Tuesday, April 16, 2024
4/16/2024
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.
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