Mental health and chronic disease: A psycheMERGE investigation into the shared biology underlying psychiatric disorders and their physical comorbidities

心理健康和慢性疾病：对精神疾病及其身体合并症的共同生物学基础的 psycheMERGE 调查

• 批准号: 9981494
• 负责人: Lea K Davis
• 金额: $ 80.46万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-20 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9981494
• 关键词: Academic Medical Centers; Address; Age; Area; Behavior; Biological Markers; Biology; Bipolar Disorder; Cardiovascular Diseases; Caring; Cessation of life; Chronic; Chronic Disease; Clinical; Clinical Research; Collaborations; Collection; Complex; Computerized Medical Record; DNA Repository; Data; Databases; Development; Diagnosis; Diagnostic; Disease; Disease Outcome; Electronic Health Record; Electronic Medical Records and Genomics Network; Epidemiology; Excess Mortality; Fibrinogen; Genes; Genetic; Genetic Research; Genetic Risk; Genomic medicine; Genomics; Health system; Healthcare; Healthcare Systems; Home environment; Individual; Infrastructure; Intentional injury; Investigation; Joints; Knowledge; Life; Life Expectancy; Light; Link; Major Depressive Disorder; Medical; Medical Genetics; Mental Depression; Mental Health; Mental disorders; Modeling; Morbidity - disease rate; National Human Genome Research Institute; Neurobiology; Non-Insulin-Dependent Diabetes Mellitus; Outcome; Pathway interactions; Pattern; Pharmaceutical Preparations; Phenotype; Population; Population Characteristics; Prognostic Marker; Psychiatric Diagnosis; Psychiatric therapeutic procedure; Public Health; Race; Research; Research Personnel; Resources; Rest; Risk; Risk Factors; Schizophrenia; Site; Smoking; Suicide; Symptoms; Testing; Weight; Weight Gain; base; biobank; biopsychosocial; burden of illness; cardiovascular disorder risk; clinical Diagnosis; clinical risk; comorbidity; deprivation; disability; disorder risk; epidemiology study; genetic risk factor; genome wide association study; genomic data; improved; indexing; modifiable risk; mortality; mortality risk; neuropsychiatric disorder; phenome; physical conditioning; pleiotropism; premature; prognostic; psychiatric genomics; psychosocial; severe mental illness; severe psychiatric disorder; sex; sudden cardiac death

Neuropsychiatric disorders are associated with significantly increased morbidity and mortality. Chronic complex diseases including cardiovascular disease (CVD) are the primary drivers of premature death among individuals with psychiatric disorders. While there is evidence that modifiable risk factors (i.e., smoking, weight, medication use, etc.) increase risk, they do not fully account for the excess morbidity and mortality in this population. The growing availability of large-scale biobanks linking electronic health records (EHRs) to biospecimens has created a powerful, but still relatively untapped, opportunity for psychiatric research aimed at addressing this excess morbidity and mortality. In 2007, the National Human Genome Research Institute (NHGRI) organized the Electronic Medical Records and Genomics (eMERGE) network which brought together investigators around the U.S. to facilitate EHR-based genomic research and the implementation of genomic medicine. We have created a new, large-scale collaborative consortium—PsycheMERGE—that leverages the resources and existing infrastructure of the eMERGE network, the Psychiatric Genomics Consortium (PGC), and local EHR and biobank resources. This application uses EHR and genomic data across multiple health care systems (Partners Health Care, Vanderbilt University Medical Center, and Geisinger Health Systems) that are collaborative partners in the PsycheMERGE network. Our preliminary data also demonstrates that polygenic risk for Major Depressive Disorder (MDD) is associated with important prognostic biomarkers of CVD widely available within the EHR. Building on this preliminary data, our first aim is to discover pleiotropic genes contributing to MDD risk, CVD risk, and known CVD biomarkers which we hypothesize will also point to important pathways involved in the biology of MDD. In aim 2 we employ a population epidemiological approach to investigate the moderating effects of biopsychosocial variables on the genetic and phenotypic risk factors linking MDD and CVD. Finally, in aim 3 we characterize the phenotypic and genomic relationships between each of three common severe mental illnesses, and the rest of the medical phenome including >500 clinical lab tests in over 300,000 individuals with data present in the EHR. There is an urgent public health need to improve care and treatment of psychiatric disorders and their comorbidities. The proposed research includes a comprehensive set of integrative analyses aimed at investigating the genetic, clinical, and psychosocial risk factors that contribute to the development of psychiatric disorders and their life-threatening comorbidities in the context of a national network of EHRs and associated biobanks. !

神经精神疾病与发病率和死亡率增加显着相关。 包括心血管疾病（CVD）在内的慢性复杂疾病是导致健康问题的主要原因 虽然有证据表明患有精神疾病的人过早死亡。 可改变的风险因素（即吸烟、体重、药物使用等）会增加风险，但它们不会增加风险 充分考虑到该人群的发病率和死亡率不断增加。 将电子健康记录 (EHR) 与生物样本连接起来的大型生物银行创建了 旨在解决精神病学研究问题的强大但相对尚未开发的机会 2007年，国家人类基因组研究所指出了这一过高的发病率和死亡率。 (NHGRI) 组织了电子病历和基因组学 (eMERGE) 网络 汇集了美国各地的研究人员，以促进基于电子病历的基因组研究和 我们创建了一个新的、大规模的合作。 联盟 - PsycheMERGE - 利用资源和现有基础设施 eMERGE 网络、精神病基因组学联盟 (PGC) 以及当地 EHR 和生物样本库 该应用程序使用跨多个医疗保健系统的 EHR 和基因组数据。 （合作伙伴医疗保健、范德比尔特大学医学中心和盖辛格卫生系统） 他们也是 PsycheMERGE 网络中的合作伙伴。 表明重度抑郁症 (MDD) 的多基因风险与 在此基础上，EHR 中广泛提供了 CVD 的重要预后生物标志物。 初步数据，我们的首要目标是发现导致 MDD 风险、CVD 的多效性基因 风险，以及我们勇敢的已知 CVD 生物标志物也将指出重要的途径 在目标 2 中，我们采用人群流行病学方法来研究 MDD 的生物学。 研究生物心理社会变量对遗传和表型的调节作用 最后，在目标 3 中，我们描述了表型和基因组的特征。 三种常见严重精神疾病与其他疾病之间的关系 医学现象，包括对超过 300,000 人进行的超过 500 次临床实验室测试，并提供数据 电子病历中迫切需要改善精神科护理和治疗。 拟议的研究包括一套全面的疾病及其合并症。 旨在调查遗传、临床和社会心理危险因素的综合分析 导致精神疾病的发展并危及生命 国家电子病历和相关生物库网络背景下的合并症。 ！