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Excessive alcohol consumption is one of the leading causes of preventable death in the United States. Approximately 14% of those who use alcohol meet criteria during their lifetime for alcohol dependence, which is characterized by tolerance, withdrawal, inability to stop drinking, and continued drinking despite serious psychological or physiological problems. We explored genetic influences on alcohol dependence among 1,897 European-American and African-American subjects with alcohol dependence compared with 1,932 unrelated, alcohol-exposed, nondependent controls. Constitutional DNA of each subject was genotyped using the Illumina 1M beadchip. Fifteen SNPs yielded P < 10⁻⁵, but in two independent replication series, no SNP passed a replication threshold of P < 0.05. Candidate gene GABRA2, which encodes the GABA receptor α2 subunit, was evaluated independently. Five SNPs at GABRA2 yielded nominal (uncorrected) P < 0.05, with odds ratios between 1.11 and 1.16. Further dissection of the alcoholism phenotype, to disentangle the influence of comorbid substance-use disorders, will be a next step in identifying genetic variants associated with alcohol dependence.

Identifying the genetic variants that increase the risk of type 2 diabetes (T2D) in humans has been a formidable challenge. Adopting a genome-wide association strategy, we genotyped 1161 Finnish T2D cases and 1174 Finnish normal glucose-tolerant (NGT) controls with >315,000 single-nucleotide polymorphisms (SNPs) and imputed genotypes for an additional >2 million autosomal SNPs. We carried out association analysis with these SNPs to identify genetic variants that predispose to T2D, compared our T2D association results with the results of two similar studies, and genotyped 80 SNPs in an additional 1215 Finnish T2D cases and 1258 Finnish NGT controls. We identify T2D-associated variants in an intergenic region of chromosome 11p12, contribute to the identification of T2D-associated variants near the genes IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirm that variants near TCF7L2, SLC30A8, HHEX, FTO, PPARG, and KCNJ11 are associated with T2D risk. This brings the number of T2D loci now confidently identified to at least 10.

Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping was performed with the Illumina HumanCNV370Duo array in 857 familial PD cases and 867 controls. A logistic model was employed to test for association under additive and recessive modes of inheritance after adjusting for gender and age. No result met genomewide significance based on a conservative Bonferroni correction. The strongest association result was with SNPs in the GAK/DGKQ region on chromosome 4 (additive model: p = 3.4 x 10⁻⁶; OR = 1.69). Consistent evidence of association was also observed to the chromosomal regions containing SNCA (additive model: p = 5.5 x 10⁻⁵; OR = 1.35) and MAPT (recessive model: p = 2.0 x 10⁻⁵; OR = 0.56). Both of these genes have been implicated previously in PD susceptibility; however, neither was identified in previous GWAS studies of PD. Meta-analysis was performed using data from a previous case-control GWAS, and yielded improved p values for several regions, including GAK/DGKQ (additive model: p = 2.5 x 10⁻⁷) and the MAPT region (recessive model: p = 9.8 x 10⁻⁶; additive model: p = 4.8 x 10⁻⁵). These data suggest the identification of new susceptibility alleles for PD in the GAK/DGKQ region, and also provide further support for the role of SNCA and MAPT in PD susceptibility.

Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87–100%)). All monoallelic MUTYH carriers are classified with the non- MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers ( p  = 2 × 10 −23 and p  = 6 × 10 −11 , respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers. Germline biallelic pathogenic MUTYH variants predispose patients to colorectal cancer (CRC); however, approaches to identify MUTYH variant carriers are lacking. Here, the authors evaluated mutational signatures that could distinguish MUTYH carriers in large CRC cohorts, and found MUTYH -associated somatic mutations.

Background With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. Results PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients’ phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. Conclusion Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative.

Circulating homocysteine levels (tHcy), a product of the folate one carbon metabolism pathway (FOCM) through the demethylation of methionine, are heritable and are associated with an increased risk of common diseases such as stroke, cardiovascular disease (CVD), cancer and dementia. The FOCM is the sole source of de novo methyl group synthesis, impacting many biological and epigenetic pathways. However, the genetic determinants of elevated tHcy (hyperhomocysteinemia), dysregulation of methionine metabolism and the underlying biological processes remain unclear. We conducted independent genome-wide association studies and a meta-analysis of methionine metabolism, characterized by post-methionine load test tHcy, in 2,710 participants from the Framingham Heart Study (FHS) and 2,100 participants from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, and then examined the association of the identified loci with incident stroke in FHS. Five genes in the FOCM pathway (GNMT [p = 1.60 × 10(-63)], CBS [p = 3.15 × 10(-26)], CPS1 [p = 9.10 × 10(-13)], ALDH1L1 [p = 7.3 × 10(-13)] and PSPH [p = 1.17 × 10(-16)]) were strongly associated with the difference between pre- and post-methionine load test tHcy levels (ΔPOST). Of these, one variant in the ALDH1L1 locus, rs2364368, was associated with incident ischemic stroke. Promoter analyses reveal genetic and epigenetic differences that may explain a direct effect on GNMT transcription and a downstream affect on methionine metabolism. Additionally, a genetic-score consisting of the five significant loci explains 13% of the variance of ΔPOST in FHS and 6% of the variance in VISP. Association between variants in FOCM genes with ΔPOST suggest novel mechanisms that lead to differences in methionine metabolism, and possibly the epigenome, impacting disease risk. These data emphasize the importance of a concerted effort to understand regulators of one carbon metabolism as potential therapeutic targets.

