Trans-omics integration of multi-omics studies for male osteoporosis

项目总结 新冠肺炎是一场全球性的流行病，引发了医疗和社会经济危机。有很大的变种 个人对SARS-CoV-2感染反应的症状/结果。一个关键问题是：什么是外在的 (aging/environmental/medical/medication/lifestyle/diet/metagenomic)和内在(例如，基因组/转录本- 组学/代谢学)因素在新冠肺炎易感性、严重性和预后中的个体差异？ 我们建议在这里适时解决上述问题。我们将利用现有的1055人的独特队列 高加索人和非裔美国人招募/表型/概况与尖端的多重组学技术在 我们正在进行的U19母项目(U19AG055373)和更大的LOS的大新奥尔良(GNO)区域 (路易斯安那州骨质疏松症研究)队列包括16,400名受试者(所有种族，性别，年龄17-97岁)。 GNO是美国新冠肺炎受灾最严重的地区之一。我们处于独特的地位，可以实现以下目标： 科目招募和数据收集：我们将从U19和LOS队列中招募400名科目，包括 新冠肺炎和匹配的对照组，都具有确认的感染状态，并从他们那里获得所需的生物检疫试剂。 我们还将通过以下途径招募和收集600名新冠肺炎患者的表型信息和生物标本 Ochsner Health System是路易斯安那州最大的医疗保健系统。对于U19和LOS队列，我们将处于 独一无二的地位，可以利用他们现有的感染前(基线)多组学资料。对于所有被招募的 COVID19受试者，我们将评估他们感染后的多组学特征，以追求以下几点： 目的1：确定人类宿主和肠道微生物组中潜在的基因/细菌物种/分子途径 通过对新冠肺炎感染者的比较多组学分析，影响COVID19易感性的因素 感染前多组学数据的受试者及其匹配的对照组。 目标2：通过以下方式确定与疾病严重程度相关的衰老/环境/遗传/分子因素 比较个人情况(年龄、性别、种族、饮食、医疗、药物、生活方式等)和感染后 具有不同疾病严重程度/结果的1,000例柯萨奇病毒感染者的多重组学特征。 目标3：通过比较感染前(基线)，确定影响疾病严重程度的潜在原因分子因素 COVID19感染者的多重组学图谱及其变化(感染后与感染前) 疾病严重程度/结局各不相同的受试者。 目标4：对药物再利用进行生物信息学分析，以确定有效的现有药物 治疗新冠肺炎，基于从多组学数据中获得的在人体内的分子机制。 这项研究将获得关于COVID个体差异背后的基本机制的重要信息。 19敏感性/严重性/结果，并为个性化医疗铺平道路(特别是针对各种 年龄组/医疗条件)使用现有药物作为紧急应对措施。获得的数据/样本/队列将 这对于在未来的后续研究中研究新冠肺炎对健康，特别是老龄化的长期影响具有不可估量的价值。

PROJECT SUMMARY COVID-19 is a global pandemic, causing a medical and social-economic crisis. There are large variations of symptoms/outcomes in individual responses to SARS-CoV-2 infection. A key question is: what extrinsic (aging/environmental/medical/medication/lifestyle/diet/metagenomic) and intrinsic (e.g., genomic/transcript- omic/metabolomic) factors underlie individual variation in COVID-19 susceptibility, severity and outcomes? We propose to timely address the above question here. We will leverage on an existing unique cohort of 1,055 Caucasian and African American recruited/phenotyped/profiled with cutting-edge multi-omics technologies in the Greater New Orleans (GNO) area for our ongoing U19 parent project (U19AG055373) and the larger LOS (Louisiana Osteoporosis Study) cohort with >16,400 subjects (all ethnicities, both sexes, aged 17-97 years old). GNO is one of the hardest hit areas in US by COVID-19. We are in a unique position to fulfill the following: Subject Recruitment and Data Collection: From the U19 and LOS cohorts, we will recruit >400 subjects with COVID-19 and matched controls, all with confirmed infection status, and obtain the needed biospecimens from them. We will also recruit and collect phenotypic information and biospecimens from 600 COVID-19 patients through Ochsner Health System, Louisiana’s largest healthcare system. For the U19 and LOS cohorts, we will be in a unique position to leverage their existing pre-infection (baseline) multi-omics profiles. For all the recruited COVID19 subjects, we will assess their post-infection multi-omics profiles, to pursue the following: Aim 1: Identify potential genes/bacteria species/molecular pathways in human hosts and gut microbiome that influence susceptibility of COVID-19, by comparative multi-omics analyses of those COVID19 infected subjects with pre-infection multi-omics data and their matched controls. Aim 2: Identify aging/environmental/genetic/molecular factors associated with disease severity, by comparing individual conditions (aging, gender, ethnicity, diet, medical, medication, lifestyle, etc.) and post-infection multi-omics profiles among >1,000 COVID19 infected subjects with various disease severities/outcomes. Aim 3: Identify potential causal molecular factors for disease severity, by comparing the pre-infection (baseline) multi-omics profiles and changes in multi-omics profiles (post- vs. pre-infection) among the COVID19 infected subjects with various disease severities/outcomes. Aim 4: Perform bioinformatic analyses for drug repurposing to identify existing drugs that would effectively treat COVID-19, based on the molecular mechanisms gained in vivo in humans from the multi-omics data. This study will gain significant information on the fundamental mechanisms underlying individual variation in COVID- 19 susceptibility/severity/outcomes, and pave the way for personalized medicine (especially those targeting various age groups/medical conditions) using existing drugs as urgent responses. The data/samples/cohorts obtained will be invaluable for studying the long-term effects of COVID-19 on health, especially aging, in future follow-up studies.