Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes

Analysis of Whole Exome Sequencing with Cardiometabolic Traits Using Family‐Based Linkage and Association in the IRAS Family Study

Family-based methods are a potentially powerful tool to identify trait-defining genetic variants in extended families, particularly when used to complement conventional association analysis. We utilized two-point linkage analysis and single variant association analysis to evaluate whole exome sequencing (WES) data from 1205 Hispanic Americans (78 families) from the Insulin Resistance Atherosclerosis Family Study. WES identified 211,612 variants above the minor allele frequency threshold of ≥0.005. These variants were tested for linkage and/or association with 50 cardiometabolic traits after quality control checks. Two-point linkage analysis yielded 10,580,600 logarithm of the odds (LOD) scores with 1148 LOD scores ≥3, 183 LOD scores ≥4, and 29 LOD scores ≥5. The maximal novel LOD score was 5.50 for rs2289043:T>C, in UNC5C with subcutaneous adipose tissue volume. Association analysis identified 13 variants attaining genome-wide significance (P < 5 × 10-08 ), with the strongest association between rs651821:C>T in APOA5 and triglyceride levels (P  =  3.67 × 10-10 ). Overall, there was a 5.2-fold increase in the number of informative variants detected by WES compared to exome chip analysis in this population, nearly 30% of which were novel variants relative to the Database of Single Nucleotide Polymorphisms (dbSNP) build 138. Thus, integration of results from two-point linkage and single-variant association analysis from WES data enabled identification of novel signals potentially contributing to cardiometabolic traits

Associations between inhibitory control, eating behaviours and adiposity in 6 year-old children

BackgroundLower inhibitory control has been associated with obesity. One prediction is that lower inhibitory control underlies eating behaviours that promote increased energy intakes. This study examined the relationships between children’s inhibitory control measured using the Stop Signal Task (SST), body composition and eating behaviours, which included self-served portion size, number of servings, eating rate, and energy intake at lunch and in an eating in the absence of hunger (EAH) task.MethodsThe sample included 255 6-year-old children from an Asian cohort. Stop-signal reaction time (SSRT) was used as an index of inhibitory control. Children participated in a recorded self-served lunchtime meal, followed by the EAH task where they were exposed to energy-dense snacks. Behavioural coding of oral processing was used to estimate eating rates (g/min). BMI, waist circumference and skinfolds were used as indices of adiposity.ResultsChildren with lower inhibitory control tended to self-serve larger food portions (p = 0.054), had multiple food servings (p = 0.006) and significantly faster eating rates (p = 0.041). Inhibitory control did not predict energy intake at lunch (p = 0.17) or during the EAH task (p = 0.45), and was unrelated to measures of adiposity (p &gt; 0.32). Twenty percent of the children in the sample had problems focusing on the SST and were described as ‘restless’. Post-hoc analysis revealed that these children had lower inhibitory control (p &lt; 0.001) and consumed more energy during the EAH task (p = 0.01), but did not differ in any other key outcomes from the rest of the sample (p &gt; 0.1).ConclusionsChildren with lower inhibitory control showed a trend to select larger food portions, had multiple food servings and faster eating rates, but were equally as responsive to snacks served in the absence of hunger as children with better inhibitory control. Inhibitory control may impact a number of eating behaviours, not limited to energy-dense snacks.</p

Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes