Overview of the MHC fine mapping data

Risk loci involved in giant cell arteritis susceptibility: a genome-wide association study

BACKGROUND

Giant cell arteritis is an age-related vasculitis that mainly affects the aorta and its branches in individuals aged 50 years and older. Current options for diagnosis and treatment are scarce, highlighting the need to better understand its underlying pathogenesis. Genome-wide association studies (GWAS) have emerged as a powerful tool for unravelling the pathogenic mechanisms involved in complex diseases. We aimed to characterise the genetic basis of giant cell arteritis by performing the largest GWAS of this vasculitis to date and to assess the functional consequences and clinical implications of identified risk loci.

METHODS

We collected and meta-analysed genomic data from patients with giant cell arteritis and healthy controls of European ancestry from ten cohorts across Europe and North America. Eligible patients required confirmation of giant cell arteritis diagnosis by positive temporal artery biopsy, positive temporal artery doppler ultrasonography, or imaging techniques confirming large-vessel vasculitis. We assessed the functional consequences of loci associated with giant cell arteritis using cell enrichment analysis, fine-mapping, and causal gene prioritisation. We also performed a drug repurposing analysis and developed a polygenic risk score to explore the clinical implications of our findings.

FINDINGS

We included a total of 3498 patients with giant cell arteritis and 15 550 controls. We identified three novel loci associated with risk of giant cell arteritis. Two loci, MFGE8 (rs8029053; p=4·96 × 10-8; OR 1·19 [95% CI 1·12-1·26]) and VTN (rs704; p=2·75 × 10-9; OR 0·84 [0·79-0·89]), were related to angiogenesis pathways and the third locus, CCDC25 (rs11782624; p=1·28 × 10-8; OR 1·18 [1·12-1·25]), was related to neutrophil extracellular traps (NETs). We also found an association between this vasculitis and HLA region and PLG. Variants associated with giant cell arteritis seemed to fulfil a specific regulatory role in crucial immune cell types. Furthermore, we identified several drugs that could represent promising candidates for treatment of this disease. The polygenic risk score model was able to identify individuals at increased risk of developing giant cell arteritis (90th percentile OR 2·87 [95% CI 2·15-3·82]; p=1·73 × 10-13).

INTERPRETATION

We have found several additional loci associated with giant cell arteritis, highlighting the crucial role of angiogenesis in disease susceptibility. Our study represents a step forward in the translation of genomic findings to clinical practice in giant cell arteritis, proposing new treatments and a method to measure genetic predisposition to this vasculitis.

FUNDING

Institute of Health Carlos III, Spanish Ministry of Science and Innovation, UK Medical Research Council, and National Institute for Health and Care Research.

Polygenic risk score for ulcerative colitis predicts immune checkpoint inhibitor-mediated colitis

Immune checkpoint inhibitor-mediated colitis (IMC) is a common adverse event of treatment with immune checkpoint inhibitors (ICI). We hypothesize that genetic susceptibility to Crohn's disease (CD) and ulcerative colitis (UC) predisposes to IMC. In this study, we first develop a polygenic risk scores for CD (PRSCD) and UC (PRSUC) in cancer-free individuals and then test these PRSs on IMC in a cohort of 1316 patients with ICI-treated non-small cell lung cancer and perform a replication in 873 ICI-treated pan-cancer patients. In a meta-analysis, the PRSUC predicts all-grade IMC (ORmeta=1.35 per standard deviation [SD], 95% CI = 1.12-1.64, P = 2×10-03) and severe IMC (ORmeta=1.49 per SD, 95% CI = 1.18-1.88, P = 9×10-04). PRSCD is not associated with IMC. Furthermore, PRSUC predicts severe IMC among patients treated with combination ICIs (ORmeta=2.20 per SD, 95% CI = 1.07-4.53, P = 0.03). Overall, PRSUC can identify patients receiving ICI at risk of developing IMC and may be useful to monitor patients and improve patient outcomes.

The Application of High-Throughput Approaches in Identifying Novel Therapeutic Targets and Agents to Treat Diabetes

During the past decades, unprecedented progress in technologies has revolutionized traditional research methodologies. Among these, advances in high-throughput drug screening approaches have permitted the rapid identification of potential therapeutic agents from drug libraries that contain thousands or millions of molecules. Moreover, high-throughput-based therapeutic target discovery strategies can comprehensively interrogate relationships between biomolecules (e.g., gene, RNA, and protein) and diseases and significantly increase the authors' knowledge of disease mechanisms. Diabetes is a chronic disease primarily characterized by the incapacity of the body to maintain normoglycemia. The prevalence of diabetes in modern society has become a severe public health issue that threatens the well-being of millions of patients. Although a number of pharmacological treatments are available, there is no permanent cure for diabetes, and discovering novel therapeutic targets and agents continues to be an urgent need. The present review discusses the technical details of high-throughput screening approaches in drug discovery, followed by introducing the applications of such approaches to diabetes research. This review aims to provide an example of the applicability of high-throughput technologies in facilitating different aspects of disease research.

Immune and spermatogenesis-related loci are involved in the development of extreme patterns of male infertility

We conducted a genome-wide association study in a large population of infertile men due to unexplained spermatogenic failure (SPGF). More than seven million genetic variants were analysed in 1,274 SPGF cases and 1,951 unaffected controls from two independent European cohorts. Two genomic regions were associated with the most severe histological pattern of SPGF, defined by Sertoli cell-only (SCO) phenotype, namely the MHC class II gene HLA-DRB1 (rs1136759, P = 1.32E-08, OR = 1.80) and an upstream locus of VRK1 (rs115054029, P = 4.24E-08, OR = 3.14), which encodes a protein kinase involved in the regulation of spermatogenesis. The SCO-associated rs1136759 allele (G) determines a serine in the position 13 of the HLA-DRβ1 molecule located in the antigen-binding pocket. Overall, our data support the notion of unexplained SPGF as a complex trait influenced by common variation in the genome, with the SCO phenotype likely representing an immune-mediated condition.

A GWAS in a large case-control cohort of European ancestry identifies two genomic regions, the MHC class II gene HLA-DRB1 and an upstream locus of VRK1, that are associated with the most severe phenotype of spermatogenic failure.

Complement component C4 structural variation and quantitative traits contribute to sex-biased vulnerability in systemic sclerosis

Copy number (CN) polymorphisms of complement C4 play distinct roles in many conditions, including immune-mediated diseases. We investigated the association of C4 CN with systemic sclerosis (SSc) risk. Imputed total C4, C4A, C4B, and HERV-K CN were analyzed in 26,633 individuals and validated in an independent cohort. Our results showed that higher C4 CN confers protection to SSc, and deviations from CN parity of C4A and C4B augmented risk. The protection contributed per copy of C4A and C4B differed by sex. Stronger protection was afforded by C4A in men and by C4B in women. C4 CN correlated well with its gene expression and serum protein levels, and less C4 was detected for both in SSc patients. Conditioned analysis suggests that C4 genetics strongly contributes to the SSc association within the major histocompatibility complex locus and highlights classical alleles and amino acid variants of HLA-DRB1 and HLA-DPB1 as C4-independent signals.

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.

