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Association Between Psychiatric Polygenic Scores, Healthcare Utilization and Comorbidity Burden.
Kirchner, H Lester; Rocha, Daniel; Linner, Richard K; Wilimitis, Drew; Walsh, Colin G; Ripperger, Michael; Lee, Hyunjoon; Liu, Zhaowen; Davis, Lea; Hu, Yirui; Chabris, Christopher F; Smoller, Jordan W.
Affiliation
  • Kirchner HL; Department of Population Health Sciences, Geisinger, Danville PA.
  • Rocha D; Phenomic Analytics and Clinical Data Core, Geisinger, Danville PA.
  • Linner RK; Department of Bioethics and Decision Sciences, Geisinger, Danville PA.
  • Wilimitis D; Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN.
  • Walsh CG; Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN.
  • Ripperger M; Department of Medicine, Vanderbilt University Medicine Center, Nashville, TN.
  • Lee H; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN.
  • Liu Z; Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN.
  • Davis L; Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA.
  • Hu Y; Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA.
  • Chabris CF; Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
  • Smoller JW; Department of Population Health Sciences, Geisinger, Danville PA.
medRxiv ; 2023 Sep 30.
Article in En | MEDLINE | ID: mdl-37808705
ABSTRACT

Purpose:

To estimate the association of psychiatric polygenic scores with healthcare utilization and comorbidity burden.

Methods:

Observational cohort study (N = 118,882) of adolescent and adult biobank participants with linked electronic health records (EHRs) from three diverse study sites; (Massachusetts General Brigham, Vanderbilt University Medical Center, Geisinger). Polygenic scores (PGS) were derived from the largest available GWAS of major depressive depression, bipolar disorder, and schizophrenia at the time of analysis. Negative binomial regression models were used to estimate the association between each psychiatric PGS and healthcare utilization and comorbidity burden. Healthcare utilization was measured as frequency of emergency department (ED), inpatient (IP), and outpatient (OP) visits. Comorbidity burden was defined by the Elixhauser Comorbidity Index and the Charlson Comorbidity Index.

Results:

Participants had a median follow-up duration of 12 years in the EHR. Individuals in the top decile of polygenic score for major depressive disorder had significantly more ED visits (RR=1.22, 95% CI; 1.17, 1.29) compared to those the lowest decile. Increases were also observed with IP and comorbidity burden. Among those diagnosed with depression and in the highest decile of the PGS, there was an increase in all utilization types (ED RR=1.56, 95% CI 1.41, 1.72; OP RR=1.16, 95% CI 1.08, 1.24; IP RR=1.23, 95% CI 1.12, 1.36) post-diagnosis. No clinically significant results were observed with bipolar and schizophrenia polygenic scores.

Conclusions:

Polygenic score for depression is modestly associated with increased healthcare resource utilization and comorbidity burden, in the absence of diagnosis. Following a diagnosis of depression, the PGS was associated with further increases in healthcare utilization. These findings suggest that depression genetic risk is associated with utilization and burden of chronic disease in real-world settings.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Aspects: Implementation_research Language: En Journal: MedRxiv Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Aspects: Implementation_research Language: En Journal: MedRxiv Year: 2023 Document type: Article