Investigating the role of immune genes and inflammatory biomarkers in schizophrenia heterogeneity
Investigating the role of immune genes and inflammatory biomarkers in schizophrenia heterogeneity
批准号:
10602725
负责人:
Allison Michelle Lake
金额:
$3.19万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-01-01 至 2026-12-31
关键词:
AgeAll of Us Research ProgramAntipsychotic AgentsAutoimmune DiseasesBehaviorBiologicalBiological MarkersBloodC-reactive proteinChromosome 6ClinicalCodeComplementCopy Number PolymorphismDataDevelopmentDiagnosisDiagnosticDimensionsDiseaseElectronic Health RecordEtiologyGenesGeneticGenetic RiskGenotypeHeritabilityHeterogeneityHospitalizationImmuneImmune systemImmunogeneticsImmunologic EpidemiologyImmunologic FactorsImmunologic MarkersIndividualInflammationInflammatoryInformaticsInpatientsInstitutionInterleukin-6JointsLaboratoriesLeukocytesLinkLongitudinal cohortLow PrevalenceMajor Histocompatibility ComplexMeasuresMediatingMediationMediatorMendelian randomizationMentorsModelingNatureOutcomePathogenesisPathway interactionsPatientsPatternPerceptual distortionsPeripheralPopulationProcessProteinsResearchResourcesRetrospective cohort studyRoleSamplingSchizophreniaSignal TransductionStructureTherapeutic InterventionTimeVeteransWithdrawalWorkbiobankclinical biomarkersclinical heterogeneitycohortcytokinedigital repositoriesdisabilityfirst episode psychosisgenetic epidemiologygenetic predictorsgenetic risk factorgenome wide association studygenomic locusimmune functionindexinginsightneuropsychiatric disorderneuropsychiatrypredict clinical outcomepredictive markerprogramsrepositoryschizophrenia riskschizophrenia spectrum disordersocialtargeted treatmenttreatment responsewhole genome
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英文摘要
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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