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Lu Y, Han L, Wang X, Liu X, Jia X, Lan K, Gao S, Feng Z, Yu L, Yang Q, Cui N, Wei YB, Liu JJ. Association between blood mitochondrial DNA copy number and mental disorders: A bidirectional two-sample mendelian randomization study. J Affect Disord 2024; 366:370-378. [PMID: 39197553 DOI: 10.1016/j.jad.2024.08.162] [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: 06/24/2024] [Revised: 08/22/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024]
Abstract
BACKGROUND Mitochondria is essential for cellular energy production, oxidative stress, and apoptosis. Mitochondrial DNA (mtDNA) encodes essential proteins for mitochondrial function. Although several studies have explored the association between changes in mtDNA copy number (mtDNA-CN) and risk of mental disorders, the results remain debated. This study used a bidirectional two-sample Mendelian randomization (MR) analysis to examine the genetic causality between mtDNA-CN and mental disorders. METHODS Genome-wide association study (GWAS) data for mtDNA-CN were sourced from UK biobank, involving 383,476 European cases. GWAS data for seven mental disorders-attention deficit/hyperactivity disorder, autism spectrum disorder (ASD), schizophrenia, bipolar disorder, major depressive disorder, anxiety, and obsessive-compulsive disorder-were primarily obtained from the Psychiatric Genomics Consortium. Causal associations were assessed using inverse variance weighting, with sensitivity analyses via the weighted median and MR-Egger methods. Reverse MR considered the seven mental disorders as exposures. All analyses were replicated with additional mtDNA-CN GWAS data from 465,809 individuals in the Heart and Ageing Research in Genomic Epidemiology consortium and the UK Biobank. RESULTS Forward MR observed a 27 % decrease in the risk of ASD per standard deviation increase in genetically determined blood mtDNA-CN (OR = 0.73, 95%CI: 0.58-0.92, p = 0.002), with no causal effects on other disorders. Additionally, reverse MR did not indicate a causal association between any of the mental disorders and mtDNA-CN. Validation analyses corroborated these findings, indicating their robustness. CONCLUSIONS Our study supports the potential causal association between mtDNA-CN and the risk of ASD, suggesting that mtDNA-CN could serve as a promising biomarker for early screening of ASD.
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Affiliation(s)
- Yan'e Lu
- School of Nursing, Peking University, Beijing 100191, China
| | - Lei Han
- Beijing Key Laboratory of Drug Dependence Research, National Institute on Drug Dependence, Peking University, Beijing 100191, China
| | - Xingxing Wang
- School of Nursing, Peking University, Beijing 100191, China
| | - Xiaotong Liu
- School of Nursing, Peking University, Beijing 100191, China
| | - Xinlei Jia
- School of Nursing, Peking University, Beijing 100191, China
| | - Kunyi Lan
- School of Nursing, Peking University, Beijing 100191, China
| | - Shumin Gao
- Beijing Key Laboratory of Drug Dependence Research, National Institute on Drug Dependence, Peking University, Beijing 100191, China
| | - Zhendong Feng
- Beijing Key Laboratory of Drug Dependence Research, National Institute on Drug Dependence, Peking University, Beijing 100191, China
| | - Lulu Yu
- Mental Health Center, the First Hospital of Hebei Medical University, Hebei Technical Innovation Center for Mental Health Assessment and Intervention, Shijiazhuang, Hebei Province 050031, China
| | - Qian Yang
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Naixue Cui
- School of Nursing and Rehabilitation, Shandong University, Shandong Province 250012, China
| | - Ya Bin Wei
- Beijing Key Laboratory of Drug Dependence Research, National Institute on Drug Dependence, Peking University, Beijing 100191, China.
| | - Jia Jia Liu
- School of Nursing, Peking University, Beijing 100191, China.
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2
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Chen X, Liu S, Liu C, Huang Y, Hou X, Zhuang J, Luo Y, Yu N, Zhuang J, Yu K. Genetic Evidence Supporting a Causal Role of Snoring in Keratoconus: A Bidirectional Mendelian Randomization Study. Cornea 2024:00003226-990000000-00730. [PMID: 39499135 DOI: 10.1097/ico.0000000000003741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 09/17/2024] [Indexed: 11/07/2024]
Abstract
PURPOSE To clarify the controversial causal association between snoring and keratoconus (KCN), which is crucial in clinical prevention and treatment. METHODS This is a 2-sample bidirectional mendelian randomization (MR) case-control study. MR is an innovative method that uses genetic variation as a natural experiment to investigate the causal relationships between potentially modifiable risk factors and health outcomes in observational data. The single nucleotide polymorphisms associated with snoring were retrieved from the UK biobank cohort with 218,346 participants (61,792 cases and 156,554 controls). The summary statistics of KCN were obtained from the European ancestry with 209,598 subjects (311 cases and 209,287 controls). The inverse-variance-weighted method was applied as the primary estimate, whereas weighted median and MR-pleiotropy residual sum and outlier played a subsidiary role. RESULTS Elevated risk of snoring showed a robust causal effect on KCN (inverse-variance-weighted: causal effect = 9.821, 95% confidence interval [CI], 1.944-17.699, P = 0.015), which was consistent with complementary methods of the weighted median (causal effect = 11.117, 95% CI, 2.603-19.631, P = 0.010), maximum likelihood (causal effect = 10.245, 95% CI, 3.967-16.523, P = 0.001), and MR-pleiotropy residual sum and outlier (causal effect = 9.793, 95% CI, 2.316-17.269, P = 0.028). However, there was no causality of KCN on the increasing risk of snoring. CONCLUSIONS This study provides genetic evidence supporting the causal role of snoring on KCN. Our findings provide new insights into potential strategies to manage KCN.
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Affiliation(s)
- Xi Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Shiji Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Chang Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Yuke Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Xiangtao Hou
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Jiejie Zhuang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Yiqi Luo
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Na Yu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Jing Zhuang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Keming Yu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Tianhe District, Guangzhou, China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China; and
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
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Solmi M, Miola A, Capone F, Pallottino S, Højlund M, Firth J, Siskind D, Holt RIG, Corbeil O, Cortese S, Dragioti E, Du Rietz E, Nielsen RE, Nordentoft M, Fusar-Poli P, Hartman CA, Høye A, Koyanagi A, Larsson H, Lehto K, Lindgren P, Manchia M, Skonieczna-Żydecka K, Stubbs B, Vancampfort D, Vieta E, Taipale H, Correll CU. Risk factors, prevention and treatment of weight gain associated with the use of antidepressants and antipsychotics: a state-of-the-art clinical review. Expert Opin Drug Saf 2024; 23:1249-1269. [PMID: 39225182 DOI: 10.1080/14740338.2024.2396396] [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: 01/05/2023] [Revised: 06/12/2024] [Accepted: 08/14/2024] [Indexed: 09/04/2024]
Abstract
INTRODUCTION People with severe mental illness have poor cardiometabolic health. Commonly used antidepressants and antipsychotics frequently lead to weight gain, which may further contribute to adverse cardiovascular outcomes. AREAS COVERED We searched MEDLINE up to April 2023 for umbrella reviews, (network-)meta-analyses, trials and cohort studies on risk factors, prevention and treatment strategies of weight gain associated with antidepressants/antipsychotics. We developed 10 clinical recommendations. EXPERT OPINION To prevent, manage, and treat antidepressant/antipsychotic-related weight gain, we recommend i) assessing risk factors for obesity before treatment, ii) monitoring metabolic health at baseline and regularly during follow-up, iii) offering lifestyle interventions including regular exercise and healthy diet based on patient preference to optimize motivation, iv) considering first-line psychotherapy for mild-moderate depression and anxiety disorders, v)choosing medications based on medications' and patient's weight gain risk, vi) choosing medications based on acute vs long-term treatment, vii) using effective, tolerated medications, viii) switching to less weight-inducing antipsychotics/antidepressants where possible, ix) using early weight gain as a predictor of further weight gain to inform the timing of intervention/switch options, and x) considering adding metformin or glucagon-like peptide-1 receptor agonists, or topiramate(second-line due to potential adverse cognitive effects) to antipsychotics, or aripiprazole to clozapine or olanzapine.
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Affiliation(s)
- Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada
- Department of Mental Health, The Ottawa Hospital, Ottawa, Ontario, Canada
- Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program, University of Ottawa, Ottawa, Ontario, Canada
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | | | - Federico Capone
- Department of Medicine (DIMED), Unit of Internal Medicine III, Padua University Hospital, University of Padua, Padova, Italy
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | | | - Mikkel Højlund
- Department of Psychiatry Aabenraa, Mental Health Services in the Region of Southern Denmark, Aabenraa, Denmark
- Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Joseph Firth
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Dan Siskind
- Metro South Addiction and Mental Health Service, Princess Alexandra Hospital, Brisbane, Qld, Australia
- Physical and Mental Health Research Stream, Queensland Centre for Mental Health Research, School of Clinical Medicine, Brisbane, Qld, Australia
| | - Richard I G Holt
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- Southampton National Institute for Health Research Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Olivier Corbeil
- Faculty of Pharmacy, Université Laval, Québec, Canada
- Department of Pharmacy, Quebec Mental Health University Institute, Québec, Canada
| | - Samuele Cortese
- Developmental EPI (Evidence synthesis, Prediction, Implementation) lab, Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Child and Adolescent Mental Health Service, Solent NHS Trust, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA
- DiMePRe-J-Department of Precision and Regenerative Medicine-Jonic Area, University of Bari 'Aldo Moro', Bari, Italy
| | - Elena Dragioti
- Pain and Rehabilitation Centre, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Research Laboratory Psychology of Patients, Families & Health Professionals, Department of Nursing, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - René Ernst Nielsen
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
- Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
| | - Merete Nordentoft
- Mental Health Centre Copenhagen, Department of Clinical Medicine, Copenhagen University Hospital, Glostrup, Denmark
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Outreach and Support in South-London (OASIS) service, South London and Maudlsey (SLaM) NHS Foundation Trust, London, UK
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University (LMU), Munich, Germany
| | - Catharina A Hartman
- Interdisciplinary Centre Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Anne Høye
- Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Mental Health and Substance Abuse, University Hospital of North Norway, Tromsø, Norway
| | - Ai Koyanagi
- Research and Development Unit, Parc Sanitari Sant Joan de Déu, Barcelona, Spain
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Peter Lindgren
- Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden
- The Swedish Institute for Health Economics, Lund, Sweden
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Brendon Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Davy Vancampfort
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- University Psychiatric Centre KU Leuven, Leuven, Belgium
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Heidi Taipale
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Psychiatry Research, Stockholm City Council, Stockholm, Sweden
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
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Luo X, Ruan Z, Liu L. The association between overweight and varying degrees of obesity with subjective well-being and depressive symptoms: A two sample Mendelian randomization study. J Psychosom Res 2024; 187:111940. [PMID: 39317092 DOI: 10.1016/j.jpsychores.2024.111940] [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: 03/06/2023] [Revised: 08/25/2024] [Accepted: 09/18/2024] [Indexed: 09/26/2024]
Abstract
OBJECTIVE This study utilized the Mendelian randomization (MR) method to elucidate the causal relationship between genetically predicted overweight and various degrees of obesity with depressive symptoms and subjective well-being (SWB). METHODS Pooled genome-wide association studies (GWAS) data for overweight (BMI ≥ 25 kg/m2), class 1 obesity (BMI ≥ 30 kg/m2), and class 2 obesity (BMI ≥ 35 kg/m2) were used as exposures. Summary GWAS data for depressive symptoms and SWB were used as outcomes. Multiple MR methods, primarily inverse-variance weighted (IVW), were applied, and sensitivity analyses were conducted to assess heterogeneity and pleiotropy. RESULTS The MR analysis provided evidence that genetically predicted overweight(IVW β = 0.033; 95 %CI 0.008-0.057; P = 0.010) and class 1 obesity(IVW β = -0.033; 95 %CI -0.047 - -0.020; P < 0.001) were causally associated with increased depressive symptoms. Genetically predicted class 2 obesity(IVW β = 1.428; 95 %CI 1.193-1.710; P < 0.001) were associated with reduced SWB. There was no strong evidence of a causal association between genetically predicted overweight and class 1 obesity with SWB. Similarly, genetically predicted class 2 and class 3 obesity did not show strong evidence of a causal association with depressive symptoms. Sensitivity analysis revealed relationships of a similar magnitude. CONCLUSION This genetically informed MR study suggests that Overweight and class 1 obesity may causally increased depressive symptoms but not decrease SWB. In contrast, class 2 obesity may causally decrease SWB but not increase depressive symptoms.
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Affiliation(s)
- Xinxin Luo
- Department of Pharmacy, Jiangxi Provincial People's Hospital & The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Zhichao Ruan
- First School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Ling Liu
- Department of Pharmacy, Jiangxi Provincial People's Hospital & The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
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5
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Beltrán-Garrayo L, Larsen JK, Eisinga R, Vink JM, Blanco M, Graell M, Sepúlveda AR. Childhood obesity and adolescent follow-up depressive symptoms: exploring a moderated mediation model of body esteem and gender. Eur Child Adolesc Psychiatry 2024; 33:2859-2869. [PMID: 38326572 PMCID: PMC11272700 DOI: 10.1007/s00787-023-02348-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 12/03/2023] [Indexed: 02/09/2024]
Abstract
Obesity is a well-recognized risk factor for adolescent depressive symptoms, but mediating mechanisms of this association have scarcely been studied. This study is unique in examining an indirect pathway of this link via body esteem (BE) prospectively from childhood (8-12 years) to adolescence (13-18 years). In addition, potential gender moderation was examined. This study utilized data from a case-control study comparing 100 children with and without obesity matched on important confounders (age, gender, and socioeconomic status). Our findings provide support for the mediating role of BE in the link between childhood weight status and adolescent depressive symptoms at a 5-year follow-up. This mediation effect did not differ between boys and girls. The findings suggest the relevance of specifically targeting children's BE in preventive intervention programs among children with obesity to prevent future mental health problems.
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Affiliation(s)
- Lucia Beltrán-Garrayo
- Department of Biological and Health Psychology, Faculty of Psychology, Autonomous University of Madrid, Madrid, Spain.
| | - Junilla K Larsen
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Rob Eisinga
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Miriam Blanco
- Department of Biological and Health Psychology, Faculty of Psychology, Autonomous University of Madrid, Madrid, Spain
| | - Montserrat Graell
- Department of Child and Adolescent Psychiatry and Psychology, University Hospital Niño Jesús, Madrid, Spain
| | - Ana Rosa Sepúlveda
- Department of Biological and Health Psychology, Faculty of Psychology, Autonomous University of Madrid, Madrid, Spain.
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6
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Lane MM, Travica N, Gamage E, Marshall S, Trakman GL, Young C, Teasdale SB, Dissanayaka T, Dawson SL, Orr R, Jacka FN, O'Neil A, Lawrence M, Baker P, Rebholz CM, Du S, Marx W. Sugar-Sweetened Beverages and Adverse Human Health Outcomes: An Umbrella Review of Meta-Analyses of Observational Studies. Annu Rev Nutr 2024; 44:383-404. [PMID: 39207876 DOI: 10.1146/annurev-nutr-062322-020650] [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: 09/04/2024]
Abstract
Our aim was to conduct an umbrella review of evidence from meta-analyses of observational studies investigating the link between sugar-sweetened beverage consumption and human health outcomes. Using predefined evidence classification criteria, we evaluated evidence from 47 meta-analyses encompassing 22,055,269 individuals. Overall, 79% of these analyses indicated direct associations between greater sugar-sweetened beverage consumption and higher risks of adverse health outcomes. Convincing evidence (class I) supported direct associations between sugar-sweetened beverage consumption and risks of depression, cardiovascular disease, nephrolithiasis, type 2 diabetes mellitus, and higher uric acid concentrations. Highly suggestive evidence (class II) supported associations with risks of nonalcoholic fatty liver disease and dental caries. Out of the remaining 40 meta-analyses, 29 were graded as suggestive or weak in the strength of evidence (classes III and IV), and 11 showed no evidence (class V). These findings inform and provide support for population-based and public health strategies aimed at reducing sugary drink consumption for improved health.
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Affiliation(s)
- Melissa M Lane
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Nikolaj Travica
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Elizabeth Gamage
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Skye Marshall
- Research Institute for Future Health, Gold Coast, Queensland, Australia
- Bond University Nutrition and Dietetics Research Group, Faculty of Health Science and Medicine, Bond University, Gold Coast, Queensland, Australia
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Gina L Trakman
- Department of Food, Nutrition, and Dietetics, Sport, Performance, and Nutrition Research Group, La Trobe University, Melbourne, Victoria, Australia
| | - Claire Young
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Scott B Teasdale
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
- Mindgardens Neuroscience Network, Randwick, New South Wales, Australia
| | - Thusharika Dissanayaka
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Samantha L Dawson
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Rebecca Orr
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Felice N Jacka
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Immunology, Therapeutics, and Vaccines, James Cook University, Townsville, Queensland, Australia
| | - Adrienne O'Neil
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
| | - Mark Lawrence
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - Phillip Baker
- Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Shutong Du
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Wolfgang Marx
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), Food & Mood Centre, School of Medicine, Deakin University, Barwon Health, Geelong, Victoria, Australia;
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7
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Chen S, Zhang H, Gao M, Machado DB, Jin H, Scherer N, Sun W, Sha F, Smythe T, Ford TJ, Kuper H. Dose-Dependent Association Between Body Mass Index and Mental Health and Changes Over Time. JAMA Psychiatry 2024; 81:797-806. [PMID: 38748415 PMCID: PMC11097104 DOI: 10.1001/jamapsychiatry.2024.0921] [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: 10/23/2023] [Accepted: 03/06/2024] [Indexed: 05/18/2024]
Abstract
Importance Overweight and obesity affect 340 million adolescents worldwide and constitute a risk factor for poor mental health. Understanding the association between body mass index (BMI) and mental health in adolescents may help to address rising mental health issues; however, existing studies lack comprehensive evaluations spanning diverse countries and periods. Objective To estimate the association between BMI and mental health and examine changes over time from 2002 to 2018. Design, Setting, and Participants This was a repeated multicountry cross-sectional study conducted between 2002 and 2018 and utilizing data from the Health Behaviour in School-aged Children (HBSC) survey in Europe and North America. The study population consisted of more than 1 million adolescents aged 11 to 15 years, with all surveyed children included in the analysis. Data were analyzed from October 2022 to March 2023. Main Outcomes and Measures Mental health difficulties were measured by an 8-item scale for psychological concerns, scoring from 0 to 32, where a higher score reflects greater psychosomatic issues. BMI was calculated using weight divided by height squared and adjusted for age and sex. Data were fitted by multilevel generalized additive model. Confounders included sex, living with parents, sibling presence, academic pressure, the experience of being bullied, family affluence, screen time, and physical activity. Results Our analysis of 1 036 869 adolescents surveyed from 2002 to 2018, with a mean (SD) age of 13.55 (1.64) years and comprising 527 585 girls (50.9%), revealed a consistent U-shaped association between BMI and mental health. After accounting for confounders, adolescents with low body mass and overweight or obesity had increased psychosomatic symptoms compared to those with healthy weight (unstandardized β, 0.14; 95% CI, 0.08 to 0.19; unstandardized β, 0.27; 95% CI, 0.24 to 0.30; and unstandardized β, 0.62; 95% CI, 0.56 to 0.67, respectively), while adolescents with underweight had fewer symptoms (unstandardized β, -0.18; 95% CI, -0.22 to -0.15). This association was observed across different years, sex, and grade, indicating a broad relevance to adolescent mental health. Compared to 2002, psychosomatic concerns increased significantly in 2006 (unstandardized β, 0.19; 95% CI, 0.11 to 0.26), 2010 (unstandardized β, 0.14; 95% CI, 0.07 to 0.22), 2014 (unstandardized β, 0.48; 95% CI, 0.40 to 0.56), and 2018 (unstandardized β, 0.82; 95% CI, 0.74 to 0.89). Girls reported significantly higher psychosomatic concerns than boys (unstandardized β, 2.27; 95% CI, 2.25 to 2.30). Compared to primary school, psychosomatic concerns rose significantly in middle school (unstandardized β, 1.15; 95% CI, 1.12 to 1.18) and in high school (unstandardized β, 2.12; 95% CI, 2.09 to 2.15). Conclusions and Relevance Our study revealed a U-shaped association between adolescent BMI and mental health, which was consistent across sex and grades and became stronger over time. These insights emphasize the need for targeted interventions addressing body image and mental health, and call for further research into underlying mechanisms.
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Affiliation(s)
- Shanquan Chen
- International Centre for Evidence in Disability, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Hao Zhang
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Min Gao
- Nuffield Department of Primary Care Health, University of Oxford, Oxford, United Kingdom
- National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Daiane Borges Machado
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts
- Center of Data and Knowledge Integration for Health, Fiocruz, Salvador, Brazil
| | - Huajie Jin
- Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Nathaniel Scherer
- International Centre for Evidence in Disability, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Wei Sun
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Feng Sha
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Tracey Smythe
- International Centre for Evidence in Disability, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Division of Physiotherapy, Department of Health and Rehabilitation Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tamsin J. Ford
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Hannah Kuper
- International Centre for Evidence in Disability, London School of Hygiene & Tropical Medicine, London, United Kingdom
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Tsang RSM, Stow D, Kwong ASF, Donnelly NA, Fraser H, Barroso IA, Holmans PA, Owen MJ, Wood ML, van den Bree MBM, Timpson NJ, Khandaker GM. Immunometabolic Blood Biomarkers of Developmental Trajectories of Depressive Symptoms: Findings From the ALSPAC Birth Cohort. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.12.24310330. [PMID: 39040209 PMCID: PMC11261916 DOI: 10.1101/2024.07.12.24310330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Studies of longitudinal trends of depressive symptoms in young people could provide insight into aetiologic mechanism, heterogeneity and origin of common cardiometabolic comorbidities for depression. Depression is associated with immunological and metabolic alterations, but immunometabolic characteristics of developmental trajectories of depressive symptoms remain unclear. Using depressive symptoms scores measured on 10 occasions between ages 10 and 25 years in the Avon Longitudinal Study of Parents and Children (n=7302), we identified four distinct trajectories: low-stable (70% of the sample), adolescent-limited (13%), adulthood-onset (10%) and adolescent-persistent (7%). We examined associations of these trajectories with: i) anthropometric, cardiometabolic and psychiatric phenotypes using multivariable regression (n=1709-3410); ii) 67 blood immunological proteins and 57 metabolomic features using empirical Bayes moderated linear models (n=2059 and n=2240 respectively); and iii) 28 blood cell counts and biochemical measures using multivariable regression (n=2256). Relative to the low-stable group, risk of depression and anxiety in adulthood was higher for all other groups, especially in the adolescent-persistent (ORdepression=22.80, 95% CI 15.25-34.37; ORGAD=19.32, 95% CI 12.86-29.22) and adulthood-onset (ORdepression=7.68, 95% CI 5.31-11.17; ORGAD=5.39, 95% CI 3.65-7.94) groups. The three depression-related trajectories vary in their immunometabolic profile, with evidence of little or no alterations in the adolescent-limited group. The adulthood-onset group shows widespread classical immunometabolic changes (e.g., increased immune cell counts and insulin resistance), while the adolescent-persistent group is characterised by higher BMI both in childhood and adulthood with few other immunometabolic changes. These findings point to distinct mechanisms and intervention opportunities for adverse cardiometabolic profile in different groups of young people with depression.
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Affiliation(s)
- Ruby S M Tsang
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Bristol, UK
| | - Daniel Stow
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Alex S F Kwong
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Nicholas A Donnelly
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon and Wiltshire NHS Mental Health Partnership NHS Trust, Bristol, UK
| | - Holly Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Bristol, UK
| | - Inês A Barroso
- Exeter Centre of Excellence for Diabetes Research, University of Exeter, UK
| | - Peter A Holmans
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Megan L Wood
- School of Psychology, University of Leeds, Leeds, UK
| | - Marianne B M van den Bree
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Golam M Khandaker
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
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9
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Jibril AT, Ganjeh BJ, Mirrafiei A, Firouzi M, Norouziasl R, Ghaemi S, Bafkar N, Jayedi A, Djafarian K, Shab-Bidar S. Dose-response association of obesity and risk of mental health among tehranian residents: result of a cross-sectional study. BMC Public Health 2024; 24:1444. [PMID: 38811944 PMCID: PMC11138087 DOI: 10.1186/s12889-024-18670-z] [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: 06/05/2023] [Accepted: 04/19/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND Obesity and mental health issues are two of the most prevalent global public health issues for a significant portion of people. The purpose of this study was to investigate the relationship between obesity indicators and mental health in Tehran-dwelling Iranian adults. METHODS We conducted a cross-sectional study on healthy Iranian adults using a convenience sampling technique. The short form of the Depression Anxiety and Stress Scale (DASS-21) was used to measure the outcome, and independent variables included body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body adiposity index (BAI), and a body shape index (ABSI). The relationship between obesity and mental health was investigated using a multivariate logistic regression model. The non-linear dose-response relationships were evaluated using restricted cubic splines (RCS) with three knots. The Benjamini-Hochberg procedure was used to adjust for multiple testing. RESULTS In our study of 434 participants, females made up 52% of the participants, with a mean age of 38.57 years. In all, 54.6%, 53.9%, and 56.6% were classified as having anxiety, depression, and stress respectively. Logistic regression analysis showed that the odds of mental health components including anxiety, depression, or stress was not significantly different across the tertiles of the obesity indicators. We observed a significant dose-response relationship between BAI and ABSI and the risk of anxiety (PBenjamini-Hochberg 0.028 > Pdose-response 0.023) and stress (PBenjamini-Hochberg 0.028 > Pdose-response 0.003) but not depression (PBenjamini-Hochberg 0.014 < Pdose-response 0.018). The lowest risk for anxiety was observed in people with a BAI of 28% and ABSI equal to 0.079. The risk of stress seemed to increase beyond an ABSI of 0.086. CONCLUSION Our findings showed no direct linear association between obesity indices and anxiety. However, a dose-response relationship was observed between BAI and ABSI and the risk of anxiety and stress, indicating the need for further investigation.
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Affiliation(s)
- Aliyu Tijani Jibril
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Bahareh Jabbarzadeh Ganjeh
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Amin Mirrafiei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahsa Firouzi
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Reyhane Norouziasl
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Shadi Ghaemi
- Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran
| | - Negar Bafkar
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Jayedi
- Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran
| | - Kurosh Djafarian
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sakineh Shab-Bidar
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
- Sports Medicine Research Center, Neuroscience Institute, Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
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10
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Chai L. Interplay between actual and perceived weight on mental health among Canadian Indigenous post-secondary students. JOURNAL OF AMERICAN COLLEGE HEALTH : J OF ACH 2024:1-9. [PMID: 38592936 DOI: 10.1080/07448481.2024.2338419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/22/2024] [Indexed: 04/11/2024]
Abstract
OBJECTIVES Research increasingly focuses on the mental health implications of both actual and perceived weight, particularly among post-secondary students. Considering their unique socio-cultural context and the frequent oversight in research, this study examines these implications specifically among Canadian Indigenous post-secondary students. Recent evidence indicates that students with normal weight may also experience increased mental health risks due to negative weight perceptions. Therefore, this study explores the independent and combined effects of actual and perceived weight on the mental health of this group. PARTICIPANTS AND METHODS This study utilized data from the 2017 Aboriginal Peoples Survey, a nationally representative sample of First Nations peoples living off-reserve, Métis, and Inuit. The focus was on Canadian Indigenous post-secondary students aged 19-34 years (n = 1,518). Logistic regression models, stratified by sex, were employed to analyze the data. RESULTS Perceptions of being overweight were linked to a higher risk of mood and anxiety disorders, poor self-rated mental health, and suicidal ideation among female students. This pattern was less evident among male students. Notably, female students who were overweight and perceived themselves as such were more likely to report poor mental health across all four indicators examined. In contrast, male students exhibited a less clear pattern. Diverging from recent studies, the findings indicated less robust mental health disparities among students with normal weight who perceived themselves as overweight, potentially due to the insufficient cell size of this category among Indigenous post-secondary students. CONCLUSIONS The study highlights the complex interplay between actual and perceived weight and its impact on mental health, particularly among female Indigenous post-secondary students.
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Affiliation(s)
- Lei Chai
- Department of Sociology, University of Toronto, Toronto, Ontario, Canada
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11
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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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Berk M, Köhler-Forsberg O, Turner M, Penninx BWJH, Wrobel A, Firth J, Loughman A, Reavley NJ, McGrath JJ, Momen NC, Plana-Ripoll O, O'Neil A, Siskind D, Williams LJ, Carvalho AF, Schmaal L, Walker AJ, Dean O, Walder K, Berk L, Dodd S, Yung AR, Marx W. Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management. World Psychiatry 2023; 22:366-387. [PMID: 37713568 PMCID: PMC10503929 DOI: 10.1002/wps.21110] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/17/2023] Open
Abstract
Populations with common physical diseases - such as cardiovascular diseases, cancer and neurodegenerative disorders - experience substantially higher rates of major depressive disorder (MDD) than the general population. On the other hand, people living with MDD have a greater risk for many physical diseases. This high level of comorbidity is associated with worse outcomes, reduced adherence to treatment, increased mortality, and greater health care utilization and costs. Comorbidity can also result in a range of clinical challenges, such as a more complicated therapeutic alliance, issues pertaining to adaptive health behaviors, drug-drug interactions and adverse events induced by medications used for physical and mental disorders. Potential explanations for the high prevalence of the above comorbidity involve shared genetic and biological pathways. These latter include inflammation, the gut microbiome, mitochondrial function and energy metabolism, hypothalamic-pituitary-adrenal axis dysregulation, and brain structure and function. Furthermore, MDD and physical diseases have in common several antecedents related to social factors (e.g., socioeconomic status), lifestyle variables (e.g., physical activity, diet, sleep), and stressful live events (e.g., childhood trauma). Pharmacotherapies and psychotherapies are effective treatments for comorbid MDD, and the introduction of lifestyle interventions as well as collaborative care models and digital technologies provide promising strategies for improving management. This paper aims to provide a detailed overview of the epidemiology of the comorbidity of MDD and specific physical diseases, including prevalence and bidirectional risk; of shared biological pathways potentially implicated in the pathogenesis of MDD and common physical diseases; of socio-environmental factors that serve as both shared risk and protective factors; and of management of MDD and physical diseases, including prevention and treatment. We conclude with future directions and emerging research related to optimal care of people with comorbid MDD and physical diseases.
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Affiliation(s)
- Michael Berk
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Ole Köhler-Forsberg
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Megan Turner
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Brenda W J H Penninx
- Department of Psychiatry and Amsterdam Public Health, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Anna Wrobel
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Joseph Firth
- Division of Psychology and Mental Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Amy Loughman
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Nicola J Reavley
- Centre for Mental Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Queensland Centre for Mental Health Research, Park Centre for Mental Health, Brisbane, QLD, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Natalie C Momen
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
| | - Oleguer Plana-Ripoll
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
| | - Adrienne O'Neil
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Dan Siskind
- Queensland Centre for Mental Health Research, Park Centre for Mental Health, Brisbane, QLD, Australia
- Metro South Addiction and Mental Health Service, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Lana J Williams
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Andre F Carvalho
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Lianne Schmaal
- Centre for Youth Mental Health, University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Adam J Walker
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Olivia Dean
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Ken Walder
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Lesley Berk
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Seetal Dodd
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Alison R Yung
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Wolfgang Marx
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
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Jokela M, Laakasuo M. Obesity as a causal risk factor for depression: Systematic review and meta-analysis of Mendelian Randomization studies and implications for population mental health. J Psychiatr Res 2023; 163:86-92. [PMID: 37207436 DOI: 10.1016/j.jpsychires.2023.05.034] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/17/2023] [Accepted: 05/03/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND/OBJECTIVES Obesity has been associated with elevated risk of depression. If this association is causal, the increasing obesity prevalence might lead to worsening population mental health, but the strength of the causal effect has not been systematically evaluated. SUBJECTS/METHODS The current study provides a systematic review and meta-analysis of studies examining associations between body mass index and depression using Mendelian randomization with multiple genetic variants as instruments for body mass index. We used this estimate to calculate the expected changes in prevalence of population psychological distress from the 1990s-2010s, which were compared with the empirically observed trends in psychological distress in the Health Survey for England (HSE) and U.S. National Health Interview Surveys (NHIS). RESULTS Meta-analysis of 8 Mendelian randomization studies indicated an OR = 1.33 higher depression risk associated with obesity (95% confidence interval 1.19, 1.48). Between 15% and 20% of the participants of HSE and NHIS reported at least moderate psychological distress. The increase of obesity prevalence from the 1990s-2010s in HSE and NHIS would have led to a 0.6 percentage-point increase in population psychological distress. CONCLUSIONS Mendelian randomization studies suggest that obesity is a causal risk factor for elevated risk of depression. The increasing obesity rates may have modestly increased the prevalence of depressive symptoms in the general population. Mendelian randomization relies on methodological assumptions that may not always hold, so other quasi-experimental methods are needed to confirm the current conclusions.
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Affiliation(s)
- Markus Jokela
- Department of Psychology and Logopedics, Medicum, University of Helsinki, Finland.
| | - Michael Laakasuo
- Department of Psychology and Logopedics, Medicum, University of Helsinki, Finland
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Baltramonaityte V, Pingault JB, Cecil CAM, Choudhary P, Järvelin MR, Penninx BWJH, Felix J, Sebert S, Milaneschi Y, Walton E. A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity. PLoS Genet 2023; 19:e1010508. [PMID: 37390107 DOI: 10.1371/journal.pgen.1010508] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.
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Affiliation(s)
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational, and Health Psychology, University College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marjo-Riitta Järvelin
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Janine Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sylvain Sebert
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, United Kingdom
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van Haeringen M, Milaneschi Y, Lamers F, Penninx BW, Jansen R. Dissection of depression heterogeneity using proteomic clusters. Psychol Med 2023; 53:2904-2912. [PMID: 35039097 PMCID: PMC10235664 DOI: 10.1017/s0033291721004888] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 09/23/2021] [Accepted: 11/05/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND The search for relevant biomarkers of major depressive disorder (MDD) is challenged by heterogeneity; biological alterations may vary in patients expressing different symptom profiles. Moreover, most research considers a limited number of biomarkers, which may not be adequate for tagging complex network-level mechanisms. Here we studied clusters of proteins and examined their relation with MDD and individual depressive symptoms. METHODS The sample consisted of 1621 subjects from the Netherlands Study of Depression and Anxiety (NESDA). MDD diagnoses were based on DSM-IV criteria and the Inventory of Depressive Symptomatology questionnaire measured endorsement of 30 symptoms. Serum protein levels were detected using a multi-analyte platform (171 analytes, immunoassay, Myriad RBM DiscoveryMAP 250+). Proteomic clusters were computed using weighted correlation network analysis (WGCNA). RESULTS Six proteomic clusters were identified, of which one was nominally significantly associated with current MDD (p = 9.62E-03, Bonferroni adj. p = 0.057). This cluster contained 21 analytes and was enriched with pathways involved in inflammation and metabolism [including C-reactive protein (CRP), leptin and insulin]. At the individual symptom level, this proteomic cluster was associated with ten symptoms, among which were five atypical, energy-related symptoms. After correcting for several health and lifestyle covariates, hypersomnia, increased appetite, panic and weight gain remained significantly associated with the cluster. CONCLUSIONS Our findings support the idea that alterations in a network of proteins involved in inflammatory and metabolic processes are present in MDD, but these alterations map predominantly to clinical symptoms reflecting an imbalance between energy intake and expenditure.
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Affiliation(s)
- Marije van Haeringen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Femke Lamers
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Brenda W.J.H. Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, The Netherlands
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Palmos AB, Hübel C, Lim KX, Hunjan AK, Coleman JR, Breen G. Assessing the Evidence for Causal Associations Between Body Mass Index, C-Reactive Protein, Depression, and Reported Trauma Using Mendelian Randomization. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:110-118. [PMID: 36712567 PMCID: PMC9874165 DOI: 10.1016/j.bpsgos.2022.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 02/01/2023] Open
Abstract
Background Traumatic experiences are described as the strongest predictors of major depressive disorder (MDD), with inflammation potentially mediating the association between trauma and symptom onset. However, several studies indicate that body mass index (BMI) exerts a large confounding effect on both inflammation and MDD. Methods First, we sought to replicate previously reported associations between these traits in a large subset of the UK Biobank, using regression models with C-reactive protein (CRP) and MDD and as the outcome variables in 113,481 and 30,137 individuals, respectively. Second, we ran bidirectional Mendelian randomization analyses between these traits to establish a potential causal framework between BMI, MDD, reported childhood trauma, and inflammation. Results Our phenotypic analyses revealed no association between CRP and MDD but did suggest a strong effect of BMI and reported trauma on both CRP (BMI: β = 0.43, 95% CI = 0.43-0.43, p ≤ .001; childhood trauma: β = 0.02, 95% CI = 0.00-0.03, p = .006) and MDD (BMI: odds ratio [OR] = 1.16, 95% CI = 1.14-1.19, p ≤ .001; childhood trauma: OR = 1.99, 95% CI = 1.88-2.11, p ≤ .001). Our Mendelian randomization analyses confirmed a lack of causal relationship between CRP and MDD but showed evidence consistent with a strong causal influence of higher BMI on increased CRP (β = 0.37, 95% CI = 0.36-0.39, p ≤ .001) and a bidirectional influence between reported trauma and MDD (OR trauma-MDD = 1.75, 95% CI = 1.49-2.07, p ≤ .001; OR MDD-trauma = 1.22, 95% CI = 1.18-1.27, p ≤ .001). Conclusions Our findings highlight the importance of controlling for both BMI and trauma when studying MDD in the context of inflammation. They also suggest that the experience of traumatic events can increase the risk for MDD and that MDD can increase the experience of traumatic events.
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Affiliation(s)
- Alish B. Palmos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- UK National Institute for Health Research Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, United Kingdom
| | - Christopher Hübel
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- UK National Institute for Health Research Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, United Kingdom
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
| | - Kai Xiang Lim
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Avina K. Hunjan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- UK National Institute for Health Research Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, United Kingdom
| | - Jonathan R.I. Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- UK National Institute for Health Research Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, United Kingdom
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He R, Zheng R, Zheng J, Li M, Wang T, Zhao Z, Wang S, Lin H, Lu J, Chen Y, Xu Y, Wang W, Xu M, Bi Y, Ning G. Causal association between obesity, circulating glutamine levels, and depression: a Mendelian randomization study. J Clin Endocrinol Metab 2022; 108:1432-1441. [PMID: 36510667 DOI: 10.1210/clinem/dgac707] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/02/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Observational studies indicated obesity and glutamatergic dysfunction as potential risk factors of depression, and reported disturbance of glutamine metabolism in obese state. However, it remains unclear whether the inter-relationships between obesity, glutamine and depression are causal. METHODS We conducted two-sample bidirectional Mendelian Randomization (MR) analyses to explore the causalities between circulating glutamine levels, specific depressive symptoms, major depressive disorder (MDD) and body mass index (BMI). Univariable MR, multivariable MR (MVMR) and linkage disequilibrium score regression (LDSR) analyses were performed. RESULTS Genetic downregulation of glutamine was causally associated with MDD, anhedonia, tiredness, and depressed mood at the false discovery rate (FDR)-controlled significance level (estimate, -0·036∼ -0·013, P = 0·005 to P = 0·050). Elevated BMI was causally linked to lower glutamine level (estimate = -0·103, P = 0·037), as well as more severe depressed mood, tiredness, and anhedonia (estimate, 0·017∼0·050, P < 0·001 to P = 0·040). In MVMR analysis, BMI was causally related to depressed mood dependently of glutamine levels. Reversely, it showed limited evidence supporting causal effects of depression on glutamine levels or BMI, except a causal association of tiredness with elevated BMI (estimate = 0·309, P = 0·003). LDSR estimates were directionally consistent with MR results. CONCLUSION The present study reported that higher BMI was causally associated with lower glutamine levels. Both obesity and down-regulation of glutamine were causally linked to depression.
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Affiliation(s)
- Ruixin He
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ruizhi Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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18
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Frank P, Jokela M, Batty GD, Lassale C, Steptoe A, Kivimäki M. Overweight, obesity, and individual symptoms of depression: A multicohort study with replication in UK Biobank. Brain Behav Immun 2022; 105:192-200. [PMID: 35853559 PMCID: PMC10499756 DOI: 10.1016/j.bbi.2022.07.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 07/14/2022] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVES Obesity is associated with increased risk of depression, but the extent to which this association is symptom-specific is unknown. We examined the associations of overweight and obesity with individual depressive symptoms. METHODS We pooled data from 15 population-based cohorts comprising 57,532 individuals aged 18 to 100 years at study entry. Primary analyses were replicated in an independent cohort, the UK Biobank study (n = 122,341, age range 38 to 72). Height and weight were assessed at baseline and body mass index (BMI) was computed. Using validated self-report measures, 24 depressive symptoms were ascertained once in 16 cross-sectional, and twice in 7 prospective cohort studies (mean follow-up 3.2 years). RESULTS In the pooled analysis of the primary cohorts, 22,045 (38.3 %) participants were overweight (BMI between 25 and 29.9 kg/m2), 12,025 (20.9 %) class I obese (BMI between 30 and 34.9 kg/m2), 7,467 (13.0 %) class II-III obese (BMI ≥ 35 kg/m2); and 7,046 (12.3 %) were classified as depressed. After multivariable adjustment, obesity class I was cross-sectionally associated with 1.11-fold (95 % confidence interval 1.01-1.22), and obesity class II-III with 1.31-fold (1.16-1.49) higher odds of overall depression. In symptom-specific analyses, robust associations were apparent for 4 of the 24 depressive symptoms ('could not get going/lack of energy', 'little interest in doing things', 'feeling bad about yourself, and 'feeling depressed'), with confounder-adjusted odds ratios of having 3 or 4 of these symptoms being 1.32 (1.10-1.57) for individuals with obesity class I, and 1.70 (1.34-2.14) for those with obesity class II-III. Elevated C-reactive protein and 21 obesity-related diseases explained 23 %-31 % of these associations. Symptom-specific associations were confirmed in longitudinal analyses where obesity preceded symptom onset, were stronger in women compared with men, and were replicated in UK Biobank. CONCLUSIONS Obesity is associated with a distinct set of depressive symptoms. These associations are partially explained by systemic inflammation and obesity-related morbidity. Awareness of this obesity-related symptom profile and its underlying biological correlates may inform better targeted treatments for comorbid obesity and depression.
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Affiliation(s)
- Philipp Frank
- Research Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, WC1E 6BT London, UK; Research Department of Behavioural Science and Health, University College, London, 1-19 Torrington Place, WC1E 7HB London, UK.
| | - Markus Jokela
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Haartmaninkatu 3, Helsinki 00290, Finland.
| | - G David Batty
- Research Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, WC1E 6BT London, UK.
| | - Camille Lassale
- Hospital del Mar Research Institute (IMIM), Dr Aiguader 88, 08003 Barcelona, Spain.
| | - Andrew Steptoe
- Research Department of Behavioural Science and Health, University College, London, 1-19 Torrington Place, WC1E 7HB London, UK.
| | - Mika Kivimäki
- Research Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, WC1E 6BT London, UK; Clinicum, Faculty of Medicine, University of Helsinki, Tukholmankatu 8 B, FI-00014 Helsinki, Finland.
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19
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Steel A. Naturopathic patient care during different life stages: an international observational study of naturopathic practitioners and their patients. BMC Health Serv Res 2022; 22:947. [PMID: 35883061 PMCID: PMC9316703 DOI: 10.1186/s12913-022-08344-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 07/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND An individual's health status varies with age, with most health problems increasing through different life stages. Yet, a key feature of the majority of conditions contributing burden to society globally, irrespective of life stage, is the predominance of chronic, non-communicable diseases (NCDs). An important response to this growing burden is the increasing recognition of addressing NCD prevention through a life-course perspective through primary care and public health. Naturopathy is a traditional medicine system originating from Europe, and its practitioners commonly provide primary care and focus on prevention and wellness. However, little is known about naturopathic practitioners (NPs) contribution to health care across different life stages. METHODS This secondary analysis of a cross-sectional study aimed to describe the approach to the care of NPs based on the life stage of their patients. The primary study recruited NPs from 14 regions or countries, who were invited to complete a short survey about 20 consecutive patients. The multilingual survey included the following domains: patient demographics, reason for visit, prescribed or recommended treatments, and naturopathic interpretation of the health conditions. Descriptive statistics were tabulated as frequencies and percentages and chi square tests were used to test associations and compare groups. Effect size was determined by Cramer's V. RESULTS Participant NPs (n = 56) provided consultation details for 854 patients encounters. There were differences in the patient's primary reason for visiting, the additional physiological systems the NP considered important in the management of the patient's health, and the treatments prescribed across all life stages. However, diet (45.1-70.0%) and lifestyle (14.3-60.0%) prescription were the most common categories of treatments across all patient groups. CONCLUSION NPs provide care to patients across all life stages, and diverse conditions pertinent to those life stages while also demonstrating a holistic approach that considers broader health concerns and long term treatment practices. While there may be emerging evidence supporting and informing NP clinical outcomes, the breadth and diversity of health conditions, populations and treatments within the scope of naturopathic practice underscores a need for urgent and widescale research investigating naturopathic care across the life course.
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Affiliation(s)
- Amie Steel
- Australian Research Centre in Complementary and Integrative Medicine, School of Public Health, Faculty of Health, University of Technology Sydney, Ultimo, 2006, Australia.
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20
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Bidirectional two-sample Mendelian randomization analysis identifies causal associations between relative carbohydrate intake and depression. Nat Hum Behav 2022; 6:1569-1576. [DOI: 10.1038/s41562-022-01412-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 06/15/2022] [Indexed: 02/06/2023]
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21
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Mbutiwi FIN, Dessy T, Sylvestre MP. Mendelian Randomization: A Review of Methods for the Prevention, Assessment, and Discussion of Pleiotropy in Studies Using the Fat Mass and Obesity-Associated Gene as an Instrument for Adiposity. Front Genet 2022; 13:803238. [PMID: 35186031 PMCID: PMC8855149 DOI: 10.3389/fgene.2022.803238] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 01/14/2022] [Indexed: 11/25/2022] Open
Abstract
Pleiotropy assessment is critical for the validity of Mendelian randomization (MR) analyses, and its management remains a challenging task for researchers. This review examines how the authors of MR studies address bias due to pleiotropy in practice. We reviewed Pubmed, Medline, Embase and Web of Science for MR studies published before 21 May 2020 that used at least one single-nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene as instrumental variable (IV) for body mass index, irrespective of the outcome. We reviewed: 1) the approaches used to prevent pleiotropy, 2) the methods cited to detect or control the independence or the exclusion restriction assumption highlighting whether pleiotropy assessment was explicitly stated to justify the use of these methods, and 3) the discussion of findings related to pleiotropy. We included 128 studies, of which thirty-three reported one approach to prevent pleiotropy, such as the use of multiple (independent) SNPs combined in a genetic risk score as IVs. One hundred and twenty studies cited at least one method to detect or account for pleiotropy, including robust and other IV estimation methods (n = 70), methods for detection of heterogeneity between estimated causal effects across IVs (n = 72), methods to detect or account associations between IV and outcome outside thought the exposure (n = 85), and other methods (n = 5). Twenty-one studies suspected IV invalidity, of which 16 explicitly referred to pleiotropy, and six incriminating FTO SNPs. Most reviewed MR studies have cited methods to prevent or to detect or control bias due to pleiotropy. These methods are heterogeneous, their triangulation should increase the reliability of causal inference.
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Affiliation(s)
- Fiston Ikwa Ndol Mbutiwi
- University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC, Canada
- Faculty of Medicine, University of Kikwit, Kikwit, Democratic Republic of the Congo
| | - Tatiana Dessy
- University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC, Canada
| | - Marie-Pierre Sylvestre
- University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC, Canada
- Department of Social and Preventive Medicine, University of Montreal Public Health School (ESPUM), Montreal, QC, Canada
- *Correspondence: Marie-Pierre Sylvestre,
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22
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Adame JL, Lo CC, Cheng TC. Ethnicity and Self-reported Depression Among Hispanic Immigrants in the U.S. Community Ment Health J 2022; 58:121-135. [PMID: 33604742 DOI: 10.1007/s10597-021-00801-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 02/09/2021] [Indexed: 12/29/2022]
Abstract
Viewed to be healthier than ethnic Hispanics born in the United States, Hispanic immigrants represent numerous subgroups with clearly heterogeneous geographic, cultural, structural, and social origins. This study asked how the factors length of U.S. residency, social status, lifestyle, and health care might explain self-reported depression within 5 large, discrete subgroups comprising immigrants from, in turn, Mexico, Puerto Rico, Cuba, the Dominican Republic, and other nations in Central and South America. The study also examined ethnicity's potential role moderating self-reported depression's associations. With pooled data from National Health Interview Surveys 1999-2015, it evaluated each ethnic group separately. Self-reported depression was associated generally with lengthening residence in the U.S., with being female, with poverty, with unemployment, with lack of education, and with lifestyle and health-care factors. These associations were not uniform across ethnic groups, however. Where self-reported depression is concerned, descriptive results suggest the proverbial health advantage may largely accrue specifically to Hispanic immigrants of Cuban and of Central/South American origin.
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Affiliation(s)
- Jessica L Adame
- Department of Sociology, Texas Woman's University, CFO 305, P.O. Box 425887, Denton, TX, 76204, USA
| | - Celia C Lo
- Department of Sociology, Texas Woman's University, CFO 305, P.O. Box 425887, Denton, TX, 76204, USA.
| | - Tyrone C Cheng
- School of Social Work, University of Alabama, Tuscaloosa, AL, USA
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23
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Casanova F, O’Loughlin J, Martin S, Beaumont RN, Wood AR, Watkins ER, Freathy RM, Hagenaars SP, Frayling TM, Yaghootkar H, Tyrrell J. Higher adiposity and mental health: causal inference using Mendelian randomization. Hum Mol Genet 2021; 30:2371-2382. [PMID: 34270736 PMCID: PMC8643500 DOI: 10.1093/hmg/ddab204] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/24/2021] [Accepted: 07/12/2021] [Indexed: 11/14/2022] Open
Abstract
Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one- and two- sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß: -0.15, 95%CI: -0.26, -0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being.
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Affiliation(s)
- Francesco Casanova
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Jessica O’Loughlin
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Susan Martin
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Robin N Beaumont
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Andrew R Wood
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Edward R Watkins
- Mood Disorders Centre, School of Psychology, University of Exeter, Exeter, EX4 4QG, UK
| | - Rachel M Freathy
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Saskia P Hagenaars
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
| | - Jess Tyrrell
- Genetics of Complex Traits, The College of Medicine and Health, RD&E Hospital, University of Exeter, Exeter EX2 5DW, UK
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Pyne T, Ghosh P, Dhauria M, Ganguly K, Sengupta D, Nandagopal K, Sengupta M, Das M. Prioritization of human well-being spectrum related GWAS-SNVs using ENCODE-based web-tools predict interplay between PSMC3, ITIH4, and SERPINC1 genes in modulating well-being. J Psychiatr Res 2021; 145:92-101. [PMID: 34883412 DOI: 10.1016/j.jpsychires.2021.11.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 04/16/2021] [Accepted: 11/21/2021] [Indexed: 11/23/2022]
Abstract
Several traits related to positive and negative affect show a high genetic as well as phenotypic correlation with well-being in humans, and are therefore collectively termed as "Well-being spectrum". Genome-Wide Association studies (GWA studies) on "well-being measurement" have led to identification of several genomic variants (Single Nucleotide Variants - SNVs), but very little has been explained with respect to their functionality and mode of alteration of well-being. Utilizing a pool of 1258 GWA studies based SNVs on "well-being measurement", we prioritized the SNVs and tried to annotate well-being related functionality through several bioinformatic tools to predict whether a protein sequence variation affects protein function, as well as experimentally validated datasets available in ENCODE based web-tools namely rSNPBase, RegulomeDB, Haploreg, along with GTEx Portal and STRING based protein interaction networks. Prioritization yielded three key SNVs; rs3781627-A, rs13072536-T and 5877-C potentially regulating three genes, PSMC3, ITIH4 and SERPINC1, respectively. Interestingly, the genes showed well clustered protein-protein interaction (maximum combined confidence score >0.4) with other well-being candidate genes, namely TNF and CRP genes suggesting their important role in modulation of well-being. PSMC3 and ITIH4 genes are also involved in driving acute phase responses signifying a probable cross-talk between well-being and psychoneuroimmunological system. To best of our knowledge this study is the first of its kind where the well-being associated GWA studies-SNVs were prioritized and functionally annotated, majorly based on functional data available in public domain, which revealed PSMC3, ITIH4 and SERPINC1 genes as probable candidates in regulation of well-being spectrum.
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Affiliation(s)
- Tushar Pyne
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Poulomi Ghosh
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Mrinmay Dhauria
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Kausik Ganguly
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Debmalya Sengupta
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Krishnadas Nandagopal
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India
| | - Mainak Sengupta
- Department of Genetics, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, 700019, India.
| | - Madhusudan Das
- Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata, West Bengal, 700019, India.
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de Kluiver H, Jansen R, Milaneschi Y, Bot M, Giltay EJ, Schoevers R, Penninx BW. Metabolomic profiles discriminating anxiety from depression. Acta Psychiatr Scand 2021; 144:178-193. [PMID: 33914921 PMCID: PMC8361773 DOI: 10.1111/acps.13310] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 04/23/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Depression has been associated with metabolomic alterations. Depressive and anxiety disorders are often comorbid diagnoses and are suggested to share etiology. We investigated whether differential metabolomic alterations are present between anxiety and depressive disorders and which clinical characteristics of these disorders are related to metabolomic alterations. METHODS Data were from the Netherlands Study of Depression and Anxiety (NESDA), including individuals with current comorbid anxiety and depressive disorders (N = 531), only a current depression (N = 304), only a current anxiety disorder (N = 548), remitted depressive and/or anxiety disorders (N = 897), and healthy controls (N = 634). Forty metabolites from a proton nuclear magnetic resonance lipid-based metabolomics panel were analyzed. First, we examined differences in metabolites between disorder groups and healthy controls. Next, we assessed whether depression or anxiety clinical characteristics (severity and symptom duration) were associated with metabolites. RESULTS As compared to healthy controls, seven metabolomic alterations were found in the group with only depression, reflecting an inflammatory (glycoprotein acetyls; Cohen's d = 0.12, p = 0.002) and atherogenic-lipoprotein-related (e.g., apolipoprotein B: Cohen's d = 0.08, p = 0.03, and VLDL cholesterol: Cohen's d = 0.08, p = 0.04) profile. The comorbid group showed an attenuated but similar pattern of deviations. No metabolomic alterations were found in the group with only anxiety disorders. The majority of metabolites associated with depression diagnosis were also associated with depression severity; no associations were found with anxiety severity or disease duration. CONCLUSION While substantial clinical overlap exists between depressive and anxiety disorders, this study suggests that altered inflammatory and atherogenic-lipoprotein-related metabolomic profiles are uniquely associated with depression rather than anxiety disorders.
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Affiliation(s)
- Hilde de Kluiver
- Department of PsychiatryAmsterdam UMCVrije Universiteit AmsterdamDepartment of Amsterdam Public Health Research Institute and Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Rick Jansen
- Department of PsychiatryAmsterdam UMCVrije Universiteit AmsterdamDepartment of Amsterdam Public Health Research Institute and Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Yuri Milaneschi
- Department of PsychiatryAmsterdam UMCVrije Universiteit AmsterdamDepartment of Amsterdam Public Health Research Institute and Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Mariska Bot
- Department of PsychiatryAmsterdam UMCVrije Universiteit AmsterdamDepartment of Amsterdam Public Health Research Institute and Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Erik J. Giltay
- Department of PsychiatryLeiden University Medical CenterLeidenthe Netherlands
| | - Robert Schoevers
- Department of PsychiatryUniversity Medical Center GroningenUniversity of GroningenGroningenthe Netherlands,Research School of Behavioral and Cognitive NeurosciencesUniversity of GroningenGroningenthe Netherlands
| | - Brenda W.J.H. Penninx
- Department of PsychiatryAmsterdam UMCVrije Universiteit AmsterdamDepartment of Amsterdam Public Health Research Institute and Amsterdam NeuroscienceAmsterdamthe Netherlands
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26
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Lahti-Pulkkinen M, Räikkönen K, Bhattacharya S, Reynolds RM. Maternal body mass index in pregnancy and mental disorders in adult offspring: a record linkage study in Aberdeen, Scotland. Sci Rep 2021; 11:15132. [PMID: 34302021 PMCID: PMC8302653 DOI: 10.1038/s41598-021-94511-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 07/08/2021] [Indexed: 12/14/2022] Open
Abstract
Maternal obesity in pregnancy predicts offspring psychopathology risk in childhood but it remains unclear whether maternal obesity or underweight associate with adult offspring mental disorders. We examined longitudinally whether maternal body mass index (BMI) in pregnancy predicted mental disorders in her offspring and whether the associations differed by offspring birth year among 68,571 mother–child dyads of Aberdeen Maternity and Neonatal Databank, Scotland. The offspring were born 1950–1999. Maternal BMI was measured at a mean 15.7 gestational weeks and classified into underweight, normal weight, overweight, moderate obesity and severe obesity. Mental disorders were identified from nationwide registers carrying diagnoses of all hospitalizations and deaths in Scotland in 1996–2017. We found that maternal BMI in pregnancy was associated with offspring mental disorders in a time-dependent manner: In offspring born 1950–1974, maternal underweight predicted an increased hazard of mental disorders [Hazard Ratio (HR) = 1.74; 95% Confidence Interval (CI) = 1.01–3.00)]. In offspring born 1975–1999, maternal severe obesity predicted increased hazards of any mental (HR 1.60; 95% CI 1.08–2.38) substance use (HR 1.91; 95% CI 1.03–3.57) and schizophrenia spectrum (HR 2.80; 95% CI 1.40–5.63) disorders. Our findings of time-specific associations between maternal prenatal BMI and adult offspring mental disorders may carry important public health implications by underlining possible lifelong effects of maternal BMI on offspring psychopathology.
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Affiliation(s)
- Marius Lahti-Pulkkinen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland.
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland
| | | | - Rebecca M Reynolds
- Centre for Cardiovascular Science and Tommy's Centre for Fetal and Maternal Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
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27
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Giöstad A, Räntfors R, Nyman T, Nyman E. Enrollment in Treatment at a Specialized Pain Management Clinic at a Tertiary Referral Center after Surgery for Ulnar Nerve Compression: Patient Characteristics and Outcome. JOURNAL OF HAND SURGERY GLOBAL ONLINE 2021; 3:110-116. [PMID: 35415548 PMCID: PMC8991748 DOI: 10.1016/j.jhsg.2021.02.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 02/02/2021] [Indexed: 02/08/2023] Open
Abstract
Purpose To study patients who enroll in treatment at a specialized pain management clinic at a tertiary referral center following ulnar nerve decompression. Methods Data from medical charts and postoperative questionnaires were collected for all patients after surgery for ulnar nerve compression at the elbow from 2011 to 2014 (n = 173) at a tertiary referral center. Differences in characteristics between patients who enrolled in treatment at the pain management clinic (study group, n = 26) and the rest of the patients (reference group, n = 147) were analyzed. The study group was further evaluated using questionnaires from the Swedish Quality Registry for Pain Rehabilitation (SQRP) and regarding outcome of pain treatment. Results The study group was characterized by prior pain conditions, earlier contact with a pain management clinic, and high degrees of kinesiophobia, depression/anxiety, low quality of life, and low life satisfaction. These patients had significantly higher postoperative Disabilities of the Arm, Shoulder, and Hand (DASH) scores, were significantly younger, and had bilateral surgery significantly more often than the reference group. For patients with unilateral surgery, simple decompression was significantly more common in the reference group. The most common treatments at the clinic were antidepressants and anticonvulsants for neurogenic pain. In 5 of 26 patients, pain relief, or pain reduction was the documented reason for discharge. Conclusions Pain is a relevant outcome measure for ulnar nerve decompression among complicated cases at a referral center. Severe postoperative pain is connected to higher disability, reduced life satisfaction, and overall low health status. This study maps out characteristics of patients who postoperatively enroll in treatment at a specialized pain management clinic following ulnar nerve decompression. Further studies are needed to define predictive factors for such pain. Type of study/level of evidence Prognostic III.
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Affiliation(s)
- Alice Giöstad
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Ronja Räntfors
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Torbjörn Nyman
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.,Department of Medical and Health Sciences, Pain and Rehabilitation Center, Linköping University Hospital, Linköping, Sweden
| | - Erika Nyman
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.,Department of Hand Surgery, Plastic Surgery and Burns, Linköping University Hospital, Linköping, Sweden
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Pistis G, Milaneschi Y, Vandeleur CL, Lasserre AM, Penninx BW, Lamers F, Boomsma DI, Hottenga JJ, Marques-Vidal P, Vollenweider P, Waeber G, Aubry JM, Preisig M, Kutalik Z. Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts. Transl Psychiatry 2021; 11:96. [PMID: 33542229 PMCID: PMC7862438 DOI: 10.1038/s41398-021-01236-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 02/08/2023] Open
Abstract
Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.
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Affiliation(s)
- Giorgio Pistis
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Yuri Milaneschi
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Caroline L. Vandeleur
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Aurélie M. Lasserre
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Brenda W.J.H. Penninx
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Femke Lamers
- grid.420193.d0000 0004 0546 0540Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- grid.12380.380000 0004 1754 9227Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- grid.12380.380000 0004 1754 9227Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Pedro Marques-Vidal
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Peter Vollenweider
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Gérard Waeber
- grid.8515.90000 0001 0423 4662Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Michel Aubry
- grid.150338.c0000 0001 0721 9812Department of Psychiatry, University Hospital of Geneva, Geneva, Switzerland
| | - Martin Preisig
- grid.8515.90000 0001 0423 4662Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- grid.9851.50000 0001 2165 4204Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland
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de Kluiver H, Milaneschi Y, Jansen R, van Sprang ED, Giltay EJ, Hartman CA, Penninx BWJH. Associations between depressive symptom profiles and immunometabolic characteristics in individuals with depression and their siblings. World J Biol Psychiatry 2021; 22:128-138. [PMID: 32425087 DOI: 10.1080/15622975.2020.1761562] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
OBJECTIVES The present study examined associations between immunometabolic characteristics (IMCs) and depressive symptom profiles (DSPs) in probands with lifetime diagnoses of depression and/or anxiety disorders and their siblings. METHODS Data were from the Netherlands Study of Depression and Anxiety, comprising 256 probands with lifetime diagnoses of depression and/or anxiety and their 380 siblings. Measured IMCs included blood pressure, waist circumference, and levels of glucose, triglycerides, HDL cholesterol, CRP, TNF-α and IL-6. DSPs included mood, cognitive, somatic and atypical-like profiles. We cross-sectionally examined whether DSPs were associated with IMCs within probands and within siblings, and whether DSPs were associated with IMCs between probands and siblings. RESULTS Within probands and within siblings, higher BMI and waist circumference were associated with higher somatic and atypical-like profiles. Other IMCs (IL-6, glucose and HDL cholesterol) were significantly related to DSPs either within probands or within siblings. DSPs and IMCs were not associated between probands and siblings. CONCLUSIONS The results suggest that there is a familial component for each trait, but no common familial factors for the association between DSPs and IMCs. Alternative mechanisms, such as direct causal effects or non-shared environmental risk factors, may better fit these results.
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Affiliation(s)
- Hilde de Kluiver
- Department of Psychiatry, Amsterdam UMC, Department of Amsterdam Public Health research institute and Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC, Department of Amsterdam Public Health research institute and Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Department of Amsterdam Public Health research institute and Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eleonore D van Sprang
- Department of Psychiatry, Amsterdam UMC, Department of Amsterdam Public Health research institute and Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Erik J Giltay
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam UMC, Department of Amsterdam Public Health research institute and Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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30
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A Randomised Experiment Evaluating the Mindful Raisin Practice as a Method of Reducing Chocolate Consumption During and After a Mindless Activity. JOURNAL OF COGNITIVE ENHANCEMENT 2019. [DOI: 10.1007/s41465-019-00159-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
AbstractThe present study investigated the impact of the mindful raisin exercise on overeating during and after the experiment while controlling for wellbeing. One-hundred and twenty-eight participants were recruited and completed a questionnaire on wellbeing (i.e. depression, anxiety and stress) and state mindfulness. Participants were randomly allocated to either the mindful raisin exercise or a newspaper reading control condition. The State Mindfulness Scale was then completed again, and participants watched a neutral video while exposed to chocolate for 10 min. For those 10 min, results showed that the mindfulness condition translated into lower food consumption during the mindless activity when compared to the control condition. Post experiment, participants were asked to wait for 5 min, and any extra chocolate consumption during this time was recorded. Post-consumption was non-significantly different between the two groups, with those in the mindfulness condition consuming 1.3 g less than those in the control group. Controlling for wellbeing did not alter the impact of the mindfulness intervention on consumption. Implications for future work and practical applications for weight regulation are discussed.
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31
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Gomes AP, Soares ALG, Menezes AMB, Assunção MC, Wehrmeister FC, Howe LD, Gonçalves H. Adiposity, depression and anxiety: interrelationship and possible mediators. Rev Saude Publica 2019; 53:103. [PMID: 31800914 PMCID: PMC6863175 DOI: 10.11606/s1518-8787.2019053001119] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 03/13/2019] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES To explore the association between adiposity, major depressive disorder and generalized anxiety disorder, and to assess the role of inflammation, diet quality and physical activity in this association. METHODS We used data from 2,977 individuals from the 1993 Pelotas Cohort (Brazil) who attended the 18- and 22-year follow-ups. We assessed general obesity using body mass index, fat mass index, and abdominal obesity using waist circumference. Major Depressive Disorder and generalized anxiety disorder were assessed using the mini-international neuropsychiatric interview. C-reactive protein and interleukin-6 (IL-6) levels were used as a measure of inflammation; diet quality was estimated using the revised diet quality index, and physical activity was assessed by the International physical activity questionnaire (IPAQ, min/day). The association between adiposity and major depressive disorder and generalized anxiety disorder was assessed using logistic regression, and the natural indirect effect via the mediators was estimated using G-computation. RESULTS General obesity assessed by body mass index (OR: 2.3; 95% CI:1.13; 4.85), fat mass index (OR: 2.6; 95%CI: 1.37; 4.83), and abdominal obesity (OR: 2.5; 95%CI: 1.18; 5.39) were associated with higher odds of major depressive disorder, whereas major depressive disorder was only associated with obesity assessed by body mass index (OR=1.9; 95% CI: 1.09; 3.46). Obesity and generalized anxiety disorder were not associated. C-reactive protein, diet quality and physical activity did not mediate the effect of obesity on major depressive disorder, and C-reactive protein mediated about 25% of the effect of major depressive disorder on adiposity. CONCLUSIONS Depression, but not generalized anxiety disorder, is associated with adiposity in both directions, with a stronger evidence for the direction obesity-depression. Inflammation explains part of the effect of major depressive disorder on obesity but not the other way around. Further research should explore other mechanisms that could be involved in the association between obesity and depression.
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Affiliation(s)
- Ana Paula Gomes
- Universidade Federal de Pelotas. Programa de Pós-graduação em Epidemiologia. Pelotas, RS, Brasil
| | - Ana Luiza G Soares
- University of Bristol. Population Health Sciences. Bristol Medical School. Bristol, United Kingdom
| | - Ana M B Menezes
- Universidade Federal de Pelotas. Programa de Pós-graduação em Epidemiologia. Pelotas, RS, Brasil
| | - Maria Cecília Assunção
- Universidade Federal de Pelotas. Programa de Pós-graduação em Epidemiologia. Pelotas, RS, Brasil
| | - Fernando C Wehrmeister
- Universidade Federal de Pelotas. Programa de Pós-graduação em Epidemiologia. Pelotas, RS, Brasil
| | - Laura D Howe
- University of Bristol. Population Health Sciences. Bristol Medical School. Bristol, United Kingdom
| | - Helen Gonçalves
- Universidade Federal de Pelotas. Programa de Pós-graduação em Epidemiologia. Pelotas, RS, Brasil
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32
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Abdellaoui A, Sanchez-Roige S, Sealock J, Treur JL, Dennis J, Fontanillas P, Elson S, Nivard MG, Ip HF, van der Zee M, Baselmans BML, Hottenga JJ, Willemsen G, Mosing M, Lu Y, Pedersen NL, Denys D, Amin N, M van Duijn C, Szilagyi I, Tiemeier H, Neumann A, Verweij KJH, Cacioppo S, Cacioppo JT, Davis LK, Palmer AA, Boomsma DI. Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness. Hum Mol Genet 2019; 28:3853-3865. [PMID: 31518406 PMCID: PMC6935385 DOI: 10.1093/hmg/ddz219] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 07/24/2019] [Accepted: 08/21/2019] [Indexed: 12/31/2022] Open
Abstract
Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.
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Affiliation(s)
- Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | | | - Julia Sealock
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- School of Experimental Psychology, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Jessica Dennis
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | | | | | | | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Hill Fung Ip
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Matthijs van der Zee
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Bart M L Baselmans
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Miriam Mosing
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Translational Epidemiology, Faculty Science, Leiden University, Leiden, The Netherlands
| | - Ingrid Szilagyi
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Alexander Neumann
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Stephanie Cacioppo
- Center for Cognitive and Social Neuroscience, Department of Psychology, The University of Chicago, Chicago, Illinois, USA
| | - John T Cacioppo
- Center for Cognitive and Social Neuroscience, Department of Psychology, The University of Chicago, Chicago, Illinois, USA
| | - Lea K Davis
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
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33
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Marteene W, Winckel K, Hollingworth S, Kisely S, Gallagher E, Hahn M, Ebdrup BH, Firth J, Siskind D. Strategies to counter antipsychotic-associated weight gain in patients with schizophrenia. Expert Opin Drug Saf 2019; 18:1149-1160. [PMID: 31564170 DOI: 10.1080/14740338.2019.1674809] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Introduction: Patients living with schizophrenia have a marked risk of clinically significant weight gain and obesity compared to the general population. The risks have been highlighted following the introduction of second-generation antipsychotics. In turn, obesity is associated with a higher prevalence of cardiovascular disease, the most common cause of premature mortality in patients with schizophrenia.Areas covered: In this review, the authors outline possible mechanisms that induce obesity in patients with schizophrenia taking antipsychotics. The authors discuss the safety and effectiveness of three main approaches for attenuating antipsychotic-associated weight gain (AAWG), including lifestyle interventions, switching antipsychotics, and augmentation with other medications.Expert opinion: When selecting antipsychotics, effective treatment of psychotic symptoms should be highest priority but obesity and related metabolic comorbidities associated with antipsychotics should not be neglected. Further research into mechanisms of weight gain associated with antipsychotics will guide future treatments for AAWG and development of antipsychotics that produce minimal metabolic adverse effects. With current strategies only producing modest weight loss in already overweight and obese individuals, clinicians should transition to an approach where they aim to prevent weight gain when initiating antipsychotic treatment.
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Affiliation(s)
- Wade Marteene
- University of Queensland School of Pharmacy, Brisbane, Australia
| | - Karl Winckel
- University of Queensland School of Pharmacy, Brisbane, Australia.,Department of Pharmacy, Princess Alexandra Hospital, Brisbane, Australia
| | - Sam Hollingworth
- University of Queensland School of Pharmacy, Brisbane, Australia
| | - Steve Kisely
- Metro South Addiction and Mental Health Service, Brisbane, Australia.,School of Medicine, University of Queensland, Brisbane, Australia
| | - Erin Gallagher
- Metro South Addiction and Mental Health Service, Brisbane, Australia.,School of Medicine, University of Queensland, Brisbane, Australia
| | - Margaret Hahn
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Centre for Addiction and Mental Health, Toronto, Canada
| | - Bjørn H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Glostrup, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Joseph Firth
- NICM Health Research Institute, Western Sydney University, Westmead, Australia.,Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Dan Siskind
- Metro South Addiction and Mental Health Service, Brisbane, Australia.,School of Medicine, University of Queensland, Brisbane, Australia
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34
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de Kluiver H, Jansen R, Milaneschi Y, Penninx BWJH. Involvement of inflammatory gene expression pathways in depressed patients with hyperphagia. Transl Psychiatry 2019; 9:193. [PMID: 31431611 PMCID: PMC6702221 DOI: 10.1038/s41398-019-0528-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 04/25/2019] [Accepted: 06/20/2019] [Indexed: 12/21/2022] Open
Abstract
The pathophysiology of major depressive disorder (MDD) is highly heterogeneous. Previous evidence at the DNA level as well as on the serum protein level suggests that the role of inflammation in MDD pathology is stronger in patients with hyperphagia during an active episode. Which inflammatory pathways differ in MDD patients with hyperphagia inflammatory pathways in terms of gene expression is unknown. We analyzed whole-blood gene expression profiles of 881 current MDD cases and 331 controls from the Netherlands Study of Depression and Anxiety (NESDA). The MDD patients were stratified according to patients with hyperphagia (characterized by increased appetite and/or weight, N = 246) or hypophagia (characterized by decreased appetite and/or weight, N = 342). Using results of differential gene expression analysis between controls and the MDD subgroups, enrichment of curated inflammatory pathways was estimated. The majority of the pathways were significantly (FDR < 0.1) enriched in the expression profiles of MDD cases with hyperphagia, including top pathways related to factors responsible for the onset of inflammatory response ('caspase', 'GATA3', 'NFAT', and 'inflammasomes' pathways). Only two pathways ('adaptive immune system' and 'IL-8- and CXCR2-mediated signaling') were enriched in the MDD with hypophagia subgroup, these were also enriched in the total current MDD group and the group with hyperphagia. This confirms the importance of inflammation in MDD pathology of patients with hyperphagia, and suggests that distinguishing more uniform MDD phenotypes can help in finding their pathophysiological basis.
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Affiliation(s)
- Hilde de Kluiver
- Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute and Amsterdam Neuroscience, Oldenaller 1, 1081 HJ, Amsterdam, the Netherlands.
| | - Rick Jansen
- grid.484519.5Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Neuroscience, Oldenaller 1, 1081 HJ Amsterdam, the Netherlands
| | - Yuri Milaneschi
- 0000 0004 0435 165Xgrid.16872.3aAmsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute and Amsterdam Neuroscience, Oldenaller 1, 1081 HJ Amsterdam, the Netherlands
| | - Brenda W. J. H. Penninx
- 0000 0004 0435 165Xgrid.16872.3aAmsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute and Amsterdam Neuroscience, Oldenaller 1, 1081 HJ Amsterdam, the Netherlands
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35
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Investigating the association between body fat and depression via Mendelian randomization. Transl Psychiatry 2019; 9:184. [PMID: 31383844 PMCID: PMC6683191 DOI: 10.1038/s41398-019-0516-4] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 05/14/2019] [Accepted: 06/20/2019] [Indexed: 12/20/2022] Open
Abstract
Obesity and depression are major public health concerns that are both associated with substantial morbidity and mortality. There is a considerable body of literature linking obesity to the development of depression. Recent studies using Mendelian randomization indicate that this relationship is causal. Most studies of the obesity-depression association have used body mass index as a measure of obesity. Body mass index is defined as weight (measured in kilograms) divided by the square of height (meters) and therefore does not distinguish between the contributions of fat and nonfat to body weight. To better understand the obesity-depression association, we conduct a Mendelian randomization study of the relationship between fat mass, nonfat mass, height, and depression, using genome-wide association study results from the UK Biobank (n = 332,000) and the Psychiatric Genomics Consortium (n = 480,000). Our findings suggest that both fat mass and height (short stature) are causal risk factors for depression, while nonfat mass is not. These results represent important new knowledge on the role of anthropometric measures in the etiology of depression. They also suggest that reducing fat mass will decrease the risk of depression, which lends further support to public health measures aimed at reducing the obesity epidemic.
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36
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Vainik U, Dagher A, Realo A, Colodro-Conde L, Mortensen EL, Jang K, Juko A, Kandler C, Sørensen TIA, Mõttus R. Personality-obesity associations are driven by narrow traits: A meta-analysis. Obes Rev 2019; 20:1121-1131. [PMID: 30985072 DOI: 10.1111/obr.12856] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 02/22/2019] [Accepted: 03/03/2019] [Indexed: 01/12/2023]
Abstract
Obesity has inconsistent associations with broad personality domains, possibly because the links pertain to only some facets of these domains. Collating published and unpublished studies (N = 14 848), we meta-analysed the associations between body mass index (BMI) and Five-Factor Model personality domains as well as 30 Five-Factor Model personality facets. At the domain level, BMI had a positive association with Neuroticism and a negative association with Conscientiousness domains. At the facet level, we found associations between BMI and 15 facets from all five personality domains, with only some Neuroticism and Conscientiousness facets among them. Certain personality-BMI associations were moderated by sample properties, such as proportions of women or participants with obesity; these moderation effects were replicated in the individual-level analysis. Finally, facet-based personality "risk" scores accounted for 2.3% of variance in BMI in a separate sample of individuals (N = 3569), 409% more than domain-based scores. Taken together, personality-BMI associations are facet specific, and delineating them may help to explain obesity-related behaviours and inform intervention designs. Preprint and data are available at https://psyarxiv.com/z35vn/.
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Affiliation(s)
- Uku Vainik
- Montreal Neurological Institute, McGill University, Montreal, Canada.,Institute of Psychology, University of Tartu, Tartu, Estonia
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Anu Realo
- Institute of Psychology, University of Tartu, Tartu, Estonia.,Department of Psychology, University of Warwick, Coventry, UK
| | | | | | - Kerry Jang
- Division of Behavioural Sciences, Department of Psychiatry, The University of British Columbia, Vancouver, Canada
| | - Ando Juko
- Faculty of Letters, Keio University, Tokyo, Japan
| | | | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - René Mõttus
- Institute of Psychology, University of Tartu, Tartu, Estonia.,Department of Psychology, University of Edinburgh, Edinburgh, UK
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37
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Does perceived overweight increase risk of depressive symptoms and suicidality beyond objective weight status? A systematic review and meta-analysis. Clin Psychol Rev 2019; 73:101753. [PMID: 31715442 DOI: 10.1016/j.cpr.2019.101753] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 05/22/2019] [Accepted: 07/05/2019] [Indexed: 01/24/2023]
Abstract
Obesity is associated with a significant disease burden, but whether recognising as opposed to failing to recognise personal overweight is beneficial or detrimental to mental health is unclear. Here we examine the associations between perceived overweight and depressive symptoms and suicidality. A systematic search of three electronic databases yielded 10,398 unique records, from which 32 studies (110 observations) were eligible for inclusion. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated for each outcome using random effects meta-analyses and potential publication bias was examined. Perceived overweight was associated with an increased risk of depressive symptoms (OR: 1.42, CI: 1.31, 1.54 p <.0001, N >128,585) and suicidality (OR: 1.41, CI: 1.28, 1.56, p <.0001, N = 133,576) in both cross-sectional and longitudinal studies. The association between perceived overweight and poorer mental health was observed irrespective of study origin, participant age (children vs. adults), gender, and whether or not a person was objectively overweight. The pooled statistical relationship between objective weight status and poorer mental health was attenuated to non-significance when perceived overweight was accounted for, suggesting that the detrimental effect of overweight on mental health is largely dependent on whether or not a person identifies as overweight.
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38
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Taylor AE, Richmond RC, Palviainen T, Loukola A, Wootton RE, Kaprio J, Relton CL, Davey Smith G, Munafò MR. The effect of body mass index on smoking behaviour and nicotine metabolism: a Mendelian randomization study. Hum Mol Genet 2019; 28:1322-1330. [PMID: 30561638 PMCID: PMC6452214 DOI: 10.1093/hmg/ddy434] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 11/21/2018] [Accepted: 11/30/2018] [Indexed: 12/21/2022] Open
Abstract
Given clear evidence that smoking lowers weight, it is possible that individuals with higher body mass index (BMI) smoke in order to lose or maintain their weight. We performed Mendelian randomization (MR) analyses of the effects of BMI on smoking behaviour in UK Biobank and the Tobacco and Genetics Consortium genome-wide association study (GWAS), on cotinine levels and nicotine metabolite ratio (NMR) in published GWAS and on DNA methylation in the Avon Longitudinal Study of Parents and Children. Our results indicate that higher BMI causally influences lifetime smoking, smoking initiation, smoking heaviness and also DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) locus, but we do not see evidence for an effect on smoking cessation. While there is no strong evidence that BMI causally influences cotinine levels, suggestive evidence for a negative causal influence on NMR may explain this. There is a causal effect of BMI on smoking, but the relationship is likely to be complex due to opposing effects on behaviour and metabolism.
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Affiliation(s)
- Amy E Taylor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute for Life Science, University of Helsinki, Helsinki, Finland
| | - Anu Loukola
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute for Life Science, University of Helsinki, Helsinki, Finland
| | - Robyn E Wootton
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute for Life Science, University of Helsinki, Helsinki, Finland
- Department of Public Health, Medical Faculty, University of Helsinki, Helsinki, Finland
| | - Caroline L Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK
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39
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Glaus J, Cui L, Hommer R, Merikangas KR. Association between mood disorders and BMI/overweight using a family study approach. J Affect Disord 2019; 248:131-138. [PMID: 30731280 DOI: 10.1016/j.jad.2019.01.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 12/19/2018] [Accepted: 01/12/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND We previously demonstrated the specificity of familial transmission of the atypical subtype of depression, primarily characterized by overeating and oversleeping. However, the specific components of this subtype that are familial have not been established. The aim of this paper is to examine whether the familial specificity of atypical depression can be attributed to the association between Body Mass Index (BMI) and overweight/obesity with mood disorders. METHODS The sample included 293 probands recruited from the community and their 544 adult first-degree relatives. Diagnostic assignment was based on a direct semi-structured interview. Mixed effect models were employed to test the familial aggregation and the familial cross-aggregation of mood disorders and BMI/overweight. RESULTS There were significant within-individual associations between overweight and the atypical subtype of depression (p-value = 0.003). There was also an association for BMI/overweight between probands and relatives (β = 0.23, p-value < 0.001; odds ratio [OR] = 1.57, 95% confidence interval [CI] = 1.02-2.43, respectively). Atypical depression in probands was significantly associated with BMI and overweight in relatives (β = 0.001, p-value = 0.040; OR = 2.79, 95%CI = 1.20-6.49, respectively). LIMITATIONS The cross-sectional design impedes our ability to evaluate the direction of these associations. Other potential risk factors, such as diabetes, physical activity and unhealthy diet were not considered. CONCLUSIONS These findings imply that overweight may be either a precursor or consequence of atypical depression rather than a manifestation of a common diathesis underlying depression in families. Clinicians should pay particular attention to this subtype that could be at increased risk for the development of cardiovascular risk factors and diseases.
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Affiliation(s)
- Jennifer Glaus
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, 35 Convent Drive, MSC 3720, Bldg 35A, Room 2E422A, Bethesda, MD, USA.
| | - Lihong Cui
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, 35 Convent Drive, MSC 3720, Bldg 35A, Room 2E422A, Bethesda, MD, USA
| | - Rebecca Hommer
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, 35 Convent Drive, MSC 3720, Bldg 35A, Room 2E422A, Bethesda, MD, USA
| | - Kathleen R Merikangas
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, 35 Convent Drive, MSC 3720, Bldg 35A, Room 2E422A, Bethesda, MD, USA
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Millard LAC, Davies NM, Tilling K, Gaunt TR, Davey Smith G. Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization. PLoS Genet 2019; 15:e1007951. [PMID: 30707692 PMCID: PMC6373977 DOI: 10.1371/journal.pgen.1007951] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 02/13/2019] [Accepted: 01/09/2019] [Indexed: 12/30/2022] Open
Abstract
Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We performed a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n = 334 968), using the PHESANT open-source phenome scan tool. A subset of identified associations were followed up with a formal two-stage instrumental variable analysis in UK Biobank, to estimate the causal effect of BMI on these phenotypes. Of the 22 922 tests performed, our MR-pheWAS identified 587 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate. These included many previously identified causal effects, for instance, an adverse effect of higher BMI on risk of diabetes and hypertension. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS in circa 115,000 UK Biobank participants and replicated in a different subset of circa 223,000 UK Biobank participants. Our comprehensive MR-pheWAS identified potential causal effects of BMI on a large and diverse set of phenotypes. This included both previously identified causal effects, and novel effects such as a protective effect of higher BMI on feelings of nervousness.
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Affiliation(s)
- Louise A. C. Millard
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
- Intelligent Systems Laboratory, Department of Computer Science, University of Bristol, Bristol, United Kingdom
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
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Wootton RE, Lawn RB, Millard LAC, Davies NM, Taylor AE, Munafò MR, Timpson NJ, Davis OSP, Davey Smith G, Haworth CMA. Evaluation of the causal effects between subjective wellbeing and cardiometabolic health: mendelian randomisation study. BMJ 2018; 362:k3788. [PMID: 30254091 PMCID: PMC6155050 DOI: 10.1136/bmj.k3788] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/31/2018] [Indexed: 01/09/2023]
Abstract
OBJECTIVES To investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and cardiometabolic health is causal. DESIGN Two sample, bidirectional mendelian randomisation study. SETTING Genetic data taken from various cohorts comprised of the general population (mostly individuals of European ancestry, plus a small proportion of other ancestries); follow-up analysis included individuals from the United Kingdom. PARTICIPANTS Summary data were used from previous genome wide association studies (number of participants ranging from 83 198 to 339 224), which investigated traits related to cardiovascular or metabolic health, had the largest sample sizes, and consisted of the most similar populations while minimising sample overlap. A follow-up analysis included 337 112 individuals from the UK Biobank (54% female (n=181 363), mean age 56.87 years (standard deviation 8.00) at recruitment). MAIN OUTCOME MEASURES Subjective wellbeing and 11 measures of cardiometabolic health (coronary artery disease; myocardial infarction; total, high density lipoprotein, and low density lipoprotein cholesterol; diastolic and systolic blood pressure; body fat; waist to hip ratio; waist circumference; and body mass index). RESULTS Evidence of a causal effect of body mass index on subjective wellbeing was seen; each 1 kg/m2 increase in body mass index caused a -0.045 (95% confidence interval -0.084 to -0.006, P=0.02) standard deviation reduction in subjective wellbeing. Follow-up analysis of this association in an independent sample from the UK Biobank provided strong evidence of an effect of body mass index on satisfaction with health (β=-0.035 unit decrease in health satisfaction (95% confidence interval -0.043 to -0.027) per standard deviation increase in body mass index, P<0.001). No clear evidence of a causal effect was seen between subjective wellbeing and the other cardiometabolic health measures, in either direction. CONCLUSIONS These results suggest that a higher body mass index is associated with a lower subjective wellbeing. A follow-up analysis confirmed this finding, suggesting that the effect in middle aged people could be driven by satisfaction with health. Body mass index is a modifiable determinant, and therefore, this study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher body mass index on subjective wellbeing.
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Affiliation(s)
- Robyn E Wootton
- School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Rebecca B Lawn
- School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Louise A C Millard
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Intelligent Systems Laboratory, Department of Computer Science, University of Bristol, Bristol, UK
| | - Neil M Davies
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Amy E Taylor
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Marcus R Munafò
- School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, University of Bristol, Bristol, UK
| | - Nicholas J Timpson
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Avon Longitudinal Study of Parents and Children, Bristol, UK
| | - Oliver S P Davis
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - George Davey Smith
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Claire M A Haworth
- School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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