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Wagh R, Hatem G, Andersson J, Kunte P, Bandyopadhyay S, Yajnik CS, Prasad RB. Parent-of-origin effects in the life-course evolution of cardiometabolic traits. Diabetologia 2025:10.1007/s00125-025-06396-5. [PMID: 40175764 DOI: 10.1007/s00125-025-06396-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2024] [Accepted: 01/22/2025] [Indexed: 04/04/2025]
Abstract
AIMS/HYPOTHESIS Cardiometabolic traits are heritable, and some display parent-of-origin effects, which indicates preferential inheritance from one parent or parental bias. Most studies of these phenomena have focused on adult populations. We aimed to investigate the heritability and parent-of-origin effects on cardiometabolic traits in a birth cohort with serial measurements to determine whether these patterns emerged early in life. METHODS The Pune Maternal Nutrition Study comprises a birth cohort in which offspring and parents were studied from birth and followed up for 24 years. We investigated parent-of-origin effects on cardiometabolic traits cross-sectionally at available timepoints using linear regression, and longitudinally across the life course using mixed-effect regression. Maternal and paternal effects on offspring phenotype were modelled after adjusting for age, sex and BMI. Parent-of-origin effects were calculated based on the difference between maternal and paternal effects. We also investigated these effects in another birth cohort, that of the Pune Children's Study. Genetic parent-of-origin effects were assessed using generalised estimating equations after taking the parental origin of the alleles into account. RESULTS Birthweight showed a maternal parent-of-origin effect. At 24 years, maternal bias was seen for some obesity-related traits for daughters, while paternal bias was seen for WHR in sons. A shift from paternal bias at 6 years to maternal bias at 24 years for the skinfold thickness was observed in daughters. Fasting glucose and lipids showed maternal bias at 6, 12 and 24 years. For fasting insulin and HOMA2-S, a negative maternal effect at 6 years transitioned to a positive one at 12 years. For HOMA2-B, a paternal effect at 6 years transitioned to a maternal one at 12 years, and this remained so at 24 years. Some of these findings were also observed in the cohort from the Pune Children's Study. Longitudinal modelling revealed stronger paternal effects over time for fasting insulin and HOMA indices but maternal effects for glucose and lipids, reflecting their cumulative effect over time. Genetic variants at the KCNQ1 locus showed a maternal parent-of-origin effect on birthweight, on HOMA2-B at 12 years, and on lipids at 6 and 12 years. CONCLUSIONS/INTERPRETATION Our study provides proof of concept of the existence of parent-of-origin effects on cardiometabolic traits from birth, through childhood and puberty, until adult age. Our results indicate a predominantly maternal influence on intrauterine, pubertal and reproductive-age metabolism in the offspring. While the longitudinal analysis indicated a maternal bias for the macronutrients (glucose and lipids), and a paternal bias for glucose-insulin metabolism, the cross-sectional analysis revealed a transition between parental influence across physiological stages. This dynamic relationship may have its origins in the life-history theory of evolution, and could inform strategies for primordial prevention aimed at curbing the rising burden of cardiometabolic disease. Further studies are needed to determine the mechanisms underlying such effects.
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Affiliation(s)
- Rucha Wagh
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Gad Hatem
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Jonas Andersson
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Pooja Kunte
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | | | - Chittaranjan S Yajnik
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Rashmi B Prasad
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden.
- Institute of Molecular Medicine Finland, Helsinki University, Helsinki, Finland.
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Goulet D, Boivin M, Gravel CA, Little J, Potter BK, Dubois L. Mediation of genetic susceptibility to obesity through eating behaviours in children. Pediatr Obes 2025; 20:e13180. [PMID: 39390328 PMCID: PMC11936709 DOI: 10.1111/ijpo.13180] [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: 06/25/2024] [Revised: 09/09/2024] [Accepted: 09/13/2024] [Indexed: 10/12/2024]
Abstract
BACKGROUND/OBJECTIVES Few studies have examined the putative mediating role of eating behaviours linking genetic susceptibility and body weight. The goal of this study was to investigate the extent to which two polygenic scores (PGSs) for body mass index (BMI), based on child and adult data, predicted BMI through over-eating and fussy eating across childhood. SUBJECTS/METHODS The study sample involved 692 participants from a birth cohort study. Height and weight were measured on six occasions between ages 6 and 13 years. Over-eating and fussy eating behaviours were assessed five times between ages 2 and 6 years. Longitudinal growth curve mediation analysis was used to estimate the contributions of the PGSs to BMI z-scores mediated by over-eating and fussy eating. RESULTS Both PGSs predicted BMI z-scores (PGSchild: β = 0.26, 95% CI: 0.19-0.33; PGSadult: β = 0.34, 95% CI: 0.27-0.41). Over-eating significantly mediated these associations, but this mediation decreased over time from 6 years (PGSchild: 18.0%, 95% CI: 3.1-32.9, p-value = 0.018; PGSadult: 14.2%, 95% CI: 2.8-25.5, p-value = 0.014) to 13 years (PGSchild: 11.4%, 95% CI: -0.4-23.1, p-value = 0.057; PGSadult: 6.2%, 95% CI: 0.4-12.0, p-value = 0.037). Fussy eating did not show any mediation. CONCLUSIONS Our results support the view that appetite is key to translating genetic susceptibility into changes in body weight.
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Affiliation(s)
- Danick Goulet
- School of Epidemiology and Public HealthUniversity of OttawaOttawaOntarioCanada
| | | | - Christopher A. Gravel
- School of Epidemiology and Public HealthUniversity of OttawaOttawaOntarioCanada
- Department of Epidemiology, Biostatistics and Occupational HealthMcGill UniversityMontrealQuebecCanada
- Department of Mathematics and StatisticsUniversity of OttawaOttawaOntarioCanada
| | - Julian Little
- School of Epidemiology and Public HealthUniversity of OttawaOttawaOntarioCanada
| | - Beth K. Potter
- School of Epidemiology and Public HealthUniversity of OttawaOttawaOntarioCanada
| | - Lise Dubois
- School of Epidemiology and Public HealthUniversity of OttawaOttawaOntarioCanada
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Nair JM, Chauhan G, Prasad G, Bandesh K, Giri AK, Chakraborty S, Marwaha RK, Mathur S, Choudhury D, Tandon N, Basu A, Bharadwaj D. Mapping the landscape of childhood obesity: genomic insights and socioeconomic status in Indian school-going children. Obesity (Silver Spring) 2025; 33:754-765. [PMID: 40000390 DOI: 10.1002/oby.24248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Revised: 11/19/2024] [Accepted: 12/20/2024] [Indexed: 02/27/2025]
Abstract
OBJECTIVE Childhood obesity (OB) is influenced by complex gene-environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand. METHODS A two-staged genome-wide association study (GWAS; N = 5673) and an independent exome-wide association study (ExWAS; N = 4963) were performed using a generalized linear model assuming additive effect to identify the common and rare genetic variants respectively associated with childhood OB. Rare-variant burden testing was also performed. We used the gene expression profiles and regulatory data from public databases to explain the novel associations. The implications of SES as a potential modifier of genetic susceptibility were evaluated. RESULTS GWAS identified novel associations in TCF7L2, IMMP2L, IPMK, CDC5L, SNTG1, and MX1, whereas ExWAS uncovered CNTN4, COQ4, TNFRSF10D, FLG-AS1, and BMP3. Both GWAS and ExWAS validated known associations in FTO and MC4R. Furthermore, rare-variant testing highlighted the role of 101 genes. We also observed that SES can modulate the inherent susceptibility to OB. CONCLUSIONS Our study identified genetic variants associated with childhood OB and highlighted the gene-environmental interaction in childhood OB.
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Affiliation(s)
- Janaki M Nair
- School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Ganesh Chauhan
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Gauri Prasad
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Khushdeep Bandesh
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Anil K Giri
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Shraddha Chakraborty
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Raman K Marwaha
- International Life Sciences Institute (ILSI), New Delhi, India
| | - Sandeep Mathur
- Department of Endocrinology, SMS Medical College and Hospital, Jaipur, India
| | | | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India
| | - Analabha Basu
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics, Kalyani, India
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Chen XX, Lu FY, Wang Y, Zhang L, Li SQ, Lin YN, Yan YR, Ding YJ, Li N, Zhou JP, Sun XW, Li QY. Causal effect of life-course adiposity on the risk of respiratory diseases: a Mendelian randomization study. Nutr Metab (Lond) 2025; 22:25. [PMID: 40119483 PMCID: PMC11929217 DOI: 10.1186/s12986-025-00915-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Accepted: 03/03/2025] [Indexed: 03/24/2025] Open
Abstract
BACKGROUND There is limited evidence on the causal associations of life-course adiposity with the risk of respiratory diseases. This study aimed to elucidate these associations. METHODS Two-sample Mendelian randomization was conducted using genetic instruments of life-course adiposity (including birth weight, childhood BMI, and adulthood adiposity) to estimate their causal effect on respiratory diseases in participants of European ancestry from the UK Biobank, the FinnGen consortium, and other large consortia. RESULTS Genetically predicted higher birth weight was associated with decreased risk of acute upper respiratory infections and increased risk of pulmonary embolism, sleep apnea, and lung cancer. Genetically predicted high childhood BMI was associated with increased risk of asthma, COPD, pulmonary embolism, and sleep apnea. However, most of these observed associations were no longer significant after adjusting for adult BMI. Genetically predicted higher adult BMI and WHR were associated with 10 and 4 respiratory diseases, respectively. High adult body fat percentage and visceral adiposity were genetically associated with increased risk of 9 and 11 respiratory diseases, respectively. Consistently, genetically predicted higher whole-body fat mass was associated with increased risk of 8 respiratory diseases. CONCLUSIONS This study provides genetic evidence that greater adiposity in childhood and adulthood has a causal effect in increasing the risk of a wide range of respiratory diseases. Furthermore, the effects of childhood obesity on respiratory outcomes may be mediated by adult obesity.
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Affiliation(s)
- Xi Xi Chen
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Fang Ying Lu
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yi Wang
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Liu Zhang
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shi Qi Li
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ying Ni Lin
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ya Ru Yan
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yong Jie Ding
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ning Li
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jian Ping Zhou
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xian Wen Sun
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Qing Yun Li
- Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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5
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Huang J, Che J, Kee MZL, Tan AP, Law EC, Silveira PP, Pokhvisneva I, Patel S, Godfrey KM, Daniel LM, Tan KH, Chong YS, Chan SY, Eriksson JG, Wang D, Huang JY. Linking obesity-associated genotype to child language development: the role of early-life neurology-related proteomics and brain myelination. EBioMedicine 2025; 113:105579. [PMID: 39938231 PMCID: PMC11868953 DOI: 10.1016/j.ebiom.2025.105579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 01/06/2025] [Accepted: 01/17/2025] [Indexed: 02/14/2025] Open
Abstract
BACKGROUND The association between childhood obesity and language development may be confounded by socio-environmental factors and attributed to comorbid pathways. METHODS In a longitudinal Singaporean mother-offspring cohort, we leveraged trans-ancestry polygenic predictions of body mass index (BMI) to interrogate the causal effects of early-life BMI on child language development and its effects on molecular and neuroimaging measures. Leveraging large genome-wide association studies, we examined whether the link between obesity and language development is causal or due to a shared genetic basis. FINDINGS We found an inverse association between polygenic risk for obesity, which is less susceptible to confounding, and language ability assessed at age 9. Our findings suggested a shared genetic basis between obesity and language development rather than a causal effect of obesity on language development. Interrogating early-life mechanisms including neurology-related proteomics and language-related white matter microstructure, we found that EFNA4 and VWC2 expressions were associated with language ability as well as fractional anisotropy of language-related white matter tracts, suggesting a role in brain myelination. Additionally, the expression of the EPH-Ephrin signalling pathway in the hippocampus might contribute to language development. Polygenic risk for obesity was nominally associated with EFNA4 and VWC2 expression. However, we did not find support for mediating mechanisms via these proteins. INTERPRETATION This study demonstrates the potential of examining early-life proteomics in conjunction with deep genotyping and phenotyping and provides biological insights into the shared genomic links between obesity and language development. FUNDING Singapore National Research Foundation and Agency for Science, Technology and Research.
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Affiliation(s)
- Jian Huang
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK.
| | - Jinyi Che
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore
| | - Michelle Z L Kee
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore
| | - Ai Peng Tan
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Department of Diagnostic Imaging, National University Hospital, Singapore, Republic of Singapore; Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, NUS, Singapore, Republic of Singapore
| | - Evelyn C Law
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Paediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, Singapore, Republic of Singapore
| | - Patricia Pelufo Silveira
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Psychiatry, Faculty of Medicine and Ludmer Centre for Neuroinformatics and Mental Health, Douglas Hospital Research Centre, McGill University, Montreal, Canada
| | - Irina Pokhvisneva
- Department of Psychiatry, Faculty of Medicine and Ludmer Centre for Neuroinformatics and Mental Health, Douglas Hospital Research Centre, McGill University, Montreal, Canada
| | - Sachin Patel
- Department of Psychiatry, Faculty of Medicine and Ludmer Centre for Neuroinformatics and Mental Health, Douglas Hospital Research Centre, McGill University, Montreal, Canada
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Centre and NIHR Southampton Biomedical Research Centre, University of Southampton & University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Lourdes Mary Daniel
- Department of Child Development, KK Women's and Children's Hospital, Singapore, Republic of Singapore
| | - Kok Hian Tan
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Republic of Singapore
| | - Yap Seng Chong
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore
| | - Shiao-Yng Chan
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore
| | - Johan G Eriksson
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore; Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | - Dennis Wang
- Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Human Potential Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore; National Heart and Lung Institute, Imperial College London, London, UK; Department of Computer Science, University of Sheffield, Sheffield, UK
| | - Jonathan Yinhao Huang
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Republic of Singapore; Thompson School of Social Work & Public Health, Office of Public Health Studies, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA
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Halder SK, Melkani GC. The Interplay of Genetic Predisposition, Circadian Misalignment, and Metabolic Regulation in Obesity. Curr Obes Rep 2025; 14:21. [PMID: 40024983 PMCID: PMC11872776 DOI: 10.1007/s13679-025-00613-3] [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] [Accepted: 02/11/2025] [Indexed: 03/04/2025]
Abstract
PURPOSE OF REVIEW This review explores the complex interplay between genetic predispositions to obesity, circadian rhythms, metabolic regulation, and sleep. It highlights how genetic factors underlying obesity exacerbate metabolic dysfunction through circadian misalignment and examines promising interventions to mitigate these effects. RECENT FINDINGS Genome-wide association Studies (GWAS) have identified numerous Single Nucleotide Polymorphisms (SNPs) associated with obesity traits, attributing 40-75% heritability to body mass index (BMI). These findings illuminate critical links between genetic obesity, circadian clocks, and metabolic processes. SNPs in clock-related genes influence metabolic pathways, with disruptions in circadian rhythms-driven by poor sleep hygiene or erratic eating patterns-amplifying metabolic dysfunction. Circadian clocks, synchronized with the 24-h light-dark cycle, regulate key metabolic activities, including glucose metabolism, lipid storage, and energy utilization. Genetic mutations or external disruptions, such as irregular sleep or eating habits, can destabilize circadian rhythms, promoting weight gain and metabolic disorders. Circadian misalignment in individuals with genetic predispositions to obesity disrupts the release of key metabolic hormones, such as leptin and insulin, impairing hunger regulation and fat storage. Interventions like time-restricted feeding (TRF) and structured physical activity offer promising strategies to restore circadian harmony, improve metabolic health, and mitigate obesity-related risks.
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Affiliation(s)
- Sajal Kumar Halder
- Department of Pathology, Division of Molecular and Cellular Pathology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Girish C Melkani
- Department of Pathology, Division of Molecular and Cellular Pathology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
- UAB Nathan Shock Center, Birmingham, AL, 35294, USA.
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Xu G, Liu Z, Hou P. Causality of Childhood and Adult Body Mass Index on Sick Sinus Syndrome: A Mendelian Randomization Study. Cureus 2025; 17:e80913. [PMID: 40125526 PMCID: PMC11929112 DOI: 10.7759/cureus.80913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/19/2025] [Indexed: 03/25/2025] Open
Abstract
Background The relationship between body mass index (BMI) and the risk of sick sinus syndrome (SSS) remains unclear. Clarifying the impact of BMI on SSS at different life stages is essential for advancing precision medicine and implementing effective prevention strategies to reduce the burden of SSS. Methods The causalities of childhood and adult BMI with SSS were investigated by univariate and multivariate Mendelian randomization. Reverse causalities were also explored to improve the accuracy of causality findings. Different sources of exposure data were used for replication analysis, and the effects of sample overlap were investigated using MRlap. The stability of the results was further enhanced through meta-analysis. Results There was a positive correlation of adult BMI with the risk of SSS in both the FinnGen (odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.01-1.35, P = 0.031) and Integrative Epidemiology Unit (IEU) open genome-wide association study (GWAS) project (OR = 1.18, 95% CI 1.04-1.34, P = 0.009) databases. The causality remained valid after the correction of telomere length. There was no causality detected between childhood BMI and SSS, as determined by independent studies of the Early Growth Genetics (EGG) 2020 (OR = 1.06, 95% CI 0.89-1.27, P = 0.513) and EGG2015 (OR = 1.02, 95% CI 0.97-1.09, P = 0.423). Meta-analysis results further confirmed the reliability of the causal inference. Conclusions The findings indicate that elevated BMI in adults, particularly among middle-aged and elderly populations, increases the risk of developing SSS. In contrast, no causal relationship was observed between childhood BMI and SSS, suggesting that the influence of BMI on SSS susceptibility may predominantly emerge during later life stages. These results highlight the need for targeted public health interventions to address adult obesity as a modifiable risk factor for SSS.
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Affiliation(s)
- Guanzhen Xu
- Graduate School, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, CHN
| | - Zhuang Liu
- Cardiology Department, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, CHN
| | - Ping Hou
- Graduate School, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, CHN
- Cardiology Department, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, CHN
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Chen L, Qu Y, Cui H, Zhang W, Wu X, Zhao X, Xiao J, Tang M, Wang Y, Zou Y, Qiu L, Tan Z, Lei B, Ma X, Zhang D, Liu Y, Fan M, Li J, Zhang B, Jiang X. Genomic correlation, shared loci, and causal association between obesity, periodontitis and tooth loss. Sci Rep 2025; 15:5155. [PMID: 39934647 DOI: 10.1038/s41598-025-89782-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Accepted: 02/07/2025] [Indexed: 02/13/2025] Open
Abstract
Observational studies have reported an association of obesity with periodontitis and tooth loss, yet findings remain inconsistent. We aim to investigate the genetic link underlying obesity-related traits (BMI [body mass index], WHR [waist-to-hip ratio], WHRadjBMI and childhood BMI), periodontitis and tooth loss. Leveraging summary statistics from large-scale genome-wide association studies, we comprehensively investigated the pair-wise genetic correlation using linkage disequilibrium score regression (LDSC) and SUPERGNOVA, identified shared loci using cross-phenotype association analysis (CPASSOC), and estimated causal association using Mendelian randomization. We identified a significant genetic correlation of obesity with tooth loss, but not with periodontitis. Partitioning the genome into LD-independent regions revealed 10 significantly shared local signals across six regions. Genome-wide cross-trait analysis uncovered 14 shared loci, four of which were colocalized: rs2064044 (PP4 = 0.94), rs6000329 (PP4 = 0.86), rs7134628 (PP4 = 0.86), and rs1286769 (PP4 = 0.90). Notably, rs1286769, identified via CPASSOC and validated through colocalization analysis, is located near RARβ, a gene associated with both BMI and denture use. Mendelian randomization revealed a nominally-significant causal association of obesity with periodontitis (P = 0.045) but a robust causal association with tooth loss represented by number of teeth (BMI: beta = [Formula: see text]0.20, 95%CI = [Formula: see text]0.26 to [Formula: see text]0.14, P = 5.27 × 10-11; WHR: beta = [Formula: see text]0.16, 95%CI = [Formula: see text]0.24 to [Formula: see text]0.08, P = 3.71 × 10-5). Results of CAUSE were consistent with main findings. From a genetic perspective, our work highlights an intrinsic link between obesity, periodontitis and tooth loss, which may add new lines of evidence and provide insights for clinical and public oral health applications.
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Affiliation(s)
- Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Yang Qu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Xuan Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Jinyu Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Lingli Qiu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Zhixin Tan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Bowen Lei
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Xiaofeng Ma
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Di Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Mengyu Fan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China.
