ 2.06, 95%
CI ¼ 1.42–2.99, respectively) and RA patients (44.4%, p-value ¼ .00014, OR ¼ 1.43, 95% CI ¼ 1.19–1.72; 49.2%, p-value ¼ .011, OR ¼ 1.45, 95% CI ¼ 1.1–1.95; and 19.7%, pvalue ¼ .0003, OR ¼ 2.03, 95% CI ¼ 1.36–3.03, respectively)
than in controls (35.7%, 45.5%, and 13%, respectively).
When we performed a binary logistic regression adjusting
for gender and geographical origin of sample, the association between C/T and T/T genotypes and susceptibility to
SLE (p-value ¼ .00018, OR ¼ 1.76, 95% CI ¼ 1.31–2.36; pvalue ¼ .000053, OR ¼ 2.35, 95% CI ¼ 1.55–3.55, respectively) and RA (p-value ¼ .019, OR ¼ 1.49, 95% CI ¼
1.1–2.09; p-value ¼ .0019, OR ¼ 2.07, 95% CI ¼ 1.31–3.27,
respectively) remained statistically significant. After applying
Bonferroni’s correction, the associations still remained statistically significant (pBonf < .05) with exception of C/T
genotype for RA group (pBonf ¼ .076). SEMA4A rs3738581
genotype and allele frequencies are shown in Table 2.
When we assessed the influence of SEMA4A polymorphisms on SLE and RA clinical and laboratorial features, the
association between T/C and C/C genotypes for rs12401573
SNP [T > C] and hematological alterations in SLE patients
was observed (p-value ¼ .007, OR ¼ 2.01, 95% CI ¼
1.21–3.32; p-value ¼ .018, OR ¼ 2.09, 95% CI ¼ 1.14–3.84,
respectively) (Supplementary Table 2). Linkage disequilibrium was not observed for the studied SEMA4A
polymorphisms.
3.2. SEMA4A expression analyses
To determine whether SLE and RA associated SEMA4A
rs3738581 SNP differentially affects gene expression, we
compared SEMA4A mRNA levels of C/C healthy individuals
with heterozygous (C/T) and homozygous (T/T) individuals
for the risk allele in whole blood cells. Our findings indicated C/T and T/T genotypes do not impact SEMA4A gene
regulation (p-value > .05) (Figure 2). To explore if any
genotype-associated down or upregulation of SEMA4A
could be cell type or stimulus dependent, we evaluated the
in vitro sema4A expression in mature DCs as well as resting
and active T lymphocytes. We found a significantly
increased expression of sema4A on the surface of stimulated
T cells (CD3þCD4þCD25þ) from individuals homozygous
for the risk allele when compared to the expression of C/C
AUTOIMMUNITY
Figure 3. Sema4A production in 28 healthy controls stratified by genotypes (T/
T genotype: 7 individuals; C/T: 14; C/C:7). Data are presented as mean fluorescence intensity (MFI) of sema4A. p-value < .05.
T cells (MFI 682.85 ± 25.03 vs. MFI 217.14 ± 14.05 respectively, p-value ¼ .04) (Figure 3).
4. Discussion
The development of SLE and RA autoimmunity is related to
both environmental and genetic factors, the latter involving
immune response–related genes variants and differential
expression [20,21]. In this study we evidenced for the first
time an increased sema4A expression in active T cells
related to the SLE and RA-associated polymorphism
rs3738581 [C > T]. The SEMA4A rs3738581 T allele seems
to confer a similar augmented risk for the development of
both RA and SLE when in homozygous condition (OR ¼
2.07 and 2.35, respectively) with a power of 100%. When
considering SEMA4A SNPs in SLE clinical and laboratorial
manifestations we observed the association between T/C
and C/C genotypes for rs12401573 SNP [T > C] and hematological alterations.
The polymorphism rs3738581 is located within an
intronic region near 30 UTR of SEMA4A gene, which could
interfere with the binding of miRNAs. In whole blood cells,
we did not observe statistically significant changes in
SEMA4A mRNA expression in heterozygous or homozygous
healthy individuals for rs3738581 risk allele. When we evaluated the in vitro sema4A production in mature DCs and T
cells, in nonstimulated and stimulated conditions, to further
explore if any genotype-associated down or upregulation of
SEMA4A could be cell type or stimulus dependent, an
increased sema4A production was observed in active T lymphocytes of risk allele homozygous subjects.
Our results are indicative of a T cell-specific upregulation
of sema4A after activation in the presence of T/T genotype.
The risk allele in homozygous individuals may have an
impact on amplified sema4A production in T cells, being a
susceptibility factor for the autoimmunity development. The
specific mechanism by which the sema4A manifests greater
production due to T/T genotype remains unknown.
Studies on the roles of sema4A have observed this molecule as critical immune regulators in Th1 and Th17 differentiation [9]. SLE and RA are inherited as complex traits, in
69
which no single gene variant is sufficient to cause disease.
Due to the moderate value of OR, the high risk SEMA4A
allele is not sufficient by itself to result in disease development. Rather, increased sema4A levels may contribute to
the pathogenesis of autoimmunity, perhaps by functioning
as an adjuvant, exacerbating Th1 and Th17 response.
It is important to point out that increased levels of
sema4A have already been observed in the synovial tissue
and serum of RA patients compared to osteoarthritis.
Further, increased sema4A levels were also correlated with
RA activity [22]. Moreover, as before mentioned, SandrinGarcia et al. [10] observed the upregulation of SEMA4A
gene in active SLE patients. Wang et al. [22] observed the
in vitro upregulated expression of matrix metalloproteinases
and proinflammatory cytokines interleukin-1b and tumour
necrosis factor (TNF)-a through the treatment with human
recombinant sema4A. High levels of metalloproteinases as
well as the pro-inflammatory cytokines IL-1b and TNF-a
have been involved in SLE and RA pathogenesis, revealing
an important role in autoimmunity and inflammation
[23–27]. Sema4A is also considered a player in experimental
autoimmune encephalomyelitis as increased expression of
sema4A was shown to cause neuroinflammation that leads
to demyelination [28]. These findings together with our
results indicate a relationship between altered expression of
sema4A and the beginning of autoimmunity, which may
culminate in the development of autoimmune diseases such
as SLE and RA.
5. Conclusion
In conclusion, our results support a role of SEMA4A gene
in the susceptibility to RA and SLE. To the best of our
knowledge, this is the first association study between
SEMA4A SNPs and RA and SLE. We also showed an impact
of rs3738581 SNP on increased sema4A expression levels
and their potential correlation with SLE and RA development and worsening. Further studies in different cohorts
and mechanistic studies are required to confirm and fully
understand the role of SEMA4A in autoimmunity
development.
Disclosure statement
The authors have declared no conflicts of interest.
Funding
This work was supported by the following Brazilian funding agencies:
CAPES (Coordenaç~ao de Aperfeiçoamento de Pessoal de Nıvel
Superior), CNPq (Conselho Nacional de Desenvolvimento Cientıfico e
Tecnol
ogico), FAPESP (Fundaç~ao de Amparo a Pesquisa do Estado de
S~ao Paulo), FAPERGS (Fundaç~ao de Amparo a Pesquisa do Estado do
Rio Grande do Sul), FACEPE (Fundaç~ao de Amparo a Ci^encia e
Tecnologia de Pernambuco), and FIPE/HCPA (Fundo de Incentivo a
Pesquisa e Eventos do Hospital de Clınicas de Porto Alegre).
70
C. A. J. CAVALCANTI ET AL.
References
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
Kolodkin AL, Matthes DJ, Goodman CS. The semaphorin
genes encode a family of transmembrane and secreted growth
cone guidance molecules. Cell. 1993;75(7):1389–1399.
Gitler AD, Lu MM, Epstein JA. PlexinD1 and semaphorin signaling are required in endothelial cells for cardiovascular development. Dev Cell. 2004;7(1):107–116.
Gu C, Rodriguez ER, Reimert DV, et al. Neuropilin-1 conveys
semaphorin and VEGF signaling during neural and cardiovascular development. Dev Cell. 2003;5(1):45–57.
Tomizawa Y, Sekido Y, Kondo M, et al. Inhibition of lung cancer cell growth and induction of apoptosis after reexpression of
3p21.3 candidate tumor suppressor gene SEMA3B. Proc Natl
Acad Sci USA. 2001;98(24):13954–13959.
Tse C, Xiang RH, Bracht T, et al. Human Semaphorin 3B
(SEMA3B) located at chromosome 3p21.3 suppresses tumor
formation in an adenocarcinoma cell line. Cancer Res. 2002;
62(2):542–546.
