Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia
Kevin S. O’Connell, Elise Koch, Hasan Çağın Lenk, Ibrahim A. Akkouh, Guy Hindley, Piotr Jahołkowski, Robert L. Smith, Børge Holen, Alexey Shadrin, Oleksandr Frei, Olav B. Smeland, Nils Eiel Steen, Anders M. Dale, Espen Molden, Srdjan Djurovic, Ole A. Andreassen
Abstract
Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.