Claudia H.T. Tam

Abstract Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes 1,2 and molecular mechanisms that are often specific to cell type 3,4 . 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 < 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 scores 5 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.

Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P<5 × 10(-8)), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P<0.007). These results indicate that expansion of single ethnic GWAS is still useful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but also for common loci across different ethnicities.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Aims/hypothesis Accumulating evidence suggests an impact of gestational weight gain (GWG) on pregnancy outcomes; however, data on cardiometabolic risk factors later in life have not been comprehensively studied. This study aimed to evaluate the relationship between GWG and cardiometabolic risk in offspring aged 7 years. Methods We included a total of 905 mother-child pairs who enrolled in the follow-up visit of the multicentre Hyperglycemia and Adverse Pregnancy Outcome study, at the Hong Kong Centre. Women were classified as having gained weight below, within or exceeding the 2009 Institute of Medicine (IOM) guidelines. A standardised GWG according to pre-pregnancy BMI categories was calculated to explore for any quadratic relationship. Results Independent of pre-pregnancy BMI, gestational hyperglycaemia and other confounders, women who gained more weight than the IOM recommendations had offspring with a larger body size and increased odds of adiposity, hypertension and insulin resistance (range of p values of all the traits: 4.6 10 -9 < p < 0.0390) than women who were within the recommended range of weight gain during pregnancy. Meanwhile, women who gained less weight than outlined in the recommendations had offspring with increased risks of hypertension and insulin resistance, compared with those who gained weight within the recommended range (7.9 10 -3 < p < 0.0477). Quadratic relationships for diastolic blood pressure, AUC for insulin, pancreatic beta cell function and insulin sensitivity index were confirmed in the analysis of standardised GWG (1.4 10 -3 < p quadratic < 0.0282). Further adjustment for current BMI noticeably attenuated the observed associations. Conclusions/interpretation Both excessive and inadequate GWG have independent and significant impacts on childhood adiposity, hypertension and insulin resistance. Our findings support the notion that adverse intrauterine exposures are associated with persistent cardiometabolic risk in the offspring.

BACKGROUND: Maternal gestational weight gain (GWG) influences not only on pregnancy outcome but also impacts on mothers' and children's long-term health. However, there is no consensus on recommendations of optimal GWG in Asians or the Chinese population. METHODS: We performed a secondary analysis of the birth outcome of Chinese women who had joined the "Hyperglycemia and Adverse Pregnancy Outcome" study in Hong Kong and their children's cardiometabolic risk at 7-year of age. Optimal ranges of GWG were derived from models based on the probabilities of small for gestational age and large for gestational age (model 1), lean and fat infants (model 2) and the integration of model 1 and 2 (model 3), and were compared with that recommended by the Institute of Medicine (IOM) on children's cardiometabolic risk. FINDINGS: GWG range derived from model 2 is associated with 8 cardiometabolic risk factors, while that from models 1 and 3 are associated with 1 and 7 of them respectively. Mothers whose GWG lie within the recommended range increases from 40.8% according to the IOM recommendation to 50.2% according to that derived from model 2. INTERPRETATION: Optimal GWG derived from model 2 (i.e. 14.0-18.5 kg, 9.0-16.5 kg and 5.0-11.0 kg for underweight, normal weight and overweight Chinese women, respectively) appeared to be associated with the lowest cardiometabolic risk in the offspring. FUNDING: General Research Fund of the Research Grants Council of the Hong Kong SAR, China (grants CUHK 473408 and, in part, CUHK 471713).