Relation between Retinopathy and Progression of Coronary Artery Calcium in Individuals with Versus Without Diabetes Mellitus (From the Multi-Ethnic Study of Atherosclerosis).

Retinopathy is a microvascular complication of diabetes mellitus (DM); however, it is also increasingly recognized in persons without DM. The microvascular diseases may play a prominent role in coronary heart disease (CHD) development in individuals with DM. We performed the study to evaluate the relation between non-DM retinopathy and CHD and also the association between baseline retinopathy and incidence and progression of CHD in individuals with and without DM. We included 5709 subjects with and without DM from the Multi-Ethnic Study of Atherosclerosis, who had retinal photos and coronary artery calcium score (CACS) available. We studied the association between baseline retinopathy and incidence and progression of coronary artery calcification (CAC) in subjects with and without DM. In DM group, the presence of retinopathy was significantly associated with an increased rate of CAC (RR 1.3 (95% CI [1.02, 1.66]) after adjusting for age, sex, race, follow-up time, and CHD risk factors. In non-DM group, the presence of retinopathy was not significantly associated with increased risk of CAC, however, the interaction between presence of retinopathy and DM status was not statistically significant. Within the DM group with CAC present at baseline, the presence of retinopathy was significantly associated with greater CAC progression (113 Agatson units (AU) greater, (95% CI [51-174]). In the non-DM group with present CAC at baseline; the presence of retinopathy was associated with 24 (95% CI [-0.69, 48.76]) AU higher CAC progression. All findings were adjusted for CHD risk factors. In conclusion, after adjustment for major CHD risk factors, retinopathy was associated with progression of CAC in both DM and non-DM individuals. However, the association was stronger in those with DM

Genetically Determined Plasma Lipid Levels and Risk of Diabetic Retinopathy: A Mendelian Randomization Study.

Results from observational studies examining dyslipidemia as a risk factor for diabetic retinopathy (DR) have been inconsistent. We evaluated the causal relationship between plasma lipids and DR using a Mendelian randomization approach. We pooled genome-wide association studies summary statistics from 18 studies for two DR phenotypes: any DR (N = 2,969 case and 4,096 control subjects) and severe DR (N = 1,277 case and 3,980 control subjects). Previously identified lipid-associated single nucleotide polymorphisms served as instrumental variables. Meta-analysis to combine the Mendelian randomization estimates from different cohorts was conducted. There was no statistically significant change in odds ratios of having any DR or severe DR for any of the lipid fractions in the primary analysis that used single nucleotide polymorphisms that did not have a pleiotropic effect on another lipid fraction. Similarly, there was no significant association in the Caucasian and Chinese subgroup analyses. This study did not show evidence of a causal role of the four lipid fractions on DR. However, the study had limited power to detect odds ratios less than 1.23 per SD in genetically induced increase in plasma lipid levels, thus we cannot exclude that causal relationships with more modest effect sizes exist

Genome-wide association study of iron traits and relation to diabetes in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL): potential genomic intersection of iron and glucose regulation?

Genetic variants contribute to normal variation of iron-related traits and may also cause clinical syndromes of iron deficiency or excess. Iron overload and deficiency can adversely affect human health. For example, elevated iron storage is associated with increased diabetes risk, although mechanisms are still being investigated. We conducted the first genome-wide association study of serum iron, total iron binding capacity (TIBC), transferrin saturation, and ferritin in a Hispanic/Latino cohort, the Hispanic Community Health Study/Study of Latinos (>12 000 participants) and also assessed the generalization of previously known loci to this population. We then evaluated whether iron-associated variants were associated with diabetes and glycemic traits. We found evidence for a novel association between TIBC and a variant near the gene for protein phosphatase 1, regulatory subunit 3B (PPP1R3B; rs4841132, β = -0.116, P = 7.44 × 10-8). The effect strengthened when iron deficient individuals were excluded (β = -0.121, P = 4.78 × 10-9). Ten of sixteen variants previously associated with iron traits generalized to HCHS/SOL, including variants at the transferrin (TF), hemochromatosis (HFE), fatty acid desaturase 2 (FADS2)/myelin regulatory factor (MYRF), transmembrane protease, serine 6 (TMPRSS6), transferrin receptor (TFR2), N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2), ABO blood group (ABO), and GRB2 associated binding protein 3 (GAB3) loci. In examining iron variant associations with glucose homeostasis, an iron-raising variant of TMPRSS6 was associated with lower HbA1c levels (P = 8.66 × 10-10). This association was attenuated upon adjustment for iron measures. In contrast, the iron-raising allele of PPP1R3B was associated with higher levels of fasting glucose (P = 7.70 × 10-7) and fasting insulin (P = 4.79 × 10-6), but these associations were not attenuated upon adjustment for TIBC-so iron is not likely a mediator. These results provide new genetic information on iron traits and their connection with glucose homeostasis

Multiethnic Genome-Wide Association Study of Diabetic Retinopathy Using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control

Correction: Volume69, Issue6 Page1306-1306 DOI10.2337/db20-er06a Published JUN 2020To identify genetic variants associated with diabetic retinopathy (DR), we performed a large multiethnic genome-wide association study. Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P valuePeer reviewe

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD

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 \u3c 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

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 &lt; 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.</p

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (Stage 1, n=59,771) and generalized our findings in 9 additional studies (HISLA Stage 2, n=10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA Stage 1 and existing consortia of European and African ancestries. In our HISLA Stage 1+2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified three secondary signals for BMI, 28 for height, and two for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification