Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms.

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT.

Analysis of protein-coding genetic variation in 60,706 humans.

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

A novel test for recessive contributions to complex diseases implicates Bardet-Biedl syndrome gene BBS10 in idiopathic type 2 diabetes and obesity.

Rare-variant association studies in common, complex diseases are customarily conducted under an additive risk model in both single-variant and burden testing. Here, we describe a method to improve detection of rare recessive variants in complex diseases termed RAFT (recessive-allele-frequency-based test). We found that RAFT outperforms existing approaches when the variant influences disease risk in a recessive manner on simulated data. We then applied our method to 1,791 Finnish individuals with type 2 diabetes (T2D) and 2,657 matched control subjects. In BBS10, we discovered a rare variant (c.1189A>G [p.Ile397Val]; rs202042386) that confers risk of T2D in a recessive state (p = 1.38 × 10(-6)) and would be missed by conventional methods. Testing of this variant in an established in vivo zebrafish model confirmed the variant to be pathogenic. Taken together, these data suggest that RAFT can effectively reveal rare recessive contributions to complex diseases overlooked by conventional association tests.

Distribution and medical impact of loss-of-function variants in the Finnish founder population.

Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5-5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10⁻8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10⁻¹¹7). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10⁻4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.

Increased burden of cardiovascular disease in carriers of APOL1 genetic variants.

RATIONALE: Two distinct alleles in the gene encoding apolipoprotein L1 (APOL1), a major component of high-density lipoprotein, confer protection against Trypanosoma brucei rhodesiense infection and also increase risk for chronic kidney disease. Approximately 14% of Americans with African ancestry carry 2 APOL1 risk alleles, accounting for the high chronic kidney disease burden in this population. OBJECTIVE: We tested whether APOL1 risk alleles significantly increase risk for atherosclerotic cardiovascular disease (CVD) in African Americans. METHODS AND RESULTS: We sequenced APOL1 in 1959 randomly selected African American participants in the Jackson Heart Study (JHS) and evaluated associations between APOL1 genotypes and renal and cardiovascular phenotypes. Previously identified association between APOL1 genotypes and chronic kidney disease was confirmed (P=2.4×10(-6)). Among JHS participants with 2 APOL1 risk alleles, we observed increased risk for CVD (50/763 events among participants without versus 37/280 events among participants with 2 risk alleles; odds ratio, 2.17; P=9.4×10(-4)). We replicated this novel association of APOL1 genotype with CVD in Women's Health Initiative (WHI) participants (66/292 events among participants without versus 37/101 events among participants with 2 risk alleles; odds ratio, 1.98; P=8.37×10(-3); JHS and WHI combined, P=8.5×10(-5); odds ratio, 2.12). The increased risk for CVD conferred by APOL1 alleles was robust to correction for both traditional CVD risk factors and chronic kidney disease. CONCLUSIONS: APOL1 variants contribute to atherosclerotic CVD risk, indicating a genetic component to cardiovascular health disparities in individuals of African ancestry. The considerable population of African Americans with 2 APOL1 risk alleles may benefit from intensive interventions to reduce CVD.

A null mutation in ANGPTL8 does not associate with either plasma glucose or type 2 diabetes in humans.

BACKGROUND: Experiments in mice initially suggested a role for the protein angiopoietin-like 8 (ANGPTL8) in glucose homeostasis. However, subsequent experiments in model systems have challenged this proposed role. We sought to better understand the importance of ANGPTL8 in human glucose homeostasis by examining the association of a null mutation in ANGPTL8 with fasting glucose levels and risk for type 2 diabetes. METHODS: A naturally-occurring null mutation in human ANGPTL8 (rs145464906; c.361C > T; p.Q121X) is carried by ~1 in 1000 individuals of European ancestry and is associated with higher levels of plasma high-density lipoprotein cholesterol, suggesting that this mutation has functional significance. We examined the association of p.Q121X with fasting glucose levels and risk for type 2 diabetes in up to 95,558 individuals (14,824 type 2 diabetics and 80,734 controls). RESULTS: We found no significant association of p.Q121X with either fasting glucose or type 2 diabetes (p-value = 0.90 and 0.65, respectively). Given our sample sizes, we had >98 % power to detect at least a 0.23 mmol/L effect on plasma glucose and >95 % power to detect a 70 % increase in risk for type 2 diabetes. CONCLUSION: Disruption of ANGPTL8 function in humans does not seem to have a large effect on measures of glucose tolerance.

