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Hicks EM, Niarchou M, Goleva S, Kabir D, Johnson J, Johnston KJ, Ciarcia J, Pathak GA, Smoller JW, Davis LK, Nievergelt CM, Koenen KC, Huckins LM, Choi KW. Comorbidity Profiles of Posttraumatic Stress Disorder Across the Medical Phenome. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100337. [PMID: 39050781 PMCID: PMC11268109 DOI: 10.1016/j.bpsgos.2024.100337] [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: 10/17/2023] [Revised: 04/09/2024] [Accepted: 04/19/2024] [Indexed: 07/27/2024] Open
Abstract
Background Previous epidemiological research has linked posttraumatic stress disorder (PTSD) with specific physical health problems, but the comprehensive landscape of medical conditions associated with PTSD remains uncharacterized. Electronic health records provide an opportunity to overcome clinical knowledge gaps and uncover associations with biological relevance that potentially vary by sex. Methods PTSD was defined among biobank participants (N = 145,959) in 3 major healthcare systems using 2 ICD code-based definitions: broad (≥1 PTSD or acute stress codes vs. 0; n cases = 16,706) and narrow (≥2 PTSD codes vs. 0; n cases = 3325). Using a phenome-wide association study design, we tested associations between each PTSD definition and all prevalent disease umbrella categories, i.e., phecodes. We also conducted sex-stratified phenome-wide association study analyses including a sex × diagnosis interaction term in each logistic regression. Results A substantial number of phecodes were significantly associated with PTSDNarrow (61%) and PTSDBroad (83%). While the strongest associations were shared between the 2 definitions, PTSDBroad captured 334 additional phecodes not significantly associated with PTSDNarrow and exhibited a wider range of significantly associated phecodes across various categories, including respiratory, genitourinary, and circulatory conditions. Sex differences were observed in that PTSDBroad was more strongly associated with osteoporosis, respiratory failure, hemorrhage, and pulmonary heart disease among male patients and with urinary tract infection, acute pharyngitis, respiratory infections, and overweight among female patients. Conclusions This study provides valuable insights into a diverse range of comorbidities associated with PTSD, including both known and novel associations, while highlighting the influence of sex differences and the impact of defining PTSD using electronic health records.
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Affiliation(s)
- Emily M. Hicks
- Pamela Sklar Division of Psychiatric Genetics, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Maria Niarchou
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee
| | - Slavina Goleva
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee
| | - Dia Kabir
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genetics, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Keira J.A. Johnston
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Julia Ciarcia
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Gita A. Pathak
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Jordan W. Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, Massachusetts
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
| | - Lea K. Davis
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee
| | - Caroline M. Nievergelt
- Department of Psychiatry, University of California San Diego, La Jolla, California
- Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, California
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, California
| | - Karestan C. Koenen
- Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, Massachusetts
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Laura M. Huckins
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Karmel W. Choi
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - PGC/PsycheMERGE PTSD & Trauma EHR Working Group
- Pamela Sklar Division of Psychiatric Genetics, Icahn School of Medicine at Mount Sinai, New York, New York
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, Connecticut
- Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, Massachusetts
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, University of California San Diego, La Jolla, California
- Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, California
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, California
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Sanchez-Ruiz JA, Treviño-Alvarez AM, Zambrano-Lucio M, Lozano Díaz ST, Wang N, Biernacka JM, Tye SJ, Cuellar-Barboza AB. The Wnt signaling pathway in major depressive disorder: A systematic review of human studies. Psychiatry Res 2024; 339:115983. [PMID: 38870775 DOI: 10.1016/j.psychres.2024.115983] [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: 03/01/2024] [Revised: 05/20/2024] [Accepted: 05/26/2024] [Indexed: 06/15/2024]
Abstract
Despite uncertainty about the specific molecular mechanisms driving major depressive disorder (MDD), the Wnt signaling pathway stands out as a potentially influential factor in the pathogenesis of MDD. Known for its role in intercellular communication, cell proliferation, and fate, Wnt signaling has been implicated in diverse biological phenomena associated with MDD, spanning neurodevelopmental to neurodegenerative processes. In this systematic review, we summarize the functional differences in protein and gene expression of the Wnt signaling pathway, and targeted genetic association studies, to provide an integrated synthesis of available human data examining Wnt signaling in MDD. Thirty-three studies evaluating protein expression (n = 15), gene expression (n = 9), or genetic associations (n = 9) were included. Only fifteen demonstrated a consistently low overall risk of bias in selection, comparability, and exposure. We found conflicting observations of limited and distinct Wnt signaling components across diverse tissue sources. These data do not demonstrate involvement of Wnt signaling dysregulation in MDD. Given the well-established role of Wnt signaling in antidepressant response, we propose that a more targeted and functional assessment of Wnt signaling is needed to understand its role in depression pathophysiology. Future studies should include more components, assess multiple tissues concurrently, and follow a standardized approach.
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Affiliation(s)
- Jorge A Sanchez-Ruiz
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | | | | | - Sofía T Lozano Díaz
- Vicerrectoría de Ciencias de la Salud, Universidad de Monterrey, San Pedro Garza Garcia, Nuevo Leon, Mexico
| | - Ning Wang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Joanna M Biernacka
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Susannah J Tye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Department of Psychiatry & Behavioral Sciences, Emory University, Atlanta, GA, USA; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Alfredo B Cuellar-Barboza
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico.
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3
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Litman A, Sauerwald N, Snyder LG, Foss-Feig J, Park CY, Hao Y, Dinstein I, Theesfeld CL, Troyanskaya OG. Decomposition of phenotypic heterogeneity in autism reveals distinct and coherent genetic programs. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.15.24312078. [PMID: 39185525 PMCID: PMC11343255 DOI: 10.1101/2024.08.15.24312078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Unraveling the phenotypic and genetic complexity of autism is extremely challenging yet critical for understanding the biology, inheritance, trajectory, and clinical manifestations of the many forms of the condition. Here, we leveraged broad phenotypic data from a large cohort with matched genetics to characterize classes of autism and their patterns of core, associated, and co-occurring traits, ultimately demonstrating that phenotypic patterns are associated with distinct genetic and molecular programs. We used a generative mixture modeling approach to identify robust, clinically-relevant classes of autism which we validate and replicate in a large independent cohort. We link the phenotypic findings to distinct patterns of de novo and inherited variation which emerge from the deconvolution of these genetic signals, and demonstrate that class-specific common variant scores strongly align with clinical outcomes. We further provide insights into the distinct biological pathways and processes disrupted by the sets of mutations in each class. Remarkably, we discover class-specific differences in the developmental timing of genes that are dysregulated, and these temporal patterns correspond to clinical milestone and outcome differences between the classes. These analyses embrace the phenotypic complexity of children with autism, unraveling genetic and molecular programs underlying their heterogeneity and suggesting specific biological dysregulation patterns and mechanistic hypotheses.
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4
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Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. J Clin Invest 2024; 134:e172885. [PMID: 39145449 PMCID: PMC11324314 DOI: 10.1172/jci172885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024] Open
Abstract
Alcohol use disorder (AUD) is a prominent contributor to global morbidity and mortality. Its complex etiology involves genetics, epigenetics, and environmental factors. We review progress in understanding the genetics and epigenetics of AUD, summarizing the key findings. Advancements in technology over the decades have elevated research from early candidate gene studies to present-day genome-wide scans, unveiling numerous genetic and epigenetic risk factors for AUD. The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Science
- Center for Brain and Mind Health
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Genetics, and
- Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut, USA
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5
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Jácome-Ferrer P, Costas J. Exploring the causal effect of placental physiology in susceptibility to mental and addictive disorders: a Mendelian randomization study. Front Psychiatry 2024; 15:1396837. [PMID: 39135989 PMCID: PMC11317394 DOI: 10.3389/fpsyt.2024.1396837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 07/02/2024] [Indexed: 08/15/2024] Open
Abstract
Background Epidemiological studies have linked low birth weight to psychiatric disorders, including substance use disorders. Genomic analyses suggest a role of placental physiology on psychiatric risk. We investigated whether this association is causally related to impaired trophoblast function. Methods We conducted a two-sample summary-data Mendelian randomization study using as instrumental variables those genetic variants strongly associated with birth weight, whose effect is exerted through the fetal genome, and are located near genes with differential expression in trophoblasts. Eight psychiatric and substance use disorders with >10,000 samples were included as outcomes. The inverse variance weighted method was used as the main analysis and several sensitivity analyses were performed for those significant results. Results The inverse variance weighted estimate, based on 14 instrumental variables, revealed an association, after correction for multiple tests, between birth weight and broadly defined depression (β = -0.165, 95% CI = -0.282 to -0.047, P = 0.0059). Sensitivity analyses revealed the absence of heterogeneity in the effect of instrumental variables, confirmed by leave-one-out analysis, MR_Egger intercept, and MR_PRESSO. The effect was consistent using robust methods. Reverse causality was not detected. The effect was specifically linked to genetic variants near genes involved in trophoblast physiology instead of genes with fetal effect on birth weight or involved in placenta development. Conclusion Impaired trophoblast functioning, probably leading to reduced fetal brain oxygen and nutrient supply, is causally related to broadly defined depression. Considering the therapeutic potential of some agents to treat fetal growth restriction, further research on the effect of trophoblast physiology on mental disorders may have future implications in prevention.
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Affiliation(s)
- Pablo Jácome-Ferrer
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - Javier Costas
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
- Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Spain
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6
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Monson ET, Colbert SMC, Andreassen OA, Ayinde OO, Bejan CA, Ceja Z, Coon H, DiBlasi E, Izotova A, Kaufman EA, Koromina M, Myung W, Nurnberger JI, Serretti A, Smoller JW, Stein MB, Zai CC, Aslan M, Barr PB, Bigdeli TB, Harvey PD, Kimbrel NA, Patel PR, Ruderfer D, Docherty AR, Mullins N, Mann JJ. Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.27.24311110. [PMID: 39132474 PMCID: PMC11312669 DOI: 10.1101/2024.07.27.24311110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Background Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.
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Affiliation(s)
- Eric T Monson
- Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine
- Huntsman Mental Health Institute
| | - Sarah M C Colbert
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Oslo University Hospital
- NORMENT Centre, University of Oslo
| | | | - Cosmin A Bejan
- Department of Biomedical Informatics, Vanderbilt University Medical Center
| | - Zuriel Ceja
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
| | - Hilary Coon
- Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine
- Huntsman Mental Health Institute
| | - Emily DiBlasi
- Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine
- Huntsman Mental Health Institute
| | - Anastasia Izotova
- Nic Waals Institute, Lovisenberg Diaconal Hospital
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health
- Department of Psychology, University of Oslo
| | - Erin A Kaufman
- Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine
- Huntsman Mental Health Institute
| | - Maria Koromina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital
- Department of Psychiatry, Seoul National University College of Medicine
| | - John I Nurnberger
- Department of Psychiatry, Indiana University School of Medicine
- Department of Medical & Molecular Genetics, Indiana University
| | | | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital
- Stanley Center for Psychiatric Research, Broad Institute
- Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital
| | - Murray B Stein
- Department of Psychiatry and School of Public Health, University of California San Diego
| | - Clement C Zai
- Stanley Center for Psychiatric Research, Broad Institute
- Department of Psychiatry, University of Toronto
- Institute of Medical Science, University of Toronto
- Molecular Brain Science, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health
- Laboratory Medicine and Pathobiology, University of Toronto
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System
- Department of Internal Medicine, Yale University School of Medicine
| | - Peter B Barr
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
- VA New York Harbor Healthcare System
- Institute for Genomics in Health, SUNY Downstate Health Sciences University
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
- VA New York Harbor Healthcare System
- Institute for Genomics in Health, SUNY Downstate Health Sciences University
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center
- University of Miami School of Medicine
| | - Nathan A Kimbrel
- Durham VA Health Care System
- VA Health Services Research and Development Center of Innovation to Accelerate Discovery and Practice Transformation
- VISN 6 Mid-Atlantic Mental Illness Research, Education, and Clinical Center
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine
| | - Pujan R Patel
- Durham VA Health Care System
- VA Health Services Research and Development Center of Innovation to Accelerate Discovery and Practice Transformation
| | - Douglas Ruderfer
- Department of Biomedical Informatics, Vanderbilt University Medical Center
- Vanderbilt Genetics Institute, Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center
| | - Anna R Docherty
- Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine
- Huntsman Mental Health Institute
- Clinical and Translational Science Institute & the Center for Genomic Medicine, University of Utah
| | - Niamh Mullins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
| | - J John Mann
- Departments of Psychiatry and Radiology, Columbia University
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7
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics. Nat Commun 2024; 15:6064. [PMID: 39025851 PMCID: PMC11258354 DOI: 10.1038/s41467-024-50309-w] [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: 06/23/2023] [Accepted: 07/02/2024] [Indexed: 07/20/2024] Open
Abstract
The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA.
- Applied Mathematics and Computational Science Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Population Aging Research Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yilin Yang
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT, 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, Philadelphia, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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8
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Grillo AR. Polygene by environment interactions predicting depressive outcomes. Am J Med Genet B Neuropsychiatr Genet 2024:e33000. [PMID: 39012198 DOI: 10.1002/ajmg.b.33000] [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: 05/01/2023] [Revised: 06/13/2024] [Accepted: 06/17/2024] [Indexed: 07/17/2024]
Abstract
Depression is a major public health problem with a continued need to uncover its etiology. Current models of depression contend that gene-by-environment (G × E) interactions influence depression risk, and further, that depression is polygenic. Thus, recent models have emphasized two polygenic approaches: a hypothesis-driven multilocus genetic profile score (MGPS; "MGPS × E") and a polygenic risk score (PRS; "PRS × E") derived from genome-wide association studies (GWAS). This review for the first time synthesizes current knowledge on polygene by environment "P × E" interaction research predicting primarily depression-related outcomes, and in brief, neurobiological outcomes. The "environment" of focus in this project is stressful life events. It further discusses findings in the context of differential susceptibility and diathesis-stress theories-two major theories guiding G × E work. This synthesis indicates that, within the MGPS literature, polygenic scores based on the serotonin system, the HPA axis, or across multiple systems, interact with environmental stress exposure to predict outcomes at multiple levels of analyses and most consistently align with differential susceptibility theory. Depressive outcomes are the most studied, but neuroendocrine, and neuroimaging findings are observed as well. By contrast, vast methodological differences between GWAS-based PRS studies contribute to mixed findings that yield inconclusive results.
