Integrating lifecourse approaches, biologic and digital phenotypes in support of heart and lung disease epidemiologic research

整合生命历程方法、生物学和数字表型以支持心肺疾病流行病学研究

• 批准号: 10764391
• 负责人: Jorge Eduardo Chavarro
• 金额: $ 13.1万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-08 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10764391
• 关键词: Address; Adult Children; Affect; African American population; Age; Air Pollution; Anthropometry; Area; Asthma; Behavioral; Big Data; Biological; Biological Markers; Biological Specimen Banks; Blood Pressure; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Cellular Phone; Cessation of life; Characteristics; Child; Chronic Obstructive Pulmonary Disease; Clinical; Collection; Communities; Coronary heart disease; DNA; Data; Data Collection; Databases; Diet; Dimensions; Disease; Dyslipidemias; Educational Materials; Electronic cigarette; Environmental Exposure; Epidemiology; Erythrocytes; Etiology; Event; Exposure to; Food; Food Access; Future; Generations; Genes; Geographic Distribution; Geographic Information Systems; Geography; Gestational Diabetes; Goals; Green space; Health; Health Care Costs; Heart Diseases; Hispanic Americans; Hypertension; Individual; Infrastructure; Infrastructure Activities; Life; Life Cycle Stages; Link; Lung diseases; Maintenance; Marijuana; Measurement; Measures; Medical History; Medical Records; Minority; Morbidity - disease rate; Mothers; Nurses' Health Study; Obesity; Obstructive Lung Diseases; Online Systems; Participant; Periodicals; Persons; Phenotype; Physical activity; Plasma; Pregnancy; Pregnancy Complications; Premature Birth; Process; Protocols documentation; Questionnaires; RNA; Recording of previous events; Recreation; Reporting; Research; Research Support; Resolution; Resources; Risk; Risk Factors; Rural Population; Sleep; Socioeconomic Status; Specimen; Stroke; Technology; Temperature; Total Lung Capacity; Translational Research; United States; Update; Urine; Visualization software; Woman; Women' s Health; analytical tool; attributable mortality; biobank; built environment; cardiorespiratory fitness; cardiovascular health; cardiovascular risk factor; cohort; data infrastructure; data repository; data resource; data sharing; digital; disability; disorder risk; epidemiology study; ethnic minority; excessive weight gain; follow-up; frontier; innovation; interest; intergenerational; lifestyle factors; lung health; men; mobile computing; mortality; novel; offspring; pregnancy disorder; racial minority; reproductive; spatiotemporal; stool sample

PROJECT SUMMARY Increasing evidence suggests that early life and reproductive events, including specific pregnancy complications, predict future health risks including cardiovascular (CVD) risk factors (e.g., dyslipidemia, hypertension, obesity), clinical CVD events, and obstructive lung disease. Similarly, increasing evidence suggests that exposures during pregnancy may affect offspring’s cardiovascular and lung health throughout life. In this application, we propose to strengthen the infrastructure necessary to collect data on traditional and emerging risk factors for heart and lung diseases and to document the occurrence of these conditions within three related cohorts: the Nurses’ Health Study II (NHS-II), the Nurses’ Health Study 3 (NHS3), and the Growing Up Today Study (GUTS). These cohorts collectively follow 188,698 individuals including more than 14,000 minority participants with large numbers of African Americans and Hispanic Americans. The cohorts also follow more than 65,000 mother-adult offspring pairs, over 13,000 grandmother-mother-adult child triads and over 16,000 sib-groups; resources that facilitate research aimed at identifying inter-generational risk factors for CVD and obstructive lung diseases. Women in the two younger cohorts (NHS3 and GUTS) are in the middle of the reproductive years, resulting in the accrual of approximately 1,000 new pregnancies per year. Furthermore, study participants are broadly distributed across the United States, giving us the ability to address questions regarding rural populations including areas considered to be Frontier. The proposed infrastructure activities in these three related cohorts will ultimately support research aimed at identifying intergenerational and early life risk factors for CVD (CHD, stroke) and obstructive lung disease (COPD and asthma), as well as of relevant biologic intermediate endpoints, from genes to geography. We will focus our efforts in four areas: 1) the maximization of existing resources – including updating and maintenance of food composition databases and geographically-linked exposure data based on geographical information systems (GIS), 2) the collection of biological specimens tied to an in-person collection of blood pressure and anthropometric data, 3) the expansion of web-based mobile technology and “Big Data” capabilities for the cohorts, and 4) strengthening our capability for data sharing. The ability to combine biomarker data, state-of- the-art mobile high-resolution measures, and traditional epidemiologic risk factor data, collected across generations and throughout the life-course in three related cohorts will enable us and others to conduct powerful etiologic and translational research. Our goal is to maintain the quality of follow-up and associated data, as well as to broaden the technologies that would provide innovative dimensions to the cohort for novel scientific discovery.

项目摘要 越来越多的证据表明，早期生活和生殖事件，包括特定的怀孕 并发症，预测未来的健康风险，包括心血管（CVD）风险因素（例如血脂异常， 高血压，肥胖症），临床CVD事件和阻塞性肺部疾病。同样，越来越多的证据 表明怀孕期间的暴露可能会影响后代的心血管和肺部健康 生活。在此应用程序中，我们建议加强收集传统数据数据所需的基础设施 出现心脏和肺部疾病的新兴危险因素，并记录这些疾病的发生 三个相关队列：护士健康研究II（NHS-II），护士健康研究3（NHS3）和 在今天长大的研究（胆量）。这些队列集体遵循188,698个人，包括 有14,000名少数非洲裔美国人和西班牙裔美国人的少数民族参与者。同伙 还要跟随超过65,000个母子后代对，超过13,000个祖母母亲三合会 以及超过16,000个同胞组；促进旨在确定代际风险的研究的资源 CVD和阻塞性肺部疾病的因素。两个年轻队列（NHS3和胆量）的女性在 生殖年的中间，每年大约有1,000个新怀孕的准确性。 此外，研究参与者大致分布在美国，使我们能够 解决有关民众的问题，包括被认为是前沿的地区。提议 这三个相关队列中的基础设施活动最终将支持旨在识别的研究 CVD（CHD，中风）和阻塞性肺疾病（COPD和COPD和 从基因到地理，哮喘）以及相关的生物中间终点。我们将集中精力 在四个领域的努力：1）现有资源的最大化 - 包括更新和维护食物 基于地理信息系统的组成数据库和与地理联系的暴露数据 （GIS），2）与血压的亲自收集相关的生物标本的收集 人体测量数据，3）基于Web的移动技术和“大数据”功能的扩展 队列和4）增强我们的数据共享能力。结合生物标志物数据的能力，最新 收集的 几代人以及整个生命过程中的三个相关队列将使我们和其他人能够进行 强大的病因和翻译研究。我们的目标是保持随访的质量和关联 数据，以及扩大将为新颖的队列提供创新维度的技术 科学发现。