Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. 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 scores5 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.

Understanding the impact of maternal and infant nutrition on infant/child health: multiethnic considerations, knowledge translation, and future directions for equitable health research.

A mother's intrauterine environment influences her health and that of her offspring, at birth and in the future. Herein, we present an overview of our Canadian Institutes of Health Research (CIHR)-funded grant "Understanding the impact of maternal and infant nutrition on infant/child health"-set within The NutriGen Birth Cohort Alliance. NutriGen is a consortium of four Canadian prospective birth cohorts representing >5000 mother-child pairs of diverse ethnic groups including South Asians, White Europeans, and Indigenous peoples. We summarize our objectives and main findings on outcomes of maternal diet, gestational diabetes, birth weight, cardiometabolic health, the microbiome, and epigenetic modifications. We append this work with 10 key messages when conducting multiethnic research and review our knowledge translation products. We describe the clinical impact of our research on maternal and child health and conclude with future directions on biomarker discovery, expansion to other ethnic groups, and interventions for high-risk populations.

Maternal smoking DNA methylation risk score associated with health outcomes in offspring of European and South Asian ancestry.

Background: Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations. Methods: We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504). Results: Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (-0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (-0.043±0.013 kg, p=0.0011) in the combined cohorts. Conclusions: This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers. Funding: This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.

A genome-wide association, polygenic risk score and sex study on opioid use disorder treatment outcomes.

Opioid use disorder continues to be a health concern with a high rate of opioid related deaths occurring worldwide. Medication Assisted Treatments (MAT) have been shown to reduce opioid withdrawal, cravings and opioid use, however variability exists in individual's treatment outcomes. Sex-specific differences have been reported in opioid use patterns, polysubstance use and health and social functioning. Candidate gene studies investigating methadone dose as an outcome have identified several candidate genes and only five genome-wide associations studies have been conducted for MAT outcomes. This study aimed to identify genetic variants associated with MAT outcomes through genome-wide association study (GWAS) and test the association between genetic variants previously associated with methadone dose through a polygenic risk score (PRS). Study outcomes include: continued opioid use, relapse, methadone dose and opioid overdose. No genome-wide significance SNPs or sex-specific results were identified. The PRS identified statistically significant results (p < 0.05) for the outcome of methadone dose (R2 = 3.45 × 10-3). No other PRS was statistically significant. This study provides evidence for association between a PRS and methadone dose. More research on the PRS to increase the variance explained is needed before it can be used as a tool to help identify a suitable methadone dose within this population.