A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease.

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia.

A low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker.

Background: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits.

Methods And Results: Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.

Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes.

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects).

The association of the mitochondrial DNA OriB variant (16184-16193 polycytosine tract) with type 2 diabetes in Europid populations.

Aims/hypothesis: The association between the mitochondrial DNA 16181-16193 polycytosine variant (known as the OriB variant as it maps to the OriB origin of replication) and type 2 diabetes has not been reliably characterised, with studies reporting conflicting results. We report a systematic review of published literature in Europid populations, new data from the Norfolk Diabetes Case-Control Study and a meta-analysis to help quantify this association.

Methods: We performed a systematic review identifying all the studies of the OriB variant and type 2 diabetes in Europid populations published before January 2013.

Contrasting signals of positive selection in genes involved in human skin-color variation from tests based on SNP scans and resequencing.

Background: Numerous genome-wide scans conducted by genotyping previously ascertained single-nucleotide polymorphisms (SNPs) have provided candidate signatures for positive selection in various regions of the human genome, including in genes involved in pigmentation traits. However, it is unclear how well the signatures discovered by such haplotype-based test statistics can be reproduced in tests based on full resequencing data. Four genes (oculocutaneous albinism II (OCA2), tyrosinase-related protein 1 (TYRP1), dopachrome tautomerase (DCT), and KIT ligand (KITLG)) implicated in human skin-color variation, have shown evidence for positive selection in Europeans and East Asians in previous SNP-scan data.