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Karadag N, Hagen E, Shadrin AA, van der Meer D, O'Connell KS, Rahman Z, Kutrolli G, Parker N, Bahrami S, Fominykh V, Heuser K, Taubøll E, Steen NE, Djurovic S, Dale AM, Frei O, Andreassen OA, Smeland OB. Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology. Neurol Genet 2024; 10:e200143. [PMID: 38817246 PMCID: PMC11139015 DOI: 10.1212/nxg.0000000000200143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/27/2024] [Indexed: 06/01/2024]
Abstract
Background and Objectives Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.
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Affiliation(s)
- Naz Karadag
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Espen Hagen
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Alexey A Shadrin
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Dennis van der Meer
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Kevin S O'Connell
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Zillur Rahman
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Gleda Kutrolli
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Nadine Parker
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Shahram Bahrami
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Vera Fominykh
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Kjell Heuser
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Erik Taubøll
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Nils Eiel Steen
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Srdjan Djurovic
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Anders M Dale
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Oleksandr Frei
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Ole A Andreassen
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
| | - Olav B Smeland
- From the Institute of Clinical Medicine (N.K., E.H., A.A.S., D.M., K.S.O.C., Z.R., G.K., N.P., S.B., V.F., N.E.S., O.F., O.A.A., O.B.S.), NORMENT, University of Oslo; K.G. Jebsen Centre for Neurodevelopmental Disorders (A.A.S., O.A.A.), University of Oslo and Oslo University Hospital, Norway; Faculty of Health (D.M.), School of Mental Health and Neuroscience, Maastricht University, Netherlands; Department of Neurology (K.H., E.T.), Oslo University Hospital; Faculty of Medicine (E.T.), University of Oslo; Division of Mental Health and Addiction (N.E.S., O.A.A., O.B.S.), Oslo University Hospital; Department of Psychiatric Research (N.E.S.), Diakonhjemmet Hospital; Department of Medical Genetics (S.D.), Oslo University Hospital, Norway; Department of Clinical Science (S.D.), NORMENT, University of Bergen, Norway; Department of Cognitive Science (A.M.D.); Multimodal Imaging Laboratory (A.M.D.); Department of Psychiatry (A.M.D.); Department of Neurosciences (A.M.D.), University of California, San Diego; and Department of Informatics (O.F.), Center for Bioinformatics, University of Oslo, Norway
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Ge YJ, Fu Y, Gong W, Cheng W, Yu JT. Genetic architecture of brain morphology and overlap with neuropsychiatric traits. Trends Genet 2024:S0168-9525(24)00079-9. [PMID: 38702264 DOI: 10.1016/j.tig.2024.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/05/2024] [Accepted: 04/12/2024] [Indexed: 05/06/2024]
Abstract
Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.
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Affiliation(s)
- Yi-Jun Ge
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Weikang Gong
- School of Data Science, Fudan University, Shanghai, China; Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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Tao Y, Zhao R, Yang B, Han J, Li Y. Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia. J Transl Med 2024; 22:373. [PMID: 38637810 PMCID: PMC11025255 DOI: 10.1186/s12967-024-05153-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/01/2024] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies. METHODS We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets. RESULTS We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data. CONCLUSIONS Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.
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Affiliation(s)
- Yiming Tao
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China
- Department of Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250101, Shandong, China
| | - Rui Zhao
- Department of Laboratory Medicine, The First Afliated Hospital of Chongqing Medical University, Chongqing, 400042, China
| | - Bin Yang
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China
| | - Jie Han
- Department of Emergency, School of Medicine, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China.
| | - Yongsheng Li
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China.
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4
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Zhang X, Wang S, Liu S, Du Z, Wu G, Liang Y, Huang Y, Shang X, Hu Y, Zhu Z, Sun W, Zhang X, Yu H. Epidemiologic association and shared genetic architecture between cataract and hearing difficulties among middle-aged and older adults. Hum Genomics 2024; 18:39. [PMID: 38632618 PMCID: PMC11022469 DOI: 10.1186/s40246-024-00601-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 03/20/2024] [Indexed: 04/19/2024] Open
Abstract
Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98-2.27; OR, 2.03; 95% CI, 1.86-2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.
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Affiliation(s)
- Xiayin Zhang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Shan Wang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Shunming Liu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Zijing Du
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Guanrong Wu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yingying Liang
- Department of Ophthalmology, Guangzhou First people's Hospital, Guangzhou, China
| | - Yu Huang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xianwen Shang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yijun Hu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Zhuoting Zhu
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, VIC, East Melbourne, Australia
| | - Wei Sun
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
| | - Xueli Zhang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
| | - Honghua Yu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.
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5
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Sun X, Qian Y, Cheng W, Ye D, Liu B, Zhou D, Wen C, Andreassen OA, Mao Y. Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases. BMC Med 2024; 22:152. [PMID: 38589871 PMCID: PMC11003061 DOI: 10.1186/s12916-024-03376-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 03/26/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. METHODS Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. RESULTS Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. CONCLUSIONS This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.
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Affiliation(s)
- Xiaohui Sun
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yu Qian
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- School of Life Sciences, Westlake University, Hangzhou, 310024, China
| | - Weiqiu Cheng
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway
| | - Ding Ye
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Bin Liu
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chengping Wen
- College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway.
| | - Yingying Mao
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
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6
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Karadag N, Hagen E, Shadrin AA, van der Meer D, O’Connell KS, Rahman Z, Kutrolli G, Parker N, Bahrami S, Fominykh V, Heuser K, Taubøll E, Ueland T, Steen NE, Djurovic S, Dale AM, Frei O, Andreassen OA, Smeland OB. Unraveling the shared genetics of common epilepsies and general cognitive ability. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.25.24304773. [PMID: 38585944 PMCID: PMC10996742 DOI: 10.1101/2024.03.25.24304773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Objective Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.
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Affiliation(s)
- Naz Karadag
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Espen Hagen
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Alexey A. Shadrin
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Dennis van der Meer
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Maastricht University, Maastricht, Netherlands
| | - Kevin S. O’Connell
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Zillur Rahman
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Gleda Kutrolli
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Nadine Parker
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Shahram Bahrami
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Vera Fominykh
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
| | - Kjell Heuser
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Erik Taubøll
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Torill Ueland
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M. Dale
- Department of Cognitive Science, University of California, San Diego, United States
- Multimodal Imaging Laboratory, University of California, San Diego, United States
- Department of Psychiatry, University of California, San Diego, United States
- Department of Neurosciences, University of California, San Diego, United States
| | - Oleksandr Frei
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Olav B. Smeland
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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7
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Tissink EP, Shadrin AA, van der Meer D, Parker N, Hindley G, Roelfs D, Frei O, Fan CC, Nagel M, Nærland T, Budisteanu M, Djurovic S, Westlye LT, van den Heuvel MP, Posthuma D, Kaufmann T, Dale AM, Andreassen OA. Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study. Nat Commun 2024; 15:2655. [PMID: 38531894 DOI: 10.1038/s41467-024-46817-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 03/12/2024] [Indexed: 03/28/2024] Open
Abstract
Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.
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Affiliation(s)
- E P Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands.
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
| | - A A Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - D van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - N Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - G Hindley
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, 16 De Crespigny Park, London, SE5 8AB, United Kingdom
| | - D Roelfs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - O Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - C C Fan
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, 92037, USA
| | - M Nagel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
| | - T Nærland
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
| | - M Budisteanu
- Prof. Dr. Alex Obregia Clinical Hospital of Psychiatry, Bucharest, Romania
- "Victor Babes" National Institute of Pathology, Bucharest, Romania
| | - S Djurovic
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - L T Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - M P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - D Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - T Kaufmann
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
| | - A M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, 92037, USA
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92037, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, 92037, USA
| | - O A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway.
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway.
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8
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Chen S, Tan Y, Tian L. Immunophenotypes in psychosis: is it a premature inflamm-aging disorder? Mol Psychiatry 2024:10.1038/s41380-024-02539-z. [PMID: 38532012 DOI: 10.1038/s41380-024-02539-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 03/28/2024]
Abstract
Immunopsychiatric field has rapidly accumulated evidence demonstrating the involvement of both innate and adaptive immune components in psychotic disorders such as schizophrenia. Nevertheless, researchers are facing dilemmas of discrepant findings of immunophenotypes both outside and inside the brains of psychotic patients, as discovered by recent meta-analyses. These discrepancies make interpretations and interrogations on their roles in psychosis remain vague and even controversial, regarding whether certain immune cells are more activated or less so, and whether they are causal or consequential, or beneficial or harmful for psychosis. Addressing these issues for psychosis is not at all trivial, as immune cells either outside or inside the brain are an enormously heterogeneous and plastic cell population, falling into a vast range of lineages and subgroups, and functioning differently and malleably in context-dependent manners. This review aims to overview the currently known immunophenotypes of patients with psychosis, and provocatively suggest the premature immune "burnout" or inflamm-aging initiated since organ development as a potential primary mechanism behind these immunophenotypes and the pathogenesis of psychotic disorders.
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Affiliation(s)
- Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, PR China
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, PR China
| | - Li Tian
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
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9
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Zhang J, Qiu H, Zhao Q, Liao C, Guoli Y, Luo Q, Zhao G, Zhang N, Wang S, Zhang Z, Lei M, Liu F, Peng Y. Genetic overlap between schizophrenia and cognitive performance. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:31. [PMID: 38443399 PMCID: PMC10914834 DOI: 10.1038/s41537-024-00453-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/16/2024] [Indexed: 03/07/2024]
Abstract
Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.
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Affiliation(s)
- Jianfei Zhang
- College of Computer and Control Engineering, Qiqihar University, Qiqihar, Heilongjiang, China
| | - Hao Qiu
- College of Computer and Control Engineering, Qiqihar University, Qiqihar, Heilongjiang, China
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chongjian Liao
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Yuxuan Guoli
- The Second Hospital of Tianjin Medial University, Tianjin, China
| | - Qi Luo
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Guoshu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Nannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
| | - Yanmin Peng
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.
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10
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Zhang X, Liang Y, Huang Y, Liu S, Li Q, Wang S, Wu G, Du Z, Wang Y, Wang J, Hu Y, Zang S, Hu Y, Shang X, Zhang X, Zhang L, Brown A, Zhu Z, He M, Yu H. Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety. Invest Ophthalmol Vis Sci 2024; 65:12. [PMID: 38466289 PMCID: PMC10929750 DOI: 10.1167/iovs.65.3.12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/29/2024] [Indexed: 03/12/2024] Open
Abstract
Purpose Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety. Methods Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations. Results Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression. Conclusions Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.
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Affiliation(s)
- Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yingying Liang
- Department of Ophthalmology, Guangzhou First People's Hospital, Guangzhou, China
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland, United Kingdom
| | - Shunming Liu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Qinyi Li
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Shan Wang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Guanrong Wu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Zijing Du
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yaxin Wang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Jinghui Wang
- Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Haikou, China
| | - Yunyan Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Siwen Zang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Lei Zhang
- Clinical Medical Research Center, Children's Hospital of Nanjing Medical University, Nanjing, China
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia
- Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
| | - Andrew Brown
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland, United Kingdom
| | - Zhuoting Zhu
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
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11
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Nordengen K, Cappelletti C, Bahrami S, Frei O, Pihlstrøm L, Henriksen SP, Geut H, Rozemuller AJM, van de Berg WDJ, Andreassen OA, Toft M. Pleiotropy with sex-specific traits reveals genetic aspects of sex differences in Parkinson's disease. Brain 2024; 147:858-870. [PMID: 37671566 PMCID: PMC10907091 DOI: 10.1093/brain/awad297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 08/01/2023] [Accepted: 08/22/2023] [Indexed: 09/07/2023] Open
Abstract
Parkinson's disease is an age-related neurodegenerative disorder with a higher incidence in males than females. The causes for this sex difference are unknown. Genome-wide association studies (GWAS) have identified 90 Parkinson's disease risk loci, but the genetic studies have not found sex-specific differences in allele frequency on autosomal chromosomes or sex chromosomes. Genetic variants, however, could exert sex-specific effects on gene function and regulation of gene expression. To identify genetic loci that might have sex-specific effects, we studied pleiotropy between Parkinson's disease and sex-specific traits. Summary statistics from GWASs were acquired from large-scale consortia for Parkinson's disease (n cases = 13 708; n controls = 95 282), age at menarche (n = 368 888 females) and age at menopause (n = 69 360 females). We applied the conditional/conjunctional false discovery rate (FDR) method to identify shared loci between Parkinson's disease and these sex-specific traits. Next, we investigated sex-specific gene expression differences in the superior frontal cortex of both neuropathologically healthy individuals and Parkinson's disease patients (n cases = 61; n controls = 23). To provide biological insights to the genetic pleiotropy, we performed sex-specific expression quantitative trait locus (eQTL) analysis and sex-specific age-related differential expression analysis for genes mapped to Parkinson's disease risk loci. Through conditional/conjunctional FDR analysis we found 11 loci shared between Parkinson's disease and the sex-specific traits age at menarche and age at menopause. Gene-set and pathway analysis of the genes mapped to these loci highlighted the importance of the immune response in determining an increased disease incidence in the male population. Moreover, we highlighted a total of nine genes whose expression or age-related expression in the human brain is influenced by genetic variants in a sex-specific manner. With these analyses we demonstrated that the lack of clear sex-specific differences in allele frequencies for Parkinson's disease loci does not exclude a genetic contribution to differences in disease incidence. Moreover, further studies are needed to elucidate the role that the candidate genes identified here could have in determining a higher incidence of Parkinson's disease in the male population.
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Affiliation(s)
- Kaja Nordengen
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
| | - Chiara Cappelletti
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
- Department of Mechanical, Electronics and Chemical Engineering, Faculty of Technology, Art and Design, OsloMet—Oslo Metropolitan University, 0130 Oslo, Norway
- Department of Research, Innovation and Education, Oslo University Hospital, 0424 Oslo, Norway
| | - Shahram Bahrami
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0450 Oslo, Norway
| | - Oleksandr Frei
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0450 Oslo, Norway
| | - Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | | | - Hanneke Geut
- Section of Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 Amsterdam, The Netherlands
| | - Annemieke J M Rozemuller
- Department of Pathology, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 Amsterdam, The Netherlands
| | - Wilma D J van de Berg
- Section of Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 Amsterdam, The Netherlands
| | - Ole A Andreassen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0450 Oslo, Norway
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
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12
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Walker EF, Aberizk K, Yuan E, Bilgrami Z, Ku BS, Guest RM. Developmental perspectives on the origins of psychotic disorders: The need for a transdiagnostic approach. Dev Psychopathol 2024:1-11. [PMID: 38406831 DOI: 10.1017/s0954579424000397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Research on serious mental disorders, particularly psychosis, has revealed highly variable symptom profiles and developmental trajectories prior to illness-onset. As Dante Cicchetti pointed out decades before the term "transdiagnostic" was widely used, the pathways to psychopathology emerge in a system involving equifinality and multifinality. Like most other psychological disorders, psychosis is associated with multiple domains of risk factors, both genetic and environmental, and there are many transdiagnostic developmental pathways that can lead to psychotic syndromes. In this article, we discuss our current understanding of heterogeneity in the etiology of psychosis and its implications for approaches to conceptualizing etiology and research. We highlight the need for examining risk factors at multiple levels and to increase the emphasis on transdiagnostic developmental trajectories as a key variable associated with etiologic subtypes. This will be increasingly feasible now that large, longitudinal datasets are becoming available and researchers have access to more sophisticated analytic tools, such as machine learning, which can identify more homogenous subtypes with the ultimate goal of enhancing options for treatment and preventive intervention.
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Affiliation(s)
- Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Katrina Aberizk
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Emerald Yuan
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Zarina Bilgrami
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Benson S Ku
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Ryan M Guest
- Department of Psychology, Emory University, Atlanta, GA, USA
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13
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Tandon R, Nasrallah H, Akbarian S, Carpenter WT, DeLisi LE, Gaebel W, Green MF, Gur RE, Heckers S, Kane JM, Malaspina D, Meyer-Lindenberg A, Murray R, Owen M, Smoller JW, Yassin W, Keshavan M. The schizophrenia syndrome, circa 2024: What we know and how that informs its nature. Schizophr Res 2024; 264:1-28. [PMID: 38086109 DOI: 10.1016/j.schres.2023.11.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.
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Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI 49008, United States of America.
| | - Henry Nasrallah
- Department of Psychiatry, University of Cincinnati College of Medicine Cincinnati, OH 45267, United States of America
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance and Harvard Medical School, Cambridge, MA 02139, United States of America
| | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Dusseldorf, Heinrich-Heine University, Dusseldorf, Germany
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute of Neuroscience and Human Behavior, UCLA, Los Angeles, CA 90024, United States of America; Greater Los Angeles Veterans' Administration Healthcare System, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States of America
| | - Stephan Heckers
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37232, United States of America
| | - John M Kane
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Glen Oaks, NY 11004, United States of America
| | - Dolores Malaspina
- Department of Psychiatry, Neuroscience, Genetics, and Genomics, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannhein/Heidelberg University, Mannheim, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology, and Neuroscience, Kings College, London, UK
| | - Michael Owen
- Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Psychiatric and Neurodevelopmental Unit, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States of America
| | - Walid Yassin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
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14
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Tan W, Cheng Y, Huang D, Liu D, Zhang J, Li J, Liu Z, Pan Y. Influence of TMX2-CTNND1 polymorphism on cortical thickness in schizophrenia patients and unaffected siblings: an exploratory study based on target region sequencing. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2024; 46:e20233322. [PMID: 38219215 PMCID: PMC11189138 DOI: 10.47626/1516-4446-2023-3322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/25/2023] [Indexed: 01/16/2024]
Abstract
OBJECTIVE The advancement of neuroimaging and genetic research has revealed the presence of morphological abnormalities and numerous risk genes, along with their associations. We aimed to estimate magnetic resonance imaging-derived cortical thickness across multiple brain regions. METHODS The cortical thickness of 129 schizophrenia patients, 42 of their unaffected siblings, and 112 healthy controls was measured and the candidate genes were sequenced. Comparisons were made of cortical thickness (including 68 regions of the Desikan-Killiany Atlas) and genetic variants (in 108 risk genes for schizophrenia) among the three groups, and correlation analyses were performed regarding cortical thickness, clinical symptoms, cognitive tests (such as the N-back task and the logical memory test), and genetic variants. RESULTS Schizophrenia patients had significantly thinner bilateral frontal, temporal, and parietal gyri than healthy controls and unaffected siblings. Association analyses in target genes showed that four single nucleotide variants (SNVs) were significantly associated with schizophrenia, including thioredoxin-related transmembrane protein 2-catenin, cadherin-associated protein, delta 1 (SNV20673) (positive false discovery rate [PFDR] = 0.008) and centromere protein M (rs35542507, rs41277477, rs73165153) (PFDR = 0.030). Additionally, cortical thickness in the right pars triangularis was lower in carriers of the SNV20673 variant than in non-carriers (PFDR = 0.048). Finally, a positive correlation was found between right pars triangularis cortical thickness and logical memory in schizophrenia patients (r = 0.199, p = 0.032). CONCLUSIONS This study identified regional morphological abnormalities in schizophrenia, including the right homologue of Broca's area, which was associated with a risk variant that affected delta-1 catenin and logical memory. These findings suggest a potential association between candidate gene loci, cortical thickness, and schizophrenia.
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Affiliation(s)
- Wenjian Tan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yixin Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Danqing Huang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Dayi Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jiamei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinyue Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhening Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yunzhi Pan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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15
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Parker N, Cheng W, Hindley GFL, O'Connell KS, Karthikeyan S, Holen B, Shadrin AA, Rahman Z, Karadag N, Bahrami S, Lin A, Steen NE, Ueland T, Aukrust P, Djurovic S, Dale AM, Smeland OB, Frei O, Andreassen OA. Genetic Overlap Between Global Cortical Brain Structure, C-Reactive Protein, and White Blood Cell Counts. Biol Psychiatry 2024; 95:62-71. [PMID: 37348803 DOI: 10.1016/j.biopsych.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 06/02/2023] [Accepted: 06/11/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND For many brain disorders, a subset of patients jointly exhibit alterations in cortical brain structure and elevated levels of circulating immune markers. This may be driven in part by shared genetic architecture. Therefore, we investigated the phenotypic and genetic associations linking global cortical surface area and thickness with blood immune markers (i.e., white blood cell counts and plasma C-reactive protein levels). METHODS Linear regression was used to assess phenotypic associations in 30,823 UK Biobank participants. Genome-wide and local genetic correlations were assessed using linkage disequilibrium score regression and local analysis of covariance annotation. The number of shared trait-influencing genetic variants was estimated using MiXeR. Shared genetic architecture was assessed using a conjunctional false discovery rate framework, and mapped genes were included in gene-set enrichment analyses. RESULTS Cortical structure and blood immune markers exhibited predominantly inverse phenotypic associations. There were modest genome-wide genetic correlations, the strongest of which were for C-reactive protein levels (rg_surface_area = -0.13, false discovery rate-corrected p = 4.17 × 10-3; rg_thickness = -0.13, false discovery rate-corrected p = 4.00 × 10-2). Meanwhile, local genetic correlations showed a mosaic of positive and negative associations. White blood cells shared on average 46.24% and 38.64% of trait-influencing genetic variants with surface area and thickness, respectively. Additionally, surface area shared 55 unique loci with the blood immune markers while thickness shared 15. Overall, monocyte count exhibited the largest genetic overlap with cortical brain structure. A series of gene enrichment analyses implicated neuronal-, astrocytic-, and schizophrenia-associated genes. CONCLUSIONS The findings indicate shared genetic underpinnings for cortical brain structure and blood immune markers, with implications for neurodevelopment and understanding the etiology of brain-related disorders.
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Affiliation(s)
- Nadine Parker
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Weiqiu Cheng
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, United Kingdom
| | - Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sandeep Karthikeyan
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Børge Holen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Zillur Rahman
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Naz Karadag
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aihua Lin
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thor Ueland
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway; KG Jebsen Thrombosis Research and Expertise Centre, University of Tromsø, Tromsø, Norway
| | - Pål Aukrust
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway; Section of Clinical Immunology and Infectious Disease, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California; Department of Psychiatry, University of California, San Diego, La Jolla, California; Department of Neurosciences, University of California San Diego, La Jolla, California; Department of Radiology, University of California San Diego, La Jolla, California
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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16
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Ma DR, Li SJ, Shi JJ, Liang YY, Hu ZW, Hao XY, Li MJ, Guo MN, Zuo CY, Yu WK, Mao CY, Tang MB, Zhang C, Xu YM, Wu J, Sun SL, Shi CH. Shared Genetic Architecture between Parkinson's Disease and Brain Structural Phenotypes. Mov Disord 2023; 38:2258-2268. [PMID: 37990409 DOI: 10.1002/mds.29598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/02/2023] [Accepted: 08/21/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) have consistently demonstrated brain structure abnormalities, indicating the presence of shared etiological and pathological processes between PD and brain structures; however, the genetic relationship remains poorly understood. OBJECTIVE The aim of this study was to investigate the extent of shared genetic architecture between PD and brain structural phenotypes (BSPs) and to identify shared genomic loci. METHODS We used the summary statistics from genome-wide association studies to conduct MiXeR and conditional/conjunctional false discovery rate analyses to investigate the shared genetic signatures between PD and BSPs. Subsequent expression quantitative trait loci mapping in the human brain and enrichment analyses were also performed. RESULTS MiXeR analysis identified genetic overlap between PD and various BSPs, including total cortical surface area, average cortical thickness, and specific brain volumetric structures. Further analysis using conditional false discovery rate (FDR) identified 21 novel PD risk loci on associations with BSPs at conditional FDR < 0.01, and the conjunctional FDR analysis demonstrated that PD shared several genomic loci with certain BSPs at conjunctional FDR < 0.05. Among the shared loci, 16 credible mapped genes showed high expression in the brain tissues and were primarily associated with immune function-related biological processes. CONCLUSIONS We confirmed the polygenic overlap with mixed directions of allelic effects between PD and BSPs and identified multiple shared genomic loci and risk genes, which are likely related to immune-related biological processes. These findings provide insight into the complex genetic architecture associated with PD. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dong-Rui Ma
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Shuang-Jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Jing-Jing Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Yuan-Yuan Liang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Zheng-Wei Hu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Xiao-Yan Hao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Meng-Jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Meng-Nan Guo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Chun-Yan Zuo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Wen-Kai Yu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Cheng-Yuan Mao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Mi-Bo Tang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Chan Zhang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Yu-Ming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Jun Wu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Shi-Lei Sun
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Chang-He Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
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17
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Jaholkowski P, Hindley GFL, Shadrin AA, Tesfaye M, Bahrami S, Nerhus M, Rahman Z, O’Connell KS, Holen B, Parker N, Cheng W, Lin A, Rødevand L, Karadag N, Frei O, Djurovic S, Dale AM, Smeland OB, Andreassen OA. Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci. Schizophr Bull 2023; 49:1654-1664. [PMID: 37163672 PMCID: PMC10686370 DOI: 10.1093/schbul/sbad063] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR < 0.05. Among the 72 shared loci, 40 loci have not previously been reported for vitD, and 9 were novel for SCZ. Further, 64% had discordant effects on SCZ-risk and vitD levels. A mixture of shared variants with concordant and discordant effects with a predominance of discordant effects was in line with weak negative genetic correlation (rg = -0.085). Our results displayed shared genetic architecture between SCZ and vitD with mixed effect directions, suggesting overlapping biological pathways. Shared genetic variants with complex overlapping mechanisms may contribute to the coexistence of SCZ and vitD deficiency and influence the clinical picture.
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Affiliation(s)
- Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King’s College
London, London, UK
| | - Alexey A Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and
Oslo University Hospital, Oslo, Norway
| | - Markos Tesfaye
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Department of Psychiatry, St. Paul’s Hospital Millennium Medical
College, Addis Ababa, Ethiopia
| | - Shahram Bahrami
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Mari Nerhus
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Department of Special Psychiatry, Akershus University
Hospital, Lørenskog, Norway
- Division of Health Services Research and Psychiatry,
Institute of Clinical Medicine, Campus Ahus, University of Oslo,
Oslo, Norway
| | - Zillur Rahman
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Kevin S O’Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Nadine Parker
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Aihua Lin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of
Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital,
Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University of
Bergen, Bergen, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego,
La Jolla, CA
- Multimodal Imaging Laboratory, University of California San
Diego, La Jolla, CA
- Department of Psychiatry, University of California, San
Diego, La Jolla, CA
- Department of Neurosciences, University of California San
Diego, La Jolla, CA
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and
Oslo University Hospital, Oslo, Norway
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18
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Stauffer EM, Bethlehem RAI, Dorfschmidt L, Won H, Warrier V, Bullmore ET. The genetic relationships between brain structure and schizophrenia. Nat Commun 2023; 14:7820. [PMID: 38016951 PMCID: PMC10684873 DOI: 10.1038/s41467-023-43567-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023] Open
Abstract
Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer's disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders.
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Affiliation(s)
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Lena Dorfschmidt
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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19
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Rødevand L, Rahman Z, Hindley GFL, Smeland OB, Frei O, Tekin TF, Kutrolli G, Bahrami S, Hoseth EZ, Shadrin A, Lin A, Djurovic S, Dale AM, Steen NE, Andreassen OA. Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors. Am J Psychiatry 2023; 180:815-826. [PMID: 37752828 DOI: 10.1176/appi.ajp.20220660] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
OBJECTIVE Schizophrenia is associated with increased risk of cardiovascular disease (CVD), although there is variation in risk among individuals. There are indications of shared genetic etiology between schizophrenia and CVD, but the nature of the overlap remains unclear. The aim of this study was to fill this gap in knowledge. METHODS Overlapping genetic architectures between schizophrenia and CVD risk factors were assessed by analyzing recent genome-wide association study (GWAS) results. The bivariate causal mixture model (MiXeR) was applied to estimate the number of shared variants and the conjunctional false discovery rate (conjFDR) approach was used to pinpoint specific shared loci. RESULTS Extensive genetic overlap was found between schizophrenia and CVD risk factors, particularly smoking initiation (N=8.6K variants) and body mass index (BMI) (N=8.1K variants). Several specific shared loci were detected between schizophrenia and BMI (N=304), waist-to-hip ratio (N=193), smoking initiation (N=293), systolic (N=294) and diastolic (N=259) blood pressure, type 2 diabetes (N=147), lipids (N=471), and coronary artery disease (N=35). The schizophrenia risk loci shared with smoking initiation had mainly concordant effect directions, and the risk loci shared with BMI had mainly opposite effect directions. The overlapping loci with lipids, blood pressure, waist-to-hip ratio, type 2 diabetes, and coronary artery disease had mixed effect directions. Functional analyses implicated mapped genes that are expressed in brain tissue and immune cells. CONCLUSIONS These findings indicate a genetic propensity to smoking and a reduced genetic risk of obesity among individuals with schizophrenia. The bidirectional effects of the shared loci with the other CVD risk factors may imply differences in genetic liability to CVD across schizophrenia subgroups, possibly underlying the variation in CVD comorbidity.
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Affiliation(s)
- Linn Rødevand
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Zillur Rahman
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Guy F L Hindley
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Olav B Smeland
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Oleksandr Frei
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Tahir Filiz Tekin
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Gleda Kutrolli
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Shahram Bahrami
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Eva Z Hoseth
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Alexey Shadrin
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Aihua Lin
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Srdjan Djurovic
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Anders M Dale
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Nils Eiel Steen
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
| | - Ole A Andreassen
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo (Rødevand, Rahman, Hindley, Smeland, Frei, Tekin, Kutrolli, Bahrami, Hoseth, Shadrin, Lin, Steen, Andreassen); Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway (Hoseth); Department of Medical Genetics, Oslo University Hospital, Oslo, and NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); Multimodal Imaging Laboratory and Departments of Radiology, Psychiatry, and Neurosciences, University of California San Diego, La Jolla (Dale)
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20
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Parker N, Cheng W, Hindley GFL, Parekh P, Shadrin AA, Maximov II, Smeland OB, Djurovic S, Dale AM, Westlye LT, Frei O, Andreassen OA. Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology. Mol Psychiatry 2023; 28:4924-4932. [PMID: 37759039 DOI: 10.1038/s41380-023-02264-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 09/06/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023]
Abstract
Improved understanding of the shared genetic architecture between psychiatric disorders and brain white matter may provide mechanistic insights for observed phenotypic associations. Our objective is to characterize the shared genetic architecture of bipolar disorder (BD), major depression (MD), and schizophrenia (SZ) with white matter fractional anisotropy (FA) and identify shared genetic loci to uncover biological underpinnings. We used genome-wide association study (GWAS) summary statistics for BD (n = 413,466), MD (n = 420,359), SZ (n = 320,404), and white matter FA (n = 33,292) to uncover the genetic architecture (i.e., polygenicity and discoverability) of each phenotype and their genetic overlap (i.e., genetic correlations, overlapping trait-influencing variants, and shared loci). This revealed that BD, MD, and SZ are at least 7-times more polygenic and less genetically discoverable than average FA. Even in the presence of weak genetic correlations (range = -0.05 to -0.09), average FA shared an estimated 42.5%, 43.0%, and 90.7% of trait-influencing variants as well as 12, 4, and 28 shared loci with BD, MD, and SZ, respectively. Shared variants were mapped to genes and tested for enrichment among gene-sets which implicated neurodevelopmental expression, neural cell types, myelin, and cell adhesion molecules. For BD and SZ, case vs control tract-level differences in FA associated with genetic correlations between those same tracts and the respective disorder (rBD = 0.83, p = 4.99e-7 and rSZ = 0.65, p = 5.79e-4). Genetic overlap at the tract-level was consistent with average FA results. Overall, these findings suggest a genetic basis for the involvement of brain white matter aberrations in the pathophysiology of psychiatric disorders.
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Affiliation(s)
- Nadine Parker
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Weiqiu Cheng
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
| | - Ivan I Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Olav B Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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21
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Steen NE, Rahman Z, Szabo A, Hindley GFL, Parker N, Cheng W, Lin A, O’Connell KS, Sheikh MA, Shadrin A, Bahrami S, Karthikeyan S, Hoseth EZ, Dale AM, Aukrust P, Smeland OB, Ueland T, Frei O, Djurovic S, Andreassen OA. Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities. Schizophr Bull 2023; 49:1345-1354. [PMID: 37319439 PMCID: PMC10483470 DOI: 10.1093/schbul/sbad082] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
BACKGROUND Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ. STUDY DESIGN GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects. STUDY RESULTS The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms. CONCLUSIONS Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.
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Affiliation(s)
- Nils Eiel Steen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Zillur Rahman
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Attila Szabo
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aihua Lin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin S O’Connell
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Mashhood A Sheikh
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sandeep Karthikeyan
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Eva Z Hoseth
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Cognitive Sciences, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Pål Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Olav B Smeland
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Thor Ueland
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen—Thrombosis Research and Expertise Center (TREC), University of Tromsø, Tromsø, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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22
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Chen Y, Lyu S, Xiao W, Yi S, Liu P, Liu J. Sleep Traits Causally Affect the Brain Cortical Structure: A Mendelian Randomization Study. Biomedicines 2023; 11:2296. [PMID: 37626792 PMCID: PMC10452307 DOI: 10.3390/biomedicines11082296] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/01/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Background: Brain imaging results in sleep deprived patients showed structural changes in the cerebral cortex; however, the reasons for this phenomenon need to be further explored. Methods: This MR study evaluated causal associations between morningness, ease of getting up, insomnia, long sleep, short sleep, and the cortex structure. Results: At the functional level, morningness increased the surface area (SA) of cuneus with global weighted (beta(b) (95% CI): 32.63 (10.35, 54.90), p = 0.004). Short sleep increased SA of the lateral occipital with global weighted (b (95% CI): 394.37(107.89, 680.85), p = 0.007. Short sleep reduced cortical thickness (TH) of paracentral with global weighted (OR (95% CI): -0.11 (-0.19, -0.03), p = 0.006). Short sleep reduced TH of parahippocampal with global weighted (b (95% CI): -0.25 (-0.42, -0.07), p = 0.006). No pleiotropy was detected. However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and the five types of sleep traits met the threshold. Conclusions: Our results potentially show evidence of a higher risk association between neuropsychiatric disorders and not only paracentral and parahippocampal brain areas atrophy, but also an increase in the middle temporal zone. Our findings shed light on the associations of cortical structure with the occurrence of five types of sleep traits.
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Affiliation(s)
- Yanjing Chen
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha 410011, China; (Y.C.); (S.L.); (S.Y.); (P.L.)
| | - Shiyi Lyu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha 410011, China; (Y.C.); (S.L.); (S.Y.); (P.L.)
| | - Wang Xiao
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha 410011, China;
| | - Sijie Yi
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha 410011, China; (Y.C.); (S.L.); (S.Y.); (P.L.)
| | - Ping Liu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha 410011, China; (Y.C.); (S.L.); (S.Y.); (P.L.)
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha 410011, China; (Y.C.); (S.L.); (S.Y.); (P.L.)
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha 410011, China
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23
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Cui LB, Wang XY, Fu YF, Liu XF, Wei Y, Zhao SW, Gu YW, Fan JW, Wu WJ, Gong H, Lin BD, Yin H, Guan F, Chang X. Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia. BMC Med 2023; 21:250. [PMID: 37424013 DOI: 10.1186/s12916-023-02963-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023] Open
Abstract
BACKGROUND Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.
| | - Xian-Yang Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hengfen Gong
- School of Medicine, Shanghai Pudong New Area Mental Health Center, Tongji University, Shanghai, China
| | - Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, China.
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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24
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Roelfs D, Frei O, van der Meer D, Tissink E, Shadrin A, Alnaes D, Andreassen OA, Westlye LT, Kaufmann T. Shared genetic architecture between mental health and the brain functional connectome in the UK Biobank. BMC Psychiatry 2023; 23:461. [PMID: 37353766 PMCID: PMC10290393 DOI: 10.1186/s12888-023-04905-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 05/26/2023] [Indexed: 06/25/2023] Open
Abstract
Psychiatric disorders are complex clinical conditions with large heterogeneity and overlap in symptoms, genetic liability and brain imaging abnormalities. Building on a dimensional conceptualization of mental health, previous studies have reported genetic overlap between psychiatric disorders and population-level mental health, and between psychiatric disorders and brain functional connectivity. Here, in 30,701 participants aged 45-82 from the UK Biobank we map the genetic associations between self-reported mental health and resting-state fMRI-based measures of brain network function. Multivariate Omnibus Statistical Test revealed 10 genetic loci associated with population-level mental symptoms. Next, conjunctional FDR identified 23 shared genetic variants between these symptom profiles and fMRI-based brain network measures. Functional annotation implicated genes involved in brain structure and function, in particular related to synaptic processes such as axonal growth (e.g. NGFR and RHOA). These findings provide further genetic evidence of an association between brain function and mental health traits in the population.
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Affiliation(s)
- Daniel Roelfs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, 1081 HV, The Netherlands
| | - Alexey Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnaes
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Bjørknes College, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany.
- German Center for Mental Health (DZPG), Tübingen, Germany.
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25
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Murray SO, Kolodny T, Webb SJ. Cortical Surface Area Relates to Distinct Computational Properties in Human Visual Perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.16.545373. [PMID: 37398212 PMCID: PMC10312808 DOI: 10.1101/2023.06.16.545373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Understanding the relationship between cortical structure and function is essential for elucidating the neural basis of human behavior. However, the impact of cortical structural features on the computational properties of neural circuits remains poorly understood. In this study, we demonstrate that a simple structural feature - cortical surface area (SA) - relates to specific computational properties underlying human visual perception. By combining psychophysical, neuroimaging, and computational modeling approaches, we show that differences in SA in the parietal and frontal cortices are associated with distinct patterns of behavior in a motion perception task. These behavioral differences can be accounted for by specific parameters of a divisive normalization model, suggesting that SA in these regions contributes uniquely to the spatial organization of cortical circuitry. Our findings provide novel evidence linking cortical structure to distinct computational properties and offer a framework for understanding how cortical architecture can impact human behavior.
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Affiliation(s)
- Scott O. Murray
- Department of Psychology, University of Washington, Seattle WA USA 98195
| | - Tamar Kolodny
- Department of Psychology, University of Washington, Seattle WA USA 98195
| | - Sara Jane Webb
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle WA USA 98195
- Seattle Children’s Research Institute, 1920 Terry Ave, Building Cure-03, Seattle WA 98101
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26
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Fominykh V, Shadrin AA, Jaholkowski PP, Bahrami S, Athanasiu L, Wightman DP, Uffelmann E, Posthuma D, Selbæk G, Dale AM, Djurovic S, Frei O, Andreassen OA. Shared genetic loci between Alzheimer's disease and multiple sclerosis: Crossroads between neurodegeneration and immune system. Neurobiol Dis 2023:106174. [PMID: 37286172 DOI: 10.1016/j.nbd.2023.106174] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/27/2023] [Accepted: 05/26/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. METHODS We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. RESULTS MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. CONCLUSIONS Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.
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Affiliation(s)
- Vera Fominykh
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Alexey A Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Piotr P Jaholkowski
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lavinia Athanasiu
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Douglas P Wightman
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Emil Uffelmann
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Pediatric Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam, the Netherlands
| | - Geir Selbæk
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Vestfold Hospital Trust, Norwegian National Centre for Ageing and Health, Tonsberg, Vestfold, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, California, USA; Department of Psychiatry, University of California San Diego, La Jolla, California, USA; Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Srdjan Djurovic
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Informatics, Centre for Bioinformatics, University of Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
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27
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Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, Yang YF, Xiao X, Yan H, Lu TL, Li J, Liao YD, Kang ZW, Wang LF, Li Y, Li M, Liu B, Huang HL, Lv LX, Yao Y, Tan YL, Breen G, Everall I, Wang HX, Huang Z, Zhang D, Yue WH. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res 2023; 10:24. [PMID: 37269009 DOI: 10.1186/s40779-023-00459-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/05/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment. METHODS Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial (n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial (n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls (n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R2 for regression, and decision curve analysis. RESULTS Six risk genes for SCZ (LINC01795, DDHD2, SBNO1, KCNG2, SEMA7A, and RUFY1) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867-0.881), R2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R2 = 0.507]. CONCLUSIONS This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC-ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).
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Affiliation(s)
- Liang-Kun Guo
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yi Su
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Yu-Ya-Nan Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, 272067, Shandong, China
| | - Zhe Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Wen-Qiang Li
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yong-Feng Yang
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hao Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Tian-Lan Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Jun Li
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yun-Dan Liao
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Zhe-Wei Kang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Li-Fang Wang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yue Li
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hai-Liang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Lu-Xian Lv
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yin Yao
- Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Yun-Long Tan
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ian Everall
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Hong-Xing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Zhuo Huang
- State Key Laboratory of Natural and Biomimetic Drugs, Key Laboratory for Neuroscience for Ministry of Education, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, 100191, China.
| | - Dai Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Wei-Hua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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28
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Cheng W, Parker N, Karadag N, Koch E, Hindley G, Icick R, Shadrin A, O'Connell KS, Bjella T, Bahrami S, Rahman Z, Tesfaye M, Jaholkowski P, Rødevand L, Holen B, Lagerberg TV, Steen NE, Djurovic S, Dale AM, Frei O, Smeland OB, Andreassen OA. The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study. Lancet Psychiatry 2023; 10:441-451. [PMID: 37208114 PMCID: PMC10311008 DOI: 10.1016/s2215-0366(23)00143-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). METHODS We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. FINDINGS Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22-0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug-gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. INTERPRETATION A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments. FUNDING US National Institutes of Health, the Research Council Norway, the South-East Regional Health Authority, Stiftelsen Kristian Gerhard Jebsen, EEA-RO-NO-2018-0535, European Union's Horizon 2020 Research and Innovation Programme, the Marie Skłodowska-Curie Actions, and University of Oslo Life Science.
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Affiliation(s)
- Weiqiu Cheng
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Nadine Parker
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Elise Koch
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Guy Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Romain Icick
- INSERM UMR-S1144, University of Paris, Paris, France
| | - Alexey Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Thomas Bjella
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Zillur Rahman
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Markos Tesfaye
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway; Department of Psychiatry, St Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Trine Vik Lagerberg
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M Dale
- Department of Psychiatry, and Department of Neurosciences, and Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway; Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway.
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29
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Wu BS, Ge YJ, Zhang W, Chen SD, Xiang ST, Zhang YR, Ou YN, Jiang YC, Tan L, Cheng W, Suckling J, Feng JF, Yu JT, Mao Y. Genome-wide association study of cerebellar white matter microstructure and genetic overlap with common brain disorders. Neuroimage 2023; 269:119928. [PMID: 36740028 DOI: 10.1016/j.neuroimage.2023.119928] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/12/2023] [Accepted: 02/02/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The cerebellum is recognized as being involved in neurocognitive and motor functions with communication with extra-cerebellar regions relying on the white matter integrity of the cerebellar peduncles. However, the genetic determinants of cerebellar white matter integrity remain largely unknown. METHODS We conducted a genome-wide association analysis of cerebellar white matter microstructure using diffusion tensor imaging data from 25,415 individuals from UK Biobank. The integrity of cerebellar white matter microstructure was measured as fractional anisotropy (FA) and mean diffusivity (MD). Identification of independent genomic loci, functional annotation, and tissue and cell-type analysis were conducted with FUMA. The linkage disequilibrium score regression (LDSC) was used to calculate genetic correlations between cerebellar white matter microstructure and regional brain volumes and brain-related traits. Furthermore, the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was employed to identify the shared genetic basis between cerebellar white matter microstructure and common brain disorders. RESULTS We identified 11 genetic loci (P < 8.3 × 10-9) and 86 genes associated with cerebellar white matter microstructure. Further functional enrichment analysis implicated the involvement of GABAergic neurons and cholinergic pathways. Significant polygenetic overlap between cerebellar white matter tracts and their anatomically connected or adjacent brain regions was detected. In addition, we report the overall genetic correlation and specific loci shared between cerebellar white matter microstructural integrity and brain-related traits, including movement, cognitive, psychiatric, and cerebrovascular categories. CONCLUSIONS Collectively, this study represents a step forward in understanding the genetics of cerebellar white matter microstructure and its shared genetic etiology with common brain disorders.
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Affiliation(s)
- Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Tong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yu-Chao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - John Suckling
- Department of Psychiatry, Brain Mapping Unit, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Ying Mao
- Department of Neurosurgery and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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30
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Andreassen OA, Hindley GFL, Frei O, Smeland OB. New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications. World Psychiatry 2023; 22:4-24. [PMID: 36640404 PMCID: PMC9840515 DOI: 10.1002/wps.21034] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/07/2022] [Indexed: 01/15/2023] Open
Abstract
Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.
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Affiliation(s)
- Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Guy F L Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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31
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Cheng W, van der Meer D, Parker N, Hindley G, O'Connell KS, Wang Y, Shadrin AA, Alnæs D, Bahrami S, Lin A, Karadag N, Holen B, Fernandez-Cabello S, Fan CC, Dale AM, Djurovic S, Westlye LT, Frei O, Smeland OB, Andreassen OA. Shared genetic architecture between schizophrenia and subcortical brain volumes implicates early neurodevelopmental processes and brain development in childhood. Mol Psychiatry 2022; 27:5167-5176. [PMID: 36100668 DOI: 10.1038/s41380-022-01751-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 01/14/2023]
Abstract
Patients with schizophrenia have consistently shown brain volumetric abnormalities, implicating both etiological and pathological processes. However, the genetic relationship between schizophrenia and brain volumetric abnormalities remains poorly understood. Here, we applied novel statistical genetic approaches (MiXeR and conjunctional false discovery rate analysis) to investigate genetic overlap with mixed effect directions using independent genome-wide association studies of schizophrenia (n = 130,644) and brain volumetric phenotypes, including subcortical brain and intracranial volumes (n = 33,735). We found brain volumetric phenotypes share substantial genetic variants (74-96%) with schizophrenia, and observed 107 distinct shared loci with sign consistency in independent samples. Genes mapped by shared loci revealed (1) significant enrichment in neurodevelopmental biological processes, (2) three co-expression clusters with peak expression at the prenatal stage, and (3) genetically imputed thalamic expression of CRHR1 and ARL17A was associated with the thalamic volume as early as in childhood. Together, our findings provide evidence of shared genetic architecture between schizophrenia and brain volumetric phenotypes and suggest that altered early neurodevelopmental processes and brain development in childhood may be involved in schizophrenia development.
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Affiliation(s)
- Weiqiu Cheng
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Nadine Parker
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy Hindley
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Kevin S O'Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Centre for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aihua Lin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sara Fernandez-Cabello
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Chun-Chieh Fan
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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32
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Shang MY, Wu Y, Zhang CY, Qi HX, Zhang Q, Huo JH, Wang L, Wang C, Li M. Bidirectional genetic overlap between bipolar disorder and intelligence. BMC Med 2022; 20:464. [PMID: 36447210 PMCID: PMC9710050 DOI: 10.1186/s12916-022-02668-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 11/17/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence. METHODS To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed. RESULTS Analysis with MiXeR suggested that approximately 10.3K variants could influence intelligence, among which 7.6K variants were correlated with the risk of BD (Dice: 0.80), and 47% of these variants predicted BD risk and intelligence in consistent allelic directions. The conjFDR analysis identified 37 distinct genomic loci that were jointly associated with BD and intelligence with a conjFDR < 0.01, and 16 loci (43%) had the same directions of allelic effects in both phenotypes. Brain eQTL analyses found that genes affected by the "concordant loci" were distinct from those modulated by the "discordant loci". Enrichment analyses suggested that genes related to the "concordant loci" were significantly enriched in pathways/phenotypes related with synapses and sleep quality, whereas genes associated with the "discordant loci" were enriched in pathways related to cell adhesion, calcium ion binding, and abnormal emotional phenotypes. CONCLUSIONS We confirmed the polygenic overlap with mixed directions of allelic effects between BD and intelligence and identified multiple genomic loci and risk genes. This study provides hints for the mesoscopic phenotypes of BD and relevant biological mechanisms, promoting the knowledge of the genetic and phenotypic heterogeneity of BD. The essential value of leveraging intelligence in BD investigations is also highlighted.
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Affiliation(s)
- Meng-Yuan Shang
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.,School of Basic Medical Science, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Yong Wu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Hao-Xiang Qi
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Qing Zhang
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.,School of Basic Medical Science, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Jin-Hua Huo
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chuang Wang
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China. .,School of Basic Medical Science, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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33
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Ahangari M, Kirkpatrick R, Nguyen TH, Gillespie N, Kendler KS, Bacanu SA, Webb BT, Verrelli BC, Riley BP. Examining the source of increased bipolar disorder and major depressive disorder common risk variation burden in multiplex schizophrenia families. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:106. [PMID: 36434002 PMCID: PMC9700852 DOI: 10.1038/s41537-022-00317-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/03/2022] [Indexed: 11/27/2022]
Abstract
Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia, and genetic studies show substantial genetic correlation among schizophrenia, bipolar disorder, and major depressive disorder. In this study, we examined the polygenic risk burden of bipolar disorder and major depressive disorder in 257 multiplex schizophrenia families (N = 1005) from the Irish Study of High-Density Multiplex Schizophrenia Families versus 2205 ancestry-matched controls. Our results indicate that members of multiplex schizophrenia families have an increased polygenic risk for bipolar disorder and major depressive disorder compared to population controls. However, this observation is largely attributable to the part of the genetic risk that bipolar disorder or major depressive disorder share with schizophrenia due to genetic correlation, rather than the affective portion of the genetic risk unique to them. These findings suggest that a complete interpretation of cross-disorder polygenic risks in multiplex families requires an assessment of the relative contribution of shared versus unique genetic factors to account for genetic correlations across psychiatric disorders.
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Affiliation(s)
- Mohammad Ahangari
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA USA
| | - Robert Kirkpatrick
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Tan-Hoang Nguyen
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Nathan Gillespie
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Kenneth S. Kendler
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
| | - Silviu-Alin Bacanu
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Bradley T. Webb
- grid.62562.350000000100301493GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC USA
| | - Brian C. Verrelli
- grid.224260.00000 0004 0458 8737Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA USA
| | - Brien P. Riley
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
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Hindley G, Frei O, Shadrin AA, Cheng W, O’Connell KS, Icick R, Parker N, Bahrami S, Karadag N, Roelfs D, Holen B, Lin A, Fan CC, Djurovic S, Dale AM, Smeland OB, Andreassen OA. Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation. Am J Psychiatry 2022; 179:833-843. [PMID: 36069018 PMCID: PMC9633354 DOI: 10.1176/appi.ajp.21101051] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Mental disorders are heritable and polygenic, and genome-wide genetic correlations (rg) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, rg may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions. METHODS The authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of "causal" variants for a given trait ("polygenicity"), the number of variants shared between traits, and the genetic correlation of shared variants (rgs). Local rg was investigated using LAVA. RESULTS Among mental disorders, ADHD was the least polygenic (5.6K "causal" variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in rg and rgs. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local rg (r=0.88, p<0.001). CONCLUSIONS There is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction.
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Affiliation(s)
- Guy Hindley
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and
Neurosciences, King’s College London, 16 De Crespigny Park, London SE5 8AB,
United Kingdom
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
- Center for Bioinformatics, Department of Informatics,
University of Oslo, PO box 1080, Blindern, 0316 Oslo, Norway
| | - Alexey A. Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders,
University of Oslo, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Kevin S. O’Connell
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Romain Icick
- INSERM UMR-S1144, Paris University, F-75006, France
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Naz Karadag
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Daniel Roelfs
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Børge Holen
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Aihua Lin
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Chun C Fan
- Department of Cognitive Science, University of California,
San Diego, La Jolla, CA, USA
- Multimodal Imaging Laboratory, University of California San
Diego, La Jolla, CA 92093, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital,
Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University
of Bergen, Bergen, Norway
- KG Jebsen Centre for Neurodevelopmental disorders,
University of Oslo, Oslo, Norway
| | - Anders M. Dale
- Multimodal Imaging Laboratory, University of California San
Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California, San
Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San
Diego, La Jolla, CA 92093, United States of America
- Department of Radiology, University of California, San
Diego, La Jolla, CA 92093, United States of America
| | - Olav B. Smeland
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University
of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407
Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders,
University of Oslo, Oslo, Norway
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Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives. Transl Psychiatry 2022; 12:447. [PMID: 36241627 PMCID: PMC9568576 DOI: 10.1038/s41398-022-02193-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 09/06/2022] [Accepted: 09/20/2022] [Indexed: 11/26/2022] Open
Abstract
Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other 'omics data, and mapping of effects from gene to brain to behavior across the lifespan.