- Departments of Cardiology, Neurology, and Oncology, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
- Department of Occupational and Environmental Health, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, China-PUMC C. C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
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9
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Fu L, Liu Q, Cheng H, Zhao X, Xiong J, Mi J. Insights Into Causal Effects of Genetically Proxied Lipids and Lipid-Modifying Drug Targets on Cardiometabolic Diseases. J Am Heart Assoc 2025; 14:e038857. [PMID: 39868518 DOI: 10.1161/jaha.124.038857] [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: 09/13/2024] [Accepted: 12/13/2024] [Indexed: 01/28/2025]
Abstract
BACKGROUND The differential impact of serum lipids and their targets for lipid modification on cardiometabolic disease risk is debated. This study used Mendelian randomization to investigate the causal relationships and underlying mechanisms. METHODS Genetic variants related to lipid profiles and targets for lipid modification were sourced from the Global Lipids Genetics Consortium. Summary data for 10 cardiometabolic diseases were compiled from both discovery and replication data sets. Expression quantitative trait loci data from relevant tissues were employed to evaluate significant lipid-modifying drug targets. Comprehensive analyses including colocalization, mediation, and bioinformatics were conducted to validate the results and investigate potential mediators and mechanisms. RESULTS Significant causal associations were identified between lipids, lipid-modifying drug targets, and various cardiometabolic diseases. Notably, genetic enhancement of LPL (lipoprotein lipase) was linked to reduced risks of myocardial infarction (odds ratio [OR]1, 0.65 [95% CI, 0.57-0.75], P1=2.60×10-9; OR2, 0.59 [95% CI, 0.49-0.72], P2=1.52×10-7), ischemic heart disease (OR1, 0.968 [95% CI, 0.962-0.975], P1=5.50×10-23; OR2, 0.64 [95% CI, 0.55-0.73], P2=1.72×10-10), and coronary heart disease (OR1, 0.980 [95% CI, 0.975-0.985], P1=3.63×10-14; OR2, 0.64 [95% CI, 0.54-0.75], P2=6.62×10-8) across 2 data sets. Moreover, significant Mendelian randomization and strong colocalization associations for the expression of LPL in blood and subcutaneous adipose tissue were linked with myocardial infarction (OR, 0.918 [95% CI, 0.872-0.967], P=1.24×10-3; PP.H4, 0.99) and coronary heart disease (OR, 0.991 [95% CI, 0.983-0.999], P=0.041; PP.H4=0.92). Glucose levels and blood pressure were identified as mediators in the total effect of LPL on cardiometabolic outcomes. CONCLUSIONS The study substantiates the causal role of lipids in specific cardiometabolic diseases, highlighting LPL as a potent drug target. The effects of LPL are suggested to be influenced by changes in glucose and blood pressure, providing insights into its mechanism of action.
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Affiliation(s)
- Liwan Fu
- Center for Non-Communicable Disease Management Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China
| | - Qin Liu
- Department of Ultrasound Children's Hospital of the Capital Institute of Pediatrics Beijing China
| | - Hong Cheng
- Department of Epidemiology Capital Institute of Pediatrics Beijing China
| | - Xiaoyuan Zhao
- Department of Epidemiology Capital Institute of Pediatrics Beijing China
| | - Jingfan Xiong
- Child and Adolescent Chronic Disease Prevention and Control Department Shenzhen Center for Chronic Disease Control Shenzhen China
| | - Jie Mi
- Center for Non-Communicable Disease Management Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China
- Key Laboratory of Major Diseases in Children, Ministry of Education China
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10
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Obeso A, Drouard G, Jelenkovic A, Aaltonen S, Palviainen T, Salvatore JE, Dick DM, Kaprio J, Silventoinen K. Genetic contributions to body mass index over adolescence and its associations with adult weight gain: a 25-year follow-up study of Finnish twins. Int J Obes (Lond) 2025; 49:357-363. [PMID: 39567637 PMCID: PMC11805703 DOI: 10.1038/s41366-024-01684-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 11/05/2024] [Accepted: 11/08/2024] [Indexed: 11/22/2024]
Abstract
INTRODUCTION High body mass index (BMI) in adolescence is a strong predictor of adult obesity. However, the nature of this association is unclear. We investigated how adolescent BMI is associated with adult weight change using longitudinal data from ages 11.5 to 37 years and examined the genetic factors behind these associations. DATA AND METHODS The study cohort consisted of 1400 Finnish twin individuals (40% males) with 494 complete twin pairs who reported their body mass index (BMI) at five ages: 11.5, 14, 17.5, 24, and 37 years. BMI trajectories (defined as BMI changes (i.e., slope) and BMI at baseline age (i.e., intercept)) were calculated in adulthood (from 17.5 to 37 years of age) using linear mixed-effects models. Polygenic Risk Scores of BMI (PRSBMI) and genetic twin models were utilised to analyse the role of genetic factors underlying BMI trajectories and their associations with BMI at 11.5 and 14 years of age. RESULTS Mean BMI increased in adulthood (4.06 kg/m2 in men and 3.39 kg/m2 in women). The BMI changes correlated with BMI at the baseline age of 17.5 years (i.e. intercept) (r = 0.24 in men and r = 0.35 in women) as well as with BMI in adolescence (11.5 and 14 years of age). Genetic factors contributed to the BMI changes during adulthood (correlation with PRSBMI r = 0.25 in men and r = 0.27 in women; heritability estimates 0.63 and 0.64 respectively) as well as to their correlations with BMI at the baseline age (rA = 0.5 in men and 0.54 in women) and BMI during adolescence (at 11.5 and 14 years of age) (rA = 0.63-0.64). CONCLUSION We found that genetic factors play a role in BMI change in adulthood, and part of this genetic component overlaps with the genetics of BMI in adolescence. Genetic predisposition to high BMI in adolescence is also related to adult weight gain.
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Affiliation(s)
- Alvaro Obeso
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country, Bilbao, Spain.
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Gabin Drouard
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aline Jelenkovic
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country, Bilbao, Spain
| | - Sari Aaltonen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jessica E Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland
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11
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Downie CG, Shrestha P, Okello S, Yaser M, Lee HH, Wang Y, Krishnan M, Chen HH, Justice AE, Chittoor G, Josyula NS, Gahagan S, Blanco E, Burrows R, Correa-Burrows P, Albala C, Santos JL, Angel B, Lozoff B, Hartwig FP, Horta B, Brina KR, Isasi CR, Qi Q, Gallo LC, Perreira KM, Thyagarajan B, Daviglus M, Van Horn L, Gonzalez F, Bradfield JP, Hakonarson H, Grant SFA, Below JE, Felix J, Graff M, Divaris K, North KE. Trans-ancestry genome-wide association study of childhood body mass index identifies novel loci and age-specific effects. HGG ADVANCES 2025; 6:100411. [PMID: 39885687 PMCID: PMC11875162 DOI: 10.1016/j.xhgg.2025.100411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 01/25/2025] [Accepted: 01/25/2025] [Indexed: 02/01/2025] Open
Abstract
Over the past 30 years, obesity prevalence has markedly increased globally, including among children. Although genome-wide association studies (GWASs) have identified over 1,000 genetic loci associated with obesity-related traits in adults, the genetic architecture of childhood obesity is less well characterized. Moreover, most childhood obesity GWASs have been restricted to severely obese children, in relatively small sample sizes, and in primarily European-ancestry populations. To identify genetic loci associated with early-childhood body mass index (BMI), we performed GWAS of BMI Z scores in eight ancestrally diverse cohorts: ZOE 2.0 cohort, the Santiago Longitudinal Study (SLS), the Vanderbilt University BioVU biobank, the Geisinger MyCode Health Initiative biobank, Study of Latino (SOL) Youth, Pelotas (Brazil) Birth Cohort, Cameron County Hispanic Cohort (CCHC), and Viva La Familia cohort. We subsequently performed inverse-variance-weighted fixed-effect meta-analysis of these results with previously published GWAS summary statistics of BMI Z scores of children in the Early Growth Genetics (EGG) Consortium and the Norwegian Mother and Child Cohort (MoBa), constituting a final total of 84,804 individuals. We identified 39 genome-wide significant loci associated with childhood BMI, including three putatively novel loci (EFNA5 and DTWD2, RP11-2N5.1 on chromosome 5, and LSM14A on chromosome 19). We also observed a dynamic nature of genetic loci-BMI associations across the life course, with distinct effects across childhood and adulthood, highlighting possible critical periods for early-childhood interventions. These findings strengthen calls for larger population-based studies of children across age strata and across diverse populations.
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Affiliation(s)
- Carolina G Downie
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA.
| | - Poojan Shrestha
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Samson Okello
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA
| | - Mohammad Yaser
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA
| | - Harold H Lee
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA 16802, USA
| | - Yujie Wang
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA
| | - Mohanraj Krishnan
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA; Carolina Population Center, UNC Chapel Hill, Chapel Hill, NC, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | | | - Sheila Gahagan
- Department of Pediatrics, University of San Diego, La Jolla, CA 92093, USA
| | - Estela Blanco
- Centro de Investigación en Sociedad y Salud y Núcleo Milenio de Sociomedicina, Universidad Mayor, Santiago, Chile
| | - Raquel Burrows
- Centro de Investigación en Sociedad y Salud y Núcleo Milenio de Sociomedicina, Universidad Mayor, Santiago, Chile
| | - Paulina Correa-Burrows
- Centro de Investigación en Sociedad y Salud y Núcleo Milenio de Sociomedicina, Universidad Mayor, Santiago, Chile
| | - Cecilia Albala
- Centro de Investigación en Sociedad y Salud y Núcleo Milenio de Sociomedicina, Universidad Mayor, Santiago, Chile
| | - José L Santos
- Department of Nutrition, Diabetes and Metabolism. School of Medicine. Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Bárbara Angel
- Public Nutrition Unit, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Betsy Lozoff
- Department of Pediatrics, Medical School, and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | | | - Bernardo Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Karisa Roxo Brina
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Carmen R Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, Chula Vista, CA 91910, USA
| | - Krista M Perreira
- Department of Social Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Bharat Thyagarajan
- Department of Epidemiology, University of Minnesota Medical Center, Minneapolis, MN 55454, USA
| | - Martha Daviglus
- Department of Preventive Medicine, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Linda Van Horn
- Department of Preventive Medicine, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Franklyn Gonzalez
- Collaborative Studies Coordinating Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Division Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Janine Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mariaelisa Graff
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA
| | - Kimon Divaris
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC 27514, USA.
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12
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Hui D, Dudek S, Kiryluk K, Walunas TL, Kullo IJ, Wei WQ, Tiwari H, Peterson JF, Chung WK, Davis BH, Khan A, Kottyan LC, Limdi NA, Feng Q, Puckelwartz MJ, Weng C, Smith JL, Karlson EW, Jarvik GP, Ritchie MD. Risk factors affecting polygenic score performance across diverse cohorts. eLife 2025; 12:RP88149. [PMID: 39851248 PMCID: PMC11771958 DOI: 10.7554/elife.88149] [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] [Indexed: 01/26/2025] Open
Abstract
Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed the effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N = 491,111) and African (N = 21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best- and worst-performing quintiles for certain covariates. Twenty-eight covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account nonlinear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge genome-wide association studies effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.
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Affiliation(s)
- Daniel Hui
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Scott Dudek
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia UniversityNew YorkUnited States
| | - Theresa L Walunas
- Department of Preventive Medicine, Northwestern University Feinberg School of MedicineChicagoUnited States
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo ClinicRochesterUnited States
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical CenterNashvilleUnited States
| | - Hemant Tiwari
- Department of Pediatrics, University of Alabama at BirminghamBirminghamUnited States
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical CenterNashvilleUnited States
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, Columbia UniversityNew YorkUnited States
| | - Brittney H Davis
- Department of Neurology, School of Medicine, University of Alabama at BirminghamBirminghamUnited States
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia UniversityNew YorkUnited States
| | - Leah C Kottyan
- The Center for Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children's Hospital Medical CenterCincinnatiUnited States
| | - Nita A Limdi
- Department of Neurology, School of Medicine, University of Alabama at BirminghamBirminghamUnited States
| | - Qiping Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical CenterNashvilleUnited States
| | - Megan J Puckelwartz
- Center for Genetic Medicine, Northwestern University Feinberg School of MedicineChicagoUnited States
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia UniversityNew YorkUnited States
| | - Johanna L Smith
- Department of Cardiovascular Medicine, Mayo ClinicRochesterUnited States
| | - Elizabeth W Karlson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical SchoolBostonUnited States
| | | | | | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical CenterSeattleUnited States
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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13
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Trang KB, Pahl MC, Pippin JA, Su C, Littleton SH, Sharma P, Kulkarni NN, Ghanem LR, Terry NA, O'Brien JM, Wagley Y, Hankenson KD, Jermusyk A, Hoskins J, Amundadottir LT, Xu M, Brown K, Anderson S, Yang W, Titchenell P, Seale P, Kaestner KH, Cook L, Levings M, Zemel BS, Chesi A, Wells AD, Grant SFA. 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity. eLife 2025; 13:RP95411. [PMID: 39813287 PMCID: PMC11735026 DOI: 10.7554/elife.95411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2025] Open
Abstract
The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci, we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18, and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.
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Affiliation(s)
- Khanh B Trang
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - James A Pippin
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Chun Su
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Sheridan H Littleton
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Prabhat Sharma
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Nikhil N Kulkarni
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Louis R Ghanem
- Division of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Natalie A Terry
- Division of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Joan M O'Brien
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Penn Medicine Center for Ophthalmic Genetics in Complex DiseasePhiladelphiaUnited States
| | - Yadav Wagley
- Department of Orthopedic Surgery University of Michigan Medical School Ann ArborAnn ArborUnited States
| | - Kurt D Hankenson
- Department of Orthopedic Surgery University of Michigan Medical School Ann ArborAnn ArborUnited States
| | - Ashley Jermusyk
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer InstituteBethesdaUnited States
| | - Jason Hoskins
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer InstituteBethesdaUnited States
| | - Laufey T Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer InstituteBethesdaUnited States
| | - Mai Xu
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer InstituteBethesdaUnited States
| | - Kevin Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer InstituteBethesdaUnited States
| | - Stewart Anderson
- Department of Child and Adolescent Psychiatry, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Psychiatry, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Wenli Yang
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Paul Titchenell
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Physiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Patrick Seale
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Klaus H Kaestner
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Laura Cook
- Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and ImmunityMelbourneAustralia
- Department of Critical Care, Melbourne Medical School, University of MelbourneMelbourneAustralia
- Division of Infectious Diseases, Department of Medicine, University of British ColumbiaVancouverCanada
| | - Megan Levings
- Department of Surgery, University of British ColumbiaVancouverCanada
- BC Children's Hospital Research InstituteVancouverCanada
- School of Biomedical Engineering, University of British ColumbiaVancouverCanada
| | - Babette S Zemel
- Division of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pediatrics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Immunology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Struan FA Grant
- Center for Spatial and Functional Genomics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Pediatrics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Division Endocrinology and Diabetes, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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Jung EM, Raduski AR, Mills LJ, Spector LG. A phenome-wide association study of polygenic scores for selected childhood cancer: Results from the UK Biobank. HGG ADVANCES 2025; 6:100356. [PMID: 39340156 PMCID: PMC11538869 DOI: 10.1016/j.xhgg.2024.100356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 09/24/2024] [Accepted: 09/04/2024] [Indexed: 09/30/2024] Open
Abstract
The aim of this study was to scan phenotypes in adulthood associated with polygenic risk scores (PRS) for childhood cancers with well-articulated genetic architectures-acute lymphoblastic leukemia (ALL), Ewing sarcoma, and neuroblastoma-to examine genetic pleiotropy. Furthermore, we aimed to determine which SNPs could drive associations. Per-SNP summary statistics were extracted for PRS calculation. Participants with white British ancestry were exclusively included for analyses. SNPs were queried from the UK Biobank genotype imputation data. Records from the cancer registry, death registry, and inpatient diagnoses were abstracted for phenome-wide scans. Firth logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) alongside corresponding p values, adjusting for age at recruitment and sex. A total of 244,332 unrelated white British participants were included. We observed a significant association between ALL-PRS and ALL (OR: 1.20e+24, 95% CI: 9.08e+14-1.60e+33). In addition, we observed a significant association between high-risk neuroblastoma PRS and nonrheumatic aortic valve disorders (OR: 43.9, 95% CI: 7.42-260). There were no significant phenotype associations with Ewing sarcoma and neuroblastoma PRS. Regarding individual SNPs, rs17607816 increased the risk of ALL (OR: 6.40, 95% CI: 3.26-12.57). For high-risk neuroblastoma, rs80059929 elevated the risk of atrioventricular block (OR: 3.04, 95% CI: 1.85-4.99). Our findings suggest that individuals with genetic susceptibility to ALL may face a lifelong risk for developing ALL, along with a genetic pleiotropic association between high-risk neuroblastoma and circulatory diseases.
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Affiliation(s)
- Eun Mi Jung
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Andrew R Raduski
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Lauren J Mills
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Logan G Spector
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
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Wang H, Min J, Zhong L, Zhang J, Ye L, Chen C. Life-course obesity and heart failure: a two-sample Mendelian randomization study. Intern Emerg Med 2025; 20:171-180. [PMID: 39316280 DOI: 10.1007/s11739-024-03772-8] [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: 07/12/2024] [Accepted: 09/08/2024] [Indexed: 09/25/2024]
Abstract
Heart failure is a multifaceted clinical syndrome, with obesity identified as a significant modifiable risk factor. This study employed a two-sample Mendelian randomization (MR) design, incorporating obesity data across life stages, to elucidate the causal link between obesity and heart failure. Data on heart failure from the 2023 Finngen database and genetic predictors of obesity from the IEU OpenGWAS project were analyzed using the IVW method, MR-Egger regression, weighted median, simple mode, weighted mode, and scatter plots. Heterogeneity was assessed with Cochran's Q test, and horizontal pleiotropy with MR-Egger intercept test. Sensitivity to single-nucleotide polymorphisms (SNPs) was tested via leave-one-out analysis, and funnel plots were utilized for visual inspection of horizontal pleiotropy. Statistical powers were also calculated. The MR analysis findings indicate a significant relationship between birth weight and the likelihood of developing heart failure (Odds Ratio [OR] 1.134, 95% Confidence Interval [CI] 1.033-1.245, P = 0.008). In addition, a heightened childhood BMI was found to be a significant predictor of heart failure risk (OR 1.307, 95% CI 1.144-1.494, P = 8.51E-05), as was childhood obesity (OR 1.123, 95% CI 1.074-1.173, P = 2.37E-07). Furthermore, adult BMI sex-combined exhibited a strong correlation with the risk of heart failure (OR 2.365, 95% CI 2.128-2.629, P = 1.91E-57). Sensitivity analyses provided further support for the reliability of these results, with no significant indication of horizontal pleiotropy observed. This study shows that obesity, including childhood obesity, is linked to a higher risk of heart failure. These findings highlight the urgent need for early weight management interventions in public health and clinical settings to reduce heart failure rates.
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Affiliation(s)
- Haili Wang
- Department of Obstetrics and Gynecology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China
| | - Jie Min
- Department of Intensive Care Unit, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China
| | - Lei Zhong
- Department of Intensive Care Unit, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China
| | - Jinyu Zhang
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China
| | - Lili Ye
- Department of Intensive Care Unit, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China
| | - Chunrong Chen
- Department of Pediatrics, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, China.
- Fifth School of Clinical Medicine of Zhejiang, Huzhou Central Hospital, Chinese Medical University, Huzhou, 313000, China.
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16
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Chen J, Wang Y, Jiang R, Qu Y, Li Y, Zhang Y. Application of Mendelian randomized research method in oncology research: bibliometric analysis. Front Oncol 2024; 14:1424812. [PMID: 39741977 PMCID: PMC11685051 DOI: 10.3389/fonc.2024.1424812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Accepted: 11/26/2024] [Indexed: 01/03/2025] Open
Abstract
Background Cancer has always been a difficult problem in the medical field, and with the gradual deepening of Genome-wide association studies (GWAS), Mendelian randomization methods have been increasingly used to study cancer pathogenesis. In this study, we examine the literature on Mendelian cancer, summarize the status of the research, and analyze the development trends in the field. Methods Publications on "Mendelian Randomization - Cancer" were retrieved and downloaded from the Web of Science Core Collection database. CiteSpace 6.2.R4, VOSviewer 1.6.19, Scimago Graphica 1.0.38, Bibliometrix R-package, and a bibliometric online analysis platform were used for data analysis and visualization. An in-depth analysis of country or region, authors, journals, keywords, and references was performed to provide insights into the content related to the field. Results A total of 836 articles were included in the analysis; 643 authors from 72 countries had published articles related to the field. China and Harvard University (among countries and institutions, respectively) had the highest number of articles. Martin, Richard M and Smith, George Davey were the largest contributors. A total of 27 cancers have been studied, with breast, colorectal, and liver cancers being the most studied. Conclusion This study is the first to use bibliometric methods to visualize the application of Mendelian randomization analysis in the field of cancer, revealing research trends and research frontiers in the field. This information will provide a strong reference for cancer researchers and epidemiologic researchers.
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Affiliation(s)
- Jiahao Chen
- College of Medical Information, Changchun University of Chinese Medicine, Changchun, China
| | - Yunli Wang
- College of Medical Information, Changchun University of Chinese Medicine, Changchun, China
| | - Rongsheng Jiang
- College of Acupuncture and Tuina, Changchun University of Chinese Medicine, Changchun, China
| | - Yawei Qu
- College of Medical Information, Changchun University of Chinese Medicine, Changchun, China
| | - Yan Li
- College of Medical Information, Changchun University of Chinese Medicine, Changchun, China
| | - Yang Zhang
- College of Medical Information, Changchun University of Chinese Medicine, Changchun, China
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17
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Jasper EA, Hellwege JN, Greene CA, Edwards TL, Velez Edwards DR. Genomic insights into gestational weight gain uncover tissue-specific mechanisms and pathways. NPJ WOMEN'S HEALTH 2024; 2:42. [PMID: 39651376 PMCID: PMC11624131 DOI: 10.1038/s44294-024-00035-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Accepted: 09/18/2024] [Indexed: 12/11/2024]
Abstract
Gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and offspring. The Early Growth Genetics Consortium previously identified genetic variants contributing to GWG from fetal and maternal genomes. However, their biologic mechanisms and tissue-specificity are unknown. We evaluated the association between genetically predicted gene expression in relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) tissues from GTEx (v7) and fetal (placenta) tissue and early, late, and total GWG using S-PrediXcan. We tested for pathway enrichment using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After Bonferroni correction, we found no associations between maternal or fetal gene expression and GWG. Among nominally significant (P < 0.05) maternal genes, there was enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, that varied across pregnancy. These results indicate the likely influence of diverse pathways, varying by tissue and weeks of gestation, on GWG.
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Affiliation(s)
- Elizabeth A. Jasper
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN USA
- Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, TN USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN USA
| | - Jacklyn N. Hellwege
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
| | - Catherine A. Greene
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN USA
| | - Todd L. Edwards
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
| | - Digna R. Velez Edwards
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN USA
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18
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Yun SY, Yun JY, Lim C, Oh H, Son E, Shin K, Kim K, Ko DS, Kim YH. Exploring the complex link between obesity and intelligence: Evidence from systematic review, updated meta-analysis, and Mendelian randomization. Obes Rev 2024; 25:e13827. [PMID: 39228076 DOI: 10.1111/obr.13827] [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: 04/05/2024] [Revised: 07/16/2024] [Accepted: 08/18/2024] [Indexed: 09/05/2024]
Abstract
Obesity is a major public health concern associated with a higher risk of various comorbidities. Some studies have explored the impact of obesity on cognitive function and, conversely, how lower intelligence might increase the risk of later obesity. The aim of this study is to analyze a complex relationship between body mass index (BMI) and intelligence quotient (IQ), employing a comprehensive approach, including a systematic review, meta-analysis, and Mendelian randomization (MR). We extracted the data from Medline and Embase to identify relevant studies published since June 22, 2009. MR analysis relied on genetic databases such as the Genome-Wide Association Study (GWAS) and the Genetic Investigation of Anthropometric Traits (GIANT) to explore potential causal relationships. The systematic review and meta-analysis encompassed 34 and 17 studies, respectively. They revealed a substantial correlation between obesity and reduced IQ, particularly notable among school-age children (mean difference -5.26; 95% CI: -7.44 to -3.09). Notably, within the IQ subgroup, verbal IQ also exhibited a significant association with a mean difference of -7.73 (95% CI: -14.70 to -0.77) in school-age children. In contrast, the MR did not unveil a significant causal relationship between BMI and IQ, both in childhood and adulthood. This comprehensive analysis underscores a significant correlation between BMI and IQ, particularly in school-age children. However, the MR analysis implies a potentially weaker causal relationship. Future large-scale cohort studies should address potential confounding factors to provide further insights into the BMI-IQ relationship.
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Affiliation(s)
- Seo Young Yun
- School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Joo Young Yun
- School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Chaeseong Lim
- Occupational and Environmental Medicine, Kosin University Gospel Hospital, Busan, Republic of Korea
| | - Hyeoncheol Oh
- Occupational and Environmental Medicine, Kosin University Gospel Hospital, Busan, Republic of Korea
| | - Eunjeong Son
- Division of Respiratory and Allergy, Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Kihyuk Shin
- Department of Dermatology, College of Medicine, Pusan National University, Busan, Republic of Korea
- Department of Dermatology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Kihun Kim
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Dai Sik Ko
- Division of Vascular Surgery, Department of General Surgery, Gachon University College of Medicine, Gil Medical Center, Incheon, Republic of Korea
| | - Yun Hak Kim
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
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19
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Peng L, Shen J, Li L, Liu J, Jiang X, Zhang G, Li Y. Birthweight influences liver structure, function and disease risk: Evidence of a causal association. Diabetes Obes Metab 2024; 26:4976-4988. [PMID: 39228281 DOI: 10.1111/dom.15910] [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: 06/11/2024] [Revised: 08/16/2024] [Accepted: 08/16/2024] [Indexed: 09/05/2024]
Abstract
AIM Low birthweight is an issue during pregnancy associated with an increased risk of developing liver disease later in life. Previous Mendelian randomisation (MR) studies which explored this issue have not isolated the direct impact of the foetus on birthweight. In the present study, MR was used to assess whether direct foetal effects on birthweight were causally associated with liver structure, function and disease risk independent of intrauterine effects. MATERIALS AND METHODS We extracted single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) about direct foetal-affected birthweight (321 223 cases) to conduct univariable and multivariable MR analyses to explore the relationships between birthweight and 4 liver structure measures, 9 liver function measures and 18 liver diseases. A two-step MR analysis was used to further assess and quantify the mediating effects of the mediators. RESULTS When isolating direct foetal effects, genetically predicted lower birthweight was associated with a higher risk of non-alcoholic fatty liver disease (NAFLD) (odds ratios [OR], 95% confidence interval [CI]: 1.61, 1.29-2.02, p < 0.001), higher magnetic resonance imaging [MRI] proton density fat fraction (PDFF) and higher serum gamma glutamyltransferase (GGT). Two-step MR identified two candidate mediators that partially mediate the direct foetal effect of lower birthweight on NAFLD, including fasting insulin (proportion mediated: 22.29%) and triglycerides (6.50%). CONCLUSIONS Our MR analysis reveals a direct causal association between lower birthweight and liver MRI PDFF, as well as the development of NAFLD, which persisted even after accounting for the potential influence of maternal factors. In addition, we identified fasting insulin and triglycerides as mediators linking birthweight and hepatic outcomes, providing insights for early clinical interventions.
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Affiliation(s)
- Lei Peng
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiajia Shen
- Department of General Surgery, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Lurong Li
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiahao Liu
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xingzhou Jiang
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guoxin Zhang
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuanyuan Li
- Department of Endocrinology, Children's Hospital of Nanjing Medical University, Nanjing, China
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20
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Olwi DI, Kaisinger LR, Kentistou KA, Vaudel M, Stankovic S, Njølstad PR, Johansson S, Perry JRB, Day FR, Ong KK. Likely causal effects of insulin resistance and IGF-1 bioaction on childhood and adult adiposity: a Mendelian randomization study. Int J Obes (Lond) 2024; 48:1650-1655. [PMID: 39174749 PMCID: PMC11502485 DOI: 10.1038/s41366-024-01605-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 07/23/2024] [Accepted: 08/06/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND Circulating insulin and insulin-like growth factor-1 (IGF-1) concentrations are positively correlated with adiposity. However, the causal effects of insulin and IGF-1 on adiposity are unclear. METHODS We performed two-sample Mendelian randomization analyses to estimate the likely causal effects of fasting insulin and IGF-1 on relative childhood adiposity and adult body mass index (BMI). To improve accuracy and biological interpretation, we applied Steiger filtering (to avoid reverse causality) and 'biological effect' filtering of fasting insulin and IGF-1 associated variants. RESULTS Fasting insulin-increasing alleles (35 variants also associated with higher fasting glucose, indicative of insulin resistance) were associated with lower relative childhood adiposity (P = 3.8 × 10-3) and lower adult BMI (P = 1.4 × 10-5). IGF-1-increasing alleles also associated with taller childhood height (351 variants indicative of greater IGF-1 bioaction) showed no association with relative childhood adiposity (P = 0.077) or adult BMI (P = 0.562). Conversely, IGF-1-increasing alleles also associated with shorter childhood height (306 variants indicative of IGF-1 resistance) were associated with lower relative childhood adiposity (P = 6.7 × 10-3), but effects on adult BMI were inconclusive. CONCLUSIONS Genetic causal modelling indicates negative effects of insulin resistance on childhood and adult adiposity, and negative effects of IGF-1 resistance on childhood adiposity. Our findings demonstrate the need to distinguish between bioaction and resistance when modelling variants associated with biomarker concentrations.
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Affiliation(s)
- Duaa I Olwi
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
- King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia
| | - Lena R Kaisinger
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Katherine A Kentistou
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, NO-0213, Oslo, Norway
| | - Stasa Stankovic
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Pediatrics and Adolescents, Haukeland University Hospital, NO-5021, Bergen, Norway
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, NO-5021, Bergen, Norway
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Metabolic Research Laboratory, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
- Department of Paediatrics, University of Cambridge, Cambridge, UK.
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21
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Zhang J, Chen ZK, Triatin RD, Snieder H, Thio CHL, Hartman CA. Mediating pathways between attention deficit hyperactivity disorder and type 2 diabetes mellitus: evidence from a two-step and multivariable Mendelian randomization study. Epidemiol Psychiatr Sci 2024; 33:e54. [PMID: 39465621 PMCID: PMC11561680 DOI: 10.1017/s2045796024000593] [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: 11/22/2023] [Revised: 05/20/2024] [Accepted: 07/14/2024] [Indexed: 10/29/2024] Open
Abstract
AIMS Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways. METHODS We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators. RESULTS Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: -1.99%, 110.38%) of the ADHD-T2D association. CONCLUSIONS These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.
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Affiliation(s)
- J Zhang
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Division of Communicable Disease Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Z K Chen
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - R D Triatin
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Faculty of Medicine, Department of Biomedical Sciences, Universitas Padjadjaran, Bandung, Indonesia
| | - H Snieder
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - C H L Thio
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, University of Utrecht, Utrecht, The Netherlands
| | - C A Hartman
- Interdisciplinary Centre Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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22
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Xiao P, Li C, Wu J, Dai J. Unravel the distinct effects of adiposity at different life stages on COVID-19 susceptibility and severity: A life-course Mendelian randomization study. J Med Virol 2024; 96:e29943. [PMID: 39360640 DOI: 10.1002/jmv.29943] [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: 07/29/2024] [Revised: 09/09/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024]
Abstract
Childhood obesity is widely recognized as a risk factor for numerous health conditions, particularly cardiovascular disease. However, it remains unclear whether childhood adiposity directly affects the risk of COVID-19 in later life. We aimed to investigate the causal effects of early life adiposity on COVID-19 susceptibility and severity. We used genetic instruments from large-scale genome-wide association studies to examine the relationships between birth weight, childhood and adulthood adiposity indicators (including body mass index [BMI], obesity, and body size), and COVID-19 outcomes. Univariable and multivariable Mendelian randomization (MR) analyses were used to obtain the causal estimates. Univariable MR analyses found that childhood BMI and obesity were positively associated with COVID-19 risk and severity in adulthood, however, the significant associations were attenuated to null after further adjusting for adulthood adiposity indicators in multivariable MR analyses. In contrast, our analysis revealed strong evidence of a genetically predicted effect of childhood obesity on COVID-19 hospitalization (OR 1.08, 95% CI: 1.01-1.15, p = 2.12E-2), which remained robust even after adjusting for adulthood obesity and potential lifestyle confounders. Our results highlight the importance of promoting healthy weight management throughout life to reduce the risk of COVID-19.
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Affiliation(s)
- Pei Xiao
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Chi Li
- Department of AIDS/STD Control and Prevention, Shijingshan District Center for Disease Control and Prevention, Beijing, China
| | - Jinyi Wu
- Department of Public Health, Wuhan Fourth Hospital, Wuhan, China
- School of public health, Fudan university, Shanghai, China
| | - Jiayuan Dai
- Department of Rare Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
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23
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He D, Cheng S, Wei W, Zhao Y, Cai Q, Chu X, Shi S, Zhang N, Qin X, Liu H, Jia Y, Cheng B, Wen Y, Zhang F. Body shape from birth to adulthood is associated with skeletal development: A Mendelian randomization study. Bone 2024; 187:117191. [PMID: 38969278 DOI: 10.1016/j.bone.2024.117191] [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: 01/25/2024] [Revised: 05/21/2024] [Accepted: 07/01/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Observational studies have shown that childhood obesity is associated with adult bone health but yield inconsistent results. We aimed to explore the potential causal association between body shape and skeletal development. METHODS We used two-sample Mendelian randomization (MR) to estimate causal relationships between body shape from birth to adulthood and skeletal phenotypes, with exposures including placental weight, birth weight, childhood obesity, BMI, lean mass, fat mass, waist circumference, and hip circumference. Independent genetic instruments associated with the exposures at the genome-wide significance level (P < 5 × 10-8) were selected from corresponding large-scale genome-wide association studies. The inverse-variance weighted analysis was chosen as the primary method, and complementary MR analyses included the weighted median, MR-Egger, weighted mode, and simple mode. RESULTS The MR analysis shows strong evidence that childhood (β = -1.29 × 10-3, P = 8.61 × 10-5) and adulthood BMI (β = -1.28 × 10-3, P = 1.45 × 10-10) were associated with humerus length. Tibiofemoral angle was negatively associated with childhood BMI (β = -3.60 × 10-1, P = 3.00 × 10-5) and adolescent BMI (β = -3.62 × 10-1, P = 2.68 × 10-3). In addition, genetically predicted levels of appendicular lean mass (β = 1.16 × 10-3, P = 1.49 × 10-13), whole body fat mass (β = 1.66 × 10-3, P = 1.35 × 10-9), waist circumference (β = 1.72 × 10-3, P = 6.93 × 10-8) and hip circumference (β =1.28 × 10-3, P = 4.34 × 10-6) were all associated with tibia length. However, we found no causal association between placental weight, birth weight and bone length/width. CONCLUSIONS This large-scale MR analysis explores changes in growth patterns in the length/width of major bone sites, highlighting the important role of childhood body shape in bone development and providing insights into factors that may drive bone maturation.
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Affiliation(s)
- Dan He
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Wenming Wei
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yijing Zhao
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Qingqing Cai
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoge Chu
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Sirong Shi
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Na Zhang
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoyue Qin
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huan Liu
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
| | - Feng Zhang
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
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24
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Zhou B, Zhu L, Du X, Meng H. Early-life body mass index and the risk of six cardiovascular diseases: A Mendelian Randomization study. Pediatr Obes 2024; 19:e13157. [PMID: 39135386 DOI: 10.1111/ijpo.13157] [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: 11/01/2023] [Revised: 07/04/2024] [Accepted: 07/22/2024] [Indexed: 11/21/2024]
Abstract
BACKGROUND Observational studies consistently indicate an association between early-life body mass index (BMI) and several cardiovascular diseases (CVDs). However, the causal relationship remains uncertain. The primary objective of this study was to assess the causal relationship between early-life BMI and six types of CVDs using the Mendelian Randomization (MR) approach. METHODS The dataset for this study was derived from large-scale, summary-level Genome-Wide Association Studies. Specifically, the following datasets we used, early-life BMI (n = 61 111, age = 2-10), heart failure (HF) dataset (n = 977 323), atrial fibrillation (AF) dataset (n = 1 030 836), coronary artery disease (CAD) dataset (n = 184 305), peripheral artery disease (PAD) dataset (n = 243 060), deep venous thrombosis (DVT) dataset (n = 1 500 861) and myocardial infarction (MI) dataset (n = 638 000). Multiple MR methods were utilized to evaluate the causal relationship between exposure and outcomes, accompanied by sensitivity analysis. RESULTS Early-life BMI positively correlates with the risk of developing the six distinct CVDs included in this study. Specifically, elevated BMI during childhood is associated with a 31.9% risk for HF (Odds ratio [OR] = 1.319, 95% CI [1.160 to 1.499], p = 2.33 × 10-5), an 18.3% risk for AF (R = 1.183, 95% CI [1.088 to 1.287], p = 8.22 × 10-5), an 14.8% risk for CAD (OR = 1.148, 95% CI [1.028 to 1.283], p = 1.47 × 10-2), a 40.5% risk for PAD (OR = 1.405, 95% CI [1.233 to 1.600], p = 3.10 × 10-7) and 12.0% risk for MI (OR = 1.120, 95% CI [1.017 to 1.234], p = 2.18 × 10-2). Interestingly, the risk for deep venous thrombosis only increased by 0.5% (OR = 1.005, 95% CI [1.001 to 1.008], p = 2.13 × 10-3). CONCLUSION Genetically inferred early-life BMI is significantly associated with six distinct CVDs. This indicates that elevated early-life BMI is a significant risk factor for multiple cardiovascular disorders.
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Affiliation(s)
- Bojun Zhou
- Department of Exercise Physiology, Beijing Sport University, Beijing, China
- Department of General Surgery and Obesity and Metabolic Disease Center, China-Japan Friendship Hospital, Beijing, China
| | - Lianghao Zhu
- Key Laboratory of Competitive Sport Psychological and Psychological Regulation, Tianjin University of Sport, Tianjin, China
| | - Xia Du
- Qinghai Institute of Sports Science Limited Company, Xining, China
| | - Hua Meng
- Department of General Surgery and Obesity and Metabolic Disease Center, China-Japan Friendship Hospital, Beijing, China
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25
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Cai J, Zhao L, Li N, Xiao Z, Huang G. Mendelian randomization analysis separated the independent impact of childhood obesity and adult obesity on socioeconomic status, psychological status, and substance use. Heliyon 2024; 10:e36835. [PMID: 39263080 PMCID: PMC11388778 DOI: 10.1016/j.heliyon.2024.e36835] [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: 12/25/2023] [Revised: 08/06/2024] [Accepted: 08/22/2024] [Indexed: 09/13/2024] Open
Abstract
Background Obesity is linked to a variety of psychosocial and behavioral outcomes but the causalities remain unclear yet. Determining the causalities and distinguishing between the separate effects of childhood and adult obesity is critical to develop more targeted strategies to prevent adverse outcomes. Methods With single nucleotide polymorphisms (SNPs) used as genetic variables, we employed univariable Mendelian randomization (UVMR) to explore the causalities between childhood and adult body mass index (BMI) and socioeconomic status, psychological status, and substance use. Genetic data for childhood and adult BMI came respectively from 47,541 children aged 10 years and 339,224 adult participants. The outcome data were obtained from corresponding consortia. The direct impact of childhood BMI and adult BMI was then examined using a multivariable MR (MVMR). Results UVMR found that higher childhood BMI was linked causally to lower household income (β = -0.06, 95 % CI = -0.08 ∼ -0.03, P = 4.86 × 10-5), decreased subjective well-being (β = -0.07, 95 % CI = -0.12 ∼ -0.03, P = 1.74 × 10-3), and an increased tendency of smoking regularly (OR = 1.12, 95 % CI = 1.04-1.20, P = 1.52 × 10-3). Similar results were observed in adult BMI. MVMR further revealed that after adjusting with adult BMI, childhood BMI remained an isolated impact on household income. The impacts of adult BMI on the outcomes were diminished when adjusting with childhood BMI. Conclusion The findings indicate the impacts of childhood obesity on subjective well-being and smoking initiation are a result of higher BMI sustaining into adulthood, whereas the effect on household income is attributed to a lasting impact of obesity in early life. The results would help facilitate more targeted strategies for obesity management to prevent adverse outcomes.
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Affiliation(s)
- Jiahao Cai
- School of Pediatrics, Guangzhou Medical University, China
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Lei Zhao
- The Third Clinical Institute, Guangzhou Medical University, Guangzhou, China
| | - Nanfang Li
- Graduate School of Human Science, Osaka University, Osaka, Japan
| | - Zijin Xiao
- Guangzhou Medical University, Guangzhou, China
| | - Guiwu Huang
- Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, New Haven, CT, USA
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26
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Xiao P, Li C, Mi J, Wu J. Evaluating the distinct effects of body mass index at childhood and adulthood on adult major psychiatric disorders. SCIENCE ADVANCES 2024; 10:eadq2452. [PMID: 39270013 PMCID: PMC11397431 DOI: 10.1126/sciadv.adq2452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Accepted: 08/06/2024] [Indexed: 09/15/2024]
Abstract
Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.
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Affiliation(s)
- Pei Xiao
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Chi Li
- Department of AIDS/STD Control and Prevention, Shijingshan District Center for Disease Control and Prevention, Beijing 100043, China
| | - Jie Mi
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Jinyi Wu
- Department of Public Health, Wuhan Fourth Hospital, Wuhan 430000, China
- School of Public Health, Fudan University, Shanghai 210000, China
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27
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M JN, Bharadwaj D. The complex web of obesity: from genetics to precision medicine. Expert Rev Endocrinol Metab 2024; 19:403-418. [PMID: 38869356 DOI: 10.1080/17446651.2024.2365785] [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: 11/06/2023] [Accepted: 06/05/2024] [Indexed: 06/14/2024]
Abstract
INTRODUCTION Obesity is a growing public health concern affecting both children and adults. Since it involves both genetic and environmental components, the management of obesity requires both, an understanding of the underlying genetics and changes in lifestyle. The knowledge of obesity genetics will enable the possibility of precision medicine in anti-obesity medications. AREAS COVERED Here, we explore health complications and the prevalence of obesity. We discuss disruptions in energy balance as a symptom of obesity, examining evolutionary theories, its multi-factorial origins, and heritability. Additionally, we discuss monogenic and polygenic obesity, the converging biological pathways, potential pharmacogenomics applications, and existing anti-obesity medications - specifically focussing on the leptin-melanocortin and incretin pathways. Comparisons between childhood and adult obesity genetics are made, along with insights into structural variants, epigenetic changes, and environmental influences on epigenetic signatures. EXPERT OPINION With recent advancements in anti-obesity drugs, genetic studies pinpoint new targets and allow for repurposing existing drugs. This creates opportunities for genotype-informed treatment options. Also, lifestyle interventions can help in the prevention and treatment of obesity by altering the epigenetic signatures. The comparison of genetic architecture in adults and children revealed a significant overlap. However, more robust studies with diverse ethnic representation is required in childhood obesity.
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Affiliation(s)
- Janaki Nair M
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
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28
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Jensen SK, Pedersen CET, Fischer-Rasmussen K, Melgaard ME, Brustad N, Kyvsgaard JN, Vahman N, Schoos AMM, Stokholm J, Chawes B, Eliasen A, Bønnelykke K. Genetic predisposition to high BMI increases risk of early life respiratory infections and episodes of severe wheeze and asthma. Eur Respir J 2024; 64:2400169. [PMID: 38811044 DOI: 10.1183/13993003.00169-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/20/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND High body mass index (BMI) is an established risk factor for asthma, but the underlying mechanisms remain unclear. OBJECTIVE To increase understanding of the BMI-asthma relationship by studying the association between genetic predisposition to higher BMI and asthma, infections and other asthma traits during childhood. METHODS Data were obtained from the two ongoing Copenhagen Prospective Studies on Asthma in Childhood (COPSAC) mother-child cohorts. Polygenic risk scores for adult BMI were calculated for each child. Replication was done in the large-scale register-based Integrative Psychiatric Research (iPSYCH) cohort using data on hospitalisation for asthma and infections. RESULTS In the COPSAC cohorts (n=974), the adult BMI polygenic risk score was significantly associated with lower respiratory tract infections (incidence rate ratio (IRR) 1.20, 95% CI 1.08-1.33, false discovery rate p-value (pFDR)=0.005) at age 0-3 years and episodes of severe wheeze (IRR 1.30, 95% CI 1.06-1.60, pFDR=0.04) at age 0-6 years. Lower respiratory tract infections partly mediated the association between the adult BMI polygenic risk score and severe wheeze (proportion mediated: 0.59, 95% CI 0.28-2.24, p-value associated with the average causal mediation effect (pACME)=2e-16). In contrast, these associations were not mediated through the child's current BMI and the polygenic risk score was not associated with an asthma diagnosis or reduced lung function up to age 18 years. The associations were replicated in iPSYCH (n=114 283), where the adult BMI polygenic risk score significantly increased the risk of hospitalisations for lower respiratory tract infections and wheeze or asthma throughout childhood to age 18 years. CONCLUSION Children with genetic predisposition to higher BMI had increased risk of lower respiratory tract infections and severe wheeze, independent of the child's current BMI. These results shed further light on the complex relationship between body mass BMI and asthma.
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Affiliation(s)
- Signe Kjeldgaard Jensen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Casper-Emil Tingskov Pedersen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Kasper Fischer-Rasmussen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Mathias Elsner Melgaard
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Nicklas Brustad
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Julie Nyholm Kyvsgaard
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
| | - Nilo Vahman
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Ann-Marie Malby Schoos
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jakob Stokholm
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
- Section of Microbiology and Fermentation, Department of Food Science, University of Copenhagen, Copenhagen, Denmark
| | - Bo Chawes
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anders Eliasen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Shared senior author
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Shared senior author
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Ma X, Chang L, Li S, Gu Y, Wan J, Sang H, Ding L, Liu M, He Q. Genetic associations of birthweight, childhood, and adult BMI with metabolic dysfunction-associated steatotic liver disease: a Mendelian randomization. BMC Gastroenterol 2024; 24:291. [PMID: 39198755 PMCID: PMC11351507 DOI: 10.1186/s12876-024-03383-9] [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: 03/24/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024] Open
Abstract
PURPOSE The causal relationship between life course adiposity with metabolic dysfunction-associated steatotic liver disease (MASLD) is ambiguous. We aimed to investigate whether there is an independent genetic causal relationship between body size at various life course and MASLD. METHODS We performed univariable and multivariable Mendelian randomization (MR) to estimate the causal effect of body size at different life stages on MASLD (i.e., defined by the clinical comprehensive diagnosis from the electronic health record [HER] codes [ICD9/ICD10] or diagnostic phrases), including birthweight, childhood body mass index (BMI), adult BMI, waist circumference (WC), waist-to-hip ratio (WHR), body fat percentage (BFP). RESULTS In univariate analyses, higher genetically predicted lower birthweight (ORIVW = 0.61, 95%CI, 0.52 to 0.74), Childhood BMI ( ORIVW = 1.37, 95%CI, 1.12 to 1.64), and adult BMI (ORIVW = 1.41, 95%CI, 1.27 to 1.57) was significantly associated with subsequent risk of MASLD after Bonferroni correction. The MVMR analysis demonstrated compelling proof that birthweight and adult BMI had a direct causal relationship with MASLD. However, after adjusting for birthweight and adult BMI, the direct causal relationship between childhood BMI and MASLD disappeared. CONCLUSION For the first time, this MR elucidated new evidence for the effect of life course adiposity on MASLD risk, providing lower birthweight and duration of obesity are independent risk factors for MASLD. Our findings indicated that weight management during distinct time periods plays a significant role in the prevention and treatment of MASLD.
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Affiliation(s)
- Xiaohui Ma
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Lina Chang
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Shuo Li
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Yian Gu
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Jieying Wan
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Hequn Sang
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Li Ding
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
| | - Ming Liu
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
| | - Qing He
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
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30
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Trang KB, Pahl MC, Pippin JA, Su C, Littleton SH, Sharma P, Kulkarni NN, Ghanem LR, Terry NA, O’Brien JM, Wagley Y, Hankenson KD, Jermusyk A, Hoskins JW, Amundadottir LT, Xu M, Brown KM, Anderson SA, Yang W, Titchenell PM, Seale P, Cook L, Levings MK, Zemel BS, Chesi A, Wells AD, Grant SF. 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294092. [PMID: 37693606 PMCID: PMC10491377 DOI: 10.1101/2023.08.30.23294092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.
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Affiliation(s)
- Khanh B. Trang
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Chun Su
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sheridan H. Littleton
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Prabhat Sharma
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nikhil N. Kulkarni
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Louis R. Ghanem
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
| | - Natalie A. Terry
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
| | - Joan M. O’Brien
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Disease
| | - Yadav Wagley
- Department of Orthopedic Surgery University of Michigan Medical School Ann Arbor, MI, USA
| | - Kurt D. Hankenson
- Department of Orthopedic Surgery University of Michigan Medical School Ann Arbor, MI, USA
| | - Ashley Jermusyk
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jason W. Hoskins
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Laufey T. Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mai Xu
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kevin M Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stewart A. Anderson
- Department of Child and Adolescent Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wenli Yang
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul M. Titchenell
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick Seale
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura Cook
- Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Megan K. Levings
- Department of Surgery, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Babette S. Zemel
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division Endocrinology and Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Hu X, Cai M, Xiao J, Wan X, Wang Z, Zhao H, Yang C. Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics. Am J Hum Genet 2024; 111:1717-1735. [PMID: 39059387 PMCID: PMC11339627 DOI: 10.1016/j.ajhg.2024.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 06/26/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.
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Affiliation(s)
- Xianghong Hu
- School of Mathematical Sciences, Institute of Statistical Sciences, Shenzhen University, Shenzhen 518060, China; Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Mingxuan Cai
- Department of Biostatistics, City University of Hong Kong, Hong Kong, China
| | - Jiashun Xiao
- Shenzhen Research Institute of Big Data, Shenzhen 518172, China
| | - Xiaomeng Wan
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Zhiwei Wang
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.
| | - Can Yang
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China; Big Data Bio-Intelligence Lab, The Hong Kong University of Science and Technology, Hong Kong SAR, China.
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Xiong Y, Tang Y, Zhou J, Tian Y, Chen F, Li G, Huang H, Huang H, Zhou L. Childhood Adiposity and Risk of Major Clinical Heart Diseases in Adulthood: A Mendelian Randomization Study. J Am Heart Assoc 2024; 13:e035365. [PMID: 39085751 PMCID: PMC11964076 DOI: 10.1161/jaha.124.035365] [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: 03/05/2024] [Accepted: 07/01/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND The causal relationship between childhood adiposity and adult risk of heart diseases has not been clearly demonstrated. This study aims to ascertain whether genetically predicted childhood body mass index (BMI) and childhood obesity are causally associated with adult coronary heart disease, myocardial infarction, heart failure, atrial fibrillation, hypertrophic cardiomyopathy, and pulmonary heart disease. METHODS AND RESULTS To investigate the causative relationships and underlying mechanisms between childhood adiposity and adult heart diseases, 3 main methods of Mendelian randomization were used: 2-sample Mendelian randomization, multivariable Mendelian randomization with controlling for several cardiometabolic risk variables, and mediation analysis. Every 1-SD rise in genetically predicted childhood body mass index was associated with 24% (odds ratio [OR], 1.24 [95% CI, 1.12-1.37]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), and 27% (OR, 1.27 [95% CI, 1.04-1.49]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. Every 1-unit increase in log-odds in childhood obesity was associated with 11% (OR, 1.11 [95% CI, 1.06-1.16]), 14% (OR, 1.14 [95% CI, 1.04-1.23]), 10% (OR, 1.10 [95% CI, 1.03-1.18]), and 20% (OR, 1.20 [95% CI, 1.08-1.32]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. The link between childhood adiposity and adult heart diseases was found to be mediated by high-density lipoprotein cholesterol, triglyceride, hypertension, and type 2 diabetes. CONCLUSIONS Our findings support the causal relationships between childhood adiposity and risk of adult coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation. Blood lipids, hypertension, and type 2 diabetes are factors that mediate the aforementioned associations.
