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.

To characterise 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 cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). 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 SNVs. 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.

We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Background NUT midline carcinoma, renamed NUT carcinoma (NC), is an aggressive squamous cancer defined by rearrangement of the NUTM1 gene. Although a subset of patients can be cured, for the majority of patients the prognosis is grim. We sought to classify patients into risk groups based on molecular and clinicopathologic factors at the time of diagnosis. Methods Clinicopathologic variables and survival outcomes were extracted for a total of 141 NC patients from the NUT midline carcinoma Registry using questionnaires and medical records. Translocation type was identified by molecular analyses. Survival tree regression analysis was performed to determine risk factors associated with overall survival (OS). Results For 141 patients, the median age at diagnosis was 23.6 years. Fifty-one percent had thoracic origin compared with 49% nonthoracic sites (41% head and neck, 6% bone or soft tissue, 1% other). The median OS was 6.5 months (95% confidence interval [CI] = 5.8 to 9.1 months). Most patients had the BRD4-NUTM1 fusion (78%), followed by BRD3-NUTM1 (15%) and NSD3-NUTM1 (6%). Survival tree regression identified three statistically distinct risk groups among 124 patients classified by anatomical site and genetics: group A is nonthoracic primary, BRD3-, or NSD3-NUT (n = 12, median OS = 36.5 months, 95% CI = 12.5 to not reported months); group B is nonthoracic primary, BRD4-NUT (n = 45, median OS = 10 months, 95% CI = 7 to 14.6 months); and group C is thoracic primary (n = 67, median OS = 4.4 months, 95% CI = 3.5 to 5.6 months). Only groups A and B had long-term (≥3 years, n = 12) survivors. Conclusions We identify three risk groups defined by anatomic site and NUT fusion type. Nonthoracic primary with non-BRD4-NUT fusion confers the best prognosis, followed by nonthoracic primary with BRD4-NUT. Thoracic NC patients, regardless of the NUT fusion, have the worst survival.