The pancreas contains both exocrine and endocrine cells, but the molecular mechanisms controlling the differentiation of these cell types are largely unknown. Despite their endodermal origin, pancreatic endocrine cells share several molecular characteristics with neurons, and, like neurons in the central nervous system, differentiating endocrine cells in the pancreas appear in a scattered fashion within a field of progenitor cells. This indicates that they may be generated by lateral specification through Notch signalling. Here, to test this idea, we analysed pancreas development in mice genetically altered at several steps in the Notch signalling pathway. Mice deficient for Delta-like gene 1 (Dll1) or the intracellular mediator RBP-Jkappa showed accelerated differentiation of pancreatic endocrine cells. A similar phenotype was observed in mice over-expressing neurogenin 3 (ngn 3) or the intracellular form of Notch3 (a repressor of Notch signalling). These data provide evidence that ngn3 acts as proendocrine gene and that Notch signalling is critical for the decision between the endocrine and progenitor/exocrine fates in the developing pancreas.

SUMMARY Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 exhibit effect sizes that are unusually high for GWAS and account for 10-60% of metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism, and Crohn’s disease. Taken together our study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes.