Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.     

Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.     

Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes

Genome-wide association studies have revealed that common noncoding variants in MTNR1B (encoding melatonin receptor 1B, also known as MT(2)) increase type 2 diabetes (T2D) risk(1,2). Although the strongest association signal was highly significant (P < 1 × 10(-20)), its contribution to T2D risk was modest (odds ratio (OR) of ～1.10-1.15)(1-3). We performed large-scale exon resequencing in 7,632 Europeans, including 2,186 individuals with T2D, and identified 40 nonsynonymous variants, including 36 very rare variants (minor allele frequency (MAF) <0.1%), associated with T2D (OR = 3.31, 95% confidence interval (CI) = 1.78-6.18; P = 1.64 × 10(-4)). A four-tiered functional investigation of all 40 mutants revealed that 14 were non-functional and rare (MAF < 1%), and 4 were very rare with complete loss of melatonin binding and signaling capabilities. Among the very rare variants, the partial- or total-loss-of-function variants but not the neutral ones contributed to T2D (OR = 5.67, CI = 2.17-14.82; P = 4.09 × 10(-4)). Genotyping the four complete loss-of-function variants in 11,854 additional individuals revealed their association with T2D risk (8,153 individuals with T2D and 10,100 controls; OR = 3.88, CI = 1.49-10.07; P = 5.37 × 10(-3)). This study establishes a firm functional link between MTNR1B and T2D risk.     

Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes

We performed a genome-wide association scan to search for sequence variants conferring risk of prostate cancer using 1,501 Icelandic men with prostate cancer and 11,290 controls. Follow-up studies involving three additional case-control groups replicated an association of two variants on chromosome 17 with the disease. These two variants, 33 Mb apart, fall within a region previously implicated by family-based linkage studies on prostate cancer. The risks conferred by these variants are moderate individually (allele odds ratio of about 1.20), but because they are common, their joint population attributable risk is substantial. One of the variants is in TCF2 (HNF1beta), a gene known to be mutated in individuals with maturity-onset diabetes of the young type 5. Results from eight case-control groups, including one West African and one Chinese, demonstrate that this variant confers protection against type 2 diabetes.     

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.     

Common variants in WFS1 confer risk of type 2 diabetes

We studied genes involved in pancreatic beta cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.     

Assessing the impact of population stratification on genetic association studies

Population stratification refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease. It has been proposed that false positive associations due to stratification can be controlled by genotyping a few dozen unlinked genetic markers. To assess stratification empirically, we analyzed data from 11 case-control and case-cohort association studies. We did not detect statistically significant evidence for stratification but did observe that assessments based on a few dozen markers lack power to rule out moderate levels of stratification that could cause false positive associations in studies designed to detect modest genetic risk factors. After increasing the number of markers and samples in a case-cohort study (the design most immune to stratification), we found that stratification was in fact present. Our results suggest that modest amounts of stratification can exist even in well designed studies.     

Transferability of tag SNPs in genetic association studies in multiple populations

A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.     

Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease

Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to common disease, but are plagued by the impression that they are not consistently reproducible. In principle, the inconsistency may be due to false positive studies, false negative studies or true variability in association among different populations. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P < 10(-14)). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically significant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably contribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that studies using large samples will convincingly identify such variants.     

Genome-wide association study of prostate cancer in men of African ancestry identifies a susceptibility locus at 17q21

In search of common risk alleles for prostate cancer that could contribute to high rates of the disease in men of African ancestry, we conducted a genome-wide association study, with 1,047,986 SNP markers examined in 3,425 African-Americans with prostate cancer (cases) and 3,290 African-American male controls. We followed up the most significant 17 new associations from stage 1 in 1,844 cases and 3,269 controls of African ancestry. We identified a new risk variant on chromosome 17q21 (rs7210100, odds ratio per allele = 1.51, P = 3.4 × 10(-13)). The frequency of the risk allele is ～5% in men of African descent, whereas it is rare in other populations (<1%). Further studies are needed to investigate the biological contribution of this allele to prostate cancer risk. These findings emphasize the importance of conducting genome-wide association studies in diverse populations.     

The effects of human population structure on large genetic association studies

Large-scale association studies hold substantial promise for unraveling the genetic basis of common human diseases. A well-known problem with such studies is the presence of undetected population structure, which can lead to both false positive results and failures to detect genuine associations. Here we examine approximately 15,000 genome-wide single-nucleotide polymorphisms typed in three population groups to assess the consequences of population structure on the coming generation of association studies. The consequences of population structure on association outcomes increase markedly with sample size. For the size of study needed to detect typical genetic effects in common diseases, even the modest levels of population structure within population groups cannot safely be ignored. We also examine one method for correcting for population structure (Genomic Control). Although it often performs well, it may not correct for structure if too few loci are used and may overcorrect in other settings, leading to substantial loss of power. The results of our analysis can guide the design of large-scale association studies.     