Integrative epigenomics in Sjögren´s syndrome reveals novel pathways and a strong interaction between the HLA, autoantibodies and the interferon signature

Primary Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

Germline determinants of humoral immune response to HPV-16 protect against oropharyngeal cancer

Although several oropharyngeal cancer (OPC) susceptibility loci have been identified, most previous studies lacked detailed information on human papillomavirus (HPV) status. We conduct a genome-wide analysis by HPV16 serology status in 4,002 oral cancer cases (OPC and oral cavity cancer (OCC)) and 5,256 controls. We detect four susceptibility loci pointing to a distinct genetic predisposition by HPV status. Our most notable finding in the HLA region, that is now confirmed to be specific of HPV(+)OPC risk, reveal two independent loci with strong protective effects, one refining the previously reported HLA class II haplotype association. Antibody levels against HPV16 viral proteins strongly implicate the protective HLA variants as major determinants of humoral response against L1 capsid protein or E6 oncoprotein suggesting a natural immune response against HPV(+)OPC promoted by HLA variants. This indicates that therapeutic vaccines that target E6 and attenuate viral response after established HPV infections might protect against HPV(+)OPC.

Comprehensive analysis of the major histocompatibility complex in systemic sclerosis identifies differential HLA associations by clinical and serological subtypes

OBJECTIVE

The greatest genetic effect reported for systemic sclerosis (SSc) lies in the major histocompatibility complex (MHC) locus. Leveraging the largest SSc genome-wide association study, we aimed to fine-map this region to identify novel human leucocyte antigen (HLA) genetic variants associated with SSc susceptibility and its main clinical and serological subtypes.

METHODS

9095 patients with SSc and 17 584 controls genome-wide genotyped were used to impute and test single-nucleotide polymorphisms (SNPs) across the MHC, classical HLA alleles and their composite amino acid residues. Additionally, patients were stratified according to their clinical and serological status, namely, limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), anticentromere (ACA), antitopoisomerase (ATA) and anti-RNApolIII autoantibodies (ARA).

RESULTS

Sequential conditional analyses showed nine SNPs, nine classical alleles and seven amino acids that modelled the observed associations with SSc. This confirmed previously reported associations with HLA-DRB1*11:04 and HLA-DPB1*13:01, and revealed a novel association of HLA-B*08:01. Stratified analyses showed specific associations of HLA-DQA1*02:01 with lcSSc, and an exclusive association of HLA-DQA1*05:01 with dcSSc. Similarly, private associations were detected in HLA-DRB1*08:01 and confirmed the previously reported association of HLA-DRB1*07:01 with ACA-positive patients, as opposed to the HLA-DPA1*02:01 and HLA-DQB1*03:01 alleles associated with ATA presentation.

CONCLUSIONS

This study confirms the contribution of HLA class II and reveals a novel association of HLA class I with SSc, suggesting novel pathways of disease pathogenesis. Furthermore, we describe specific HLA associations with SSc clinical and serological subtypes that could serve as biomarkers of disease severity and progression.

Pulmonary fibrosis in relation to genetic loci in an inception cohort of patients with early rheumatoid arthritis from northern Sweden

Objectives

Pulmonary manifestations in RA are common comorbidities. Interstitial lung disease (ILD), both idiopathic and in RA, has been associated with several genetic variants. We assessed pulmonary fibrosis (PF) in an inception cohort of RA patients in relation to genetic variants and disease-related factors.

Methods

A total of 1466 early RA patients were consecutively included and followed prospectively from the index date until death or 31 December 2016. Clinical and laboratory data and treatment were continuously registered according to the Swedish Rheumatology Quality Register. DNA was available from 1184 patients and 571 151 genome-wide single-nucleotide polymorphisms (SNPs) were analysed. Thirteen identified genetic variants were extracted. At follow-up, the patients answered a questionnaire regarding disease progression and lung involvement that was validated by reviewing medical records and analysing radiological examinations.

Results

The prevalence of PF was 5.6% and the annualized incidence rate was 5.0/1000 (95% CI 3.80, 6.54). Four SNPs were associated with PF in RA: rs35705950 [MUC5B; OR 2.5 (95% CI 1.5, 4.0), adjusted P-value = 0.00016, q-value = 0.0021]; rs111521887 [TOLLIP; OR 1.9 (95% CI 1.3, 2.8), adjusted P-value = 0.0014, q-value = 0.0092]; rs2609255 [FAM13A; OR 1.7 (95% CI 1.1, 2.5), adjusted P-value = 0.013, q-value = 0.055] and rs2736100 [TERT; OR 1.5 (95% CI 1.0, 2.2), adjusted P-value = 0.046, q-value = 0.15]. Older age and RF positivity were associated with increased risk, while MTX treatment was associated with a lower risk of PF.

Conclusions

Development of PF in an inception cohort of RA patients was associated with 4 of 12 ILD risk genes. RA-related factors except for age at diagnosis and RF positivity were of limited importance in PF development.

Accurate imputation of human leukocyte antigens with CookHLA

The recent development of imputation methods enabled the prediction of human leukocyte antigen (HLA) alleles from intergenic SNP data, allowing studies to fine-map HLA for immune phenotypes. Here we report an accurate HLA imputation method, CookHLA, which has superior imputation accuracy compared to previous methods. CookHLA differs from other approaches in that it locally embeds prediction markers into highly polymorphic exons to account for exonic variability, and in that it adaptively learns the genetic map within MHC from the data to facilitate imputation. Our benchmarking with real datasets shows that our method achieves high imputation accuracy in a wide range of scenarios, including situations where the reference panel is small or ethnically unmatched.

A cross-disease meta-GWAS identifies four new susceptibility loci shared between systemic sclerosis and Crohn's disease

Genome-wide association studies (GWASs) have identified a number of genetic risk loci associated with systemic sclerosis (SSc) and Crohn’s disease (CD), some of which confer susceptibility to both diseases. In order to identify new risk loci shared between these two immune-mediated disorders, we performed a cross-disease meta-analysis including GWAS data from 5,734 SSc patients, 4,588 CD patients and 14,568 controls of European origin. We identified 4 new loci shared between SSc and CD, IL12RB2, IRF1/SLC22A5, STAT3 and an intergenic locus at 6p21.31. Pleiotropic variants within these loci showed opposite allelic effects in the two analysed diseases and all of them showed a significant effect on gene expression. In addition, an enrichment in the IL-12 family and type I interferon signaling pathways was observed among the set of SSc-CD common genetic risk loci. In conclusion, through the first cross-disease meta-analysis of SSc and CD, we identified genetic variants with pleiotropic effects on two clinically distinct immune-mediated disorders. The fact that all these pleiotropic SNPs have opposite allelic effects in SSc and CD reveals the complexity of the molecular mechanisms by which polymorphisms affect diseases.

Distinct HLA Associations with Rheumatoid Arthritis Subsets Defined by Serological Subphenotype

Rheumatoid arthritis (RA) is the most common immune-mediated arthritis. Anti-citrullinated peptide antibodies (ACPA) are highly specific to RA and assayed with the commercial CCP2 assay. Genetic drivers of RA within the MHC are different for CCP2-positive and -negative subsets of RA, particularly at HLA-DRB1. However, aspartic acid at amino acid position 9 in HLA-B (B^pos-9) increases risk to both RA subsets. Here we explore how individual serologies associated with RA drive associations within the MHC. To define MHC differences for specific ACPA serologies, we quantified a total of 19 separate ACPAs in RA-affected case subjects from four cohorts (n = 6,805). We found a cluster of tightly co-occurring antibodies (canonical serologies, containing CCP2), along with several independently expressed antibodies (non-canonical serologies). After imputing HLA variants into 6,805 case subjects and 13,467 control subjects, we tested associations between the HLA region and RA subgroups based on the presence of canonical and/or non-canonical serologies. We examined CCP2(+) and CCP2(−) RA-affected case subjects separately. In CCP2(−) RA, we observed that the association between CCP2(−) RA and B^pos-9 was derived from individuals who were positive for non-canonical serologies (omnibus_p = 9.2 × 10⁻¹⁷). Similarly, we observed in CCP2(+) RA that associations between subsets of CCP2(+) RA and B^pos-9 were negatively correlated with the number of positive canonical serologies (p = 0.0096). These findings suggest unique genetic characteristics underlying fine-specific ACPAs, suggesting that RA may be further subdivided beyond simply seropositive and seronegative.

A New Pedigree-Based SNP Haplotype Method for Genomic Polymorphism and Genetic Studies

Single nucleotide polymorphisms (SNPs) are usually the most frequent genomic variants. Directly pedigree-phased multi-SNP haplotypes provide a more accurate view of polymorphic population genomic structure than individual SNPs. The former are, therefore, more useful in genetic correlation with subject phenotype. We describe a new pedigree-based methodology for generating non-ambiguous SNP haplotypes for genetic study. SNP data for haplotype analysis were extracted from a larger Type 1 Diabetes Genetics Consortium SNP dataset based on minor allele frequency variation and redundancy, coverage rate (the frequency of phased haplotypes in which each SNP is defined) and genomic location. Redundant SNPs were eliminated, overall haplotype polymorphism was optimized and the number of undefined haplotypes was minimized. These edited SNP haplotypes from a region containing HLA-DRB1 (DR) and HLA-DQB1 (DQ) both correlated well with HLA-typed DR,DQ haplotypes and differentiated HLA-DR,DQ fragments shared by three pairs of previously identified megabase-length conserved extended haplotypes. In a pedigree-based genetic association assay for type 1 diabetes, edited SNP haplotypes and HLA-typed HLA-DR,DQ haplotypes from the same families generated essentially identical qualitative and quantitative results. Therefore, this edited SNP haplotype method is useful for both genomic polymorphic architecture and genetic association evaluation using SNP markers with diverse minor allele frequencies.

Analysis of the genetic component of systemic sclerosis in Iranian and Turkish populations through a genome-wide association study

Objectives

SSc is an autoimmune disease characterized by alteration of the immune response, vasculopathy and fibrosis. Most genetic studies on SSc have been performed in European-ancestry populations. The aim of this study was to analyse the genetic component of SSc in Middle Eastern patients from Iran and Turkey through a genome-wide association study.

Methods

This study analysed data from a total of 834 patients diagnosed with SSc and 1455 healthy controls from Iran and Turkey. DNA was genotyped using high-throughput genotyping platforms. The data generated were imputed using the Michigan Imputation Server, and the Haplotype Reference Consortium as a reference panel. A meta-analysis combining both case-control sets was conducted by the inverse variance method.

Results

The highest peak of association belonged to the HLA region in both the Iranian and Turkish populations. Strong and independent associations between the classical alleles HLA-DRB1*11: 04 [P = 2.10 × 10-24, odds ratio (OR) = 3.14] and DPB1*13: 01 (P = 5.37 × 10-14, OR = 5.75) and SSc were observed in the Iranian population. HLA-DRB1*11: 04 (P = 4.90 × 10-11, OR = 2.93) was the only independent signal associated in the Turkish cohort. An omnibus test yielded HLA-DRB1 58 and HLA-DPB1 76 as relevant amino acid positions for this disease. Concerning the meta-analysis, we also identified two associations close to the genome-wide significance level outside the HLA region, corresponding to IRF5-TNPO3 rs17424921-C (P = 1.34 × 10-7, OR = 1.68) and NFKB1 rs4648133-C (P = 3.11 × 10-7, OR = 1.47).

Conclusion

We identified significant associations in the HLA region and suggestive associations in IRF5-TNPO3 and NFKB1 loci in Iranian and Turkish patients affected by SSc through a genome-wide association study and an extensive HLA analysis.

Fine mapping of MHC region in lung cancer highlights independent susceptibility loci by ethnicity

The basis for associations between lung cancer and major histocompatibility complex genes is not completely understood. Here the authors further consider genetic variation within the MHC region in lung cancer patients and identify independent associations within HLA genes that explain MHC lung cancer associations in Europeans and Asian populations.

Lung cancer has several genetic associations identified within the major histocompatibility complex (MHC); although the basis for these associations remains elusive. Here, we analyze MHC genetic variation among 26,044 lung cancer patients and 20,836 controls densely genotyped across the MHC, using the Illumina Illumina OncoArray or Illumina 660W SNP microarray. We impute sequence variation in classical HLA genes, fine-map MHC associations for lung cancer risk with major histologies and compare results between ethnicities. Independent and novel associations within HLA genes are identified in Europeans including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701; the latter better represented by the amino acid Ala-104. These results implicate several HLA–tumor peptide interactions as the major MHC factor modulating lung cancer susceptibility.

Fine-mapping the MHC region in Asian populations identified novel variants modifying susceptibility to lung cancer

OBJECTIVES

The polymorphic major histocompatibility complex (MHC) plays a vital role in the immune system and drives predisposition to multiple cancers. A number of lung cancer-related genetic variants in the MHC have been identified in recent genome-wide association studies; however, the causal variants remain unclear.

MATERIALS AND METHODS

In the present study, we conducted a large-scale fine-mapping study of lung cancer in the MHC region of 13,945 unrelated Asian individuals to search for potential causal variants. We used the recently constructed Pan-Asian panel as the reference and imputed eight HLA genes (HLA-A, HLC-B, HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1) using SNP2HLA software.

RESULTS

We identified one single nucleotide polymorphism, rs12333226 (OR=1.41, P=3.97×10^-7), five HLA amino acid polymorphisms in HLA-DRB1 (OR=0.89, P=7.51×10^-6-8.57×10^-6), and one two-digit classic HLA allele HLA-A*11 (OR=0.87, P=9.68×10^-6) that were strongly associated with the risk of lung cancer. Rs12333226 was an expression quantitative trait locus of HLA-A and HLA-H in circulating monocytes, and exerted effect on lung cancer risk especially in the younger. HLA-DRβ1 positions 10, 16, and 25 drove the effect of one reported SNP rs2395185. The peptide position analysis identified additional lung cancer susceptibility amino acid positions, including HLA-DRβ1 position 30 and 11 (P_omnibus=6.11×10^-5 and 6.91×10^-5), HLA-DQa1 47 and 76 (P_omnibus=3.96×10^-4 and 1.41×10^-2) and HLA-A 152 (P_omnibus=4.86×10^-4). Most of the peptide positions were located in the peptide-binding grooves and seemed to affect antigen presentation. All the existing and novel variants explained approximately 2.37% of the phenotypic variances, while 21.10% was attributed to the variants identified in this study.

CONCLUSION

We identified seven novel bi-allelic variants and five polymorphic amino acid positions in HLA-DRβ1, HLA-DQα1, and HLA-A that confer a risk of lung cancer. This finding provides evidence for the substantial contributions of HLA class I and II molecules to lung cancer susceptibility.