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Alagöz G, Molz B, Eising E, Schijven D, Francks C, Stein JL, Fisher SE. Using neuroimaging genomics to investigate the evolution of human brain structure. Proc Natl Acad Sci U S A 2022; 119:e2200638119. [PMID: 36161899 PMCID: PMC9546597 DOI: 10.1073/pnas.2200638119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 08/15/2022] [Indexed: 01/16/2023] Open
Abstract
Alterations in brain size and organization represent some of the most distinctive changes in the emergence of our species. Yet, there is limited understanding of how genetic factors contributed to altered neuroanatomy during human evolution. Here, we analyze neuroimaging and genetic data from up to 30,000 people in the UK Biobank and integrate with genomic annotations for different aspects of human evolution, including those based on ancient DNA and comparative genomics. We show that previously reported signals of recent polygenic selection for cortical anatomy are not replicable in a more ancestrally homogeneous sample. We then investigate relationships between evolutionary annotations and common genetic variants shaping cortical surface area and white-matter connectivity for each hemisphere. Our analyses identify single-nucleotide polymorphism heritability enrichment in human-gained regulatory elements that are active in early brain development, affecting surface areas of several parts of the cortex, including left-hemispheric speech-associated regions. We also detect heritability depletion in genomic regions with Neanderthal ancestry for connectivity of the uncinate fasciculus; this is a white-matter tract involved in memory, language, and socioemotional processing with relevance to neuropsychiatric disorders. Finally, we show that common genetic loci associated with left-hemispheric pars triangularis surface area overlap with a human-gained enhancer and affect regulation of ZIC4, a gene implicated in neurogenesis. This work demonstrates how genomic investigations of present-day neuroanatomical variation can help shed light on the complexities of our evolutionary past.
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Affiliation(s)
- Gökberk Alagöz
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Barbara Molz
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Dick Schijven
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6500 HB Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, 6500 HB Nijmegen, The Netherlands
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Simon E. Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6500 HB Nijmegen, The Netherlands
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37
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Li Z, Li D, He Y, Wang K, Ma X, Chen X. Cross-Disorder Analysis of Shared Genetic Components Between Cortical Structures and Major Psychiatric Disorders. Schizophr Bull 2022; 48:1145-1154. [PMID: 35265999 PMCID: PMC9434450 DOI: 10.1093/schbul/sbac019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Although large-scale neuroimaging studies have demonstrated similar patterns of structural brain abnormalities across major psychiatric disorders, the underlying genetic etiology behind these similar cross-disorder patterns is not well understood. STUDY DESIGN We quantified the extent of shared genetic components between cortical structures and major psychiatric disorders (CS-MPD) by using genome-wide association study (GWAS) summary statistics of 70 cortical structures (surface area and thickness of the whole cortex and 34 cortical regions) and five major psychiatric disorders, consisting of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-disorder analyses were then conducted to estimate the degree of similarity in CS-MPD shared genetic components among these disorders. STUDY RESULTS The CS-MPD shared genetic components have medium-to-strong positive correlations in ADHD, BD, MDD, and SCZ (r = 0.415 to r = 0.806) while ASD was significantly correlated with ADHD, BD, and SCZ (r = 0.388 to r = 0.403). These pairwise correlations of CS-MPD shared genetic components among disorders were significantly associated with corresponding cross-disorder similarities in cortical structural abnormalities (r = 0.668), accounting for 44% variance. In addition, one latent shared factor consisted primarily of BD, MDD, and SCZ, explaining 62.47% of the total variance in CS-MPD shared genetic components of all disorders. CONCLUSIONS The current results bridge the gap between shared cross-disorder heritability and shared structural brain abnormalities in major psychiatric disorders, providing important implications for a shared genetic basis of cortical structures in these disorders.
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Affiliation(s)
- Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - David Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, PR China
| | - Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
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38
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Schizophrenia and Macroscale Brain Structure: Genes in Context. Biol Psychiatry 2022; 92:258-260. [PMID: 35902137 DOI: 10.1016/j.biopsych.2022.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 06/09/2022] [Indexed: 11/22/2022]
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39
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van der Meer D, Shadrin AA, O'Connell K, Bettella F, Djurovic S, Wolfers T, Alnæs D, Agartz I, Smeland OB, Melle I, Sánchez JM, Linden DEJ, Dale AM, Westlye LT, Andreassen OA, Frei O, Kaufmann T. Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology. Biol Psychiatry 2022; 92:291-298. [PMID: 35164939 DOI: 10.1016/j.biopsych.2021.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/06/2021] [Accepted: 12/09/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. METHODS We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. RESULTS We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. CONCLUSIONS Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue-specific genetic variants and its use in polygenic risk frameworks.
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Affiliation(s)
- Dennis van der Meer
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.
| | - Alexey A Shadrin
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin O'Connell
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Thomas Wolfers
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo Sánchez
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - David E J Linden
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
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Ahangari M, Everest E, Nguyen TH, Verrelli BC, Webb BT, Bacanu SA, Tahir Turanli E, Riley BP. Genome-wide analysis of schizophrenia and multiple sclerosis identifies shared genomic loci with mixed direction of effects. Brain Behav Immun 2022; 104:183-190. [PMID: 35714915 DOI: 10.1016/j.bbi.2022.06.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/09/2022] [Accepted: 06/13/2022] [Indexed: 11/18/2022] Open
Abstract
Common genetic variants identified in genome-wide association studies (GWAS) show varying degrees of genetic pleiotropy across complex human disorders. Clinical studies of schizophrenia (SCZ) suggest that in addition to neuropsychiatric symptoms, patients with SCZ also show variable immune dysregulation. Epidemiological studies of multiple sclerosis (MS), an autoimmune, neurodegenerative disorder of the central nervous system, suggest that in addition to the manifestation of neuroinflammatory complications, patients with MS may also show co-occurring neuropsychiatric symptoms with disease progression. In this study, we analyzed the largest available GWAS datasets for SCZ (N = 161,405) and MS (N = 41,505) using Gaussian causal mixture modeling (MiXeR) and conditional/conjunctional false discovery rate (condFDR) frameworks to explore and quantify the shared genetic architecture of these two complex disorders at common variant level. Despite detecting only a negligible genetic correlation (rG = 0.057), we observe polygenic overlap between SCZ and MS, and a substantial genetic enrichment in SCZ conditional on associations with MS, and vice versa. By leveraging this cross-disorder enrichment, we identified 36 loci jointly associated with SCZ and MS at conjunctional FDR < 0.05 with mixed direction of effects. Follow-up functional analysis of the shared loci implicates candidate genes and biological processes involved in immune response and B-cell receptor signaling pathways. In conclusion, this study demonstrates the presence of polygenic overlap between SCZ and MS in the absence of a genetic correlation and provides new insights into the shared genetic architecture of these two disorders at the common variant level.
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Affiliation(s)
- Mohammad Ahangari
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA, USA.
| | - Elif Everest
- Department of Molecular Biology and Genetics, Istanbul Technical University, Istanbul, Turkey
| | - Tan-Hoang Nguyen
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Brian C Verrelli
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Bradley T Webb
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Eda Tahir Turanli
- Faculty of Engineering and Natural Sciences, Department of Molecular Biology and Genetics, Acibadem University, Istanbul, Turkey
| | - Brien P Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
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41
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Characterizing the polygenic overlaps of bipolar disorder subtypes with schizophrenia and major depressive disorder. J Affect Disord 2022; 309:242-251. [PMID: 35487438 DOI: 10.1016/j.jad.2022.04.097] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 04/09/2022] [Accepted: 04/13/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Large-scale studies have shown that bipolar I disorder (BD-I) and bipolar II disorder (BD-II) have differences in genetic association with schizophrenia (SCZ) and major depressive disorder (MDD). However, the underlying shared genetic architectures between BD subtypes and both SCZ and MDD remain largely unknown. METHODS We applied univariate and bivariate causal mixture models (MiXeR) to estimate the polygenicity and polygenic overlaps on large GWASs summary statistics of BD-I (n = 25,060), BD-II (n = 6781), SCZ (n = 69,369) and MDD (n = 170,756). Then, conjunctional false discovery rate approach was used to identify specific shared genetic loci between BD subtypes and both SCZ and MDD. RESULTS Univariate MiXeR revealed that BD-II was substantially more polygenic (22.37 K causal variants) as compared to BD-I, SCZ and MDD (7.87-12.43 K causal variants). Bivariate MiXeR revealed substantial polygenic overlaps between BD-I and SCZ (Dice-coefficient = 0.83) and between BD-I and MDD (Dice-coefficient = 0.76), which are beyond the genetic correlation (rg = 0.71 and 0.36). Conjunctional FDR analysis identified 236 distinct shared loci between BD-I and BD-II (2 loci), BD-I and SCZ (227 loci), BD-I and MDD (19 loci), BD-II and SCZ (1 locus), and BD-II and MDD (3 loci). Most of these shared loci have concordant effect directions among BD subtypes, SCZ and MDD. LIMITATIONS The bivariate MiXeR model was not applied for the BD-II because of insufficient power and inadequate model fit. CONCLUSIONS These findings provide evidence for extensive polygenic effects across BD subtypes, SCZ and MDD, which further our understanding of the potential genetic basis for the comorbid symptoms across these disorders.
