Investigating the role of immune genes and inflammatory biomarkers in schizophrenia heterogeneity

研究免疫基因和炎症生物标志物在精神分裂症异质性中的作用

• 批准号: 10602725
• 负责人: Allison Michelle Lake
• 金额: $ 3.19万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10602725
• 关键词: Age; All of Us Research Program; Antipsychotic Agents; Autoimmune Diseases; Behavior; Biological; Biological Markers; Blood; C-reactive protein; Chromosome 6; Clinical; Code; Complement; Copy Number Polymorphism; Data; Development; Diagnosis; Diagnostic; Dimensions; Disease; Electronic Health Record; Etiology; Genes; Genetic; Genetic Risk; Genotype; Heritability; Heterogeneity; Hospitalization; Immune; Immune system; Immunogenetics; Immunologic Epidemiology; Immunologic Factors; Immunologic Markers; Individual; Inflammation; Inflammatory; Informatics; Inpatients; Institution; Interleukin-6; Joints; Laboratories; Leukocytes; Link; Longitudinal cohort; Low Prevalence; Major Histocompatibility Complex; Measures; Mediating; Mediation; Mediator; Mendelian randomization; Mentors; Modeling; Nature; Outcome; Pathogenesis; Pathway interactions; Patients; Pattern; Perceptual distortions; Peripheral; Population; Process; Proteins; Research; Resources; Retrospective cohort study; Role; Sampling; Schizophrenia; Signal Transduction; Structure; Therapeutic Intervention; Time; Veterans; Withdrawal; Work; biobank; clinical biomarkers; clinical heterogeneity; cohort; cytokine; digital repositories; disability; first episode psychosis; genetic epidemiology; genetic predictors; genetic risk factor; genome wide association study; genomic locus; immune function; indexing; insight; neuropsychiatric disorder; neuropsychiatry; predict clinical outcome; predictive marker; programs; repository; schizophrenia risk; schizophrenia spectrum disorder; social; targeted treatment; treatment response; whole genome

PROJECT SUMMARY/ABSTRACT Schizophrenia is a debilitating neuropsychiatric condition with a strong genetic component but poorly understood biological mechanisms. The strongest signal from genome-wide association studies (GWAS) of schizophrenia lies in the major histocompatibility complex locus and is in part driven by copy number variation in the complement component 4 (C4) gene, an important mediator in the complement cascade. Furthermore, cross-disorder studies implicate shared genetic risk in schizophrenia and autoimmune disorders, suggesting a potential immunogenetic role in pathogenesis. Schizophrenia has been linked to increased levels of peripheral inflammation, and immune biomarkers predict worse outcomes in patients with the disorder. However, it is unclear whether inflammation is a causal factor or a consequence of the disease process, and to what extent immune-regulating genes play a role. This work will investigate the joint role of immune biomarkers and genetics in schizophrenia in a large biobank linked to electronic health records (EHRs). First, a repository of EHRs with longitudinal clinical laboratory data will be used to examine the temporal relationship between immune biomarker levels and schizophrenia diagnoses. Within schizophrenia spectrum patients, these biomarker levels will be assessed for their ability to predict specific clinical outcomes. Second, longitudinal cohorts paralleling those proposed in Aim 1 will be constructed but incorporating whole-genome genotyping data from a subset of ~90,000 individuals that are a part of the BioVU, VUMC’s biorepository resource. Genetic predictors of immune biomarkers will be included in these models and evaluated for their relative contributions to schizophrenia risk and their ability to predict clinical outcomes. Mediation analyses will then be conducted to investigate causal pathways linking C4 CNV and immune biomarker alterations in schizophrenia in BioVU. These analyses will be replicated and meta- analyzed in additional well-powered EHR-linked biobanks from the Million Veteran Program and All of Us research program. The proposed studies will elucidate the poorly understood relationships between immune-regulating genetic risk factors, immune biomarkers, and clinical heterogeneity in schizophrenia spectrum disorders. Understanding these relationships will yield mechanistic insights and uncover potentially clinically useful biomarkers of schizophrenia disease course.

项目总结/摘要 精神分裂症是一种使人衰弱的神经精神疾病，具有很强的遗传成分， 了解生物机制。来自全基因组关联研究（GWAS）的最强信号， 精神分裂症位于主要组织相容性复合体基因座，部分由拷贝数驱动 补体成分4（C4）基因的变异，补体级联反应中的重要介质。 此外，交叉疾病研究暗示精神分裂症和自身免疫性疾病的遗传风险是相同的。 疾病，提示在发病机制中的潜在免疫遗传作用。精神分裂症与 外周炎症水平升高和免疫生物标志物可预测患者的不良结局 与疾病有关。然而，目前还不清楚炎症是一个因果因素还是一个后果， 疾病过程，以及免疫调节基因在多大程度上发挥作用。这项工作将调查 在与电子健康相关的大型生物库中，免疫生物标志物和遗传学在精神分裂症中的联合作用 记录（EHR）。首先，将使用具有纵向临床实验室数据的EHR存储库， 检查免疫生物标志物水平和精神分裂症诊断之间的时间关系。内 对于精神分裂症谱患者，将评估这些生物标志物水平预测特异性 临床结果。第二，将建立与目标1所建议的纵向队列平行的纵向队列， 整合来自约90，000个个体的子集的全基因组基因分型数据，这些个体是 BioVU，VUMC的生物资源库。免疫生物标志物的遗传预测因子将包括在这些研究中。 模型，并评估其对精神分裂症风险的相对贡献及其预测临床 结果。然后将进行中介分析，以研究C4 CNV和 BioVU中精神分裂症的免疫生物标志物改变。这些分析将被复制和Meta- 在来自百万退伍军人计划和我们所有人的其他功能良好的EHR相关生物库中进行了分析 研究计划。拟议中的研究将阐明人们所知甚少的 精神分裂症的免疫调节遗传危险因素、免疫生物标志物和临床异质性 谱系障碍理解这些关系将产生机械的见解，并揭示 精神分裂症病程的潜在临床有用的生物标志物。