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Identifying genetic variants associated with lower waist-to-hip ratio can reveal new therapeutic targets for abdominal obesity. We use exome sequences from 362,679 individuals to identify genes associated with waist-to-hip ratio adjusted for BMI (WHRadjBMI), a surrogate for abdominal fat that is causally linked to type 2 diabetes and coronary heart disease. Predicted loss of function (pLOF) variants in INHBE associate with lower WHRadjBMI and this association replicates in data from AMP-T2D-GENES. INHBE encodes a secreted protein, the hepatokine activin E. In vitro characterization of the most common INHBE pLOF variant in our study, indicates an in-frame deletion resulting in a 90% reduction in secreted protein levels. We detect associations with lower WHRadjBMI for variants in ACVR1C, encoding an activin receptor, further highlighting the involvement of activins in regulating fat distribution. These findings highlight activin E as a potential therapeutic target for abdominal obesity, a phenotype linked to cardiometabolic disease. Abdominal fat has been shown to increase cardiometabolic disease risk. In this study, the authors report that loss-of-function variants in the gene INHBE associate with lower BMI-adjusted waist-to-hip ratio, a surrogate measure of abdominal fat. [ABSTRACT FROM AUTHOR]

Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and type 2 diabetes (T2D) diagnosis in 379,066 exome-sequenced participants in the UK Biobank. We identified associations for variants in GCK, HNF1A and PDX1, which are known to be involved in Mendelian forms of diabetes. Notably, we uncovered novel associations for GIGYF1, a gene not previously implicated by human genetics in diabetes. GIGYF1 predicted loss of function (pLOF) variants associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 × 10–12) and HbA1c (4.33 mmol/mol, p = 1.28 × 10–14) as well as T2D diagnosis (OR = 4.15, p = 6.14 × 10–11). Multiple rare variants contributed to these associations, including singleton variants. GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. The association of GIGYF1 pLOF with T2D diagnosis replicated in an independent cohort from the Geisinger Health System. In addition, a common variant association for glucose and T2D was identified at the GIGYF1 locus. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes. [ABSTRACT FROM AUTHOR]

Novel modalities such as PROTAC and RNAi have the ability to inadvertently alter the abundance of endogenous proteins. Currently available in vitro secondary pharmacology assays, which evaluate off-target binding or activity of small molecules, do not fully assess the off-target effects of PROTAC and are not applicable to RNAi. To address this gap, we developed a proteomics-based platform to comprehensively evaluate the abundance of off-target proteins. First, we selected off-target proteins using genetics and pharmacology evidence. This process yielded 2813 proteins, which we refer to as the "selected off-target proteome" (SOTP). An iterative algorithm was then used to identify four human cell lines out of 932. The 4 cell lines collectively expressed ~ 80% of the SOTP based on transcriptome data. Second, we used mass spectrometry to quantify the intracellular and extracellular proteins from the selected cell lines. Among over 10,000 quantifiable proteins identified, 1828 were part of the predefined SOTP. The SOTP was designed to be easily modified or expanded, owing to the rational selection process developed and the label free LC–MS/MS approach chosen. This versatility inherent to our platform is essential to design fit-for-purpose studies that can address the dynamic questions faced in investigative toxicology. [ABSTRACT FROM AUTHOR]

Understanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1. Circulating liver enzymes, like alanine aminotransferase (ALT) and aspartate aminotransferase (AST), are highly heritable and predictive of disease. Here, the authors perform a genome-wide association study on ALT and AST, revealing a rare variant in SLC30A10 associated with elevated ALT and AST. [ABSTRACT FROM AUTHOR]