Imputation of orofacial clefting data identifies novel risk loci and sheds light on the genetic background of cleft lip ± cleft palate and cleft palate only

Nonsyndromic cleft lip with or without cleft palate (nsCL/P) is among the most common human birth defects with multifactorial etiology. Here, we present results from a genome-wide imputation study of nsCL/P in which, after adding replication cohort data, four novel risk loci for nsCL/P are identified (at chromosomal regions 2p21, 14q22, 15q24 and 19p13). On a systematic level, we show that the association signals within this high-density dataset are enriched in functionally-relevant genomic regions that are active in both human neural crest cells (hNCC) and mouse embryonic craniofacial tissue. This enrichment is also detectable in hNCC regions primed for later activity. Using GCTA analyses, we suggest that 30% of the estimated variance in risk for nsCL/P in the European population can be attributed to common variants, with 25.5% contributed to by the 24 risk loci known to date. For each of these, we identify credible SNPs using a Bayesian refinement approach, with two loci harbouring only one probable causal variant. Finally, we demonstrate that there is no polygenic component of nsCL/P detectable that is shared with nonsyndromic cleft palate only (nsCPO). Our data suggest that, while common variants are strongly contributing to risk for nsCL/P, they do not seem to be involved in nsCPO which might be more often caused by rare deleterious variants. Our study generates novel insights into both nsCL/P and nsCPO etiology and provides a systematic framework for research into craniofacial development and malformation.

Fine-mapping the MHC locus in juvenile idiopathic arthritis (JIA) reveals genetic heterogeneity corresponding to distinct adult inflammatory arthritic diseases

Objectives

Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.

Methods

Dense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.

Results

We identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.

Conclusions

The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.

New insights into the genetic component of non-infectious uveitis through an Immunochip strategy

BACKGROUND

Large-scale genetic studies have reported several loci associated with specific disorders involving uveitis. Our aim was to identify genetic risk factors that might predispose to uveitis per se, independent of the clinical diagnosis, by performing a dense genotyping of immune-related loci.

METHODS

613 cases and 3693 unaffected controls from three European case/control sets were genotyped using the Immunochip array. Only patients with non-infectious non-anterior uveitis and without systemic features were selected. To perform a more comprehensive analysis of the human leucocyte antigen (HLA) region, SNPs, classical alleles and polymorphic amino acid variants were obtained via imputation. A meta-analysis combining the three case/control sets was conducted by the inverse variance method.

RESULTS

The highest peak belonged to the HLA region. A more detailed analysis of this signal evidenced a strong association between the classical allele HLA-A*2902 and birdshot chorioretinopathy (p=3.21E-35, OR=50.95). An omnibus test yielded HLA-A 62 and 63 as relevant amino acid positions for this disease. In patients with intermediate and posterior uveitis, the strongest associations belonged to the rs7197 polymorphism, within HLA-DRA (p=2.07E-11, OR=1.99), and the HLA-DR15 haplotype (DRB1*1501: p=1.16E-10, OR=2.08; DQA1*0102: p=4.37E-09, OR=1.77; DQB1*0602: p=7.26E-10, OR=2.02). Outside the HLA region, the MAP4K4/IL1R2 locus reached statistical significance (rs7608679: p=8.38E-07, OR=1.42). Suggestive associations were found at five other loci.

CONCLUSIONS

We have further interrogated the association between the HLA region and non-infectious non-anterior uveitis. In addition, we have identified a new non-HLA susceptibility factor and proposed additional risk loci with putative roles in this complex condition.

Genetic Analysis with the Immunochip Platform in Behçet Disease. Identification of Residues Associated in the HLA Class I Region and New Susceptibility Loci

Behcet's disease (BD) is an immuno-mediated vasculitis in which knowledge of its etiology and genetic basis is limited. To improve the current knowledge, a genetic analysis performed with the Immunochip platform was carried out in a population from Spain. A discovery cohort comprising 278 BD cases and 1,517 unaffected controls were genotyped using the Immunochip platform. The validation step was performed on an independent replication cohort composed of 130 BD cases and 600 additional controls. The strongest association signals were observed in the HLA class I region, being HLA-B*51 the highest peak (overall P = 6.82E-32, OR = 3.82). A step-wise conditional logistic regression with classical alleles identified HLA-B*57 and HLA-A*03 as additional independent markers. The amino acid model that best explained the association, includes the position 97 of the HLA-B molecule and the position 66 of the HLA-A. Among the non-HLA loci, the most significant in the discovery analysis were: IL23R (rs10889664: P = 3.81E-12, OR = 2.00), the JRKL/CNTN5 region (rs2848479: P = 5.00E-08, OR = 1.68) and IL12A (rs1874886: P = 6.67E-08, OR = 1.72), which were confirmed in the validation phase (JRKL/CNTN5 rs2848479: P = 3.29E-10, OR = 1.66; IL12A rs1874886: P = 1.62E-08, OR = 1.61). Our results confirm HLA-B*51 as a primary-association marker in predisposition to BD and suggest additional independent signals within the class I region, specifically in the genes HLA-A and HLA-B. Regarding the non-HLA genes, in addition to IL-23R, previously reported in our population; IL12A, described in other populations, was found to be a BD susceptibility factor also in Spaniards; finally, a new associated locus was found in the JRKL/CNTN5 region.

Effects of the genome on immune regulation in type 1 diabetes

Type 1 diabetes (T1DM) is a complex disease, arising through the interaction of an incompletely defined combination of genetic susceptibility and environmental factors. It is well accepted that T1DM results from selective immune-mediated destruction of the insulin-producing β cells in the islets of langerhans. Genetic studies of T1DM have identified several regions of susceptibility and identified major networks and pathways contributing to risk. In this study, we have taken advantages of the Immunochip fine-mapping genotyping data to address different aspects of immune regulation in relation to T1DM. First, we confirm that dense single nucleotide polymorphism (SNP) genotyping of the major histocompatibility complex/human leukocyte antigen (MHC/HLA) region capture the complex genetic contribution of this region to disease risk. Furthermore, it is shown that Immunochip genotyping can translate into a limited number of DRB1 and DQB1 amino acid residues that account for most of the HLA-risk. Second, we use the Immunochip data to look for functional significance by correlation to circulating levels of chemokines and demonstrate that genetic variation at chromosome 2, 3, and 6 correlates with circulating CCL2 and CCL4 in recent onset T1DM patients. Finally, we report that genetic variants predict autoantibody positivity in T1DM cases.

Design and Measurement of Nonislet-Specific Autoantibodies for the Type 1 Diabetes Genetics Consortium Autoantibody Workshop

The Type 1 Diabetes Genetics Consortium (T1DGC) comprised groups of investigators from many countries throughout the world, with a common goal of identifying genes predisposing to type 1 diabetes. The T1DGC ascertained and collected samples from families with two or more affected siblings with type 1 diabetes and generated a broad array of clinical, genetic, and immunologic data. The T1DGC Autoantibody Workshop was designed to distribute data for analyses to discover genes associated with autoantibodies in those with type 1 diabetes. In the T1DGC-affected sibling pair families, three T1DGC Network laboratories measured antibodies to the islet autoantigens GAD65 and the intracellular portion of protein tyrosine phosphatase (IA-2A). The availability of extensive genetic data provided an opportunity to investigate the associations between type 1 diabetes and other autoimmune diseases for which autoantibodies could be measured. Measurements of additional nonislet autoantibodies, including thyroid peroxidase, tissue transglutaminase, 21-hydroxylase, and the potassium/hydrogen ion transporter H+/K+-ATPase, were performed by the T1DGC laboratory at the Barbara Davis Center for Childhood Diabetes, Aurora, CO. Measurements of all autoantibodies were transmitted to the T1DGC Coordinating Center, and the data were made available to members of the T1DGC Autoantibody Working Groups for analysis in conjunction with existing T1DGC genetic data. This article describes the design of the T1DGC Autoantibody Workshop and the quality-control procedures to maintain and monitor the performance of each laboratory and provides the quality-control results for the nonislet autoantibody measurements.

Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk

Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.

Association of valine and leucine at HLA-DRB1 position 11 with radiographic progression in rheumatoid arthritis, independent of the shared epitope alleles but not independent of anti-citrullinated protein antibodies

OBJECTIVE

For decades it has been known that the HLA-DRB1 shared epitope (SE) alleles are associated with an increased risk of development and progression of rheumatoid arthritis (RA). Recently, the following variations in the peptide-binding grooves of HLA molecules that predispose to RA development have been identified: Val and Leu at HLA-DRB1 position 11, Asp at HLA-B position 9, and Phe at HLA-DPB1 position 9. This study was undertaken to investigate whether these variants are also associated with radiographic progression in RA, independent of SE and anti-citrullinated protein antibody (ACPA) status.

METHODS

A total of 4,911 radiograph sets from 1,878 RA patients included in the Leiden Early Arthritis Clinic (The Netherlands), Umeå (Sweden), Hospital Clinico San Carlos-Rheumatoid Arthritis (Spain), and National Data Bank for Rheumatic Diseases (US) cohorts were studied. HLA was imputed using single-nucleotide polymorphism data from an Immunochip, and the amino acids listed above were tested in relation to radiographic progression per cohort using an additive model. Results from the 4 cohorts were combined in inverse-variance weighted meta-analyses using a fixed-effects model. Analyses were conditioned on SE and ACPA status.

RESULTS

Val and Leu at HLA-DRB1 position 11 were associated with more radiographic progression (meta-analysis P = 5.11 × 10(-7)); this effect was independent of SE status (meta-analysis P = 0.022) but not independent of ACPA status. Phe at HLA-DPB1 position 9 was associated with more severe radiographic progression (meta-analysis P = 0.024), though not independent of SE status. Asp at HLA-B position 9 was not associated with radiographic progression.

CONCLUSION

Val and Leu at HLA-DRB1 position 11 conferred a risk of a higher rate of radiographic progression independent of SE status but not independent of ACPA status. These findings support the relevance of these amino acids at position 11.

Do Genetic Susceptibility Variants Associate with Disease Severity in Early Active Rheumatoid Arthritis?

OBJECTIVE

Genetic variants affect both the development and severity of rheumatoid arthritis (RA). Recent studies have expanded the number of RA susceptibility variants. We tested the hypothesis that these associated with disease severity in a clinical trial cohort of patients with early, active RA.

METHODS

We evaluated 524 patients with RA enrolled in the Combination Anti-Rheumatic Drugs in Early RA (CARDERA) trials. We tested validated susceptibility variants - 69 single-nucleotide polymorphisms (SNP), 15 HLA-DRB1 alleles, and amino acid polymorphisms in 6 HLA molecule positions - for their associations with progression in Larsen scoring, 28-joint Disease Activity Scores, and Health Assessment Questionnaire (HAQ) scores over 2 years using linear mixed-effects and latent growth curve models.

RESULTS

HLA variants were associated with joint destruction. The *04:01 SNP (rs660895, p = 0.0003), *04:01 allele (p = 0.0002), and HLA-DRβ1 amino acids histidine at position 13 (p = 0.0005) and valine at position 11 (p = 0.0012) significantly associated with radiological progression. This association was only significant in anticitrullinated protein antibody (ACPA)-positive patients, suggesting that while their effects were not mediated by ACPA, they only predicted joint damage in ACPA-positive RA. Non-HLA variants did not associate with radiograph damage (assessed individually and cumulatively as a weighted genetic risk score). Two SNP - rs11889341 (STAT4, p = 0.0001) and rs653178 (SH2B3-PTPN11, p = 0.0004) - associated with HAQ scores over 6-24 months.

CONCLUSION

HLA susceptibility variants play an important role in determining radiological progression in early, active ACPA-positive RA. Genome-wide and HLA-wide analyses across large populations are required to better characterize the genetic architecture of radiological progression in RA.

A large-scale genetic analysis reveals a strong contribution of the HLA class II region to giant cell arteritis susceptibility

We conducted a large-scale genetic analysis on giant cell arteritis (GCA), a polygenic immune-mediated vasculitis. A case-control cohort, comprising 1,651 case subjects with GCA and 15,306 unrelated control subjects from six different countries of European ancestry, was genotyped by the Immunochip array. We also imputed HLA data with a previously validated imputation method to perform a more comprehensive analysis of this genomic region. The strongest association signals were observed in the HLA region, with rs477515 representing the highest peak (p = 4.05 × 10(-40), OR = 1.73). A multivariate model including class II amino acids of HLA-DRβ1 and HLA-DQα1 and one class I amino acid of HLA-B explained most of the HLA association with GCA, consistent with previously reported associations of classical HLA alleles like HLA-DRB1(∗)04. An omnibus test on polymorphic amino acid positions highlighted DRβ1 13 (p = 4.08 × 10(-43)) and HLA-DQα1 47 (p = 4.02 × 10(-46)), 56, and 76 (both p = 1.84 × 10(-45)) as relevant positions for disease susceptibility. Outside the HLA region, the most significant loci included PTPN22 (rs2476601, p = 1.73 × 10(-6), OR = 1.38), LRRC32 (rs10160518, p = 4.39 × 10(-6), OR = 1.20), and REL (rs115674477, p = 1.10 × 10(-5), OR = 1.63). Our study provides evidence of a strong contribution of HLA class I and II molecules to susceptibility to GCA. In the non-HLA region, we confirmed a key role for the functional PTPN22 rs2476601 variant and proposed other putative risk loci for GCA involved in Th1, Th17, and Treg cell function.

Fine mapping seronegative and seropositive rheumatoid arthritis to shared and distinct HLA alleles by adjusting for the effects of heterogeneity

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.

Immunochip analysis identifies multiple susceptibility loci for systemic sclerosis

In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, provided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci.

Association of granulomatosis with polyangiitis (Wegener's) with HLA-DPB1*04 and SEMA6A gene variants: evidence from genome-wide analysis

OBJECTIVE

To identify genetic determinants of granulomatosis with polyangiitis (Wegener's) (GPA).

METHODS

We carried out a genome-wide association study (GWAS) of 492 GPA cases and 1,506 healthy controls (white subjects of European descent), followed by replication analysis of the most strongly associated signals in an independent cohort of 528 GPA cases and 1,228 controls.

RESULTS

Genome-wide significant associations were identified in 32 single-nucleotide polymorphic (SNP) markers across the HLA region, the majority of which were located in the HLA-DPB1 and HLA-DPA1 genes encoding the class II major histocompatibility complex (MHC) DPβ chain 1 and DPα chain 1 proteins, respectively. Peak association signals in these 2 genes, emanating from SNPs rs9277554 (for DPβ chain 1) and rs9277341 (DPα chain 1) were strongly replicated in an independent cohort (in the combined analysis of the initial cohort and the replication cohort, P = 1.92 × 10(-50) and 2.18 × 10(-39) , respectively). Imputation of classic HLA alleles and conditional analyses revealed that the SNP association signal was fully accounted for by the classic HLA-DPB1*04 allele. An independent single SNP, rs26595, near SEMA6A (the gene for semaphorin 6A) on chromosome 5, was also associated with GPA, reaching genome-wide significance in a combined analysis of the GWAS and replication cohorts (P = 2.09 × 10(-8) ).

