New classification of HLA-DRB1 alleles in rheumatoid arthritis susceptibility: a combined analysis of worldwide samples
Arthritis Research & Therapy
Vol10No1 New classification of HLA-DRB1 alleles in rheumatoid arthritis susceptibility: a combined analysis of worldwide samples Thomas Barnetche1, Arnaud Constantin1,2, Alain Cantagrel2,3, Anne Cambon-Thomsen1 and Pierre-Antoine Gourraud1,4
Corresponding author: Pierre-Antoine Gourraud
0 JE2510, University Paul Sabatier Toulouse III , 118 route de Narbonne, Toulouse, 31062 cedex 9 , France
1 Rheumatology Department, Larrey University Hospital , 24 chemin de Pouvourville, Toulouse cedex 9, 31059 , France
2 Department of Epidemiology and Public Health, UMR Inserm U 558, University Paul Sabatier Toulouse III, Faculty of Medicine Purpan , 37 Allées Jules Guesde, Toulouse cedex 7, 31073 , France
3 UF de Méthodologie de la recherche clinique, Epidemioloy Unit, Toulouse University Hospital , 37 Allées Jules Guesde, Toulouse cedex 7, 31073 , France
Introduction Rheumatoid arthritis (RA) is a complex polygenic disease of unknown etiology. HLA-DRB1 alleles encoding the shared epitope (SE) (RAA amino acid pattern in positions 72 to 74 of the third hypervariable region of the DRβ1 chain) are associated with RA susceptibility. A new classification of HLADRB1 SE alleles has been developed by Tezenas du Montcel and colleagues to refine the association between HLA-DRB1 and RA. In the present study, we used RA samples collected worldwide to investigate the relevance of this new HLA-DRB1 classification in terms of RA susceptibility across various Caucasoid and non-Caucasoid patients. Methods Eighteen subsamples were defined from a total number of 759 cases and 789 controls and grouped in 10 samples on the basis of their ethnic origin. HLA-DRB1 alleles were divided into five groups (S1, S2, S3D, S3P, and X) according to the new HLA-DRB1 allele classification. The whole analysis was performed by comparing carrier frequencies for the five HLA-DRB1 allele groups between RA patients and controls across the 10 Caucasoid and non-Caucasoid samples. The Mantel-Haenszel method of meta-analysis provided a global odds ratio (OR) estimate with 95% confidence interval (CI).
Rheumatoid arthritis (RA) is the most frequent chronic
inflammatory rheumatic disease in the world, with prevalence
estimates of 0.25% to 0.5%. Its pathogenesis is multifactorial and
genetic factors may contribute for 40% to 60% of the total risk
. Among possible genetic factors, the HLA-DRB1 gene
appears clearly associated with RA . This association was
first suggested more than 30 years ago  and was
elaborated 10 years later by Gregersen and colleagues , who
demonstrated that RA was associated with several
HLAAnti-CCP = anti-cyclic citrullinated peptide; CI = confidence interval; IHWG = International Histocompatibility Working Group; OR = odds ratio; RA
= rheumatoid arthritis; SE = shared epitope.
DRB1 alleles (DRB1*0101, DRB1*0102, DRB1*0401,
DRB1*0404, DRB1*0405, DRB1*0408, DRB1*1001, and
DRB1*1402) encoding the RAA sequence of amino acids at
positions 72 to 74 in the third hypervariable region of the
DRβ1 chain, known as the shared epitope (SE). Despite
significant improvement in molecular biology techniques,
association mechanisms between HLA-DRB1*SE+ alleles and RA
remain debated and authors have demonstrated that each SE
allele does not confer the same risk [4-6].
In a more recent study, Tezenas du Montcel and colleagues
 advanced a new classification of HLA-DRB1 alleles,
reconsidering the SE model in RA susceptibility. According to
this new classification, the susceptibility to RA, which
depends on whether the RAA sequence occupies positions
72 to 74, was modulated by the amino acids at positions 70
and 71, which led to the definition of five groups of
HLADRB1 alleles: S1, S2, S3P, S3D, and X alleles. Michou and
colleagues  tested and validated this new classification in an
independent sample of 100 French Caucasoid RA trio
families, providing estimates for the susceptibility risk genotypes.
In the present study, we used worldwide RA samples from the
13th International Histocompatibility Working Group (IHWG)
to investigate the relevance of this new HLA-DRB1 allele
classification in terms of RA susceptibility across various
Caucasoid and non-Caucasoid population samples.
Materials and methods
Selection process of case and control population
RA cases and healthy controls included in the present study
were selected from a population of 2,376 individuals (1,210
cases and 1,166 controls), initially gathered by 19 laboratories
in 17 countries in the framework of the 13th IHWG. The data
are publicly available from the dbMHC (Major
Histocompatibility Complex database) website of the National Center for
Biotechnology Information (Bethesda, MD, USA) . All RA
cases met the following criteria: adult onset RA (by definition,
16 years of age or older) and the American College of
Rheumatology criteria for RA . For each laboratory, healthy
controls were selected within the same geographical area as the
RA cases. A selection procedure of cases and controls was
carried out in order to allow the comparison of the data issued
from the different laboratories that participated in the 13th
IHWG: (a) cases and controls of undocumented origin were
excluded, (b) samples consisting of cases without controls
and samples of less than 20 individuals were discarded, and
(c) cases and controls that were matched beforehand for
specific HLA-DRB1–HLA-DQB1 haplotypes were excluded.
Data from different submitters consisting of individuals from
the same origin were pooled when no significant departures
were found as assessed by an admixture test, which
asymptotically follows a chi-square distribution with 1 degree of
freedom. According to this selection procedure, 758 cases and
789 controls, issued from 10 different ethnic origin
subsamples, were included in the present study (Table 1).
All RA cases and controls were genotyped for HLA-DRB1.
HLA-DRB1 typing techniques used in the framework of the
13th IHWG are described extensively in the 13th IHWG
HLA-DRB1 alleles were divided into five groups according to
the classification proposed by Tezenas du Montcel and
colleagues [11,12]. Briefly, the HLA-DRB1 alleles were first
divided into two groups according to the presence or absence
of the RAA sequence at positions 72 to 74 and were denoted
S and X alleles, respectively. The S alleles were subsequently
divided into three groups according to the amino acid (alanine
[A], glutamic acid [E], lysine [K], or arginine [R]) at position 71:
S1 for ARAA and ERAA, S2 for KRAA, and S3 for RRAA. Since
an aspartic acid (D) at position 70 was reported to be
protective against RA in contrast to a glutamine (Q) or an arginine (R)
at the same position , two additional groups were defined:
S3D for DRRAA and S3P for QRRAA or RRRAA [11,12].
To identify association with RA susceptibility, odds ratios
(ORs) were calculated for the presence of the S1, S2, S3P, S3D,
and X alleles. Confidence intervals (CIs) are given at 95%
confidence. Consistently with previous findings [7-9] and with the
main objective of this work (which is to challenge these
previous findings in various Caucasoid and non-Caucasoid
populations), we performed the whole analysis under a dominant
effect model by comparing carrier frequencies for the different
HLA-DRB1 allele groups defined according to the
classification between RA patients and controls across the 10
Caucasoid and non-Caucasoid samples.
We used a meta-analysis approach to combine the data
issued from the different laboratories that participated in the
13th IHWG. The Mantel-Haenszel method assumes a fixed
effect and combines studies using a method similar to inverse
variance approaches to determine the weight given to each
study. It provides a common OR estimate, taking into account
the weight of the different samples and 95% CI. OR and 95%
CI are shown on forest plots for each allele group studied.
Statistical heterogeneity of the considered samples was
assessed on the basis of the Q test (chi-square), using a
significance level of 0.05, and reported with the I2 statistic (in
which high values indicate high heterogeneity). An I2 value of
greater than 50% was considered the threshold for
heterogeneity. Genotype risk analyses were conducted using the same
method. All computations were performed using the Revman
4.2.8 software package developed by the Nordic Cochrane
Center (Copenhagen, Denmark)  and Stata version 7.0
software (StataCorp LP, College Station, TX, USA). All p
valComposition of the selected rheumatoid arthritis case and control population samples
North American (Amerinds)
North American (Blacks)
Carrier frequencies of the different HLA-DRB1 allele
groups in RA cases and controls for the various
Caucasoid and non-Caucasoid population samples
Figure 1 shows the carrier frequencies for the different
HLADRB1 allele groups, as defined according to the classification
developed by Tezenas du Montcel and colleagues , in
cases and controls of each sample selected from the 13th
IHWG. No significant departures from Hardy-Weinberg
equilibrium were observed (all p > 0.05 after correction for multiple
testing). Statistical testing for heterogeneity in the X allele
group revealed a significant difference between samples (I2 =
62.9%, p = 4 × 10-3). No significant heterogeneity could be
observed for the S1 (I2 = 0%, p = 0.57), S2 (I2 = 15.9%, p =
0.30), S3P (I2 = 19.5%, p = 0.27), or S3D (I2 = 23.6%, p = 0.23)
groups of HLA-DRB1 alleles.