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Affiliation(s)
- Alessandra R Grillo
- Department of Psychology, University of North Carolina, Greensboro, North Carolina, USA
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9
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Jiang JW, Jian ZC, Waye MMY, Liang WC, Li MX, Shen XP, Rao ST. Editorial: Decipherment of genetic architecture of psychiatric disorders via combination of multi-omics data. Front Genet 2024; 15:1430517. [PMID: 39045322 PMCID: PMC11263200 DOI: 10.3389/fgene.2024.1430517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 06/26/2024] [Indexed: 07/25/2024] Open
Affiliation(s)
- Jian-Wei Jiang
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Zhong-Cheng Jian
- Department of Pediatrics, Longyan People Hospital of Fujian, Longyan, China
| | - Mary Miu Yee Waye
- Croucher Laboratory for Human Genomics, The Nethersole School of Nursing, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Wei-Cheng Liang
- Vaccine Research Institute, The Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Miao-Xin Li
- Zhongshan School of Medicine, Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Disease Control (SYSU), Ministry of Education, Guangzhou, China
| | - Xiao-Pei Shen
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Shi-Tao Rao
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
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10
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Strom NI, Verhulst B, Bacanu SA, Cheesman R, Purves KL, Gedik H, Mitchell BL, Kwong AS, Faucon AB, Singh K, Medland S, Colodro-Conde L, Krebs K, Hoffmann P, Herms S, Gehlen J, Ripke S, Awasthi S, Palviainen T, Tasanko EM, Peterson RE, Adkins DE, Shabalin AA, Adams MJ, Iveson MH, Campbell A, Thomas LF, Winsvold BS, Drange OK, Børte S, Ter Kuile AR, Nguyen TH, Meier SM, Corfield EC, Hannigan L, Levey DF, Czamara D, Weber H, Choi KW, Pistis G, Couvy-Duchesne B, Van der Auwera S, Teumer A, Karlsson R, Garcia-Argibay M, Lee D, Wang R, Bjerkeset O, Stordal E, Bäckmann J, Salum GA, Zai CC, Kennedy JL, Zai G, Tiwari AK, Heilmann-Heimbach S, Schmidt B, Kaprio J, Kennedy MM, Boden J, Havdahl A, Middeldorp CM, Lopes FL, Akula N, McMahon FJ, Binder EB, Fehm L, Ströhle A, Castelao E, Tiemeier H, Stein DJ, Whiteman D, Olsen C, Fuller Z, Wang X, Wray NR, Byrne EM, Lewis G, Timpson NJ, Davis LK, Hickie IB, Gillespie NA, Milani L, Schumacher J, Woldbye DP, Forstner AJ, Nöthen MM, Hovatta I, Horwood J, Copeland WE, Maes HH, McIntosh AM, Andreassen OA, Zwart JA, Mors O, Børglum AD, Mortensen PB, Ask H, Reichborn-Kjennerud T, Najman JM, Stein MB, Gelernter J, Milaneschi Y, Penninx BW, Boomsma DI, Maron E, Erhardt-Lehmann A, Rück C, Kircher TT, Melzig CA, Alpers GW, Arolt V, Domschke K, Smoller JW, Preisig M, Martin NG, Lupton MK, Luik AI, Reif A, Grabe HJ, Larsson H, Magnusson PK, Oldehinkel AJ, Hartman CA, Breen G, Docherty AR, Coon H, Conrad R, Lehto K, Deckert J, Eley TC, Mattheisen M, Hettema JM. Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.03.24309466. [PMID: 39006447 PMCID: PMC11245051 DOI: 10.1101/2024.07.03.24309466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.
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Affiliation(s)
- Nora I Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Brad Verhulst
- Psychiatry and Behavioral Sciences, Texas A&M University, College Station, Texas, USA
| | | | - Rosa Cheesman
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Kirstin L Purves
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hüseyin Gedik
- Institute for Genomics in Health, Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Health Sciences University, Brooklyn, New York, USA
- Life Sciences, Integrative Life Sciences Doctoral Program, Virginia Commonwealth University, Richmond, Virginia, USA
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Brittany L Mitchell
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, Queensland University , Brisbane, Queensland, Australia
| | - Alex S Kwong
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Centre for Clinical Brain Sciences, Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Annika B Faucon
- Division of Medicine, Human Genetics, Vanderbilt University, Nashville, Tennessee, USA
| | - Kritika Singh
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah Medland
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Lucia Colodro-Conde
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, The University of Queensland, Brisbane, Queensland, Australia
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Department of Biomedicine, Human Genomics Research Group, University of Basel; University Hospital Basel, Basel, Switzerland
| | - Stefan Herms
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Medical Genetics and Pathology, Medical Faculty, University Hospital Basel, Basel, Switzerland
- Department of Biomedicine, Human Genomics Research Group, University of Basel; University Hospital Basel, Basel, Switzerland
| | - Jan Gehlen
- Center for Human Genetics, University of Marburg, Marburg, Germany
| | - Stephan Ripke
- Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Swapnil Awasthi
- Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Teemu Palviainen
- Helsinki Institute of Life Science, Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Elisa M Tasanko
- Faculty of Medicine, Department of Psychology and Logopedics, SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - Roseann E Peterson
- Institute for Genomics in Health, Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Health Sciences University, Brooklyn, New York, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Daniel E Adkins
- School of Medicine, Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Andrey A Shabalin
- School of Medicine, Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Mark J Adams
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Matthew H Iveson
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- College of Medicine and Veterinary Medicine, Institute of Genetics and Cancer; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Laurent F Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bendik S Winsvold
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Ole Kristian Drange
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Mental Health, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre of Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Psychiatry, Sørlandet Hospital, Kristiansand, Norway
| | - Sigrid Børte
- Division of Clinical Neuroscience, Department of Research and Innovation; Musculoskeletal Health, Oslo University Hospital, Oslo, Norway
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Abigail R Ter Kuile
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Tan-Hoang Nguyen
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Sandra M Meier
- Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Elizabeth C Corfield
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute , Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Laurie Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Daniel F Levey
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
- Psychiatry, Research, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Darina Czamara
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
| | - Heike Weber
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
| | - Karmel W Choi
- Psychiatry, Center for Precision Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Giorgio Pistis
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Baptiste Couvy-Duchesne
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- ARAMIS laboratory, Paris Brain Institute, Paris, France
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Miguel Garcia-Argibay
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Donghyung Lee
- Department of Statistics, Miami University, Oxford, Ohio, USA
| | - Rujia Wang
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ottar Bjerkeset
- Faculty of Nursing and Health Science, Nord University, Levanger, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Eystein Stordal
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trustt, Namsos, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Julia Bäckmann
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Giovanni A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Child Psychiatry, National Institute of Developmental Psychiatry, São Paulo, Brazil
| | - Clement C Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - James L Kennedy
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Gwyneth Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Arun K Tiwari
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Jaakko Kaprio
- Helsinki Institute of Life Science, Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Martin M Kennedy
- Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Joseph Boden
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Alexandra Havdahl
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - 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
| | - Fabiana L Lopes
- National Institute of Mental Health, Human Genetics Branch, National Institutes of Health, Bethesda, Maryland, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Nirmala Akula
- National Institute of Mental Health, Genetic Basis of Mood and Anxiety Disorders, National Institutes of Health, Bethesda, Maryland, USA
| | - Francis J McMahon
- National Institute of Mental Health, Genetic Basis of Mood and Anxiety Disorders, National Institutes of Health, Bethesda, Maryland, USA
- Psychiatry & Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Elisabeth B Binder
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
| | - Lydia Fehm
- Department of Psychology, Zentrum für Psychotherapie, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andreas Ströhle
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Enrique Castelao
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Henning Tiemeier
- Social and Behavioral Science, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - David Whiteman
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Catherine Olsen
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enda M Byrne
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
| | - Glyn Lewis
- UCL Division of Psychiatry, University College London, London, UK
| | - Nicholas J Timpson
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lea K Davis
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | | | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - David P Woldbye
- Department of Neuroscience, Laboratory of Neural Plasticity, University of Copenhagen, Copenhagen, Denmark
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Center for Human Genetics, University of Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Iiris Hovatta
- Faculty of Medicine, Department of Psychology and Logopedics and SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - John Horwood
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - William E Copeland
- UVM Medical Center, Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Hermine H Maes
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre of Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
| | - John-Anker Zwart
- Division of Clinical Neuroscience, Department of Research and Innovation; Musculoskeletal Health, Oslo University Hospital, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole Mors
- Department of Psychiatry, Psychosis Research Unit, Aarhus University Hospital, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalised Medicine, Aarhus University, Aarhus, Denmark
| | - Preben B Mortensen
- The National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Helga Ask
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Ted Reichborn-Kjennerud
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- NORMENT Centre, University of Oslo, Oslo, Norway
| | - Jackob M Najman
- Faculty of Medicine, School of Public Health, University of Queensland, Herston, Queensland, Australia
| | - Murray B Stein
- Psychiatry, University of California San Diego, La Jolla, CA, USA
- School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
- Psychiatry Research, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Departments of Genetics and Neuroscience, Yale University of Medicine, New Haven, Connecticut, USA
| | - Yuri Milaneschi
- Amsterdam Neuroscience; Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Brenda W Penninx
- Amsterdam Neuroscience; Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Twin Register and Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Eduard Maron
- Psychiatry, University of Tartu, Tartu, Estonia
- Department of Medicine, Centre for Neuropsychopharmacology,, Division of Brain Sciences, Imperial College London, London, UK
| | - Angelika Erhardt-Lehmann
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Tilo T Kircher
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Christiane A Melzig
- Psychology, Clinical Psychology, Experimental Psychopathology and Psychotherapy, University of Marburg, Marburg, Germany
- Psychology, Biological and Clinical Psychology, University of Greifswald, Greifswald, Germany
| | - Georg W Alpers
- School of Social Sciences, Department of Psychology, University of Mannheim, Mannheim, Germany
| | - Volker Arolt
- Department of Mental Health, Institute for Translational Psychiatry, University of Muenster, Muenster, Germany
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Center for Mental Health (DZPG), Partner Site Berlin, Berlin, Germany
| | - Jordan W Smoller
- Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry, Center for Precision Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Martin Preisig
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Nicholas G Martin
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Michelle K Lupton
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, Queensland University , Brisbane, Queensland, Australia
- Faculty of Health, Queensland University of technology, Queensland, Australia
| | - Annemarie I Luik
- Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt - Goethe University, Frankfurt, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Henrik Larsson
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Albertine J Oldehinkel
- Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Catharina A Hartman
- Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anna R Docherty
- School of Medicine, Psychiatry, University of Utah, Salt Lake City, Utah, USA
- School of Medicine, Psychiatry; Huntsman Mental Health Institute, University of Utah, Salt Lake City, Utah, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Hilary Coon
- School of Medicine, Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Rupert Conrad
- Department of Psychosomatic Medicine and Psychotherapy, University Hospital Münster, Münster, Germany
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jürgen Deckert
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Manuel Mattheisen
- Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - John M Hettema
- Psychiatry and Behavioral Sciences, Texas A&M University, Bryan, Texas, USA
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11
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Gustavson DE, Stern EF, Reynolds CA, Grotzinger AD, Corley RP, Wadsworth SJ, Rhee SH, Friedman NP. Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2024; 133:347-357. [PMID: 38722592 PMCID: PMC11232111 DOI: 10.1037/abn0000905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
The internalizing construct captures shared variance underlying risk for mood and anxiety disorders. Internalizing factors based on diagnoses (or symptoms) of major depressive disorder (MDD) and generalized anxiety disorder (GAD) are well established. Studies have also integrated self-reported measures of associated traits (e.g., questionnaires assessing neuroticism, worry, and rumination) onto these factors, despite having not tested the assumption that these measures truly capture the same sets of risk factors. This study examined the overlap among both sets of measures using converging approaches. First, using genomic structural equation modeling, we constructed internalizing factors based on genome-wide association studies (GWASs) of internalizing diagnoses (e.g., MDD) and traits associated with internalizing (neuroticism, loneliness, and reverse-scored subjective well-being). Results indicated the two factors were highly (rg = .79) but not perfectly genetically correlated (rg < 1.0, p < .001). Second, we constructed similar latent factors in a combined twin/adoption sample of adults from the Colorado Adoption/Twin Study of Lifespan Behavioral Development and Cognitive Aging. Again, both factors demonstrated strong overlap at the level of genetic (rg = .76, 95% confidence interval [CI] [0.40, 0.97]) and nonshared environmental influences (re = .80, 95% CI [0.53, 1.0]). Shared environmental influences were estimated near zero for both factors. Our findings are consistent with current frameworks of psychopathology, though they suggest there are some unique genetic influences captured by internalizing diagnosis compared to trait measures, with potentially more nonadditive genetic influences on trait measures. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Affiliation(s)
| | - Elisa F Stern
- Institute for Behavioral Genetics, University of Colorado Boulder
| | | | | | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado Boulder
| | | | - Soo H Rhee
- Institute for Behavioral Genetics, University of Colorado Boulder
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder
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12
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Legge SE, Pardiñas AF, Woolway G, Rees E, Cardno AG, Escott-Price V, Holmans P, Kirov G, Owen MJ, O’Donovan MC, Walters JTR. Genetic and Phenotypic Features of Schizophrenia in the UK Biobank. JAMA Psychiatry 2024; 81:681-690. [PMID: 38536179 PMCID: PMC10974692 DOI: 10.1001/jamapsychiatry.2024.0200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/07/2024] [Indexed: 04/04/2024]
Abstract
Importance Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings. Objective To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings. Design, Setting, and Participants This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023. Main Outcomes and Measures A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression. Results The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis. Conclusions and Relevance Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.
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Affiliation(s)
- Sophie E. Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Antonio F. Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Grace Woolway
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Alastair G. Cardno
- Leeds Institute of Health Sciences, Division of Psychological and Social Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Valentina Escott-Price
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Peter Holmans
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - George Kirov
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael J. Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael C. O’Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T. R. Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
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13
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Benstock SE, Weaver K, Hettema JM, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. Behav Genet 2024; 54:353-366. [PMID: 38869698 DOI: 10.1007/s10519-024-10187-w] [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: 01/12/2024] [Accepted: 05/29/2024] [Indexed: 06/14/2024]
Abstract
Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Affiliation(s)
- Sarah E Benstock
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Katherine Weaver
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - John M Hettema
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA.
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14
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Huang L, Tang S, Rietkerk J, Appadurai V, Krebs MD, Schork AJ, Werge T, Zuber V, Kendler K, Cai N. Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments. Biol Psychiatry 2024; 95:1110-1121. [PMID: 38056704 PMCID: PMC11139567 DOI: 10.1016/j.biopsych.2023.11.021] [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: 03/10/2023] [Revised: 11/06/2023] [Accepted: 11/26/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity. METHODS Using data from the UK Biobank (n = 41,948-109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms. RESULTS Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences. CONCLUSIONS MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.
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Affiliation(s)
- Lianyun Huang
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany
| | - Sonja Tang
- School of Public Health, Imperial College London, London, United Kingdom; MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Jolien Rietkerk
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark
| | - Morten Dybdahl Krebs
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark; Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, Arizona; Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark; Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Verena Zuber
- School of Public Health, Imperial College London, London, United Kingdom; MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Kenneth Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany.