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics 1 – 4 . The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health 5 , 6 . Here we describe the programme’s genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all. A study describes the release of clinical-grade whole-genome sequence data for 245,388 diverse participants by the All of Us Research Program and characterizes the properties of the dataset.

Copy number variants (CNVs) are known to cause Mendelian forms of Parkinson disease (PD), most notably in SNCA and PARK2. PARK2 has a recessive mode of inheritance; however, recent evidence demonstrates that a single CNV in PARK2 (but not a single missense mutation) may increase risk for PD. We recently performed a genome-wide association study for PD that excluded individuals known to have either a LRRK2 mutation or two PARK2 mutations. Data from the Illumina370Duo arrays were re-clustered using only white individuals with high quality intensity data, and CNV calls were made using two algorithms, PennCNV and QuantiSNP. After quality assessment, the final sample included 816 cases and 856 controls. Results varied between the two CNV calling algorithms for many regions, including the PARK2 locus (genome-wide p = 0.04 for PennCNV and p = 0.13 for QuantiSNP). However, there was consistent evidence with both algorithms for two novel genes, USP32 and DOCK5 (empirical, genome-wide p-values<0.001). PARK2 CNVs tended to be larger, and all instances that were molecularly tested were validated. In contrast, the CNVs in both novel loci were smaller and failed to replicate using real-time PCR, MLPA, and gel electrophoresis. The DOCK5 variation is more akin to a VNTR than a typical CNV and the association is likely caused by artifact due to DNA source. DNA for all the cases was derived from whole blood, while the DNA for all controls was derived from lymphoblast cell lines. The USP32 locus contains many SNPs with low minor allele frequency leading to a loss of heterozygosity that may have been spuriously interpreted by the CNV calling algorithms as support for a deletion. Thus, only the CNVs within the PARK2 locus could be molecularly validated and associated with PD susceptibility.

TET3 encodes an essential dioxygenase involved in epigenetic regulation through DNA demethylation. TET3 deficiency, or Beck-Fahrner syndrome (BEFAHRS; MIM: 618798), is a recently described neurodevelopmental disorder of the DNA demethylation machinery with a nonspecific phenotype resembling other chromatin-modifying disorders, but inconsistent variant types and inheritance patterns pose diagnostic challenges. Given TET3’s direct role in regulating 5-methylcytosine and recent identification of syndrome-specific DNA methylation profiles, we analyzed genome-wide DNA methylation in whole blood of TET3-deficient individuals and identified an episignature that distinguishes affected and unaffected individuals and those with mono-allelic and bi-allelic pathogenic variants. Validation and testing of the episignature correctly categorized known TET3 variants and determined pathogenicity of variants of uncertain significance. Clinical utility was demonstrated when the episignature alone identified an affected individual from over 1000 undiagnosed cases and was confirmed upon distinguishing TET3-deficient individuals from those with 46 other disorders. The TET3-deficient signature - and the signature resulting from activating mutations in DNMT1 which normally opposes TET3 - are characterized by hypermethylation, which for BEFAHRS involves CpG sites that may be biologically relevant. This work expands the role of epi-phenotyping in molecular diagnosis and reveals genome-wide DNA methylation profiling as a quantitative, functional readout for characterization of this new biochemical category of disease.

Fifty percent of variability in HIV-1 susceptibility is attributable to host genetics. Thus identifying genetic associations is essential to understanding pathogenesis of HIV-1 and important for targeting drug development. To date, however, CCR5 remains the only gene conclusively associated with HIV acquisition. To identify novel host genetic determinants of HIV-1 acquisition, we conducted a genome-wide association study among a high-risk sample of 3,136 injection drug users (IDUs) from the Urban Health Study (UHS). In addition to being IDUs, HIV-controls were frequency-matched to cases on environmental exposures to enhance detection of genetic effects. We tested independent replication in the Women's Interagency HIV Study (N=2,533). We also examined publicly available gene expression data to link SNPs associated with HIV acquisition to known mechanisms affecting HIV replication/infectivity. Analysis of the UHS nominated eight genetic regions for replication testing. SNP rs4878712 in FRMPD1 met multiple testing correction for independent replication (P=1.38x10(-4)), although the UHS-WIHS meta-analysis p-value did not reach genome-wide significance (P=4.47x10(-7) vs. P<5.0x10(-8)) Gene expression analyses provided promising biological support for the protective G allele at rs4878712 lowering risk of HIV: (1) the G allele was associated with reduced expression of FBXO10 (r=-0.49, P=6.9x10(-5)); (2) FBXO10 is a component of the Skp1-Cul1-F-box protein E3 ubiquitin ligase complex that targets Bcl-2 protein for degradation; (3) lower FBXO10 expression was associated with higher BCL2 expression (r=-0.49, P=8x10(-5)); (4) higher basal levels of Bcl-2 are known to reduce HIV replication and infectivity in human and animal in vitro studies. These results suggest new potential biological pathways by which host genetics affect susceptibility to HIV upon exposure for follow-up in subsequent studies.