Vanessa F Gonçalves1, Carolina Cappi2, Christian M Hagen3, Adolfo Sequeira4, Marquis P Vawter4, Andriy Derkach5, Clement C Zai6, Paula L Hedley3, Jonas Bybjerg-Grauholm3, Jennie G Pouget6, Ari B Cuperfain6, Patrick F Sullivan7, Michael Christiansen8, James L Kennedy6, Lei Sun9. 1. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Neuroscience Section, Centre for Addiction and Mental Health, Toronto, Ontario, Canada. Electronic address: Vanessa.Goncalves@camh.ca. 2. Department of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil. 3. Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark. 4. Department of Psychiatry and Human Behavior, University of California, Irvine, California. 5. Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, Ontario, Canada. 6. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Neuroscience Section, Centre for Addiction and Mental Health, Toronto, Ontario, Canada. 7. Department of Genetics, University of North Carolina, Chapel Hill, North Carolina; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 8. Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark; Department of Biomedical Science, University of Copenhagen, Copenhagen, Denmark. 9. Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, Ontario, Canada; Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Abstract
BACKGROUND: The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. METHODS: We conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects. RESULTS: In the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes. CONCLUSIONS: This study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample.
BACKGROUND: The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. METHODS: We conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects. RESULTS: In the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes. CONCLUSIONS: This study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample.
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