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15
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Thorpe HHA, Fontanillas P, Meredith JJ, Jennings MV, Cupertino RB, Pakala S, Elson SL, Khokhar JY, Davis LK, Johnson EC, Palmer AA, Sanchez-Roige S. Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308946. [PMID: 38947071 PMCID: PMC11213095 DOI: 10.1101/2024.06.14.24308946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Shreya Pakala
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | | | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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16
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Farré X, Blay N, Espinosa A, Castaño-Vinyals G, Carreras A, Garcia-Aymerich J, Cardis E, Kogevinas M, Goldberg X, de Cid R. Decoding depression by exploring the exposome-genome edge amidst COVID-19 lockdown. Sci Rep 2024; 14:13562. [PMID: 38866890 PMCID: PMC11169603 DOI: 10.1038/s41598-024-64200-7] [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: 11/09/2023] [Accepted: 06/06/2024] [Indexed: 06/14/2024] Open
Abstract
Risk of depression increased in the general population after the COVID-19 pandemic outbreak. By examining the interplay between genetics and individual environmental exposures during the COVID-19 lockdown, we have been able to gain an insight as to why some individuals are more vulnerable to depression, while others are more resilient. This study, conducted on a Spanish cohort of 9218 individuals (COVICAT), includes a comprehensive non-genetic risk analysis, the exposome, complemented by a genomics analysis in a subset of 2442 participants. Depression levels were evaluated using the Hospital Anxiety and Depression Scale. Together with Polygenic Risk Scores (PRS), we introduced a novel score; Poly-Environmental Risk Scores (PERS) for non-genetic risks to estimate the effect of each cumulative score and gene-environment interaction. We found significant positive associations for PERSSoc (Social and Household), PERSLife (Lifestyle and Behaviour), and PERSEnv (Wider Environment and Health) scores across all levels of depression severity, and for PRSB (Broad depression) only for moderate depression (OR 1.2, 95% CI 1.03-1.40). On average OR increased 1.2-fold for PERSEnv and 1.6-fold for PERLife and PERSoc from mild to severe depression level. The complete adjusted model explained 16.9% of the variance. We further observed an interaction between PERSEnv and PRSB showing a potential mitigating effect. In summary, stressors within the social and behavioral domains emerged as the primary drivers of depression risk in this population, unveiling a mitigating interaction effect that should be interpreted with caution.
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Affiliation(s)
- Xavier Farré
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Natalia Blay
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Ana Espinosa
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Gemma Castaño-Vinyals
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Anna Carreras
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Judith Garcia-Aymerich
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Elisabeth Cardis
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Ximena Goldberg
- ISGlobal, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- CIBER Salud Mental (CIBERSAM), Madrid, Spain.
| | - Rafael de Cid
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
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17
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Gueltzow M, Lahtinen H, Bijlsma MJ, Myrskylä M, Martikainen P. Genetic propensity to depression and the role of partnership status. Soc Sci Med 2024; 351:116992. [PMID: 38772210 DOI: 10.1016/j.socscimed.2024.116992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024]
Abstract
Social relationships and genetic propensity are known to affect depression risk, but their joint effects are poorly understood. This study examined the association of a polygenic index for depression with time to antidepressant (AD) purchasing and the moderating role of partnership status. We analysed data from 30,192 Finnish individuals who participated in the FINRISK and Health 2000 and 2011 surveys and had register and medication data available. We measured genetic risk with a polygenic index (PGI) for depression. Depression was assessed through antidepressant purchases. We estimated an accelerated failure time model with partnership status as time-varying and different sets of confounder adjustments. The predicted cumulative hazard of antidepressant purchasing varied across PGI and partnership status. At follow-up year 10, being widowed was associated with the largest cumulative hazard of 0.34 (95%CI: 0.28-0.39) in the 80th and 0.20 (95%CI: 0.17-0.23) in the 20th PGI percentile, followed by divorced, single, married and cohabiting. Cohabiting was associated with a cumulative hazard of 0.19 (95%CI: 0.16-0.23) in the 80th and 0.11 (95%CI: 0.1-0.13) in the 20th PGI percentile. We found no evidence for an interaction between the PGI and partnership status. Results were robust to different model specifications, gender stratification, and the choice of PGI. Although antidepressant purchasing correlated with both PGI and partnership status, we found no evidence that partnership status could partially offset or amplify the association between the PGI for depression and antidepressant purchasing incidence.
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Affiliation(s)
- Maria Gueltzow
- Max Planck Institute for Demographic Research, Rostock, Germany; Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland.
| | - Hannu Lahtinen
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
| | - Maarten J Bijlsma
- Max Planck Institute for Demographic Research, Rostock, Germany; Unit PharmacoTherapy, -Epidemiology, and -Economics (PTEE), Groningen Research Institute of Pharmacy, University of Groningen, the Netherlands
| | - Mikko Myrskylä
- Max Planck Institute for Demographic Research, Rostock, Germany; Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
| | - Pekka Martikainen
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland; Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
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18
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Monosov IE, Zimmermann J, Frank MJ, Mathis MW, Baker JT. Ethological computational psychiatry: Challenges and opportunities. Curr Opin Neurobiol 2024; 86:102881. [PMID: 38696972 PMCID: PMC11162904 DOI: 10.1016/j.conb.2024.102881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 04/02/2024] [Accepted: 04/03/2024] [Indexed: 05/04/2024]
Abstract
Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring.
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Affiliation(s)
- Ilya E. Monosov
- Departments of Neuroscience, Biomedical Engineering, Electrical Engineering, and Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Michael J. Frank
- Carney Center for Computational Brain Science, Brown University, Providence, RI, USA
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19
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Zhang Y, Li Y, Peila R, Wang T, Xue X, Kaplan RC, Dannenberg AJ, Qi Q, Rohan TE. Associations of Lifestyle and Genetic Risks with Obesity and Related Chronic Diseases in the UK Biobank: A Prospective Cohort Study. Am J Clin Nutr 2024; 119:1514-1522. [PMID: 38677521 PMCID: PMC11251215 DOI: 10.1016/j.ajcnut.2024.04.025] [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: 11/03/2023] [Revised: 04/01/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024] Open
Abstract
BACKGROUND Interplay between lifestyle risk scores (LRSs) and genetic risk scores (GRSs) on obesity and related chronic diseases are underinvestigated and necessary for understanding obesity causes and developing prevention strategies. OBJECTIVES This study aimed to investigate independent and joint associations and interactions of LRS and GRS with obesity prevalence and risks of diabetes, cardiovascular disease (CVD), and obesity-related cancer. METHODS In this cohort study of 444,957 UK Biobank participants [age: 56.5 ± 8.1 y; BMI (in kg/m2): 27.4 ± 4.7], LRS included physical activity, dietary score, sedentary behavior, sleep duration, and smoking (range: 0-20, each factor had 5 levels). GRS was calculated based on 941 genetic variants related to BMI. Both scores were categorized into quintiles. Obesity (n = 106,301) was defined as baseline BMI ≥30. Incident diabetes (n = 16,311), CVD (n = 18,076), and obesity-related cancer (n = 17,325) were ascertained through linkage to registries over a median of 12-y follow-up. RESULTS The LRS and GRS were independently positively associated with all outcomes. Additive interactions of LRS and GRS were observed for all outcomes (P < 0.021). Comparing the top with bottom LRS quintile, prevalence differences (95% CIs) for obesity were 17.8% (15.9%, 19.7%) in the top GRS quintile and 10.7% (8.3%, 13.1%) in the bottom GRS quintile; for diabetes, CVD, and obesity-related cancer, incidence rate differences associated with per SD increase in LRS were greater in the top than that in the bottom GRS quintile. Participants from top quintiles of both LRS and GRS had 6.16-fold, 3.81-fold, 1.56-fold, and 1.44-fold higher odds/risks of obesity, diabetes, CVD, and obesity-related cancer, respectively, than those from bottom quintiles of both scores. CONCLUSIONS Higher LRS was associated with higher obesity prevalence and risks of related chronic diseases regardless of GRS, highlighting the broad benefits of healthy lifestyles. Additive gene-lifestyle interactions emphasize the public health importance of lifestyle interventions among people with high genetic risks.
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Affiliation(s)
- Yanbo Zhang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Yang Li
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Rita Peila
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Xiaonan Xue
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | | | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States.
| | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States.
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20
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Koch E, Kämpe A, Alver M, Sigurðarson S, Einarsson G, Partanen J, Smith RL, Jaholkowski P, Taipale H, Lähteenvuo M, Steen NE, Smeland OB, Djurovic S, Molden E, Sigurdsson E, Stefánsson H, Stefánsson K, Palotie A, Milani L, O'Connell KS, Andreassen OA. Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study. Neuropsychopharmacology 2024; 49:1113-1119. [PMID: 38184734 PMCID: PMC11109158 DOI: 10.1038/s41386-023-01792-0] [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: 08/29/2023] [Revised: 11/10/2023] [Accepted: 12/19/2023] [Indexed: 01/08/2024]
Abstract
Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.
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Affiliation(s)
- Elise Koch
- 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.
| | - Anders Kämpe
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Maris Alver
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | | | - Juulia Partanen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Robert L Smith
- 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 Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - 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
| | - Heidi Taipale
- Niuvanniemi Hospital, Kuopio, Finland
- Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | | | - 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
| | - 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
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
- Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Engilbert Sigurdsson
- Faculty of Medicine, University of Iceland and Department of Psychiatry, Landspitali, National University Hospital, Reykjavík, Iceland
| | | | | | - Aarno Palotie
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - 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
| | - 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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21
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Capalbo A, de Wert G, Mertes H, Klausner L, Coonen E, Spinella F, Van de Velde H, Viville S, Sermon K, Vermeulen N, Lencz T, Carmi S. Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations. Hum Reprod Update 2024:dmae012. [PMID: 38805697 DOI: 10.1093/humupd/dmae012] [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: 01/10/2024] [Revised: 03/25/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. OBJECTIVE AND RATIONALE This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. SEARCH METHODS We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. OUTCOMES The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. WIDER IMPLICATIONS The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.
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Affiliation(s)
- Antonio Capalbo
- Juno Genetics, Department of Reproductive Genetics, Rome, Italy
- Center for Advanced Studies and Technology (CAST), Department of Medical Genetics, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Guido de Wert
- Department of Health, Ethics & Society, CAPHRI-School for Public Health and Primary Care and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Heidi Mertes
- Department of Philosophy and Moral Sciences, Ghent University, Ghent, Belgium
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Liraz Klausner
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Edith Coonen
- Departments of Clinical Genetics and Reproductive Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
- School for Oncology and Developmental Biology, GROW, Maastricht University, Maastricht, The Netherlands
| | - Francesca Spinella
- Eurofins GENOMA Group Srl, Molecular Genetics Laboratories, Department of Scientific Communication, Rome, Italy
| | - Hilde Van de Velde
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
- Brussels IVF, UZ Brussel, Brussel, Belgium
| | - Stephane Viville
- Laboratoire de Génétique Médicale LGM, Institut de Génétique Médicale d'Alsace IGMA, INSERM UMR 1112, Université de Strasbourg, France
- Laboratoire de Diagnostic Génétique, Unité de Génétique de l'infertilité (UF3472), Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Karen Sermon
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
| | | | - Todd Lencz
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
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22
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Daskalakis NP, Iatrou A, Chatzinakos C, Jajoo A, Snijders C, Wylie D, DiPietro CP, Tsatsani I, Chen CY, Pernia CD, Soliva-Estruch M, Arasappan D, Bharadwaj RA, Collado-Torres L, Wuchty S, Alvarez VE, Dammer EB, Deep-Soboslay A, Duong DM, Eagles N, Huber BR, Huuki L, Holstein VL, Logue ΜW, Lugenbühl JF, Maihofer AX, Miller MW, Nievergelt CM, Pertea G, Ross D, Sendi MSE, Sun BB, Tao R, Tooke J, Wolf EJ, Zeier Z, Berretta S, Champagne FA, Hyde T, Seyfried NT, Shin JH, Weinberger DR, Nemeroff CB, Kleinman JE, Ressler KJ. Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood. Science 2024; 384:eadh3707. [PMID: 38781393 PMCID: PMC11203158 DOI: 10.1126/science.adh3707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.
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Affiliation(s)
- Nikolaos P. Daskalakis
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Artemis Iatrou
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Chris Chatzinakos
- McLean Hospital; Belmont, MA, 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, 11203, USA
- VA New York Harbor Healthcare System, Brooklyn, NY, 11209, USA
| | - Aarti Jajoo
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Clara Snijders
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Dennis Wylie
- Center for Biomedical Research Support, The University of Texas at Austin; Austin, TX, 78712, USA
| | - Christopher P. DiPietro
- McLean Hospital; Belmont, MA, 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Ioulia Tsatsani
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
- Department of Psychiatry and Neuropsychology, School for Mental Health, and Neuroscience (MHeNs), Maastricht University, Maastricht, 6229 ER, The Netherlands
| | | | - Cameron D. Pernia
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Marina Soliva-Estruch
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
- Department of Psychiatry and Neuropsychology, School for Mental Health, and Neuroscience (MHeNs), Maastricht University, Maastricht, 6229 ER, The Netherlands
| | - Dhivya Arasappan
- Center for Biomedical Research Support, The University of Texas at Austin; Austin, TX, 78712, USA
| | - Rahul A. Bharadwaj
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Stefan Wuchty
- Departments of Computer Science, University of Miami, Miami, FL, 33146, USA
- Department of Biology, University of Miami, Miami, FL, 33146, USA
| | - Victor E. Alvarez
- Department of Neurology, Boston University, Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
- VA Bedford Healthcare System, Bedford, MA, 01730, USA
- National Posttraumatic Stress Disorder Brain Bank, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Eric B Dammer
- Department of Biochemistry, Center for Neurodegenerative Disease, Emory School of Medicine; Atlanta GA, 30329, USA
| | - Amy Deep-Soboslay
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Duc M. Duong
- Department of Biochemistry, Center for Neurodegenerative Disease, Emory School of Medicine; Atlanta GA, 30329, USA
| | - Nick Eagles
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Bertrand R. Huber
- Department of Neurology, Boston University, Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
- National Posttraumatic Stress Disorder Brain Bank, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Louise Huuki
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Vincent L Holstein
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Μark W. Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Justina F. Lugenbühl
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
- Department of Psychiatry and Neuropsychology, School for Mental Health, and Neuroscience (MHeNs), Maastricht University, Maastricht, 6229 ER, The Netherlands
| | - Adam X. Maihofer
- Department of Psychiatry, University of California San Diego; La Jolla, CA, 92093, USA
- Center for Excellence in Stress and Mental Health, Veterans Affairs San Diego Healthcare System; San Diego, CA, 92161, USA
- Research Service, Veterans Affairs San Diego Healthcare System; San Diego, CA, 92161, USA
| | - Mark W. Miller
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego; La Jolla, CA, 92093, USA
- Center for Excellence in Stress and Mental Health, Veterans Affairs San Diego Healthcare System; San Diego, CA, 92161, USA
- Research Service, Veterans Affairs San Diego Healthcare System; San Diego, CA, 92161, USA
| | - Geo Pertea
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Deanna Ross
- Department of Psychology, University of Texas at Austin; Austin, TX, 78712, USA
| | - Mohammad S. E Sendi
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | | | - Ran Tao
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - James Tooke
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Erika J. Wolf
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Zane Zeier
- Department of Psychiatry & Behavioral Sciences, Center for Therapeutic Innovation, University of Miami Miller School of Medicine; Miami, FL, 33136, USA
| | | | - Sabina Berretta
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | | | - Thomas Hyde
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Center for Neurodegenerative Disease, Emory School of Medicine; Atlanta GA, 30329, USA
| | - Joo Heon Shin
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
| | - Daniel R. Weinberger
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
| | - Charles B. Nemeroff
- Department of Psychology, University of Texas at Austin; Austin, TX, 78712, USA
- Department of Psychiatry and Behavioral Sciences, University of Texas at Austin; Austin, TX, 78712, USA
| | - Joel E. Kleinman
- Lieber Institute for Brain Development; Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine; Baltimore, MD, 21205, USA
| | - Kerry J. Ressler
- McLean Hospital; Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard Medical School; Boston, MA, 02115, USA
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23
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Pasman JA, Bergstedt J, Harder A, Gong T, Xiong Y, Hägg S, Fang F, Treur JL, Choi KW, Sullivan PF, Lu Y. Causes and consequences of major depressive disorder: An encompassing Mendelian randomization study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.21.24307678. [PMID: 38826420 PMCID: PMC11142270 DOI: 10.1101/2024.05.21.24307678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background Major depressive disorder (MDD) is a prevalent and debilitating disorder that has been associated with a range of risk factors and outcomes. Causal pathways between MDD and other traits can be studied using genetic variants as instrumental variables. Methods A literature review was conducted to identify 201 MDD-associated traits. For 115 traits, there were well-powered genome-wide association study (GWAS) results available that could be used to assess the genetic correlation with MDD. Of these, there were 89 meeting criteria for investigating causal associations in both directions using two-sample Mendelian randomization (TSMR). Of the traits that were not captured by GWAS, 43 could be included as outcomes of MDD using one-sample MR (OSMR). A range of methods and sensitivity tests was applied to gauge robustness of results, together with statistical power analyses to aid interpretation. Outcomes Moderate to strong genetic overlap was found between MDD and most traits. Support for causal effects of MDD liability were found for circadian, cognitive, diet, medical disease, endocrine, functional, inflammatory, metabolic, mortality, physical activity, reproduction, risk behavior, social, socioeconomic, and suicide outcomes. Most associations were bidirectional, although there was less evidence for diet, disease, and endocrine traits causing MDD risk. Results were robust across sensitivity analyses. Interpretation This study provides a systematic overview of traits putatively causally related to MDD, confirming previous findings as well as identifying new associations. Our results highlight the importance of MDD as a risk factor cross-cutting across medical, functional, and psychosocial domains and emphasize the need for concerted efforts at reducing this highly prevalent disorder.
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Affiliation(s)
- Joëlle A. Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Genetic Epidemiology, Meibergdreef 9, Amsterdam, The Netherlands
| | - Jacob Bergstedt
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
- Institute of Environmental Medicine, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Arvid Harder
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Ying Xiong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Fang Fang
- Institute of Environmental Medicine, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
| | - Jorien L. Treur
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Genetic Epidemiology, Meibergdreef 9, Amsterdam, The Netherlands
| | - Karmel W. Choi
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
- Departments of Genetics and Psychiatry, UNC Chapel Hill, NC, USA
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels Väg 12, Stockholm, Sweden
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24
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Voorhies K, Hecker J, Lee S, Hahn G, Prokopenko D, McDonald ML, Wu AC, Wu A, Hokanson JE, Cho MH, Lange C, Hoth KF, Lutz SM. Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex. Genes (Basel) 2024; 15:565. [PMID: 38790194 PMCID: PMC11120779 DOI: 10.3390/genes15050565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 04/20/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
Depression is heritable, differs by sex, and has environmental risk factors such as cigarette smoking. However, the effect of single nucleotide polymorphisms (SNPs) on depression through cigarette smoking and the role of sex is unclear. In order to examine the association of SNPs with depression and smoking in the UK Biobank with replication in the COPDGene study, we used counterfactual-based mediation analysis to test the indirect or mediated effect of SNPs on broad depression through the log of pack-years of cigarette smoking, adjusting for age, sex, current smoking status, and genetic ancestry (via principal components). In secondary analyses, we adjusted for age, sex, current smoking status, genetic ancestry (via principal components), income, education, and living status (urban vs. rural). In addition, we examined sex-stratified mediation models and sex-moderated mediation models. For both analyses, we adjusted for age, current smoking status, and genetic ancestry (via principal components). In the UK Biobank, rs6424532 [LOC105378800] had a statistically significant indirect effect on broad depression through the log of pack-years of cigarette smoking (p = 4.0 × 10-4) among all participants and a marginally significant indirect effect among females (p = 0.02) and males (p = 4.0 × 10-3). Moreover, rs10501696 [GRM5] had a marginally significant indirect effect on broad depression through the log of pack-years of cigarette smoking (p = 0.01) among all participants and a significant indirect effect among females (p = 2.2 × 10-3). In the secondary analyses, the sex-moderated indirect effect was marginally significant for rs10501696 [GRM5] on broad depression through the log of pack-years of cigarette smoking (p = 0.01). In the COPDGene study, the effect of an SNP (rs10501696) in GRM5 on depressive symptoms and medication was mediated by log of pack-years (p = 0.02); however, no SNPs had a sex-moderated mediated effect on depressive symptoms. In the UK Biobank, we found SNPs in two genes [LOC105378800, GRM5] with an indirect effect on broad depression through the log of pack-years of cigarette smoking. In addition, the indirect effect for GRM5 on broad depression through smoking may be moderated by sex. These results suggest that genetic regions associated with broad depression may be mediated by cigarette smoking and this relationship may be moderated by sex.
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Affiliation(s)
- Kirsten Voorhies
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sanghun Lee
- Division of Medicine, Department of Medical Consilience, Graduate School, Dankook University, Yongin 16890, Republic of Korea
| | - Georg Hahn
- Brigham and Women’s Hospital, Division of Pharmacoepidemiology and Pharmacoeconomics, and Department of Medicine, Harvard Medical School, Boston, MA 02120, USA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Merry-Lynn McDonald
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35233, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | | | - Ann Wu
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - John E. Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Karin F. Hoth
- Department of Psychiatry and Iowa Neuroscience Institute, University of Iowa, Iowa City, IA 52242, USA
| | - Sharon M. Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
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25
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Sanchez-Ruiz JA, Coombes BJ, Pazdernik VM, Melhuish Beaupre LM, Jenkins GD, Pendegraft RS, Batzler A, Ozerdem A, McElroy SL, Gardea-Resendez MA, Cuellar-Barboza AB, Prieto ML, Frye MA, Biernacka JM. Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data. Mol Psychiatry 2024:10.1038/s41380-024-02530-8. [PMID: 38548982 DOI: 10.1038/s41380-024-02530-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 02/21/2024] [Accepted: 03/13/2024] [Indexed: 06/14/2024]
Abstract
Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.
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Affiliation(s)
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Greg D Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Anthony Batzler
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Aysegul Ozerdem
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Susan L McElroy
- Lindner Center of HOPE/University of Cincinnati, Cincinnati, OH, USA
| | - Manuel A Gardea-Resendez
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Alfredo B Cuellar-Barboza
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Miguel L Prieto
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Faculty of Medicine, Universidad de Los Andes, Santiago, Chile
- Mental Health Service, Clínica Universidad de los Andes, Santiago, Chile
| | - Mark A Frye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Joanna M Biernacka
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
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26
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Strom NI, Gerring ZF, Galimberti M, Yu D, Halvorsen MW, Abdellaoui A, Rodriguez-Fontenla C, Sealock JM, Bigdeli T, Coleman JR, Mahjani B, Thorp JG, Bey K, Burton CL, Luykx JJ, Zai G, Alemany S, Andre C, Askland KD, Banaj N, Barlassina C, Nissen JB, Bienvenu OJ, Black D, Bloch MH, Boberg J, Børte S, Bosch R, Breen M, Brennan BP, Brentani H, Buxbaum JD, Bybjerg-Grauholm J, Byrne EM, Cabana-Dominguez J, Camarena B, Camarena A, Cappi C, Carracedo A, Casas M, Cavallini MC, Ciullo V, Cook EH, Crosby J, Cullen BA, De Schipper EJ, Delorme R, Djurovic S, Elias JA, Estivill X, Falkenstein MJ, Fundin BT, Garner L, German C, Gironda C, Goes FS, Grados MA, Grove J, Guo W, Haavik J, Hagen K, Harrington K, Havdahl A, Höffler KD, Hounie AG, Hucks D, Hultman C, Janecka M, Jenike E, Karlsson EK, Kelley K, Klawohn J, Krasnow JE, Krebs K, Lange C, Lanzagorta N, Levey D, Lindblad-Toh K, Macciardi F, Maher B, Mathes B, McArthur E, McGregor N, McLaughlin NC, Meier S, Miguel EC, Mulhern M, Nestadt PS, Nurmi EL, O’Connell KS, Osiecki L, Ousdal OT, Palviainen T, Pedersen NL, Piras F, Piras F, Potluri S, Rabionet R, Ramirez A, Rauch S, Reichenberg A, Riddle MA, Ripke S, Rosário MC, Sampaio AS, Schiele MA, Skogholt AH, Sloofman LGSG, Smit J, Soler AM, Thomas LF, Tifft E, Vallada H, van Kirk N, Veenstra-VanderWeele J, Vulink NN, Walker CP, Wang Y, Wendland JR, Winsvold BS, Yao Y, Zhou H, Agrawal A, Alonso P, Berberich G, Bucholz KK, Bulik CM, Cath D, Denys D, Eapen V, Edenberg H, Falkai P, Fernandez TV, Fyer AJ, Gaziano JM, Geller DA, Grabe HJ, Greenberg BD, Hanna GL, Hickie IB, Hougaard DM, Kathmann N, Kennedy J, Lai D, Landén M, Le Hellard S, Leboyer M, Lochner C, McCracken JT, Medland SE, Mortensen PB, Neale BM, Nicolini H, Nordentoft M, Pato M, Pato C, Pauls DL, Piacentini J, Pittenger C, Posthuma D, Ramos-Quiroga JA, Rasmussen SA, Richter MA, Rosenberg DR, Ruhrmann S, Samuels JF, Sandin S, Sandor P, Spalletta G, Stein DJ, Stewart SE, Storch EA, Stranger BE, Turiel M, Werge T, Andreassen OA, Børglum AD, Walitza S, Hveem K, Hansen BK, Rück CP, Martin NG, Milani L, Mors O, Reichborn-Kjennerud T, Ribasés M, Kvale G, Mataix-Cols D, Domschke K, Grünblatt E, Wagner M, Zwart JA, Breen G, Nestadt G, Kaprio J, Arnold PD, Grice DE, Knowles JA, Ask H, Verweij KJ, Davis LK, Smit DJ, Crowley JJ, Scharf JM, Stein MB, Gelernter J, Mathews CA, Derks EM, Mattheisen M. Genome-wide association study identifies 30 obsessive-compulsive disorder associated loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.13.24304161. [PMID: 38712091 PMCID: PMC11071577 DOI: 10.1101/2024.03.13.24304161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.
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Affiliation(s)
- Nora I. Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychiatric Phenomics and Genomics (IPPG), Ludwig-Maximilians University Munich, Munich, Germany
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Zachary F. Gerring
- Department of Mental Health and Neuroscience, Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Department of Population Health and Immunity, Healthy Development and Ageing, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Marco Galimberti
- Department of Psychiatry, Human Genetics, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Dongmei Yu
- Department of Center for Genomic Medicine, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Matthew W. Halvorsen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Cristina Rodriguez-Fontenla
- CIMUS (Center for Research in Molecular Medicine and Chronic Diseases), Genomics and Bioinformatics, University of Santiago de Compostela, Santiago de Compostela, A Coruña, Spain
- Grupo de Medicina Xenómica, Genetics, FIDIS (Instituto de Investigación Sanitaria de Santiago de Compostela), Santiago de Compostela, A Coruña, Spain
| | - Julia M. Sealock
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Tim Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- VA NY Harbor Healthcare System, Brooklyn, NY, USA
| | - Jonathan R. Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Behrang Mahjani
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jackson G. Thorp
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, School of Biomedical Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Katharina Bey
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Christie L. Burton
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Jurjen J. Luykx
- Department of Psychiatry, Brain, University Medical Center Utrecht, Utrecht, The Netherlands
- Second opinion outpatient clinic, GGNet, Warnsveld, The Netherlands
| | - Gwyneth Zai
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health,, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Silvia Alemany
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d’Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
| | - Christine Andre
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Kathleen D. Askland
- Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Judith Becker Nissen
- Department of Child and Adolescent Psychiatry, Aarhus University Hospital, Psychiatry, Aarhus, Denmark
- Institute of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - O. Joseph Bienvenu
- Department of Psychiatry and Behavioral Sciences, General Hospital Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Donald Black
- Departments of Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Michael H. Bloch
- Department of Child Study Center and Psychiatry, Yale University, New Haven, CT, USA
| | - Julia Boberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
| | - Sigrid Børte
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Rosa Bosch
- Department of Child and Adolescent Mental Health, Hospital Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Instituto de Salut Carlos III, Centro de Investigación Biomédica en Red de Salut Mental (CIBERSAM), Madrid, Spain
| | - Michael Breen
- Department of Psychiatry, Icahn School of Medicine At Mount Sinai, New York, NY, USA
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine At Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine At Mount Sinai, New York, NY, USA
| | - Brian P. Brennan
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Helena Brentani
- Department of Psychiatry, Universidade De São Paulo, São Paulo, Brazil
| | - Joseph D. Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Enda M. Byrne
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
| | - Judit Cabana-Dominguez
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d’Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
| | - Beatriz Camarena
- Pharmacogenetics Department, Investigaciones Clínicas, Instituto Nacional de Psiquiatría Ramon de la Fuente Muñiz, Mexico City, México
| | | | - Carolina Cappi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
- Department of Psychiatry, University of Sao Paulo, Sao Paulo, Brazil
| | - Angel Carracedo
- Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Genomics and Bioinformatics Group, University of Santiago de Compostela, Santiago de Compostela, Spain
- Galiician Foundation of Genomic Medicine, Grupo de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago -IDIS-, Santiago de Compostela, Spain
- Medicina Genómica, Centro de Investigación Biomédica en Red, Enfermedades Raras (CIBERER), Santiago de Compostela, Spain
| | - Miguel Casas
- Programa MIND Escoles, Hospital Sant Joan de Déu , Esplugues de Llobregat, Barcelona, Spain
- Departamento de Psiquiatría y Medicina Legal, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | | | - Valentina Ciullo
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Edwin H. Cook
- Department of Psychiatry, University of Illinois Chicago, Chicago, IL, USA
| | - Jesse Crosby
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Bernadette A. Cullen
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Medical Institutions, Baltimore , MD, USA
- Department of Mental Health, Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elles J. De Schipper
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
| | - Richard Delorme
- Child and Adolesccent Psycchiatry Department, APHP, Paris, France
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Jason A. Elias
- Psychiatry, McLean Hospital OCDI, Harvard Medical School, Belmont, MA, USA
- Adult Psychological Services, CBTeam LLC, Lexington, MA, USA
| | - Xavier Estivill
- qGenomics (Quantitative Genomics Laboratories), Esplugues de Llobregat, Barcelona, Spain
| | - Martha J. Falkenstein
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Bengt T. Fundin
- Department of Medical Epidemiology and Biostatistics, Center for Eating Disorders Innovation, Karolinska Institutet, Stockholm, Sweden
| | - Lauryn Garner
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | | | - Christina Gironda
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Fernando S. Goes
- Department of Psychiatry, Johns Hopkins University, Baltimore, MD, USA
| | - Marco A. Grados
- Department of Psychiatry and Behavioral Sciences, Child & Adolescent Psychiatry, Johns Hopkins University, Baltimore, MD, 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, Denmark
| | - Wei Guo
- Genetic Epidemiology Research Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Bergen Center for Brain Plasticity, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Kristen Hagen
- Department of Psychiatry, Møre og Romsdal Hospital Trust, Molde, Norway
- Bergen Center for Brain Plasticity, Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Mental Health, Norwegian University for Science and Technology, Trondheim, Norway
| | - Kelly Harrington
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Alexandra Havdahl
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Kira D. Höffler
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway
- Department of Medical Genetics, Dr. Einar Martens Research Group for Biological Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Ana G. Hounie
- Department of Psychiatry, University of São Paulo, São Paulo, Brazil
| | - Donald Hucks
- Department of Medicine, Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christina Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Magdalena Janecka
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Eric Jenike
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Elinor K. Karlsson
- Department of Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
- Department of Vertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kara Kelley
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Julia Klawohn
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Medicine, MSB Medical School Berlin, Berlin, Germany
| | - Janice E. Krasnow
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | | | - Daniel Levey
- Department of Psychiatry, Yale University, West Haven, CT, USA
- Office of Research & Development, United States Department of Veterans Affairs, West Haven, CT, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Vertebrate Genomics, Broad Institute, Cambridge, MA, USA
| | - Fabio Macciardi
- Department of Psychiatry, University of California, Irvine (UCI), Irvine, CA, USA
| | - Brion Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brittany Mathes
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Evonne McArthur
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Nicole C. McLaughlin
- Department of Psychiatry & Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
- Butler Hospital, Providence, RI, USA
| | - Sandra Meier
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Euripedes C. Miguel
- Department of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Maureen Mulhern
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Paul S. Nestadt
- Department of Psychiatry and Behavioral Science, Johns Hopkins University, Baltimore, MD, USA
| | - Erika L. Nurmi
- Department of Psychiatry and Biobehavioral Sciences, Division of Child and Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kevin S. O’Connell
- Department of Clinical Medicine, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- NORMENT, University of Oslo, Oslo, Norway
| | - Lisa Osiecki
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Harvard Medical School, Boston, MA, USA
| | - Olga Therese Ousdal
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Department of Biomedicine, Haukeland University Hospital, Bergen, Norway
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Department of Clinical Neuroscience and Neurorehabilitation, Neuropsychiatry Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Sriramya Potluri
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Raquel Rabionet
- Department of Genetics, microbiology and statistics, IBUB, Universitat de Barcelona, Barcelona, Spain
- CIBERER, Centro de investigación biomédica en red, Madrid, Spain
- Department of Human Molecular Genetics, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Alfredo Ramirez
- Department of Psychiatry and Psychotherapy, Division of Neurogenetics and Molecular Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
- DZNE Bonn, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
- Cologne Excellence Cluster for Stress Responses in Ageing-associated diseases (CECAD), University of Cologne, Cologne, Germany
| | - Scott Rauch
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Abraham Reichenberg
- Department of Mental disorders, Norwegian Institute of Public Health, New York, NY, USA
| | - Mark A. Riddle
- Department of Psychiatry and Behavioral Sciences, Child and Adolescent, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- site Berlin-Potsdam, German Center for Mental Health (DZPG), Berlin, Germany
| | - Maria C. Rosário
- Department of Psychiatry, Child and Adolescent Psychiatry Unit (UPIA), Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Aline S. Sampaio
- Department of Neurosciences and Mental Health, Medical School, Federal University of Bahia, Salvador, Brazil
| | - Miriam A. Schiele
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Freiburg, Medical Center - University of Freiburg, Freiburg, Germany
| | - Anne Heidi Skogholt
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Trondheim, Norway
| | | | - Jan Smit
- Department of Psychiatry, Faculty of Medicine, Locaion Vumc, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Artigas María Soler
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d’Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Spain
| | - Laurent F. Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, K. G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St.Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Eric Tifft
- Obsessive-Compulsive Disorder Institute, McLean Hospital, Belmont, MA, USA
| | - Homero Vallada
- Department of Psychiatry, Universidade de Sao Paulo, São Paulo, Brazil
- Department of Molecular Medicine and Surgery, CMM, Karolinska Institutet, Stockholm, Sweden
| | - Nathanial van Kirk
- OCD Institute, Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Belmont, MA, USA
| | - Jeremy Veenstra-VanderWeele
- Department of Psychiatry, Division of Child and Adolescent Psychiatry, Columbia University, New York, NY, USA
- Department of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Nienke N. Vulink
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Ying Wang
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jens R. Wendland
- Laboratory of Clinical Science, NIMH Intramural Research Program, Bethesda, MD, USA
| | - Bendik S. Winsvold
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Yin Yao
- Department of Computional Biology, Institute of Life Science, Fudan University, Fudan, China
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA
| | | | | | | | | | | | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Pino Alonso
- Department of Psychiatry, OCD Clinical and Research Unit, Bellvitge Hospital, Barcelona, Spain
- Department of Clinical Sciences, University of Barcelona, Barcelona, Spain
- Department of Psychiatry and Mental Health, Bellvitge Biomedical Research Institute IDIBELLL, Barcelona, Spain
- CIBERSAM, Mental Health Network Biomedical Research Center, Madrid, Spain
| | - Götz Berberich
- Psychosomatic Department, Windach Hospital of Neurobehavioural Research and Therapy, Windach, Germany
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington U. School of Medicine, St Louis, MO, USA
| | - Cynthia M. Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danielle Cath
- Departments of Rijksuniversiteit Groningen and Psychiatry, University Medical Center Groninge, Groningen, The Netherlands
- Department of Specialized Training, Drenthe Mental Health Care Institute, Groningen, The Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Institute of The Royal Netherlands Academy of Arts and Sciences (NIN-KNAW), Amsterdam, The Netherlands
| | - Valsamma Eapen
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, NSW, Australia
- Academic Unit of Child Psychiatry South-West Sydney (AUCS), South-West Sydney Clinical School, SWSLHD & Ingham Institute, Sydney, NSW, Australia
| | - Howard Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
- Department of Psychiatry, Max Planck Institute, Munich, Germany
| | - Thomas V. Fernandez
- Child Study Center and Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Abby J. Fyer
- Department of Psychiatry, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, , Columbia University Medical Center, New York, NY, USA
| | - J M. Gaziano
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Mass General Brigham, Boston, MA, USA
| | - Dan A. Geller
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Child Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Hans J. Grabe
- Department of Psychiatry & Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Benjamin D. Greenberg
- COBRE Center on Neuromodulation, Butler Hospital, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
| | - Gregory L. Hanna
- Department of Psychiatry, Child and Adolescent Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Ian B. Hickie
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - David M. Hougaard
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - Norbert Kathmann
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - James Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Stéphanie Le Hellard
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Bergen Center for brain plasticity, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Marion Leboyer
- Department of Addictology and Psychiatry, Univ Paris Est Créteil, AP-HP, Inserm, Paris, France
| | - Christine Lochner
- Department of Psychiatry, SA MRC Unit on Risk and Resilience in Mental Disorders, Stellenbosch University, Stellenbosch, South Africa
| | - James T. McCracken
- Department of Psychiatry and Biobehavioral Sciences, Division of Child and Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sarah E. Medland
- Department of Mental Health, Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Preben B. Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, , Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Humberto Nicolini
- Department of Psychiatry, Psychiatry, Carracci Medical Group, Mexico City, México
- Psiquiatría, Instituto Nacional de Medicina Genómica, Mexico City, México
| | - Merete Nordentoft
- Mental Health Center Copenhagen, Copenhagen Research Center for Mental Health, Mental Health services in the Capital Region of Denmark, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Michele Pato
- Department of Psychiatry, Rutgers University, Piscataway, NJ, USA
| | - Carlos Pato
- Department of Psychiatry, Rutgers University, Piscataway, NJ, USA
| | - David L. Pauls
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - John Piacentini
- Department of Psychiatry and Biobehavioral Sciences, Child and Adolescent Psychiatry, UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | | | - Danielle Posthuma
- Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatric, Section Complex Trait Genetics, VU Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Josep Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d’Hebron, Barcelona, Spain
- Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Steven A. Rasmussen
- Department of Psychiatry & Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
| | - Margaret A. Richter
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - David R. Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Child and Adolescent Psychiatry, Wayne State University School of Medicine, Detroit, MI, USA
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Jack F. Samuels
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sven Sandin
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Sandor
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Division of Neuropsychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Dan J. Stein
- Dept of Psychiatry & Neuroscience Institute, SAMRC Unit on Risk & Reslience in Mental Disorders, University of Cape Town, Cape Town, Western Cape, South Africa
| | - S. Evelyn Stewart
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada
- British Columbia Mental Health and Substance Use Services Research Institute (BCMHSUS), Vancouver, BC, Canada
| | - Eric A. Storch
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Barbara E. Stranger
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Copenhagen University Hospital, Mental Health Services (RHP), Copenhagen, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Ole A. Andreassen
- Institute of Clinical Medicine, NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Center for Precision Psychiatry, Oslo University Hospital, Oslo, , Norway
| | - Anders D. Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich (PUK), University of Zurich, Zürich, Switzerland
- Neuroscience Center Zurich, University of Zurich and the ETH Zuric, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Kristian Hveem
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bjarne K. Hansen
- Bergen Center for Brain Plasticity (BCBP), Psychiatry, Haukeland University Hospital, Bergen, Norway
- Centre for Crisis Psychology, Psychology, University of Bergen, Bergen, Norway
| | - Christian P. Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
| | - Nicholas G. Martin
- Department of Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ole Mors
- Psychosis Reasearch Unit, Aarhus University Hospital - Psychiatry, 8200 Aarhus N, Denmark
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Marta Ribasés
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d’Hebron , Barcelona, Spain
| | - Gerd Kvale
- Bergen Center for Brain Plasticity, Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Psychology, Faculty of Psychology, University of Bergen, Bergen, Vestland
| | - David Mataix-Cols
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
| | - Katharina Domschke
- Department of Psychiatry, University of Freiburg - Medical Faculty, Freiburg, Germany
- German Center for Mental Health (DZPG), Partner Site Berlin, Berlin, Germany
| | - Edna Grünblatt
- Neuroscience Center Zurich, University of Zurich and the ETH Zuric, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich (PUK), University of Zurich, Zürich, Schweiz
| | - Michael Wagner
- Departments of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - John-Anker Zwart
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Innovation, Clinical Neuroscience, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Gerome Breen
- Social, Genetic, and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Gerald Nestadt
- Department of Psychiatry and Behavioral Science, Johns Hopkins University, Baltimore, MD, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Paul D. Arnold
- Department of Psychiatry, The Mathison Centre for Mental Health Research & Education, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, ON, Canada
| | - Dorothy E. Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - James A. Knowles
- Department of Genetics, Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA
| | - Helga Ask
- PsychGen Center for Genetic Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Karin J. Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Lea K. Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dirk J. Smit
- Department of Psychiatry, Amsterdam UMC location AMC, Amsterdam, The Netherlands
| | - James J. Crowley
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Services, Region Stockholm , Stockholm, Sweden
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeremiah M. Scharf
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Murray B. Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry and School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, Human Genetics (Psychiatry), Yale University School of Medicine, West Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Carol A. Mathews
- Psychiatry and Genetics Institute, Center for OCD, Anxiety and Related Disorders, University of Florida, Gainesville, FL, USA
| | - Eske M. Derks
- Department of Mental Health and Neuroscience, QIMR Berghofer, Brisbane, Australia
| | - Manuel Mattheisen
- Department of Psychiatric Phenomics and Genomics (IPPG), Ludwig-Maximilians University Munich, Munich, Germany
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Community Health and Epidemiology and Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
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27
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Tian R, Ge T, Kweon H, Rocha DB, Lam M, Liu JZ, Singh K, Levey DF, Gelernter J, Stein MB, Tsai EA, Huang H, Chabris CF, Lencz T, Runz H, Chen CY. Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression. Nat Commun 2024; 15:1755. [PMID: 38409228 PMCID: PMC10897433 DOI: 10.1038/s41467-024-45774-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/02/2024] [Indexed: 02/28/2024] Open
Abstract
Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.