Carrier frequency comparisons of the different
HLADRB1 allele groups between RA cases and controls
across the various Caucasoid and non-Caucasoid
population samples and overall effect estimation
Results of allele carrier frequency comparisons between RA
cases and controls across the various Caucasoid and
nonCaucasoid population samples are presented in Figure 1. An
overall positive association with RA susceptibility was found
for S2 alleles (OR 2.15, 95% CI 1.54 to 3.00; p < 10-5) and
S3P alleles (OR 2.74, 95% CI 2.01 to 3.74; p < 10-5). An
overall negative association with RA susceptibility was highlighted
for S1 alleles (OR 0.60, 95% CI 0.48 to 0.76; p < 10-4) and X
alleles (OR 0.58, 95% CI 0.39 to 0.84; p = 4 × 10-3). No
sigThese data were extracted from the 13th International Histocompatibility Working Group rheumatoid arthritis samples and are available on the
National Center for Biotechnology Information website . For the sample selection procedure, please refer to the Materials and methods
section of this article.
ues were two-sided. P values of less than 0.05 were
considered significant, and corrections for multiple testing were
mentioned when relevant.
nificant association with RA susceptibility was found for the
S3D group of alleles (OR 0.89, 95% CI 0.69 to 1.14; p = 0.88).
In such an analysis, a potential bias may be introduced by the
presence of allele adverse effect in the control group. For
example, in the analysis of the S2 effect, the association may
be overestimated due to the presence of S3D carriers in the
control group (noncarrier of S2). Similarly, the effect of S2 may
be underestimated thanks to the presence of S3P carriers.
After controlling for the adverse effect of S3D and S1 in the
analysis of S2, the association with RA susceptibility remained
significant (p < 0.05).
Carrier frequency comparisons of the different
HLADRB1 allele groups between RA cases and controls in
Caucasoid and non-Caucasoid population samples
Results of allele carrier frequency comparisons between RA
cases and controls in Caucasoid and non-Caucasoid
population samples are presented in Table 2. In the Caucasoid
population sample, S2 alleles (OR 2.61, 95% CI 1.87 to 3.64) and
S3P alleles (OR 1.86, 95% CI 1.39 to 2.49) were positively
associated with RA susceptibility, whereas S1 alleles (OR
0.59, 95% CI 0.45 to 0.79) and X alleles (OR 0.74, 95% CI
0.56 to 0.96) were negatively associated with RA
susceptibility. In the non-Caucasoid population sample, S3P alleles (OR
2.93, 95% CI 2.21 to 4.04) were positively associated with
RA susceptibility, whereas S1 alleles (OR 0.52, 95% CI 0.37
to 0.71) and X alleles (OR 0.61, 95% CI 0.45 to 0.83) were
negatively associated with RA susceptibility.
Overall effect estimation of genotypes resulting from the
classification of HLA-DRB1 alleles on RA susceptibility
Using the approach proposed by Michou and colleagues ,
we further pooled the three low-risk allele groups (S1, S3D, and
X), thus producing a new grouping called L alleles. Thus, in
Caurrciearsforeidqaunedncnyocno-Cmapuacriassoonids opfotphueladtifofenrseanmtHplLeAs-aDnRdBo1vearllaelleefgferocutpesstbimetawtieoenn rheumatoid arthritis (RA) cases and controls across the various
Caucasoid and non-Caucasoid population samples and overall effect estimation. This figure provides a summary meta-analysis of allele carrier
frequencies according to HLA-DRB1 allele classification, in selected samples among the data available from the 13th International Histocompatibility
Working Group on Rheumatoid Arthritis. For each population sample, odds ratios (ORs) and 95% confidence intervals (95% CIs) evaluate the
significance of the association between the different HLA-DRB1 allele groups and RA susceptibility (blue boxes). The combined ORs and 95% CIs
evaluate the significance of the global effect of the different HLA-DRB1 allele groups on RA susceptibility over all population samples. P values were
calculated with the Mantel-Haenszel method (black diamonds).