Hereditary transthyretin-mediated (hATTR) amyloidosis is an underdiagnosed, progressively debilitating disease caused by mutations in the transthyretin (TTR) gene. V122I, a common pathogenic TTR mutation, is found in 3–4% of individuals of African ancestry in the United States and has been associated with cardiomyopathy and heart failure. To better understand the phenotypic consequences of carrying V122I, we conducted a phenome-wide association study scanning 427 ICD diagnosis codes in UK Biobank participants of African ancestry (n = 6062). Significant associations were tested for replication in the Penn Medicine Biobank (n = 5737) and the Million Veteran Program (n = 82,382). V122I was significantly associated with polyneuropathy in the UK Biobank (odds ratio [OR] = 6.4, 95% confidence interval [CI] 2.6–15.6, p = 4.2 × 10−5), which was replicated in the Penn Medicine Biobank (OR = 1.6, 95% CI 1.2–2.4, p = 6.0 × 10–3) and Million Veteran Program (OR = 1.5, 95% CI 1.2–1.8, p = 1.8 × 10−4). Polyneuropathy prevalence among V122I carriers was 2.1%, 9.0%, and 4.8% in the UK Biobank, Penn Medicine Biobank, and Million Veteran Program, respectively. The cumulative incidence of common hATTR amyloidosis manifestations (carpal tunnel syndrome, polyneuropathy, cardiomyopathy, heart failure) was significantly enriched in V122I carriers compared with non-carriers (HR = 2.8, 95% CI 1.7–4.5, p = 2.6 × 10−5) in the UK Biobank, with 37.4% of V122I carriers having at least one of these manifestations by age 75. Our findings show that V122I carriers are at increased risk of polyneuropathy. These results also emphasize the underdiagnosis of disease in V122I carriers with a significant proportion of subjects showing phenotypic changes consistent with hATTR amyloidosis. Greater understanding of the manifestations associated with V122I is critical for earlier diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Safety-related drug failures remain a major challenge for the pharmaceutical industry. One approach to ensuring drug safety involves assessing small molecule drug specificity by examining the ability of a drug candidate to interact with a panel of "off-target" proteins, referred to as secondary pharmacology screening. Information from human genetics and pharmacology can be used to select proteins associated with adverse effects for such screening. In an analysis of marketed drugs, we found a clear relationship between the genetic and pharmacological phenotypes of a drug's off-target proteins and the observed drug side effects. In addition to using this phenotypic information for the selection of secondary pharmacology screens, we also show that it can be used to help identify drug off-target protein interactions responsible for drug-related adverse events. We anticipate that this phenotype-driven approach to secondary pharmacology screening will help to reduce safety-related drug failures due to drug off-target protein interactions. [ABSTRACT FROM AUTHOR]

The characterization of mutational processes that generate sequence diversity in the human genome is of paramount importance both to medical genetics and to evolutionary studies. To understand how the age and sex of transmitting parents affect de novo mutations, here we sequence 1,548 Icelanders, their parents, and, for a subset of 225, at least one child, to 35× genome-wide coverage. We find 108,778 de novo mutations, both single nucleotide polymorphisms and indels, and determine the parent of origin of 42,961. The number of de novo mutations from mothers increases by 0.37 per year of age (95% CI 0.32-0.43), a quarter of the 1.51 per year from fathers (95% CI 1.45-1.57). The number of clustered mutations increases faster with the mother's age than with the father's, and the genomic span of maternal de novo mutation clusters is greater than that of paternal ones. The types of de novo mutation from mothers change substantially with age, with a 0.26% (95% CI 0.19-0.33%) decrease in cytosine-phosphate-guanine to thymine-phosphate-guanine (CpG>TpG) de novo mutations and a 0.33% (95% CI 0.28-0.38%) increase in C>G de novo mutations per year, respectively. Remarkably, these age-related changes are not distributed uniformly across the genome. A striking example is a 20 megabase region on chromosome 8p, with a maternal C>G mutation rate that is up to 50-fold greater than the rest of the genome. The age-related accumulation of maternal non-crossover gene conversions also mostly occurs within these regions. Increased sequence diversity and linkage disequilibrium of C>G variants within regions affected by excess maternal mutations indicate that the underlying mutational process has persisted in humans for thousands of years. Moreover, the regional excess of C>G variation in humans is largely shared by chimpanzees, less by gorillas, and is almost absent from orangutans. This demonstrates that sequence diversity in humans results from evolving interactions between age, sex, mutation type, and genomic location. [ABSTRACT FROM AUTHOR]

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10−8). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34+ stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal. [ABSTRACT FROM AUTHOR]

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease. [ABSTRACT FROM AUTHOR]

Background Recent chromatin immunoprecipitation (ChIP) experiments in fly, mouse, and human have revealed the existence of high-occupancy target (HOT) regions or "hotspots" that show enrichment across many assayed DNA-binding proteins. Similar co-enrichment observed in yeast so far has been treated as artifactual, and has not been fully characterized. Results Here we reanalyze ChIP data from both array-based and sequencing-based experiments to show that in the yeast S. cerevisiae, the collective enrichment phenomenon is strongly associated with proximity to noncoding RNA genes and with nucleosome depletion. DNA sequence motifs that confer binding affinity for the proteins are largely absent from these hotspots, suggesting that protein-protein interactions play a prominent role. The hotspots are condition-specific, suggesting that they reflect a chromatin state or protein state, and are not a static feature of underlying sequence. Additionally, only a subset of all assayed factors is associated with these loci, suggesting that the co-enrichment cannot be simply explained by a chromatin state that is universally more prone to immunoprecipitation. Conclusions Together our results suggest that the co-enrichment patterns observed in yeast represent transcription factor co-occupancy. More generally, they make clear that great caution must be used when interpreting ChIP enrichment profiles for individual factors in isolation, as they will include factor-specific as well as collective contributions. [ABSTRACT FROM AUTHOR]

