Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Plasma lactate and stress hormones in common carp (Cyprinus carpio) and rainbow trout (Oncorhynchus mykiss) during stepwise decreasing oxygen levels

By measuring the lactate response it is possible to determine whether a teleost is able to adapt to a certain oxygen level. It is hypothesized that recovery will occur at oxygen levels above the critical oxygen level (PO2)(crit) reflected by a transient lactate increase. In contrast, continuous lactate accumulation occurs at oxygen levels below the (PO2)(crit), which will be lethal in case of prolonged exposure. Since catecholamines as well as cortisol increase the availability of glucose, it is expected that these stress hormones are involved in the activation of the anaerobic metabolism. Common carp and rainbow trout were cannulated and exposed to stepwise decreasing oxygen levels. At each oxygen level blood samples were taken at several time-points and analyzed for plasma lactate, adrenaline, noradrenaline and cortisol. The results show that both individual and inter-specific differences in lactate response occur during exposure to hypoxia. These differences can be associated with observed differences in behaviour. Whereas carp stayed quiet during the hypoxia treatment, trout displayed individually different behaviour. In contrast to the passive responders, the active responding trout did not survive as a result of continuous lactate accumulation. Interestingly, both in carp and trout a strong correlation exists between the lactate and catecholamine levels. This may indicate that these stress hormones are of importance for the metabolic changes occurring during anaerobic activation