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Cheon EJ, Bearden CE, Sun D, Ching CRK, Andreassen OA, Schmaal L, Veltman DJ, Thomopoulos SI, Kochunov P, Jahanshad N, Thompson PM, Turner JA, van Erp TG. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings. Psychiatry Clin Neurosci 2022; 76:140-161. [PMID: 35119167 PMCID: PMC9098675 DOI: 10.1111/pcn.13337] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/29/2021] [Accepted: 01/21/2022] [Indexed: 12/25/2022]
Abstract
This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.
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Affiliation(s)
- Eun-Jin Cheon
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Department of Psychiatry, Yeungnam University College of Medicine, Yeungnam University Medical Center, Daegu, Republic of Korea
| | - Carrie E. Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Daqiang Sun
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, Parkville, Australia
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlant, GA, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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Zheng C, Liu S, Zhang X, Hu Y, Shang X, Zhu Z, Huang Y, Wu G, Xiao Y, Du Z, Liang Y, Chen D, Zang S, Hu Y, He M, Zhang X, Yu H. Shared genetic architecture between the two neurodegenerative diseases: Alzheimer's disease and glaucoma. Front Aging Neurosci 2022; 14:880576. [PMID: 36118709 PMCID: PMC9476600 DOI: 10.3389/fnagi.2022.880576] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 07/13/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Considered as the representatives of neurodegenerative diseases, Alzheimer's disease (AD) and glaucoma are complex progressive neuropathies affected by both genetic and environmental risk factors and cause irreversible damages. Current research indicates that there are common features between AD and glaucoma in terms of epidemiology and pathophysiology. However, the understandings and explanations of their comorbidity and potential genetic overlaps are still limited and insufficient. METHOD Genetic pleiotropy analysis was performed using large genome-wide association studies summary statistics of AD and glaucoma, with an independent cohort of glaucoma for replication. Conditional and conjunctional false discovery rate methods were applied to identify the shared loci. Biological function and network analysis, as well as the expression level analysis were performed to investigate the significance of the shared genes. RESULTS A significant positive genetic correlation between AD and glaucoma was identified, indicating that there were significant polygenetic overlaps. Forty-nine shared loci were identified and mapped to 11 shared protein-coding genes. Functional genomic analyses of the shared genes indicate their modulation of critical physiological processes in human cells, including those occurring in the mitochondria, nucleus, and cellular membranes. Most of the shared genes indicated a potential modulation of metabolic processes in human cells and tissues. Furthermore, human protein-protein interaction network analyses revealed that some of the shared genes, especially MTCH2, NDUFS3, and PTPMT1, as well as SPI1 and MYBPC3, may function concordantly. The modulation of their expressions may be related to metabolic dysfunction and pathogenic processes. CONCLUSION Our study identified a shared genetic architecture between AD and glaucoma, which may explain their shared features in epidemiology and pathophysiology. The potential involvement of these shared genes in molecular and cellular processes reflects the "inter-organ crosstalk" between AD and glaucoma. These results may serve as a genetic basis for the development of innovative and effective therapeutics for AD, glaucoma, and other neurodegenerative diseases.
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Affiliation(s)
- Chunwen Zheng
- Shantou University Medical College, Shantou, China
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Shunming Liu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yunyan Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhuoting Zhu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Guanrong Wu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Xiao
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zijing Du
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yingying Liang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Daiyu Chen
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Siwen Zang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Medical Research Center, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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Năstase MG, Vlaicu I, Trifu SC, Trifu SC. Genetic polymorphism and neuroanatomical changes in schizophrenia. ROMANIAN JOURNAL OF MORPHOLOGY AND EMBRYOLOGY = REVUE ROUMAINE DE MORPHOLOGIE ET EMBRYOLOGIE 2022; 63:307-322. [PMID: 36374137 PMCID: PMC9801677 DOI: 10.47162/rjme.63.2.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The article is a review of the latest meta-analyses regarding the genetic spectrum in schizophrenia, discussing the risks given by the disrupted-in-schizophrenia 1 (DISC1), catechol-O-methyltransferase (COMT), monoamine oxidases-A∕B (MAO-A∕B), glutamic acid decarboxylase 67 (GAD67) and neuregulin 1 (NRG1) genes, and dysbindin-1 protein. The DISC1 polymorphism significantly increases the risk of schizophrenia, as well injuries from the prefrontal cortex that affect connectivity. NRG1 is one of the most important proteins involved. Its polymorphism is associated with the reduction of areas in the corpus callosum, right uncinate, inferior lateral fronto-occipital fascicle, right external capsule, fornix, right optic tract, gyrus. NRG1 and the ErbB4 receptor (tyrosine kinase receptor) are closely related to the N-methyl-D-aspartate receptor (NMDAR) (glutamate receptor). COMT is located on chromosome 22 and together with interleukin-10 (IL-10) have an anti-inflammatory and immunosuppressive function that influences the dopaminergic system. MAO gene methylation has been associated with mental disorders. MAO-A is a risk gene in the onset of schizophrenia, more precisely a certain type of single-nucleotide polymorphism (SNP), at the gene level, is associated with schizophrenia. In schizophrenia, we find deficits of the γ-aminobutyric acid (GABA)ergic neurotransmitter, the dysfunctions being found predominantly at the level of the substantia nigra. In schizophrenia, missing an allele at GAD67, caused by a SNP, has been correlated with decreases in parvalbumin (PV), somatostatin receptor (SSR), and GAD ribonucleic acid (RNA). Resulting in the inability to mature PV and SSR neurons, which has been associated with hyperactivity.
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Affiliation(s)
- Mihai Gabriel Năstase
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania;
| | - Ilinca Vlaicu
- Department of Psychiatry, Hospital for Psychiatry, Săpunari, Călăraşi County, Romania
| | - Simona Corina Trifu
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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van der Meer D, Kaufmann T, Shadrin AA, Makowski C, Frei O, Roelfs D, Monereo-Sánchez J, Linden DEJ, Rokicki J, Alnæs D, de Leeuw C, Thompson WK, Loughnan R, Fan CC, Westlye LT, Andreassen OA, Dale AM. The genetic architecture of human cortical folding. SCIENCE ADVANCES 2021; 7:eabj9446. [PMID: 34910505 PMCID: PMC8673767 DOI: 10.1126/sciadv.abj9446] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 10/27/2021] [Indexed: 05/04/2023]
Abstract
The folding of the human cerebral cortex is a highly genetically regulated process that allows for a much larger surface area to fit into the cranial vault and optimizes functional organization. Sulcal depth is a robust yet understudied measure of localized folding, previously associated with multiple neurodevelopmental disorders. Here, we report the first genome-wide association study of sulcal depth. Through the multivariate omnibus statistical test (MOSTest) applied to vertex-wise measures from 33,748 U.K. Biobank participants (mean age, 64.3 years; 52.0% female), we identified 856 genome-wide significant loci (P < 5 × 10−8). Comparisons with cortical thickness and surface area indicated that sulcal depth has higher locus yield, heritability, and effective sample size. There was a large amount of genetic overlap between these traits, with gene-based analyses indicating strong associations with neurodevelopmental processes. Our findings demonstrate sulcal depth is a promising neuroimaging phenotype that may enhance our understanding of cortical morphology.
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Affiliation(s)
- Dennis van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Tobias Kaufmann
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Alexey A. Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Daniel Roelfs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo-Sánchez
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - David E. J. Linden
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Jaroslav Rokicki
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Bjørknes College, Oslo, Norway
| | - Christiaan de Leeuw
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Wesley K. Thompson
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California at San Diego, La Jolla, CA 92037, USA
| | - Robert Loughnan
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
| | - Chun Chieh Fan
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
| | - Lars T. Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Anders M. Dale
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
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