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，有60％的成年人患有慢性疾病，40％的成年人患有两种或更多。集体这些 疾病是死亡和残疾的主要原因，占我们国家3.3万亿美元的90％ 年度医疗保健费用。 全基因组关联研究（GWAS）已经确定了疾病的遗传基础，并使得能够 多基因风险评分（PR）的发展可能有助于预测 常见的第三次。 与Emerge团队合作，我们将选择15种公共卫生影响的疾病。对于这些疾病， 我们将最终确定将要采用的PR，包括适应（如果有的话）少数族裔群体，即基因分型 阵列，家族史（FHX）工具和关键临床变量用于计算基因组风险估计 （GRE）。我们将确定基因组风险评估（GRA）并降低风险的GRE阈值 建议（RRR）与实践指南一致。加强对种族特定的评估 PRS，我们带来了30,0000 AA的额外队列。 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FHX和使用的看法 估计阿拉巴马州基因组健康倡议（一项范围广泛的人群）参与者中疾病风险的PR。 结果将为同意的发展，教育材料和沟通策略提供信息 增强出现参与者的招聘和保留。 我们将前瞻性地招募2500名来自医疗不足社区的患者> 75％的患者， 将PRS，FHX和临床数据纳入所有患者的GRE，以计算GRE。为了 高风险患者，GRE超过预先指定的阈值（在整个20,000名中招募的20,000个n〜5000 网络），部署临床决策支持（CD）并介绍GRA和RRR。我们预计吸收≥50％ RRR。 我们将评估GRA-RRR的摄取是否改善结果。我们将评估三个结果：吸收 GRA-RRR（实施结果），遵守诊所就诊（参与结果）和代理 疾病 /对照（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 尚未在临床护理中确定并在适当的情况下进行治疗的处于危险患者。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给 与出现的调查团队合作，迈出了这一至关重要的第一步。