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To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS) including 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican American ancestry. We observed significant excess in directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven novel T2D susceptibility loci. Furthermore, we observed considerable improvements in fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterisation of complex trait loci, and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in East Asian populations. The first stage meta-analysis of eight T2D genome-wide association studies (6,952 cases and 11,865 controls) was followed by a second stage in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which were mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of T2D association for PEPD5 and HNF4A6,7 has been detected in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings derived from East Asians provide new perspectives on the etiology of T2D.

In confirmation of our original hypothesis, IGT in the offspring is a long-term complication of maternal diabetes. Excessive insulin secretion in utero, as assessed by AFI concentration, is a strong predictor of IGT in childhood.

We have suggested that altered maternal metabolism may affect the subsequent anthropometric and neuropsychological development of children who were in utero during disturbances in maternal fuel economy. This study reports the physical growth through 8 yr of age and the neuropsychological development through 4 yr of age in offspring of diabetic mothers (ODM). At birth, 50% of infants had weights greater than 90th percentile for gestational age. By 12 mo, length and weight were similar to the general population. Height remained normal until 7 yr of age, when it became slightly greater than average. After 5 yr of age, relative weight increased dramatically, and by 8 yr of age, half of the ODM had weights greater than 90th percentile. This childhood obesity in ODM is correlated with maternal prepregnant weight and independently with amniotic fluid insulin at 32-38 wk gestation. The Brazelton Neonatal Behavioral Assessment Scale (BNBAS) was administered to 185 newborn ODM. Significant correlations were found between poorer second- and third-trimester glycemic regulation and lower scores in three of four newborn BNBAS dimensions. The Stanford-Binet Intelligence Scale was measured in 102 ODM at 4 yr of age. We found an inverse correlation between childhood IQ and second- and third-trimester maternal lipid metabolism (serum free fatty acids and beta-hydroxybutyrate). This correlation is not explained by adverse perinatal events, socioeconomic status, maternal IQ, ethnicity, or diabetes type. These long-range associations between altered maternal metabolism and childhood growth and development continue to support Freinkel's hypothesis of fuel-mediated teratogenesis.

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10−8), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.

l e t t e r sTo identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery metaanalysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall metaanalysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study.