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Hedges DW, Chase M, Farrer TJ, Gale SD. Psychiatric Disease as a Potential Risk Factor for Dementia: A Narrative Review. Brain Sci 2024; 14:722. [PMID: 39061462 PMCID: PMC11274614 DOI: 10.3390/brainsci14070722] [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: 06/24/2024] [Revised: 07/10/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024] Open
Abstract
Neurodegenerative disease is a major global health problem with 150 million people predicted to have dementia by 2050. Genetic factors, environmental factors, demographics, and some diseases have been associated with dementia. In addition to associations between diseases such as hypertension and cerebrovascular disease and dementia, emerging findings associate some psychiatric disorders with incident dementia. Because of the high and increasing global prevalence of dementia and the high worldwide prevalence of psychiatric disorders, the primary objective of this narrative review was to evaluate published findings that evaluate the association between bipolar disorder, depression, anxiety, post-traumatic stress disorder, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, schizophrenia and other psychosis syndromes, and personality disorders and personality traits and incident dementia. Here, we highlight findings indicating possible associations between these psychiatric disorders and subsequent dementia and suggest that some psychiatric disorders may be risk factors for incident dementia. Further research, including more large longitudinal studies and additional meta-analyses, however, is needed to better characterize the associations between psychiatric disorders and incident dementia, to identify possible mechanisms for these putative associations, and to identify risk factors within psychiatric disorders that predispose some people with a psychiatric disorder but not others to subsequent dementia. Additional important questions concern how the treatment of psychiatric disorders might affect the risk of incident dementia.
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Affiliation(s)
- Dawson W. Hedges
- The Department of Psychology, Brigham Young University, Provo, UT 84602, USA;
- The Neuroscience Center, Brigham Young University, Provo, UT 84602, USA;
| | - Morgan Chase
- The Neuroscience Center, Brigham Young University, Provo, UT 84602, USA;
| | - Thomas J. Farrer
- Idaho WWAMI Medical Education Program, University of Idaho, Moscow, ID 83844, USA;
| | - Shawn D. Gale
- The Department of Psychology, Brigham Young University, Provo, UT 84602, USA;
- The Neuroscience Center, Brigham Young University, Provo, UT 84602, USA;
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Misicka E, Huang Y, Loomis S, Sadhu N, Fisher E, Gafson A, Runz H, Tsai E, Jia X, Herman A, Bronson PG, Bhangale T, Briggs FB. Adaptive and Innate Immunity Are Key Drivers of Age at Onset of Multiple Sclerosis. Neurol Genet 2024; 10:e200159. [PMID: 38817245 PMCID: PMC11139017 DOI: 10.1212/nxg.0000000000200159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 04/16/2024] [Indexed: 06/01/2024]
Abstract
Background and Objectives Multiple sclerosis (MS) age at onset (AAO) is a clinical predictor of long-term disease outcomes, independent of disease duration. Little is known about the genetic and biological mechanisms underlying age of first symptoms. We conducted a genome-wide association study (GWAS) to investigate associations between individual genetic variation and the MS AAO phenotype. Methods The study population was comprised participants with MS in 6 clinical trials: ADVANCE (N = 655; relapsing-remitting [RR] MS), ASCEND (N = 555; secondary-progressive [SP] MS), DECIDE (N = 1,017; RRMS), OPERA1 (N = 581; RRMS), OPERA2 (N = 577; RRMS), and ORATORIO (N = 529; primary-progressive [PP] MS). Altogether, 3,905 persons with MS of European ancestry were analyzed. GWAS were conducted for MS AAO in each trial using linear additive models controlling for sex and 10 principal components. Resultant summary statistics across the 6 trials were then meta-analyzed, for a total of 8.3 × 10-6 single nucleotide polymorphisms (SNPs) across all trials after quality control and filtering for heterogeneity. Gene-based tests of associations, pathway enrichment analyses, and Mendelian randomization analyses for select exposures were also performed. Results Four lead SNPs within 2 loci were identified (p < 5 × 10-8), including a) 3 SNPs in the major histocompatibility complex and their effects were independent of HLA-DRB1*15:01 and b) a LOC105375167 variant on chromosome 7. At the gene level, the top association was HLA-C (p = 1.2 × 10-7), which plays an important role in antiviral immunity. Functional annotation revealed the enrichment of pathways related to T-cell receptor signaling, autoimmunity, and the complement cascade. Mendelian randomization analyses suggested a link between both earlier age at puberty and shorter telomere length and earlier AAO, while there was no evidence for a role for either body mass index or vitamin D levels. Discussion Two genetic loci associated with MS AAO were identified, and functional annotation demonstrated an enrichment of genes involved in adaptive and complement immunity. There was also evidence supporting a link with age at puberty and telomere length. The findings suggest that AAO in MS is multifactorial, and the factors driving onset of symptoms overlap with those influencing MS risk.
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Affiliation(s)
- Elina Misicka
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Yunfeng Huang
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Stephanie Loomis
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Nilanjana Sadhu
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Elizabeth Fisher
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Arie Gafson
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Heiko Runz
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Ellen Tsai
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Xiaoming Jia
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Ann Herman
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Paola G Bronson
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Tushar Bhangale
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
| | - Farren B Briggs
- From the Department of Population and Quantitative Health Sciences (E.M.), Case Western Reserve University, Cleveland, OH; Biogen (Y.H., S.L., N.S., E.F., A.G., H.R., E.T., P.G.B.), Cambridge, MA; Human Genetics and Bioinformatics (X.J., A.H., T.B.), Genentech, San Francisco, CA; and Department of Public Health Sciences (F.B.B.), University of Miami, FL
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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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4
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Pisanu C, Congiu D, Meloni A, Paribello P, Patrinos GP, Severino G, Ardau R, Chillotti C, Manchia M, Squassina A. Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets. Neuropsychopharmacology 2024; 49:1033-1041. [PMID: 38402365 PMCID: PMC11039620 DOI: 10.1038/s41386-024-01822-5] [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: 11/22/2023] [Revised: 01/17/2024] [Accepted: 02/04/2024] [Indexed: 02/26/2024]
Abstract
Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.
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Affiliation(s)
- Claudia Pisanu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
| | - Donatella Congiu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Anna Meloni
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Pasquale Paribello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, School of Health Sciences, Department of Pharmacy, University of Patras, Patras, Greece
- College of Medicine and Health Sciences, Department of Genetics and Genomics, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
- Zayed Center for Health Sciences, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
| | - Giovanni Severino
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, NS, Canada
| | - Alessio Squassina
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
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5
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Patel K, Xie Z, Yuan H, Islam SMS, Xie Y, He W, Zhang W, Gottlieb A, Chen H, Giancardo L, Knaack A, Fletcher E, Fornage M, Ji S, Zhi D. Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging. Commun Biol 2024; 7:414. [PMID: 38580839 PMCID: PMC10997628 DOI: 10.1038/s42003-024-06096-7] [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: 01/31/2024] [Accepted: 03/22/2024] [Indexed: 04/07/2024] Open
Abstract
Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.
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Affiliation(s)
- Khush Patel
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Ziqian Xie
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Hao Yuan
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, 77843, USA
| | | | - Yaochen Xie
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Wei He
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Wanheng Zhang
- School of Public Health, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Assaf Gottlieb
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Han Chen
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
- School of Public Health, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Luca Giancardo
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Alexander Knaack
- Department of Neurology and Imaging of Dementia and Aging (IDeA) Laboratory, University of California at Davis, Davis, CA, 95618, USA
| | - Evan Fletcher
- Department of Neurology and Imaging of Dementia and Aging (IDeA) Laboratory, University of California at Davis, Davis, CA, 95618, USA
| | - Myriam Fornage
- School of Public Health, University of Texas Health Science Center, Houston, TX, 77030, USA
- McGovern Medical School, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Shuiwang Ji
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Degui Zhi
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA.
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6
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Chacar S, Abdi A, Almansoori K, Alshamsi J, Al Hageh C, Zalloua P, Khraibi AA, Holt SG, Nader M. Role of CaMKII in diabetes induced vascular injury and its interaction with anti-diabetes therapy. Rev Endocr Metab Disord 2024; 25:369-382. [PMID: 38064002 PMCID: PMC10943158 DOI: 10.1007/s11154-023-09855-9] [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] [Accepted: 11/16/2023] [Indexed: 03/16/2024]
Abstract
Diabetes mellitus is a metabolic disorder denoted by chronic hyperglycemia that drives maladaptive structural changes and functional damage to the vasculature. Attenuation of this pathological remodeling of blood vessels remains an unmet target owing to paucity of information on the metabolic signatures of this process. Ca2+/calmodulin-dependent kinase II (CaMKII) is expressed in the vasculature and is implicated in the control of blood vessels homeostasis. Recently, CaMKII has attracted a special attention in view of its chronic upregulated activity in diabetic tissues, yet its role in the diabetic vasculature remains under investigation.This review highlights the physiological and pathological actions of CaMKII in the diabetic vasculature, with focus on the control of the dialogue between endothelial (EC) and vascular smooth muscle cells (VSMC). Activation of CaMKII enhances EC and VSMC proliferation and migration, and increases the production of extracellular matrix which leads to maladaptive remodeling of vessels. This is manifested by activation of genes/proteins implicated in the control of the cell cycle, cytoskeleton organization, proliferation, migration, and inflammation. Endothelial dysfunction is paralleled by impaired nitric oxide signaling, which is also influenced by CaMKII signaling (activation/oxidation). The efficiency of CaMKII inhibitors is currently being tested in animal models, with a focus on the genetic pathways involved in the regulation of CaMKII expression (microRNAs and single nucleotide polymorphisms). Interestingly, studies highlight an interaction between the anti-diabetic drugs and CaMKII expression/activity which requires further investigation. Together, the studies reviewed herein may guide pharmacological approaches to improve health-related outcomes in patients with diabetes.
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Affiliation(s)
- Stephanie Chacar
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
- Center for Biotechnology, Khalifa University of Science and Technology, 127788, Abu Dhabi, United Arab Emirates.
| | - Abdulhamid Abdi
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Khalifa Almansoori
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Jawaher Alshamsi
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Cynthia Al Hageh
- Department of Molecular Biology and Genetics, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Pierre Zalloua
- Department of Molecular Biology and Genetics, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Center for Biotechnology, Khalifa University of Science and Technology, 127788, Abu Dhabi, United Arab Emirates
| | - Ali A Khraibi
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Center for Biotechnology, Khalifa University of Science and Technology, 127788, Abu Dhabi, United Arab Emirates
| | - Stephen G Holt
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- SEHA Kidney Care, SEHA, Abu Dhabi, UAE
| | - Moni Nader
- Department of Physiology and Immunology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
- Center for Biotechnology, Khalifa University of Science and Technology, 127788, Abu Dhabi, United Arab Emirates.
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7
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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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8
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Karunakaran KB, Jain S, Brahmachari SK, Balakrishnan N, Ganapathiraju MK. Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:26. [PMID: 38413605 PMCID: PMC10899210 DOI: 10.1038/s41537-024-00439-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 01/24/2024] [Indexed: 02/29/2024]
Abstract
Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.
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Affiliation(s)
- Kalyani B Karunakaran
- Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, India.
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan.
| | - Sanjeev Jain
- National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, India.
| | | | - N Balakrishnan
- Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, India
| | - Madhavi K Ganapathiraju
- Department of Computer Science, Carnegie Mellon University Qatar, Doha, Qatar.
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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9
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Ma Y, Bendl J, Hartley BJ, Fullard JF, Abdelaal R, Ho SM, Kosoy R, Gochman P, Rapoport J, Hoffman GE, Brennand KJ, Roussos P. Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders. Biol Psychiatry 2024; 95:187-198. [PMID: 37454787 PMCID: PMC10787819 DOI: 10.1016/j.biopsych.2023.07.003] [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: 10/12/2022] [Revised: 06/07/2023] [Accepted: 07/09/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Converging evidence from large-scale genetic and postmortem studies highlights the role of aberrant neurotransmission and genetic regulation in brain-related disorders. However, identifying neuronal activity-regulated transcriptional programs in the human brain and understanding how changes contribute to disease remain challenging. METHODS To better understand how the activity-dependent regulome contributes to risk for brain-related disorders, we profiled the transcriptomic and epigenomic changes following neuronal depolarization in human induced pluripotent stem cell-derived glutamatergic neurons (NGN2) from 6 patients with schizophrenia and 5 control participants. RESULTS Multiomic data integration associated global patterns of chromatin accessibility with gene expression and identified enhancer-promoter interactions in glutamatergic neurons. Within 1 hour of potassium chloride-induced depolarization, independent of diagnosis, glutamatergic neurons displayed substantial activity-dependent changes in the expression of genes regulating synaptic function. Depolarization-induced changes in the regulome revealed significant heritability enrichment for schizophrenia and Parkinson's disease, adding to mounting evidence that sequence variation within activation-dependent regulatory elements contributes to the genetic risk for brain-related disorders. Gene coexpression network analysis elucidated interactions among activity-dependent and disease-associated genes and pointed to a key driver (NAV3) that interacted with multiple genes involved in axon guidance. CONCLUSIONS Overall, we demonstrated that deciphering the activity-dependent regulome in glutamatergic neurons reveals novel targets for advanced diagnosis and therapy.
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Affiliation(s)
- Yixuan Ma
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Brigham J Hartley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Black Family Stem Cell Institute, New York, New York
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Rawan Abdelaal
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Black Family Stem Cell Institute, New York, New York
| | - Seok-Man Ho
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Black Family Stem Cell Institute, New York, New York
| | - Roman Kosoy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Peter Gochman
- Childhood Psychiatry Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Judith Rapoport
- Childhood Psychiatry Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Kristen J Brennand
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Black Family Stem Cell Institute, New York, New York.
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York; Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, New York; Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York.
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10
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Clarin JD, Reddy N, Alexandropoulos C, Gao WJ. The role of cell adhesion molecule IgSF9b at the inhibitory synapse and psychiatric disease. Neurosci Biobehav Rev 2024; 156:105476. [PMID: 38029609 PMCID: PMC10842117 DOI: 10.1016/j.neubiorev.2023.105476] [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: 09/06/2023] [Revised: 11/15/2023] [Accepted: 11/18/2023] [Indexed: 12/01/2023]
Abstract
Understanding perturbations in synaptic function between health and disease states is crucial to the treatment of neuropsychiatric illness. While genome-wide association studies have identified several genetic loci implicated in synaptic dysfunction in disorders such as autism and schizophrenia, many have not been rigorously characterized. Here, we highlight immunoglobulin superfamily member 9b (IgSF9b), a cell adhesion molecule thought to localize exclusively to inhibitory synapses in the brain. While both pre-clinical and clinical studies suggest its association with psychiatric diseases, our understanding of IgSF9b in synaptic maintenance, neural circuits, and behavioral phenotypes remains rudimentary. Moreover, these functions wield undiscovered influences on neurodevelopment. This review evaluates current literature and publicly available gene expression databases to explore the implications of IgSF9b dysfunction in rodents and humans. Through a focused analysis of one high-risk gene locus, we identify areas requiring further investigation and unearth clues related to broader mechanisms contributing to the synaptic etiology of psychiatric disorders.
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Affiliation(s)
- Jacob D Clarin
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, United States
| | - Natasha Reddy
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, United States
| | - Cassandra Alexandropoulos
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, United States
| | - Wen-Jun Gao
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, United States.
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11
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Kim JJ, Vitale D, Otani DV, Lian MM, Heilbron K, Iwaki H, Lake J, Solsberg CW, Leonard H, Makarious MB, Tan EK, Singleton AB, Bandres-Ciga S, Noyce AJ, Blauwendraat C, Nalls MA, Foo JN, Mata I. Multi-ancestry genome-wide association meta-analysis of Parkinson's disease. Nat Genet 2024; 56:27-36. [PMID: 38155330 PMCID: PMC10786718 DOI: 10.1038/s41588-023-01584-8] [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: 08/26/2022] [Accepted: 10/20/2023] [Indexed: 12/30/2023]
Abstract
Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations.
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Affiliation(s)
- Jonggeol Jeffrey Kim
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Preventive Neurology Unit, Centre for Prevention Diagnosis and Detection, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
| | - Dan Vitale
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Diego Véliz Otani
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Institute for Genome Sciences, University of Maryland, Baltimore, MD, USA
| | - Michelle Mulan Lian
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, A*STAR, Singapore, Singapore
| | | | - Hirotaka Iwaki
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Caroline Warly Solsberg
- Pharmaceutical Sciences and Pharmacogenomics, UCSF, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, UCSF, San Francisco, CA, USA
| | - Hampton Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Eng-King Tan
- Department of Neurology, National Neuroscience Institute, Duke NUS Medical School, Singapore, Singapore
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Alastair J Noyce
- Preventive Neurology Unit, Centre for Prevention Diagnosis and Detection, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Data Tecnica International, Washington, DC, USA.
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
| | - Jia Nee Foo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.
- Genome Institute of Singapore, Agency for Science, Technology and Research, A*STAR, Singapore, Singapore.
| | - Ignacio Mata
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
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12
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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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13
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Subramaniyan S, Kuriakose BB, Mushfiq S, Prabhu NM, Muthusamy K. Gene Signals and SNPs Associated with Parkinson's Disease: A Nutrigenomics and Computational Prospective Insights. Neuroscience 2023; 533:77-95. [PMID: 37858629 DOI: 10.1016/j.neuroscience.2023.10.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/05/2023] [Accepted: 10/11/2023] [Indexed: 10/21/2023]
Abstract
Parkinson's disease is the most prevalent chronic neurodegenerative disease. Neurological conditions for PD were influenced by a variety of epigenetic factors and SNPs in some of the coexisting genes that were expressed. This article focused on nutrigenomics of PD and the prospective highlighting of how these genes are regulated in terms of nutritive factors and the genetic basis of PD risk, onset, and progression. Multigenetic associations of the following genetic alterations in the genes of SNCA, LRRK2, UCHL1, PARK2,PINK1, DJ-1, and ATP13A2 have been reported with the familial and de novo genetic origins of PD. Over the past two decades, significant attempts have been made to understand the biological mechanisms that are potential causes for this disease, as well as to identify therapeutic substances for the prevention and management of PD. Nutrigenomics has sparked considerable interest due to its nutritional, safe, and therapeutic effects on a variety of chronic diseases. In this study, we summarise some of the nutritive supplements that have an impact on PD.
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Affiliation(s)
- Swetha Subramaniyan
- Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Beena Briget Kuriakose
- Department of Basic Medical Sciences, College of Applied Medical Sciences, King Khalid University, Khamis Mushayt, Saudi Arabia
| | - Sakeena Mushfiq
- Department of Public Health, College of Applied Medical Sciences, King Khalid University, Khamis Mushayt, Saudi Arabia
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14
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Dahimene S, Page KM, Nieto-Rostro M, Pratt WS, Dolphin AC. The Interplay Between Splicing of Two Exon Combinations Differentially Affects Membrane Targeting and Function of Human Ca V2.2. FUNCTION 2023; 5:zqad060. [PMID: 38020068 PMCID: PMC10666670 DOI: 10.1093/function/zqad060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/16/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
N-type calcium channels (CaV2.2) are predominantly localized in presynaptic terminals, and are particularly important for pain transmission in the spinal cord. Furthermore, they have multiple isoforms, conferred by alternatively spliced or cassette exons, which are differentially expressed. Here, we have examined alternatively spliced exon47 variants that encode a long or short C-terminus in human CaV2.2. In the Ensembl database, all short exon47-containing transcripts were associated with the absence of exon18a, therefore, we also examined the effect of inclusion or absence of exon18a, combinatorially with the exon47 splice variants. We found that long exon47, only in the additional presence of exon18a, results in CaV2.2 currents that have a 3.6-fold greater maximum conductance than the other three combinations. In contrast, cell-surface expression of CaV2.2 in both tsA-201 cells and hippocampal neurons is increased ∼4-fold by long exon47, relative to short exon47, in either the presence or the absence of exon18a. This surprising discrepancy between trafficking and function indicates that cell-surface expression is enhanced by long exon47, independently of exon18a. However, in the presence of long exon47, exon18a mediates an additional permissive effect on CaV2.2 gating. We also investigated the single-nucleotide polymorphism in exon47 that has been linked to schizophrenia and Parkinson's disease, which we found is only non-synonymous in the short exon47 C-terminal isoform, resulting in two minor alleles. This study highlights the importance of investigating the combinatorial effects of exon inclusion, rather than each in isolation, in order to increase our understanding of calcium channel function.
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Affiliation(s)
- Shehrazade Dahimene
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Karen M Page
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Manuela Nieto-Rostro
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Wendy S Pratt
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
| | - Annette C Dolphin
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK
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15
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Morey R, Zheng Y, Sun D, Garrett M, Gasperi M, Maihofer A, Baird CL, Grasby K, Huggins A, Haswell C, Thompson P, Medland S, Gustavson D, Panizzon M, Kremen W, Nievergelt C, Ashley-Koch A, Logue L. Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture. RESEARCH SQUARE 2023:rs.3.rs-3253035. [PMID: 37886496 PMCID: PMC10602057 DOI: 10.21203/rs.3.rs-3253035/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Paul Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, California, USA
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16
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Smeland OB, Kutrolli G, Bahrami S, Fominykh V, Parker N, Hindley GFL, Rødevand L, Jaholkowski P, Tesfaye M, Parekh P, Elvsåshagen T, Grotzinger AD, Steen NE, van der Meer D, O’Connell KS, Djurovic S, Dale AM, Shadrin AA, Frei O, Andreassen OA. The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.21.23292993. [PMID: 37503175 PMCID: PMC10371109 DOI: 10.1101/2023.07.21.23292993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.
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Affiliation(s)
- Olav B. Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gleda Kutrolli
- 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
| | - Vera Fominykh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadine Parker
- 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, United Kingdom
| | - Linn Rødevand
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Piotr Jaholkowski
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Markos Tesfaye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torbjørn Elvsåshagen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Andrew D. Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | | | | | - Nils Eiel Steen
- 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, The Netherlands
| | - Kevin S. O’Connell
- 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, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, USA
- Department of Neurosciences, University of California San Diego, La Jolla, USA
- Department of Radiology, University of California, San Diego, La Jolla, USA
| | - 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
| | - 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
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
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Zhong Q, Xiao X, Qiu Y, Xu Z, Chen C, Chong B, Zhao X, Hai S, Li S, An Z, Dai L. Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications. MedComm (Beijing) 2023; 4:e261. [PMID: 37143582 PMCID: PMC10152985 DOI: 10.1002/mco2.261] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 05/06/2023] Open
Abstract
Protein posttranslational modifications (PTMs) refer to the breaking or generation of covalent bonds on the backbones or amino acid side chains of proteins and expand the diversity of proteins, which provides the basis for the emergence of organismal complexity. To date, more than 650 types of protein modifications, such as the most well-known phosphorylation, ubiquitination, glycosylation, methylation, SUMOylation, short-chain and long-chain acylation modifications, redox modifications, and irreversible modifications, have been described, and the inventory is still increasing. By changing the protein conformation, localization, activity, stability, charges, and interactions with other biomolecules, PTMs ultimately alter the phenotypes and biological processes of cells. The homeostasis of protein modifications is important to human health. Abnormal PTMs may cause changes in protein properties and loss of protein functions, which are closely related to the occurrence and development of various diseases. In this review, we systematically introduce the characteristics, regulatory mechanisms, and functions of various PTMs in health and diseases. In addition, the therapeutic prospects in various diseases by targeting PTMs and associated regulatory enzymes are also summarized. This work will deepen the understanding of protein modifications in health and diseases and promote the discovery of diagnostic and prognostic markers and drug targets for diseases.
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Affiliation(s)
- Qian Zhong
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Xina Xiao
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Yijie Qiu
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Zhiqiang Xu
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Chunyu Chen
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Baochen Chong
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Xinjun Zhao
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Shan Hai
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Shuangqing Li
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Zhenmei An
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
| | - Lunzhi Dai
- Department of Endocrinology and MetabolismGeneral Practice Ward/International Medical Center WardGeneral Practice Medical Center and National Clinical Research Center for GeriatricsState Key Laboratory of BiotherapyWest China Hospital, Sichuan UniversityChengduChina
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Reynolds RH, Wagen AZ, Lona-Durazo F, Scholz SW, Shoai M, Hardy J, Gagliano Taliun SA, Ryten M. Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases. NPJ Parkinsons Dis 2023; 9:70. [PMID: 37117178 PMCID: PMC10147945 DOI: 10.1038/s41531-023-00504-1] [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] [Received: 03/16/2023] [Accepted: 03/27/2023] [Indexed: 04/30/2023] Open
Abstract
Genetic correlation ([Formula: see text]) between traits can offer valuable insight into underlying shared biological mechanisms. Neurodegenerative diseases overlap neuropathologically and often manifest comorbid neuropsychiatric symptoms. However, global [Formula: see text] analyses show minimal [Formula: see text] among neurodegenerative and neuropsychiatric diseases. Importantly, local [Formula: see text] s can exist in the absence of global relationships. To investigate this possibility, we applied LAVA, a tool for local [Formula: see text] analysis, to genome-wide association studies of 3 neurodegenerative diseases (Alzheimer's disease, Lewy body dementia and Parkinson's disease) and 3 neuropsychiatric disorders (bipolar disorder, major depressive disorder and schizophrenia). We identified several local [Formula: see text] s missed in global analyses, including between (i) all 3 neurodegenerative diseases and schizophrenia and (ii) Alzheimer's and Parkinson's disease. For those local [Formula: see text] s identified in genomic regions containing disease-implicated genes, such as SNCA, CLU and APOE, incorporation of expression quantitative trait loci identified genes that may drive genetic overlaps between diseases. Collectively, we demonstrate that complex genetic relationships exist among neurodegenerative and neuropsychiatric diseases, highlighting putative pleiotropic genomic regions and genes. These findings imply sharing of pathogenic processes and the potential existence of common therapeutic targets.
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Affiliation(s)
- Regina H Reynolds
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
| | - Aaron Z Wagen
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, London, UK
- Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK
| | - Frida Lona-Durazo
- Montréal Heart Institute, Montréal, QC, Canada
- Faculty of Medicine, Université de Montréal, Montréal, Canada
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Maryam Shoai
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Neurodegenerative Diseases, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - John Hardy
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Neurodegenerative Diseases, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Sarah A Gagliano Taliun
- Montréal Heart Institute, Montréal, QC, Canada
- Department of Medicine & Department of Neurosciences, Université de Montréal, Montréal, QC, Canada
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK.
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Alemany-Navarro M, Tubío-Fungueiriño M, Diz-de Almeida S, Cruz R, Lombroso A, Real E, Soria V, Bertolín S, Fernández-Prieto M, Alonso P, Menchón JM, Carracedo A, Segalàs C. The genomics of visuospatial neurocognition in obsessive-compulsive disorder: A preliminary GWAS. J Affect Disord 2023; 333:365-376. [PMID: 37094658 DOI: 10.1016/j.jad.2023.04.060] [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: 01/31/2023] [Revised: 04/04/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND The study of Obsessive-Compulsive Disorder (OCD) genomics has primarily been tackled by Genome-wide association studies (GWAS), which have encountered troubles in identifying replicable single nucleotide polymorphisms (SNPs). Endophenotypes have emerged as a promising avenue of study in trying to elucidate the genomic bases of complex traits such as OCD. METHODS We analyzed the association of SNPs across the whole genome with the construction of visuospatial information and executive performance through four neurocognitive variables assessed by the Rey-Osterrieth Complex Figure Test (ROCFT) in a sample of 133 OCD probands. Analyses were performed at SNP- and gene-level. RESULTS No SNP reached genome-wide significance, although there was one SNP almost reaching significant association with copy organization (rs60360940; P = 9.98E-08). Suggestive signals were found for the four variables at both SNP- (P < 1E-05) and gene-levels (P < 1E-04). Most of the suggestive signals pointed to genes and genomic regions previously associated with neurological function and neuropsychological traits. LIMITATIONS Our main limitations were the sample size, which was limited to identify associated signals at a genome-wide level, and the composition of the sample, more representative of rather severe OCD cases than a population-based OCD sample with a broad severity spectrum. CONCLUSIONS Our results suggest that studying neurocognitive variables in GWAS would be more informative on the genetic basis of OCD than the classical case/control GWAS, facilitating the genetic characterization of OCD and its different clinical profiles, the development of individualized treatment approaches, and the improvement of prognosis and treatment response.
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Affiliation(s)
- M Alemany-Navarro
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; IBIS (Universidad de Sevilla, HUVR, Junta de Andalucia, CSIC) Sevilla, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain.
| | - M Tubío-Fungueiriño
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - S Diz-de Almeida
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - R Cruz
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - A Lombroso
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - E Real
- Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - V Soria
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - S Bertolín
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - M Fernández-Prieto
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - P Alonso
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - J M Menchón
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Servicio Galego de Saúde (SERGAS), Santiago de Compostela, Spain
| | - C Segalàs
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
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Schrag A, Bohlken J, Dammertz L, Teipel S, Hermann W, Akmatov MK, Bätzing J, Holstiege J. Widening the Spectrum of Risk Factors, Comorbidities, and Prodromal Features of Parkinson Disease. JAMA Neurol 2023; 80:161-171. [PMID: 36342675 PMCID: PMC9641600 DOI: 10.1001/jamaneurol.2022.3902] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Importance The prodromal phase of Parkinson disease (PD) may last for more than 10 years. Recognition of the spectrum and occurrence of risk factors, comorbidities, and prodromal features of PD can increase understanding of the causes and development of the disease and help identify individuals at risk. Objective To identify the association of a subsequent diagnosis of PD with a range of risk factors and prodromal features, including lifestyle factors, comorbidities, and potential extracerebral manifestations of PD. Design, Setting, and Participants This was a case-control study using insurance claims of outpatient consultations of patients with German statutory health insurance between January 1, 2011, and December 31, 2020. Included were patients with incident diagnosis of PD without a previous diagnosis of parkinsonism or dementia and controls matched 1:2 for age, sex, region, and earliest year of outpatient encounter. Exposures Exposures were selected based on previous systematic reviews, case-control and cohort studies reporting on risk factors, comorbidities, and prodromal features of PD. Main Outcomes and Measures Previously postulated risk factors and prodromal features of PD, using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding. Results A total of 138 345 patients with incident PD (mean [SD] age, 75.1 [9.8] years; 73 720 male [53.3%]) and 276 690 matched controls (mean [SD] age, 75.1 (9.8) years; 147 440 male [53.3%]) were identified. Study participants were followed up for a mean (SD) of 6.0 (2.0) years. Consistent with previous reports, risk factors and prodromal features associated with PD included traumatic brain injury, odds ratio (OR), 1.62; 95% CI, 1.36-1.92; alcohol misuse, OR, 1.32; 95% CI, 1.21-1.44; hypertension, OR, 1.29; 95% CI, 1.26-1.31; anosmia, OR, 2.16; 95% CI, 1.59-2.93; and parasomnias (including RBD), OR, 1.62; 95% CI, 1.42-1.84. In addition, there were associations with restless legs syndrome (OR, 4.19; 95% CI, 3.91-4.50), sleep apnea (OR, 1.45; 95% CI, 1.37-1.54), epilepsy (OR, 2.26; 95% CI, 2.07-2.46), migraine (OR, 1.21; 95% CI, 1.12-1.29), bipolar disorder (OR, 3.81; 95% CI, 3.11-4.67), and schizophrenia (OR, 4.48; 95% CI, 3.82-5.25). The following diagnoses were also found to be associated with PD: sensory impairments beyond anosmia, such as hearing loss (OR, 1.14; 95% CI, 1.09-1.20) and changes of skin sensation (OR, 1.31; 95% CI, 1.21-1.43). There were also positive associations with skin disorders (eg, seborrheic dermatitis, OR, 1.30; 95% CI, 1.15-1.46; psoriasis, OR, 1.13; 95% CI, 1.05-1.21), gastrointestinal disorders (eg, gastroesophageal reflux, OR, 1.29; 95% CI, 1.25-1.33; gastritis, OR, 1.28; 95% CI, 1.24-1.33), conditions with a potential inflammatory component (eg, seronegative osteoarthritis, OR, 1.21; 95% CI, 1.03-1.43), and diabetes types 1 (OR, 1.32; 95% CI, 1.21-1.43) and 2 (OR, 1.24; 95% CI, 1.20-1.27). Associations even 5 to 10 years before diagnosis included tremor (odds ratio [OR], 4.49; 95% CI, 3.98-5.06), restless legs syndrome (OR, 3.73; 95% CI, 3.39-4.09), bipolar disorder (OR, 3.80; 95% CI, 2.82-5.14), and schizophrenia (OR, 4.00; 95% CI, 3.31-4.85). Conclusions and Relevance Results of this case-control study suggest that the associations found between PD and certain risk factors, comorbidities, and prodromal symptoms in a representative population may reflect possible early extrastriatal and extracerebral pathology of PD. This may be due to shared genetic risk with PD, medication exposure, or direct causation, or represent pathophysiologically relevant factors contributing to the pathogenesis of PD.
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Affiliation(s)
- Anette Schrag
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom
| | - Jens Bohlken
- Institut für Sozialmedizin, Arbeitsmedizin und Public Health der Medizinischen Fakultät der Universität Leipzig, Leipzig, Germany
| | - Lotte Dammertz
- Central Research Institute of Ambulatory Health Care in Germany, Department of Epidemiology and Healthcare Atlas, Berlin, Germany
| | - Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen Rostock/Greifswald, Rostock, Germany,Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
| | - Wiebke Hermann
- Department of Neurology, University of Rostock, Rostock, Germany
| | - Manas K. Akmatov
- Central Research Institute of Ambulatory Health Care in Germany, Department of Epidemiology and Healthcare Atlas, Berlin, Germany
| | - Jörg Bätzing
- Central Research Institute of Ambulatory Health Care in Germany, Department of Epidemiology and Healthcare Atlas, Berlin, Germany
| | - Jakob Holstiege
- Central Research Institute of Ambulatory Health Care in Germany, Department of Epidemiology and Healthcare Atlas, Berlin, Germany
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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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Parkinson's Disease, It Takes Guts: The Correlation between Intestinal Microbiome and Cytokine Network with Neurodegeneration. BIOLOGY 2023; 12:biology12010093. [PMID: 36671785 PMCID: PMC9856109 DOI: 10.3390/biology12010093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 01/11/2023]
Abstract
Parkinson's disease is a progressive neurodegenerative disorder with motor, physical and behavioral symptoms that can have a profound impact on the patient's quality of life. Most cases are idiopathic, and the exact mechanism of the disease's cause is unknown. The current hypothesis focuses on the gut-brain axis and states that gut microbiota dysbiosis can trigger inflammation and advances the development of Parkinson's disease. This systematic review presents the current knowledge of gut microbiota analysis and inflammation based on selected studies on Parkinson's patients and experimental animal models. Changes in gut microbiota correlate with Parkinson's disease, but only a few studies have considered inflammatory modulators as important triggers of the disease. Nevertheless, it is evident that proinflammatory cytokines and chemokines are induced in the gut, the circulation, and the brain before the development of the disease's neurological symptoms and exacerbate the disease. Increased levels of tumor necrosis factor, interleukin-1β, interleukin-6, interleukin-17A and interferon-γ can correlate with altered gut microbiota. Instead, treatment of gut dysbiosis is accompanied by reduced levels of inflammatory mediators in specific tissues, such as the colon, brain and serum and/or cerebrospinal fluid. Deciphering the role of the immune responses and the mechanisms of the PD-associated gut microbiota will assist the interpretation of the pathogenesis of Parkinson's and will elucidate appropriate therapeutic strategies.
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23
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Decreased Prosaposin and Progranulin in the Cingulate Cortex Are Associated with Schizophrenia Pathophysiology. Int J Mol Sci 2022; 23:ijms231912056. [PMID: 36233357 PMCID: PMC9570388 DOI: 10.3390/ijms231912056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/02/2022] [Accepted: 10/05/2022] [Indexed: 11/17/2022] Open
Abstract
Prosaposin (PSAP) and progranulin (PGRN) are two lysosomal proteins that interact and modulate the metabolism of lipids, particularly sphingolipids. Alterations in sphingolipid metabolism have been found in schizophrenia. Genetic associations of PSAP and PGRN with schizophrenia have been reported. To further clarify the role of PSAP and PGRN in schizophrenia, we examined PSAP and PGRN levels in postmortem cingulate cortex tissue from healthy controls along with patients who had suffered from schizophrenia, bipolar disorder, or major depressive disorder. We found that PSAP and PGRN levels are reduced specifically in schizophrenia patients. To understand the role of PSAP in the cingulate cortex, we used an AAV strategy to knock down PSAP in neurons located in this region. Neuronal PSAP knockdown led to the downregulation of neuronal PGRN levels and behavioral abnormalities. Cingulate-PSAP-deficient mice exhibited increased anxiety-like behavior and impaired prepulse inhibition, as well as intact locomotion, working memory, and a depression-like state. The behavioral changes were accompanied by increased early growth response protein 1 (EGR-1) and activity-dependent cytoskeleton-associated protein (ARC) levels in the sensorimotor cortex and hippocampus, regions implicated in circuitry dysfunction in schizophrenia. In conclusion, PSAP and PGRN downregulation in the cingulate cortex is associated with schizophrenia pathophysiology.
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24
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Development of a novel high-throughput screen for the identification of new inhibitors of protein S-acylation. J Biol Chem 2022; 298:102469. [PMID: 36087837 PMCID: PMC9558053 DOI: 10.1016/j.jbc.2022.102469] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/24/2022] [Accepted: 08/27/2022] [Indexed: 11/24/2022] Open
Abstract
Protein S-acylation is a reversible post-translational modification that modulates the localization and function of many cellular proteins. S-acylation is mediated by a family of zinc finger DHHC (Asp-His-His-Cys) domain–containing (zDHHC) proteins encoded by 23 distinct ZDHHC genes in the human genome. These enzymes catalyze S-acylation in a two-step process involving “autoacylation” of the cysteine residue in the catalytic DHHC motif followed by transfer of the acyl chain to a substrate cysteine. S-acylation is essential for many fundamental physiological processes, and there is growing interest in zDHHC enzymes as novel drug targets for a range of disorders. However, there is currently a lack of chemical modulators of S-acylation either for use as tool compounds or for potential development for therapeutic purposes. Here, we developed and implemented a novel FRET-based high-throughput assay for the discovery of compounds that interfere with autoacylation of zDHHC2, an enzyme that is implicated in neuronal S-acylation pathways. Our screen of >350,000 compounds identified two related tetrazole-containing compounds (TTZ-1 and TTZ-2) that inhibited both zDHHC2 autoacylation and substrate S-acylation in cell-free systems. These compounds were also active in human embryonic kidney 293T cells, where they inhibited the S-acylation of two substrates (SNAP25 and PSD95 [postsynaptic density protein 95]) mediated by different zDHHC enzymes, with some apparent isoform selectivity. Furthermore, we confirmed activity of the hit compounds through resynthesis, which provided sufficient quantities of material for further investigations. The assays developed provide novel strategies to screen for zDHHC inhibitors, and the identified compounds add to the chemical toolbox for interrogating cellular activities of zDHHC enzymes in S-acylation.
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25
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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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26
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Wingo TS, Liu Y, Gerasimov ES, Vattathil SM, Wynne ME, Liu J, Lori A, Faundez V, Bennett DA, Seyfried NT, Levey AI, Wingo AP. Shared mechanisms across the major psychiatric and neurodegenerative diseases. Nat Commun 2022; 13:4314. [PMID: 35882878 PMCID: PMC9325708 DOI: 10.1038/s41467-022-31873-5] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 07/07/2022] [Indexed: 12/14/2022] Open
Abstract
Several common psychiatric and neurodegenerative diseases share epidemiologic risk; however, whether they share pathophysiology is unclear and is the focus of our investigation. Using 25 GWAS results and LD score regression, we find eight significant genetic correlations between psychiatric and neurodegenerative diseases. We integrate the GWAS results with human brain transcriptomes (n = 888) and proteomes (n = 722) to identify cis- and trans- transcripts and proteins that are consistent with a pleiotropic or causal role in each disease, referred to as causal proteins for brevity. Within each disease group, we find many distinct and shared causal proteins. Remarkably, 30% (13 of 42) of the neurodegenerative disease causal proteins are shared with psychiatric disorders. Furthermore, we find 2.6-fold more protein-protein interactions among the psychiatric and neurodegenerative causal proteins than expected by chance. Together, our findings suggest these psychiatric and neurodegenerative diseases have shared genetic and molecular pathophysiology, which has important ramifications for early treatment and therapeutic development.
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Affiliation(s)
- Thomas S Wingo
- Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA.
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
| | - Yue Liu
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | - Selina M Vattathil
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Meghan E Wynne
- Department of Cell Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jiaqi Liu
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Adriana Lori
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
| | - Victor Faundez
- Department of Cell Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Aliza P Wingo
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA.
- Veterans Affairs Atlanta Health Care System, Decatur, GA, USA.
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27
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Ruffini N, Klingenberg S, Heese R, Schweiger S, Gerber S. The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach. Front Aging Neurosci 2022; 14:866886. [PMID: 35832065 PMCID: PMC9271745 DOI: 10.3389/fnagi.2022.866886] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 05/13/2022] [Indexed: 12/12/2022] Open
Abstract
The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.
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Affiliation(s)
- Nicolas Ruffini
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Leibniz Institute for Resilience Research, Leibniz Association, Mainz, Germany
| | - Susanne Klingenberg
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Raoul Heese
- Fraunhofer Institute for Industrial Mathematics (ITWM), Kaiserslautern, Germany
| | - Susann Schweiger
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Susanne Gerber
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
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28
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Wang C, Martins-Bach AB, Alfaro-Almagro F, Douaud G, Klein JC, Llera A, Fiscone C, Bowtell R, Elliott LT, Smith SM, Tendler BC, Miller KL. Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging. Nat Neurosci 2022; 25:818-831. [PMID: 35606419 PMCID: PMC9174052 DOI: 10.1038/s41593-022-01074-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 04/11/2022] [Indexed: 12/17/2022]
Abstract
A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.
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Affiliation(s)
- Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Aurea B Martins-Bach
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
| | - Cristiana Fiscone
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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29
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Yoritaka A, Hayashi T, Fusegi K, Inami R, Hattori N. Prospective Five-Year Follow-Up of Patients with Schizophrenia Suspected with Parkinson's Disease. PARKINSON'S DISEASE 2022; 2022:2727515. [PMID: 35698464 PMCID: PMC9188471 DOI: 10.1155/2022/2727515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 05/04/2022] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVE It is difficult to distinguish patients with schizophrenia with neuroleptic-induced parkinsonism (NIP) from those with existing idiopathic Parkinson's disease when their striatal dopamine transporter uptake is reduced. There is a possibility of misdiagnosis of Parkinson's disease in patients with schizophrenia as schizophrenia with NIP, which leads to inappropriate treatment. This prospective study aimed at determining the underlying pathophysiology using detailed clinical and psychological assessments. METHODS We enrolled six patients with schizophrenia who had parkinsonism and were diagnosed with Parkinson's disease according to the Movement Disorder Society Clinical Diagnostic Criteria, except for the fifth absolute exclusion criteria. RESULTS Five patients had been treated with neuroleptics for 20 years. One patient refused treatment for schizophrenia. All patients had impaired cognitive function at enrolment, olfactory dysfunction, and constipation. All patients were treated with dopaminergic therapy, and their parkinsonism substantially improved; one woman in her 40s experienced a wearing-off effect and dyskinesia. The uptake of dopamine transporter in the striatum decreased by 13%/year during the study period. CONCLUSION Some patients with schizophrenia and parkinsonism benefit from dopaminergic therapy. Some of these patients may also exhibit Lewy pathology.
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Affiliation(s)
- Asako Yoritaka
- Department of Neurology, Juntendo University Koshigaya Hospital, Saitama, Japan
| | - Tetsuo Hayashi
- Department of Neurology, Juntendo University Koshigaya Hospital, Saitama, Japan
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Keiko Fusegi
- Department of Neurology, Juntendo University Koshigaya Hospital, Saitama, Japan
| | - Rie Inami
- Department of Psychiatry, Juntendo University Koshigaya Hospital, Saitama, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
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30
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Li C, Pang D, Lin J, Yang T, Shang H. Shared genetic links between frontotemporal dementia and psychiatric disorders. BMC Med 2022; 20:131. [PMID: 35509074 PMCID: PMC9069762 DOI: 10.1186/s12916-022-02335-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/14/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Epidemiological and clinical studies have suggested comorbidity between frontotemporal dementia (FTD) and psychiatric disorders. FTD patients carrying specific mutations were at higher risk for some psychiatric disorders, and vice versa, implying potential shared genetic etiology, which is still less explored. METHODS We examined the genetic correlation using summary statistics from genome-wide association studies and analyzed their genetic enrichment leveraging the conditional false discovery rate method. Furthermore, we explored the causal association between FTD and psychiatric disorders with Mendelian randomization (MR) analysis. RESULTS We identified a significant genetic correlation between FTD and schizophrenia at both genetic and transcriptomic levels. Meanwhile, robust genetic enrichment was observed between FTD and schizophrenia and alcohol use disorder. Seven shared genetic loci were identified, which were mainly involved in interleukin-induced signaling, synaptic vesicle, and brain-derived neurotrophic factor signaling pathways. By integrating cis-expression quantitative trait loci analysis, we identified MAPT and CADM2 as shared risk genes. MR analysis showed mutual causation between FTD and schizophrenia with nominal association. CONCLUSIONS Our findings provide evidence of shared etiology between FTD and schizophrenia and indicate potential common molecular mechanisms contributing to the overlapping pathophysiological and clinical characteristics. Our results also demonstrate the essential role of autoimmunity in these diseases. These findings provide a better understanding of the pleiotropy between FTD and psychiatric disorders and have implications for therapeutic trials.
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Affiliation(s)
- Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Dejiang Pang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China.
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31
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Zhang H, Zhou W, Zhang D. Direct Medical Costs of Parkinson's Disease in Southern China: A Cross-Sectional Study Based on Health Insurance Claims Data in Guangzhou City. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063238. [PMID: 35328925 PMCID: PMC8953775 DOI: 10.3390/ijerph19063238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/01/2022] [Accepted: 03/04/2022] [Indexed: 11/16/2022]
Abstract
Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder. This study aims to evaluate the direct medical costs of patients with PD using a large sample from an entire city and to identity the potential factors correlating with their inpatient costs in Guangzhou City, Southern China. Methods: This retrospective cross-sectional study uses data obtained from the Urban Employee-based Basic Medical Insurance (UEBMI) and the Urban Resident-based Basic Medical Insurance (URBMI) administrative claims databases in Guangzhou City from 2008 to 2012. The total sample was comprised of 2660 patients with PD. Costs were evaluated for the total sample and by types of insurance. The composition of costs was compared between the UEBMI and URBMI subgroups. The extended estimating-equations model was applied to identify the potential impact factors influencing the inpatient costs. Results: The direct medical costs per patient with PD were CNY 14,514.9 (USD 2299.4) in 2012, consisting of inpatient costs of CNY 13,551.4 and outpatient costs of CNY 963.5. The medication costs accounted for the largest part (50.3%). The inpatient costs of PD patients under the UEBMI scheme (CNY 13,651.0) were significantly higher than those of patients in the URBMI subgroup (CNY 12,402.2) (p < 0.05). The proportion of out-of-pocket spending out of inpatient and outpatient costs for UEBMI beneficiaries (24.3% and 56.1%) was much lower than that for patients under the URBMI scheme (47.9% and 76.2%). The regression analysis suggested that types of insurance, age, hospital levels, length of stay (LOS) and comorbidities were significantly correlated with the inpatient costs of patients with PD. Conclusions: The direct medical costs of patients with PD in China were high compared to the GDP per capita in Guangzhou City and different between the two evaluated types of insurance. Patients with the UEBMI scheme, of older age, with comorbidities, staying in tertiary hospitals and with longer LOS had significantly higher inpatient costs. Thus, policymakers need to reduce the gaps between the two urban insurance schemes in benefit levels, provide support for the development of a comprehensive long-term care insurance system and promote the use of telemedicine in China.
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Affiliation(s)
- Hui Zhang
- School of Public Health, Sun Yat-sen University, No. 74, Zhongshan 2nd Road, Guangzhou 510080, China;
- Correspondence:
| | - Wenjing Zhou
- School of Public Health, Sun Yat-sen University, No. 74, Zhongshan 2nd Road, Guangzhou 510080, China;
| | - Donglan Zhang
- Division of Health Services Research, New York University Long Island School of Medicine, Mineola, NY 11501, USA;
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32
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Hemmings SMJ, Swart P, Womersely JS, Ovenden ES, van den Heuvel LL, McGregor NW, Meier S, Bardien S, Abrahams S, Tromp G, Emsley R, Carr J, Seedat S. RNA-seq analysis of gene expression profiles in posttraumatic stress disorder, Parkinson's disease and schizophrenia identifies roles for common and distinct biological pathways. DISCOVER MENTAL HEALTH 2022; 2:6. [PMID: 37861850 PMCID: PMC10501040 DOI: 10.1007/s44192-022-00009-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 02/14/2022] [Indexed: 10/21/2023]
Abstract
Evidence suggests that shared pathophysiological mechanisms in neuropsychiatric disorders (NPDs) may contribute to risk and resilience. We used single-gene and network-level transcriptomic approaches to investigate shared and disorder-specific processes underlying posttraumatic stress disorder (PTSD), Parkinson's disease (PD) and schizophrenia in a South African sample. RNA-seq was performed on blood obtained from cases and controls from each cohort. Gene expression and weighted gene correlation network analyses (WGCNA) were performed using DESeq2 and CEMiTool, respectively. Significant differences in gene expression were limited to the PTSD cohort. However, WGCNA implicated, amongst others, ribosomal expression, inflammation and ubiquitination as key players in the NPDs under investigation. Differential expression in ribosomal-related pathways was observed in the PTSD and PD cohorts, and focal adhesion and extracellular matrix pathways were implicated in PD and schizophrenia. We propose that, despite different phenotypic presentations, core transdiagnostic mechanisms may play important roles in the molecular aetiology of NPDs.
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Affiliation(s)
- Sian M J Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa.
| | - Patricia Swart
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Jacqueline S Womersely
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Ellen S Ovenden
- Systems Genetics Working Group, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa
| | - Leigh L van den Heuvel
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Nathaniel W McGregor
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- Systems Genetics Working Group, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa
| | - Stuart Meier
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa
| | - Soraya Bardien
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Shameemah Abrahams
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Gerard Tromp
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
| | - Jonathan Carr
- Division of Neurology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
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Sun J, Lyu R, Deng L, Li Q, Zhao Y, Zhang Y. SMetABF: A rapid algorithm for Bayesian GWAS meta-analysis with a large number of studies included. PLoS Comput Biol 2022; 18:e1009948. [PMID: 35286307 PMCID: PMC8947622 DOI: 10.1371/journal.pcbi.1009948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 03/24/2022] [Accepted: 02/21/2022] [Indexed: 12/15/2022] Open
Abstract
Bayesian methods are widely used in the GWAS meta-analysis. But the considerable consumption in both computing time and memory space poses great challenges for large-scale meta-analyses. In this research, we propose an algorithm named SMetABF to rapidly obtain the optimal ABF in the GWAS meta-analysis, where shotgun stochastic search (SSS) is introduced to improve the Bayesian GWAS meta-analysis framework, MetABF. Simulation studies confirm that SMetABF performs well in both speed and accuracy, compared to exhaustive methods and MCMC. SMetABF is applied to real GWAS datasets to find several essential loci related to Parkinson's disease (PD) and the results support the underlying relationship between PD and other autoimmune disorders. Developed as an R package and a web tool, SMetABF will become a useful tool to integrate different studies and identify more variants associated with complex traits.
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Affiliation(s)
- Jianle Sun
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Ruiqi Lyu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Luojia Deng
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Qianwen Li
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Yang Zhao
- Department of Biostatistics, Nanjing Medical University School of Public Health, Nanjing, Jiangsu, China
- * E-mail: (YAZ); (YUZ)
| | - Yue Zhang
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- * E-mail: (YAZ); (YUZ)
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Van Assche E, Schulte EC, Andreassen OA, Smeland OB, Luykx JJ. Editorial: Cross-disorder Genetics in Neuropsychiatry. Front Neurosci 2022; 16:826300. [PMID: 35221906 PMCID: PMC8863965 DOI: 10.3389/fnins.2022.826300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Evelien Van Assche
- Department of Psychiatry, University of Münster, Münster, Germany
- *Correspondence: Evelien Van Assche
| | - Eva C. Schulte
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, University of Munich, Munich, Germany
- Department of Psychiatry & Psychotherapy, University Hospital, University of Munich, Munich, Germany
| | - Ole A. Andreassen
- Division of Mental Health and Addiction, NORMENT Centre, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre of Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B. Smeland
- Division of Mental Health and Addiction, NORMENT Centre, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jurjen J. Luykx
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, Netherlands
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Outpatient Second Opinion Clinic, GGNet Mental Health, Warnsveld, Netherlands
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Dopamine transporter silencing in the rat: systems-level alterations in striato-cerebellar and prefrontal-midbrain circuits. Mol Psychiatry 2022; 27:2329-2339. [PMID: 35246636 PMCID: PMC9126810 DOI: 10.1038/s41380-022-01471-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 01/15/2022] [Accepted: 02/02/2022] [Indexed: 12/12/2022]
Abstract
Silencing of dopamine transporter (DAT), a main controlling factor of dopaminergic signaling, results in biochemical and behavioral features characteristic for neuropsychiatric diseases with presumed hyperdopaminergia including schizophrenia, attention deficit hyperactivity disorder (ADHD), bipolar disorder, and obsessive-compulsive disorder (OCD). Investigation of DAT silencing thus provides a transdiagnostic approach towards a systems-level understanding of common underlying pathways. Using a high-field multimodal imaging approach and a highly sensitive cryogenic coil, we integrated structural, functional and metabolic investigations in tandem with behavioral assessments on a newly developed preclinical rat model, comparing DAT homozygous knockout (DAT-KO, N = 14), heterozygous knockout (N = 8) and wild-type male rats (N = 14). We identified spatially distributed structural and functional brain alterations encompassing motor, limbic and associative loops that demonstrated strong behavioral relevance and were highly consistent across imaging modalities. DAT-KO rats manifested pronounced volume loss in the dorsal striatum, negatively correlating with cerebellar volume increase. These alterations were associated with hyperlocomotion, repetitive behavior and loss of efficient functional small-world organization. Further, prefrontal and midbrain regions manifested opposite changes in functional connectivity and local network topology. These prefrontal disturbances were corroborated by elevated myo-inositol levels and increased volume. To conclude, our imaging genetics approach provides multimodal evidence for prefrontal-midbrain decoupling and striato-cerebellar neuroplastic compensation as two key features of constitutive DAT blockade, proposing them as transdiagnostic mechanisms of hyperdopaminergia. Thus, our study connects developmental DAT blockade to systems-level brain changes, underlying impaired action inhibition control and resulting in motor hyperactivity and compulsive-like features relevant for ADHD, schizophrenia and OCD.
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Fritze S, Harneit A, Waddington JL, Kubera KM, Schmitgen MM, Otte ML, Geiger LS, Tost H, Meyer-Lindenberg A, Wolf RC, Hirjak D. Structural alterations in brainstem, basal ganglia and thalamus associated with parkinsonism in schizophrenia spectrum disorders. Eur Arch Psychiatry Clin Neurosci 2021; 271:1455-1464. [PMID: 33950322 PMCID: PMC8563526 DOI: 10.1007/s00406-021-01270-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 04/22/2021] [Indexed: 12/13/2022]
Abstract
The relative roles of brainstem, thalamus and striatum in parkinsonism in schizophrenia spectrum disorder (SSD) patients are largely unknown. To determine whether topographical alterations of the brainstem, thalamus and striatum contribute to parkinsonism in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-P, n = 35) and without (SSD-nonP, n = 64) parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥ 4 and < 4, respectively, in comparison with healthy controls (n = 20). FreeSurfer v6.0 was used for segmentation of four brainstem regions (medulla oblongata, pons, superior cerebellar peduncle and midbrain), caudate nucleus, putamen and thalamus. Patients with parkinsonism had significantly smaller medulla oblongata (p = 0.01, false discovery rate (FDR)-corrected) and putamen (p = 0.02, FDR-corrected) volumes when compared to patients without parkinsonism. Across the entire patient sample (n = 99), significant negative correlations were identified between (a) medulla oblongata volumes and both SAS total (p = 0.034) and glabella-salivation (p = 0.007) scores, and (b) thalamic volumes and both SAS total (p = 0.033) and glabella-salivation (p = 0.007) scores. These results indicate that brainstem and thalamic structures as well as basal ganglia-based motor circuits play a crucial role in the pathogenesis of parkinsonism in SSD.
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Affiliation(s)
- Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anais Harneit
- Research Group System Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - John L Waddington
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Mike M Schmitgen
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Marie-Luise Otte
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Lena S Geiger
- Research Group System Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Heike Tost
- Research Group System Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Research Group System Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Robert C Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
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37
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Hindley G, Bahrami S, Steen NE, O'Connell KS, Frei O, Shadrin A, Bettella F, Rødevand L, Fan CC, Dale AM, Djurovic S, Smeland OB, Andreassen OA. Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking. Transl Psychiatry 2021; 11:466. [PMID: 34497263 PMCID: PMC8426401 DOI: 10.1038/s41398-021-01576-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/19/2021] [Accepted: 08/18/2021] [Indexed: 02/08/2023] Open
Abstract
Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.
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Affiliation(s)
- Guy Hindley
- NORMENT, 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, London, UK.
| | - Shahram Bahrami
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, 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, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, 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, Blindern, 0316, Oslo, Norway
| | - Alexey Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Francesco Bettella
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Linn Rødevand
- NORMENT, 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 Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, 92093, USA
| | - Anders M Dale
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Olav B Smeland
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
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Wasserthal J, Maier-Hein KH, Neher PF, Wolf RC, Northoff G, Waddington JL, Kubera KM, Fritze S, Harneit A, Geiger LS, Tost H, Hirjak D. White matter microstructure alterations in cortico-striatal networks are associated with parkinsonism in schizophrenia spectrum disorders. Eur Neuropsychopharmacol 2021; 50:64-74. [PMID: 33984810 DOI: 10.1016/j.euroneuro.2021.04.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 03/15/2021] [Accepted: 04/10/2021] [Indexed: 12/17/2022]
Abstract
The specific role of white matter (WM) microstructure in parkinsonism among patients with schizophrenia spectrum disorders (SSD) is largely unknown. To determine whether topographical alterations of WM microstructure contribute to parkinsonism in SSD patients, we examined healthy controls (HC, n=16) and SSD patients with and without parkinsonism, as defined by Simpson-Angus Scale total score of ≥4 (SSD-P, n=33) or <4 (SSD-nonP, n=62). We used whole brain tract-based spatial statistics (TBSS), tractometry (along tract statistics using TractSeg) and graph analytics (clustering coefficient (CCO), local betweenness centrality (BC)) to provide a framework of specific WM microstructural changes underlying parkinsonism in SSD. Using these methods, post hoc analyses showed (a) decreased fractional anisotrophy (FA), as measured via tractometry, in the corpus callosum, corticospinal tract and striato-fronto-orbital tract, and (b) increased CCO, as derived by graph analytics, in the left orbitofrontal cortex (OFC) and left superior frontal gyrus (SFG), in SSD-P patients when compared to SSD-nonP patients. Increased CCO in the left OFC and SFG was associated with SAS scores. These findings indicate the prominence of OFC alterations and aberrant connectivity with fronto-parietal regions and striatum in the pathogenesis of parkinsonism in SSD. This study further supports the notion of altered "bottom-up modulation" between basal ganglia and fronto-parietal regions in the pathobiology of parkinsonism, which may reflect an interaction between movement disorder intrinsic to SSD and antipsychotic drug-induced sensorimotor dysfunction.
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Affiliation(s)
- Jakob Wasserthal
- Division of Medical Imaging Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Klaus H Maier-Hein
- Division of Medical Imaging Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany; Section of Automated Image Analysis, Heidelberg University Hospital, Heidelberg, Germany
| | - Peter F Neher
- Division of Medical Imaging Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Robert C Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Germany
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - John L Waddington
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Germany
| | - Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anais Harneit
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lena S Geiger
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
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Pisanu C, Congiu D, Severino G, Ardau R, Chillotti C, Del Zompo M, Baune BT, Squassina A. Investigation of genetic loci shared between bipolar disorder and risk-taking propensity: potential implications for pharmacological interventions. Neuropsychopharmacology 2021; 46:1680-1692. [PMID: 34035470 PMCID: PMC8280111 DOI: 10.1038/s41386-021-01045-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 11/09/2022]
Abstract
Patients with bipolar disorder (BD) often show increased risk-taking propensity, which may contribute to poor clinical outcome. While these two phenotypes are genetically correlated, there is scarce knowledge on the shared genetic determinants. Using GWAS datasets on BD (41,917 BD cases and 371,549 controls) and risk-taking (n = 466,571), we dissected shared genetic determinants using conjunctional false discovery rate (conjFDR) and local genetic covariance analysis. We investigated specificity of identified targets using GWAS datasets on schizophrenia (SCZ) and attention-deficit hyperactivity disorder (ADHD). The putative functional role of identified targets was evaluated using different tools and GTEx v. 8. Target druggability was evaluated using DGIdb and enrichment for drug targets with genome for REPositioning drugs (GREP). Among 102 loci shared between BD and risk-taking, 87% showed the same direction of effect. Sixty-two were specifically shared between risk-taking propensity and BD, while the others were also shared between risk-taking propensity and either SCZ or ADHD. By leveraging pleiotropic enrichment, we reported 15 novel and specific loci associated with BD and 22 with risk-taking. Among cross-disorder genes, CACNA1C (a known target of calcium channel blockers) was significantly associated with risk-taking propensity and both BD and SCZ using conjFDR (p = 0.001 for both) as well as local genetic covariance analysis, and predicted to be differentially expressed in the cerebellar hemisphere in an eQTL-informed gene-based analysis (BD, Z = 7.48, p = 3.8E-14; risk-taking: Z = 4.66, p = 1.6E-06). We reported for the first time shared genetic determinants between BD and risk-taking propensity. Further investigation into calcium channel blockers or development of innovative ligands of calcium channels might form the basis for innovative pharmacotherapy in patients with BD with increased risk-taking propensity.
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Affiliation(s)
- Claudia Pisanu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Donatella Congiu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Giovanni Severino
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Raffaella Ardau
- Unit of Clinical Pharmacology of the University Hospital of Cagliari, Cagliari, Italy
| | - Caterina Chillotti
- Unit of Clinical Pharmacology of the University Hospital of Cagliari, Cagliari, Italy
| | - Maria Del Zompo
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
- Unit of Clinical Pharmacology of the University Hospital of Cagliari, Cagliari, Italy
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Alessio Squassina
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
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Lyu R, Sun J, Xu D, Jiang Q, Wei C, Zhang Y. GESLM algorithm for detecting causal SNPs in GWAS with multiple phenotypes. Brief Bioinform 2021; 22:6329404. [PMID: 34323927 DOI: 10.1093/bib/bbab276] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/05/2021] [Accepted: 06/29/2021] [Indexed: 12/13/2022] Open
Abstract
With the development of genome-wide association studies, how to gain information from a large scale of data has become an issue of common concern, since traditional methods are not fully developed to solve problems such as identifying loci-to-loci interactions (also known as epistasis). Previous epistatic studies mainly focused on local information with a single outcome (phenotype), while in this paper, we developed a two-stage global search algorithm, Greedy Equivalence Search with Local Modification (GESLM), to implement a global search of directed acyclic graph in order to identify genome-wide epistatic interactions with multiple outcome variables (phenotypes) in a case-control design. GESLM integrates the advantages of score-based methods and constraint-based methods to learn the phenotype-related Bayesian network and is powerful and robust to find the interaction structures that display both genetic associations with phenotypes and gene interactions. We compared GESLM with some common phenotype-related loci detecting methods in simulation studies. The results showed that our method improved the accuracy and efficiency compared with others, especially in an unbalanced case-control study. Besides, its application on the UK Biobank dataset suggested that our algorithm has great performance when handling genome-wide association data with more than one phenotype.
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Affiliation(s)
- Ruiqi Lyu
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
| | - Jianle Sun
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
| | - Dong Xu
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
| | - Qianxue Jiang
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
| | - Chaochun Wei
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
| | - Yue Zhang
- Shanghai Jiao Tong University, Department of Bioinformatics and Biostatistics, Shanghai, 200240, China
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41
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Rødevand L, Bahrami S, Frei O, Chu Y, Shadrin A, O'Connell KS, Smeland OB, Elvsåshagen T, Hindley GFL, Djurovic S, Dale AM, Lagerberg TV, Steen NE, Andreassen OA. Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes. Transl Psychiatry 2021; 11:407. [PMID: 34301917 PMCID: PMC8302675 DOI: 10.1038/s41398-021-01527-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 12/13/2022] Open
Abstract
Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208-795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20-22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.
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Affiliation(s)
- 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.
| | - 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
| | - 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
| | - Yunhan Chu
- 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
| | - Alexey 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
| | - 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
| | - 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
| | - Torbjørn Elvsåshagen
- 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 Neurology, Oslo University Hospital, 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
| | - 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, USA
- 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
| | - Trine V Lagerberg
- 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
| | - Nils Eiel Steen
- 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.
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42
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Bahrami S, Hindley G, Winsvold BS, O'Connell KS, Frei O, Shadrin A, Cheng W, Bettella F, Rødevand L, Odegaard KJ, Fan CC, Pirinen MJ, Hautakangas HM, Headache HAI, Dale AM, Djurovic S, Smeland OB, Andreassen OA. Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools. Brain 2021; 145:142-153. [PMID: 34273149 PMCID: PMC8967089 DOI: 10.1093/brain/awab267] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 05/18/2021] [Accepted: 06/21/2021] [Indexed: 11/24/2022] Open
Abstract
Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine’s polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100–12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of ‘pleiotropic’ variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.
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Affiliation(s)
- Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway
| | - Guy Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway.,Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Bendik Slagsvold Winsvold
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway.,K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, 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
| | - 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 Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 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
| | - Francesco Bettella
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway
| | - Linn Rødevand
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway
| | - Ketil J Odegaard
- NORMENT, Division of Psychiatry, Haukeland University Hospital and Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway
| | - Chun C Fan
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Matti J Pirinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland.,Department of Public Health, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland.,Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland
| | - Heidi M Hautakangas
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland
| | - Hunt All-In Headache
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, USA.,Department of Radiology, 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
| | - Srdjan Djurovic
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway.,Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - 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
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43
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Quattrone D. Do Idiopathic Parkinson's Disease and Schizophrenia Lie on the Same Genetic Spectrum? Biol Psychiatry 2021; 89:207-208. [PMID: 33357627 DOI: 10.1016/j.biopsych.2020.11.011] [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: 11/13/2020] [Accepted: 11/16/2020] [Indexed: 10/22/2022]
Affiliation(s)
- Diego Quattrone
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
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44
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Oliveira PRS, de Matos LO, Araujo NM, Sant Anna HP, da Silva E Silva DA, Damasceno AKA, Martins de Carvalho L, Horta BL, Lima-Costa MF, Barreto ML, Wiers CE, Volkow ND, Brunialti Godard AL. LRRK2 Gene Variants Associated With a Higher Risk for Alcohol Dependence in Multiethnic Populations. Front Psychiatry 2021; 12:665257. [PMID: 34135785 PMCID: PMC8202767 DOI: 10.3389/fpsyt.2021.665257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/12/2021] [Indexed: 11/22/2022] Open
Abstract
Background: Genetics influence the vulnerability to alcohol use disorders, and among the implicated genes, three previous studies have provided evidences for the involvement of LRRK2 in alcohol dependence (AD). LRRK2 expression is broadly dysregulated in postmortem brain from AD humans, as well as in the brain of mice with alcohol dependent-like behaviors and in a zebrafish model of alcohol preference. The aim of the present study was to evaluate the association of variants in the LRRK2 gene with AD in multiethnic populations from South and North America. Methods: Alcohol-screening questionnaires [such as CAGE and Alcohol Use Disorders Identification Test (AUDIT)] were used to determine individual risk of AD. Multivariate logistic regression analyses were done in three independent populations (898 individuals from Bambuí, Brazil; 3,015 individuals from Pelotas, Brazil; and 1,316 from the United States). Linkage disequilibrium and conditional analyses, as well as in silico functional analyses, were also conducted. Results: Four LRRK2 variants were significantly associated with AD in our discovery cohort (Bambuí): rs4768231, rs4767971, rs7307310, and rs1465527. Two of these variants (rs4768231 and rs4767971) were replicated in both Pelotas and US cohorts. The consistent association signal (at the LRRK2 locus) found in populations with different genetic backgrounds reinforces the relevance of our findings. Conclusion: Taken together, these results support the notion that genetic variants in the LRRK2 locus are risk factors for AD in humans.
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Affiliation(s)
- Pablo Rafael Silveira Oliveira
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Lorena Oliveira de Matos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Nathalia Matta Araujo
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Hanaísa P Sant Anna
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Andresa K Andrade Damasceno
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Luana Martins de Carvalho
- Department of Psychiatry, Center for Alcohol Research in Epigenetics, University of Illinois, Chicago, IL, United States
| | - Bernardo L Horta
- Programa de Pos-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil
| | | | - Mauricio Lima Barreto
- Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Corinde E Wiers
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Ana Lúcia Brunialti Godard
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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45
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Smeland OB, Frei O, Dale AM, Andreassen OA. The polygenic architecture of schizophrenia — rethinking pathogenesis and nosology. Nat Rev Neurol 2020; 16:366-379. [DOI: 10.1038/s41582-020-0364-0] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 02/07/2023]
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