Leveraging type 1 diabetes human genetic and genomic data in the T1D knowledge portal.

To address the challenge of translating genetic discoveries for type 1 diabetes (T1D) into mechanistic insight, we have developed the T1D Knowledge Portal (T1DKP), an open-access resource for hypothesis development and target discovery in T1D.

The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits.

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Leveraging type 1 diabetes human genetic and genomic data in the T1D Knowledge Portal.

Translating genetic discoveries for type 1 diabetes (T1D) into mechanistic insight can reveal novel biology and therapeutic targets but remains a major challenge. We developed the T1D Knowledge Portal (T1DKP), a disease-specific resource of genetic and functional annotation data that enables users to develop hypotheses for T1D-based research and target discovery. The T1DKP can be used to query genes and genomic regions for genetic associations, identify epigenomic features, access results of bioinformatic analyses, and obtain expert-curated resources. The T1DKP is available at http://t1d.hugeamp.org .

A combined polygenic score of 21,293 rare and 22 common variants improves diabetes diagnosis based on hemoglobin A1C levels.

Polygenic scores (PGSs) combine the effects of common genetic variants1,2 to predict risk or treatment strategies for complex diseases3-7. Adding rare variation to PGSs has largely unknown benefits and is methodically challenging. Here, we developed a method for constructing rare variant PGSs and applied it to calculate genetically modified hemoglobin A1C thresholds for type 2 diabetes (T2D) diagnosis7-10. The resultant rare variant PGS is highly polygenic (21,293 variants across 154 genes), depends on ultra-rare variants (72.7% observed in fewer than three people) and identifies significantly more undiagnosed T2D cases than expected by chance (odds ratio = 2.71; P = 1.51 × 10-6). A PGS combining common and rare variants is expected to identify 4.9 million misdiagnosed T2D cases in the United States-nearly 1.5-fold more than the common variant PGS alone. These results provide a method for constructing complex trait PGSs from rare variants and suggest that rare variants will augment common variants in precision medicine approaches for common disease.

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

Genome-wide association study of rate of cognitive decline in Alzheimer's disease patients identifies novel genes and pathways.

INTRODUCTION: Variability exists in the disease trajectories of Alzheimer's disease (AD) patients. We performed a genome-wide association study to examine rate of cognitive decline (ROD) in patients with AD. METHODS: We tested for interactions between genetic variants and time since diagnosis to predict the ROD of a composite cognitive score in 3946 AD cases and performed pathway analysis on the top genes. RESULTS: Suggestive associations (P < 1.0 × 10-6 ) were observed on chromosome 15 in DNA polymerase-γ (rs3176205, P = 1.11 × 10-7 ), chromosome 7 (rs60465337,P = 4.06 × 10-7 ) in contactin-associated protein-2, in RP11-384F7.1 on chromosome 3 (rs28853947, P = 5.93 × 10-7 ), family with sequence similarity 214 member-A on chromosome 15 (rs2899492, P = 5.94 × 10-7 ), and intergenic regions on chromosomes 16 (rs4949142, P = 4.02 × 10-7 ) and 4 (rs1304013, P = 7.73 × 10-7 ). Significant pathways involving neuronal development and function, apoptosis, memory, and inflammation were identified. DISCUSSION: Pathways related to AD, intelligence, and neurological function determine AD progression, while previously identified AD risk variants, including the apolipoprotein (APOE) ε4 and ε2 variants, do not have a major impact.

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179.

Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Genomewide Association Study of Alcohol Dependence Identifies Risk Loci Altering Ethanol-Response Behaviors in Model Organisms.

