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Kanjira SC, Adams MJ, Jiang Y, Tian C, Lewis CM, Kuchenbaecker K, McIntosh AM. Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants. Mol Psychiatry 2024:10.1038/s41380-024-02662-x. [PMID: 39014000 DOI: 10.1038/s41380-024-02662-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 06/27/2024] [Accepted: 07/03/2024] [Indexed: 07/18/2024]
Abstract
Genome-Wide Association Studies (GWAS) over-represent European ancestries, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to Africans. We assessed the comparative accuracy of depression PRS trained on European and African Ancestries GWAS studies to predict major depressive disorder (MDD) and related traits in African ancestry participants from the UK Biobank. UK Biobank participants were selected based on Principal component analysis clustering with an African genetic similarity reference population, MDD was assessed with the Composite International Diagnostic Interview (CIDI). PRS were computed using PRSice2 software using either European or African Ancestries GWAS summary statistics. PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (R2 = 2%, β = 0.32, empirical p-value = 0.002) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R² = 1.8%, β = 0.28, empirical p-value = 0.008). This suggests that prediction of MDD status from Africans to Africans had greater efficiency relative to discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of likely causal risk factors from European ancestries was non-significant. GWAS of MDD in European ancestries are inefficient for improving polygenic prediction in African samples; urgent MDD studies in Africa are needed.
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Affiliation(s)
- S C Kanjira
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
| | - M J Adams
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Y Jiang
- 23andMe Inc, Sunnyvale, CA, USA
| | - C Tian
- 23andMe Inc, Sunnyvale, CA, USA
| | - C M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - K Kuchenbaecker
- UCL Genetics Institute, University College London, London, UK
| | - A M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK.
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Xiu Z, Sun L, Liu K, Cao H, Qu HQ, Glessner JT, Ding Z, Zheng G, Wang N, Xia Q, Li J, Li MJ, Hakonarson H, Liu W, Li J. Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders. Brain Behav Immun 2024; 119:767-780. [PMID: 38677625 DOI: 10.1016/j.bbi.2024.04.026] [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: 10/21/2023] [Revised: 02/27/2024] [Accepted: 04/22/2024] [Indexed: 04/29/2024] Open
Abstract
The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.
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Affiliation(s)
- Zhanjie Xiu
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ling Sun
- Department of Child and Adolescent Psychology, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Kunlun Liu
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Haiyan Cao
- Department of Child and Adolescent Psychology, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Hui-Qi Qu
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Joseph T Glessner
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Zhiyong Ding
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd., Jinan, China
| | - Gang Zheng
- National Supercomputer Center in Tianjin (NSCC-TJ), Tianjin, China
| | - Nan Wang
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd., Jinan, China
| | - Qianghua Xia
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jie Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
| | - Wei Liu
- Tianjin Children's Hospital (Tianjin University Children's Hospital), Tianjin, China; Tianjin Key Laboratory of Birth Defects for Prevention and Treatment, Tianjin, China.
| | - Jin Li
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Rheumatology and Immunology, Tianjin Medical University General Hospital, Tianjin, China.
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3
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Yuan D, Wu J, Li S, Zhou X, Zhang R, Zhang Y. Causal relationships between serum albumin, neuroticism and suicidal ideation in depressed patients: A Mendelian randomization study. Heliyon 2024; 10:e30718. [PMID: 38765065 PMCID: PMC11098842 DOI: 10.1016/j.heliyon.2024.e30718] [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: 03/05/2023] [Revised: 04/28/2024] [Accepted: 05/02/2024] [Indexed: 05/21/2024] Open
Abstract
Although serum albumin and neuroticism have revealed a strong association with suicidal ideation in individuals with depression, the causal relationship between them is uncertain. This study analyzed the causal association of serum albumin, neuroticism and suicidal ideation using large-scale GWAS data and Univariable Mendelian Randomization (UVMR) methods. The Multivariable MR (MVMR) analysis was used to explore the causal pathways. UVMR analysis revealed that genetically determined serum albumin is causally associated with neuroticism (β = -0.006 S.D.; 95 % CI: 0.009, -0.002; p = 0.003) and suicidal ideation (β = 0.009 S.D.; 95 % CI: 0.001, 0.016; p = 0.037); and that neuroticism mediates 100 % of the causal association between serum albumin and suicidal ideation in individuals with depression. These findings suggest genetic evidence for the causal effect of serum albumin on suicidal ideation in depressed patients and the significant mediation effect of neuroticism on this causal association. This study proves the protective role of serum albumin for neuroticism and the riskiness of personality traits for suicidal ideation in individuals with depression.
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Affiliation(s)
- Dongling Yuan
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jialing Wu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shansi Li
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xiao Zhou
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ruoyi Zhang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yi Zhang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
- Medical Psychological Institute of Central South University, Central South University, Changsha, China
- National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
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4
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Kanjira SC, Adams MJ, Yunxuan J, Chao T, Lewis CM, Kuchenbaecker K, McIntosh AM. Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.24.23300412. [PMID: 38234770 PMCID: PMC10793522 DOI: 10.1101/2023.12.24.23300412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Introduction Genome-Wide Association Studies (GWAS) over-represent European ancestries compared to the global population, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to non-Europeans. We assessed the comparative accuracy of PRS for Major Depressive Disorder (MDD) trained on European and African Ancestries GWAS studies to predict MDD and related traits in African Ancestries participants from the UK Biobank. Methods UK Biobank participants were selected based on Principal component analysis (PCA) clustering with an African genetic similarity reference population and MDD was assessed with the Composite International Diagnostic Interview (CIDI). Polygenic Risk Scores (PRS) were computed using PRSice2 using either European or African Ancestries GWAS summary statistics. Results PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (190 cases, R2=2%) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R2=1.8%). This suggests that prediction of MDD status from Africans to Africans had greater efficiency per unit increase in the discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of causal risk factors from European ancestries was non-significant. Conclusion GWAS studies of MDD in European ancestries are an inefficient means of improving polygenic prediction accuracy in African samples.
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Affiliation(s)
- S C Kanjira
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
| | - M J Adams
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | | | | | | | - A M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Centre for Genomic and Experimental Medicine, University of Edinburgh, UK
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Peter HL, Giglberger M, Streit F, Frank J, Kreuzpointner L, Rietschel M, Kudielka BM, Wüst S. Association of polygenic scores for depression and neuroticism with perceived stress in daily life during a long-lasting stress period. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12872. [PMID: 37876358 PMCID: PMC10733580 DOI: 10.1111/gbb.12872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/31/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
Genetic factors contribute significantly to interindividual differences in the susceptibility to stress-related disorders. As stress can also be conceptualized as environmental exposure, controlled gene-environment interaction (GxE) studies with an in-depth phenotyping may help to unravel mechanisms underlying the interplay between genetic factors and stress. In a prospective-longitudinal quasi-experimental study, we investigated whether polygenic scores (PGS) for depression (DEP-PGS) and neuroticism (NEU-PGS), respectively, were associated with responses to chronic stress in daily life. We examined law students (n = 432) over 13 months. Participants in the stress group experienced a long-lasting stress phase, namely the preparation for the first state examination for law students. The control group consisted of law students without particular stress exposure. In the present manuscript, we analyzed perceived stress levels assessed at high frequency and in an ecologically valid manner by ambulatory assessments as well as depression symptoms and two parameters of the cortisol awakening response. The latter was only assessed in a subsample (n = 196). No associations between the DEP-PGS and stress-related variables were found. However, for the NEU-PGS we found a significant GxE effect. Only in individuals experiencing academic stress a higher PGS for neuroticism predicted stronger increases of perceived stress levels until the exam. At baseline, a higher NEU-PGS was associated with higher perceived stress levels in both groups. Despite the small sample size, we provide preliminary evidence that the genetic disposition for neuroticism is associated with stress level increases in daily life during a long-lasting stress period.
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Affiliation(s)
- Hannah L. Peter
- Institute of PsychologyUniversity of RegensburgRegensburgGermany
| | | | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | | | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental HealthUniversity of MannheimMannheimGermany
| | | | - Stefan Wüst
- Institute of PsychologyUniversity of RegensburgRegensburgGermany
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Steen NE, Rahman Z, Szabo A, Hindley GFL, Parker N, Cheng W, Lin A, O’Connell KS, Sheikh MA, Shadrin A, Bahrami S, Karthikeyan S, Hoseth EZ, Dale AM, Aukrust P, Smeland OB, Ueland T, Frei O, Djurovic S, Andreassen OA. Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities. Schizophr Bull 2023; 49:1345-1354. [PMID: 37319439 PMCID: PMC10483470 DOI: 10.1093/schbul/sbad082] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
BACKGROUND Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ. STUDY DESIGN GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects. STUDY RESULTS The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms. CONCLUSIONS Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.
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Affiliation(s)
- Nils Eiel Steen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Zillur Rahman
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Attila Szabo
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aihua Lin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin S O’Connell
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Mashhood A Sheikh
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sandeep Karthikeyan
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Eva Z Hoseth
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health, Helse Møre Romsdal HF, Kristiansund, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Cognitive Sciences, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Pål Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Olav B Smeland
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Thor Ueland
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen—Thrombosis Research and Expertise Center (TREC), University of Tromsø, Tromsø, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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7
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Als TD, Kurki MI, Grove J, Voloudakis G, Therrien K, Tasanko E, Nielsen TT, Naamanka J, Veerapen K, Levey DF, Bendl J, Bybjerg-Grauholm J, Zeng B, Demontis D, Rosengren A, Athanasiadis G, Bækved-Hansen M, Qvist P, Bragi Walters G, Thorgeirsson T, Stefánsson H, Musliner KL, Rajagopal VM, Farajzadeh L, Thirstrup J, Vilhjálmsson BJ, McGrath JJ, Mattheisen M, Meier S, Agerbo E, Stefánsson K, Nordentoft M, Werge T, Hougaard DM, Mortensen PB, Stein MB, Gelernter J, Hovatta I, Roussos P, Daly MJ, Mors O, Palotie A, Børglum AD. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nat Med 2023; 29:1832-1844. [PMID: 37464041 PMCID: PMC10839245 DOI: 10.1038/s41591-023-02352-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 04/17/2023] [Indexed: 07/20/2023]
Abstract
Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment.
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Affiliation(s)
- Thomas D Als
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
- Center for Genomics and Personalized Medicine, Aarhus, Denmark.
| | - Mitja I Kurki
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jakob Grove
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J Peters VA Medical Center, Bronx, NY, USA
| | - Karen Therrien
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J Peters VA Medical Center, Bronx, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elisa Tasanko
- Department of Psychology and Logopedics, SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - Trine Tollerup Nielsen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Joonas Naamanka
- Department of Psychology and Logopedics, SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - Kumar Veerapen
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jonas Bybjerg-Grauholm
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Biao Zeng
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ditte Demontis
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Anders Rosengren
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Mental Health Centre Sct. Hans, Capital Region of Denmark, Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
| | - Georgios Athanasiadis
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Mental Health Centre Sct. Hans, Capital Region of Denmark, Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona, Spain
| | - Marie Bækved-Hansen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Per Qvist
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | | | | | | | - Katherine L Musliner
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- National Centre for Register-Based Research (NCRR), Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark
- The Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Veera M Rajagopal
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Leila Farajzadeh
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Janne Thirstrup
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Manuel Mattheisen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Sandra Meier
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Esben Agerbo
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- National Centre for Register-Based Research (NCRR), Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, CIRRAU, Aarhus University, Aarhus, Denmark
| | | | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Mental Health Centre Copenhagen, Capital Region of Denmark, Copenhagen University Hospital, Copenhagen, Denmark
| | - Thomas Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Mental Health Centre Sct. Hans, Capital Region of Denmark, Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- Institute of Clinical Sciences and GLOBE Institute, LF Center for GeoGenetics, University of Copenhagen, Copenhagen, Denmark
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Preben B Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- National Centre for Register-Based Research (NCRR), Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, CIRRAU, Aarhus University, Aarhus, Denmark
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Departments of Psychiatry and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Iiris Hovatta
- Department of Psychology and Logopedics, SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J Peters VA Medical Center, Bronx, NY, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Mark J Daly
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital-Psychiatry, Aarhus, Denmark
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
- Center for Genomics and Personalized Medicine, Aarhus, Denmark.
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8
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Nowakowska-Domagała K, Podlecka M, Stecz P, Lewandowska A, Sipowicz K, Kosmalski M, Pietras T, Mokros Ł. The Relationship between Selected Factors (Temperament, Bipolar Traits, Sleep Quality, Severity of Addiction) and Depressive Symptoms in Alcohol-Dependent Men. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4072. [PMID: 36901082 PMCID: PMC10001749 DOI: 10.3390/ijerph20054072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/11/2023] [Accepted: 02/22/2023] [Indexed: 06/18/2023]
Abstract
Clinical and epidemiological studies have demonstrated a relationship between alcohol addiction and mood disorders. Alcohol-dependent patients with depression tend to demonstrate clinically more severe manic symptoms, which complicates the process of diagnosis and therapy. However, the predictors indicating the risk of mood disorders in addicted patients remain unclear. The aim of the study was to examine the relationship between personal dispositions, bipolar traits, depth of addiction, quality of sleep, and depressive symptoms in alcohol-dependent men. The study group comprised 70 men (age M = 46.06, SD = 11.29) diagnosed with alcohol addiction. The participants completed a battery of questionnaires: BDI, HCL-32, PSQI, EPQ-R and MAST. The results were tested using Pearson's correlation quotient and general linear model. The findings indicate that some of the studied patients are likely to have mood disorders of clinically significant severity. High neuroticism and poor sleep quality are independent predictors of depressive symptoms in alcohol-dependent patients. Among the components of sleep quality, problems with falling asleep and waking up at night appear to be most strongly associated with depressive symptoms. The intensity of depressive symptoms may relate to the intensity of certain bipolar features, such as risk-taking activity and irritability. High neuroticism and poor sleep quality are independent predictors of depressive symptoms in the studied group.
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Affiliation(s)
- Katarzyna Nowakowska-Domagała
- Institute of Psychology, Faculty of Educational Sciences, University of Lodz, Al. Rodzeństwa Scheiblerów 2, 90-128 Lodz, Poland
| | - Marlena Podlecka
- Institute of Psychiatry and Neurology, Department of Neurosis, Personality and Eating Disorders, Sobieskiego Street 9, 02-957 Warsaw, Poland
| | - Patryk Stecz
- Institute of Psychology, Faculty of Educational Sciences, University of Lodz, Al. Rodzeństwa Scheiblerów 2, 90-128 Lodz, Poland
| | - Aleksandra Lewandowska
- J. Babiński Specialist Psychiatric Health Care Team, Psychiatric Ward for Children, Aleksandrowska 159, 02-229 Lodz, Poland
| | - Kasper Sipowicz
- Department of Interdisciplinary Disability Studies, The Maria Grzegorzewska University in Warsaw, Szczęśliwicka 40, 02-353 Warsaw, Poland
| | - Marcin Kosmalski
- Department of Clinical Pharmacology, Medical University of Lodz, Kopcinskiego Street 22, 90-153 Lodz, Poland
| | - Tadeusz Pietras
- Institute of Psychiatry and Neurology, Second Department of Psychiatry, Sobieskiego Street 9, 02-957 Warsaw, Poland
| | - Łukasz Mokros
- Department of Clinical Pharmacology, Medical University of Lodz, Kopcinskiego Street 22, 90-153 Lodz, Poland
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9
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Identification of Personality-Related Candidate Genes in Thoroughbred Racehorses Using a Bioinformatics-Based Approach Involving Functionally Annotated Human Genes. Animals (Basel) 2023; 13:ani13040769. [PMID: 36830556 PMCID: PMC9951868 DOI: 10.3390/ani13040769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 02/07/2023] [Accepted: 02/20/2023] [Indexed: 02/25/2023] Open
Abstract
Considering the personality traits of racehorses (e.g., flightiness, anxiety, and affability) is considered essential to improve training efficiency and decrease accident frequency, especially when retraining for a second career that may involve contact with inexperienced personnel after retiring from racing. Studies on human personality-related genes are frequently conducted; however, such studies are rare in horses because a consistent methodology for personality evaluation is lacking. Using the recently published whole genome variant database of 101 Thoroughbred horses, we compared horse genes orthologous to human genes related to the Big Five personality traits, and identified 18 personality-related candidate genes in horses. These genes include 55 variants that involve non-synonymous substitutions that highly impact the encoded protein. Moreover, we evaluated the allele frequencies and functional impact on the proteins in terms of the difference in molecular weights and hydrophobicity levels between reference and altered amino acids. We identified 15 newly discovered genes that may affect equine personality, but their associations with personality are still unclear. Although more studies are required to compare genetic and behavioral information to validate this approach, it may be useful under limited conditions for personality evaluation.
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10
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Current State of Modeling Human Psychiatric Disorders Using Zebrafish. Int J Mol Sci 2023; 24:ijms24043187. [PMID: 36834599 PMCID: PMC9959486 DOI: 10.3390/ijms24043187] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/17/2023] [Accepted: 02/01/2023] [Indexed: 02/08/2023] Open
Abstract
Psychiatric disorders are highly prevalent brain pathologies that represent an urgent, unmet biomedical problem. Since reliable clinical diagnoses are essential for the treatment of psychiatric disorders, their animal models with robust, relevant behavioral and physiological endpoints become necessary. Zebrafish (Danio rerio) display well-defined, complex behaviors in major neurobehavioral domains which are evolutionarily conserved and strikingly parallel to those seen in rodents and humans. Although zebrafish are increasingly often used to model psychiatric disorders, there are also multiple challenges with such models as well. The field may therefore benefit from a balanced, disease-oriented discussion that considers the clinical prevalence, the pathological complexity, and societal importance of the disorders in question, and the extent of its detalization in zebrafish central nervous system (CNS) studies. Here, we critically discuss the use of zebrafish for modeling human psychiatric disorders in general, and highlight the topics for further in-depth consideration, in order to foster and (re)focus translational biological neuroscience research utilizing zebrafish. Recent developments in molecular biology research utilizing this model species have also been summarized here, collectively calling for a wider use of zebrafish in translational CNS disease modeling.
