Genetic architecture of substance use disorders and major depression

重度抑郁症（MDD）通常发生在酒精使用障碍的个体中， (AUD)和处方阿片类药物使用障碍（POUD），这种合并症在退伍军人中非常普遍。 由于结果不佳（例如，复发、治疗退出、功能受损）和 个体与这些共病的疾病，更好地了解他们的病因和基础， 合并症具有重要的临床意义。虽然这些发展的共同途径 已经提出了合并症（例如，自我药疗），共同的遗传途径的MDD和这些 物质使用障碍（SUD）还没有得到很好的表征，这一努力是复杂的表型 异质性例如，并非所有个体都具有相同的物质使用率或SUD严重程度 症状与表型复杂性一致，这些SUD可能是遗传异质性的， 导致AUD或POUD的多种遗传途径。因此，通过改进SUD表型并减少 表型异质性，研究大量明确的病例和对照，我们可以减少 遗传异质性，并确定真正的遗传关联。百万退伍军人计划（MVP） 样本使得调查因果途径成为可能。本CDA-2提案的目标是 描述AUD和POUD的遗传结构，有和没有MDD，确定新的关系 在疾病的遗传易感性和其它表型之间（即，多效性），并指定因果途径 使用MVP示例。具体目标是：（1）识别患有AUD、POUD和合并MDD的退伍军人 并使用ICD-9/10诊断和自我评估， 报告措施;（2）评估遗传结构和因果关系的澳元和澳元与共同发生的 POUD和POUD与MDD共病的遗传结构和因果关系。 使用所有可用数据，将在芬奇中识别患有AUD的退伍军人，并根据 存在共同发生的MDD。同样，长期接受处方阿片类药物治疗的退伍军人， 将确定被诊断患有阿片类药物使用障碍的患者，并确定他们的MDD病史。关键数据 医学和精神病合并症（例如，创伤后应激障碍（PTSD）也将被提取。对照组和比较组 对于没有合并AUD或POUD和MDD以及仅合并MDD的退伍军人，将进行确定。我们还将 使用酒精使用障碍识别测试提取自我报告的酒精消费数据- 使用患者健康问卷-2进行的消耗和自我报告的抑郁症状， 在初级保健中定期使用。三个独立的全基因组关联研究， 带MDD的SUD（第一个AUD，第二个POUD）、不带MDD的SUD和MDD（无SUD）将于 使用PLINK的GenISIS平台。使用这些GWAS的汇总统计量，多基因风险评分（PRS） 将在3个独立样本中计算（MVP的下一版本[N = ~ 200，000]，PennMedicine BioBank [N = > 63，000]和Yale-Penn样品[N = > 17，300个深度表型个体]）。我们还将 执行下游分析（例如，SNP h2，注释，遗传相关），全表型关联 独立样本中PRS的分析，以及孟德尔随机化以评估遗传因果关系。 通过提高我们对SUD和MDD共病的遗传结构和因果关系的理解， 这些发现将通过识别风险最大的个体， 阐明药物发现的新生物学途径，并为个性化治疗提供信息。这 这一努力也将有助于退伍军人管理局治疗抑郁症的努力，抑郁症是自杀风险的主要因素， 强调其临床意义。该CDA-2还将为申请人提供以下方面的重点培训 遗传学，生物信息学，先进的统计方法，以及为成功的VA做好准备的granectin 研究生涯的重点是提高生活质量的退伍军人与SUD和共病疾病。

Major depressive disorder (MDD) occurs commonly among individuals both with alcohol use disorder (AUD) and prescription opioid use disorder (POUD) and such comorbidity is highly prevalent in Veterans. Given the poor outcomes (e.g., relapse, treatment drop out, impaired functioning) and increased mortality of individuals with these comorbid disorders, a better understanding of their etiology and the basis for the comorbidity is of great clinical importance. Although common pathways for the development of these comorbidities have been proposed (e.g., self-medication), the shared genetic pathways of MDD and these substance use disorders (SUDs) have not been well characterized, an effort that is complicated by phenotypic heterogeneity. For example, not all individuals present with the same rate of substance use or severity of SUD symptoms. Consistent with the phenotypic complexity, these SUDs are likely to be genetically heterogeneous, with multiple genetic pathways leading to AUD or POUD. Thus, by refining the SUD phenotype and reducing the phenotypic heterogeneity, studying a large number of well-defined cases and controls, we may reduce the genetic heterogeneity and identify true genetic associations. Moreover, the Million Veteran Program (MVP) sample makes possible the investigation of causal pathways. The objectives of this CDA-2 proposal are to characterize the genetic architecture of AUD and POUD, with and without MDD, identify novel relationships between genetic liability for the disorders and other phenotypes (i.e., pleiotropy), and specify causal pathways using the MVP sample. The specific aims are to: (1) identify Veterans with AUD, POUD, and co-occurring MDD and characterize their depressive symptomatology and substance use using ICD-9/10 diagnoses and self- report measures; (2) assess the genetic architecture and causal relations of AUD and AUD with co-occurring MDD; and (3) the genetic architecture and causal relations of POUD and POUD with co-occurring MDD. Using all available data, Veterans with AUD will be identified in VINCI and categorized based on the presence co-occurring MDD. Similarly, Veterans treated chronically with prescription opioids who have been diagnosed with an opioid use disorder will be identified and their MDD history ascertained. Data on key medical and psychiatric comorbidities (e.g., pain, PTSD) will also be extracted. Control and comparison groups of Veterans without comorbid AUD or POUD and MDD and with MDD alone will be ascertained. We will also extract self-reported alcohol consumption data using the Alcohol Use Disorders Identification Test- Consumption and self-reported depressive symptoms using the Patient Health Questionnaire-2, both administered regularly in primary care. Three separate genome-wide association studies of individuals with an SUD (first AUD, secondly POUD) with MDD, an SUD without MDD, and MDD (no SUD) will be conducted on the GenISIS platform using PLINK. Using summary statistics from these GWAS, polygenic risk scores (PRS) will be calculated in 3 independent samples (the next release of MVP [N = ~200,000], the PennMedicine BioBank [N = >63,000], and the Yale-Penn sample [N = >17,300 deeply phenotyped individuals]). We will also perform downstream analyses (e.g., SNP h2, annotation, genetic correlation), phenome-wide association analyses of the PRS in independent samples, and Mendelian randomization to assess genetic causal relations. By improving our understanding of the genetic architecture and causality of comorbid SUDs and MDD, these findings will inform prevention and treatment of SUDs and MDD by identifying individuals at greatest risk, elucidating novel biological pathways for medications discovery, and informing personalized treatment. This effort will also contribute to the VA’s efforts to treat depression, a leading contributor to suicide risk, further underscoring its clinical implications. This CDA-2 will also provide the applicant with focused training in genetics, bioinformatics, advanced statistical methods, and grantsmanship to prepare her for a successful VA research career focused on improving the quality of life for Veterans with SUDs and comorbid disorders.