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We examined the shared genetic components between these disorders based on multipopulation data sets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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\u2010wide 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\u2010analysis for each result from EAS and EUR samples to obtain robust evidence. Subsequent mendelian randomization analysis was also included to examine the causal effect.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A significant genetic correlation between SCZ and several metabolic syndrome (MetS) traits was detected in the combined samples (meta\u2010analysis between EAS and EUR data) (body mass index [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a0\u22120.10, q\u2010value\u00a0=\u00a01.0\u2009\u00d7\u200910\n                      <jats:sup>\u22129<\/jats:sup>\n                      ], high\u2010density\u2010lipoprotein cholesterol [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a00.072, q\u2010value\u00a0=\u00a02.9\u2009\u00d7\u200910\n                      <jats:sup>\u22123<\/jats:sup>\n                      ], blood sugar [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a0\u22120.068, q\u2010value\u00a0=\u00a01.4\u2009\u00d7\u200910\n                      <jats:sup>\u22122<\/jats:sup>\n                      ], triglycerides [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a0\u22120.052, q\u2010value\u00a0=\u00a02.4\u2009\u00d7\u200910\n                      <jats:sup>\u22122<\/jats:sup>\n                      ], systolic blood pressure [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a0\u22120.054, q\u2010value\u00a0=\u00a03.5\u2009\u00d7\u200910\n                      <jats:sup>\u22122<\/jats:sup>\n                      ], and C\u2010reactive protein [r\n                      <jats:sub>g<\/jats:sub>\n                      \u00a0=\u00a0\u22120.076, q\u2010value\u00a0=\u00a07.8\u2009\u00d7\u200910\n                      <jats:sup>\u22125<\/jats:sup>\n                      ]. However, no causal relationship on SCZ susceptibility was detected for these traits based on the mendelian randomization analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our results indicate shared genetic components between SCZ and MetS traits and C\u2010reactive 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/pcn.13372","type":"journal-article","created":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T10:19:05Z","timestamp":1652177945000},"page":"361-366","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Shared genetic components between metabolic syndrome and schizophrenia: Genetic correlation using multipopulation data sets"],"prefix":"10.1111","volume":"76","author":[{"given":"Rei","family":"Aoki","sequence":"first","affiliation":[{"name":"Department of Psychiatry Fujita Health University School of Medicine  Toyoake 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