Information Fusion of Cognition, and Brain MRI on Cardio-Metabolic Risk Factors in the Middle-Aged: the CARDIA Study

认知信息融合和脑 MRI 对中年人心脏代谢危险因素的影响：CARDIA 研究

• 批准号: 2366862
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2366862
• 关键词: Information; Fusion; Cognition; Brain; MRI

Background: There is a lack of evidence of the role of cardio-metabolic risk factors in brain health from large cohort studies which are comprised of metabolites; specifically, from a life-course perspective with increasing CVD risk profiles. Aim: The primary aim of this study is to investigate associations between cardio-metabolic risk factors and cognition with brain MRI characteristics in the Coronary Artery Risk Development in Young Adults (CARDIA) Study at Year 30, and to investigate if the urinary metabolites are mediators of the associations. Significant epidemiological exposures and targeted urinary metabolites will be examined, and the information will be used to develop a risk assessment tool for brain health (i.e., cognition).Design and population: This present study focuses on the CARDIA Study sub-cohort of the 606 participants in middle-aged (aged 48-60 years who completed cognitive tests) at Year 30, 2015-16. The high-resolution nuclear magnetic resonance (NMR) spectroscopy and the liquid-chromatography mass spectrometry (LC-MS) data for the 606 participants and the brain MRI data for the 280 participant are available. Methods: Bayesian models and advanced network classification models will be employed to investigate metabolic phenotypes and other exposures. Different types of significant cardio-metabolic risk factors, other clinical, socio-demographic, lifestyle exposures and metabolite markers on cognition and brain MRI measures will be integrated (i.e., fusion) to provide a cardio-metabolic risk-specific integrated map of brain health. The longitudinal associations will be examined to explore the possibility of developing a novel, comprehensive risk assessment tool of brain health.Discussion: This study will employ a novel biostatistical approach of a fusion analytic method for the different types or levels of data on the large-scale epidemiological study. The approach may be able to recognise complex multivariate epidemiologic, pathologic and phenotypic relationships across the disease networks that are yet unidentified.

背景资料：从由代谢物组成的大型队列研究中缺乏心脏代谢风险因素在大脑健康中作用的证据;特别是从生命过程的角度来看，CVD风险状况不断增加。目的：本研究的主要目的是调查年轻人冠状动脉风险发展（CARDIA）研究中30岁时心脏代谢危险因素和认知与脑MRI特征之间的相关性，并调查尿代谢产物是否是相关性的介导剂。将对重要的流行病学暴露和目标尿代谢物进行检查，并将使用这些信息开发脑健康风险评估工具（即，设计和人群：本研究集中于2015-16年30岁的606名中年参与者（年龄48-60岁，完成认知测试）的CARDIA研究子队列。606名参与者的高分辨率核磁共振（NMR）光谱和液相色谱质谱（LC-MS）数据以及280名参与者的大脑MRI数据可用。方法：贝叶斯模型和先进的网络分类模型将被用来调查代谢表型和其他暴露。将整合不同类型的显著心脏代谢风险因素、其他临床、社会人口统计学、生活方式暴露以及认知和脑MRI测量的代谢物标志物（即，融合），以提供大脑健康的心脏代谢风险特异性综合图。纵向协会将被检查，以探索开发一种新的，全面的风险评估工具的脑health.Discussion的可能性：本研究将采用一种新的生物统计方法的融合分析方法的不同类型或水平的数据的大规模流行病学研究。该方法可能能够识别复杂的多变量流行病学，病理学和表型之间的关系，疾病网络尚未确定。