Resequencing of positional candidates identifies low frequency IL23R coding variants protecting against inflammatory bowel disease

Genome-wide association studies (GWAS) have identified dozens of risk loci for many complex disorders, including Crohn's disease. However, common disease-associated SNPs explain at most ～20% of the genetic variance for Crohn's disease. Several factors may account for this unexplained heritability, including rare risk variants not adequately tagged thus far in GWAS. That rare susceptibility variants indeed contribute to variation in multifactorial phenotypes has been demonstrated for colorectal cancer, plasma high-density lipoprotein cholesterol levels, blood pressure, type 1 diabetes, hypertriglyceridemia and, in the case of Crohn's disease, for NOD2 (refs. 14,15). Here we describe the use of high-throughput resequencing of DNA pools to search for rare coding variants influencing susceptibility to Crohn's disease in 63 GWAS-identified positional candidate genes. We identify low frequency coding variants conferring protection against inflammatory bowel disease in IL23R, but we conclude that rare coding variants in positional candidates do not make a large contribution to inherited predisposition to Crohn's disease.     

Common genetic variants account for differences in gene expression among ethnic groups

Variation in DNA sequence contributes to individual differences in quantitative traits, but in humans the specific sequence variants are known for very few traits. We characterized variation in gene expression in cells from individuals belonging to three major population groups. This quantitative phenotype differs significantly between European-derived and Asian-derived populations for 1,097 of 4,197 genes tested. For the phenotypes with the strongest evidence of cis determinants, most of the variation is due to allele frequency differences at cis-linked regulators. The results show that specific genetic variation among populations contributes appreciably to differences in gene expression phenotypes. Populations differ in prevalence of many complex genetic diseases, such as diabetes and cardiovascular disease. As some of these are probably influenced by the level of gene expression, our results suggest that allele frequency differences at regulatory polymorphisms also account for some population differences in prevalence of complex diseases.     

Common genetic variation near MC4R is associated with waist circumference and insulin resistance

We carried out a genome-wide association study (318,237 SNPs) for insulin resistance and related phenotypes in 2,684 Indian Asians, with further testing in 11,955 individuals of Indian Asian or European ancestry. We found associations of rs12970134 near MC4R with waist circumference (P = 1.7 x 10(-9)) and, independently, with insulin resistance. Homozygotes for the risk allele of rs12970134 have approximately 2 cm increased waist circumference. Common genetic variation near MC4R is associated with risk of adiposity and insulin resistance.     

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.     

MYH9 is associated with nondiabetic end-stage renal disease in African Americans

As end-stage renal disease (ESRD) has a four times higher incidence in African Americans compared to European Americans, we hypothesized that susceptibility alleles for ESRD have a higher frequency in the West African than the European gene pool. We carried out a genome-wide admixture scan in 1,372 ESRD cases and 806 controls and found a highly significant association between excess African ancestry and nondiabetic ESRD (lod score = 5.70) but not diabetic ESRD (lod = 0.47) on chromosome 22q12. Each copy of the European ancestral allele conferred a relative risk of 0.50 (95% CI = 0.39-0.63) compared to African ancestry. Multiple common SNPs (allele frequencies ranging from 0.2 to 0.6) in the gene encoding nonmuscle myosin heavy chain type II isoform A (MYH9) were associated with two to four times greater risk of nondiabetic ESRD and accounted for a large proportion of the excess risk of ESRD observed in African compared to European Americans.     

Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus

Type 2 or non-insulin-dependent diabetes mellitus (NIDDM) is the most common form of diabetes worldwide, affecting approximately 4% of the world's adult population. It is multifactorial in origin with both genetic and environmental factors contributing to its development. A genome-wide screen for type 2 diabetes genes carried out in Mexican Americans localized a susceptibility gene, designated NIDDM1, to chromosome 2. Here we describe the positional cloning of a gene located in the NIDDM1 region that shows association with type 2 diabetes in Mexican Americans and a Northern European population from the Botnia region of Finland. This putative diabetes-susceptibility gene encodes a ubiquitously expressed member of the calpain-like cysteine protease family, calpain-10 (CAPN10). This finding suggests a novel pathway that may contribute to the development of type 2 diabetes.