Fine Mapping Seronegative and Seropositive Rheumatoid Arthritis to Shared and Distinct HLA Alleles by Adjusting for the Effects of Heterogeneity

Abstract

Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA(-) RA and observed independent associations for serine and leucine at position 11 in HLA-DRβ1 (p = 1.4 × 10(-13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 × 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1(∗)03 (encoding serine at 11) and HLA-B(∗)08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DRβ1 Ser11+Leu11: p = 5.8 × 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 × 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DRβ1 position 11 were distinct (p < 2.9 × 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 × 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions.

The HLA-DRβ1 amino acid positions 11–13–26 explain the majority of SLE–MHC associations

“…We calculated multivariate betas and s.e. for each residue against a reference residue (Pro11 and Phe13) from our data set and original rheumatoid arthritis data sets 11,13,18 and tested the discordance of effect sizes between the diseases using the following statistic:…”

“…Since there was notable disease pleiotropy at the HLA-DRb1 amino acid positions 11 and 13 to other diseases such as rheumatoid arthritis and follicular lymphoma [11][12][13]18 , we further investigated residue effects of these positions on different disease phenotypes. As expected, the residue effects were unique and not correlated between SLE and the two unrelated diseases ( Supplementary Fig.…”

“…Alternatively, another point worth considering is the exclusion of causal functional variants in the previous analyses. Recent studies on HLA associations in other diseases suggested that amino acid positions were the major driver conferring risk for diseases rather than the classical alleles [11][12][13] . Coding variants in HLA genes are one of the most important factors influencing the activity and specificity of the HLA molecules, but no study has investigated the possible association of amino acids of HLA genes with SLE susceptibility.…”

Genome-wide association studies: the good, the bad and the ugly

“…Multiple common variants may prove useful in identifying individuals with coeliac disease 16 and different types of rheumatoid arthritis. 17 Over the next few years, it will be worth noting how additional discoveries in the infl ammatory and autoimmune diseases, where genetic effects tend to be stronger, help clinicians and their patients.…”

The genetic architecture of psychiatric disorders

“…For example, decades ago based on clinical symptoms alone the inflammatory bowel diseases ulcerative colitis and Crohn's Disease would have been indistinguishable and given the same diagnosis. More recently, it has been recognised that diagnosis and treatment of rheumatoid arthritis should consider presence and absence of anti-citrullinated-protein-autoantibodies [147]. The genomics era has allowed good progress in subtyping of cancers (e.g., ER +ve/ER -ve and over-expression of HER2 as a breast-cancer subtype [148,149] or K-ras mutations in colorectal cancer and EGFR mutations in lung cancer, reviewed in [150]), however other branches of medicine are less able to supply measures of phenotypic heterogeneity in the tissue of relevance for mapping onto the genetic heterogeneity.…”