Javier Gutierrez-Achury

Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.

Identification of multiple independent susceptibility loci in the HLA region in Behçet's disease

Behçets disease is an inflammatory disease characterized by recurrent oral and genital ulcers and significant organ involvement. Localizing the genetic association between HLA-B*51 and Behçets disease and exploring additional susceptibility loci in the human leukocyte antigen (HLA) region are complicated by the strong linkage disequilibrium in this region. We genotyped 8,572 variants in the extended HLA locus and carried out imputation and meta-analysis of 24,834 variants in 2 independent Behçets disease cohorts from 2 ancestry groups. Genotyped SNPs were used to infer classical HLA alleles in the HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1 and HLA-DRB1 loci. Our data suggest that the robust HLA-B*51 association in Behçets disease is explained by a variant located between the HLA-B and MICA genes (rs116799036: odds ratio (OR) = 3.88, P = 9.42 × 10−50). Three additional independent genetic associations within PSORS1C1 (rs12525170: OR = 3.01, P = 3.01 × 10−26), upstream of HLA-F-AS1 (rs114854070: OR = 1.95, P = 7.84 × 10−14) and with HLA-Cw*1602 (OR = 5.38, P = 6.07 × 10−18) were also identified and replicated.

Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease

Genetic association studies have identified 215 risk loci for inflammatory bowel disease, thereby uncovering fundamental aspects of its molecular biology. We performed a genome-wide association study of 25,305 individuals and conducted a meta-analysis with published summary statistics, yielding a total sample size of 59,957 subjects. We identified 25 new susceptibility loci, 3 of which contain integrin genes that encode proteins in pathways that have been identified as important therapeutic targets in inflammatory bowel disease. The associated variants are correlated with expression changes in response to immune stimulus at two of these genes (ITGA4 and ITGB8) and at previously implicated loci (ITGAL and ICAM1). In all four cases, the expression-increasing allele also increases disease risk. We also identified likely causal missense variants in a gene implicated in primary immune deficiency, PLCG2, and a negative regulator of inflammation, SLAMF8. Our results demonstrate that new associations at common variants continue to identify genes relevant to therapeutic target identification and prioritization.

Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

Background The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case–control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD.

Shared genetics in coeliac disease and other immune‐mediated diseases

Abstract.  Gutierrez‐Achury J, Coutinho de Almeida R, Wijmenga C (University Medical Centre Groningen and University of Groningen, Groningen, the Netherlands; University of Brasilia School of Health Sciences, Brasilia, DF, Brazil). Shared genetics in coeliac disease and other immune‐mediated diseases (Symposium). J Intern Med 2011; 269: 591–603.

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with ‘true’ genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05–0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r2, increased from 0.61 to 0.71. We also saw improved imputation accuracy for other European populations (in the British samples, r2 improved from 0.58 to 0.65, and in the Italians from 0.43 to 0.47). A combined reference set comprising 1000G and GoNL improved the imputation of rare variants even further. The Italian samples benefitted the most from this combined reference (the mean r2 increased from 0.47 to 0.50). We conclude that the creation of a large population-specific reference is advantageous for imputing rare variants and that a combined reference panel across multiple populations yields the best imputation results.

Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases.

Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygotes two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 × 10−12; T1D, P = 2.4 × 10−10; psoriasis, P = 5.9 × 10−6; celiac disease, P = 1.2 × 10−87). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 × 10−3; T1D, P = 8.6 × 10−27; celiac disease, P = 6.0 × 10−100). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.

Fine mapping in the MHC region accounts for 18% additional genetic risk for celiac disease

Although dietary gluten is the trigger for celiac disease, risk is strongly influenced by genetic variation in the major histocompatibility complex (MHC) region. We fine mapped the MHC association signal to identify additional risk factors independent of the HLA-DQA1 and HLA-DQB1 alleles and observed five new associations that account for 18% of the genetic risk. Taking these new loci together with the 57 known non-MHC loci, genetic variation can now explain up to 48% of celiac disease heritability.

Genome-wide association study of primary sclerosing cholangitis identifies new risk loci and quantifies the genetic relationship with inflammatory bowel disease

Primary sclerosing cholangitis (PSC) is a rare progressive disorder leading to bile duct destruction; ∼75% of patients have comorbid inflammatory bowel disease (IBD). We undertook the largest genome-wide association study of PSC (4,796 cases and 19,955 population controls) and identified four new genome-wide significant loci. The most associated SNP at one locus affects splicing and expression of UBASH3A, with the protective allele (C) predicted to cause nonstop-mediated mRNA decay and lower expression of UBASH3A. Further analyses based on common variants suggested that the genome-wide genetic correlation (rG) between PSC and ulcerative colitis (UC) (rG = 0.29) was significantly greater than that between PSC and Crohns disease (CD) (rG = 0.04) (P = 2.55 × 10−15). UC and CD were genetically more similar to each other (rG = 0.56) than either was to PSC (P < 1.0 × 10−15). Our study represents a substantial advance in understanding of the genetics of PSC.

Systematic annotation of celiac disease loci refines pathological pathways and suggests a genetic explanation for increased interferon-gamma levels

Although genome-wide association studies and fine mapping have identified 39 non-HLA loci associated with celiac disease (CD), it is difficult to pinpoint the functional variants and susceptibility genes in these loci. We applied integrative approaches to annotate and prioritize functional single nucleotide polymorphisms (SNPs), genes and pathways affected in CD. CD-associated SNPs were intersected with regulatory elements categorized by the ENCODE project to prioritize functional variants, while results from cis-expression quantitative trait loci (eQTL) mapping in 1469 blood samples were combined with co-expression analyses to prioritize causative genes. To identify the key cell types involved in CD, we performed pathway analysis on RNA-sequencing data from different immune cell populations and on publicly available expression data on non-immune tissues. We discovered that CD SNPs are significantly enriched in B-cell-specific enhancer regions, suggesting that, besides T-cell processes, B-cell responses play a major role in CD. By combining eQTL and co-expression analyses, we prioritized 43 susceptibility genes in 36 loci. Pathway and tissue-specific expression analyses on these genes suggested enrichment of CD genes in the Th1, Th2 and Th17 pathways, but also predicted a role for four genes in the intestinal barrier function. We also discovered an intricate transcriptional connectivity between CD susceptibility genes and interferon-γ, a key effector in CD, despite the absence of CD-associated SNPs in the IFNG locus. Using systems biology, we prioritized the CD-associated functional SNPs and genes. By highlighting a role for B cells in CD, which classically has been described as a T-cell-driven disease, we offer new insights into the mechanisms and pathways underlying CD.