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.
With mutations continually occurring in each protein-coding gene (at a rate of ~1 × 10-5 per gene per generation for nonsynonymous variants)36-39 and fitness losses of less than 1% for most novel ...nonsynonymous mutations29-31,34, almost every gene is expected to harbor functionally important variants that can be tested through sequencing, even if these variants are rare. ...the strong interest in exome sequencing stems from three factors: the potential to identify many genes underlying complex traits, straightforward functional annotation of coding variation and a substantially lower cost (approximately five times lower) than that of whole-genome sequencing. ...as sample size increases, the number of observed variants grows much faster than is predicted by the neutral model with constant population size41,42 (Fig. 1).
Carbamazepine causes various forms of hypersensitivity reactions, ranging from maculopapular exanthema to severe blistering reactions. The HLA-B*1502 allele has been shown to be strongly correlated ...with carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS-TEN) in the Han Chinese and other Asian populations but not in European populations.
We performed a genomewide association study of samples obtained from 22 subjects with carbamazepine-induced hypersensitivity syndrome, 43 subjects with carbamazepine-induced maculopapular exanthema, and 3987 control subjects, all of European descent. We tested for an association between disease and HLA alleles through proxy single-nucleotide polymorphisms and imputation, confirming associations by high-resolution sequence-based HLA typing. We replicated the associations in samples from 145 subjects with carbamazepine-induced hypersensitivity reactions.
The HLA-A*3101 allele, which has a prevalence of 2 to 5% in Northern European populations, was significantly associated with the hypersensitivity syndrome (P=3.5×10(-8)). An independent genomewide association study of samples from subjects with maculopapular exanthema also showed an association with the HLA-A*3101 allele (P=1.1×10(-6)). Follow-up genotyping confirmed the variant as a risk factor for the hypersensitivity syndrome (odds ratio, 12.41; 95% confidence interval CI, 1.27 to 121.03), maculopapular exanthema (odds ratio, 8.33; 95% CI, 3.59 to 19.36), and SJS-TEN (odds ratio, 25.93; 95% CI, 4.93 to 116.18).
The presence of the HLA-A*3101 allele was associated with carbamazepine-induced hypersensitivity reactions among subjects of Northern European ancestry. The presence of the allele increased the risk from 5.0% to 26.0%, whereas its absence reduced the risk from 5.0% to 3.8%. (Funded by the U.K. Department of Health and others.).
Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets ...in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
Rheumatoid arthritis is a chronic inflammatory disease with a substantial genetic component. Susceptibility to disease has been linked with a region on chromosome 2q.
We tested single-nucleotide ...polymorphisms (SNPs) in and around 13 candidate genes within the previously linked chromosome 2q region for association with rheumatoid arthritis. We then performed fine mapping of the STAT1-STAT4 region in a total of 1620 case patients with established rheumatoid arthritis and 2635 controls, all from North America. Implicated SNPs were further tested in an independent case-control series of 1529 patients with early rheumatoid arthritis and 881 controls, all from Sweden, and in a total of 1039 case patients and 1248 controls from three series of patients with systemic lupus erythematosus.
A SNP haplotype in the third intron of STAT4 was associated with susceptibility to both rheumatoid arthritis and systemic lupus erythematosus. The minor alleles of the haplotype-defining SNPs were present in 27% of chromosomes of patients with established rheumatoid arthritis, as compared with 22% of those of controls (for the SNP rs7574865, P=2.81x10(-7); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.32). The association was replicated in Swedish patients with recent-onset rheumatoid arthritis (P=0.02) and matched controls. The haplotype marked by rs7574865 was strongly associated with lupus, being present on 31% of chromosomes of case patients and 22% of those of controls (P=1.87x10(-9); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.55). Homozygosity of the risk allele, as compared with absence of the allele, was associated with a more than doubled risk for lupus and a 60% increased risk for rheumatoid arthritis.
A haplotype of STAT4 is associated with increased risk for both rheumatoid arthritis and systemic lupus erythematosus, suggesting a shared pathway for these illnesses.
The major histocompatibility complex (MHC) region is strongly associated with multiple sclerosis (MS) susceptibility. HLA-DRB1*15:01 has the strongest effect, and several other alleles have been ...reported at different levels of validation. Using SNP data from genome-wide studies, we imputed and tested classical alleles and amino acid polymorphisms in 8 classical human leukocyte antigen (HLA) genes in 5,091 cases and 9,595 controls. We identified 11 statistically independent effects overall: 6 HLA-DRB1 and one DPB1 alleles in class II, one HLA-A and two B alleles in class I, and one signal in a region spanning from MICB to LST1. This genomic segment does not contain any HLA class I or II genes and provides robust evidence for the involvement of a non-HLA risk allele within the MHC. Interestingly, this region contains the TNF gene, the cognate ligand of the well-validated TNFRSF1A MS susceptibility gene. The classical HLA effects can be explained to some extent by polymorphic amino acid positions in the peptide-binding grooves. This study dissects the independent effects in the MHC, a critical region for MS susceptibility that harbors multiple risk alleles.
Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk ...factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype–phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.
Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted ...complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions.
We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates.
We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09-1.40, P = 7 × 10(-4)). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates.
We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.
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.
Objective:
To perform a 1‐stage meta‐analysis of genome‐wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci.
...Methods:
We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta‐analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease.
Results:
We meta‐analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934T at 3p24.1 (odds ratio OR, 1.17; p = 1.6 × 10−8) near EOMES, rs2150702G in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p = 3.3 × 10−8), and rs6718520A in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p = 3.4 × 10−8). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 × 10−6, some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1).
Interpretation:
We have performed a meta‐analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS. ANN NEUROL 2011;70:897–912