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease. [ABSTRACT FROM AUTHOR]

Association studies provide genome-wide information about the genetic basis of complex disease, but medical research has focused primarily on protein-coding variants, owing to the difficulty of interpreting noncoding mutations. This picture has changed with advances in the systematic annotation of functional noncoding elements. Evolutionary conservation, functional genomics, chromatin state, sequence motifs and molecular quantitative trait loci all provide complementary information about the function of noncoding sequences. These functional maps can help with prioritizing variants on risk haplotypes, filtering mutations encountered in the clinic and performing systems-level analyses to reveal processes underlying disease associations. Advances in predictive modeling can enable data-set integration to reveal pathways shared across loci and alleles, and richer regulatory models can guide the search for epistatic interactions. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. Ultimately, advances in regulatory and systems genomics can help unleash the value of whole-genome sequencing for personalized genomic risk assessment, diagnosis and treatment. [ABSTRACT FROM AUTHOR]

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ?4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ?60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease. [ABSTRACT FROM AUTHOR]

Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease. [ABSTRACT FROM AUTHOR]

Regulation of gene expression is a highly complex process that requires the concerted action of many proteins, including sequence-specific transcription factors, cofactors, and chromatin proteins. In higher eukaryotes, the interplay between these proteins and their interactions with the genome still is poorly understood. We systematically mapped the in vivo binding sites of seven transcription factors with diverse physiological functions, five cofactors, and two heterochromatin proteins at ≈1-kb resolution in a 2.9 Mb region of the Drosophila melanogaster genome. Surprisingly, all tested transcription factors and cofactors show strongly overlapping localization patterns, and the genome contains many ‘hotspots’ that are targeted by all of these proteins. Several control experiments show that the strong overlap is not an artifact of the techniques used. Colocalization hotspots are 1-5 kb in size, spaced on average by ≈50 kb, and preferentially located in regions of active transcription. We provide evidence that protein-protein interactions play a role in the hotspot association of some transcription factors. Colocalization hotspots constitute a previously uncharacterized type of feature in the genome of Drosophila, and our results provide insights into the general targeting mechanisms of transcription regulators in a higher eukaryote. [ABSTRACT FROM AUTHOR]

In the original version of this article, there were errors in the labelling of the colours in the key of Figure 2, whereby the labeling of the third and fourth of the four colours was reversed. This has been corrected in both the PDF and HTML versions of the article. [ABSTRACT FROM AUTHOR]

Only a small fraction of early drug programs progress to the market, due to safety and efficacy failures, despite extensive efforts to predict safety. Characterizing the effect of natural variation in the genes encoding drug targets should present a powerful approach to predict side effects arising from drugging particular proteins. In this retrospective analysis, we report a correlation between the organ systems affected by genetic variation in drug targets and the organ systems in which side effects are observed. Across 1819 drugs and 21 phenotype categories analyzed, drug side effects are more likely to occur in organ systems where there is genetic evidence of a link between the drug target and a phenotype involving that organ system, compared to when there is no such genetic evidence (30.0 vs 19.2%; OR = 1.80). This result suggests that human genetic data should be used to predict safety issues associated with drug targets. Safety issues including side effects are one of the major factors causing failure of clinical trials in drug development. Here, the authors leverage information about phenotypes associated with variation in genes encoding drug targets to predict drug-treatment-related side effects. [ABSTRACT FROM AUTHOR]

Searching for novel sequence variants associated with cholesterol levels is of particular interest due to the causative role of non-HDL cholesterol levels in cardiovascular disease. Through whole-genome sequencing of 15,220 Icelanders and imputation of the variants identified, we discovered a rare missense variant in NR1H4 (R436H) associating with lower levels of total cholesterol (effect = −0.47 standard deviations or −0.55 mmol L−1, p = 4.21 × 10−10, N = 150,211). Importantly, NR1H4 R436H also associates with lower levels of non-HDL cholesterol and, consistent with this, protects against coronary artery disease. NR1H4 encodes FXR that regulates bile acid homeostasis, however, we do not detect a significant association between R436H and biological markers of liver function. Transcriptional profiling of hepatocytes carrying R436H shows that it is not a loss-of-function variant. Rather, we observe changes in gene expression compatible with effects on lipids. These findings highlight the role of FXR in regulation of cholesterol levels in humans. Aimee Deaton et al. identify a rare missense variant in the bile acid receptor gene NR1H4, which is associated with lower levels of total cholesterol in the Icelandic population. Hepatocytes expressing the missense variant showed altered expression of a small number of genes, with enrichment in lipid-related pathways. [ABSTRACT FROM AUTHOR]