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Affiliation(s)
- Ruoyu Tian
- Biogen Inc, Cambridge, MA, USA
- Dewpoint Therapeutics, Boston, MA, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Autism & Developmental Medicine Institute, Geisinger Health System, Lewisburg, PA, USA
| | - Daniel B Rocha
- Phenomics Analytics and Clinical Data Core, Geisinger Health System, Danville, PA, USA
| | - Max Lam
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- North Region, Institute of Mental Health, Singapore, Singapore
| | - Jimmy Z Liu
- Biogen Inc, Cambridge, MA, USA
- GlaxoSmithKline, Upper Providence, Philadelphia, PA, USA
| | - Kritika Singh
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- VA Connecticut Healthcare Center, West Haven, CT, USA
- Departments of Psychiatry, Genetics, and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Murray B Stein
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | | | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Christopher F Chabris
- Autism & Developmental Medicine Institute, Geisinger Health System, Lewisburg, PA, USA
| | - Todd Lencz
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
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28
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Ojalo T, Haan E, Kõiv K, Kariis HM, Krebs K, Uusberg H, Sedman T, Võsa U, Puusepp M, Lind S, Hallik I, Alavere H, Milani L, Lehto K. Cohort Profile Update: Mental Health Online Survey in the Estonian Biobank (EstBB MHoS). Int J Epidemiol 2024; 53:dyae017. [PMID: 38381979 PMCID: PMC10881104 DOI: 10.1093/ije/dyae017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 01/29/2024] [Indexed: 02/23/2024] Open
Affiliation(s)
- Triinu Ojalo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Tallinn Children's Hospital Psychiatry Clinic, Tallinn, Estonia
| | - Elis Haan
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Viljandi Hospital Psychiatry Clinic, Viljandi, Estonia
| | - Kadri Kõiv
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hanna Maria Kariis
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Helen Uusberg
- Institute of Psychology, University of Tartu, Tartu, Estonia
| | - Tuuli Sedman
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Tartu University Hospital Psychiatry Clinic, Tartu, Estonia
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mairo Puusepp
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Sirje Lind
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Innar Hallik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Helene Alavere
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
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29
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Wang X, Hoffstaedter F, Kasper J, Eickhoff SB, Patil KR, Dukart J. Lifetime Exposure to Depression and Neuroimaging Measures of Brain Structure and Function. JAMA Netw Open 2024; 7:e2356787. [PMID: 38372997 PMCID: PMC10877455 DOI: 10.1001/jamanetworkopen.2023.56787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/28/2023] [Indexed: 02/20/2024] Open
Abstract
Importance Despite decades of neuroimaging studies reporting brain structural and functional alterations in depression, discrepancies in findings across studies and limited convergence across meta-analyses have raised questions about the consistency and robustness of the observed brain phenotypes. Objective To investigate the associations between 6 operational criteria of lifetime exposure to depression and functional and structural neuroimaging measures. Design, Setting, and Participants This cross-sectional study analyzed data from a UK Biobank cohort of individuals aged 45 to 80 years who were enrolled between January 1, 2014, and December 31, 2018. Participants included individuals with a lifetime exposure to depression and matched healthy controls without indications of psychosis, mental illness, behavior disorder, and disease of the nervous system. Six operational criteria of lifetime exposure to depression were evaluated: help seeking for depression; self-reported depression; antidepressant use; depression definition by Smith et al; hospital International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes F32 and F33; and Composite International Diagnostic Interview Short Form score. Six increasingly restrictive depression definitions and groups were defined based on the 6 depression criteria, ranging from meeting only 1 criterion to meeting all 6 criteria. Data were analyzed between January and October 2022. Main Outcomes and Measures Functional measures were calculated using voxel-wise fractional amplitude of low-frequency fluctuation (fALFF), global correlation (GCOR), and local correlation (LCOR). Structural measures were calculated using gray matter volume (GMV). Results The study included 20 484 individuals with lifetime depression (12 645 females [61.7%]; mean [SD] age, 63.91 [7.60] years) and 25 462 healthy controls (14 078 males [55.3%]; mean [SD] age, 65.05 [7.8] years). Across all depression criteria, individuals with lifetime depression displayed regionally consistent decreases in fALFF, LCOR, and GCOR (Cohen d range, -0.53 [95% CI, -0.88 to -0.15] to -0.04 [95% CI, -0.07 to -0.01]) but not in GMV (Cohen d range, -0.47 [95 % CI, -0.75 to -0.12] to 0.26 [95% CI, 0.15-0.37]). Hospital ICD-10 diagnosis codes F32 and F33 (median [IQR] difference in effect sizes, -0.14 [-0.17 to -0.11]) and antidepressant use (median [IQR] difference in effect sizes, -0.12 [-0.16 to -0.10]) were criteria associated with the most pronounced alterations. Conclusions and Relevance Results of this cross-sectional study indicate that lifetime exposure to depression was associated with robust functional changes, with a more restrictive depression definition revealing more pronounced alterations. Different inclusion criteria for depression may be associated with the substantial variation in imaging findings reported in the literature.
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Affiliation(s)
- Xinyi Wang
- School of Biological Sciences and Medical Engineering, Child Development, and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
| | - Jan Kasper
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
| | - Kaustubh R. Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
| | - Juergen Dukart
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, INM-7: Brain and Behaviour, Research Centre Jülich, Jülich, Germany
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30
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LaBianca S, Brikell I, Helenius D, Loughnan R, Mefford J, Palmer CE, Walker R, Gådin JR, Krebs M, Appadurai V, Vaez M, Agerbo E, Pedersen MG, Børglum AD, Hougaard DM, Mors O, Nordentoft M, Mortensen PB, Kendler KS, Jernigan TL, Geschwind DH, Ingason A, Dahl AW, Zaitlen N, Dalsgaard S, Werge TM, Schork AJ. Polygenic profiles define aspects of clinical heterogeneity in attention deficit hyperactivity disorder. Nat Genet 2024; 56:234-244. [PMID: 38036780 DOI: 10.1038/s41588-023-01593-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 10/25/2023] [Indexed: 12/02/2023]
Abstract
Attention deficit hyperactivity disorder (ADHD) is a complex disorder that manifests variability in long-term outcomes and clinical presentations. The genetic contributions to such heterogeneity are not well understood. Here we show several genetic links to clinical heterogeneity in ADHD in a case-only study of 14,084 diagnosed individuals. First, we identify one genome-wide significant locus by comparing cases with ADHD and autism spectrum disorder (ASD) to cases with ADHD but not ASD. Second, we show that cases with ASD and ADHD, substance use disorder and ADHD, or first diagnosed with ADHD in adulthood have unique polygenic score (PGS) profiles that distinguish them from complementary case subgroups and controls. Finally, a PGS for an ASD diagnosis in ADHD cases predicted cognitive performance in an independent developmental cohort. Our approach uncovered evidence of genetic heterogeneity in ADHD, helping us to understand its etiology and providing a model for studies of other disorders.
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Affiliation(s)
- Sonja LaBianca
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Isabell Brikell
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
| | - Dorte Helenius
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Robert Loughnan
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Joel Mefford
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Clare E Palmer
- Center for Human Development, University of California, San Diego, La Jolla, CA, USA
| | - Rebecca Walker
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jesper R Gådin
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Morten Krebs
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Morteza Vaez
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Esben Agerbo
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Marianne Giørtz Pedersen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
| | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- Copenhagen Mental Health Center, Mental Health Services Capital Region of Denmark Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Preben Bo Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Terry L Jernigan
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Center for Human Development, University of California, San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Daniel H Geschwind
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrés Ingason
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Andrew W Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Søren Dalsgaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Thomas M Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ, USA.
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31
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Clapp Sullivan ML, Schwaba T, Harden KP, Grotzinger AD, Nivard MG, Tucker-Drob EM. Beyond the factor indeterminacy problem using genome-wide association data. Nat Hum Behav 2024; 8:205-218. [PMID: 38225407 PMCID: PMC10922726 DOI: 10.1038/s41562-023-01789-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 11/20/2023] [Indexed: 01/17/2024]
Abstract
Latent factors, such as general intelligence, depression and risk tolerance, are invoked in nearly all social science research where a construct is measured via aggregation of symptoms, question responses or other measurements. Because latent factors cannot be directly observed, they are inferred by fitting a specific model to empirical patterns of correlations among measured variables. A long-standing critique of latent factor theories is that the correlations used to infer latent factors can be produced by alternative data-generating mechanisms that do not include latent factors. This is referred to as the factor indeterminacy problem. Researchers have recently begun to overcome this problem by using information on the associations between individual genetic variants and measured variables. We review historical work on the factor indeterminacy problem and describe recent efforts in genomics to rigorously test the validity of latent factors, advancing the understanding of behavioural science constructs.
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Affiliation(s)
| | - Ted Schwaba
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - 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
| | - Michel G Nivard
- Department of Biological Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
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32
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Meng X, Navoly G, Giannakopoulou O, Levey DF, Koller D, Pathak GA, Koen N, Lin K, Adams MJ, Rentería ME, Feng Y, Gaziano JM, Stein DJ, Zar HJ, Campbell ML, van Heel DA, Trivedi B, Finer S, McQuillin A, Bass N, Chundru VK, Martin HC, Huang QQ, Valkovskaya M, Chu CY, Kanjira S, Kuo PH, Chen HC, Tsai SJ, Liu YL, Kendler KS, Peterson RE, Cai N, Fang Y, Sen S, Scott LJ, Burmeister M, Loos RJF, Preuss MH, Actkins KV, Davis LK, Uddin M, Wani AH, Wildman DE, Aiello AE, Ursano RJ, Kessler RC, Kanai M, Okada Y, Sakaue S, Rabinowitz JA, Maher BS, Uhl G, Eaton W, Cruz-Fuentes CS, Martinez-Levy GA, Campos AI, Millwood IY, Chen Z, Li L, Wassertheil-Smoller S, Jiang Y, Tian C, Martin NG, Mitchell BL, Byrne EM, Awasthi S, Coleman JRI, Ripke S, Sofer T, Walters RG, McIntosh AM, Polimanti R, Dunn EC, Stein MB, Gelernter J, Lewis CM, Kuchenbaecker K. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference. Nat Genet 2024; 56:222-233. [PMID: 38177345 PMCID: PMC10864182 DOI: 10.1038/s41588-023-01596-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/26/2023] [Indexed: 01/06/2024]
Abstract
Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.
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Affiliation(s)
| | | | | | - Daniel F Levey
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Dora Koller
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Gita A Pathak
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Nastassja Koen
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - J Michael Gaziano
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Heather J Zar
- SAMRC Unit on Child and Adolescent Health, Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa
| | - Megan L Campbell
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | | | - Bhavi Trivedi
- Blizard Institute, Queen Mary University of London, London, UK
| | - Sarah Finer
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | | | - Nick Bass
- Division of Psychiatry, UCL, London, UK
| | | | | | | | | | | | - Susan Kanjira
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Po-Hsiu Kuo
- Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hsi-Chung Chen
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science and Division of Psychiatry, National Yang-Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County, Taiwan
| | | | - Roseann E Peterson
- Department of Psychiatry, VCU, Richmond, VA, USA
- Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany
- Computational Health Centre, Helmholtz Munich, Neuherberg, Germany
- Department of Medicine, Technical University of Munich, Munich, Germany
| | - Yu Fang
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Srijan Sen
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Margit Burmeister
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ky'Era V Actkins
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Monica Uddin
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Agaz H Wani
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Allison E Aiello
- Robert N. Butler Columbia Aging Center, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Robert J Ursano
- Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Masahiro Kanai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - George Uhl
- Neurology and Pharmacology, University of Maryland, Maryland VA Healthcare System, Baltimore, MD, USA
| | - William Eaton
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Carlos S Cruz-Fuentes
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Gabriela A Martinez-Levy
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Adrian I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | | | - Yunxuan Jiang
- Department of Biostatistics, Emory University, Atlanta, GA, USA
- 23andMe, Inc., Mountain View, CA, USA
| | - Chao Tian
- 23andMe, Inc., Mountain View, CA, USA
| | - Nicholas G Martin
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Swapnil Awasthi
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Jonathan R I Coleman
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stephan Ripke
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Cambridge, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Renato Polimanti
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Erin C Dunn
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Murray B Stein
- Department of Psychiatry, UC San Diego School of Medicine, La Jolla, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Cathryn M Lewis
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
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33
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Huider F, Milaneschi Y, Hottenga JJ, Bot M, Rietman ML, Kok AAL, Galesloot TE, 't Hart LM, Rutters F, Blom MT, Rhebergen D, Visser M, Brouwer I, Feskens E, Hartman CA, Oldehinkel AJ, de Geus EJC, Kiemeney LA, Huisman M, Picavet HSJ, Verschuren WMM, van Loo HM, Penninx BWJH, Boomsma DI. Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project. Twin Res Hum Genet 2024; 27:1-11. [PMID: 38497097 DOI: 10.1017/thg.2024.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.
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Affiliation(s)
- Floris Huider
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Yuri Milaneschi
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Mariska Bot
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - M Liset Rietman
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - Almar A L Kok
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
| | | | | | | | | | - Didi Rhebergen
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Mental health Institute GGZ Centraal, Amersfoort, the Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Ingeborg Brouwer
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Edith Feskens
- Division of Human Nutrition and Health, Wageningen University & Research, 6700 Wageningen, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | | | - Martijn Huisman
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
- Department of Sociology, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - H Susan J Picavet
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 Utrecht, the Netherlands
| | - Hanna M van Loo
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Brenda W J H Penninx
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
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Benstock SE, Weaver K, Hettema J, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. RESEARCH SQUARE 2024:rs.3.rs-3858178. [PMID: 38352402 PMCID: PMC10862954 DOI: 10.21203/rs.3.rs-3858178/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Genome-wide association studies (GWAS) are underpowered due to small effect sizes of single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the most statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Koch E, Pardiñas AF, O'Connell KS, Selvaggi P, Camacho Collados J, Babic A, Marshall SE, Van der Eycken E, Angulo C, Lu Y, Sullivan PF, Dale AM, Molden E, Posthuma D, White N, Schubert A, Djurovic S, Heimer H, Stefánsson H, Stefánsson K, Werge T, Sønderby I, O'Donovan MC, Walters JTR, Milani L, Andreassen OA. How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry. Biol Psychiatry 2024:S0006-3223(24)00003-9. [PMID: 38185234 DOI: 10.1016/j.biopsych.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/09/2024]
Abstract
Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.
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Affiliation(s)
- Elise Koch
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - José Camacho Collados
- CardiffNLP, School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | | | | | - Erik Van der Eycken
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Cecilia Angulo
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden; Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, California; Departments of Radiology, Psychiatry, and Neurosciences, University of California, San Diego, La Jolla, California
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Nathan White
- CorTechs Laboratories, Inc., San Diego, California
| | | | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; The Norwegian Centre for Mental Disorders Research Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Hakon Heimer
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Nordic Society of Human Genetics and Precision Medicine, Copenhagen, Denmark
| | | | | | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark; Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Ida Sønderby
- Norwegian 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 Medical Genetics, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ole A Andreassen
- Norwegian 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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McClellan JM, Zoghbi AW, Buxbaum JD, Cappi C, Crowley JJ, Flint J, Grice DE, Gulsuner S, Iyegbe C, Jain S, Kuo PH, Lattig MC, Passos-Bueno MR, Purushottam M, Stein DJ, Sunshine AB, Susser ES, Walsh CA, Wootton O, King MC. An evolutionary perspective on complex neuropsychiatric disease. Neuron 2024; 112:7-24. [PMID: 38016473 PMCID: PMC10842497 DOI: 10.1016/j.neuron.2023.10.037] [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: 08/02/2022] [Revised: 08/09/2023] [Accepted: 10/26/2023] [Indexed: 11/30/2023]
Abstract
The forces of evolution-mutation, selection, migration, and genetic drift-shape the genetic architecture of human traits, including the genetic architecture of complex neuropsychiatric illnesses. Studying these illnesses in populations that are diverse in genetic ancestry, historical demography, and cultural history can reveal how evolutionary forces have guided adaptation over time and place. A fundamental truth of shared human biology is that an allele responsible for a disease in anyone, anywhere, reveals a gene critical to the normal biology underlying that condition in everyone, everywhere. Understanding the genetic causes of neuropsychiatric disease in the widest possible range of human populations thus yields the greatest possible range of insight into genes critical to human brain development. In this perspective, we explore some of the relationships between genes, adaptation, and history that can be illuminated by an evolutionary perspective on studies of complex neuropsychiatric disease in diverse populations.