CONCLUSION

We identified the SEMA6A and HLA-DP loci as significant contributors to risk for GPA, with the HLA-DPB1*04 allele almost completely accounting for the MHC association. These two associations confirm the critical role of immunogenetic factors in the development of GPA.

Recursive organizer (ROR): an analytic framework for sequence-based association analysis

The advent of next-generation sequencing technologies affords the ability to sequence thousands of subjects cost-effectively, and is revolutionizing the landscape of genetic research. With the evolving genotyping/sequencing technologies, it is not unrealistic to expect that we will soon obtain a pair of diploidic fully phased genome sequences from each subject in the near future. Here, in light of this potential, we propose an analytic framework called, recursive organizer (ROR), which recursively groups sequence variants based upon sequence similarities and their empirical disease associations, into fewer and potentially more interpretable super sequence variants (SSV). As an illustration, we applied ROR to assess an association between HLA-DRB1 and type 1 diabetes (T1D), discovering SSVs of HLA-DRB1 with sequence data from the Wellcome Trust Case Control Consortium. Specifically, ROR reduces 36 observed unique HLA-DRB1 sequences into 8 SSVs that empirically associate with T1D, a fourfold reduction of sequence complexity. Using HLA-DRB1 data from Type 1 Diabetes Genetics Consortium as cases and data from Fred Hutchinson Cancer Research Center as controls, we are able to validate associations of these SSVs with T1D. Further, SSVs consist of nine nucleotides, and each associates with its corresponding amino acids. Detailed examination of these selected amino acids reveals their potential functional roles in protein structures and possible implication to the mechanism of T1D.

Non-random mating, parent-of-origin, and maternal-fetal incompatibility effects in schizophrenia

Although the association of common genetic variation in the extended MHC region with schizophrenia is the most significant yet discovered, the MHC region is one of the more complex regions of the human genome, with unusually high gene density and long-range linkage disequilibrium. The statistical test on which the MHC association is based is a relatively simple, additive model which uses logistic regression of SNP genotypes to predict case-control status. However, it is plausible that more complex models underlie this association. Using a well-characterized sample of trios, we evaluated more complex models by looking for evidence for: (a) non-random mating for HLA alleles, schizophrenia risk profiles, and ancestry; (b) parent-of-origin effects for HLA alleles; and (c) maternal-fetal genotype incompatibility in the HLA. We found no evidence for non-random mating in the parents of individuals with schizophrenia in terms of MHC genotypes or schizophrenia risk profile scores. However, there was evidence of non-random mating that appeared mostly to be driven by ancestry. We did not detect over-transmission of HLA alleles to affected offspring via the general TDT test (without regard to parent of origin) or preferential transmission via paternal or maternal inheritance. We evaluated the hypothesis that maternal-fetal HLA incompatibility may increase risk for schizophrenia using eight classical HLA loci. The most significant alleles were in HLA-B, HLA-C, HLA-DQB1, and HLA-DRB1 but none was significant after accounting for multiple comparisons. We did not find evidence to support more complex models of gene action, but statistical power may have been limiting.

A unified framework for haplotype inference in nuclear families

Many large genome-wide association studies include nuclear families with more than one child (trio families), allowing for analysis of differences between siblings (sib pair analysis). Statistical power can be increased when haplotypes are used instead of genotypes. Currently, haplotype inference in families with more than one child can be performed either using the familial information or statistical information derived from the population samples but not both. Building on our recently proposed tree-based deterministic framework (TDS) for trio families, we augment its applicability to general nuclear families. We impose a minimum recombinant approach locally and independently on each multiple children family, while resorting to the population-derived information to solve the remaining ambiguities. Thus our framework incorporates all available information (familial and population) in a given study. We demonstrate that using all the constraints in our approach we can have gains in the accuracy as opposed to breaking the multiple children families to separate trios and resorting to a trio inference algorithm or phasing each family in isolation. We believe that our proposed framework could be the method of choice for haplotype inference in studies that include nuclear families with multiple children. Our software (tds2.0) is downloadable from www.ee.columbia.edu/∼anastas/tds.

Association analysis of the extended MHC region in celiac disease implicates multiple independent susceptibility loci

Celiac disease is a common autoimmune disease caused by sensitivity to the dietary protein gluten. Forty loci have been implicated in the disease. All disease loci have been characterized as low-penetrance, with the exception of the high-risk genotypes in the HLA-DQA1 and HLA-DQB1 genes, which are necessary but not sufficient to cause the disease. The very strong effects from the known HLA loci and the genetically complex nature of the major histocompatibility complex (MHC) have precluded a thorough investigation of the region. The purpose of this study was to test the hypothesis that additional celiac disease loci exist within the extended MHC (xMHC). A set of 1898 SNPs was analyzed for association across the 7.6 Mb xMHC region in 1668 confirmed celiac disease cases and 517 unaffected controls. Conditional recursive partitioning was used to create an informative indicator of the known HLA-DQA1 and HLA-DQB1 high-risk genotypes that was included in the association analysis to account for their effects. A linkage disequilibrium-based grouping procedure was utilized to estimate the number of independent celiac disease loci present in the xMHC after accounting for the known effects. There was significant statistical evidence for four new independent celiac disease loci within the classic MHC region. This study is the first comprehensive association analysis of the xMHC in celiac disease that specifically accounts for the known HLA disease genotypes and the genetic complexity of the region.

Classical HLA-DRB1 and DPB1 alleles account for HLA associations with primary biliary cirrhosis

Susceptibility to primary biliary cirrhosis (PBC) is strongly associated with HLA region polymorphisms. To determine if associations can be explained by classical HLA determinants we studied Italian 676 cases and 1440 controls with genotyped with dense single nucleotide polymorphisms (SNPs) for which classical HLA alleles and amino acids were imputed. Although previous genome-wide association studies and our results show stronger SNP associations near DQB1, we demonstrate that the HLA signals can be attributed to classical DRB1 and DPB1 genes. Strong support for the predominant role of DRB1 is provided by our conditional analyses. We also demonstrate an independent association of DPB1. Specific HLA-DRB1 genes (*08, *11 and *14) account for most of the DRB1 association signal. Consistent with previous studies, DRB1*08 (p = 1.59 × 10⁻¹¹) was the strongest predisposing allele where as DRB1*11 (p = 1.42 × 10⁻¹⁰) was protective. Additionally DRB1*14 and the DPB1 association (DPB1*03:01) (p = 9.18 × 10⁻⁷) were predisposing risk alleles. No signal was observed in the HLA class 1 or class 3 regions. These findings better define the association of PBC with HLA and specifically support the role of classical HLA-DRB1 and DPB1 genes and alleles in susceptibility to PBC.

Interaction between Treg apoptosis pathways, Treg function and HLA risk evolves during type 1 diabetes pathogenesis

We have previously reported increased apoptosis of regulatory T cells (Tregs) in recent-onset Type 1 Diabetes subjects (RO T1D) in the honeymoon phase and in multiple autoantibody-positive (Ab+) subjects, some of which are developing T1D. We have also reported that increased Treg apoptosis was associated with High HLA risk and that it subsided with cessation of honeymoon period. In this report, we present results generated using genetics, genomics, functional cell-based assays and flow cytometry to assess cellular changes at the T-cell level during T1D pathogenesis. We measured ex vivo Treg apoptosis and Treg function, surface markers expression, expression of HLA class II genes, the influence of HLA risk on Treg apoptosis and function, and evaluated contribution of genes reported to be involved in the apoptosis process. This integrated comprehensive approach uncovered important information that can serve as a basis for future studies aimed to modulate Treg cell responsiveness to apoptotic signals in autoimmunity. For example, T1D will progress in those subjects where increased Treg apoptosis is accompanied with decreased Treg function. Furthermore, Tregs from High HLA risk healthy controls had increased Treg apoptosis levels and overexpressed FADD but not Fas/FasL. Tregs from RO T1D subjects in the honeymoon phase were primarily dying through withdrawal of growth hormones with contribution of oxidative stress, mitochondrial apoptotic pathways, and employment of TNF-receptor family members. Ab+ subjects, however, expressed high inflammation level, which probably contributed to Treg apoptosis, although other apoptotic pathways were also activated: withdrawal of growth hormones, oxidative stress, mitochondrial apoptosis and Fas/FasL apoptotic pathways. The value of these results lie in potentially different preventive treatment subjects would receive depending on disease progression stage when treated.

Amino acid position 11 of HLA-DRβ1 is a major determinant of chromosome 6p association with ulcerative colitis

The major histocompatibility complex (MHC) on chromosome 6p is an established risk locus for ulcerative colitis (UC) and Crohn's disease (CD). We aimed to better define MHC association signals in UC and CD by combining data from dense single-nucleotide polymorphism (SNP) genotyping and from imputation of classical human leukocyte antigen (HLA) types, their constituent SNPs and corresponding amino acids in 562 UC, 611 CD and 1428 control subjects. Univariate and multivariate association analyses were performed, controlling for ancestry. In univariate analyses, absence of the rs9269955 C allele was strongly associated with risk for UC (P = 2.67 × 10(-13)). rs9269955 is a SNP in the codon for amino acid position 11 of HLA-DRβ1, located in the P6 pocket of the HLA-DR antigen binding cleft. This amino acid position was also the most significantly UC-associated amino acid in omnibus tests (P = 2.68 × 10(-13)). Multivariate modeling identified rs9269955-C and 13 other variants in best predicting UC vs control status. In contrast, there was only suggestive association evidence between the MHC and CD. Taken together, these data demonstrate that variation at HLA-DRβ1, amino acid 11 in the P6 pocket of the HLA-DR complex antigen binding cleft is a major determinant of chromosome 6p association with UC.

Congruence as a measurement of extended haplotype structure across the genome

Background

Historically, extended haplotypes have been defined using only a few data points, such as alleles for several HLA genes in the MHC. High-density SNP data, and the increasing affordability of whole genome SNP typing, creates the opportunity to define higher resolution extended haplotypes. This drives the need for new tools that support quantification and visualization of extended haplotypes as defined by as many as 2000 SNPs. Confronted with high-density SNP data across the major histocompatibility complex (MHC) for 2,300 complete families, compiled by the Type 1 Diabetes Genetics Consortium (T1DGC), we developed software for studying extended haplotypes.

Methods

The software, called ExHap (Extended Haplotype), uses a similarity measurement we term congruence to identify and quantify long-range allele identity. Using ExHap, we analyzed congruence in both the T1DGC data and family-phased data from the International HapMap Project.

Results

Congruent chromosomes from the T1DGC data have between 96.5% and 99.9% allele identity over 1,818 SNPs spanning 2.64 megabases of the MHC (HLA-DRB1 to HLA-A). Thirty-three of 132 DQ-DR-B-A defined haplotype groups have > 50% congruent chromosomes in this region. For example, 92% of chromosomes within the DR3-B8-A1 haplotype are congruent from HLA-DRB1 to HLA-A (99.8% allele identity). We also applied ExHap to all 22 autosomes for both CEU and YRI cohorts from the International HapMap Project, identifying multiple candidate extended haplotypes.

Conclusions

Long-range congruence is not unique to the MHC region. Patterns of allele identity on phased chromosomes provide a simple, straightforward approach to visually and quantitatively inspect complex long-range structural patterns in the genome. Such patterns aid the biologist in appreciating genetic similarities and differences across cohorts, and can lead to hypothesis generation for subsequent studies.

Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis

The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to alleles in HLA-DRB1. However, debate persists about the identity of the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 individuals with seropositive rheumatoid arthritis (cases) and 14,974 unaffected controls, we imputed and tested classical alleles and amino acid polymorphisms in HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1 and HLA-DRB1, as well as 3,117 SNPs across the MHC. Conditional and haplotype analyses identified that three amino acid positions (11, 71 and 74) in HLA-DRβ1 and single-amino-acid polymorphisms in HLA-B (at position 9) and HLA-DPβ1 (at position 9), which are all located in peptide-binding grooves, almost completely explain the MHC association to rheumatoid arthritis risk. This study shows how imputation of functional variation from large reference panels can help fine map association signals in the MHC.

Immunogenetics of spontaneous control of HIV

Host genetic variation is presently estimated to account for about one-fourth of the observed differences in control of HIV across infected individuals. Genome-wide association studies have confirmed that polymorphism within the HLA class I locus is the primary host genetic contributor to determining outcome after infection. Here we progress beyond the genetic associations alone to consider the functional explanations for these correlations. In this process, the complex and multidimensional effects of HLA molecules in viral disease become apparent.

The past, present, and future of genetic associations in type 1 diabetes

Type 1 diabetes mellitus (T1DM) is an autoimmune disease affecting approximately one in 300 individuals in the United States. The majority of genetic research to date has focused on the heritability that predisposes to islet autoimmunity and T1DM. The evidence so far points to T1DM being a polygenic, common, complex disease with major susceptibility lying in the major histocompatibility complex (MHC) on chromosome 6 with other smaller effects seen in loci outside of the MHC. With recent advances in technology, novel means of exploring the human genome have given way to new information in the development of T1DM. The newest technologies, namely high-throughput polymorphism typing and sequencing, have led to a paradigm shift in studying common diseases such as T1DM. In this review we highlight the advances in genetic associations in T1DM in the last several decades and how they have led to a better understanding of T1DM pathogenesis.

Replication and further characterization of a Type 1 diabetes-associated locus at the telomeric end of the major histocompatibility complex

BACKGROUND

We recently reported an association between Type 1 diabetes and the telomeric major histocompatibility complex (MHC) single nucleotide polymorphism (SNP) rs1233478. As further families have been analyzed in the Type 1 Diabetes Genetics Consortium (T1DGC), we tested replication of the association and, with more data, analyzed haplotypic associations.

METHODS

An additional 2717 case and 1315 control chromosomes have been analyzed from the T1DGC, with human leukocyte antigen (HLA) typing and data for 2837 SNPs across the MHC region.

RESULTS

We confirmed the association of rs1233478 (new data only: P=2.2E-5, OR=1.4). We also found two additional SNPs nearby that were significantly associated with Type 1 diabetes (new data only rs3131020: P=8.3E-9, OR=0.65; rs1592410: P=2.2E-8, OR=1.5). For studies of Type 1 diabetes in the MHC region, it is critical to account for linkage disequilibrium with the HLA genes. Logistic regression analysis of these new data indicated that the effects of rs3131020 and rs1592410 on Type 1 diabetes risk are independent of HLA alleles (rs3131020: P=2.3E-3, OR=0.73; rs1592410: P=2.1E-3, OR=1.4). Haplotypes of 12 SNPs (including the three highly significant SNPs) stratify diabetes risk (high risk, protective, and neutral), with high-risk haplotypes limited to approximately 20,000 bp in length. The 20,000-bp region is telomeric of the UBD gene and contains LOC729653, a hypothetical gene.

