Genetics of diabetes mellitus and diabetes complications

We aimed to examine the mortality rates, excess mortality and causes of death in diabetic patients from ten centres throughout the world. A mortality follow-up of 4713 WHO Multinational Study of Vascular Disease in Diabetes (WHO MSVDD) participants from ten centres was carried out, causes of death were ascertained and age-adjusted mortality rates were calculated by centre, sex and type of diabetes. Excess mortality, compared with the background population, was assessed in terms of standardised mortality ratios (SMRs) for each of the 10 cohorts. Cardiovascular disease was the most common underlying cause of death, accounting for 44 % of deaths in Type I (insulin-dependent) diabetes mellitus and 52 % of deaths in Type II (non-insulin-dependent) diabetes mellitus. Renal disease accounted for 21% of deaths in Type I diabetes and 11% in Type II diabetes. For Type I diabetes, all-cause mortality rates were highest in Berlin men and Warsaw women, and lowest in London men and Zagreb women. For Type II diabetes, rates were highest in Warsaw men and Oklahoma women and lowest in Tokyo men and women. Age adjusted mortality rates and SMRs were generally higher in patients with Type I diabetes compared with those with Type II diabetes. Men and women in the Tokyo cohort had a very low excess mortality when compared with the background population. This study confirms the importance of cardiovascular disease as the major cause of death in people with both types of diabetes. The low excess mortality in the Japanese cohort could have implications for the possible reduction of the burden of mortality associated with diabetes in other parts of the world.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication ( n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen ( n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.