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.

ABSTRACT To broaden our understanding of bradyarrhythmias and diseases of the cardiac conduction system, we performed cross-sectional multi-ancestry genome-wide association study meta-analyses in up to 1.3 million individuals for sinus node dysfunction (SND), distal conduction disease (DCD), and pacemaker implantation (PM). We evaluated the biological relevance of bradyarrhythmia loci by analyses of transcriptomes, pleiotropy, and partitioned heritability based on cardiac single cell RNA sequencing data. Finally, we performed rare variant burden testing in 460,000 whole exome sequenced individuals from two biobanks. We identified 13, 28, and 21 common variant loci for SND, DCD, and PM, respectively. Four well-known common variant arrhythmia loci ( SCN5A/SCN10A , CCDC141, TBX20 , and CAMK2D) were shared for SND and DCD, while other loci were more specific for either SND or DCD. Cardiomyocyte-expressed genes were strongly enriched for contributions to DCD heritability, while SND and PM were more heterogeneous. Rare variant analyses implicated LMNA for all bradyarrhythmia subtypes; SMAD6 and SCN5A for DCD; and TTN , MYBPC3 , and SCN5A for PM. The genetic architectures of SND and DCD are both overlapping and distinct. Multiple genetic mechanisms involving ion channels, sarcomeric components, cellular homeostasis, and cardiac development may influence the development of bradyarrhythmias.