CONCLUSIONS

We believe that polymorphisms of the telomeric MHC locus LOC729653 may confer risk for Type 1 diabetes.

The HLA-B 3906 allele imparts a high risk of diabetes only on specific HLA-DR/DQ haplotypes

AIMS/HYPOTHESIS

We investigated the risk associated with HLA-B*39 alleles in the context of specific HLA-DR/DQ haplotypes.

METHODS

We studied a readily available dataset from the Type 1 Diabetes Genetics Consortium that consists of 2,300 affected sibling pair families genotyped for both HLA alleles and 2,837 single nucleotide polymorphisms across the major histocompatibility complex region.

RESULTS

The B*3906 allele significantly enhanced the risk of type 1 diabetes when present on specific HLA-DR/DQ haplotypes (DRB1 0801-DQB1 0402: p = 1.6 × 10(-6), OR 25.4; DRB1 0101-DQB1 0501: p = 4.9 × 10(-5), OR 10.3) but did not enhance the risk of DRB1 0401-DQB1 0302 haplotypes. In addition, the B 3901 allele enhanced risk on the DRB1 1601-DQB1 0502 haplotype (p = 3.7 × 10(-3), OR 7.2).

CONCLUSIONS/INTERPRETATION

These associations indicate that the B 39 alleles significantly increase risk when present on specific HLA-DR/DQ haplotypes, and HLA-B typing in concert with specific HLA-DR/DQ genotypes should facilitate genetic prediction of type 1 diabetes, particularly in a research setting.

Dominant suppression of Addison's disease associated with HLA-B15

CONTEXT

Autoimmune Addison's disease (AD) is the major cause of primary adrenal failure in developed nations. Autoantibodies to 21-hydroxylase (21OH-AA) are associated with increased risk of progression to AD. Highest genetic risk is associated with the Major Histocompatibility region (MHC), specifically human leukocyte antigen (HLA)-DR3 haplotypes (containing HLA-B8) and HLA-DR4.

OBJECTIVE

The objective of the study was the further characterization of AD risk associated with MHC alleles.

DESIGN, SETTING, AND PARTICIPANTS

MHC genotypes were determined for HLA-DRB1, DQA1, DQB1, MICA, HLA-B, and HLA-A in 168 total individuals with 21OH-AA (85 with AD at referral and 83 with positive 21OH-AA but without AD at referral).

MAIN OUTCOME MEASURE(S)

Genotype was evaluated in 21OH-AA-positive individuals. Outcomes were compared with general population controls and type 1 diabetes patients.

RESULTS

In HLA-DR4+ individuals, HLA-B15 was found in only one of 55 (2%) with AD vs. 24 of 63 (40%) 21OH-AA-positive nonprogressors (P = 2 × 10(-7)) and 518 of 1558 (33%) HLA-DR4 patients with type 1 diabetes (P = 1 × 10(-8)). On prospective follow-up, none of the HLA-B15-positive, 21-hydroxylase-positive individuals progressed to AD vs. 25% non-HLA-B15 autoantibody-positive individuals by life table analysis (P = 0.03). Single nucleotide polymorphism analysis revealed the HLA-DR/DQ region associated with risk and HLA-B15 were separated by multiple intervening single-nucleotide polymorphism haplotypes.

CONCLUSIONS

HLA-B15 is not associated with protection from 21OH-AA formation but is associated with protection from progression to AD in 21OH-AA-positive individuals. To our knowledge, this is one of the most dramatic examples of genetic disease suppression in individuals who already have developed autoantibodies and of novel dominant suppression of an autoimmune disease by a class I HLA allele.

The major genetic determinants of HIV-1 control affect HLA class I peptide presentation

Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified >300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alleles. These results implicate the nature of the HLA-viral peptide interaction as the major factor modulating durable control of HIV infection.

Conditional meta-analysis stratifying on detailed HLA genotypes identifies a novel type 1 diabetes locus around TCF19 in the MHC

The human leukocyte antigen (HLA) class II genes HLA-DRB1, -DQA1 and -DQB1 are the strongest genetic factors for type 1 diabetes (T1D). Additional loci in the major histocompatibility complex (MHC) are difficult to identify due to the region's high gene density and complex linkage disequilibrium (LD). To facilitate the association analysis, two novel algorithms were implemented in this study: one for phasing the multi-allelic HLA genotypes in trio families, and one for partitioning the HLA strata in conditional testing. Screening and replication were performed on two large and independent datasets: the Wellcome Trust Case-Control Consortium (WTCCC) dataset of 2,000 cases and 1,504 controls, and the T1D Genetics Consortium (T1DGC) dataset of 2,300 nuclear families. After imputation, the two datasets have 1,941 common SNPs in the MHC, of which 22 were successfully tested and replicated based on the statistical testing stratifying on the detailed DRB1 and DQB1 genotypes. Further conditional tests using the combined dataset confirmed eight novel SNP associations around 31.3 Mb on chromosome 6 (rs3094663, p = 1.66 × 10(-11) and rs2523619, p = 2.77 × 10(-10) conditional on the DR/DQ genotypes). A subsequent LD analysis established TCF19, POU5F1, CCHCR1 and PSORS1C1 as potential causal genes for the observed association.

Haplotype analysis discriminates genetic risk for DR3-associated endocrine autoimmunity and helps define extreme risk for Addison's disease

CONTEXT

Multiple autoimmune disorders (e.g. Addison's disease, type 1 diabetes, celiac disease) are associated with HLA-DR3, but it is likely that alleles of additional genes in linkage disequilibrium with HLA-DRB1 contribute to disease.

OBJECTIVE

The objective of the study was to characterize major histocompatability complex (MHC) haplotypes conferring extreme risk for autoimmune Addison's disease (AD).

DESIGN, SETTING, AND PARTICIPANTS

Eighty-six 21-hydroxylase autoantibody-positive, nonautoimmune polyendocrine syndrome type 1, Caucasian individuals collected from 1992 to 2009 with clinical AD from 68 families (12 multiplex and 56 simplex) were genotyped for HLA-DRB1, HLA-DQB1, MICA, HLA-B, and HLA-A as well as high density MHC single-nucleotide polymorphism (SNP) analysis for 34.

MAIN OUTCOME MEASURES

AD and genotype were measured.

RESULT

Ninety-seven percent of the multiplex individuals had both HLA-DR3 and HLA-B8 vs. 60% of simplex AD patients (P = 9.72 × 10(-4)) and 13% of general population controls (P = 3.00 × 10(-19)). The genotype DR3/DR4 with B8 was present in 85% of AD multiplex patients, 24% of simplex patients, and 1.5% of control individuals (P = 4.92 × 10(-191)). The DR3-B8 haplotype of AD patients had HLA-A1 less often (47%) than controls (81%, P = 7.00 × 10(-5)) and type 1 diabetes patients (73%, P = 1.93 × 10(-3)). Analysis of 1228 SNPs across the MHC for individuals with AD revealed a shorter conserved haplotype (3.8) with the loss of the extended conserved 3.8.1 haplotype approximately halfway between HLA-B and HLA-A.

CONCLUSION

Extreme risk for AD, especially in multiplex families, is associated with haplotypic DR3 variants, in particular a portion (3.8) but not all of the conserved 3.8.1 haplotype.