Patterns of genic intolerance of rare copy number variation in 59,898 human exomes.

Copy number variation (CNV) affecting protein-coding genes contributes substantially to human diversity and disease. Here we characterized the rates and properties of rare genic CNVs (<0.5% frequency) in exome sequencing data from nearly 60,000 individuals in the Exome Aggregation Consortium (ExAC) database. On average, individuals possessed 0.81 deleted and 1.75 duplicated genes, and most (70%) carried at least one rare genic CNV. For every gene, we empirically estimated an index of relative intolerance to CNVs that demonstrated moderate correlation with measures of genic constraint based on single-nucleotide variation (SNV) and was independently correlated with measures of evolutionary conservation. For individuals with schizophrenia, genes affected by CNVs were more intolerant than in controls. The ExAC CNV data constitute a critical component of an integrated database spanning the spectrum of human genetic variation, aiding in the interpretation of personal genomes as well as population-based disease studies. These data are freely available for download and visualization online

Genetic risk factors have a substantial impact on healthy life years

The impact of genetic variation on overall disease burden has not been comprehensively evaluated. We introduce an approach to estimate the effect of genetic risk factors on disability-adjusted life years (DALYs; 'lost healthy life years'). We use genetic information from 735,748 individuals and consider 80 diseases. Rare variants had the highest effect on DALYs at the individual level. Among common variants, rs3798220 (LPA) had the strongest individual-level effect, with 1.18 DALYs from carrying 1 versus 0 copies. Being in the top 10% versus the bottom 90% of a polygenic score for multisite chronic pain had an effect of 3.63 DALYs. Some common variants had a population-level effect comparable to modifiable risk factors such as high sodium intake and low physical activity. Attributable DALYs vary between males and females for some genetic exposures. Genetic risk factors can explain a sizable number of healthy life years lost both at the individual and population level.Peer reviewe

Effects of intraduodenal glutamine on incretin hormone and insulin release, the glycemic response to an intraduodenal glucose infusion, and antropyloroduodenal motility in health and type 2 diabetes

OBJECTIVE Glutamine reduces postprandial glycemia when given before oral glucose. We evaluated whether this is mediated by stimulation of insulin and/or slowing of gastric emptying. RESEARCH DESIGN AND METHODS Ten healthy subjects were studied during intraduodenal (ID) infusion of glutamine (7.5 or 15 g) or saline over 30 min, followed by glucose (75 g over 100 min), while recording antropyloroduodenal pressures. Ten patients with type 2 diabetes mellitus (T2DM) were also studied with 15 g glutamine or saline. RESULTS ID glutamine stimulated glucagon-like peptide 1 (GLP-1; healthy: P < 0.05; T2DM: P < 0.05), glucose-dependent insulinotropic polypeptide (GIP; P = 0.098; P < 0.05), glucagon (P < 0.01; P < 0.001), insulin (P = 0.05; P < 0.01), and phasic pyloric pressures (P < 0.05; P < 0.05), but did not lower blood glucose (P = 0.077; P = 0.5). CONCLUSIONS Glutamine does not lower glycemia after ID glucose, despite stimulating GLP-1, GIP, and insulin, probably due to increased glucagon. Its capacity for pyloric stimulation suggests that delayed gastric emptying is a major mechanism for lowering glycemia when glutamine is given before oral glucose.Jessica Chang, Tongzhi Wu, Jerry R. Greenfield, Dorit Samocha-Bonet, Michael Horowitz, and Christopher K. Rayne

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources, we find genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both inherited and de novo variation, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology

Metabolically protective cytokines adiponectin and fibroblast growth factor-21 are increased by acute overfeeding in healthy humans

Context: Circulating levels of metabolically protective and adverse cytokines are altered in obese humans and rodent models. However, it is not clear whether these cytokines are altered rapidly in response to over-nutrition, or as a later consequence of the obese state. Methods: Forty sedentary healthy individuals were examined prior to and at 3 and 28 days of high fat overfeeding (+1250 kCal/day, 45% fat). Insulin sensitivity (hyperinsulinaemic-euglycaemic clamp), adiposity, serum levels of adiponectin and fibroblast growth factor-21 (FGF21), fatty acid binding protein-4 (FABP4), lipocalin-2 and plasminogen activator factor-1 (PAI1) were assessed. Statistics were performed by repeated measures ANOVA. Results: Overfeeding increased weight, body fat and liver fat, fasting glucose, insulin and reduced insulin sensitivity by clamp (all P <0.05). Metabolically protective cytokines, adiponectin and FGF21 were increased at day 3 of overfeeding (P ≤0.001) and adiponectin was also elevated at day 28 (P=0.001). FABP4, lipocalin-2 and PAI-1 were not changed by overfeeding at either time point. Conclusion: Metabolically protective cytokines, adiponectin and FGF-21, were increased by over nutrition and weight gain in healthy humans, despite increases in insulin resistance. We speculate that this was in attempt to maintain glucose homeostasis in a state of nutritional excess. PAI-I, FABP4 and lipocalin 2 were not altered by overfeeding suggesting that changes in these cytokines may be a later consequence of the obese state.Leonie K. Heilbronn, Lesley V. Campbell, Aimin Xu, Dorit Samocha-Bone

Modified penetrance of coding variants by cis-regulatory variation contributes to disease risk

Coding variants represent many of the strongest associations between genotype and phenotype; however, they exhibit interindividual differences in effect, termed 'variable penetrance'. Here, we study how cis-regulatory variation modifies the penetrance of coding variants. Using functional genomic and genetic data from the Genotype-Tissue Expression Project (GTEx), we observed that in the general population, purifying selection has depleted haplotype combinations predicted to increase pathogenic coding variant penetrance. Conversely, in cancer and autism patients, we observed an enrichment of penetrance increasing haplotype configurations for pathogenic variants in disease-implicated genes, providing evidence that regulatory haplotype configuration of coding variants affects disease risk. Finally, we experimentally validated this model by editing a Mendelian single-nucleotide polymorphism (SNP) using CRISPR/Cas9 on distinct expression haplotypes with the transcriptome as a phenotypic readout. Our results demonstrate that joint regulatory and coding variant effects are an important part of the genetic architecture of human traits and contribute to modified penetrance of disease-causing variants.Peer reviewe

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

The contribution of X-linked coding variation to severe developmental disorders

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders

Interpreting short tandem repeat variations in humans using mutational constraint

Identifying regions of the genome that are depleted of mutations can reveal potentially deleterious variants. Short tandem repeats (STRs), also known as microsatellites, are among the largest contributors of de novo mutations in humans. However, per-locus studies of STR mutations have been limited to highly ascertained panels of several dozen loci. Here, we harnessed bioinformatics tools and a novel analytical framework to estimate mutation parameters for each STR in the human genome by correlating STR genotypes with local sequence heterozygosity. We applied our method to obtain robust estimates of the impact of local sequence features on mutation parameters and used this to create a framework for measuring constraint at STRs by comparing observed vs. expected mutation rates. Constraint scores identified known pathogenic variants with early onset effects. Our metric will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies