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. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities 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 truncating variants with 72% 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

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

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants

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 [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

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

Heterogenous Distribution of <i>MTHFR</i> Gene Variants among Mestizos and Diverse Amerindian Groups from Mexico

<div><p>Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme in folate metabolism. Folate deficiency has been related to several conditions, including neural tube defects (NTDs) and cardiovascular diseases. Hence, <i>MTHFR</i> genetic variants have been studied worldwide, particularly the C677T and A1298C. We genotyped the C677T and A1298C <i>MTHFR</i> polymorphisms in Mexican Amerindians (MAs), from the largest sample included in a genetic study (n = 2026, from 62 ethnic groups), and in a geographically-matched Mexican Mestizo population (MEZ, n = 638). The 677T allele was most frequent in Mexican individuals, particularly in MAs. The frequency of this allele in both MAs and MEZs was clearly enriched in the South region of the country, followed by the Central East and South East regions. In contrast, the frequency of the 1298C risk allele in Mexicans was one of the lowest in the world. Both in MAs and MEZs the variants 677T and 1298C displayed opposite allele frequency gradients from southern to northern Mexico. Our findings suggest that in Mestizos the 677T allele was derived from Amerindians while the 1298C allele was a European contribution. Some subgroups showed an allele frequency distribution that highlighted their genetic diversity. Notably, the distribution of the frequency of the 677T allele was consistent with that of the high incidence of NTDs reported in MEZ.</p></div

Geographic distribution of allele frequencies for the C677T polymorphism in the MA population.

<p>CDMX, Mexico City; MEX, Mexico State; MOR, Morelos; OAX, Oaxaca; PUE, Puebla; SLP, San Luis Potosí. Striped States were not sampled because they are inhabited by neighboring indigenous included in this study. *States without indigenous population [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163248#pone.0163248.ref032" target="_blank">32</a>].</p