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11
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Alshehri T, Mook- Kanamori DO, Willems van Dijk K, Dinga R, Penninx BWJH, Rosendaal FR, le Cessie S, Milaneschi Y. Metabolomics dissection of depression heterogeneity and related cardiometabolic risk. Psychol Med 2023; 53:248-257. [PMID: 34078486 PMCID: PMC9874986 DOI: 10.1017/s0033291721001471] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 03/09/2021] [Accepted: 04/06/2021] [Indexed: 02/04/2023]
Abstract
BACKGROUND A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations. METHOD Clustering data were from 1094 individuals with major depressive disorder in the last 6 months and measures of 149 metabolites from a 1H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic diseases in an independent population-based cohort (n = 6572). RESULTS CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm2 (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm2 (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -0.01). CONCLUSIONS Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.
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Affiliation(s)
- Tahani Alshehri
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Dennis O. Mook- Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Richard Dinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, The Netherlands
| | - Frits R. Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Saskia le Cessie
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, The Netherlands
- GGZ inGeest, Research & Innovation, Amsterdam, The Netherlands
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12
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Su MH, Liao SC, Chen HC, Lu ML, Chen WY, Hsiao PC, Chen CH, Huang MC, Kuo PH. The association of personality polygenic risk score, psychosocial protective factors and suicide attempt in mood disorder. J Psychiatr Res 2022; 156:422-428. [PMID: 36323145 DOI: 10.1016/j.jpsychires.2022.10.034] [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: 05/04/2022] [Revised: 08/28/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
Some personality traits, especially neuroticism, has been found to be associated with suicide attempt (SA) in mood disorder patients. The present study explored the association between personality traits and SA using polygenic risk scores (PRS) for personality among patients with mood disorders. We also investigated the effects of a variety of psychosocial variables on SA. Patients with bipolar disorder (BPD, N = 841) and major depressive disorder (MDD, N = 710) were recruited from hospitals in Taiwan. Lifetime SA and information on psychosocial factors was collected. We calculated the PRS of neuroticism and extraversion. A trend test for SA was performed across quartiles of the PRS for neuroticism and extraversion, and logistic regression analyses were performed to examine the associations between psychosocial factors and SA, accounting for the PRS of personality traits. The prevalence of SA was higher in MDD than in BPD patients. The risk of SA was elevated in MDD patients with a higher quintile of PRS in neuroticism and a lower quintile of PRS in extraversion. The multiple regression analysis results demonstrated that later age of onset, higher family support and resilience, and lower overall social support were protective factors against SA. From the perspective of suicide prevention efforts, strengthening family support and conducting resilience training for patients with mood disorders may be beneficial interventions in clinical settings.
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Affiliation(s)
- Mei-Hsin Su
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Shih-Cheng Liao
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan; Department of Psychiatry, National Taiwan University BioMedical Park Hospital, Zhubei City, Hsinchu County, Taiwan; Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Hsi-Chung Chen
- Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan
| | - Mong-Liang Lu
- Department of Psychiatry, Wan-Fang Hospital, Taipei Medical University, Taipei, Taiwan; Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taiwan
| | - Wen-Yin Chen
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Songde branch, Taipei, Taiwan
| | - Po-Chang Hsiao
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chun-Hsin Chen
- Department of Psychiatry, Wan-Fang Hospital, Taipei Medical University, Taipei, Taiwan; Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taiwan
| | - Ming-Chyi Huang
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Songde branch, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taiwan.
