Diabetic Complications and Genetic Variants in the Million Veterans Program

百万退伍军人计划中的糖尿病并发症和遗传变异

• 批准号: 10439613
• 负责人: LAWRENCE S PHILLIPS
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10439613
• 关键词: Adult; African; Age; Albuminuria; Alleles; Atherosclerosis; Blood Pressure; Body mass index; Cardiovascular system; Clinical; Complications of Diabetes Mellitus; Custom; Data; Databases; Development; Diabetes Mellitus; Electronic Health Record; Emergency department visit; End stage renal failure; Ethnic Origin; European; Eye; Frequencies; Gene Frequency; Genes; Genetic; Genetic Databases; Genotype; Glaucoma; Glucose; Glycosylated hemoglobin A; Health; Healthcare; Heart failure; Hospitalization; Hypoglycemia; Infrastructure; Insulin-Dependent Diabetes Mellitus; Kidney; Link; Lipids; Logistic Regressions; Measurement; Measures; Medicare; Metabolic; Methods; Minor; Modeling; Non-Insulin-Dependent Diabetes Mellitus; Organ; Outcome; Outcome Assessment; Outpatients; Participant; Pharmaceutical Preparations; Pharmacology; Phenotype; Population; Positioning Attribute; Prevalence; Race; Recording of previous events; Records; Research Personnel; Resources; Retinal Diseases; Risk; Risk Factors; Role; Source; Validation; Variant; Veterans; Visit; biobank; cost; demographics; design; diabetic; ethnic minority population; genetic risk factor; genetic variant; genome wide association study; genome-wide; genome-wide analysis; improved; insertion/deletion mutation; multi-ethnic; personalized care; predictive modeling; programs; racial and ethnic; rare variant; time use; trait; virtual

We propose to undertake analyses within the Million Veterans Program (MVP) database to Assess Associations between Diabetic Complications and Genetic Variants. Aim 1 involves Database Development that will create a virtual baseline examination linking MVP data to VAMC outpatient visits, and, when appropriate, VAMC hospitalizations, using the electronic health record. We will conduct cutting edge Genome Wide Association Studies (GWAS) of common (CVAS) and rare (RVAS) variants. The outcomes investigated are diabetic eye, kidney, and cardiovascular complications, and hypoglycemia. Aim 2 is Diabetes Complications Analyses concerning outcome risks using time-integrated longitudinal measures of risk factors (RFs) to include both genetic variants and traditional RFs considering both single and multiple assessments of outcomes with cross-sectional and period prevalence estimates. We will analyze organ-specific and metabolic complications according to type 1 and type 2 diabetes status using EHR data in VA records. Specific outcomes investigated: Ocular (retinal disease, glaucoma), Renal (micro- and macro-albuminuria, and decreased eGFR [CKD stages and ESRD), Cardiovascular (cardiac failure), and Hypoglycemia (emergency department visits and hospitalizations, adjusted for HbA1c and glucose levels, and use of glycemic medications [from the EHR]). Aim 3 will develop Diabetic Complications Risk Scores. Both traditional RF and separate genetic prediction models will be compared using logistic regression for each outcome. Models will evaluate the role of RFs and pharmacologic therapy for abnormal blood pressure, lipids, and glucose. We will use an outcome-specific genetic score as a potential reclassification variable.

我们建议在百万退伍军人计划 (MVP) 内进行分析 评估糖尿病并发症与遗传之间关联的数据库 变体。目标 1 涉及数据库开发，创建虚拟基线 检查将 MVP 数据与 VAMC 门诊就诊联系起来，并在适当时将 VAMC 住院治疗，使用电子健康记录。我们将进行最前沿的 常见 (CVAS) 和罕见 (RVAS) 的全基因组关联研究 (GWAS) 变种。研究的结果是糖尿病眼、肾和心血管 并发症和低血糖。目标 2 是糖尿病并发症分析 使用风险因素的时间积分纵向测量来考虑结果风险 （RF）包括遗传变异和传统 RF，考虑到单一和 对横截面和时期患病率的结果进行多重评估 估计。我们将根据类型分析器官特异性和代谢并发症 使用 VA 记录中的 EHR 数据了解 1 型和 2 型糖尿病状态。具体成果 研究：眼科（视网膜疾病、青光眼）、肾科（微量和大量白蛋白尿、 eGFR 降低（CKD 分期和 ESRD）、心血管（心力衰竭）和 低血糖（急诊科就诊和住院治疗，根据 HbA1c 进行调整 和血糖水平，以及降血糖药物的使用[来自 EHR]）。目标3将 制定糖尿病并发症风险评分。传统射频和独立射频 将使用逻辑回归对每个结果进行比较遗传预测模型。 模型将评估射频和药物治疗对异常血液的作用 压力、血脂和葡萄糖。我们将使用特定结果的遗传评分作为 潜在的重分类变量。