Kikutani H, Suzuki K, Kumanogoh A. Immune semaphorins:
increasing members and their diverse roles. Adv Immunol.
2007;93:121–143.
Eichmann A, Makinen T, Alitalo K. Neural guidance molecules
regulate vascular remodeling and vessel navigation. Genes Dev.
2005;19(9):1013–1021.
Kumanogoh A, Marukawa S, Suzuki K, et al. Class IV semaphorin Sema4A enhances T-cell activation and interacts with
Tim-2. Nature. 2002;419(6907):629–633.
Kumanogoh A, Shikina T, Suzuki K, et al. Nonredundant roles
of Sema4A in the immune system: defective T cell priming and
Th1/Th2 regulation in Sema4A-deficient mice. Immunity. 2005;
22(3):305–316.
Sandrin-Garcia P, Junta CM, Fachin AL, et al. Shared and
unique gene expression in systemic lupus erythematosus
depending on disease activity. Ann NY Acad Sci. 2009;1173(1):
493–500.
Kleczynska W, Jakiela B, Plutecka H, et al. Imbalance between
Th17 and regulatory T-cells in systemic lupus erythematosus.
Folia Histochem Cytobiol. 2012;49(4):646–653.
Hochberg MC. Updating the American College of
Rheumatology revised criteria for the classification of systemic
lupus erythematosus. Arthritis Rheum. 1997; 40 (9):1725.
Kay J, Upchurch KS. ACR/EULAR 2010 rheumatoid arthritis
classification criteria. Rheumatology. 2012;6(Suppl):vi5–vi9.
Lahiri DK, Numberger JI. A rapid non-enzymatic method for
the preparation of HMW DNA from blood for RFLP studies.
Nucl Acids Res. 1991;19(19):5444.
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
Cox DG, Canzian F. Genotype transposer: automated genotype
manipulation
for
linkage
disequilibrium
analysis.
Bioinformatics. 2001;17(8):738–739.
Sole X, Guino E, Valls J, et al. SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006;22:1928–1929.
Livak KJ, Schmittgen TD. Analysis of relative gene expression
data using real-time quantitative PCR and the 2(-Delta
DeltaC(T)) method. Methods. 2001;25(4):402–408.
Sallusto F, Lanzavecchia A. Efficient presentation of soluble
antigen by cultured human dendritic cells is maintained by
granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha. J
Exp Med. 1994;179(4):1109–1118.
Romani N, Gruner S, Brang D. Proliferating dendritic cell progenitors in human blood. J Exp Med. 1994;180(1):83–93.
De Azev^edo Silva J, Addobbati C, Sandrin-Garcia P, et al.
Systemic lupus erythematosus: old and new susceptibility genes
versus clinical manifestations. Curr Genomics. 2014;15(1):
52–65.
Suzuki A, Yamamoto K. From genetics to functional insights
into rheumatoid arthritis. Clin Exp Rheumatol. 2015;33(4 Suppl
92):S40–S43.
Wang L, Song G, Zheng Y, et al. Expression of Semaphorin 4A
and its potential role in rheumatoid arthritis. Arthritis Res
Ther. 2015;17(1):227.
Joosten LA, Helsen MM, Saxne T, et al. IL-1 alpha beta blockade prevents cartilage and bone destruction in murine type II
collagen-induced arthritis, whereas TNF-alpha blockade only
ameliorates joint inflammation. J Immunol. 1999;163:
5049–5055.
Gheita TA, Abdel Rehim DM, Kenawy SA, et al. Clinical significance of matrix metalloproteinase-3 in systemic lupus erythematosus patients: a potential biomarker for disease activity
and damage. Acta Reumatol Port. 2015;40(2):145–149.
Klein T, Bischoff R. Physiology and pathophysiology of matrix
metalloproteases. Amino Acids. 2011;41(2):271–290.
Postal M, Lapa AT, Sinicato NA, et al. Depressive symptoms
are associated with tumor necrosis factor alpha in systemic
lupus erythematosus. J Neuroinflammation. 2016;13(1):5.
Moelants EA, Mortier A, Van Damme J, et al. Regulation of
TNF-a with a focus on rheumatoid arthritis. Immunol Cell
Biol. 2013;91(6):393–401.
Chakravarti S, Sabatos CA, Xiao S, et al. TIM-2 regulates T
helper type 2 responses and autoimmunity. J Exp Med. 2005;
202(3):437–444.