Carrier frequency comparisons of the different HLA-DRB1 allele groups between rheumatoid arthritis cases and controls in
Caucasoid and non-Caucasoid population samples
The Caucasoid sample population refers to the combination of the following population samples: Greek, Spanish, Russian, and American
(Whites). The non-Caucasoid sample population refers to the combination of the following population samples: North American (Amerinds), North
American (Blacks), Bushmen, Korean, Chinese, and Javanese. The combined odds ratios (ORs) and 95% confidence intervals (CIs) evaluate the
significance of the global effect of the different HLA-DRB1 allele groups on rheumatoid arthritis (RA) susceptibility in Caucasoids and
Overall effect estimation of genotypes resulting from the classification of HLA-DRB1 alleles on rheumatoid arthritis susceptibility
Genotype distribution, n (%)
RA cases, n = 758
Controls, n = 789
S1, S2, S3P, S3D, and X allele groups were defined according to the amino acid sequence at positions 70 to 74. According to the approach
proposed by Michou and colleagues , we pooled the three low-risk allele groups (S1, S3D, and X), so called L alleles. Thus, in subsequent
analyses, we considered only three allele groups (S2, S3P, and L alleles), with six corresponding genotypes . The reference genotype is L/L.
The combined odds ratios (ORs) and 95% confidence intervals (CIs) evaluate the significance of the global effect of the different HLA-DRB1
genotype groups on rheumatoid arthritis (RA) susceptibility over all population samples. P values were calculated with the Mantel-Haenszel
subsequent analyses, we considered only three allele groups
(95% CIs) of 7.25 (3.26 to 16.14) and 5.15 (2.91 to 9.12),
(S2, S3P, and L alleles), with six corresponding genotypes .
The results of observed genotype distributions and of
genotype relative risks are shown in Table 3. S2/S3P and S3P/
S3P were associated with the greatest risks for RA, with ORs
respectively. These are followed by S2/S2, S2/L, and S3P/L,
with ORs (95% CIs) of 4.95 (2.2 to 11.18), 2.41 (1.60 to
3.65), and 2.33 (1.57 to 3.45), respectively. These analyses
were all performed using the L/L genotype as reference.
In the present association study, we investigated the relevance
of the classification of HLA-DRB1 alleles proposed by
Tezenas du Montcel and colleagues  regarding susceptibility to
RA, across various Caucasoid and non-Caucasoid population
samples, using publicly available data from the 13th IHWG RA
studies. Across these various population samples, our
approach strengthens the relevance of this classification,
exhibiting an overall positive association with RA susceptibility
for S2 and S3P alleles and an overall negative association with
RA susceptibility for S1 and X alleles. The genotype analysis
performed in the present study fits with the genotype risk
hierarchy previously reported in Caucasoid RA sporadic cases
 and families .
The present combined analysis included 10 samples from
different genetic backgrounds. Although we did not observe
significant heterogeneity for S1, S2, S3D and S3P allele groups, we
observed significant heterogeneity for the X allele group
across the different population samples. The fixed effect
model of the Mantel-Haenszel method, used for the overall
effect analysis of the HLA-DRB1 allele and genotype groups
on RA susceptibility in the present study, assumes that each
allele group carries out a homogeneous effect on RA
susceptibility across the various Caucasoid and non-Caucasoid
samples. The heterogeneity observed for the X allele group may be
questioned according the heterogeneity of the HLA-DRB1
allele and genotype groups at two levels across the different
population samples: the effect level and the frequency level.
Our data suggest that there is a differential effect of the S1, S2,
S3D and S3P allele groups on RA susceptibility. Each of these
effects seems homogenous across the various population
samples. Because the SE allele distribution varies across
these populations, the resulting effect of the X allele group on
RA susceptibility depends both on the frequency of the S1, S2,
S3D and S3P allele groups, and their respective effects on RA
susceptibility, which might explain the observed heterogeneity
of the effect of the X allele group in our study.
The contribution of SE alleles to RA susceptibility has been
confirmed by numerous studies on different populations. For
example, a recent meta-analysis on Latin American RA
patients has shown the important role played by SE in RA
susceptibility . However, RA prevalence studies have shown
differences in frequency estimations between populations
with different genetic backgrounds. The highest prevalence
rates have been found in Native American populations with
estimation ranges of 32 to 48 per 1,000 men and 59 to 70 per
1,000 women. In Afro-Caribbean people who live in the UK,
RA prevalence appeared to be lower than that in the general
population. In urban African populations, RA prevalence was
estimated around 10 per 1,000 and was found to be
significantly higher than in rural populations. Studies on Chinese
populations have reported lower prevalence estimations than
in European ones. Molokhia and McKeigue previously pointed
out the difficulty brought up by admixture in investigating the
etiology of rheumatic diseases, notably for RA . The
significant variations observed in the incidence and prevalence of
RA among different populations or ethnic groups could be
explained, in part, by genetic variations in the HLA region,
especially variations in the prevalence of SE in different
populations [17,18]. In addition, as no consideration of
environmental exposure variations between the population
samples studied was made, the heterogeneity could be
explained by the different impact of environmental factors on
RA susceptibility in each different sample, such as nutrition as
previously suggested, in particular in the Greek population
[18,19]. In addition to nutrition, environmental factors such as
exposure to cigarette smoking [20,21] or individual factors
such as gender  may influence susceptibility to RA by
interacting with genetic factors such as HLA-DRB1.
