Integrating Genomic Risk Assessment for Chronic Disease Management in a Diverse Population

整合基因组风险评估以进行不同人群的慢性病管理

• 批准号: 10207721
• 负责人: JAMES J CIMINO
• 金额: $ 163.32万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10207721
• 关键词: Accounting; Adherence; Adopted; Adult; African; African American; Alabama; American; Asians; Blood Glucose; Body mass index; Cause of Death; Cessation of life; Cholesterol; Chronic Disease; Clinic Visits; Clinical; Clinical Data; Clinical Trials; Communication; Complex; Consent; Data; Development; Diabetes Mellitus; Disease; Disease Management; Education; Educational Materials; Ensure; Environment; European; Evaluation; Family; Family history of; Genes; Genetic; Genomics; Genotype; Health; Health Care Costs; Heart Diseases; Hispanics; Individual; Informatics; Life Style; Link; Malignant Neoplasms; Medical; Methodology; Methods; Minority; Modification; Morbidity - disease rate; Outcome; Participant; Patients; Phenotype; Population; Population Heterogeneity; Practice Guidelines; Prevalence; Public Health; Publications; Race; Recommendation; Recording of previous events; Reporting; Research; Research Design; Risk; Risk Assessment; Risk Estimate; Risk Management; Risk Reduction; Sample Size; Sampling; Specific qualifier value; Trust; Underrepresented Minority; United States; biobank; clinical care; clinical decision support; cohort; digital; disability; disorder control; disorder risk; ethical legal social implication; experience; gene interaction; genetic architecture; genome wide association study; genomic signature; health disparity; health record; high risk; implementation outcomes; improved outcome; indexing; medically underserved; medically underserved population; mortality; phenotypic data; phenotyping algorithm; polygenic risk score; prevent; prospective; racial minority; recruit; statistics; tool; underserved community; uptake; visit adherence

Abstract In the United States, 60% of adults have a chronic disease and 40% have two or more. Collectively these diseases are the leading causes of death and disability accounting for >90% of our nation’s $3.3 trillion annual health care costs. Genome-wide association studies (GWAS) have identified genetic underpiinings of disease and enabled the development of polygenic risk scores (PRS) that may help to predict the occurrence and progression of common dieases. Working with the eMERGE team, we will select the fifteen diseases of public health impact. For these diseases, we will finalize the PRS to be adopted including adaptations (if any) for minority race groups, the genotyping array, the family history (FHx) tool and key clinical variables to be used in calculating genomic risk estimates (GRE). We will identify GRE thresholds at which genomic risk assessment (GRA) with risk reduction recommendations (RRR) in concordance with practice guidelines. To strengthen the evaluation of race-specific PRS, we bring an additional cohort of 30,0000 AAs. We will conduct a pilot ethical legal social implications study, to explore patient perspectives on use of FHx and PRS for estimating disease risk among Alabama Genomic Health Initiative (a state wide cohort) participants. The results will inform the development of consent, educational materials and a communication strategy to enhance recruitment and retention of eMERGE participants. We will prospectively recruit 2,500 patients with >75% patients from medically underserved communities, incorporate PRS, FHX and clinical data to compute GRE for the selected fifteen diseases for all patients. For high-risk patients, where GRE exceeds pre-specified thresholds (n~ 5000 of the 20,000 recruited across the network), deploy clinical decision support (CDS) and present the GRA and RRR. We expect ≥50% uptake of RRRs. We will assess whether the uptake of GRA-RRR improve outcomes. We will assess three outcomes: uptake of GRA-RRR (implementation outcome), adherence to clinic visits (engagement outcome), and surrogates of disease / control (clinical outcome; e.g. blood sugar, cholesterol). Although research has identified genomic signatures of common diseases, genomic risk assessments to identify, and if appropriate, pre-treat at-risk patients have not been implemented in clinical care. This is the vital first step to leverage the power of genomics to prevent disease. We bring our expertise and experience to collaborate with the eMERGE investigative team to take this vital first step.

抽象的 在美国，60% 的成年人患有慢性疾病，40% 的成年人患有两种或两种以上。统称为这些 疾病是导致死亡和残疾的主要原因，占我国 3.3 万亿美元财富的 90% 以上 每年的医疗保健费用。 全基因组关联研究（GWAS）已经确定了疾病的遗传基础，并使得 多基因风险评分（PRS）的发展可能有助于预测疾病的发生和进展 常见疾病。 我们将与 eMERGE 团队合作，选择十五种影响公共卫生的疾病。对于这些疾病， 我们将最终确定要采用的 PRS，包括针对少数族裔群体的调整（如果有）、基因分型 数组、家族史 (FHx) 工具和用于计算基因组风险估计的关键临床变量 （GRE）。我们将确定 GRE 阈值，在该阈值下进行基因组风险评估 (GRA) 和风险降低 符合实践指南的建议（RRR）。加强种族专项评估 PRS，我们带来了额外的 30,0000 个 AA 队列。 我们将进行一项试点道德法律社会影响研究，以探讨患者对使用 FHx 和 用于估计阿拉巴马州基因组健康计划（全州范围的队列）参与者疾病风险的 PRS。 结果将为同意书、教育材料和沟通策略的制定提供信息 加强 eMERGE 参与者的招募和保留。 我们将前瞻性地招募 2,500 名患者，其中 >75% 的患者来自医疗服务不足的社区， 结合 PRS、FHX 和临床数据来计算所有患者选定的 15 种疾病的 GRE。为了 高危患者，其中 GRE 超过预先指定的阈值（在全国范围内招募的 20,000 名患者中，有 5000 名患者 网络），部署临床决策支持（CDS）并呈现 GRA 和 RRR。我们预计 ≥50% 的采用率 存款准备金率。 我们将评估采用 GRA-RRR 是否可以改善结果。我们将评估三个结果： GRA-RRR（实施结果）、坚持就诊（参与结果）以及替代结果 疾病/控制（临床结果；例如血糖、胆固醇）。 尽管研究已经确定了常见疾病的基因组特征，但基因组风险评估 识别并在适当情况下对临床护理中尚未实施的高危患者进行预治疗。这是至关重要的 利用基因组学的力量预防疾病的第一步。我们将我们的专业知识和经验带到 与 eMERGE 调查团队合作，迈出至关重要的第一步。