PTSD and Autoimmune Disease: Towards Causal Effects, Risk Factors, and Mitigators
创伤后应激障碍 (PTSD) 和自身免疫性疾病:因果效应、危险因素和缓解措施
基本信息
- 批准号:10696671
- 负责人:
- 金额:--
- 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
- 起止时间:2023-07-01 至 2028-06-30
- 项目状态:未结题
- 来源:
- 关键词:AccountingAddressAntibodiesAntidepressive AgentsAntiinflammatory EffectAttenuatedAutoimmuneAutoimmune DiseasesBig Data MethodsBiological ProcessBlack raceChronicChronic DiseaseClinicalComplexDataData ScienceData ScientistDatabasesDemographic FactorsDevelopmentDiagnosisDiseaseElectronic Health RecordEpidemiologic MethodsEpidemiologyEthnic OriginEtiologyEuropeanFundingGoalsHealthHealth behaviorHealthcare SystemsImmuneImmune responseIncidenceIndividualInflammationInflammatoryInterventionK-Series Research Career ProgramsKnowledgeLassoLatinxLinkLiteratureLogistic RegressionsMachine LearningMeasuresMediatingMental HealthMental disordersMentorsMentorshipMethodsModificationNaturePathologyPatientsPatternPharmaceutical PreparationsPost-Traumatic Stress DisordersPreventionProcessPsychiatric DiagnosisPsychoneuroimmunologyPsychotherapyRaceRecordsResearchResearch PersonnelRiskRisk FactorsSamplingSan FranciscoSelective Serotonin Reuptake InhibitorSeveritiesStructural ModelsTestingTimeTrainingTraumaVeteransVeterans Health AdministrationWorkcareerdesigndisorder riskdisorder subtypeethnic disparityethnic minority populationevidence baseexperiencefeature selectionhealth disparityhealth recordhigh riskimprovedmachine learning algorithmmachine learning modelmilitary veterannovelphysical conditioningprospectiveprotective factorspsychiatric comorbiditypsychologicracial disparityracial minorityrandom forestrisk mitigationsociodemographics
项目摘要
Posttraumatic stress disorder (PTSD) is a common, chronic, and debilitating psychiatric condition in Veterans.
Beyond psychiatric features, PTSD has been linked multiple physical health conditions due to poorer health
behaviors and dysregulation of biological processes such as immune dysregulation and chronic inflammation.
Prior evidence has indicated an association between PTSD and risk for autoimmune (AI) conditions, a group of
over 80 complex diseases involving self-reactive immune responses. However, research linking PTSD and AI
disease risk has largely focused on only a few prevalent AI conditions, has not estimated potential causal
relationships, has been in European mostly White samples, and has not examined risk or mitigating factors.
Causal methods, such as marginal structural modeling, can account for time-varying factors in observational
data to better estimate causal links between factors, providing more precise inferences than prior associational
studies. Additionally, research is needed to determine associations between PTSD and all AI diseases, which
are largely heterogeneous but share underlying etiology. Indeed, determining links between PTSD and certain
forms of AI dysregulation may point to patterns of immune processes that underlie disease risk. Given higher
rates of PTSD and some AI diseases in racial or ethnic minority groups, it is necessary to explore potential
health disparities in associations between PTSD and AI disease. Moreover, other important risk or protective
factors influencing AI disease risk in PTSD can be examined empirically by utilizing a large clinical sample and
testing multiple predictors in a machine learning context. Relatedly, no studies have determined whether
treatment for PTSD, such as antidepressants or evidence-based psychotherapy, may mitigate AI disease risk
among individuals with PTSD. This study is designed to respond to these gaps in the literature by estimating
causal associations between PTSD and AI disease in a large, diverse sample of US Veterans. The first aim is
to estimate the causal impact of PTSD on AI disease risk (e.g., any AI disease, individual AI conditions) and
examining the effect of psychiatric comorbidity (e.g., multiple psychiatric diagnoses) on AI disease. The second
aim is to determine whether race and ethnicity modify the association between PTSD and AI disease and to
use data-driven methods to explore clinical factors that increase or mitigate risk for AI disease in those with
PTSD. The third aim is to investigate whether receiving treatment (e.g., antidepressant medications,
psychotherapy) for PTSD attenuates risk for AI disease compared to those with PTSD not receiving treatment.
For all aims, data from national VA electronic health records (EHR) of approximately 9 million Veterans will be
accessed and analyzed to identify diagnoses of PTSD, AI disease, and relevant covariates across time. We
will apply marginal structural models, machine learning algorithms for feature selection, and logistic regression
with propensity score matching to address the aims. Aligned with the research aims, the training aims will
support my development as an independent researcher, including to develop: 1) knowledge of clinical PTSD
pathology and treatment; 2) expertise in psychoneuroimmunological processes in PTSD; 3) understanding of
AI disorders and their etiology; and 4) proficiency in big data methods including implementing causal inference
and machine learning in large-scale EHR data. My research and training aims will be supported by an excellent
mentorship team of interdisciplinary researchers and will be conducted at the San Francisco Veterans Affairs
Health Care System. This Career Development Award is the critical next step towards my overall scientific and
career goals, which are to apply data science and epidemiology to VA data to understand relationships
between trauma, PTSD, and physical disease in order to improve the health of Veterans with PTSD.
创伤后应激障碍(PTSD)是退伍军人中一种常见的、慢性的、使人衰弱的精神疾病。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Kristen Marie Nishimi其他文献
Kristen Marie Nishimi的其他文献
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