Integrating common and rare genetic variation in diverse human populations.

Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called 'HapMap 3', includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of

Copy-number variation and association studies of human disease.

The central goal of human genetics is to understand the inherited basis of human variation in phenotypes, elucidating human physiology, evolution and disease. Rare mutations have been found underlying two thousand mendelian diseases; more recently, it has become possible to assess systematically the contribution of common SNPs to complex disease. The known role of copy-number alterations in sporadic genomic disorders, combined with emerging information about inherited copy-number variation, indicate the importance of systematically assessing copy-number variants (CNVs), including common copy-number polymorphisms (CNPs), in disease. Here we discuss evidence that CNVs affect phenotypes, directions for basic knowledge to support clinical study of CNVs, the challenge of genotyping CNPs in clinical cohorts, the use of SNPs as markers for CNPs and statistical challenges in testing CNVs for association with disease. Critical needs are high-resolution maps of common CNPs and techniques that accurately determine the allelic state of affected individuals.

Challenges and standards in integrating surveys of structural variation.

There has been an explosion of data describing newly recognized structural variants in the human genome. In the flurry of reporting, there has been no standard approach to collecting the data, assessing its quality or describing identified features. This risks becoming a rampant problem, in particular with respect to surveys of copy number variation and their application to disease studies. Here, we consider the challenges in characterizing and documenting genomic structural variants. From this, we derive recommendations for standards to be adopted, with the aim of ensuring the accurate presentation of this form of genetic variation to facilitate ongoing research.

Burden of rare sarcomere gene variants in the Framingham and Jackson Heart Study cohorts.

Rare sarcomere protein variants cause dominant hypertrophic and dilated cardiomyopathies. To evaluate whether allelic variants in eight sarcomere genes are associated with cardiac morphology and function in the community, we sequenced 3,600 individuals from the Framingham Heart Study (FHS) and Jackson Heart Study (JHS) cohorts. Out of the total, 11.2% of individuals had one or more rare nonsynonymous sarcomere variants. The prevalence of likely pathogenic sarcomere variants was 0.6%, twice the previous estimates; however, only four of the 22 individuals had clinical manifestations of hypertrophic cardiomyopathy. Rare sarcomere variants were associated with an increased risk for adverse cardiovascular events (hazard ratio: 2.3) in the FHS cohort, suggesting that cardiovascular risk assessment in the general population can benefit from rare variant analysis.

Common deletion polymorphisms in the human genome.

The locations and properties of common deletion variants in the human genome are largely unknown. We describe a systematic method for using dense SNP genotype data to discover deletions and its application to data from the International HapMap Consortium to characterize and catalogue segregating deletion variants across the human genome. We identified 541 deletion variants (94% novel) ranging from 1 kb to 745 kb in size; 278 of these variants were observed in multiple, unrelated individuals, 120 in the homozygous state. The coding exons of ten expressed genes were found to be commonly deleted, including multiple genes with roles in sex steroid metabolism, olfaction and drug response. These common deletion polymorphisms typically represent ancestral mutations that are in linkage disequilibrium with nearby SNPs, meaning that their association to disease can often be evaluated in the course of SNP-based whole-genome association studies.

DASH: a method for identical-by-descent haplotype mapping uncovers association with recent variation.

Rare variants affecting phenotype pose a unique challenge for human genetics. Although genome-wide association studies have successfully detected many common causal variants, they are underpowered in identifying disease variants that are too rare or population-specific to be imputed from a general reference panel and thus are poorly represented on commercial SNP arrays. We set out to overcome these challenges and detect association between disease and rare alleles using SNP arrays by relying on long stretches of genomic sharing that are identical by descent. We have developed an algorithm, DASH, which builds upon pairwise identical-by-descent shared segments to infer clusters of individuals likely to be sharing a single haplotype. DASH constructs a graph with nodes representing individuals and links on the basis of such segments spanning a locus and uses an iterative minimum cut algorithm to identify densely connected components. We have applied DASH to simulated data and diverse GWAS data sets by constructing haplotype clusters and testing them for association. In simulations we show this approach to be significantly more powerful than single-marker testing in an isolated population that is from Kosrae, Federated States of Micronesia and has abundant IBD, and we provide orthogonal information for rare, recent variants in the outbred Wellcome Trust Case-Control Consortium (WTCCC) data. In both cohorts, we identified a number of haplotype associations, five such loci in the WTCCC data and ten in the isolated, that were conditionally significant beyond any individual nearby markers. We have replicated one of these loci in an independent European cohort and identified putative structural changes in low-pass whole-genome sequence of the cluster carriers.

Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population.

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10⁻8).

Systematic haplotype analysis resolves a complex plasma plant sterol locus on the Micronesian Island of Kosrae.

Pinpointing culprit causal variants along signal peaks of genome-wide association studies (GWAS) is challenging. To overcome confounding effects of multiple independent variants at such a locus and narrow the interval for causal allele capture, we developed an approach that maps local shared haplotypes harboring a putative causal variant. We demonstrate our method in an extreme isolate founder population, the pacific Island of Kosrae. We analyzed plasma plant sterol (PPS) levels, a surrogate measure of cholesterol absorption from the intestine, where previous studies have implicated 2p21 mutations in the ATP binding cassette subfamily G members 5 or 8 (ABCG5 or ABCG8) genes. We have previously reported that 11.1% of the islanders are carriers of a frameshift ABCG8 mutation increasing PPS levels in carriers by 50%. GWAS adjusted for this mutation revealed genomewide significant signals along 11 Mb around it. To fine-map this signal, we detected pairwise identity-by-descent haplotypes using our tool GERMLINE and implemented a clustering algorithm to identify haplotypes shared across multiple samples with their unique shared boundaries. A single 526-kb haplotype mapped strongly to PPS levels, dramatically refining the mapped interval. This haplotype spans the ABCG5/ABCG8 genes, is carried by 1.8% of the islanders, and results in a striking 100% increase of PPS in carriers. Resequencing of ABCG5 in these carriers found a D450H missense mutation along the associated haplotype. These findings exemplify the power of haplotype analysis for mapping mutations in isolated populations and specifically for dissecting effects of multiple variants of the same locus.

Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.

It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining >/=5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.

Polymorphisms associated with cholesterol and risk of cardiovascular events.

BACKGROUND: Common single-nucleotide polymorphisms (SNPs) that are associated with blood low-density lipoprotein (LDL) or high-density lipoprotein (HDL) cholesterol modestly affect lipid levels. We tested the hypothesis that a combination of such SNPs contributes to the risk of cardiovascular disease. METHODS: We studied SNPs at nine loci in 5414 subjects from the cardiovascular cohort of the Malmö Diet and Cancer Study. We first validated the association between SNPs and either LDL or HDL cholesterol and subsequently created a genotype score on the basis of the number of unfavorable alleles. We used Cox proportional-hazards models to determine the time to the first cardiovascular event in relation to the genotype score. RESULTS: All nine SNPs showed replication of an association with levels of either LDL or HDL cholesterol. With increasing genotype scores, the level of LDL cholesterol increased from 152 mg to 171 mg per deciliter (3.9 to 4.4 mmol per liter), whereas HDL cholesterol decreased from 60 mg to 51 mg per deciliter (1.6 to 1.3 mmol per liter). During follow-up (median, 10.6 years), 238 subjects had a first cardiovascular event. The genotype score was associated with incident cardiovascular disease in models adjusted for covariates including baseline lipid levels (P<0.001). The use of the genotype score did not improve the clinical risk prediction, as assessed by the C statistic. However, there was a significant improvement in risk classification with the use of models that included the genotype score, as compared with those that did not include the genotype score. CONCLUSIONS: A genotype score of nine validated SNPs that are associated with modulation in levels of LDL or HDL cholesterol was an independent risk factor for incident cardiovascular disease. The score did not improve risk discrimination but did modestly improve clinical risk reclassification for individual subjects beyond standard clinical factors.

A novel polymorphism of the human CD40 receptor with enhanced function.

CD40 signaling is critical for innate and adaptive immunity against pathogens, and the cytoplasmic domain of CD40 is highly conserved both within and between species. A novel missense single nucleotide polymorphism (SNP) in the cytoplasmic domain of CD40 at position 227 (P227A) was identified, which resides on a conserved ancestral haplotype highly enriched in persons of Mexican and South American descent. Functional studies indicated that signaling via human (h) CD40-P227A stably expressed in several B-cell lines led to increased phosphorylation of c-Jun, increased secretion of the pro-inflammatory cytokines interleukin (IL)-6 and TNF-alpha, and increased Ig production, compared with wild-type hCD40. Cooperation between hCD40-P227A signaling and B-cell receptor (BCR)- or Toll-like receptor 9 (TLR9)-mediated signaling was also enhanced, resulting in elevated and synergistic production of IL-6 and Ig. We have thus identified a novel genetic variant of hCD40 with a gain-of-function immune phenotype.

Prospective study of the association between the proline to alanine codon 12 polymorphism in the PPARgamma gene and type 2 diabetes.

OBJECTIVE: To determine whether the Pro12Ala polymorphism in the PPARgamma gene was associated with risk of type 2 diabetes in the Nurses' Health Study. RESEARCH DESIGN AND METHODS: The study was a nested case-control study of 387 incident cases of type 2 diabetes and 771 matching control subjects nested within the Nurses' Health Study, a prospective cohort study. Association between PPARgamma genotype and incident type 2 diabetes was estimated using logistic regression. RESULTS: Carriers of the PPARgamma variant 12Ala allele had reduced risk of type 2 diabetes compared with noncarriers. Unadjusted and adjusted odds ratios of type 2 diabetes were 0.74 (95% CI 0.55-1.00) and 0.72 (0.52-0.99), respectively. CONCLUSIONS: The results of this study provide further support for an inverse association between the PPARgamma variant 12Ala allele and risk of type 2 diabetes.

Structural forms of the human amylase locus and their relationships to SNPs, haplotypes and obesity.

Hundreds of genes reside in structurally complex, poorly understood regions of the human genome. One such region contains the three amylase genes (AMY2B, AMY2A and AMY1) responsible for digesting starch into sugar. Copy number of AMY1 is reported to be the largest genomic influence on obesity, although genome-wide association studies for obesity have found this locus unremarkable. Using whole-genome sequence analysis, droplet digital PCR and genome mapping, we identified eight common structural haplotypes of the amylase locus that suggest its mutational history. We found that the AMY1 copy number in an individual's genome is generally even (rather than odd) and partially correlates with nearby SNPs, which do not associate with body mass index (BMI). We measured amylase gene copy number in 1,000 obese or lean Estonians and in 2 other cohorts totaling ∼3,500 individuals. We had 99% power to detect the lower bound of the reported effects on BMI, yet found no association.

Integrated allelic, transcriptional, and phenomic dissection of the cardiac effects of titin truncations in health and disease.

The recent discovery of heterozygous human mutations that truncate full-length titin (TTN, an abundant structural, sensory, and signaling filament in muscle) as a common cause of end-stage dilated cardiomyopathy (DCM) promises new prospects for improving heart failure management. However, realization of this opportunity has been hindered by the burden of TTN-truncating variants (TTNtv) in the general population and uncertainty about their consequences in health or disease. To elucidate the effects of TTNtv, we coupled TTN gene sequencing with cardiac phenotyping in 5267 individuals across the spectrum of cardiac physiology and integrated these data with RNA and protein analyses of human heart tissues. We report diversity of TTN isoform expression in the heart, define the relative inclusion of TTN exons in different isoforms (using the TTN transcript annotations available at http://cardiodb.org/titin), and demonstrate that these data, coupled with the position of the TTNtv, provide a robust strategy to discriminate pathogenic from benign TTNtv. We show that TTNtv is the most common genetic cause of DCM in ambulant patients in the community, identify clinically important manifestations of TTNtv-positive DCM, and define the penetrance and outcomes of TTNtv in the general population. By integrating genetic, transcriptome, and protein analyses, we provide evidence for a length-dependent mechanism of disease. These data inform diagnostic criteria and management strategies for TTNtv-positive DCM patients and for TTNtv that are identified as incidental findings.