BACKGROUND: Alcohol dependence (AD) shows evidence for genetic liability, but genes influencing risk remain largely unidentified. METHODS: We conducted a genomewide association study in 706 related AD cases and 1,748 unscreened population controls from Ireland. We sought replication in 15,496 samples of European descent. We used model organisms (MOs) to assess the role of orthologous genes in ethanol (EtOH)-response behaviors. We tested 1 primate-specific gene for expression differences in case/control postmortem brain tissue. RESULTS: We detected significant association in COL6A3 and suggestive association in 2 previously implicated loci, KLF12 and RYR3. None of these signals are significant in replication. A suggestive signal in the long noncoding RNA LOC339975 is significant in case:control meta-analysis, but not in a population sample. Knockdown of a COL6A3 ortholog in Caenorhabditis elegans reduced EtOH sensitivity. Col6a3 expression correlated with handling-induced convulsions in mice. Loss of function of the KLF12 ortholog in C. elegans impaired development of acute functional tolerance (AFT). Klf12 expression correlated with locomotor activation following EtOH injection in mice. Loss of function of the RYR3 ortholog reduced EtOH sensitivity in C. elegans and rapid tolerance in Drosophila. The ryanodine receptor antagonist dantrolene reduced motivation to self-administer EtOH in rats. Expression of LOC339975 does not differ between cases and controls but is reduced in carriers of the associated rs11726136 allele in nucleus accumbens (NAc). CONCLUSIONS: We detect association between AD and COL6A3, KLF12, RYR3, and LOC339975. Despite nonreplication of COL6A3, KLF12, and RYR3 signals, orthologs of these genes influence behavioral response to EtOH in MOs, suggesting potential involvement in human EtOH response and AD liability. The associated LOC339975 allele may influence gene expression in human NAc. Although the functions of long noncoding RNAs are poorly understood, there is mounting evidence implicating these genes in multiple brain functions and disorders.

Genome-wide Association Study of Cannabis Dependence Severity, Novel Risk Variants, and Shared Genetic Risks.

IMPORTANCE: Cannabis dependence (CAD) is a serious problem worldwide and is of growing importance in the United States because cannabis is increasingly available legally. Although genetic factors contribute substantially to CAD risk, at present no well-established specific genetic risk factors for CAD have been elucidated. OBJECTIVE: To report findings for DSM-IV CAD criteria from association analyses performed in large cohorts of African American and European American participants from 3 studies of substance use disorder genetics. DESIGN, SETTING, AND PARTICIPANTS: This genome-wide association study for DSM-IV CAD criterion count was performed in 3 independent substance dependence cohorts (the Yale-Penn Study, Study of Addiction: Genetics and Environment [SAGE], and International Consortium on the Genetics of Heroin Dependence [ICGHD]). A referral sample and volunteers recruited in the community and from substance abuse treatment centers included 6000 African American and 8754 European American participants, including some from small families. Participants from the Yale-Penn Study were recruited from 2000 to 2013. Data were collected for the SAGE trial from 1990 to 2007 and for the ICGHD from 2004 to 2009. Data were analyzed from January 2, 2013, to November 9, 2015. MAIN OUTCOMES AND MEASURES: Criterion count for DSM-IV CAD. RESULTS: Among the 14 754 participants, 7879 were male, 6875 were female, and the mean (SD) age was 39.2 (10.2) years. Three independent regions with genome-wide significant single-nucleotide polymorphism associations were identified, considering the largest possible sample. These included rs143244591 (ß = 0.54, P = 4.32 × 10-10 for the meta-analysis) in novel antisense transcript RP11-206M11.7;rs146091982 (ß = 0.54, P = 1.33 × 10-9 for the meta-analysis) in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 (ß = 0.29, P = 2.13 × 10-8 for the meta-analysis) in the CUB and Sushi multiple domains 1 gene (CSMD1). Also noted was evidence of genome-level pleiotropy between CAD and major depressive disorder and for an association with single-nucleotide polymorphisms in genes associated with schizophrenia risk. Several of the genes identified have functions related to neuronal calcium homeostasis or central nervous system development. CONCLUSIONS AND RELEVANCE: These results are the first, to our knowledge, to identify specific CAD risk alleles and potential genetic factors contributing to the comorbidity of CAD with major depression and schizophrenia.

Genomewide Association Study for Maximum Number of Alcoholic Drinks in European Americans and African Americans.

BACKGROUND: We conducted a genomewide association study (GWAS) for maximum number of alcoholic drinks consumed in a 24-hour period ("MaxDrinks"), in 2 independent samples comprised of over 9,500 subjects, following up on our GWAS for alcohol dependence (AD) in European Americans (EAs) and African Americans (AAs). METHODS: The samples included our GWAS samples (Yale-UPenn) recruited for studies of the genetics of drug or AD, and a publicly available sample: the Study of Addiction: Genetics and Environment (SAGE). Genomewide association analysis was performed for ~890,000 single nucleotide polymorphisms (SNPs) using linear association random effects models. EAs and AAs were separately analyzed. RESULTS: The results confirmed significant associations of the well-known functional loci at ADH1B with MaxDrinks in EAs (rs1229984 Arg48His p = 5.96 × 10(-15) ) and AAs (rs2066702 Arg370Cys, p = 2.50 × 10(-10) ). The region of significant association on chromosome 4 was extended to LOC100507053 in AAs but not EAs. We also identified potentially novel significant common SNPs for MaxDrinks in EAs in the Yale-UPenn sample: rs1799876 at SERPINC1 on chromosome 1 (4.00 × 10(-8) ) and rs2309169 close to ANKRD36 on chromosome 2 (p = 5.58 × 10(-9) ). After adjusting for the peak SNP rs1229984 on ADH1B, rs1799876 was nearly significant (p = 1.99 × 10(-7) ) and rs2309169 remained highly significant (2.12 × 10(-9) ). CONCLUSIONS: The results provide further support that ADH1B modulates alcohol consumption. Future replications of potential novel loci are warranted. This is the largest MaxDrinks GWAS to date, the first in AAs.

