Dataset Information

A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes.

ABSTRACT: As the role of the environment - diet, exercise, alcohol and tobacco use and sleep among others - is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate incorporation of GxE interactions into single-gene and genome-wide association studies, we have compiled from the literature a database of GxE interactions relevant to nutrition, blood lipids, cardiovascular disease and type 2 diabetes. Over 550 such interactions have been incorporated into a single database, along with over 1430 instances where a lack of statistical significance was found. This database will serve as an important resource to researchers in genetics and nutrition in order to gain an understanding of which points in the human genome are sensitive to variations in diet, physical activity and alcohol use, among other lifestyle choices. Furthermore, this GxE database has been designed with future integration into a larger database of nutritional phenotypes in mind.

SUBMITTER: Lee YC

PROVIDER: S-EPMC3275815 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes.

Lee Yu-Chi YC Lai Chao-Qiang CQ Ordovas Jose M JM Parnell Laurence D LD

Journal of data mining in genomics & proteomics 20110101 1

As the role of the environment - diet, exercise, alcohol and tobacco use and sleep among others - is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate incorporation of GxE interactions into single-gene and genome-wide association studies, we have compiled from the literature a database of GxE interactions relevant to nutrition, blood lipids, cardiova ...[more]

PMID: 22328972

Similar Datasets

Project description:ImportanceBased on contemporary estimates in the US, evidence-based therapies for cardiovascular risk reduction are generally underused among patients with type 2 diabetes and atherosclerotic cardiovascular disease (ASCVD).ObjectiveTo determine the use of evidence-based cardiovascular preventive therapies in a broad US population with diabetes and ASCVD.Design, setting, and participantsThis multicenter cohort study used health system-level aggregated data within the National Patient-Centered Clinical Research Network, including 12 health systems. Participants included patients with diabetes and established ASCVD (ie, coronary artery disease, cerebrovascular disease, and peripheral artery disease) between January 1 and December 31, 2018. Data were analyzed from September 2020 until January 2021.ExposuresOne or more health care encounters in 2018.Main outcomes and measuresPatient characteristics by prescription of any of the following key evidence-based therapies: high-intensity statin, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin-receptor blocker (ARB) and sodium glucose cotransporter-2 inhibitors (SGLT2I) or glucagon-like peptide-1 receptor agonist (GLP-1RA).ResultsThe overall cohort included 324 706 patients, with a mean (SD) age of 68.1 (12.2) years and 144 169 (44.4%) women and 180 537 (55.6%) men. A total of 59 124 patients (18.2% ) were Black, and 41 470 patients (12.8%) were Latinx. Among 205 885 patients with specialized visit data from the prior year, 17 971 patients (8.7%) visited an endocrinologist, 54 330 patients (26.4%) visited a cardiologist, and 154 078 patients (74.8%) visited a primary care physician. Overall, 190 277 patients (58.6%) were prescribed a statin, but only 88 426 patients (26.8%) were prescribed a high-intensity statin; 147 762 patients (45.5%) were prescribed an ACEI or ARB, 12 724 patients (3.9%) were prescribed a GLP-1RA, and 8989 patients (2.8%) were prescribed an SGLT2I. Overall, 14 918 patients (4.6%) were prescribed all 3 classes of therapies, and 138 173 patients (42.6%) were prescribed none. Patients who were prescribed a high-intensity statin were more likely to be men (59.9% [95% CI, 59.6%-60.3%] of patients vs 55.6% [95% CI, 55.4%-55.8%] of patients), have coronary atherosclerotic disease (79.9% [95% CI, 79.7%-80.2%] of patients vs 73.0% [95% CI, 72.8%-73.3%] of patients) and more likely to have seen a cardiologist (40.0% [95% CI, 39.6%-40.4%] of patients vs 26.4% [95% CI, 26.2%-26.6%] of patients).Conclusions and relevanceIn this large cohort of US patients with diabetes and ASCVD, fewer than 1 in 20 patients were prescribed all 3 evidence-based therapies, defined as a high-intensity statin, either an ACEI or ARB, and either an SGLT2I and/or a GLP-1RA. These findings suggest that multifaceted interventions are needed to overcome barriers to the implementation of evidence-based therapies and facilitate their optimal use.

Project description:Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (?9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (?7 to <9 h).Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

Dataset Information

A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes.

Publications

A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets