Atypical energy-related symptoms define biologically distinct subtypes of major depressive disorder
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: ABSTRACT Major depressive disorder (MDD) is a complex psychiatric disorder, characterized by a range of mood, cognitive, and neurovegetative symptoms. Current diagnostic criteria treat opposite symptom directions as equivalent; weight gain or loss, and increased or decreased sleep, each count toward a single diagnosis. We defined three subgroups of individuals meeting criteria for MDD: AERS+ (hypersomnia with increased appetite/weight gain), AERS− (insomnia with appetite/weight loss), and an Uncategorized group, and conducted genome-wide association meta-analyses for each ( N eff = 47,858, 156,624, and 215,828, respectively). We identified 27 genome-wide significant loci across subtypes, 4 for AERS+ , 10 for AERS− and 13 for Uncategorized. AERS+ showed higher SNP-based heritability (10.9%) and lower polygenicity (1.7% of SNPs) than AERS− (7.9%; 2.9%) or Uncategorized (8.6%; 5.3%), with larger effect sizes at its associated loci. The AERS+ and AERS− subtypes were moderately genetically correlated ( r g = 0.64, se = 0.04). Metabolic traits emerged as a primary differentiator: AERS+ correlated positively with BMI, metabolic syndrome, and related traits, whereas AERS− correlated weakly in the opposite direction. These findings show that the directionality of neurovegetative symptoms indexes genetic heterogeneity within MDD, with metabolic biology as a central axis of differentiation.
Source: medRxiv
Authors: Arvid Harder, Rujia Wang, Jacob Bergstedt, Floris Huider, Siim Kurvits, Jackson Thorp, Tong Gong, Elham Assary, Anaïs B. Thijssen, Giuseppe Pierpaolo Merola, Anastasia A. Goula, Sam Bentwood, Robert Karlsson, Joelle A. Pasman, Chiara Fabbri, Ian B. Hickie, Wouter J. Peyrot, Douglas F. Levinson, James B. Potash, Jianxin Shi, Sarah E. Medland, Brittany L. Mitchell, Alex S.F Kwong, Thalia C. Eley, Cathryn M. Lewis, Steven P. Hamilton, Nicholas G. Martin, Dorret I. Boomsma, Kelli Lehto, Naomi R. Wray, Gerome Breen, Brenda W.J.H. Penninx, Yuri Milaneschi, Sally Marshall, Pippa A. Thomson, Yi Lu
Institutions: Karolinska Institutet, King's College London, Amsterdam Public Health, Vrije Universiteit Amsterdam, University of Tartu, The University of Queensland, QIMR Berghofer Medical Research Institute, Amsterdam University Medical Centers, South London and Maudsley NHS Foundation Trust, Maudsley Hospital, University of Edinburgh, Amsterdam UMC Location University of Amsterdam, University of Bologna, The University of Sydney, Stanford University, Johns Hopkins University, National Cancer Institute, Division of Cancer Epidemiology and Genetics, National Institute for Health and Care Research, NIHR Maudsley Biomedical Research Centre, University of Oxford, Institute for Molecular Bioscience, Amsterdam Neuroscience, Institute of Genetics and Cancer
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: NHS Blood and Transplant, National Alliance for Research on Schizophrenia and Depression, Health and Care Research Wales, Scottish Government, UK Research and Innovation, Amsterdam University Medical Centers, National Institute for Health and Care Research, Department of Health and Social Care, Scottish Funding Council, King's College London, Public Health Agency, Koninklijke Nederlandse Akademie van Wetenschappen, Eesti Teadusagentuur, Hjärt-Lungfonden, Karolinska Institutet, Vetenskapsrådet, Tartu Ülikool, Amsterdam Neuroscience, National Institutes of Health, NIHR BioResource, Medical Research Council, National Health and Medical Research Council, National Institute of Mental Health, HORIZON EUROPE European Research Council
Awards: G1112956173, G1280483720, G131530194, G1414424926, Subtype as a key to reduce heterogeneity of treatment effects in major depressive disorder, QSKIN: the genetics of skin cancer, G1709938403, G1794528886, Genetics and prediction of treatment-resistant depression, G2071942507, G2437620908, Genetic investigation of psychiatric and cardiovascular comorbidity: from mechanisms towards improved prevention, G2538920058, G2748385693, G3025591800, G3121967442, G3210000672, A Trans-Nordic Study of Extreme Major Depression, Advancing our understanding of Psychiatric Disorders through Imaging and Genetics, DTP Bid Led by University of Edinburgh, G383582915, G4214616087, Quantitative Genomics of Common Disease, TEDS 26: A longitudinal genetic approach to understanding the development and intergenerational transmission of common mental health conditions, Understanding the Genetic Basis of Treatment Response for Depression, Glasgow Application for a Mental Health Data Pathfinder award, G5201614120, Adding value to Medicare/PBS to find the genetic causes of mental health problems and translate this to preventive measures, Tackling heterogeneity in the etiology of major depressive disorder, G6206044308, G6706341188, G6739327530, Generating the evidence to control cancer and optimise outcomes, G6995567651, Embracing clinical heterogeneity in depression: using symptom-level genetic modelling to pave the way towards more effective and personalised treatments, Using genomics and imaging to advance our understanding of mental health challenges, G7969979309, Melanoma and Skin Cancer: Burden, Prevention and Control, The Swedish Twin Registry, G842161117, QSKIN: the burden of skin cancer, G8496923857, Right care, first time: delivering technology-enabled mental health care to young people at scale, G8724570043, An Integrative Approach to the Etiology of Internalizing Disorders in the Lifelines Cohort
OpenAlex ID: W7167348627