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Affiliation(s)
- Jon M McClellan
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
| | - Anthony W Zoghbi
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Carolina Cappi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - James J Crowley
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jonathan Flint
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Dorothy E Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Suleyman Gulsuner
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Conrad Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru 560029, India
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100, Taiwan
| | | | | | - Meera Purushottam
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru 560029, India
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Anna B Sunshine
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA; Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Ezra S Susser
- Department of Epidemiology, Mailman School of Public Health, and New York State Psychiatric Institute, Columbia University, New York, NY 10032, USA
| | - Christopher A Walsh
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Genetics and Genomics and Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Olivia Wootton
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Mary-Claire King
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
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Shi Y, Sprooten E, Mulders P, Vrijsen J, Bralten J, Demontis D, Børglum AD, Walters GB, Stefansson K, van Eijndhoven P, Tendolkar I, Franke B, Mota NR. Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32951. [PMID: 37334623 PMCID: PMC10803201 DOI: 10.1002/ajmg.b.32951] [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: 09/06/2022] [Revised: 03/31/2023] [Accepted: 06/05/2023] [Indexed: 06/20/2023]
Abstract
The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.
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Affiliation(s)
- Yingjie Shi
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Emma Sprooten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Peter Mulders
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Janna Vrijsen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Pro Persona Mental Health Care, Depression Expertise Centre, Nijmegen, The Netherlands
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Ditte Demontis
- Department of Biomedicine/Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Copenhagen, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Anders D. Børglum
- Department of Biomedicine/Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Copenhagen, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - G. Bragi Walters
- deCODE Genetics, Reykjavík, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Kari Stefansson
- deCODE Genetics, Reykjavík, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Philip van Eijndhoven
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Indira Tendolkar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Nina Roth Mota
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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Kiewa J, Meltzer-Brody S, Milgrom J, Guintivano J, Hickie IB, Whiteman DC, Olsen CM, Medland SE, Martin NG, Wray NR, Byrne EM. Comprehensive Sex-Stratified Genetic Analysis of 28 Blood Biomarkers and Depression Reveals a Significant Association between Depression and Low Levels of Total Protein in Females. Complex Psychiatry 2024; 10:19-34. [PMID: 38584764 PMCID: PMC10997320 DOI: 10.1159/000538058] [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: 09/13/2023] [Accepted: 02/14/2024] [Indexed: 04/09/2024] Open
Abstract
Introduction Major depression (MD) is more common amongst women than men, and MD episodes have been associated with fluctuations in reproductive hormones amongst women. To investigate biological underpinnings of heterogeneity in MD, the associations between depression, stratified by sex and including perinatal depression (PND), and blood biomarkers, using UK Biobank (UKB) data, were evaluated, and extended to include the association of depression with biomarker polygenic scores (PGS), generated as proxy for each biomarker. Method Using female (N = 39,761) and male (N = 38,821) UKB participants, lifetime MD and PND were tested for association with 28 blood biomarkers. A GWAS was conducted for each biomarker and genetic correlations with depression subgroups were estimated. Using independent data from the Australian Genetics of Depression Study, PGS were constructed for each biomarker, and tested for association with depression status (n [female cases/controls] = 9,006/6,442; n [male cases/controls] = 3,106/6,222). Regions of significant local genetic correlation between depression subgroups and biomarkers highlighted by the PGS analysis were identified. Results Depression in females was significantly associated with levels of twelve biomarkers, including total protein (OR = 0.90, CI = [0.86, 0.94], p = 3.9 × 10-6) and vitamin D (OR = 0.94, CI = [0.90, 0.97], p = 2.6 × 10-4), and PND with five biomarker levels, also including total protein (OR = 0.88, CI = [0.81, 0.96], p = 4.7 × 10-3). Depression in males was significantly associated with levels of eleven biomarkers. In the independent Australian Genetics of Depression Study, PGS analysis found significant associations for female depression and PND with total protein (female depression: OR = 0.93, CI = [0.88, 0.98], p = 3.6 × 10-3; PND: OR = 0.91, CI = [0.86, 0.96], p = 1.1 × 10-3), as well as with vitamin D (female depression: OR = 0.93, CI = [0.89, 0.97], p = 2.0 × 10-3; PND: OR = 0.92, CI = [0.87, 0.97], p = 1.4 × 10-3). The male depression sample did not report any significant results, and the point estimate of total protein (OR = 0.98, CI = [0.92-1.04], p = 4.7 × 10-1) did not indicate any association. Local genetic correlation analysis highlighted significant genetic correlation between PND and total protein, located in 5q13.3 (rG = 0.68, CI = [0.33, 1.0], p = 3.6 × 10-4). Discussion and Conclusion Multiple lines of evidence from genetic analysis highlight an association between total serum protein levels and depression in females. Further research involving prospective measurement of total protein and depressive symptoms is warranted.
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Affiliation(s)
- Jacqueline Kiewa
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | | | - Jeannette Milgrom
- Parent-Infant Research Institute, Austin Health, Melbourne, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Jerry Guintivano
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Ian B. Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | | | | | - Sarah E. Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enda M. Byrne
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
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Woolway GE, Legge SE, Lynham A, Smart SE, Hubbard L, Daniel ER, Pardiñas AF, Escott-Price V, O'Donovan MC, Owen MJ, Jones IR, Walters JT. Assessing the validity of a self-reported clinical diagnosis of schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.06.23299622. [PMID: 38106032 PMCID: PMC10723562 DOI: 10.1101/2023.12.06.23299622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Background Diagnoses in psychiatric research can be derived from various sources. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. Methods The study included 3,029 clinically ascertained participants with schizophrenia or psychotic disorders diagnosed by self-report and/or research interview and 1,453 UK Biobank participants with self-report and/or medical record diagnosis of schizophrenia or schizoaffective disorder depressed-type (SA-D). We assessed positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. We compared polygenic risk scores (PRS) and phenotypes across diagnostic groups, and compared the variance explained by schizophrenia PRS to samples in the Psychiatric Genomics Consortium (PGC). Results In the clinically ascertained sample, the PPV of self-reported schizophrenia to a research diagnosis of schizophrenia was 0.70, which increased to 0.81 when benchmarked against schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia to a medical record diagnosis was 0.74. Compared to self-report participants, those with a research diagnosis were younger and more likely to have a high school qualification (clinically ascertained sample) and those with a medical record diagnosis were less likely to be employed or have a high school qualification (UK Biobank). Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical record diagnosis. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Conclusions Self-report measures of schizophrenia are justified in research to maximise sample size and representativeness, although within sample validation of diagnoses is recommended.
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Affiliation(s)
- Grace E Woolway
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Amy Lynham
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Smart
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Leon Hubbard
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ellie R Daniel
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Valentina Escott-Price
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian R Jones
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - James Tr Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
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Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R, Bacanu SA, Werge T, Flint J, Schork AJ, Sankararaman S, Kendler KS, Cai N. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nat Genet 2023; 55:2082-2093. [PMID: 37985818 PMCID: PMC10703686 DOI: 10.1038/s41588-023-01559-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/18/2023] [Indexed: 11/22/2023]
Abstract
Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.
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Affiliation(s)
- Andrew Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA.
| | - Michael Thompson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ulzee An
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Morten Krebs
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Richard Border
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany.
- School of Medicine, Technical University of Munich, Munich, Germany.
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Clifford R, Munro D, Dochtermann D, Devineni P, Pyarajan S, Telese F, Palmer AA, Mohammadi P, Friedman R. Genome-Wide Association Study of Chronic Dizziness in the Elderly Identifies Loci Implicating MLLT10, BPTF, LINC01224, and ROS1. J Assoc Res Otolaryngol 2023; 24:575-591. [PMID: 38036714 PMCID: PMC10752854 DOI: 10.1007/s10162-023-00917-y] [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: 02/06/2023] [Accepted: 11/12/2023] [Indexed: 12/02/2023] Open
Abstract
PURPOSE Chronic age-related imbalance is a common cause of falls and subsequent death in the elderly and can arise from dysfunction of the vestibular system, an elegant neuroanatomical group of pathways that mediates human perception of acceleration, gravity, and angular head motion. Studies indicate that 27-46% of the risk of age-related chronic imbalance is genetic; nevertheless, the underlying genes remain unknown. METHODS The cohort consisted of 50,339 cases and 366,900 controls in the Million Veteran Program. The phenotype comprised cases with two ICD diagnoses of vertigo or dizziness at least 6 months apart, excluding acute or recurrent vertiginous syndromes and other non-vestibular disorders. Genome-wide association studies were performed as individual logistic regressions on European, African American, and Hispanic ancestries followed by trans-ancestry meta-analysis. Downstream analysis included case-case-GWAS, fine mapping, probabilistic colocalization of significant variants and genes with eQTLs, and functional analysis of significant hits. RESULTS Two significant loci were identified in Europeans, another in the Hispanic population, and two additional in trans-ancestry meta-analysis, including three novel loci. Fine mapping revealed credible sets of intronic single nucleotide polymorphisms (SNPs) in MLLT10 - a histone methyl transferase cofactor, BPTF - a subunit of a nucleosome remodeling complex implicated in neurodevelopment, and LINC01224 - a proto-oncogene receptor tyrosine kinase. CONCLUSION Despite the difficulties of phenotyping the nature of chronic imbalance, we replicated two loci from previous vertigo GWAS studies and identified three novel loci. Findings suggest candidates for further study and ultimate treatment of this common elderly disorder.
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Affiliation(s)
- Royce Clifford
- Department of Otolaryngology-Head and Neck Surgery, University of California San Diego, La Jolla, CA, 92093, USA.
- Research Dept, Veteran Administration Hospitals, San Diego, CA, 92161, USA.
| | - Daniel Munro
- Dept. of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Dept. of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92093, USA
| | - Daniel Dochtermann
- Veterans Administrations Hospitals, Million Veteran Program, Boston, MA, 02130, USA
| | - Poornima Devineni
- Veterans Administrations Hospitals, Million Veteran Program, Boston, MA, 02130, USA
| | - Saiju Pyarajan
- Veterans Administrations Hospitals, Million Veteran Program, Boston, MA, 02130, USA
| | - Francesca Telese
- Dept. of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Abraham A Palmer
- Dept. of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Pejman Mohammadi
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, 98101, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Rick Friedman
- Department of Otolaryngology-Head and Neck Surgery, University of California San Diego, La Jolla, CA, 92093, USA
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Baranger DAA, Hatoum AS, Polimanti R, Gelernter J, Edenberg HJ, Bogdan R, Agrawal A. Multi-omics cannot replace sample size in genome-wide association studies. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12846. [PMID: 36977197 PMCID: PMC10733567 DOI: 10.1111/gbb.12846] [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: 10/24/2022] [Revised: 02/20/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023]
Abstract
The integration of multi-omics information (e.g., epigenetics and transcriptomics) can be useful for interpreting findings from genome-wide association studies (GWAS). It has been suggested that multi-omics could circumvent or greatly reduce the need to increase GWAS sample sizes for novel variant discovery. We tested whether incorporating multi-omics information in earlier and smaller-sized GWAS boosts true-positive discovery of genes that were later revealed by larger GWAS of the same/similar traits. We applied 10 different analytic approaches to integrating multi-omics data from 12 sources (e.g., Genotype-Tissue Expression project) to test whether earlier and smaller GWAS of 4 brain-related traits (alcohol use disorder/problematic alcohol use, major depression/depression, schizophrenia, and intracranial volume/brain volume) could detect genes that were revealed by a later and larger GWAS. Multi-omics data did not reliably identify novel genes in earlier less-powered GWAS (PPV <0.2; 80% false-positive associations). Machine learning predictions marginally increased the number of identified novel genes, correctly identifying 1-8 additional genes, but only for well-powered early GWAS of highly heritable traits (i.e., intracranial volume and schizophrenia). Although multi-omics, particularly positional mapping (i.e., fastBAT, MAGMA, and H-MAGMA), can help to prioritize genes within genome-wide significant loci (PPVs = 0.5-1.0) and translate them into information about disease biology, it does not reliably increase novel gene discovery in brain-related GWAS. To increase power for discovery of novel genes and loci, increasing sample size is required.
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Affiliation(s)
- David A. A. Baranger
- Department of Psychological & Brain SciencesWashington University in St. Louis Medical SchoolSaint LouisMissouriUSA
| | - Alexander S. Hatoum
- Department of PsychiatryWashington University School of MedicineSaint LouisMissouriUSA
| | - Renato Polimanti
- Department of Psychiatry, Division of Human GeneticsYale School of MedicineNew HavenConnecticutUSA
- PsychiatryVeterans Affairs Connecticut Healthcare SystemWest HavenConnecticutUSA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human GeneticsYale School of MedicineNew HavenConnecticutUSA
- PsychiatryVeterans Affairs Connecticut Healthcare SystemWest HavenConnecticutUSA
- Department of GeneticsYale School of MedicineNew HavenConnecticutUSA
- Department of NeuroscienceYale School of MedicineNew HavenConnecticutUSA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Ryan Bogdan
- Department of Psychological & Brain SciencesWashington University in St. Louis Medical SchoolSaint LouisMissouriUSA
| | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSaint LouisMissouriUSA
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Streit F, Zillich L, Frank J, Kleineidam L, Wagner M, Baune BT, Klinger-König J, Grabe HJ, Pabst A, Riedel-Heller SG, Schmiedek F, Schmidt B, Erhardt A, Deckert J, Rietschel M, Berger K. Lifetime and current depression in the German National Cohort (NAKO). World J Biol Psychiatry 2023; 24:865-880. [PMID: 34870540 DOI: 10.1080/15622975.2021.2014152] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 12/01/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVES The present study introduces the assessment of depression and depressive symptoms in the German National Cohort (NAKO), a population-based mega cohort. Distribution of core measures, and associations with sociodemographic factors are examined. METHODS The current analysis includes data from the first 101,667 participants (NAKO data freeze 100,000). Depression and depressive symptoms were assessed using a modified version of the depression section of the Mini-International Neuropsychiatric Interview (MINI), self-reported physician's diagnosis of depression, and the depression scale of the Patient Health Questionnaire (PHQ-9). RESULTS A lifetime physician's diagnosis of depression was reported by 15.0% of participants. Of those, 47.6% reported having received treatment for depression within the last 12 months. Of the subset of 26,342 participants undergoing the full depression section of the modified MINI, 15.9% were classified by the MINI with a lifetime depressive episode. Based on the PHQ-9, 5.8% of the participants were classified as currently having a major or other depression by the diagnostic algorithm, and 7.8% according to the dimensional assessment (score ≥ 10). Increased frequency of depression measures and higher depression scores were observed in women and participants with lower education level or a family history of depression. CONCLUSIONS The observed distributions of all depression measures and their associations with sociodemographic variables are consistent with the literature on depression. The NAKO represents a valuable epidemiologic resource to investigate depression, and the range of measures for lifetime and current depression allows users to select the most suitable instrument for their specific research question.
