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

神经精神障碍与发病率和死亡率显著增加相关。 包括心血管疾病（CVD）在内的慢性复杂疾病是导致 患有精神疾病的人过早死亡。虽然有证据表明， 可改变的风险因素（即，吸烟、体重、药物使用等）增加风险，他们不 充分解释了这一人群的发病率和死亡率过高。越来越多的可用性 将电子健康记录（EHR）与生物样本连接起来的大规模生物库创造了一个 强大的，但仍然相对未开发的机会，精神病学研究，旨在解决 这种过高的发病率和死亡率。2007年，国家人类基因组研究所 （NHGRI）组织了电子医疗记录和基因组学（eMERGE）网络， 汇集了美国各地的研究人员，以促进基于EHR的基因组研究， 基因组医学的实施。我们已经建立了一个新的，大规模的合作， 联盟-PsycheMERGE-利用资源和现有的基础设施， eMERGE网络、精神病基因组学联盟（PGC）以及当地EHR和生物库 资源该应用程序使用跨多个医疗保健系统的EHR和基因组数据 （Partners Health Care、范德比尔特大学医学中心和盖辛格卫生系统） 是PsycheMERGE网络的合作伙伴。我们的初步数据还 研究表明，重度抑郁症（MDD）的多基因风险与以下因素相关： EHR中广泛可用的CVD重要预后生物标志物。在此基础上 初步数据，我们的第一个目标是发现多效基因有助于MDD风险，心血管疾病， 风险和已知的CVD生物标志物，我们假设也将指向重要的途径 参与了MDD的生物学研究。在目标2中，我们采用人口流行病学方法， 研究生物心理社会变量对遗传和表型的调节作用 MDD和CVD的危险因素。最后，在目标3中，我们描述了表型和基因组 三种常见的严重精神疾病与其他疾病之间的关系 医学表型，包括超过300，000人的超过500项临床实验室测试，并提供数据 在EHR公共卫生迫切需要改善精神病患者的护理和治疗。 疾病及其合并症。拟议的研究包括一套全面的 旨在调查遗传、临床和心理社会风险因素的综合分析 导致精神疾病的发展及其危及生命的 EHR和相关生物库国家网络背景下的合并症。 !

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. !