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13
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Synovial Fluid-Derived Extracellular Vesicles of Patients with Arthritides Contribute to Hippocampal Synaptic Dysfunctions and Increase with Mood Disorders Severity in Humans. Cells 2022; 11:cells11152276. [PMID: 35892573 PMCID: PMC9331474 DOI: 10.3390/cells11152276] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/13/2022] [Accepted: 07/20/2022] [Indexed: 01/27/2023] Open
Abstract
Arthritides are a highly heterogeneous group of disorders that include two major clinical entities, localized joint disorders such as osteoarthritis (OA) and systemic autoimmune-driven diseases such as rheumatoid arthritis (RA). Arthritides are characterized by chronic debilitating musculoskeletal conditions and systemic chronic inflammation. Poor mental health is also one of the most common comorbidities of arthritides. Depressive symptoms which are most prevalent, negatively impact patient global assessment diminishing the probability of achieving the target of clinical remission. Here, we investigated new insights into mechanisms that link different joint disorders to poor mental health, and to this issue, we explored the action of the synovial fluid-derived extracellular vesicles (EVs) on neuronal function. Our data show that the exposure of neurons to different concentrations of EVs derived from both RA and OA synovial fluids (RA-EVs and OA-EVs) leads to increased excitatory synaptic transmission but acts on specific modifications on excitatory or inhibitory synapses, as evidenced by electrophysiological and confocal experiments carried out in hippocampal cultures. The treatment of neurons with EVs membrane is also responsible for generating similar effects to those found with intact EVs suggesting that changes in neuronal ability arise upon EVs membrane molecules′ interactions with neurons. In humans with arthritides, we found that nearly half of patients (37.5%) showed clinically significant psychiatric symptoms (CGIs score ≥ 3), and at least mild anxiety (HAM-A ≥ 7) or depression (MADRS and HAM-D ≥ 7); interestingly, these individuals revealed an increased concentration of synovial EVs. In conclusion, our data showing opposite changes at the excitatory and inhibitory levels in neurons treated with OA- and RA-EVs, lay the scientific basis for personalized medicine in OA and RA patients, and identify EVs as new potential actionable biomarkers in patients with OA/RA with poor mental health.
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14
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van Sprang ED, Maciejewski DF, Milaneschi Y, Elzinga BM, Beekman ATF, Hartman CA, van Hemert AM, Penninx BWJH. Familial risk for depressive and anxiety disorders: associations with genetic, clinical, and psychosocial vulnerabilities. Psychol Med 2022; 52:696-706. [PMID: 32624018 PMCID: PMC8961330 DOI: 10.1017/s0033291720002299] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 04/21/2020] [Accepted: 06/09/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND In research and clinical practice, familial risk for depression and anxiety is often constructed as a simple Yes/No dichotomous family history (FH) indicator. However, this measure may not fully capture the liability to these conditions. This study investigated whether a continuous familial loading score (FLS), incorporating family- and disorder-specific characteristics (e.g. family size, prevalence of depression/anxiety), (i) is associated with a polygenic risk score (PRS) for major depression and with clinical/psychosocial vulnerabilities and (ii) still captures variation in clinical/psychosocial vulnerabilities after information on FH has been taken into account. METHODS Data came from 1425 participants with lifetime depression and/or anxiety from the Netherlands Study of Depression and Anxiety. The Family Tree Inventory was used to determine FLS/FH indicators for depression and/or anxiety. RESULTS Persons with higher FLS had higher PRS for major depression, more severe depression and anxiety symptoms, higher disease burden, younger age of onset, and more neuroticism, rumination, and childhood trauma. Among these variables, FH was not associated with PRS, severity of symptoms, and neuroticism. After regression out the effect of FH from the FLS, the resulting residualized measure of FLS was still associated with severity of symptoms of depression and anxiety, rumination, and childhood trauma. CONCLUSIONS Familial risk for depression and anxiety deserves clinical attention due to its associated genetic vulnerability and more unfavorable disease profile, and seems to be better captured by a continuous score that incorporates family- and disorder-specific characteristics than by a dichotomous FH measure.
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Affiliation(s)
- Eleonore D. van Sprang
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Dominique F. Maciejewski
- Department of Developmental Psychopathology, Behavioral Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Yuri Milaneschi
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Bernet M. Elzinga
- Institute of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Aartjan T. F. Beekman
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Catharina A. Hartman
- University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation, Department of Psychiatry, Groningen, The Netherlands
| | - Albert M. van Hemert
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
| | - Brenda W. J. H. Penninx
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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15
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A scoping review and comparison of approaches for measuring genetic heterogeneity in psychiatric disorders. Psychiatr Genet 2022; 32:1-8. [PMID: 34694248 DOI: 10.1097/ypg.0000000000000304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
An improved understanding of genetic etiological heterogeneity in a psychiatric condition may help us (a) isolate a neurophysiological 'final common pathway' by identifying its upstream genetic origins and (b) facilitate characterization of the condition's phenotypic variation. This review aims to identify existing genetic heterogeneity measurements in the psychiatric literature and provides a conceptual review of their mechanisms, limitations, and assumptions. The Scopus database was searched for studies that quantified genetic heterogeneity or correlation of psychiatric phenotypes with human genetic data. Ninety studies were included. Eighty-seven reports quantified genetic correlation, five applied genomic structural equation modelling, three evaluated departure from the Hardy-Weinberg equilibrium at one or more loci, and two applied a novel approach known as MiXeR. We found no study that rigorously measured genetic etiological heterogeneity across a large number of markers. Developing such approaches may help better characterize the biological diversity of psychopathology.
