Leveraging genomic data to dissect the association of internalizing disorders with the risk, onset, and vulnerability of COVID-19

利用基因组数据剖析内化障碍与 COVID-19 风险、发病和脆弱性的关联

• 批准号: 10612299
• 负责人: RENATO POLIMANTI
• 金额: $ 369.47万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612299
• 关键词: 2019-nCoV; Address; Affect; Anxiety; Biological; Biological Process; Biology; Blood; Blood specimen; Boredom; COVID-19; COVID-19 impact; COVID-19 morbidity; COVID-19 pandemic; COVID-19 risk; COVID-19 severity; COVID-19 susceptibility; Cessation of life; Complex; Critical Illness; Data; Data Set; Disease; Economics; Epidemiology; Epigenetic Process; Etiology; Face; Family member; Fright; Genetic; Genetic Research; Genomics; Health; Health Professional; Herd Immunity; Hospitalization; Human; Immune system; Immunization Programs; Individual; Infection; Infectious Agent; Investigation; Life; Link; Major Depressive Disorder; Maps; Medical; Mental Depression; Mental Health; Mental disorders; Molecular; Molecular Target; Outcome; Participant; Pathway interactions; Post-Traumatic Stress Disorders; Process; Proteomics; Psychological Stress; Recording of previous events; Recovery; Reporting; Research; Research Personnel; Risk; SARS-CoV-2 infection; Social isolation; Societies; Socioeconomic Status; Source; Symptoms; Testing; Time; Tissues; Trauma; Uncertainty; Underrepresented Minority; Vaccines; Veterans; base; biobank; body system; cell type; cohort; comorbidity; contagion; disorder risk; epigenome; epigenomics; experience; genetic information; genome wide association study; genome-wide; genome-wide analysis; genomic data; health disparity; high risk; improved; infection risk; loved ones; mortality; multiple omics; pandemic disease; phenome; physical conditioning; pleiotropism; programs; psychiatric comorbidity; public health relevance; recruit; respiratory; severe COVID-19; social; therapy design; tool; trait; transcriptome; transcriptomics

Abstract. Although our understanding of the COVID-19 and its infectious agent, SARS-Cov-2, is greatly improved and effective vaccines have been developed, there are many uncertainties regarding how and when the pandemic is going to end. Additionally, there are many consequences due to the pervasive impact of COVID-19 on individuals and societies that we will continue to face in the post-pandemic world. An aspect that is strongly contributing to the ongoing crisis is the systematic lack of reliable information to guide healthcare professionals and policymakers. To apply a network approach to COVID-19 research, we should prioritize the “hubs” connecting the different domains of COVID-19 consequences. Mental health is surely one of the health domains that are being more strongly affected by COVID-19 outcomes. Isolation, psychological stress, and “free-time” boredom induced by COVID-19 restrictions have been consistently associated with increased internalizing symptoms, including anxiety and depression. Additionally, traumatic experiences related to COVID-19 (e.g., severe symptoms, hospitalization, and death of a loved one) have been also linked to posttraumatic stress disorder. In a vicious circle, internalizing disorders have been associated with an increased risk of SARS-Cov-2 infection and COVID-19 severe symptoms, hospitalization, and mortality. For instance, SARS-Cov-2 infection and COVID-19 severity can be due to the effect of a weakened immune system associated with internalizing disorders. In recent years, genetic research has demonstrated to be an invaluable tool to dissect the underlying dynamics related to internalizing disorders and traits. Indeed, genetic information can be used as an anchor for causal inference to test the relationships linking human traits and diseases and to investigate the effect of genomic regulatory mechanisms on disease risk. Based on our expertise and the supporting findings generated by our studies, we propose a multivariate investigation to identify the latent factors linking the internalizing spectrum (anxiety, major depressive disorder, and posttraumatic stress disorder) and COVID-19 outcomes (infection, hospitalization, and critical illness). Then, we will investigate the regulatory mechanisms of these latent factors across multiple omics domains, tissues, and cell types. In parallel, we will also test the interaction of the internalizing spectrum with blood-based transcriptomic and epigenomic changes associated with COVID-19 morbidity and psychological stress. Our findings will provide a multi-dimensional perspective on the processes underlying the associations between COVID-19 outcomes and internalizing disorders.

摘要。尽管我们对COVID-19及其感染剂SARS-COV-2的理解， 已经大大改善并且已经开发出有效的疫苗，有许多不确定性 关于大流行即将结束的方式和何时结束。此外，还有很多 由于共同-19对我们的个人和社会的普遍影响，我们的后果 大流行世界将继续面对。一个强烈贡献的方面 正在进行的危机是系统性缺乏可靠的信息来指导医疗保健专业人员 和决策者。为了将网络方法应用于Covid-19研究，我们应该优先考虑 连接COVID-19后果的不同领域的“集线器”。心理健康肯定是 受到19号结果的影响更大的健康领域之一。 隔离，心理压力和由COVID-19限制引起的“闲暇”无聊 一贯与增加内在症状的增加有关，包括动画和 沮丧。此外，与19009相关的创伤经历（例如，严重症状， 住院和亲人的死亡）也与创伤后压力有关 紊乱。在一个美妙的圈子中，内部化疾病与风险增加有关 SARS-COV-2感染和COVID-19的严重症状，住院和死亡率。为了 实例，SARS-COV-2感染和COVID-19的严重程度可能是由于弱化的影响 与内部化疾病相关的免疫系统。近年来，遗传研究已有 被证明是剖析与内部化有关的基本动力学的宝贵工具 疾病和特征。实际上，遗传信息可以用作因果推断的锚点 测试联系人类特征和疾病的关系，并研究 疾病风险的基因组调节机制。根据我们的专业知识和支持 我们的研究产生的发现，我们提出了一项多元投资，以识别潜在的 连接内在频谱（焦虑，重度抑郁症和创伤后的因素） 应激障碍）和共同的-19结局（感染，住院和危重疾病）。然后， 我们将研究多个OMIC的这些潜在因素的调节机制 域，组织和细胞类型。同时，我们还将测试内部化的相互作用 与COVID-19的血液基于血液的转录组和表观基因组变化的频谱 发病率和心理压力。我们的发现将提供多维的观点 COVID-19结果与内部化之间关联的过程 疾病。