Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.
Elise KochAnders KämpeMaris AlverSindri SigurðarsonGuðmundur EinarssonJuulia PartanenRobert L SmithPiotr JaholkowskiHeidi TaipaleMarkku LähteenvuoNiels Eiel SteenOlav B SmelandSrdjan DjurovicEspen Moldennull nullnull nullEngilbert SigurdssonHreinn StefánssonKári StefánssonAarno PalotieLili MilaniKevin S O'ConnellOle Andreas AndreassenPublished in: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology (2024)
Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.
Keyphrases
- bipolar disorder
- electronic health record
- major depressive disorder
- big data
- high dose
- adverse drug
- healthcare
- randomized controlled trial
- end stage renal disease
- copy number
- public health
- gene expression
- meta analyses
- risk assessment
- emergency department
- ejection fraction
- machine learning
- data analysis
- genome wide
- low dose
- current status
- human health
- health information
- dna methylation
- combination therapy
- high resolution