Risk Factors for Ischemic Stroke in Women

摘要 中风是美国女性死亡的第三大原因，也是导致残疾的主要原因。新 蛋白质组学技术测量了蛋白质的广泛分布，提供了蛋白质的全面图像。 功能协调发展的由于蛋白质执行大多数生物学功能，因此它们可以用作生物标志物或药物 治疗目标尽管蛋白质组学和心血管疾病的结果很有希望，但只有一个 已经进行了缺血性中风的小规模前瞻性蛋白质组学研究。 这项研究的首要目标是发现新的蛋白质组范围和多组学关联， 缺血性中风在此R 01成功的既定记录基础上，我们将测量3072 护士健康研究（NHS; 460例缺血性中风/ 460例对照）中的蛋白质（Olink平台）和维生素 D Omega 3 TriAL（VITAL; 300例缺血性卒中/ 300例对照），以及利用单独测量的数据 来自妇女健康倡议（WHI; 214例缺血性卒中），心脏病研究后代队列 （FHSOC; 103例缺血性卒中）和UK生物样本库（UKB;约450例缺血性卒中）。在目标1中，我们将测试 在使用来自NHS、VITAL、WHI、 FHSOC和UKB。缺血性卒中亚型，以及性别和种族的相互作用将被测试。在目标2中，我们将 在NHS和VITAL中进行稳健的全蛋白质组发现，并验证Meta- WHI、FHSOC和UKB的分析。将使用以下方法评价经验证的蛋白质的因果关系 孟德尔随机化（MR）分析。利用来自UKB（53，000）的蛋白质组学和遗传数据，我们将 为验证的蛋白质生成蛋白质多基因等位基因风险评分，并测试这些蛋白质多基因风险 MEGASTROKE和SiGN的缺血性卒中评分。缺血性卒中亚型，以及性别和 种族将被探索。在目标3中，我们将利用代谢组学特征的先前测量， NHS、VITAL和WHI中的生物标志物和风险因素数据，使用新的综合方法，包括相似性 网络融合，以联合收割机结合蛋白质组学和代谢组学数据、生物标志物和风险因素数据， 缺血性卒中和卒中亚型。将在NHS、VITAL和WHI中比较结果。 该研究利用来自五个队列的Olink蛋白质组学数据来识别蛋白质和多组蛋白质。 与中风发病率相关的特征，可用于改善中风预测和预防 战略和确定预防中风的新药靶点。

ABSTRACT Stroke is the third leading cause of death in women and the leading cause of disability in the US. New proteomic techniques measure a wide profile of proteins, providing a comprehensive picture of protein functions. Since proteins perform most biological functions, they may be leveraged as biomarkers or drug therapy targets. Although results for proteomics and cardiovascular disease have been promising, only one small prospective proteomics study of ischemic stroke has been conducted. The over-arching goal of this study is to discover novel proteome-wide and multi-omic associations for incident ischemic stroke. Building on an established record of success in this R01, we will measure 3072 proteins (Olink platform) in the Nurses’ Health Studies (NHS; 460 ischemic strokes/ 460 controls) and VITamin D Omega3 TriAL (VITAL; 300 ischemic strokes/ 300 controls), as well as leverage separately measured data from the Women’s Health Initiative (WHI; 214 ischemic strokes), Framingham Heart Study Offspring Cohort (FHSOC; 103 ischemic strokes), and UK Biobank (UKB; ~450 ischemic strokes). In Aim 1, we will test candidate protein hypotheses in 1334 strokes in meta-analyses using Olink data from the NHS, VITAL, WHI, FHSOC and UKB. Ischemic stroke subtypes, and interactions by sex and race will be tested. In Aim 2, we will perform robust, proteome-wide discovery in NHS and VITAL with validation of significant proteins in meta- analyses of WHI, FHSOC, and UKB. Validated proteins will be evaluated for causal associations using mendelian randomization (MR) analyses. Using proteomic and genetic data from UKB (53,000), we will generate protein polygenic allele risk scores for the validated proteins and test these protein polygenetic risk scores for ischemic stroke in MEGASTROKE and SiGN. Ischemic stroke subtypes, and interactions by sex and race will be explored. In Aim 3, we will leverage prior measures of metabolomic profiles and extensive biomarker and risk factor data in NHS, VITAL and WHI, using novel integrative approaches, including similarity network fusion, to combine proteomic and metabolomic data, biomarker and risk factor data, in associations for ischemic stroke and stroke subtypes. Findings will be compared in NHS, VITAL and WHI. The proposed study leverages Olink proteomic data from five cohorts to identify proteins and multi-omic signatures integral to the incidence of stroke, which can be used to improve stroke prediction and prevention strategies and identify new drug targets for stroke prevention.