The genetic relationship between schizophrenia (SCZ) and other nonpsychiatric disorders remains largely unknown. We examined the shared genetic components between these disorders based on multipopulation data sets. Methods:We used two data sets for East Asian (EAS) and European (EUR) samples. SCZ data was based on the Psychiatric Genomics Consortium Asia with our own genome-wide association study for EAS and Psychiatric Genomics Consortium for EUR. Nonpsychiatric data (20 binary traits [mainly nonpsychiatric complex disorders] and 34 quantitative traits [mainly laboratory examinations and physical characteristics]) were obtained from Biobank Japan and UK Biobank for EAS and EUR samples, respectively. To evaluate genetic correlation, linkage disequilibrium score regression analysis was utilized with further meta-analysis for each result from EAS and EUR samples to obtain robust evidence. Subsequent mendelian randomization analysis was also included to examine the causal effect.Results: A significant genetic correlation between SCZ and several metabolic syndrome (MetS) traits was detected in the combined samples (meta-analysis between EAS and EUR data) (body mass index [r g = À0.10, q-value = 1.0 Â 10 À9 ], high-density-lipoprotein cholesterol [r g = 0.072, q-value = 2.9 Â 10 À3 ],blood sugar [r g = À0.068, q-value = 1.4 Â 10 À2 ], triglycerides [r g = À0.052, q-value = 2.4 Â 10 À2 ], systolic blood pressure [r g = À0.054, q-value = 3.5 Â 10 À2 ], and C-reactive protein [r g = À0.076, q-value = 7.8 Â 10 À5 ]. However, no causal relationship on SCZ susceptibility was detected for these traits based on the mendelian randomization analysis. Conclusion:Our results indicate shared genetic components between SCZ and MetS traits and C-reactive protein. Specifically, we found it interesting that the correlation between MetS traits and SCZ was the opposite of that expected from clinical studies: this genetic study suggests that SCZ susceptibility was associated with reduced MetS. This implied that MetS in patients with SCZ was not associated with genetic components but with environmental factors, including antipsychotics, lifestyle changes, poor diet, lack of exercise, and living conditions.

Pharmacogenetics/pharmacogenomics have enabled the detection of risk of human leukocyte antigen (HLA) variants for clozapine-induced agranulocytosis/granulocytopenia (CIAG). To apply this evidence to the clinical setting, we compared the cost-effectiveness of the proposed “HLA-guided treatment schedule” and the “current schedule” being used in Japan and the United Kingdom (UK) (absolute neutrophil count (ANC) cutoff at 1500/mm3); in the “HLA-guided treatment schedules,” we considered a situation wherein the HLA test performed before clozapine initiation could provide “a priori information” by detecting patients harboring risk of HLA variants (HLA-B*59:01 and “HLA-B 158T/HLA-DQB1 126Q” for Japanese and Caucasian populations, respectively), a part of whom can then avoid CIAG onset (assumed 30% “prevention rate”). For the primary analysis, we estimated the incremental cost-effectiveness ratio (ICER) of “HLA-guided treatment schedule” and “current schedule” used in Japan and the UK, using a Markov model to calculate the cost and quality-adjusted life years (QALYs) over a 10-year time period. Furthermore, as an explorative analysis, we simulated several situations with various ANC cutoffs (1000/mm3 and 500/mm3) and plotted the cost/QALYs for each option to identify the best, or estimate the next best candidate option applicable in actual clinical settings. The primary probabilistic analysis showed that the “HLA-guided treatment schedule” was more cost effective than the “current schedule”; the ICER was £20,995 and £21,373 for the Japanese and the UK populations, respectively. Additional simulation revealed that the treatment option of ANC cutoff at 500/mm3 without HLA screening was the most cost-effective option; however, several options may be candidates to break away from the “current schedule” of ANC cutoff at 1500/mm3. Owing to its cost-effectiveness, we propose such pharmacogenetic-guided/pharmacogenomic-guided clozapine treatment for use in the real-world setting, which provides key information for optimization of clinical guidelines for high-risk patients for gradual change of clozapine treatment schedule under the safety consideration.