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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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2
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Saadat SH, Javanbakht M, Shahyad S. Brain-derived neurotrophic factor and C-reactive protein (CRP) biomarkers in suicide attempter and non-attempter major depression disorder (MDD) patients. Ann Gen Psychiatry 2024; 23:27. [PMID: 39039500 PMCID: PMC11264361 DOI: 10.1186/s12991-024-00511-3] [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: 04/07/2024] [Accepted: 07/15/2024] [Indexed: 07/24/2024] Open
Abstract
BACKGROUND In the available literature, levels of BDNF and CRP have been reported to correlate with suicide in depressive patients but there are inconsistencies in the results. We aimed to evaluate and compare BDNF and CRP concentrations in MDD patients with(MDD + SA) and without suicide attempts (MDD-SA) and healthy controls. METHODS 30 (MDD + SA) patients, 30 (MDD-SA) patients, and 26 healthy controls were enrolled in the study. Age, sex, and BMI of patients were recorded. Blood sample was obtained for measurement of BDNF and CRP. Smoking and drug history, family history of suicide, and history of self-harm were also documented. Data were analyzed with SPSS version 22 and R version 4.1.1. RESULTS 86 patients in three groups were evaluated (mean age: 28.45 ± 9.27 years, 56.71% female). Baseline and demographic parameters except for self-harm (40%, 3.3%, and 0% for MDD + SA, MDD-SA, and healthy controls, respectively, p = 0.001) did not differ between groups. CRP level was not significantly different between groups. BDNF showed a significant difference between groups (17.35, 16.45, and 19.43 for three groups, respectively, p < 0.001). An increase in BDNF decreased the odds of both depression and suicide. Roc curve showed excellent power for BDNF in discriminating MDD groups With healthy group.Roc can notdicrimiate MDD + SA and MDD-SA. CONCLUSION In our study, the concentration of BDNF differed significantly between depressed patients with/without suicide attempts and healthy controls which shows the association of BDNF with depression development and not suicide attempts. We could not find any association between CRP level and suicide attempt but still larger cohorts are needed for a definite conclusion.
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Affiliation(s)
- Seyed Hassan Saadat
- Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mohammad Javanbakht
- Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Shima Shahyad
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
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3
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Campbell AC, Calais-Ferreira L, Hahn E, Spinath FM, Hopper JL, Young JT. Familial confounding of internalising symptoms and obesity in adolescents and young adults; a co-twin analysis. Int J Obes (Lond) 2024; 48:876-883. [PMID: 38360935 PMCID: PMC11129947 DOI: 10.1038/s41366-024-01491-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 01/14/2024] [Accepted: 02/01/2024] [Indexed: 02/17/2024]
Abstract
BACKGROUND Obesity and internalising disorders, including depression and anxiety, often co-occur. There is evidence that familial confounding contributes to the co-occurrence of internalising disorders and obesity in adults. However, its impact on this association among young people is unclear. Our study investigated the extent to which familial factors confound the association between internalising disorders and obesity in adolescents and young adults. SUBJECTS/METHODS We used a matched co-twin design to investigate the impact of confounding by familial factors on associations between internalising symptoms and obesity in a sample of 4018 twins aged 16 to 27 years. RESULTS High levels of internalising symptoms compared to low levels increased the odds of obesity for the whole cohort (adjusted odds ratio [AOR] = 3.1, 95% confidence interval [CI]: 1.5, 6.8), and in females (AOR = 4.1, 95% CI 1.5, 11.1), but not in males (AOR = 2.8 95% CI 0.8, 10.0). We found evidence that internalising symptoms were associated with an increased between-pair odds of obesity (AOR 6.2, 95% CI 1.7, 22.8), using the paired analysis but not using a within-pair association, which controls for familial confounding. Sex-stratified analyses indicated high internalising symptoms were associated with increased between-pair odds of obesity for females (AOR 12.9, 95% CI 2.2, 76.8), but this attenuated to the null using within-pair analysis. We found no evidence of between or within-pair associations for males and weak evidence that sex modified the association between internalising symptoms and obesity (likelihood ratio test p = 0.051). CONCLUSIONS Some familial factors shared by twins confound the association between internalising symptoms and obesity in adolescent and young adult females. Internalising symptoms and obesity were not associated for adolescent and young adult males. Therefore, prevention and treatment efforts should especially address familial shared determinants of obesity, particularly targeted at female adolescents and young adults with internalising symptoms and those with a family history of these disorders.
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Affiliation(s)
- Alexander Charles Campbell
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, VIC, Australia.
- Justice Health Group, School of Population Health, Curtin University, Perth, WA, Australia.
| | - Lucas Calais-Ferreira
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Justice Health Group, School of Population Health, Curtin University, Perth, WA, Australia
- Centre for Mental Health and Community Wellbeing, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Elisabeth Hahn
- Department of Psychology, Saarland University, Saarbruecken, Germany
| | - Frank M Spinath
- Department of Psychology, Saarland University, Saarbruecken, Germany
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Jesse T Young
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
- School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
- National Drug Research Institute, Curtin University, Perth, WA, Australia
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, OC, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, OC, Canada
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4
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Ganggaya KS, Vanoh D, Ishak WRW. Prevalence of sarcopenia and depressive symptoms among older adults: a scoping review. Psychogeriatrics 2024; 24:473-495. [PMID: 38105398 DOI: 10.1111/psyg.13060] [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: 05/25/2023] [Revised: 09/19/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023]
Abstract
Sarcopenia causes a loss of skeletal muscle mass and decreases muscle strength and function. Depressive symptoms are a common cause of distress among geriatrics, significantly affecting the quality of life of older adults. Recently, studies have shown that a correlation exists between sarcopenia and depression. To determine the prevalence of sarcopenia and depressive symptoms and identify the factors associated with sarcopenia, we systematically searched the SCOPUS, Science Direct, and PubMed databases for papers on sarcopenia and depressive symptoms published from 2012 to 2022. We reviewed the literature on sarcopenia, depressive symptom prevalence, the prevalence of subjects with both sarcopenia and depressive symptoms, and the factors associated with sarcopenia. Only cross-sectional studies were included. Nineteen articles met the inclusion criteria for review, with overall sarcopenia prevalence ranging from 3.9% to 41.7%. The prevalence of depressive symptoms was reported in seven studies, ranging from 8.09% to 40%. The most commonly used tools to diagnose sarcopenia and depressive symptoms were the European Working Group on Sarcopenia in Older People consensus and the Geriatric Depression Scale, respectively. Being aged, malnourished, obese, having comorbidities (hypertension and diabetes), having impaired cognitive function, and having polypharmacy were found to be the factors associated with sarcopenia. Sarcopenia and depressive symptoms have been found to cause adverse health outcomes among older people. Appropriate nutritional assessments and interventions should be taken to manage these two geriatric conditions. Further studies should be planned, considering multidomain intervention strategies to improve sarcopenia and older people's mental health.
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Affiliation(s)
- Keerthana Sree Ganggaya
- Nutrition Program, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Divya Vanoh
- Dietetics Program, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Wan Rosli Wan Ishak
- Nutrition Program, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Malaysia
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5
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Lv X, Cai J, Li X, Wang X, Ma H, Heianza Y, Qi L, Zhou T. Body composition, lifestyle, and depression: a prospective study in the UK biobank. BMC Public Health 2024; 24:393. [PMID: 38321471 PMCID: PMC10848418 DOI: 10.1186/s12889-024-17891-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/25/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Obesity has been related to depression and adhering healthy lifestyle was beneficial to lower the risk of depression; however, little is known about the relationship between body composition and fat distribution with depression risk and the influence of body composition and fat distribution on the association of lifestyle and depression. Therefore, we aimed to investigate whether body composition and fat distribution were associated with the adverse events of depression and the relationship between lifestyle and depression. METHODS We included 330,131 participants without depression at baseline in the UK Biobank (mean age, 56.9 years; 53.83% females). The assessment of depression was sourced from health outcomes across self-report, primary care, hospital inpatient data, and death data. Body composition was determined by bioelectrical impedance. Seven lifestyles (no current smoking, moderate alcohol consumption, regular physical activity, healthy diet, less sedentary behavior, healthy sleep pattern, and appropriate social connection) were used to generate a lifestyle score. RESULTS During a median of 11.7 years of follow-up, 7576 incident depression occurred. All the body composition measures were positively associated with depression risk, with the Hazard ratios (HR) for the uppermost tertile (T3) versus the lowest tertile (T1) ranging from 1.26 (95% CI: 1.15-1.39) for trunk fat-free mass (TFFM) to 1.78 (1.62-1.97) for leg fat percentage (LFP). In addition, we found significant interactions between fat mass-related indices, especially leg fat mass (LFM) (p = 1.65 × 10-9), and lifestyle score on the risk of depression, for which the beneficial associations of a healthy lifestyle with the risk of depression were more evident among participants with low body fat measurement. CONCLUSIONS High levels of body composition measures were associated with an increased depression risk. Adverse body composition measures may weaken the link between a healthy lifestyle and a reduced risk of depression.
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Affiliation(s)
- Xingyu Lv
- Department of Epidemiology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, No.66 Gongchang Road, Guangming District, Shenzhen, People's Republic of China, 518107
| | - Jie Cai
- Department of Epidemiology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, No.66 Gongchang Road, Guangming District, Shenzhen, People's Republic of China, 518107
| | - Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA
| | - Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA
| | - Hao Ma
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Tao Zhou
- Department of Epidemiology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, No.66 Gongchang Road, Guangming District, Shenzhen, People's Republic of China, 518107.
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1724, New Orleans, LA, 70112, USA.
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6
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Hu G, Qin H, Su B, Bao Y, Liang Z, Wang Y. Composite healthy lifestyle, socioeconomic deprivation, and mental well-being during the COVID-19 pandemic: a prospective analysis. Mol Psychiatry 2024; 29:439-448. [PMID: 38114630 PMCID: PMC11116094 DOI: 10.1038/s41380-023-02338-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 12/21/2023]
Abstract
The adverse psychological and social impacts of COVID-19 pandemic are well characterized, but the role of composite, modifiable lifestyle factors that may interact to mitigate these impacts is not. The effect of socioeconomic deprivation on these lifestyle risks also remains unclear. Based on a nationally representative, longitudinal cohort, we assessed the association between a combination of pre-pandemic lifestyle factors and mental health conditions during pandemic, and the contribution of deprivation to it. Composite lifestyle factors included BMI, smoking status, alcohol consumption, physical activity, sedentary time, sleep duration, and fruit and vegetable intake, with lifestyle scores and lifestyle categories calculated for each participant. Symptoms of depression and anxiety, and personal well-being were assessed by validated scales during the pandemic. Socioeconomic deprivation was characterized by both individual-level (income, wealth, and education) and group-level factors (Index of Multiple Deprivation). Of the 5049 eligible participants (mean [SD] age, 68.1 [10.9] years; 57.2% were female) included in the study, 41.6% followed a favorable lifestyle, 48.9% followed an intermediate lifestyle, and 9.5% followed an unfavorable lifestyle. Compared with favorable lifestyle category, participants in the intermediate and unfavorable lifestyle category were at increased risk of mental health conditions, with the hazard ratio (HR) for trend per increment change towards unfavorable category of 1.17 (95% CI 1.09-1.26) for depression, 1.23 (1.07-1.42) for anxiety, and 1.39 (1.20-1.61) for low well-being. A significant trend of lower risk for mental health conditions with increasing number of healthy lifestyle factors was observed (P < 0.001 for trend). There were no significant interactions between lifestyle factors and socioeconomic deprivation for any of the outcomes, with similar HRs for trend per one increment change in lifestyle category observed in each deprivation group. Compared with those in the least deprived group with favorable lifestyle, participants in the most deprived group adherent to unfavorable lifestyle had the highest risk of mental health outcomes. These results suggest that adherence to a broad combination of healthy lifestyle factors was associated with a significantly reduced risk of mental health conditions during the COVID-19 pandemic. Lifestyle factors, in conjunction with socioeconomic deprivation, independently contribute to the risk of mental health issues. Although further research is needed to assess causality, the current findings support public health strategies and individual-level interventions that provide enhanced support in areas of deprivation and target multiple lifestyle factors to reduce health inequalities and promote mental well-being during the ongoing COVID-19 pandemic.
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Affiliation(s)
- Gang Hu
- School of Health Management (Health Management Center), Xinjiang Medical University, Urumqi, China
| | - Huibo Qin
- Quality Control Department of Liaocheng People's Hospital, Jinan, Shandong, China
| | - Binbin Su
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China
| | - Yanping Bao
- National Institute on Drug Dependence, Peking University, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - Zhengting Liang
- School of Traditional Chinese Medicine, Xinjiang Medical University, Urumqi, China.
| | - Yunhe Wang
- Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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7
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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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8
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Rebello CJ. Effect of Muscle Mass and Strength on Depression: Does Mendelian Randomization Address Causality? Am J Geriatr Psychiatry 2024; 32:42-44. [PMID: 37689532 PMCID: PMC10872736 DOI: 10.1016/j.jagp.2023.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 09/11/2023]
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9
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Ma WR, Zhang LL, Ma JY, Yu F, Hou YQ, Feng XR, Yang L. Mendelian randomization studies of depression: evidence, opportunities, and challenges. Ann Gen Psychiatry 2023; 22:47. [PMID: 37996851 PMCID: PMC10666459 DOI: 10.1186/s12991-023-00479-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) poses a significant social and economic burden worldwide. Identifying exposures, risk factors, and biological mechanisms that are causally connected to MDD can help build a scientific basis for disease prevention and development of novel therapeutic approaches. METHODS In this systematic review, we assessed the evidence for causal relationships between putative causal risk factors and MDD from Mendelian randomization (MR) studies, following PRISMA. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions. RESULTS We included methodological details and results from 52 articles. A causal link between lifestyle, metabolic, inflammatory biomarkers, particular pathological states and MDD is supported by MR investigations, although results for each category varied substantially. CONCLUSIONS While this review shows how MR can offer useful information for examining prospective treatment targets and better understanding the pathophysiology of MDD, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.
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Affiliation(s)
- Wang-Ran Ma
- Xian Hospital of Traditional Chinese Medicine, Xi'an, 710021, China
- Shanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
| | - Lei-Lei Zhang
- Xian Hospital of Traditional Chinese Medicine, Xi'an, 710021, China
| | - Jing-Ying Ma
- Shanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
| | - Fang Yu
- Shanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
| | - Ya-Qing Hou
- Shanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
| | - Xiang-Rui Feng
- Shanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
| | - Lin Yang
- Xian Hospital of Traditional Chinese Medicine, Xi'an, 710021, China.
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10
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Yu L, Chen X, Bai X, Fang J, Sui M. Microbiota Alters and Its Correlation with Molecular Regulation Underlying Depression in PCOS Patients. Mol Neurobiol 2023:10.1007/s12035-023-03744-7. [PMID: 37995075 DOI: 10.1007/s12035-023-03744-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/27/2023] [Indexed: 11/24/2023]
Abstract
Depression is one of the complications in patients with polycystic ovary syndrome (PCOS) that leads to considerable mental health. Accumulating evidence suggests that human gut microbiomes are associated with the progression of PCOS and depression. However, whether microbiota influences depression development in PCOS patients is still uncharacterized. In this study, we employed metagenomic sequencing and transcriptome sequencing (RNA-seq) to profile the composition of the fecal microbiota and gene expression of peripheral blood mononuclear cells in depressed women with PCOS (PCOS-DP, n = 27) in comparison to mentally healthy women with PCOS (PCOS, n = 18) and compared with healthy control (HC, n = 27) and patients with major depressive disorder (MDD, n = 29). Gut microbiota assessment revealed distinct patterns in the relative abundance in the PCOS-DP compared to HC, MDD, and PCOS groups. Several gut microbes exhibited uniquely and significantly higher abundance in the PCOS-DP compared to PCOS patients, inducing EC Ruminococcus torques, Coprococcus comes, Megasphaera elsdenii, Acidaminococcus intestini, and Barnesiella viscericola. Bacteroides eggerthii was a potential gut microbial biomarker for the PCOS-DP. RNA-seq profiling identified that 35 and 37 genes were significantly elevated and downregulated in the PCOS-DP, respectively. The enhanced differential expressed genes (DEGs) in the PCOS-DP were enriched in pathways involved in signal transduction and endocrine and metabolic diseases, whereas several lipid metabolism pathways were downregulated. Intriguingly, genes correlated with the gut microbiota were found to be significantly enriched in pathways of neurodegenerative diseases and the immune system, suggesting that changes in the microbiota may have a systemic impact on the expression of neurodegenerative diseases and immune genes. Gut microbe-related DEGs of CREB3L3 and CCDC173 were possible molecular biomarkers and therapeutic targets of women with PCOS-DP. Our multi-omics data indicate shifts in the gut microbiome and host gene regulation in PCOS patients with depression, which is of possible etiological and diagnostic importance.
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Affiliation(s)
- Liying Yu
- Central Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, China.
| | - Xiaoyu Chen
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, China
| | - Xuefeng Bai
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, China
| | - Jingping Fang
- College of Life Science, Fujian Normal University, Fuzhou, 350117, China
| | - Ming Sui
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, China.
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11
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Neto G, Bobak M, Gonzalez-Rivas JP, Klanova J. The Influence of Adiposity Levels on the Relation between Perfluoroalkyl Substances and High Depressive Symptom Scores in Czech Adults. TOXICS 2023; 11:946. [PMID: 37999598 PMCID: PMC10674478 DOI: 10.3390/toxics11110946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/08/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023]
Abstract
The extensive use and bioaccumulation of Perfluoroalkyl Substances (PFAS) over time raise concerns about their impact on health, including mental issues such as depression. This study aims to evaluate the association between PFAS and depression. In addition, considering the importance of PFAS as an endocrine disruptor and in adipogenesis, the analyses will also be stratified by body fat status. A cross-sectional study with 479 subjects (56.4% women, 25-89 years) was conducted. Four PFAS were measured: perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluorooctane sulfonate (PFOS). The Poisson regression model was applied using robust error variances. The fully adjusted model included age, sex, educational level, income, smoking, physical activity, body fat percentage, and the questionnaire to assess depression. The prevalence of depression and high body fat was 7.9% and 41.1%, respectively. Only PFOA was significantly associated with depression in the entire sample (prevalence rate (PR): 1.91; confidence interval (CI95%): 1.01-3.65). However, in the group with normal adiposity, PFOA (3.20, CI95%: 1.46-7.01), PFNA (2.54, CI95%: 1.29-5.00), and PFDA (2.09, CI95%: 1.09-4.00) were also significant. Future research should investigate the role of obesity as well as the biological plausibility and possible mechanisms increasing the limited number of evidences between PFAS and depression.
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Affiliation(s)
- Geraldo Neto
- International Clinical Research Center (ICRC), St. Anne’s University Hospital (FNUSA), 65691 Brno, Czech Republic;
| | - Martin Bobak
- Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, 62500 Brno, Czech Republic; (M.B.); (J.K.)
- Research Department of Epidemiology and Public Health, University College London, London WC1H 9BT, UK
| | - Juan P. Gonzalez-Rivas
- International Clinical Research Center (ICRC), St. Anne’s University Hospital (FNUSA), 65691 Brno, Czech Republic;
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Harvard University, Boston, MA 02138, USA
- Foundation for Clinic, Public Health, and Epidemiology Research of Venezuela (FISPEVEN INC), Caracas 3001, Venezuela
| | - Jana Klanova
- Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, 62500 Brno, Czech Republic; (M.B.); (J.K.)
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12
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Steptoe A, Frank P. Obesity and psychological distress. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220225. [PMID: 37661745 PMCID: PMC10475872 DOI: 10.1098/rstb.2022.0225] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/16/2023] [Indexed: 09/05/2023] Open
Abstract
The relationship between high body weight and mental health has been studied for several decades. Improvements in the quality of epidemiological, mechanistic and psychological research have brought greater consistency to our understanding of the links. Large-scale population-based epidemiological research has established that high body weight is associated with poorer mental health, particularly depression and subclinical depressive symptoms. There is some evidence for bidirectional relationships, but the most convincing findings are that greater body weight leads to psychological distress rather than the reverse. Particular symptoms of depression and distress may be specifically related to greater body weight. The psychological stress induced by weight stigma and discrimination contributes to psychological distress, and may in turn handicap efforts at weight control. Heightened systemic inflammation and dysregulation of the hypothalamic-pituitary-adrenal axis are biological mechanisms that mediate in part the relationship of greater body weight with poorer mental health. Changing negative societal attitudes to high body weights would improve the wellbeing of people living with obesity, and promote more effective weight-inclusive attitudes and behaviours in society at large, particularly in healthcare settings. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.
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Affiliation(s)
- Andrew Steptoe
- Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London WC1E BT, UK
| | - Philipp Frank
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E BT, UK
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13
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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: 18] [Impact Index Per Article: 18.0] [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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14
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Karageorgiou V, Casanova F, O'Loughlin J, Green H, McKinley TJ, Bowden J, Tyrrell J. Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study. BMC Med 2023; 21:355. [PMID: 37710313 PMCID: PMC10502981 DOI: 10.1186/s12916-023-03001-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 07/24/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR). METHODS We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects. RESULTS In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls. DISCUSSION Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.
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Affiliation(s)
| | | | | | - Harry Green
- College of Medicine & Health, University of Exeter, Exeter, UK
| | | | - Jack Bowden
- College of Medicine & Health, University of Exeter, Exeter, UK
- Genetics Department, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Jessica Tyrrell
- College of Medicine & Health, University of Exeter, Exeter, UK
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15
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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: 13] [Impact Index Per Article: 13.0] [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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16
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Fu X, Wang Y, Zhao F, Cui R, Xie W, Liu Q, Yang W. Shared biological mechanisms of depression and obesity: focus on adipokines and lipokines. Aging (Albany NY) 2023; 15:5917-5950. [PMID: 37387537 PMCID: PMC10333059 DOI: 10.18632/aging.204847] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/01/2023] [Indexed: 07/01/2023]
Abstract
Depression and obesity are both common disorders currently affecting public health, frequently occurring simultaneously within individuals, and the relationship between these disorders is bidirectional. The association between obesity and depression is highly co-morbid and tends to significantly exacerbate metabolic and related depressive symptoms. However, the neural mechanism under the mutual control of obesity and depression is largely inscrutable. This review focuses particularly on alterations in systems that may mechanistically explain the in vivo homeostatic regulation of the obesity and depression link, such as immune-inflammatory activation, gut microbiota, neuroplasticity, HPA axis dysregulation as well as neuroendocrine regulators of energy metabolism including adipocytokines and lipokines. In addition, the review summarizes potential and future treatments for obesity and depression and raises several questions that need to be answered in future research. This review will provide a comprehensive description and localization of the biological connection between obesity and depression to better understand the co-morbidity of obesity and depression.
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Affiliation(s)
- Xiying Fu
- Department of Endocrinology, The Second Hospital of Jilin University, Changchun 130041, P.R. China
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Yicun Wang
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Fangyi Zhao
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Ranji Cui
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Wei Xie
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Qianqian Liu
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
| | - Wei Yang
- Jilin Provincial Key Laboratory for Molecular and Chemical Genetics, The Second Hospital of Jilin University, Changchun 130041, P.R. China
- Department of Neurology, The Second Hospital of Jilin University, Changchun 130041, P.R. China
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17
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Zhao G, Lu Z, Sun Y, Kang Z, Feng X, Liao Y, Sun J, Zhang Y, Huang Y, Yue W. Dissecting the causal association between social or physical inactivity and depression: a bidirectional two-sample Mendelian Randomization study. Transl Psychiatry 2023; 13:194. [PMID: 37291091 DOI: 10.1038/s41398-023-02492-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/19/2023] [Accepted: 05/26/2023] [Indexed: 06/10/2023] Open
Abstract
A growing body of research suggests that social or physical activity can affect the risk of Major depressive disorder (MDD). However, the bidirectional relationship between them remains to be clarified further, especially between inactivity and MDD. Here, we performed a two-sample Mendelian Randomization analysis using genetic variants associated with social/physical activities and MDD, and assessed the mediating effect of obesity-related measures and brain imaging phenotypes. The dataset on MDD, social activities, and physical activities included 500,199; 461,369; 460,376 individuals, respectively. Information regarding body mass index (BMI), body fat percentage (BFP), IDPs for 454,633; 461,460; 8,428 participants, respectively. We identified bidirectional causal relationships between sport clubs or gyms, strenuous sports, heavy do-it-youself, other exercises and MDD. We also observed that leisure/social inactivity (odds ratio [OR] = 1.64; P = 5.14 × 10-5) or physical inactivity (OR = 3.67; P = 1.99 × 10-5) caused an increased risk of MDD, which were partially mediated by BMI or BFP and masked by the weighted-mean orientation dispersion index of left acoustic radiation or volume of right caudate. Furthermore, we discovered that MDD increased the risk of leisure/social inactivity (OR = 1.03; P = 9.89 × 10-4) or physical inactivity (OR = 1.01; P = 7.96 × 10-4). In conclusions, we found that social/physical activities reduced the risk of MDD, while MDD in turn hindered social/physical activities. Inactivity may increase the risk of MDD, which was mediated or masked by brain imaging phenotypes. These results help to understand the manifestations of MDD and provide evidence and direction for the advancement of intervention and prevention.
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Affiliation(s)
- Guorui Zhao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Xiaoyang Feng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Junyuan Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China.
| | - Yu Huang
- National Engineering Research Center for Software Engineering, Peking University, Beijing, 100871, China.
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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18
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Quan Z, Li H, Quan Z, Qing H. Appropriate Macronutrients or Mineral Elements Are Beneficial to Improve Depression and Reduce the Risk of Depression. Int J Mol Sci 2023; 24:7098. [PMID: 37108261 PMCID: PMC10138658 DOI: 10.3390/ijms24087098] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/06/2023] [Accepted: 04/09/2023] [Indexed: 04/29/2023] Open
Abstract
Depression is a common mental disorder that seriously affects the quality of life and leads to an increasing global suicide rate. Macro, micro, and trace elements are the main components that maintain normal physiological functions of the brain. Depression is manifested in abnormal brain functions, which are considered to be tightly related to the imbalance of elements. Elements associated with depression include glucose, fatty acids, amino acids, and mineral elements such as lithium, zinc, magnesium, copper, iron, and selenium. To explore the relationship between these elements and depression, the main literature in the last decade was mainly searched and summarized on PubMed, Google Scholar, Scopus, Web of Science, and other electronic databases with the keywords "depression, sugar, fat, protein, lithium, zinc, magnesium, copper, iron, and selenium". These elements aggravate or alleviate depression by regulating a series of physiological processes, including the transmission of neural signals, inflammation, oxidative stress, neurogenesis, and synaptic plasticity, which thus affect the expression or activity of physiological components such as neurotransmitters, neurotrophic factors, receptors, cytokines, and ion-binding proteins in the body. For example, excessive fat intake can lead to depression, with possible mechanisms including inflammation, increased oxidative stress, reduced synaptic plasticity, and decreased expression of 5-Hydroxytryptamine (5-HT), Brain Derived Neurotrophic Factor (BDNF), Postsynaptic density protein 95(PSD-95), etc. Supplementing mineral elements, such as selenium, zinc, magnesium, or lithium as a psychotropic medication is mostly used as an auxiliary method to improve depression with other antidepressants. In general, appropriate nutritional elements are essential to treat depression and prevent the risk of depression.
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Affiliation(s)
| | | | - Zhenzhen Quan
- Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Hong Qing
- Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China
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19
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Lam BCC, Lim AYL, Chan SL, Yum MPS, Koh NSY, Finkelstein EA. The impact of obesity: a narrative review. Singapore Med J 2023; 64:163-171. [PMID: 36876622 PMCID: PMC10071857 DOI: 10.4103/singaporemedj.smj-2022-232] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
Obesity is a disease with a major negative impact on human health. However, people with obesity may not perceive their weight to be a significant problem and less than half of patients with obesity are advised by their physicians to lose weight. The purpose of this review is to highlight the importance of managing overweight and obesity by discussing the adverse consequences and impact of obesity. In summary, obesity is strongly related to >50 medical conditions, with many of them having evidence from Mendelian randomisation studies to support causality. The clinical, social and economic burdens of obesity are considerable, with these burdens potentially impacting future generations as well. This review highlights the adverse health and economic consequences of obesity and the importance of an urgent and concerted effort towards the prevention and management of obesity to reduce the burden of obesity.
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Affiliation(s)
- Benjamin Chih Chiang Lam
- Family and Community Medicine, Khoo Teck Puat Hospital; Integrated Care for Obesity and Diabetes, Khoo Teck Puat Hospital, Singapore
| | - Amanda Yuan Ling Lim
- Singapore Association for the Study of Obesity; Division of Endocrinology, Department of Medicine, National University Hospital, Singapore
| | - Soo Ling Chan
- Division of Endocrinology, Department of Medicine, Ng Teng Fong General Hospital, Singapore
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20
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Wang J, Qiu J, Zhu T, Zeng Y, Yang H, Shang Y, Yin J, Sun Y, Qu Y, Valdimarsdóttir UA, Song H. Prediction of Suicidal Behaviors in the Middle-aged Population: Machine Learning Analyses of UK Biobank. JMIR Public Health Surveill 2023; 9:e43419. [PMID: 36805366 PMCID: PMC9989910 DOI: 10.2196/43419] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/21/2022] [Accepted: 01/12/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Suicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. OBJECTIVE We aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. METHODS Based on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. RESULTS Individuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low (<1st) genetic susceptibilities groups, respectively. CONCLUSIONS We established applicable machine learning-based models for predicting both the short- and long-term risk of suicidality with high accuracy across populations of varying genetic risk for suicide, highlighting a cost-effective method of identifying individuals with a high risk of suicidality.
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Affiliation(s)
- Junren Wang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jiajun Qiu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Ting Zhu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yu Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Huazhen Yang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yanan Shang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jin Yin
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yajing Sun
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yuanyuan Qu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Unnur A Valdimarsdóttir
- Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.,Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Epidemiology, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, United States
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China.,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland
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21
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Chaplin AB, Daniels NF, Ples D, Anderson RZ, Gregory-Jones A, Jones PB, Khandaker GM. Longitudinal association between cardiovascular risk factors and depression in young people: a systematic review and meta-analysis of cohort studies. Psychol Med 2023; 53:1049-1059. [PMID: 34167604 PMCID: PMC9975997 DOI: 10.1017/s0033291721002488] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 05/21/2021] [Accepted: 06/03/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Depression is a common and serious mental illness that begins early in life. An association between cardiovascular disease (CVD) and subsequent depression is clear in adults. We examined associations between individual CVD risk factors and depression in young people. METHODS We searched MEDLINE, EMBASE, and PsycINFO databases from inception to 1 January 2020. We extracted data from cohort studies assessing the longitudinal association between CVD risk factors [body mass index (BMI), smoking, systolic blood pressure (SBP), total cholesterol, high-density lipoprotein] and depression, measured using a validated tool in individuals with mean age of 24 years or younger. Random effect meta-analysis was used to combine effect estimates from individual studies, including odds ratio (OR) for depression and standardised mean difference for depressive symptoms. RESULTS Based on meta-analysis of seven studies, comprising 15 753 participants, high BMI was associated with subsequent depression [pooled OR 1.61; 95% confidence interval (CI) 1.21-2.14; I2 = 31%]. Based on meta-analysis of eight studies, comprising 30 539 participants, smoking was associated with subsequent depression (pooled OR 1.73; 95% CI 1.36-2.20; I2 = 74%). Low, but not high, SBP was associated with an increased risk of depression (pooled OR 3.32; 95% CI 1.68-6.55; I2 = 0%), although this was based on a small pooled high-risk sample of 893 participants. Generalisability may be limited as most studies were based in North America or Europe. CONCLUSIONS Targeting childhood/adolescent smoking and obesity may be important for the prevention of both CVD and depression across the lifespan. Further research on other CVD risk factors including blood pressure and cholesterol in young people is required.
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Affiliation(s)
- Anna B. Chaplin
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Diana Ples
- School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Rebecca Z. Anderson
- Royal Liverpool University Hospital, Liverpool, UK
- Liverpool NHS Foundation Trust, Liverpool, UK
| | | | - Peter B. Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Golam M. Khandaker
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- MRC Integrative Epidemiology Unit, Population Health Science, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, University of Bristol, Bristol, UK
- Avon and Wiltshire Mental Health Partnership NHS Trust, Bristol, UK
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22
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O'Loughlin J, Casanova F, Fairhurst-Hunter Z, Hughes A, Bowden J, Watkins ER, Freathy RM, Millwood IY, Lin K, Chen Z, Li L, Lv J, Walters RG, Howe LD, Kuchenbaecker K, Tyrrell J. Mendelian randomisation study of body composition and depression in people of East Asian ancestry highlights potential setting-specific causality. BMC Med 2023; 21:37. [PMID: 36726144 PMCID: PMC9893684 DOI: 10.1186/s12916-023-02735-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 01/12/2023] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Extensive evidence links higher body mass index (BMI) to higher odds of depression in people of European ancestry. However, our understanding of the relationship across different settings and ancestries is limited. Here, we test the relationship between body composition and depression in people of East Asian ancestry. METHODS Multiple Mendelian randomisation (MR) methods were used to test the relationship between (a) BMI and (b) waist-hip ratio (WHR) with depression. Firstly, we performed two-sample MR using genetic summary statistics from a recent genome-wide association study (GWAS) of depression (with 15,771 cases and 178,777 controls) in people of East Asian ancestry. We selected 838 single nucleotide polymorphisms (SNPs) correlated with BMI and 263 SNPs correlated with WHR as genetic instrumental variables to estimate the causal effect of BMI and WHR on depression using the inverse-variance weighted (IVW) method. We repeated these analyses stratifying by home location status: China versus UK or USA. Secondly, we performed one-sample MR in the China Kadoorie Biobank (CKB) in 100,377 participants. This allowed us to test the relationship separately in (a) males and females and (b) urban and rural dwellers. We also examined (c) the linearity of the BMI-depression relationship. RESULTS Both MR analyses provided evidence that higher BMI was associated with lower odds of depression. For example, a genetically-instrumented 1-SD higher BMI in the CKB was associated with lower odds of depressive symptoms [OR: 0.77, 95% CI: 0.63, 0.95]. There was evidence of differences according to place of residence. Using the IVW method, higher BMI was associated with lower odds of depression in people of East Asian ancestry living in China but there was no evidence for an association in people of East Asian ancestry living in the USA or UK. Furthermore, higher genetic BMI was associated with differential effects in urban and rural dwellers within China. CONCLUSIONS This study provides the first MR evidence for an inverse relationship between BMI and depression in people of East Asian ancestry. This contrasts with previous findings in European populations and therefore the public health response to obesity and depression is likely to need to differ based on sociocultural factors for example, ancestry and place of residence. This highlights the importance of setting-specific causality when using genetic causal inference approaches and data from diverse populations to test hypotheses. This is especially important when the relationship tested is not purely biological and may involve sociocultural factors.
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Affiliation(s)
- Jessica O'Loughlin
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Francesco Casanova
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Zammy Fairhurst-Hunter
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Amanda Hughes
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Jack Bowden
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | | | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit (PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit (PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit (PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | | | - Jessica Tyrrell
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
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23
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Pavlova NT, Ramasawmy C, Picariello F, Smith C, Moss‐Morris R. ‘I don't know which is the chicken and which is the egg’: A qualitative study of weight loss‐related beliefs and behaviours among adults with psoriasis and comorbid obesity. Br J Health Psychol 2022; 28:532-551. [PMID: 36484107 DOI: 10.1111/bjhp.12639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 09/12/2022] [Accepted: 11/23/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Obesity is a common (30%-40%) comorbidity of psoriasis. Weight loss is shown to improve the severity of psoriasis; however, little is known about the factors that may influence successful weight loss in the context of obesity and psoriasis. The current qualitative study aimed to explore the obesity-associated beliefs, perceptions, and behaviours related to weight loss in psoriasis. Preferences for a weight loss intervention were also explored. DESIGN Qualitative in-depth semi-structured interviews were conducted with 24 adults (62.5% male) with moderate-to-severe psoriasis and obesity (mean body mass index = 35.2 kg/m2 , SD = 4.1), recruited through a patient organization website in the UK. Data were analysed using inductive thematic analysis. RESULTS Most participants viewed psoriasis as unrelated to obesity. A well-controlled psoriasis and improvements in psoriasis symptoms were considered as major motivators for engaging in a weight loss program by individuals who viewed psoriasis and obesity as related conditions. Comfort eating was perceived as an escape strategy from the psoriasis-induced negative emotions. Participants shared their dissatisfaction with current weight loss recommendations which were too generic. They suggested that a desirable weight loss program would require both emotional and behavioural support, with an emphasis on psoriasis' burden. CONCLUSION The findings accentuate the importance of (1) clinicians discussing the link between obesity and psoriasis with patients, (2) weight loss advice to include both behavioural and emotional support, and (3) a weight loss advice to consider the psoriasis burden and the perceived barriers which may potentially lead to improved outcomes to obesity management in psoriasis.
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Affiliation(s)
- Neli T. Pavlova
- Health Psychology Section, Psychology Department, Institute of Psychiatry Psychology and Neuroscience King's College London London UK
| | - Celeny Ramasawmy
- Health Psychology Section, Psychology Department, Institute of Psychiatry Psychology and Neuroscience King's College London London UK
| | - Federica Picariello
- Health Psychology Section, Psychology Department, Institute of Psychiatry Psychology and Neuroscience King's College London London UK
| | - Catherine Smith
- Health Psychology Section, Psychology Department, Institute of Psychiatry Psychology and Neuroscience King's College London London UK
- St John's Institute of Dermatology Guy's and St Thomas' NHS Foundation Trust London UK
| | - Rona Moss‐Morris
- Health Psychology Section, Psychology Department, Institute of Psychiatry Psychology and Neuroscience King's College London London UK
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24
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Yan SS, Xu Q, Han BX, Ni JJ, Wei XT, Feng GJ, Zhang H, Zhang YJ, Zhang L, Yu WY, Pei YF. Mendelian randomization analysis identified causal Association of Childhood Obesity with adult major depressive disorder. Pediatr Obes 2022; 17:e12960. [PMID: 35869568 DOI: 10.1111/ijpo.12960] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 06/10/2022] [Accepted: 06/30/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Childhood obesity is associated with adult major depressive disorder (MDD), but their causality is not clear. METHODS We performed a two-sample Mendelian randomization (MR) analysis to explore the causality of childhood body mass index (BMI) and childhood obesity on MDD, followed by a multivariable MR (MVMR) analysis to investigate the potential role of adult BMI in mediating such effect. We accessed genome-wide association summary statistics of childhood BMI, childhood obesity, adult BMI and adult MDD from the Early Growth Genetics consortium (nBMI = 47 541, nobesity = 24 160), the Genetic Investigation of Anthropometric Traits consortium (nadult_BMI = ∼700 000) and the Psychiatric Genomics consortium (nMDD = 500 199), respectively. The MR-PRESSO test was performed to remove SNPs with potential pleiotropic effect. The MR analysis was performed by inverse-variance weighted test. Further sensitivity analyses, including the MR-Egger intercept test and leave-one-out analysis, were performed to evaluate the reliability of the results. RESULTS Our study found that childhood obesity might increase the odds of developing MDD in adults (OR = 1.03, 95% CI: 1.01-1.06, p = 2.6 × 10-3 ). Children with higher BMI were more likely to develop MDD in adulthood, with an OR of 1.12 per standard deviation score (SDS) increase in BMI (95% CI: 1.07-1.17, p = 4.4 × 10-7 ). Sensitivity analyses verified the reliability of the causality between childhood BMI/obesity and MDD. Further MVMR results revealed that the impact of childhood BMI on MDD risk was predominantly mediated by adult BMI. CONCLUSION Our findings provided evidence of a causal relationship between childhood BMI/obesity and adult MDD, thus providing new insights into the prevention of MDD.
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Affiliation(s)
- Shan-Shan Yan
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Qian Xu
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Bai-Xue Han
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Jing-Jing Ni
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Xin-Tong Wei
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Gui-Juan Feng
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Hong Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - You-Jie Zhang
- Department of Child Health Care and Social Medicine, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Lei Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
| | - Wen-Yuan Yu
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,The Second Affiliated Hospital of Soochow University, SuZhou City, China
| | - Yu-Fang Pei
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, SuZhou City, China.,Department of Epidemiology and Health Statistics, School of Public Health, Suzhou Medical College of Soochow University, SuZhou City, China
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Abstract
In the absence of obesity, adverse lifestyle behaviours, and use of medication such as opioids serum testosterone concentrations decrease by only a minimal amount at least until very advanced age in most men. Obesity is heterogeneous in its phenotype, and it is the accumulation of excess adipose tissue viscerally associated with insulin resistance, dyslipidaemia, inflammation, hypothalamic leptin resistance and gliosis that underpins the functional hypogonadism of obesity. Both central (hypothalamic) and peripheral mechanisms are involved resulting in a low serum total testosterone concentration, while LH and FSH are typically in the normal range. Peripherally a decrease in serum sex hormone binding globulin (SHBG) concentration only partially explains the decrease in testosterone and there is increasing evidence for direct effects in the testis. Men with obesity associated functional hypogonadism and serum testosterone concentrations below 16 nmol/L are at increased risk of incident type 2 diabetes (T2D); high testosterone concentrations are protective. The magnitude of weight loss is linearly associated with an increase in serum testosterone concentration and with the likelihood of preventing T2D or reverting newly diagnosed disease; treatment with testosterone for 2 years increases the probability of a positive outcome from a lifestyle intervention alone by approximately 40%. Whether the additional favourable benefits of testosterone treatment on muscle mass and strength and bone density and quality in the long-term remains to be determined.
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Affiliation(s)
- Gary Wittert
- University of Adelaide, Adelaide, Australia.
- Freemasons Centre for Male Health and Wellbeing, South Australian Health and Medical Research Institute, University of Adelaide, Adelaide, Australia.
- South Australian Health and Medical Research Institute North Terrace Adelaide, 5000, SA, Adelaide, Australia.
| | - Mathis Grossmann
- Department of Medicine (Austin Health), The University of Melbourne, Heidelberg, Victoria4, Germany
- Department of Endocrinology, Austin Health, Heidelberg, VIC, Germany
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26
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Pavlova NT, Moss‐Morris R, Smith C, Carr E, Rayner L, Picariello F. The importance of illness severity and multimorbidity in the association between mental health and body weight in psoriasis: Cross-sectional and longitudinal analysis. SKIN HEALTH AND DISEASE 2022; 2:e117. [PMID: 36479273 PMCID: PMC9720224 DOI: 10.1002/ski2.117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 04/05/2022] [Accepted: 04/05/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND High body weight is common in psoriasis and is associated with depression and anxiety. Past studies are mostly cross-sectional and may underestimate the role of demographic and illness-related factors in the association between mental health and body weight in psoriasis. OBJECTIVES This study explored the association between depression and anxiety with waist circumference and body mass index (BMI) cross-sectionally and at 12 months follow-up, adjusting for demographic and illness-related factors in people with psoriasis. METHOD Routine psoriasis care data were combined with data on depression and anxiety from a large specialist psoriasis centre. The analytical samples consisted of patients with complete data on either waist circumference (N = 326 at time 1; N = 191 at follow-up) or BMI (N = 399 at time 1; N = 233 at follow-up) and corresponding mental health, demographic, and illness-related information. Associations between weight-related outcomes and mental health variables were assessed at time one and at 12 months follow-up, after adjusting for demographic and illness-related factors. RESULTS We found no evidence of associations between mental health and waist circumference or BMI, after adjusting for age, gender and illness-related factors. Higher age, male gender and illness-related factors, specifically multimorbidity and psoriasis severity, were positively associated with waist circumference and BMI at both time points. CONCLUSION This study revealed the important role of factors related to illness severity in body weight in psoriasis. The contribution of depression and anxiety to weight was not observed here likely due to the sample and methodology used. Future work should explore other psychosocial factors such as weight-related attitudes and emotional eating in the context of weight in psoriasis, to help inform the development of successful weight-management treatments.
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Affiliation(s)
- Neli T. Pavlova
- Health Psychology SectionPsychology DepartmentInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
| | - Rona Moss‐Morris
- Health Psychology SectionPsychology DepartmentInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
| | - Catherine Smith
- Health Psychology SectionPsychology DepartmentInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
- Guy's and St Thomas' NHS Foundation TrustSt John's Institute of DermatologyLondonUK
| | - Ewan Carr
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
| | - Lauren Rayner
- Department of Psychological MedicineInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
| | - Federica Picariello
- Health Psychology SectionPsychology DepartmentInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
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27
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Jespersen A, Yilmaz Z, Vilhjálmsson BJ. Harnessing the Power of Population Cohorts to Study the Relationship Between Endocrine-Metabolic Disorders and Depression. Am J Psychiatry 2022; 179:788-790. [PMID: 36317332 DOI: 10.1176/appi.ajp.20220798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Affiliation(s)
- Anders Jespersen
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
| | - Zeynep Yilmaz
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
| | - Bjarni J Vilhjálmsson
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
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28
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Leone M, Kuja-Halkola R, Leval A, Butwicka A, Skov J, Zhang R, Liu S, Larsson H, Bergen SE. Genetic and Environmental Contribution to the Co-Occurrence of Endocrine-Metabolic Disorders and Depression: A Nationwide Swedish Study of Siblings. Am J Psychiatry 2022; 179:824-832. [PMID: 36128682 DOI: 10.1176/appi.ajp.21090954] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
OBJECTIVE Depression is common in individuals with endocrine-metabolic disorders and vice versa, and a better understanding of the underlying factors contributing to the comorbidity of these disorders is needed. This study investigated the familial coaggregation of depression and endocrine-metabolic disorders and estimated the contribution of genetic and environmental factors to their co-occurrence. METHODS This population-based cohort study included 2.2 million individuals born in Sweden between 1973 and 1996, with follow-up through 2013. Participants were linked to their biological parents, allowing identification of full siblings, maternal half siblings, and paternal half siblings. Diagnoses of depression and endocrine-metabolic conditions were investigated, with the latter grouped into autoimmune disorders (autoimmune hypothyroidism, Graves' disease, and type 1 diabetes) and non-autoimmune disorders (type 2 diabetes, obesity, and polycystic ovary syndrome). Logistic regression and Cox regression were used to estimate the associations between endocrine-metabolic disorders and depression within the same individual and across siblings. Quantitative genetic modeling was performed to investigate the relative contribution of genetic and environmental influences. RESULTS Individuals with endocrine-metabolic disorders had a significantly higher risk of depression, with odds ratios ranging from 1.43 (95% CI=1.30, 1.57) for Graves' disease to 3.48 (95% CI=3.25, 3.72) for type 2 diabetes. Increased risks extended to full and half siblings. These correlations were mainly explained by shared genetic influences for non-autoimmune conditions, and by nonshared environmental factors for autoimmune disorders, especially for type 1 diabetes. CONCLUSIONS These findings provide phenotypic and etiological insights into the co-occurrence of depression and various endocrine-metabolic conditions, which could guide future research aiming at identifying pathophysiological mechanisms and intervention targets.
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Affiliation(s)
- Marica Leone
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Ralf Kuja-Halkola
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Amy Leval
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Agnieszka Butwicka
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Jakob Skov
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Ruyue Zhang
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Shengxin Liu
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Henrik Larsson
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
| | - Sarah E Bergen
- Janssen Pharmaceutical Companies of Johnson & Johnson, Solna, Sweden (Leone, Leval); Department of Medical Epidemiology and Biostatistics (Leone, Kuja-Halkola, Leval, Butwicka, Zhang, Liu, Larsson, Bergen) and Department of Molecular Medicine and Surgery (Skov), Karolinska Institutet, Solna, Sweden; Child and Adolescent Psychiatry Stockholm, Stockholm Health Care Services, Region Stockholm, Sweden (Butwicka); Department of Child Psychiatry, Medical University of Warsaw, Warsaw (Butwicka); Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland (Butwicka); Department of Medicine, Karlstad Central Hospital, Karlstad, Sweden (Skov); School of Medical Sciences, Örebro University, Örebro, Sweden (Larsson)
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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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Lee H, Jang SJ. Social jetlag and depression in female rotating-shift nurses: A secondary analysis. Perspect Psychiatr Care 2022; 58:2246-2254. [PMID: 35146748 DOI: 10.1111/ppc.13054] [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: 11/03/2021] [Revised: 01/31/2022] [Accepted: 02/04/2022] [Indexed: 11/28/2022] Open
Abstract
PURPOSE This study aimed to identify the predictors of depression among female rotating-shift nurses. DESIGN AND METHODS This secondary data analysis used data of 190 Korean female rotating-shift nurses from the parent study conducted in 2018. A multiple logistic regression analysis was performed to identify the predictors of depression. FINDINGS Young age, poor sleep quality, and greater morning-shift social jetlag predicted depression among female nurses working a three-shift schedule. PRACTICE IMPLICATIONS Nursing management should consider scheduling shifts to minimize nurses' social jetlag and develop interventions for improving sleep quality to prevent depression among female rotating-shift nurses.
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Affiliation(s)
- Haeyoung Lee
- Red Cross College of Nursing, Chung-Ang University, Seoul, Korea
| | - Sun Joo Jang
- Red Cross College of Nursing, Chung-Ang University, Seoul, Korea
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31
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Pedroso I, Kumbhare SV, Joshi B, Saravanan SK, Mongad DS, Singh-Rambiritch S, Uday T, Muthukumar KM, Irudayanathan C, Reddy-Sinha C, Dulai PS, Sinha R, Almonacid DE. Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures. J Pers Med 2022; 12:jpm12081237. [PMID: 36013186 PMCID: PMC9409755 DOI: 10.3390/jpm12081237] [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: 05/30/2022] [Revised: 07/21/2022] [Accepted: 07/21/2022] [Indexed: 11/16/2022] Open
Abstract
Neuropsychiatric diseases and obesity are major components of morbidity and health care costs, with genetic, lifestyle, and gut microbiome factors linked to their etiology. Dietary and weight-loss interventions can help improve mental health, but there is conflicting evidence regarding their efficacy; and moreover, there is substantial interindividual heterogeneity that needs to be understood. We aimed to identify genetic and gut microbiome factors that explain interindividual differences in mental health improvement after a dietary and lifestyle intervention for weight loss. We recruited 369 individuals participating in Digbi Health’s personalized digital therapeutics care program and evaluated the association of 23 genetic scores, the abundance of 178 gut microbial genera, and 42 bacterial pathways with mental health. We studied the presence/absence of anxiety or depression, or sleep problems at baseline and improvement on anxiety, depression, and insomnia after losing at least 2% body weight. Participants lost on average 5.4% body weight and >95% reported improving mental health symptom intensity. There were statistically significant correlations between: (a) genetic scores with anxiety or depression at baseline, gut microbial functions with sleep problems at baseline, and (b) genetic scores and gut microbial taxa and functions with anxiety, depression, and insomnia improvement. Our results are concordant with previous findings, including the association between anxiety or depression at baseline with genetic scores for alcohol use disorder and major depressive disorder. As well, our results uncovered new associations in line with previous epidemiological literature. As evident from previous literature, we also observed associations of gut microbial signatures with mental health including short-chain fatty acids and bacterial neurotoxic metabolites specifically with depression. Our results also show that microbiome and genetic factors explain self-reported mental health status and improvement better than demographic variables independently. The genetic and microbiome factors identified in this study provide the basis for designing and personalizing dietary interventions to improve mental health.
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Affiliation(s)
- Inti Pedroso
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Shreyas Vivek Kumbhare
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Bharat Joshi
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Santosh K. Saravanan
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | | | - Simitha Singh-Rambiritch
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Tejaswini Uday
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Karthik Marimuthu Muthukumar
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Carmel Irudayanathan
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Chandana Reddy-Sinha
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Parambir S. Dulai
- Division of Gastroenterology, Northwestern University, Chicago, IL 60208, USA;
| | - Ranjan Sinha
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
| | - Daniel Eduardo Almonacid
- Digbi Health, Mountain View, CA 94040, USA; (I.P.); (S.V.K.); (B.J.); (S.K.S.); (S.S.-R.); (T.U.); (K.M.M.); (C.I.); (C.R.-S.); (R.S.)
- Correspondence:
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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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Fabbri C. Genetics in psychiatry: Methods, clinical applications and future perspectives. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2022; 1:e6. [PMID: 38868637 PMCID: PMC11114394 DOI: 10.1002/pcn5.6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/18/2022] [Accepted: 03/02/2022] [Indexed: 06/14/2024]
Abstract
Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi-determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome-wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome-wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data.
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Affiliation(s)
- Chiara Fabbri
- Department of Biomedical and Neuromotor SciencesUniversity of BolognaBolognaItaly
- Institute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
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da Cruz KLDO, Salla DH, de Oliveira MP, da Silva LE, Dela Vedova LM, Mendes TF, Bressan CBC, Costa AB, da Silva MR, Réus GZ, de Mello AH, Rezin GT. The impact of obesity-related neuroinflammation on postpartum depression: A narrative review. Int J Dev Neurosci 2022; 82:375-384. [PMID: 35595536 DOI: 10.1002/jdn.10198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 04/29/2022] [Accepted: 05/16/2022] [Indexed: 11/10/2022] Open
Abstract
Obesity is currently one of the most serious health problems, affecting 13% of the world's adult population. Obesity is characterized by persistent low-grade chronic inflammation that assumes systemic proportions and triggers several associated metabolic diseases. Furthermore, obesity has been associated with an increased occurrence of central disorders such as impaired cognitive function, reward system dysfunction, and depression. In summary, there is a quantitative reduction in the release of neurotransmitters in depression. Postsynaptic cells capture lower concentrations of neurotransmitters, which leads to a functional reduction in the central nervous system (CNS). Globally, approximately 15-65% of women experience depressive symptoms during pregnancy, depending on their location. Depressive symptoms persist in some women, leading to postpartum depression (PPD). Thus, obesity may be considered a risk factor for PPD development. This study aimed to synthesize studies on the impact of obesity-related neuroinflammation and PPD. We conducted a narrative review of the relevant literature. The search was performed in electronic databases, specifically PubMed, selecting articles in English published from 2014 to 2021 using the narrative review methodology.
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Affiliation(s)
- Kenia Lourdes de Oliveira da Cruz
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Daniele Hendler Salla
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Mariana Pacheco de Oliveira
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Larissa Espindola da Silva
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Larissa Marques Dela Vedova
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Talita Farias Mendes
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Catarina Barbosa Chaves Bressan
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Ana Beatriz Costa
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Mariella Reinol da Silva
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
| | - Gislaine Zilli Réus
- Translational Psychiatry Laboratory, Graduate Program in Health Sciences, University of Southern Santa Catarina, Criciuma, Brazil
| | - Aline Haas de Mello
- Department of Pediatrics, The University of Texas Medical Branch, Galveston, Texas, USA
| | - Gislaine Tezza Rezin
- Laboratory of Neurobiology of Inflammatory and Metabolic Processes, Graduate Program in Health Sciences, University of Southern Santa Catarina, Tubarao, Brazil
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Almramhi MM, Storm CS, Kia DA, Coneys R, Chhatwal BK, Wood NW. The role of body fat in multiple sclerosis susceptibility and severity: A Mendelian randomisation study. Mult Scler 2022; 28:1673-1684. [PMID: 35575213 DOI: 10.1177/13524585221092644] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE The objective of this study was to explore the potential causal associations of body mass index, height, weight, fat mass, fat percentage and non-fat mass in the whole body, arms, legs and trunk (henceforth, 'anthropometric measures') with multiple sclerosis (MS) risk and severity. We also investigated the potential for reverse causation between anthropometric measures and MS risk. METHODS We conducted a two-sample univariable, multivariable and bidirectional Mendelian randomisation (MR) analysis. RESULTS A range of features linked to obesity (body mass index, weight, fat mass and fat percentage) were risk factors for MS development and worsened the disease's severity in MS patients. Interestingly, we were able to demonstrate that height and non-fat mass have no association with MS risk or MS severity. We demonstrated that the association between anthropometric measures and MS is not subject to bias from reverse causation. CONCLUSIONS Our findings provide evidence from human genetics that a range of features linked to obesity is an important contributor to MS development and MS severity, but height and non-fat mass are not. Importantly, these findings also identify a potentially modifiable factor that may reduce the accumulation of further disability and ameliorate MS severity.
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Affiliation(s)
- Mona M Almramhi
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK/Department of Medical Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
| | - Catherine S Storm
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Demis A Kia
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Rachel Coneys
- Department of Neurodegenerative Diseases, Queen Square Institute of Neurology, University College London, London, UK
| | - Burleen K Chhatwal
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Nicholas W Wood
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, WC1N 3BG, UK
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Nowicka M, Górska M, Edyko K, Szklarek-Kubicka M, Kazanek A, Prylińska M, Niewodniczy M, Kostka T, Kurnatowska I. Association of Physical Performance, Muscle Strength and Body Composition with Self-Assessed Quality of Life in Hemodialyzed Patients: A Cross-Sectional Study. J Clin Med 2022; 11:jcm11092283. [PMID: 35566409 PMCID: PMC9103996 DOI: 10.3390/jcm11092283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 03/26/2022] [Accepted: 04/04/2022] [Indexed: 12/03/2022] Open
Abstract
(1) Patients on chronic hemodialysis (HD) experience impaired quality of life (QoL). We analyzed HD’s relationship with physical performance, body composition, and muscle strength; (2) QoL was assessed with the Short Form-36, composed of physical (PCS) and mental (MCS) health dimensions. Physical performance was assessed with the Short Physical Performance Battery (SPPB), body composition (lean tissue mass% (LTM%), fat tissue mass% (FTM%), and skeletal muscle mass% (SMM%)) was assessed with bioelectrical impedance, and lower extremity strength was assessed with a handheld dynamometer; and (3) we enrolled 76 patients (27 F, 49 M), age 62.26 ± 12.81 years, HD vintage 28.45 (8.65−77.49) months. Their QoL score was 53.57 (41.07−70.64); their PCS and MCS scores were 52.14 (38.69−65.95) and 63.39 (44.64−76.79) and strongly correlated (p < 0.0001, R = 0.738). QoL correlated positively with SPPB (R = 0.35, p ≤ 0.001), muscle strength (R from 0.21 to 0.41, p < 0.05), and LTM% (R = 0.38, p < 0.001) and negatively with FTM% (R = −0.32, p = 0.006). PCS correlated positively with SPPB (R = 0.42 p < 0.001), muscle strength (R 0.25−0.44, p < 0.05), and LTM% (R = 0.32, p = 0.006) and negatively with FTM% (R = −0.25, p = 0.031). MCS correlated positively with SPPB (R = 0.23, p = 0.047), SMM% (R = 0.25; p = 0.003), and LTM% (R = 0.39, p < 0.001) and negatively with FTM% (R = −0.34; p = 0.003). QoL was unrelated to sex (p = 0.213), age (p = 0.157), HD vintage (p = 0.156), and BMI (p = 0.202); (4) Better physical performance, leaner body composition, and higher muscle strength are associated with better mental and physical QoL in HD.
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Affiliation(s)
- Maja Nowicka
- Department of Internal Medicine and Transplant Nephrology, Medical University of Lodz, 90-153 Lodz, Poland
| | - Monika Górska
- Department of Internal Medicine and Transplant Nephrology, Medical University of Lodz, 90-153 Lodz, Poland
| | - Krzysztof Edyko
- Department of Internal Medicine and Transplant Nephrology, Medical University of Lodz, 90-153 Lodz, Poland
| | | | - Adam Kazanek
- Therapeutic Rehabilitation Outpatient Clinic, Medical Center Lodz Baluty, 91-745 Lodz, Poland
| | - Malwina Prylińska
- Therapeutic Rehabilitation Outpatient Clinic, Medical Center Lodz Baluty, 91-745 Lodz, Poland
| | - Maciej Niewodniczy
- Rehabilitation Department, Norbert Barlicki Memorial Teaching Hospital No. 1, 90-153 Lodz, Poland
| | - Tomasz Kostka
- Department of Geriatrics, Healthy Ageing Research Center, Medical University of Lodz, 90-647 Lodz, Poland
| | - Ilona Kurnatowska
- Department of Internal Medicine and Transplant Nephrology, Medical University of Lodz, 90-153 Lodz, Poland
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Cai J, Wei Z, Chen M, He L, Wang H, Li M, Peng Y. Socioeconomic Status, Individual Behaviors and Risk for Mental Disorders: A Mendelian Randomization Study. Eur Psychiatry 2022; 65:e28. [PMID: 35431011 PMCID: PMC9158396 DOI: 10.1192/j.eurpsy.2022.18] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background There is increasing attention on the association of socioeconomic status and individual behaviors (SES/IB) with mental health. However, the impacts of SES/IB on mental disorders are still unclear. To provide evidence for establishing feasible strategies on disease screening and prevention, we implemented Mendelian randomization (MR) design to appraise causality between SES/IB and mental disorders. Methods We conducted a two-sample MR study to assess the causal effects of SES and IB (dietary habits, habitual physical activity, smoking behaviors, drinking behaviors, sleeping behaviors, leisure sedentary behaviors, risky behaviors, and reproductive behaviors) on three mental disorders, including bipolar disorder, major depressive disorder and schizophrenia. A series of filtering steps were taken to select eligible genetic instruments robustly associated with each of the traits. Inverse variance weighted was used for primary analysis, with alternative MR methods including MR-Egger, weighted median, and weighted mode estimate. Complementary methods were further used to detect pleiotropic bias. Results After Bonferroni correction and rigorous quality control, we identified that SES (educational attainment), smoking behaviors (smoking initiation, number of cigarettes per day), risky behaviors (adventurousness, number of sexual partners, automobile speeding propensity) and reproductive behavior (age at first birth) were causally associated with at least one of the mental disorders. Conclusions MR study provides robust evidence that SES/IB play broad impacts on mental disorders.
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Affiliation(s)
- Jiahao Cai
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zixin Wei
- Department of Pulmonary and Critical Care Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ming Chen
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Lei He
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hongxuan Wang
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mei Li
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Peng
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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Zheng R, Chen Y, Jiang Y, Zhou B, Li S, Wei Y, Wang C, Han S, Zhang Y, Cheng J. Abnormal dynamic functional connectivity in first-episode, drug-naïve adolescents with major depressive disorder. J Neurosci Res 2022; 100:1463-1475. [PMID: 35393711 DOI: 10.1002/jnr.25047] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 01/18/2023]
Abstract
Previous neuroimaging studies have identified disrupted large-scale functional brain networks in major depressive disorder (MDD); however, most of them focused on adult patients and were based on static functional connectivity (FC). Thus, we aimed to investigate the patterns of change in dynamic FC in depressed adolescents. Resting-state functional magnetic resonance imaging data were acquired from 60 first-episode, drug-naïve adolescents with MDD and 60 matched healthy controls (HCs). Then, the dynamic FC properties were analyzed using a sliding windows approach, k-means clustering, and graph theory methods. The intrinsic brain FC were clustered into two configuration states-a more frequent and relatively sparsely connected State 1 and a less frequent and more strongly interconnected State 2. Compared with HCs, depressed adolescents had higher reoccurrence fraction and dwell time in State 1, and lower reoccurrence fraction and dwell time in State 2, and higher total number of transitions between the two states. Depressed adolescents showed decreased FC within the default mode network (DMN) and between the DMN and other networks in State 1. Additionally, the MDD group showed higher variances in the global and local efficiency. Furthermore, the duration of illness was positively correlated with the number of state transitions, and the 17-item Hamilton Depression Rating Scale score was positively correlated with the mean dwell time in State 1. This study demonstrated abnormal dynamic FC in depressed adolescents, which provided new insights into the pathophysiological mechanisms of adolescent-onset depression.
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Affiliation(s)
- Ruiping Zheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
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Food addiction comorbid to mental disorders in adolescents: a nationwide survey and register-based study. Eat Weight Disord 2022; 27:945-959. [PMID: 34089511 DOI: 10.1007/s40519-021-01212-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/08/2021] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Adolescence is a high-risk period for development of addictive behavior. This may also apply to addiction-like eating of highly processed foods-commonly referred to as "food addiction". Adolescents with mental disorder may be at particularly elevated risk of developing food addiction as addiction often accompanies mental disorder. However, there are only few studies in adolescents investigating this potential comorbidity. Therefore, the primary aim of this study was to examine the food addiction symptom load, as measured by the dimensional Yale Food Addiction Scale for Children-version 2.0 (dYFAS-C 2.0), among adolescents with a clinically verified mental disorder. METHOD A total of 3529 adolescents aged 13-17 were drawn from the Danish Psychiatric Central Research Register, stratified on six major diagnostic categories of mental disorders; psychotic disorders, affective disorders, anxiety disorders, eating disorders, autism spectrum disorders, and attention deficit disorders. Via their parents, these adolescents were invited to participate in a web-based survey. Data on health and socioeconomic factors from the Danish registers were linked to both respondents and non-respondents, allowing for thorough attrition analysis and estimation of weighted dYFAS-C 2.0 scores. RESULTS A total of 423 adolescents participated in the survey (response rate 12.0%). The mean weighted dYFAS-C 2.0 total score was 13.9 (95% CI 12.6; 14.9) for the entire sample and varied substantially across the diagnostic categories being highest for those with psychotic disorder, mean 18.4 (95% CI 14.6; 14.9), and affective disorders, mean 19.4. (95% CI 16.3; 22.5). Furthermore, the dYFAS-C 2.0 total score was positively correlated with body mass index (BMI) (r = 0.33, p < 0.05). CONCLUSION Food addiction symptomatology seems to be prevalent among adolescents with mental disorder, particularly affective and psychotic disorders. As obesity is a tremendous problem in individuals with mental disorder further investigation of food addiction in young people with mental disorder is called for. This could potentially aid in the identification of potential transdiagnostic targets for prevention and treatment of obesity in this group. LEVEL OF EVIDENCE Level IV, Observational cross-sectional descriptive study combined with retrospective register data.
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Morató L, Astori S, Zalachoras I, Rodrigues J, Ghosal S, Huang W, Guillot de Suduiraut I, Grosse J, Zanoletti O, Cao L, Auwerx J, Sandi C. eNAMPT actions through nucleus accumbens NAD +/SIRT1 link increased adiposity with sociability deficits programmed by peripuberty stress. SCIENCE ADVANCES 2022; 8:eabj9109. [PMID: 35235362 PMCID: PMC8890725 DOI: 10.1126/sciadv.abj9109] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 01/05/2022] [Indexed: 05/15/2023]
Abstract
Obesity is frequently associated with impairments in the social domain, and stress at puberty can lead to long-lasting changes in visceral fat deposition and in social behaviors. However, whether stress-induced changes in adipose tissue can affect fat-to-brain signaling, thereby orchestrating behavioral changes, remains unknown. We found that peripubertally stressed male-but not female-mice exhibit concomitant increased adiposity and sociability deficits. We show that reduced levels of the adipokine nicotinamide phosphoribosyltransferase (NAMPT) in fat and its extracellular form eNAMPT in blood contribute to lifelong reductions in sociability induced by peripubertal stress. By using a series of adipose tissue and brain region-specific loss- and gain-of-function approaches, we implicate impaired nicotinamide adenine dinucleotide (NAD+)/SIRT1 pathway in the nucleus accumbens. Impairments in sociability and accumbal neuronal excitability are prevented by normalization of eNAMPT levels or treatment with nicotinamide mononucleotide (NMN), a NAD+-boosting compound. We propose NAD+ boosters to treat social deficits of early life stress origin.
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Affiliation(s)
- Laia Morató
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Simone Astori
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ioannis Zalachoras
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Joao Rodrigues
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Sriparna Ghosal
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Wei Huang
- The Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Isabelle Guillot de Suduiraut
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Jocelyn Grosse
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Olivia Zanoletti
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Lei Cao
- The Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Carmen Sandi
- Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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Luque-Reca O, Soriano-Maldonado A, Gavilán-Carrera B, Acosta-Manzano P, Ariza-Vega P, Del Paso GAR, Álvarez-Gallardo IC, Estévez-López F. Longitudinal associations of physical fitness and affect with depression, anxiety and life satisfaction in adult women with fibromyalgia. Qual Life Res 2022; 31:2047-2058. [PMID: 35098387 DOI: 10.1007/s11136-021-03058-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE This study analysed the longitudinal associations of physical fitness and affect with depression, anxiety and life satisfaction at 2- and 5-year follow-up. METHODS In 312 adult women with fibromyalgia, physical fitness was measured by performance-based tests and affect, depression, anxiety and life satisfaction were self-reported using the Positive and Negative Affect Schedule (PANAS), Beck Depression Inventory-second edition (BDI-II), State Trait Anxiety Inventory-I (STAI) and Satisfaction with Life Scale (SWLS), respectively. We conducted sequential linear regression analyses adjusted for baseline levels of depression, anxiety, life satisfaction, age, body fat percentage and education. RESULTS At the 2-year follow-up, all the associations under study were significant. At the 5-year follow-up, a number of associations remained significant. First, lowering negative affect was independently associated with lower depression, anxiety and higher life satisfaction (β's from 0.14 to 0.31). Second, favourable changes in positive affect were independently associated with lower anxiety (β = 0.21) and higher life satisfaction (β = 0.28). Third, enhancing physical fitness was related to higher life satisfaction (β = 0.16). CONCLUSION Reductions in negative affect were associated with more favourable depression, anxiety and life satisfaction at the 2- and 5-year follow-up. Improvements in positive affect were associated with more favourable anxiety and life satisfaction and enhancements in physical fitness were associated with higher life satisfaction. If corroborated in clinical-experimental research, these findings may guide the development of interventions that are tailored to the levels of physical fitness, affect and the outcome of interest (i.e. depression, anxiety or life satisfaction) in women with fibromyalgia.
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Affiliation(s)
| | - Alberto Soriano-Maldonado
- Department of Education, Faculty of Education Sciences and SPORT Research Group (CTS-1024), CERNEP Research Center, University of Almería, Almería, Spain.
| | - Blanca Gavilán-Carrera
- Physical Activity for Health Promotion Research Group (PA-HELP), Department of Physical Education and Sport, Faculty of Sport Sciences and Sport and Health University Research Institute (iMUDS), Granada, Spain.,Department of Physical Education, Faculty of Education Sciences and Biomedical Research and Innovation Institute of Cádiz (INiBICA) Research Unit, University of Cádiz, Cádiz, Spain
| | - Pedro Acosta-Manzano
- Physical Activity for Health Promotion Research Group (PA-HELP), Department of Physical Education and Sport, Faculty of Sport Sciences and Sport and Health University Research Institute (iMUDS), Granada, Spain
| | - Patrocinio Ariza-Vega
- Occupational Therapy Division, Department of Physical Therapy, Faculty of Health Sciences, University of Granada, Granada, Spain
| | | | - Inmaculada C Álvarez-Gallardo
- Department of Physical Education, Faculty of Education Sciences and Biomedical Research and Innovation Institute of Cádiz (INiBICA) Research Unit, University of Cádiz, Cádiz, Spain
| | - Fernando Estévez-López
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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Anguita-Ruiz A, Zarza-Rebollo JA, Pérez-Gutiérrez AM, Molina E, Gutiérrez B, Bellón JÁ, Moreno-Peral P, Conejo-Cerón S, Aiarzagüena JM, Ballesta-Rodríguez MI, Fernández A, Fernández-Alonso C, Martín-Pérez C, Montón-Franco C, Rodríguez-Bayón A, Torres-Martos Á, López-Isac E, Cervilla J, Rivera M. Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals. Transl Psychiatry 2022; 12:30. [PMID: 35075110 PMCID: PMC8786870 DOI: 10.1038/s41398-022-01783-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 11/24/2021] [Accepted: 01/04/2022] [Indexed: 11/22/2022] Open
Abstract
Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.
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Affiliation(s)
- Augusto Anguita-Ruiz
- grid.4489.10000000121678994Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain ,grid.4489.10000000121678994Institute of Nutrition and Food Technology “José Mataix”, Biomedical Research Center (CIBM), University of Granada, Granada, Spain ,grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.413448.e0000 0000 9314 1427CIBEROBN (Physiopathology of Obesity and Nutrition CB12/03/30038), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Juan Antonio Zarza-Rebollo
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain. .,Institute of Neurosciences 'Federico Olóriz', Biomedical Research Center (CIBM), University of Granada, Granada, Spain.
| | - Ana M Pérez-Gutiérrez
- grid.4489.10000000121678994Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain
| | - Esther Molina
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain ,grid.4489.10000000121678994Department of Nursing, Faculty of Health Sciences, University of Granada, Granada, Spain
| | - Blanca Gutiérrez
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain ,grid.4489.10000000121678994Department of Psychiatry, Faculty of Medicine, University of Granada, Granada, Spain
| | - Juan Ángel Bellón
- grid.452525.1Primary Care District of Málaga-Guadalhorce, Biomedical Research Institute of Málaga (IBIMA), Primary Care Prevention and Health Promotion Network (redIAPP), Málaga, Spain ,grid.10215.370000 0001 2298 7828Department of Public Health and Psychiatry, Faculty of Medicine, University of Málaga, Málaga, Spain
| | - Patricia Moreno-Peral
- grid.452525.1Primary Care District of Málaga-Guadalhorce, Biomedical Research Institute of Málaga (IBIMA), Primary Care Prevention and Health Promotion Network (redIAPP), Málaga, Spain
| | - Sonia Conejo-Cerón
- grid.452525.1Primary Care District of Málaga-Guadalhorce, Biomedical Research Institute of Málaga (IBIMA), Primary Care Prevention and Health Promotion Network (redIAPP), Málaga, Spain
| | | | | | - Anna Fernández
- grid.428876.7Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, Barcelona, Spain ,grid.466571.70000 0004 1756 6246CIBERESP, Centro de Investigacion Biomedica en Red de Epidemiologia y Salud Publica, Madrid, Spain
| | | | - Carlos Martín-Pérez
- grid.418355.eMarquesado Health Centre, Servicio Andaluz de Salud, Granada, Spain
| | - Carmen Montón-Franco
- grid.488737.70000000463436020Casablanca Health Centre, Aragonese Institute of Health Sciences, IIS Aragón, Zaragoza, Spain ,grid.11205.370000 0001 2152 8769Department of Medicine and Psychiatry, University of Zaragoza, Zaragoza, Spain
| | | | - Álvaro Torres-Martos
- grid.4489.10000000121678994Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain
| | - Elena López-Isac
- grid.4489.10000000121678994Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain
| | - Jorge Cervilla
- grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain ,grid.4489.10000000121678994Department of Psychiatry, Faculty of Medicine, University of Granada, Granada, Spain
| | - Margarita Rivera
- grid.4489.10000000121678994Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain ,grid.507088.2Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain ,grid.4489.10000000121678994Institute of Neurosciences ‘Federico Olóriz’, Biomedical Research Center (CIBM), University of Granada, Granada, Spain
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Madison AA, Andridge R, Shrout MR, Renna ME, Bennett JM, Jaremka LM, Fagundes CP, Belury MA, Malarkey WB, Kiecolt-Glaser JK. Frequent Interpersonal Stress and Inflammatory Reactivity Predict Depressive-Symptom Increases: Two Tests of the Social-Signal-Transduction Theory of Depression. Psychol Sci 2022; 33:152-164. [PMID: 34932407 PMCID: PMC8985224 DOI: 10.1177/09567976211031225] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 05/26/2021] [Indexed: 11/17/2022] Open
Abstract
The social-signal-transduction theory of depression asserts that people who experience ongoing interpersonal stressors and mount a greater inflammatory response to social stress are at higher risk for depression. The current study tested this theory in two adult samples. In Study 1, physically healthy adults (N = 76) who reported more frequent interpersonal tension had heightened depressive symptoms at Visit 2, but only if they had greater inflammatory reactivity to a marital conflict at Visit 1. Similarly, in Study 2, depressive symptoms increased among lonelier and less socially supported breast-cancer survivors (N = 79). This effect was most pronounced among participants with higher inflammatory reactivity to a social-evaluative stressor at Visit 1. In both studies, noninterpersonal stress did not interact with inflammatory reactivity to predict later depressive symptoms.
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Affiliation(s)
- Annelise A. Madison
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
- Department of Psychology, The Ohio
State University
| | - Rebecca Andridge
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
- College of Public Health, The Ohio
State University
| | - M. Rosie Shrout
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
| | - Megan E. Renna
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
| | - Jeanette M. Bennett
- Department of Psychological Science,
The University of North Carolina at Charlotte
| | - Lisa M. Jaremka
- Department of Psychology and Brain
Sciences, University of Delaware
| | | | - Martha A. Belury
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
- Department of Human Sciences, The Ohio
State University College of Education and Human Ecology
| | - William B. Malarkey
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
- Department of Internal Medicine, The
Ohio State University College of Medicine
| | - Janice K. Kiecolt-Glaser
- Institute for Behavioral Medicine
Research, The Ohio State University College of Medicine
- Department of Psychiatry and Behavioral
Health, The Ohio State University College of Medicine
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44
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Yoshiji S, Tanaka D, Minamino H, Lu T, Butler-Laporte G, Murakami T, Fujita Y, Richards JB, Inagaki N. Causal associations between body fat accumulation and COVID-19 severity: A Mendelian randomization study. Front Endocrinol (Lausanne) 2022; 13:899625. [PMID: 35992131 PMCID: PMC9381824 DOI: 10.3389/fendo.2022.899625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 06/29/2022] [Indexed: 12/05/2022] Open
Abstract
Previous studies reported associations between obesity measured by body mass index (BMI) and coronavirus disease 2019 (COVID-19). However, BMI is calculated only with height and weight and cannot distinguish between body fat mass and fat-free mass. Thus, it is not clear if one or both of these measures are mediating the relationship between obesity and COVID-19. Here, we used Mendelian randomization (MR) to compare the independent causal relationships of body fat mass and fat-free mass with COVID-19 severity. We identified single nucleotide polymorphisms associated with body fat mass and fat-free mass in 454,137 and 454,850 individuals of European ancestry from the UK Biobank, respectively. We then performed two-sample MR to ascertain their effects on severe COVID-19 (cases: 4,792; controls: 1,054,664) from the COVID-19 Host Genetics Initiative. We found that an increase in body fat mass by one standard deviation was associated with severe COVID-19 (odds ratio (OR)body fat mass = 1.61, 95% confidence interval [CI]: 1.28-2.04, P = 5.51 × 10-5; ORbody fat-free mass = 1.31, 95% CI: 0.99-1.74, P = 5.77 × 10-2). Considering that body fat mass and fat-free mass were genetically correlated with each other (r = 0.64), we further evaluated independent causal effects of body fat mass and fat-free mass using multivariable MR and revealed that only body fat mass was independently associated with severe COVID-19 (ORbody fat mass = 2.91, 95% CI: 1.71-4.96, P = 8.85 × 10-5 and ORbody fat-free mass = 1.02, 95%CI: 0.61-1.67, P = 0.945). In summary, this study demonstrates the causal effects of body fat accumulation on COVID-19 severity and indicates that the biological pathways influencing the relationship between COVID-19 and obesity are likely mediated through body fat mass.
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Affiliation(s)
- Satoshi Yoshiji
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Kyoto-McGill International Collaborative Program in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Daisuke Tanaka
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hiroto Minamino
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Tianyuan Lu
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Quantitative Life Sciences Program, McGill University, Montréal, QC, Canada
| | - Guillaume Butler-Laporte
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
| | - Takaaki Murakami
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yoshihito Fujita
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - J. Brent Richards
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
- Department of Twin Research, King’s College London, London, United Kingdom
- 5 Prime Sciences, Montréal, QC, Canada
- *Correspondence: J. Brent Richards, ; Nobuya Inagaki,
| | - Nobuya Inagaki
- Department of Diabetes, Endocrinology and Nutrition, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- *Correspondence: J. Brent Richards, ; Nobuya Inagaki,
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45
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Vučković M, Radić J, Gelemanović A, Bučan Nenadić D, Kolak E, Radić M. Associations between Depression, Nutritional Status and Mediterranean Diet in Dalmatian Kidney Transplant Recipients. Nutrients 2021; 13:nu13124479. [PMID: 34960031 PMCID: PMC8709030 DOI: 10.3390/nu13124479] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/03/2021] [Accepted: 12/11/2021] [Indexed: 12/13/2022] Open
Abstract
Depression has been addressed as a predictor of worse outcomes in kidney transplant recipients (KTRs). Nutritional status plays a great role in treatment of this population. The Mediterranean diet (MeDi) has been associated with lower levels of depressive symptoms. The aim of this cross-sectional study was to determine the rate of depression and its correlations to nutritional status and dietary habits according to the MeDi in Dalmatian KTRs. We included 115 KTRs, and data about body composition and anthropometric, laboratory and clinical parameters were obtained for each study participant. The Beck Depression Inventory-II (BDI-II) questionnaire was used to assess depressive symptoms and the Mediterranean Diet Serving Score (MDSS) was used to assess adherence to the MeDi. We found the presence of depressive symptoms in 21.73% of the Dalmatian KTRs. BDI-II score was reciprocally associated with fat mass, trunk visceral fat, anthropometric parameters of obesity, triglyceride levels and olive oil consumption. Inverse associations were found between BDI-II score and skeletal muscle mass, handgrip strength, MCV, hemoglobin levels and consumption of fish and white meat, as suggested by the MeDi. Our results showed the interconnections between nutritional status, dietary habits and depression in Dalmatian KTRs.
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Affiliation(s)
- Marijana Vučković
- Department of Nephrology and Dialysis, University Hospital Centre Split, 21000 Split, Croatia;
| | - Josipa Radić
- Department of Nephrology and Dialysis, University Hospital Centre Split, 21000 Split, Croatia;
- Department of Internal Medicine, University of Split School of Medicine, 21000 Split, Croatia;
- Correspondence:
| | - Andrea Gelemanović
- Mediterranean Institute for Life Sciences (MedILS), 21000 Split, Croatia;
| | - Dora Bučan Nenadić
- Department of Nutrition and Dietetics, University Hospital Centre Split, 21000 Split, Croatia; (D.B.N.); (E.K.)
| | - Ela Kolak
- Department of Nutrition and Dietetics, University Hospital Centre Split, 21000 Split, Croatia; (D.B.N.); (E.K.)
| | - Mislav Radić
- Department of Internal Medicine, University of Split School of Medicine, 21000 Split, Croatia;
- Department of Clinical Immunology and Rheumatology, University Hospital Centre Split, 21000 Split, Croatia
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46
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Frank P, Jokela M, Batty GD, Cadar D, Steptoe A, Kivimäki M. Association Between Systemic Inflammation and Individual Symptoms of Depression: A Pooled Analysis of 15 Population-Based Cohort Studies. Am J Psychiatry 2021; 178:1107-1118. [PMID: 34645276 DOI: 10.1176/appi.ajp.2021.20121776] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Evidence from anti-inflammatory drug trials for the treatment of depression has been inconsistent. This may be ascribed to the differing symptom-specific effects of inflammation. Accordingly, the authors explored the associations between systemic inflammation and an array of individual symptoms of depression across multiple studies. METHODS This random-effects pooled analysis included 15 population-based cohorts and 56,351 individuals age 18 years and older. Serum or plasma concentrations of C-reactive protein (CRP) and interleukin-6 (IL-6) were measured at baseline. Using validated self-report measures, 24 depressive symptoms were ascertained in 15 cross-sectional studies, and, in seven cohorts, were also assessed at follow-up (mean follow-up period, 3.2 years). RESULTS The prevalence of depressive symptoms ranged from 1.1% (suicidal ideation) to 21.5% (sleep problems). In cross-sectional analyses, higher concentrations of CRP were robustly associated with an increased risk of experiencing four physical symptoms (changes in appetite, felt everything was an effort, loss of energy, sleep problems) and one cognitive symptom (little interest in doing things). These associations remained after adjustment for sociodemographic variables, behavioral factors, and chronic conditions; in sex- and age-stratified analyses; in longitudinal analyses; when using IL-6 as the inflammatory marker of interest; in depressed individuals; and after excluding chronically ill individuals. For four exclusively emotional symptoms (bothered by things, hopelessness about the future, felt fearful, life had been a failure), the overall evidence was strongly against an association with inflammation. CONCLUSIONS These findings suggest symptom-specific rather than generalized effects of systemic inflammation on depression. Future trials exploring anti-inflammatory treatment regimens for depression may benefit from targeting individuals presenting with symptom profiles characterized by distinct inflammation-related physical and cognitive symptoms.
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Affiliation(s)
- Philipp Frank
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
| | - Markus Jokela
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
| | - G David Batty
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
| | - Dorina Cadar
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
| | - Andrew Steptoe
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
| | - Mika Kivimäki
- Research Department of Epidemiology and Public Health (Frank, Batty, Kivimäki) and Research Department of Behavioural Science and Health (Frank, Cadar, Steptoe), University College London; Department of Psychology and Logopedics (Jokela) and Clinicum Unit (Kivimäki), Faculty of Medicine, University of Helsinki, Helsinki
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47
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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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48
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Subjective well-being in non-obese individuals depends strongly on body composition. Sci Rep 2021; 11:21797. [PMID: 34750456 PMCID: PMC8576020 DOI: 10.1038/s41598-021-01205-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 10/25/2021] [Indexed: 01/07/2023] Open
Abstract
While obesity has been correlated with welfare in the general population, there is not much data on the influence of body composition on welfare among the non-obese adult individuals. In this study, a total of 726 non-obese individuals from the general population were analyzed. The mean age was 46.8 ± 15.4 years and 42.1% of participants were male. The anthropometric measurements and dual energy X-ray absorptiometry (DEXA) were done. The mean value for the Satisfaction with Life Scale (SWLS) was 23.09 ± 5.43, for Euro Quality of Life Visual Analogue Scale (EQ-VAS) was 78.0 ± 14.5, and for the Beck Depression Inventory (BDI) was 6.7 ± 6.6. On the SWLS, the higher waist-hip ratio had a negative impact even after adjusting for age, gender, and concomitant diseases. EQ-VAS was inversely associated with android fat distribution and directly associated with muscle mass. BDI value was inversely associated with lower muscle mass, especially in lower limbs. The well-being of women was mainly associated with the distribution of adipose tissue and less with the distribution of muscle tissue-abdominal fat distribution has a particularly negative impact on well-being among women. In contrast, men's well-being depends more on muscle mass and to a lesser extent on the distribution of fat tissue-a positive significant effect has lean mass and a circumference of thigh below gluteal fold.
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49
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Muniz Carvalho C, Wendt FR, Pathak GA, Maihofer AX, Stein DJ, Sumner JA, Hemmings SM, Nievergelt CM, Koenen KC, Gelernter J, Belangero SI, Polimanti R. Disentangling sex differences in the shared genetic architecture of posttraumatic stress disorder, traumatic experiences, and social support with body size and composition. Neurobiol Stress 2021; 15:100400. [PMID: 34611531 PMCID: PMC8477211 DOI: 10.1016/j.ynstr.2021.100400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 09/04/2021] [Accepted: 09/14/2021] [Indexed: 11/03/2022] Open
Abstract
There is a well-known association of traumatic experiences and posttraumatic stress disorder (PTSD) with body size and composition, including consistent differences between sexes. However, the biology underlying these associations is unclear. To understand the genetic underpinnings of this complex relationship, we investigated genome-wide datasets informative of African and European ancestries from the Psychiatric Genomic Consortium, the UK Biobank, the GIANT Consortium, and the Million Veteran Program. We used genome-wide association statistics to estimate sex-specific genetic correlations (r g ) of traumatic experiences, social support, and PTSD with multiple anthropometric traits. After multiple testing corrections (false discovery rate, FDR q < 0.05), we observed 58 significant r g relationships in females (e.g., childhood physical abuse and body mass index, BMI r g = 0.245, p = 3.88 × 10-10) and 21 significant r g relationships in males (e.g., been involved in combat or exposed to warzone and leg fat percentage; r g = 0.405, p = 4.42 × 10-10). We performed causal inference analyses of these genetic overlaps using Mendelian randomization and latent causal variable approaches. Multiple female-specific putative causal relationships were observed linking body composition/size with PTSD (e.g., leg fat percentage→PTSD; beta = 0.319, p = 3.13 × 10-9), traumatic experiences (e.g., childhood physical abuse→waist circumference; beta = 0.055, p = 5.07 × 10-4), and childhood neglect (e.g., "someone to take you to doctor when needed as a child"→BMI; beta = -0.594, p = 1.09 × 10-5). In males, we observed putative causal effects linking anthropometric-trait genetic liabilities to traumatic experiences (e.g., BMI→childhood physical abuse; beta = 0.028, p = 8.19 × 10-3). Some of these findings were replicated in individuals of African descent although the limited sample size available did not permit us to conduct a sex-stratified analysis in this ancestry group. In conclusion, our findings provide insights regarding sex-specific causal networks linking anthropometric traits to PTSD, traumatic experiences, and social support.
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Affiliation(s)
- Carolina Muniz Carvalho
- Department of Psychiatry, Yale School of Medicine and VA CT Healthcare Center, West Haven, CT, 06516, USA
- Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Frank R. Wendt
- Department of Psychiatry, Yale School of Medicine and VA CT Healthcare Center, West Haven, CT, 06516, USA
| | - Gita A. Pathak
- Department of Psychiatry, Yale School of Medicine and VA CT Healthcare Center, West Haven, CT, 06516, USA
| | - Adam X. Maihofer
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Dan J. Stein
- MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jennifer A. Sumner
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Sian M.J. Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Caroline M. Nievergelt
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Karestan C. Koenen
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine and VA CT Healthcare Center, West Haven, CT, 06516, USA
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Sintia I. Belangero
- Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Genetics Division, Department of Morphology and Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine and VA CT Healthcare Center, West Haven, CT, 06516, USA
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Zhu Z, Chen H, Chen J, Ma J, He Y. The Effect of Commuting Time on Job Stress in Obese Men With Different Exercise Frequency in China. Am J Mens Health 2021; 14:1557988320975542. [PMID: 33307953 PMCID: PMC7739097 DOI: 10.1177/1557988320975542] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Previous studies have mainly focused on the independent impact of commuting time, exercise, and stress on people. There are few studies regarding the impact of the combined effect of multiple factors on special populations such as obese people. As obesity has become increasingly widespread in China, we studied the impact of commuting time on work stress on Chinese obese men (who exercise regularly vs. who exercise irregularly). We performed a secondary retrospective analysis of the cross-sectional data from the 2014 China Labor Force Dynamics Survey. We found that long commute times and less exercise have a positive effect on the increase in stress, but the effect is less evident for people who exercise regularly. Commuters traveling on foot are more stressed than those traveling by car. This study also found that commuting time had a significant impact on the perceived work stress of obese men who exercised irregularly. But the relationship between commuting time and work stress was different among groups with different commuting styles. For obese men who commuted on foot or motorcycle, commuting time had a significant impact on their job stress. However, for obese men who commuted by bicycle, bus, or car, commuting time had no significant effect on job stress. Additionally, active and passive commuting have different effects on stress. Active commuters tend to be more stressed, while passive commuters do not show a significant impact.
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Affiliation(s)
- Zhenjun Zhu
- College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China
| | - Hongsheng Chen
- School of Architecture, Southeast University, Nanjing, China
| | - Junlan Chen
- School of Transportation, Southeast University, Nanjing, China
| | - Jianxiao Ma
- College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China
| | - Yudong He
- College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China
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