Genome-wide association study of nicotine dependence in American populations: identification of novel risk loci in both African-Americans and European-Americans.

BACKGROUND: We report a genome-wide association study (GWAS) of nicotine dependence defined on the basis of scores on the Fagerström Test for Nicotine Dependence in European-American (EA) and African-American (AA) populations. METHODS: Our sample, from the one used in our previous GWAS, included only subjects who had smoked >100 cigarettes lifetime (2114 EA and 2602 AA subjects) and an additional 927 AA and 2003 EA subjects from the Study of Addiction: Genetics and Environment project [via the database of Genotypes and Phenotypes (dbGAP)]. GWAS analysis considered Fagerström Test for Nicotine Dependence score as an ordinal trait, separately in each population and sample and by combining the results in meta-analysis. We also conducted analyses that were adjusted for other substance use disorder criteria in a single nucleotide polymorphism (SNP) subset. RESULTS: In EAs, one chromosome 7 intergenic region was genome-wide significant (GWS): rs13225753, p = 3.48 × 10(-8) (adjusted). In AAs, GWS associations were observed at numerous SNPs mapped to a region on chromosome 14 of >305,000 base pairs (minimal p = 4.74 × 10(-10)). Two chromosome 8 regions were associated: p = 4.45 × 10(-8) at DLC1 SNP rs289519 (unadjusted) and p = 1.10 × 10(-9) at rs6996964 (adjusted for other substances), located between CSGALNACT1 and INTS10. No GWS associations were observed at the chromosome 15 nicotinic receptor gene cluster (CHRNA5-CHRNA3-CHRNB4) previously associated with nicotine dependence and smoking quantity traits. TSNAX-DISC1 SNP rs821722 (p = 1.46 × 10(-7)) was the most significant result with substantial contributions from both populations; we previously identified DISC1 associations with opioid dependence. Pathway analysis identified association with nitric oxide synthase and adenosine monophosphate-activated protein kinase pathways in EAs. CONCLUSIONS: The key risk loci identified, which require replication, offer novel insights into nicotine dependence biology.

Genome-wide association study of opioid dependence: multiple associations mapped to calcium and potassium pathways.

BACKGROUND: We report a genome-wide association study (GWAS) of two populations, African-American and European-American (AA, EA) for opioid dependence (OD) in three sets of subjects, to identify pathways, genes, and alleles important in OD risk. METHODS: The design employed three phases (on the basis of separate sample collections). Phase 1 included our discovery GWAS dataset consisting of 5697 subjects (58% AA) diagnosed with opioid and/or other substance dependence and control subjects. Subjects were genotyped with the Illumina OmniQuad microarray, yielding 890,000 single nucleotide polymorphisms (SNPs) suitable for analysis. Additional genotypes were imputed with the 1000 Genomes reference panel. Top-ranked findings were further evaluated in Phase 2 by incorporating information from the publicly available Study of Addiction: Genetics and Environment dataset, with GWAS data from 4063 subjects (32% AA). In Phase 3, the most significant SNPs from Phase 2 were genotyped in 2549 independent subjects (32% AA). Analyses were performed with case-control and ordinal trait designs. RESULTS: Most significant results emerged from the AA subgroup. Genome-wide-significant associations (p < 5.0 × 10(-8)) were observed with SNPs from multiple loci-KCNG2*rs62103177 was most significant after combining results from datasets in every phase of the study. The most compelling results were obtained with genes involved in potassium signaling pathways (e.g., KCNC1 and KCNG2). Pathway analysis also implicated genes involved in calcium signaling and long-term potentiation. CONCLUSIONS: This is the first study to identify risk variants for OD with GWAS. Our results strongly implicate risk pathways and provide insights into novel therapeutic and prevention strategies and might biologically bridge OD and other non-substance dependence psychiatric traits where similar pathways have been implicated.