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Affiliation(s)
- Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Luca Kleineidam
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michael Wagner
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Munster, Germany
| | - Johanna Klinger-König
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, Greifswald, Germany
| | - Alexander Pabst
- Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Florian Schmiedek
- Department of Education and Human Development, DIPF | Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany
- Institute of Psychology, Goethe University, Frankfurt am Main, Germany
- Center for Mind, Brain and Behavior, University of Marburg and Justus Liebig University, Giessen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Germany
| | - Angelika Erhardt
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, Julius-Maximilians-University, Wuerzburg, Germany
- Max Planck Institute for Psychiatry, Munich, Germany
| | - Jürgen Deckert
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, Julius-Maximilians-University, Wuerzburg, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Klaus Berger
- Institute of Epidemiology & Social Medicine, University of Muenster, Muenster, Germany
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Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
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Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
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An U, Pazokitoroudi A, Alvarez M, Huang L, Bacanu S, Schork AJ, Kendler K, Pajukanta P, Flint J, Zaitlen N, Cai N, Dahl A, Sankararaman S. Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries. Nat Genet 2023; 55:2269-2276. [PMID: 37985819 PMCID: PMC10703681 DOI: 10.1038/s41588-023-01558-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/04/2023] [Indexed: 11/22/2023]
Abstract
Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or 'fill-in' missing phenotypes in population-scale biobank datasets. When applied to collections of phenotypes measured across ~300,000 individuals from the UK Biobank, AutoComplete substantially improved imputation accuracy over existing methods. On three traits with notable amounts of missingness, we show that AutoComplete yields imputed phenotypes that are genetically similar to the originally observed phenotypes while increasing the effective sample size by about twofold on average. Further, genome-wide association analyses on the resulting imputed phenotypes led to a substantial increase in the number of associated loci. Our results demonstrate the utility of deep learning-based phenotype imputation to increase power for genetic discoveries in existing biobank datasets.
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Affiliation(s)
- Ulzee An
- Computer Science Department, UCLA, Los Angeles, CA, USA.
| | | | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Lianyun Huang
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany
- School of Medicine, Technical University of Munich, Munich, Germany
| | - Silviu Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Kenneth Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Noah Zaitlen
- Neurology Department, UCLA, Los Angeles, CA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany
- School of Medicine, Technical University of Munich, Munich, Germany
| | - Andy Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Sriram Sankararaman
- Computer Science Department, UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, UCLA, Los Angeles, CA, USA.
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Frid LM, Kessler U, Ousdal OT, Hammar Å, Haavik J, Riemer F, Hirnstein M, Ersland L, Erchinger VJ, Ronold EH, Nygaard G, Jakobsen P, Craven AR, Osnes B, Alisauskiene R, Bartsch H, Le Hellard S, Stavrum AK, Oedegaard KJ, Oltedal L. Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation. BMC Psychiatry 2023; 23:791. [PMID: 37904091 PMCID: PMC10617235 DOI: 10.1186/s12888-023-05239-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 09/30/2023] [Indexed: 11/01/2023] Open
Abstract
BACKGROUND Noninvasive neurostimulation treatments are increasingly being used to treat major depression, which is a common cause of disability worldwide. While electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) are both effective in treating depressive episodes, their mechanisms of action are, however, not completely understood. ECT is given under general anesthesia, where an electrical pulse is administered through electrodes placed on the patient's head to trigger a seizure. ECT is used for the most severe cases of depression and is usually not prescribed before other options have failed. With TMS, brain stimulation is achieved through rapidly changing magnetic fields that induce electric currents underneath a ferromagnetic coil. Its efficacy in depressive episodes has been well documented. This project aims to identify the neurobiological underpinnings of both the effects and side effects of the neurostimulation techniques ECT and TMS. METHODS The study will utilize a pre-post case control longitudinal design. The sample will consist of 150 subjects: 100 patients (bipolar and major depressive disorder) who are treated with either ECT (N = 50) or TMS (N = 50) and matched healthy controls (N = 50) not receiving any treatment. All participants will undergo multimodal magnetic resonance imaging (MRI) as well as neuropsychological and clinical assessments at multiple time points before, during and after treatment. Arterial spin labeling MRI at baseline will be used to test whether brain perfusion can predict outcomes. Signs of brain disruption, potentiation and rewiring will be explored with resting-state functional MRI, magnetic resonance spectroscopy and multishell diffusion weighted imaging (DWI). Clinical outcome will be measured by clinician assessed and patient reported outcome measures. Memory-related side effects will be investigated, and specific tests of spatial navigation to test hippocampal function will be administered both before and after treatment. Blood samples will be stored in a biobank for future analyses. The observation time is 6 months. Data will be explored in light of the recently proposed disrupt, potentiate and rewire (DPR) hypothesis. DISCUSSION The study will contribute data and novel analyses important for our understanding of neurostimulation as well as for the development of enhanced and more personalized treatment. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT05135897.
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Affiliation(s)
- Leila Marie Frid
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ute Kessler
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Olga Therese Ousdal
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Åsa Hammar
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Department of Clinical Sciences Lund, Psychiatry, Faculty of Medicine, Lund University, Lund, Sweden
- Office for Psychiatry and Habilitation, , Psychiatry Research Skåne, Region Skåne, Sweden
| | - Jan Haavik
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Marco Hirnstein
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Lars Ersland
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Vera Jane Erchinger
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Eivind Haga Ronold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Gyrid Nygaard
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Petter Jakobsen
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Berge Osnes
- Department of Clinical Psychology, University of Bergen, Bergen, Norway
| | | | - Hauke Bartsch
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Stephanie Le Hellard
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Anne-Kristin Stavrum
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Ketil J Oedegaard
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Leif Oltedal
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway.
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.
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Fatumo S, Sathan D, Samtal C, Isewon I, Tamuhla T, Soremekun C, Jafali J, Panji S, Tiffin N, Fakim YJ. Polygenic risk scores for disease risk prediction in Africa: current challenges and future directions. Genome Med 2023; 15:87. [PMID: 37904243 PMCID: PMC10614359 DOI: 10.1186/s13073-023-01245-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 10/12/2023] [Indexed: 11/01/2023] Open
Abstract
Early identification of genetic risk factors for complex diseases can enable timely interventions and prevent serious outcomes, including mortality. While the genetics underlying many Mendelian diseases have been elucidated, it is harder to predict risk for complex diseases arising from the combined effects of many genetic variants with smaller individual effects on disease aetiology. Polygenic risk scores (PRS), which combine multiple contributing variants to predict disease risk, have the potential to influence the implementation for precision medicine. However, the majority of existing PRS were developed from European data with limited transferability to African populations. Notably, African populations have diverse genetic backgrounds, and a genomic architecture with smaller haplotype blocks compared to European genomes. Subsequently, growing evidence shows that using large-scale African ancestry cohorts as discovery for PRS development may generate more generalizable findings. Here, we (1) discuss the factors contributing to the poor transferability of PRS in African populations, (2) showcase the novel Africa genomic datasets for PRS development, (3) explore the potential clinical utility of PRS in African populations, and (4) provide insight into the future of PRS in Africa.
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Affiliation(s)
- Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK.
| | - Dassen Sathan
- H3Africa Bioinformatics Network (H3ABioNet) Node, University of Mauritius, Reduit, Mauritius
| | - Chaimae Samtal
- Laboratory of Biotechnology, Environment, Agri-Food and Health, Faculty of Sciences Dhar El Mahraz-Sidi Mohammed Ben Abdellah University, 30000, Fez, Morocco
| | - Itunuoluwa Isewon
- Department of Computer and Information Sciences, Covenant University, P. M. B. 1023, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Km 10 Idiroko Road, P.M.B. 1023, Ota, Ogun State, Nigeria
- Covenant Applied Informatics and Communication African Centre of Excellence (CApIC-ACE), Covenant University, P.M.B. 1023, Ota, Ogun State, Nigeria
| | - Tsaone Tamuhla
- Division of Computational Biology, Integrative Biomedical Sciences Department, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Chisom Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
- Department of Immunology and Molecular Biology, College of Health Science, Makerere University, Kampala, Uganda
| | - James Jafali
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
- Clinical Infection, Microbiology & Immunology, The University of Liverpool, Liverpool, UK
| | - Sumir Panji
- Computational Biology Group, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, 7925, South Africa
| | - Nicki Tiffin
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
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48
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Miller AP, Kuo SIC, Johnson EC, Tillman R, Brislin SJ, Dick DM, Kamarajan C, Kinreich S, Kramer J, McCutcheon VV, Plawecki MH, Porjesz B, Schuckit MA, Salvatore JE, Edenberg HJ, Bucholz KK, Meyers JL, Agrawal A. Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder. JAMA Netw Open 2023; 6:e2337192. [PMID: 37815828 PMCID: PMC10565602 DOI: 10.1001/jamanetworkopen.2023.37192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/22/2023] [Indexed: 10/11/2023] Open
Abstract
Importance Current Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) diagnoses of substance use disorders rely on criterion count-based approaches, disregarding severity grading indexed by individual criteria. Objective To examine correlates of alcohol use disorder (AUD) across count-based severity groups (ie, mild, moderate, mild-to-moderate, severe), identify specific diagnostic criteria indicative of greater severity, and evaluate whether specific criteria within mild-to-moderate AUD differentiate across relevant correlates and manifest in greater hazards of severe AUD development. Design, Setting, and Participants This cohort study involved 2 cohorts from the family-based Collaborative Study on the Genetics of Alcoholism (COGA) with 7 sites across the United States: cross-sectional (assessed 1991-2005) and longitudinal (assessed 2004-2019). Statistical analyses were conducted from December 2022 to June 2023. Main Outcomes and Measures Sociodemographic, alcohol-related, psychiatric comorbidity, brain electroencephalography (EEG), and AUD polygenic score measures as correlates of DSM-5 AUD levels (ie, mild, moderate, severe) and criterion severity-defined mild-to-moderate AUD diagnostic groups (ie, low-risk vs high-risk mild-to-moderate). Results A total of 13 110 individuals from the cross-sectional COGA cohort (mean [SD] age, 37.8 [14.2] years) and 2818 individuals from the longitudinal COGA cohort (mean baseline [SD] age, 16.1 [3.2] years) were included. Associations with alcohol-related, psychiatric, EEG, and AUD polygenic score measures reinforced the role of increasing criterion counts as indexing severity. Yet within mild-to-moderate AUD (2-5 criteria), the presence of specific high-risk criteria (eg, withdrawal) identified a group reporting heavier drinking and greater psychiatric comorbidity even after accounting for criterion count differences. In longitudinal analyses, prior mild-to-moderate AUD characterized by endorsement of at least 1 high-risk criterion was associated with more accelerated progression to severe AUD (adjusted hazard ratio [aHR], 11.62; 95% CI, 7.54-17.92) compared with prior mild-to-moderate AUD without endorsement of high-risk criteria (aHR, 5.64; 95% CI, 3.28-9.70), independent of criterion count. Conclusions and Relevance In this cohort study of a combined 15 928 individuals, findings suggested that simple count-based AUD diagnostic approaches to estimating severe AUD vulnerability, which ignore heterogeneity among criteria, may be improved by emphasizing specific high-risk criteria. Such emphasis may allow better focus on individuals at the greatest risk and improve understanding of the development of AUD.
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Affiliation(s)
- Alex P. Miller
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Sally I-Chun Kuo
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Rebecca Tillman
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Sarah J. Brislin
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Danielle M. Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Sivan Kinreich
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City
| | - Vivia V. McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | | | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Marc A. Schuckit
- Department of Psychiatry, University of California San Diego Medical School, San Diego
| | - Jessica E. Salvatore
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Jaquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
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49
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ter Kuile AR, Hübel C, Cheesman R, Coleman JR, Peel AJ, Levey DF, Stein MB, Gelernter J, Rayner C, Eley TC, Breen G. Genetic Decomposition of the Heritable Component of Reported Childhood Maltreatment. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:716-724. [PMID: 37881567 PMCID: PMC10593925 DOI: 10.1016/j.bpsgos.2023.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/15/2023] [Accepted: 03/11/2023] [Indexed: 10/27/2023] Open
Abstract
Background Decades of research have shown that environmental exposures, including self-reports of trauma, are partly heritable. Heritable characteristics may influence exposure to and interpretations of environmental factors. Identifying heritable factors associated with self-reported trauma could improve our understanding of vulnerability to exposure and the interpretation of life events. Methods We used genome-wide association study summary statistics of childhood maltreatment, defined as reporting of abuse (emotional, sexual, and physical) and neglect (emotional and physical) (N = 185,414 participants). We calculated genetic correlations (rg) between reported childhood maltreatment and 576 traits to identify phenotypes that might explain the heritability of reported childhood maltreatment, retaining those with |rg| > 0.25. We specified multiple regression models using genomic structural equation modeling to detect residual genetic variance in childhood maltreatment after accounting for genetically correlated traits. Results In 2 separate models, the shared genetic component of 12 health and behavioral traits and 7 psychiatric disorders accounted for 59% and 56% of heritability due to common genetic variants (single nucleotide polymorphism-based heritability [h2SNP]) of childhood maltreatment, respectively. Genetic influences on h2SNP of childhood maltreatment were generally accounted for by a shared genetic component across traits. The exceptions to this were general risk tolerance, subjective well-being, posttraumatic stress disorder, and autism spectrum disorder, identified as independent contributors to h2SNP of childhood maltreatment. These 4 traits alone were sufficient to explain 58% of h2SNP of childhood maltreatment. Conclusions We identified putative traits that reflect h2SNP of childhood maltreatment. Elucidating the mechanisms underlying these associations may improve trauma prevention and posttraumatic intervention strategies.
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Affiliation(s)
- Abigail R. ter Kuile
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Christopher Hübel
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- National Centre for Register-based Research, Aarhus Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Rosa Cheesman
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Jonathan R.I. Coleman
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Alicia J. Peel
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Daniel F. Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
| | - Murray B. Stein
- Veterans Affairs San Diego Healthcare System, San Diego, California
- Department of Psychiatry and School of Public Health, University of California San Diego, La Jolla, California
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
| | - Christopher Rayner
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Thalia C. Eley
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Gerome Breen
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health and Care Research Maudsley Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
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50
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Johansson Å, Andreassen OA, Brunak S, Franks PW, Hedman H, Loos RJ, Meder B, Melén E, Wheelock CE, Jacobsson B. Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification. J Intern Med 2023; 294:378-396. [PMID: 37093654 PMCID: PMC10523928 DOI: 10.1111/joim.13640] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.
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Affiliation(s)
- Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala university, Sweden
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopment Research, University of Oslo, Oslo, Norway
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
- Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2200 Copenhagen, Denmark
| | - Paul W. Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Sweden
- Novo Nordisk Foundation, Denmark
| | - Harald Hedman
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Ruth J.F. Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin Meder
- Precision Digital Health, Cardiogenetics Center Heidelberg, Department of Cardiology, University Of Heidelberg, Germany
| | - Erik Melén
- Department of Clinical Sciences and Education, Södersjukhuset, Karolinska Institutet, Stockholm
- Sachś Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Craig E Wheelock
- Unit of Integrative Metabolomics, Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
- Department of Respiratory Medicine and Allergy, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Obstetrics and Gynaecology, Sahlgrenska University Hospital, Göteborg, Sweden
- Department of Genetics and Bioinformatics, Domain of Health Data and Digitalisation, Institute of Public Health, Oslo, Norway
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