The classification proposed by Tezenas du Montcel and
colleagues , based on amino acid sequence at positions 70
to 74, does not aim to account for all previously reported
associations between particular HLA-DRB1 alleles and RA
susceptibility in specific ethnic backgrounds. For example, the
previously reported association between the
HLADRB1*0901 allele and RA susceptibility in East Asian
populations could not be tested in the present study, as this particular
allele was classified together with many others as an X allele
[23-25]. The high frequency of the HLA-DRB1*0901 allele in
the Javanese population could contribute both to the
association found between X alleles and susceptibility to RA in this
particular population sample and to the observed
heterogeneity of the X allele group.
The contribution of the HLA-DRB1 allele classification in
accounting for the genetic contribution of the HLA-DRB1
gene was previously analyzed in terms of RA severity and in
terms of autoantibody production such as anti-cyclic
citrullinated peptide (anti-CCP) antibodies and anti-deiminated
human fibrinogen autoantibodies. As RA severity outcomes as
well as anti-CPP information were not collected in the
framework of the 13th IHWG, we were not able to discuss the
relevance of the classification of HLA-DRB1 alleles proposed by
Tezenas du Montcel and colleagues  regarding RA severity
or autoantibody production in the various Caucasoid and
nonCaucasoid population samples included in the present study.
Across these various samples coming from both Caucasoid
and non-Caucasoid populations, we investigated the
relevance of the classification of HLA-DRB1 alleles proposed
by Tezenas du Montcel and colleagues  regarding
susceptibility to RA. We confirm previous findings on the
contribution of the S2 and S3P risk allele groups to RA susceptibility.
In spite of the small sample size in some ethnic groups, the
present study allows the differentiation between predisposing
and protective HLA-DRB1 SE alleles in both Caucasoid and
non-Caucasoid RA patients.
This report also emphasized the very crucial importance of
public release of large-scale study data in genetic
epidemiology. The need for large samples to refine the study of effects
of modest magnitude and the necessity to replicate studies
across different ethnic backgrounds rely on easy access to a
large variety of data organized in a systematic way. After an
initial period of restricted use of the data by the initial
investigators, the access to clinical and genetic anonymous individual
data should be made possible; this is the current policy of the
National Institutes of Health (Bethesda, MD, USA) for
genome-wide association study results . Combined with a
detailed description of the sampling scheme for both patients
and controls, advanced statistical analysis will contribute to
enhance secondary uses of data valorizing the efforts of
previously completed studies .
The authors declare that they have no competing interests.
TB, ACo, and P-AG took the leadership of the study in both
immunological and statistical aspects. ACa contributed
through the assessment of clinical aspects. AC-T contributed
to the statistical analysis. All authors read and approved the
The authors wish to gratefully acknowledge the contributions of John
Hansen and Lee Nelson at the Fred Hutchinson Cancer Research
Center (Seattle, WA, USA) and Mike Feolo and the dbMHC (major
histocompatibility complex database) team at the National Center for
Biotechnology Information (Bethesda, MD, USA) and the help of technical
and clinical collaborators from the rheumatoid arthritis international
working group, for clinical data management and laboratory typings. The
authors are indebted to patients and controls for their kind participation.
All of these contributions were invaluable for the setting up of the
database used in this article. Infrastructures and facilities from Institut
National de la Santé et de la recherche médicale Inserm, Unit 558,
Toulouse, and from University Paul Sabatier Toulouse III were used, in
particular the TIERSMIP platform for managing multi-site clinical research
data management and analysis. The authors were supported by the
following institutions: Institut National de la Santé et de la recherche
médicale: INSERM, Unit 558, Toulouse, France (P-AG, AC-T, and AC);
Centre National de la Recherche Scientifique (AC-T); Department of
Rheumatology (AC); Department of Epidemiology (P-AG); and
University Hospital, Bordeaux (TB).
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