Multi-modal intersection of depression and genetic liability to Alzheimers disease

抑郁症与阿尔茨海默病遗传易感性的多模式交叉

• 批准号: 10697330
• 负责人: Gita A Pathak
• 金额: $ 9.99万
• 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: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10697330
• 关键词: Acceleration; Advisory Committees; Affect; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease risk; Architecture; Biological Aging; Biological Markers; Brain; Brain imaging; Chronic; Code; DRD2 gene; Data; Data Analyses; Dementia; Development; Diagnosis; Disease; Drug Targeting; Educational workshop; Electronic Health Record; Family history of; Genes; Genetic; Genetic Risk; Genetic Variation; Genomics; Genotype; Gerontology; Health; Healthcare; Heritability; Hippocampus; Impaired cognition; Individual; Laboratories; Measures; Mediating; Mental Depression; Mental Health; Mentors; Messenger RNA; Methylation; Modeling; Molecular; Neurodegenerative Disorders; Outcome; PARK2 gene; Participant; Pathogenesis; Persons; Phase; Phenotype; Population; Predisposition; Prefrontal Cortex; Process; Proteome; Proxy; Psychiatry; Psychopathology; Quantitative Trait Loci; Recording of previous events; Regulatory Pathway; Research; Research Personnel; Risk; Risk Factors; Role; SNP array; Signal Transduction; Site; Stratification; Testing; Training; United States; Untranslated RNA; Variant; Veterans; Writing; age related; apolipoprotein E-4; biobank; biological adaptation to stress; brain tissue; brain volume; care burden; career; carrier status; cohort; comorbid depression; comorbidity; depressive symptoms; disease phenotype; drug repurposing; epigenome; epigenome-wide association studies; epigenomic profiling; epigenomics; exome; genetic information; genetic variant; genome wide association study; gray matter; high throughput technology; interest; large scale data; member; model design; multidisciplinary; multimodality; neuropsychiatry; novel; phenome; programs; protein expression; protein function; psychiatric comorbidity; psychogenetics; resilience; risk variant; therapeutic target; training opportunity; trait; transcriptome; transcriptomic profiling; transcriptomics

ABSTRACT Depressive symptoms are present in up to 40% of individuals with Alzheimer’s disease (AD) and an ongoing debate regarding whether they represent a risk factor or a prodromal sign of AD. Chronic conditions such as depression impact the stress response and may accelerate biological aging further contributing to susceptibility to age-related conditions specifically cognitive decline. However, genetics of psychiatric traits and AD have been mostly studied separately. This proposal aims to identify coding and non-coding regulatory variants associated with shared genetic risk for depression and AD in multiple cohorts: UK biobank, Million Veteran Program, Alzheimer’s Disease Sequencing Project, National Health and Resilience in Veterans Study, and Yale-Penn study, and replicate findings in PsycheMERGE, cumulatively studying more than 1 million individuals. We will assess two major risk factors of AD - APOE-ε4 carrier status (Model-1) and parental history of AD (Model-2) with depression. Our previous findings from the genetically regulated expression study of depression in 1.2 million individuals using hippocampus-based expression quantitative trait loci (QTL) identified several genes which have roles in AD pathology (e.g. PARK2, NEGR1, HSPA1A, ITPR3, NLGN1, and DRD2). Therefore, we hypothesize that stratifying depression with AD phenotypes will uncover overlapping genetic contributions between depression and AD and elucidate the shared molecular mechanisms, and potential therapeutic targets. To test theses hypotheses, this proposal aims to develop a multi-modal framework to study neuropsychiatric comorbidities by investigating, Aim-1) whole exome profiles for coding regions associated with depression and genetic risk for AD (K99 phase), Aim-2) transcriptomic profiles to identify a shared molecular basis for depression and AD risk by integrating large-scale GWAS with brain tissue-based molecular QTL studies (R00 phase), and Aim-3) epigenome profiles to identify methylation sites associated with a combined polygenic score of depression and AD, and compare biological aging between depression and AD comorbidity, and either disorder alone (R00 phase). The accompanying training includes didactic courses in i) data analysis from multiple high throughput technologies, ii) developing biomarkers from large-scale datasets, iii) computational programming and iv) gerontological studies. The professional development training will include writing workshops, building mentoring portfolio, training opportunities to establish laboratory as an independent researcher. This training plan was developed under advisory team comprised of five members who are experts in AD, psychiatry, aging, large-scale genomics, and cohorts with electronic health records. Together they provide guidance on the proposed study and support a multidisciplinary neuropsychiatric research career for the candidate.

摘要 抑郁症状存在于高达40%的阿尔茨海默病（AD）患者中，并且正在进行 关于它们是否代表AD的危险因素或前驱体征的争论。等慢性病 抑郁影响应激反应，并可能加速生物衰老，进一步导致易感性 与年龄相关的疾病特别是认知能力下降。然而，精神病学特征和AD的遗传学一直是 大部分是分开研究的。 该提案旨在确定与共享遗传相关的编码和非编码调控变体， 多个队列中抑郁症和AD的风险：英国生物库，百万退伍军人计划，阿尔茨海默病 测序项目，退伍军人研究中的国家健康和恢复力，耶鲁-宾夕法尼亚大学研究，并重复 PsycheMERGE的研究结果，累计研究超过100万人。我们将评估两个主要风险 AD - APOE-ε4携带状态（Model-1）和AD伴抑郁症的父母病史（Model-2）。我们 先前的研究结果来自120万人的抑郁症基因调控表达研究， 基于基因组的表达数量性状位点（QTL）鉴定了几个与AD相关的基因 病理学（例如PARK 2、NEGR 1、HSPA 1A、ITPR 3、NLGN 1和DRD 2）。因此，我们假设 将抑郁症与AD表型进行分层将揭示抑郁症与AD表型之间的重叠遗传贡献。 和AD的分子机制和潜在的治疗靶点。 为了验证这些假设，本研究提出了一个多模态的研究框架 目的：1）与神经精神共病相关的编码区的全外显子组谱 抑郁症和AD的遗传风险（K99期），Aim-2）转录组学谱，以确定一个共享的分子 通过整合大规模GWAS和基于脑组织的分子QTL研究，为抑郁症和AD风险奠定基础 (R00阶段）和Aim-3）表观基因组图谱，以鉴定与组合的多基因突变相关的甲基化位点。 抑郁症和AD评分，并比较抑郁症和AD合并症之间的生物老化， R 00期（R 00 phase）。 伴随的培训包括以下方面的教学课程：i）来自多个高通量的数据分析 技术，ii）从大规模数据集开发生物标志物，iii）计算编程和iv） 老年学研究专业发展培训将包括写作研讨会，建筑指导 投资组合，培训机会，建立实验室作为一个独立的研究人员。这个培训计划是 由五名AD、精神病学、衰老、大规模 基因组学和电子健康记录的队列。它们共同为拟议的研究提供指导 并支持候选人的多学科神经精神病学研究生涯。