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16
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Thorp JG, Campos AI, Grotzinger AD, Gerring ZF, An J, Ong JS, Wang W, Shringarpure S, Byrne EM, MacGregor S, Martin NG, Medland SE, Middeldorp CM, Derks EM. Symptom-level modelling unravels the shared genetic architecture of anxiety and depression. Nat Hum Behav 2021; 5:1432-1442. [PMID: 33859377 DOI: 10.1038/s41562-021-01094-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 03/01/2021] [Indexed: 02/02/2023]
Abstract
Depression and anxiety are highly prevalent and comorbid psychiatric traits that cause considerable burden worldwide. Here we use factor analysis and genomic structural equation modelling to investigate the genetic factor structure underlying 28 items assessing depression, anxiety and neuroticism, a closely related personality trait. Symptoms of depression and anxiety loaded on two distinct, although highly genetically correlated factors, and neuroticism items were partitioned between them. We used this factor structure to conduct genome-wide association analyses on latent factors of depressive symptoms (89 independent variants, 61 genomic loci) and anxiety symptoms (102 variants, 73 loci) in the UK Biobank. Of these associated variants, 72% and 78%, respectively, replicated in an independent cohort of approximately 1.9 million individuals with self-reported diagnosis of depression and anxiety. We use these results to characterize shared and trait-specific genetic associations. Our findings provide insight into the genetic architecture of depression and anxiety and comorbidity between them.
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Affiliation(s)
- Jackson G Thorp
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
| | - Adrian I Campos
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Zachary F Gerring
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jiyuan An
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jue-Sheng Ong
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | | | - Enda M Byrne
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Christel M Middeldorp
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
- Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Queensland, Australia
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Eske M Derks
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
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17
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Axenovich TI, Belonogova NM, Zorkoltseva IV, Tsepilov YA. Number of Genes Associated with Neuroticism due to Their Polymorphisms. RUSS J GENET+ 2021. [DOI: 10.1134/s1022795421070024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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18
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Shared genetic architecture between neuroticism, coronary artery disease and cardiovascular risk factors. Transl Psychiatry 2021; 11:368. [PMID: 34226488 PMCID: PMC8257646 DOI: 10.1038/s41398-021-01466-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 05/07/2021] [Accepted: 05/18/2021] [Indexed: 11/08/2022] Open
Abstract
Neuroticism is associated with poor health, cardiovascular disease (CVD) risk factors and coronary artery disease (CAD). The conditional/conjunctional false discovery rate method (cond/conjFDR) was applied to genome wide association study (GWAS) summary statistics on neuroticism (n = 432,109), CAD (n = 184,305) and 12 CVD risk factors (n = 188,577-339,224) to investigate genetic overlap between neuroticism and CAD and CVD risk factors. CondFDR analyses identified 729 genomic loci associated with neuroticism after conditioning on CAD and CVD risk factors. The conjFDR analyses revealed 345 loci jointly associated with neuroticism and CAD (n = 30), body mass index (BMI) (n = 96) or another CVD risk factor (n = 1-60). Several loci were jointly associated with neuroticism and multiple CVD risk factors. Seventeen of the shared loci with CAD and 61 of the shared loci with BMI are novel for neuroticism. 21 of 30 (70%) neuroticism risk alleles were associated with higher CAD risk. Functional analyses of the genes mapped to the shared loci implicated cell division, nuclear receptor, elastic fiber formation as well as starch and sucrose metabolism pathways. Our results indicate polygenic overlap between neuroticism and CAD and CVD risk factors, suggesting that genetic factors may partly cause the comorbidity. This gives new insight into the shared molecular genetic basis of these conditions.
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Belonogova NM, Zorkoltseva IV, Tsepilov YA, Axenovich TI. Gene-based association analysis identifies 190 genes affecting neuroticism. Sci Rep 2021; 11:2484. [PMID: 33510330 PMCID: PMC7844228 DOI: 10.1038/s41598-021-82123-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 01/15/2021] [Indexed: 11/25/2022] Open
Abstract
Neuroticism is a personality trait, which is an important risk factor for psychiatric disorders. Recent genome-wide studies reported about 600 genes potentially influencing neuroticism. Little is known about the mechanisms of their action. Here, we aimed to conduct a more detailed analysis of genes that can regulate the level of neuroticism. Using UK Biobank-based GWAS summary statistics, we performed a gene-based association analysis using four sets of within-gene variants, each set possessing specific protein-coding properties. To guard against the influence of strong GWAS signals outside the gene, we used a specially designed procedure called “polygene pruning”. As a result, we identified 190 genes associated with neuroticism due to the effect of within-gene variants rather than strong GWAS signals outside the gene. Thirty eight of these genes are new. Within all genes identified, we distinguished two slightly overlapping groups obtained from using protein-coding and non-coding variants. Many genes in the former group included potentially pathogenic variants. For some genes in the latter group, we found evidence of pleiotropy with gene expression. Using a bioinformatics analysis, we prioritized the neuroticism genes and showed that the genes that contribute to neuroticism through their within-gene variants are the most appropriate candidate genes.
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Affiliation(s)
- Nadezhda M Belonogova
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Irina V Zorkoltseva
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yakov A Tsepilov
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.,Department of Natural Sciences, Novosibirsk State University, Novosibirsk, Russia
| | - Tatiana I Axenovich
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. .,Department of Natural Sciences, Novosibirsk State University, Novosibirsk, Russia.
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20
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Antioch I, Ilie OD, Ciobica A, Doroftei B, Fornaro M. Preclinical Considerations about Affective Disorders and Pain: A Broadly Intertwined, yet Often Under-Explored, Relationship Having Major Clinical Implications. MEDICINA (KAUNAS, LITHUANIA) 2020; 56:E504. [PMID: 32992963 PMCID: PMC7600172 DOI: 10.3390/medicina56100504] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 12/11/2022]
Abstract
Background: Pain, a distinctive undesirable experience, encompasses several different and fluctuating presentations across varying mood disorders. Therefore, the present narrative review aimed to shed further light on the matter, accounting for both experimental animal models and clinical observations about major depressive disorder (MDD) pathology. Method: Major databases were inquired from inception until April 2016 for records about MDD and pain. Results: Pain and MDD are tightly associated with each other in a bi-directional fashion. Several cross-sectional and retrospective studies indicated a high presence of pain in the context of mood disorders, including MDD (up to 65%), but also increased prevalence rates in the case of mood disorders documented among people with a primary diagnosis of either psychological or somatic pain (prevalence rates exceeding 45%). The clinical implications of these observations suggest the need to account for mood and pain manifestations as a whole rather than distinct entities in order to deliver more effective interventions. Limitations: Narrative review, lack of systematic control groups (e.g., people with the primary diagnosis at review, but not the associated comorbidity as a study) to allow reliable comparisons. Prevalence rates and clinical features associated with pain varied across different studies as corresponding operational definitions did. Conclusions: Pain may have a detrimental effect on the course of mood disorders-the opposite holds. Promoting a timely recognition and management of such an often neglected comorbidity would therefore represent a primary goal toward the delivery of effective, multi-disciplinary care.
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Affiliation(s)
- Iulia Antioch
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Ovidiu-Dumitru Ilie
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Alin Ciobica
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Bogdan Doroftei
- Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, no 16, 700115 Iasi, Romania
| | - Michele Fornaro
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY 10027, USA;
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21
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Genetic stratification of depression in UK Biobank. Transl Psychiatry 2020; 10:163. [PMID: 32448866 PMCID: PMC7246256 DOI: 10.1038/s41398-020-0848-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 04/28/2020] [Accepted: 04/30/2020] [Indexed: 11/18/2022] Open
Abstract
Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations were used to test for evidence of subgroups using genetic data from seven other complex traits and disorders that were genetically correlated with depression and had sufficient power (>0.6) for detection. We found no evidence for subgroups within depression for schizophrenia, bipolar disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, anorexia nervosa, inflammatory bowel disease or obesity. This suggests that for these traits, genetic correlations with depression were driven by pleiotropic genetic variants carried by everyone rather than by a specific subgroup.
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Shao X, Zhu G. Associations Among Monoamine Neurotransmitter Pathways, Personality Traits, and Major Depressive Disorder. Front Psychiatry 2020; 11:381. [PMID: 32477180 PMCID: PMC7237722 DOI: 10.3389/fpsyt.2020.00381] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Accepted: 04/16/2020] [Indexed: 12/13/2022] Open
Abstract
Major depressive disorder (MDD) is a complex psychiatric disease requiring multidisciplinary approaches to identify specific risk factors and establish more efficacious treatment strategies. Although the etiology and pathophysiology of MDD are not clear until these days, it is acknowledged that they are almost certainly multifactorial and comprehensive. Monoamine neurotransmitter system dysfunction and specific personality traits are independent risk factors for depression and suicide. These factors also demonstrate complex interactions that influence MDD pathogenesis and symptom expression. In this review, we assess these relationships with the aim of providing a reference for the development of precision medicine.
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Affiliation(s)
- Xiaojun Shao
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Gang Zhu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Central Laboratory, The First Affiliated Hospital of China Medical University, Shenyang, China
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