The role of microglia in major depressive disorder

小胶质细胞在重度抑郁症中的作用

• 批准号: 10513304
• 负责人: STELLA DRACHEVA
• 金额: --
• 依托单位: JAMES J PETERS VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10513304
• 关键词: Adult; Affect; Autopsy; Biochemical; Biological; Biological Assay; Blood; Brain; Cell Differentiation process; Cell Nucleus; Cell Separation; Cells; Cessation of life; Chromosome Mapping; Chronic; Complex; Data; Development; Disease; Disease remission; Elements; Enhancers; Epigenetic Process; Etiology; Fluorescence; Freezing; Functional disorder; Gene Expression; Genes; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genetic Transcription; Genome; Genotype; Goals; Hospitalization; Human; Human Genome; Immune; Libraries; Link; Major Depressive Disorder; Maps; Mental Depression; Mental disorders; Microglia; Morbidity - disease rate; Myeloid Cells; Neurobiology; Neuronal Dysfunction; Pathogenesis; Patients; Persons; Play; Population; Predisposition; Prefrontal Cortex; Prevalence; Protocols documentation; Quality of life; Quantitative Trait Loci; Recurrence; Regulator Genes; Regulatory Element; Reporter; Risk; Role; Signal Transduction; Sorting; Specimen; Suicide; Testing; Time; Tissues; Untranslated RNA; Validation; Variant; Veterans; base; brain cell; candidate identification; candidate validation; case control; causal variant; cell type; cohort; cost; disability; disorder risk; efficacious treatment; genome wide association study; genome-wide; induced pluripotent stem cell; ineffective therapies; military veteran; mortality; neuropsychiatry; novel; novel strategies; novel therapeutic intervention; promoter; protective allele; recruit; risk variant; societal costs; suicidal risk; transcription factor; transcriptome; transcriptome sequencing; treatment strategy; whole genome

Major depressive disorder (MDD) is a common mental illness that affects more than 300 million people worldwide. Depression is the most prevalent mental illness among U.S. veterans and increases their risk of hospitalization and death. Also, the prevalence of depression in veterans is significantly higher than in general U.S. adult population. Available treatments are ineffective for many MDD patients, and there is an urgent need to obtain a better understanding of biological bases of MDD in order to develop novel therapeutic strategies. Genetic contribution to MDD is ~40%, and recent large-scale GWAS discovered 102 significant loci that are linked to MDD risk. However, as in other complex disorders, the majority of the MDD risk loci reside within non-coding regions of the genome and are predicted to alter the activity of gene regulatory elements (GREs; e.g., enhancers or promoters). In addition, the effect of a GRE on gene expression is frequently dependent on the cell and tissue type, making it a challenge to understand the functional impact of GWAS risk loci. Linking the disease risk variants with expression quantitative trait loci (eQTLs) and/or with epigenetic maps of GREs in relevant tissues/cell types yielded formidable results in other psychiatric diseases and holds promise for MDD. In addition, a systematic experimental validation of eQTLs/enhancers’ activity via massively parallel reporter assays (MPRAs) provides a powerful platform to decipher the functional impact of the disease risk variants. To date, many neurobiological studies of MDD have been concentrated on neuronal dysfunction. However, multiple studies implicate microglia (MG)—the immune cells of the brain—to the pathogenesis of this disorder. Our preliminary data shows that MDD genetic risk is reflected in gene expression changes in the blood- derived myeloid cells. Because of the substantial overlap in transcriptomes of these cells and MG, these data suggest that MG might play an important role in susceptibility to MDD. However, large-scale gene expression data in purified MG are not available to test this hypothesis. Our overarching goal is to discern MG dysfunction in MDD as well as to link this dysfunction to genetic predisposition to MDD by integrating MDD GWAS, MG eQTLs, and epigenetic maps of enhancers that are active in MG. In Aim1, we will use our novel fluorescence-activated nuclei sorting (FANS) protocol (which allows the separation of MG from autopsied human brain) to generate high-quality gene expression data in MG purified from a large cohort of MDD cases and controls (N~300). Importantly, the cohort includes specimens from the U.S. veteran population. We will also perform a case-control comparison of gene expression in MG, including testing if alterations in MDD are different in veterans vs. non-veterans, In Aim2, we will use gene expression data from Aim 1 to map MG eQTLs, and will integrate these eQTLs with MDD GWAS findings using rigorous computational approaches. These analyses will unravel the functional implications of MDD risk variants on gene expression in MG, and will identify candidate causal eSNPs that will be functionally validated in Aim 3. Finally, in Aim3, we will use MPRAs to validate the candidate causal eSNPs that are harbored by putative enhancers and/or eQTL regions in MG. MPRAs will be performed in MG-like cells that will be differentiated from human induced pluripotent stem cells. Collectively, the proposed studies will lead to the discovery of MDD risk variants and the affected genes that are likely to be causal for MDD and act specifically in MG cells, paving the way for the development of novel treatment approaches. These studies are especially important for U.S. veterans, as the surge of depression- related suicides among veterans necessitate the development of novel therapeutic strategies for MDD.

重度抑郁症 (MDD) 是一种常见的精神疾病，影响着超过 3 亿人 全世界。抑郁症是美国退伍军人中最常见的精神疾病，并增加了他们患病的风险 住院和死亡。此外，退伍军人的抑郁症患病率明显高于一般人 美国成年人口。现有的治疗方法对许多 MDD 患者无效，迫切需要 更好地了解 MDD 的生物学基础，以便开发新的治疗策略。 遗传对 MDD 的贡献约为 40%，最近大规模 GWAS 发现了 102 个显着位点 与 MDD 风险相关。然而，与其他复杂疾病一样，大多数 MDD 风险位点位于 基因组的非编码区域，预计会改变基因调控元件（GRE； 例如，增强子或启动子）。此外，GRE 对基因表达的影响通常取决于 细胞和组织类型，这使得了解 GWAS 风险位点的功能影响成为一项挑战。链接 具有表达数量性状位点（eQTL）和/或 GRE 表观遗传图谱的疾病风险变异 相关组织/细胞类型在其他精神疾病中产生了令人惊叹的结果，并为MDD带来了希望。 此外，通过大规模并行报告系统对 eQTL/增强子的活性进行了系统的实验验证 分析（MPRA）提供了一个强大的平台来破译疾病风险变异的功能影响。 迄今为止，许多 MDD 的神经生物学研究都集中在神经元功能障碍上。 然而，多项研究表明小胶质细胞（MG）——大脑的免疫细胞——与这种疾病的发病机制有关。 紊乱。我们的初步数据表明，MDD 遗传风险反映在血液中基因表达的变化上。 衍生的骨髓细胞。由于这些细胞和 MG 的转录组有很大的重叠，这些数据 表明 MG 可能在 MDD 易感性中发挥重要作用。然而，大规模基因表达 纯化 MG 的数据无法用来检验这一假设。 我们的首要目标是识别 MDD 中的 MG 功能障碍，并将这种功能障碍与遗传联系起来。 通过整合 MDD GWAS、MG eQTL 和活跃增强子的表观遗传图谱来评估 MDD 的易感性 在MG。在 Aim1 中，我们将使用我们新颖的荧光激活核分选 (FANS) 方案（该方案允许 从尸检人脑中分离 MG），以在 MG 纯化中生成高质量的基因表达数据 来自大量 MDD 病例和对照 (N~300)。重要的是，该队列包括来自 美国退伍军人人口。我们还将对 MG 中的基因表达进行病例对照比较，包括 测试退伍军人与非退伍军人的 MDD 变化是否不同，在 Aim2 中，我们将使用基因表达数据 从目标 1 绘制 MG eQTL，并将使用严格的方法将这些 eQTL 与 MDD GWAS 结果整合 计算方法。这些分析将揭示 MDD 风险变异对基因的功能影响 MG 中的表达，并将识别候选因果 eSNP，这些 eSNP 将在目标 3 中进行功能验证。最后， 在 Aim3 中，我们将使用 MPRA 来验证假定增强子所携带的候选因果 eSNP 和/或 MG 中的 eQTL 区域。 MPRA 将在与人类分化的 MG 样细胞中进行 诱导多能干细胞。 总的来说，拟议的研究将导致 MDD 风险变异和受影响基因的发现 可能是 MDD 的病因，并且专门作用于 MG 细胞，为新型药物的开发铺平了道路 治疗方法。这些研究对于美国退伍军人来说尤其重要，因为抑郁症的激增 退伍军人中相关的自杀事件需要开发新的抑郁症治疗策略。