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Affiliation(s)
- Yan Xiong
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Yijia Tang
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Jie Zhou
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Yang Tian
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Fuli Chen
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Gang Li
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Hui Huang
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Hao Huang
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Long Zhou
- Institute of Cardiovascular Diseases and Department of Cardiology, Sichuan Provincial People’s Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
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Zhou X, Ruan W, Li J, Wang T, Liu H, Zhang G. No causal associations of genetically predicted birth weight and life course BMI with thyroid function and diseases. Obesity (Silver Spring) 2024; 32:1585-1593. [PMID: 38956411 DOI: 10.1002/oby.24095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/26/2024] [Accepted: 05/20/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVE Observational studies have suggested associations of birth weight, childhood BMI, and adulthood BMI with thyroid function or diseases. However, the causal relationships remain unclear due to residual confounding inherent in conventional epidemiological studies. METHODS We performed a two-sample Mendelian randomization (MR) study to investigate causal relationships of genetically predicted birth weight, childhood BMI, and adulthood BMI with a range of clinically relevant thyroid outcomes. Additionally, we conducted a reverse MR analysis on adulthood BMI. Data on exposures and outcomes were obtained from large-scale genome-wide association study meta-analyses predominantly composed of individuals of European ancestry. RESULTS The MR analysis revealed no evidence of causal associations of birth weight or BMI at different life stages with thyrotropin (TSH) levels, hypothyroidism, hyperthyroidism, autoimmune thyroid disorders, or thyroid cancer. Contrarily, thyroid cancer demonstrated a significant causal relationship with increased adulthood BMI (β = 0.010, 95% CI: 0.006-0.015; p = 5.21 × 10-6). CONCLUSIONS Our comprehensive MR did not find causal links of birth weight, childhood BMI, or adulthood BMI with thyroid diseases but provided evidence that thyroid cancer may play a role in weight gain. Our research findings offer valuable insights into the intricate relationship between body weight and thyroid health throughout an individual's life.
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Affiliation(s)
- Xiaoqin Zhou
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China
- Research Center of Clinical Epidemiology and Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, People's Republic of China
- Center of Biostatistics, Design, Measurement and Evaluation (CBDME), Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Weiqiang Ruan
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Jing Li
- Research Center of Clinical Epidemiology and Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Ting Wang
- Center of Biostatistics, Design, Measurement and Evaluation (CBDME), Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Huizhen Liu
- Center of Biostatistics, Design, Measurement and Evaluation (CBDME), Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Guiying Zhang
- Research Center of Clinical Epidemiology and Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, People's Republic of China
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Hirtz R, Grasemann C, Hölling H, von Holt BH, Albers N, Hinney A, Hebebrand J, Peters T. No relationship between male pubertal timing and depression - new insights from epidemiology and Mendelian randomization. Psychol Med 2024; 54:1975-1984. [PMID: 38515277 DOI: 10.1017/s0033291724000060] [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] [Indexed: 03/23/2024]
Abstract
BACKGROUND In males, the relationship between pubertal timing and depression is understudied and less consistent than in females, likely for reasons of unmeasured confounding. To clarify this relationship, a combined epidemiological and genetic approach was chosen to exploit the methodological advantages of both approaches. METHODS Data from 2026 males from a nationwide, representative study were used to investigate the non-/linear relationship between pubertal timing defined by the age at voice break and depression, considering a multitude of potential confounders and their interactions with pubertal timing. This analysis was complemented by Mendelian randomization (MR), which is robust to inferential problems inherent to epidemiological studies. We used 71 single nucleotide polymorphisms related to pubertal timing in males as instrumental variable to clarify its causal relationship with depression based on data from 807 553 individuals (246 363 cases and 561 190 controls) by univariable and multivariable MR, including BMI as pleiotropic phenotype. RESULTS Univariable MR indicated a causal effect of pubertal timing on depression risk (inverse-variance weighted: OR 0.93, 95%-CI [0.87-0.99)], p = 0.03). However, this was not confirmed by multivariable MR (inverse-variance weighted: OR 0.95, 95%-CI [0.88-1.02)], p = 0.13), consistent with the epidemiological approach (OR 1.01, 95%-CI [0.81-1.26], p = 0.93). Instead, the multivariable MR study indicated a causal relationship of BMI with depression by two of three methods. CONCLUSIONS Pubertal timing is not related to MDD risk in males.
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Affiliation(s)
- Raphael Hirtz
- Department of Pediatrics, Division of Rare Diseases, and CeSER, Ruhr-University Bochum, Alexandrinenstr. 5, 44791 Bochum, Germany
- Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics II, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 40211 Essen, Germany
- Helios University Medical Centre Wuppertal - Children's Hospital, Witten/Herdecke University, Wuppertal, Germany
| | - Corinna Grasemann
- Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics II, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 40211 Essen, Germany
| | - Heike Hölling
- Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany
| | - Björn-Hergen von Holt
- Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, 23562 Lübeck, Germany
| | - Nicola Albers
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Virchowstr. 174, 45147 Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Anke Hinney
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Virchowstr. 174, 45147 Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Virchowstr. 174, 45147 Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Triinu Peters
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Virchowstr. 174, 45147 Essen, Germany
- Center for Translational Neuro- and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
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Gou H, Liu L, Sun X. Causal effects of childhood obesity on neuroticism and subjective well-being: A two-sample Mendelian randomization study. J Affect Disord 2024; 354:110-115. [PMID: 38479511 DOI: 10.1016/j.jad.2024.03.056] [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: 12/06/2023] [Revised: 02/28/2024] [Accepted: 03/09/2024] [Indexed: 03/17/2024]
Abstract
BACKGROUND Childhood obesity is linked to both neuroticism and subjective wellbeing (SWB); however, the causal relations between them remain unclear. METHODS Two-sample Mendelian randomization (MR) analysis was applied to determine the causal effects of childhood BMI (n = 39,620) on neuroticism (n = 366,301) and SWB (n = 298,420) using summary statistics from large scale genome-wide association studies (GWASs). Inverse-variance weighting (IVW), weighted mode, weighted median, and MR-Egger approaches were used to estimate the causal effects. Sensitivity analyses including the Cochran's Q statistics, MR-Egger intercept test, MR-PRESSO global test, and the leave-one-out (LOO) analysis were used to assess potential heterogeneity and horizontal pleiotropy. Two-step MR mediation analysis was employed to explore the potential mediation effects of neuroticism on the causal relationship between childhood BMI and SWB. RESULTS Our study revealed that genetically predicted higher childhood BMI was causally associated with increased neuroticism (beta = 0.045, 95%CI = 0.013,0.077, p = 6.066e-03) and reduced SWB (beta = -0.059, 95%CI = -0.093,-0.024, p = 9.585e-04). Sensitivity analyses didn't detect any significant heterogeneity and horizontal pleiotropy (all p > 0.05). Additionally, the two-step MR mediation analysis indicated that the causal relationship between childhood BMI and SWB was partially mediated by neuroticism (proportion of mediation effects in total effects: 21.3 %, 95%CI: 5.4 % to 37.2, p = 0.0088). CONCLUSION Genetically proxy for higher childhood BMI was associated with increased neuroticism and reduced SWB. Further studies were warranted to investigate the underlying molecular mechanisms and potential use of weight management for improving personality and SWB.
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Affiliation(s)
- Hao Gou
- Department of Pediatrics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610000, Sichuan Province, China
| | - Li Liu
- College of Clinical Medical, Chengdu University of Traditional Chinese Medicine, Chengdu 610000, Sichuan Province, China
| | - Xiangjuan Sun
- Department of Pediatrics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610000, Sichuan Province, China.
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Zhou F, Liu X, Chang C, Liu J, He S, Yan Y. Separating the effects of early and later life body mass index on liver diseases: A Mendelian randomization study. Clin Res Hepatol Gastroenterol 2024; 48:102352. [PMID: 38670486 DOI: 10.1016/j.clinre.2024.102352] [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: 03/30/2024] [Accepted: 04/24/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND AND AIM The independent effects of childhood and adult body mass index (BMI) on non-alcoholic fatty liver disease (NAFLD), cirrhosis, and hepatocellular carcinoma (HCC) are lacking assessment. We aimed to separate the effects of childhood and adult BMI on NAFLD, cirrhosis, and HCC. METHODS Genetic variants associated with childhood and adult BMI were selected as instrumental variables. Two-sample univariable and multivariable MR estimated the total and direct effect of childhood and adult BMI on NAFLD, cirrhosis, and HCC. RESULTS Genetically predicted each 1-SD increased childhood BMI (OR = 1.30, 95 % CI = 1.12 to 1.51, P = 0.001) and adult BMI (OR = 1.57 95 % CI = 1.33 to 1.84, P = 5.49E-08) was associated with an increased risk of NAFLD. The association between childhood BMI (OR = 0.97, 95 % CI = 0.77 to 1.24, P = 0.825) and NAFLD did not remain significant after adjusting for adult BMI (OR = 1.64, 95 % CI = 1.23 to 2.20, P = 0.001). The direct effects of childhood and adult BMI on cirrhosis and HCC were insignificant after considering their relationship. CONCLUSION Maintaining a normal BMI in adulthood significantly reduces the adverse effect of a higher childhood BMI on NAFLD. Further investigation is required to clarify the presence of this effect in cirrhosis and HCC.
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Affiliation(s)
- Feixiang Zhou
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, PR China
| | - Xia Liu
- Sixth Oil Production Plant, PetroChina Changqing Oilfield Company, Xian, Shaanxi, PR China
| | - Canyan Chang
- Fifth Oil Production Plant, PetroChina Changqing Oilfield Company, Xian, Shaanxi, PR China
| | - Jing Liu
- Twelfth Oil Production Plant, PetroChina Changqing Oilfield Company, Xian, Shaanxi, PR China
| | - Simin He
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, PR China
| | - Yan Yan
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, PR China.
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Jasper E, Hellwege J, Greene C, Edwards TL, Edwards DV. Genomic Insights into Gestational Weight Gain: Uncovering Tissue-Specific Mechanisms and Pathways. RESEARCH SQUARE 2024:rs.3.rs-4427250. [PMID: 38854080 PMCID: PMC11160900 DOI: 10.21203/rs.3.rs-4427250/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Increasing gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and their children. The Early Growth Genetics (EGG) Consortium identified previously genetic variants that could contribute to early, late, and total GWG from fetal and maternal genomes. However, the biologic mechanisms and tissue-Specificity of these variants in GWG is unknown. We evaluated the association between genetically predicted gene expression in five relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) from GTEx (v7) and fetal (placenta) tissues and early, late, and total GWG using S-PrediXcan. We tested enrichment of pre-defined biological pathways for nominally (P < 0.05) significant associations using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After multiple testing correction, we did not find significant associations between maternal and fetal gene expression and early, late, or total GWG. There was significant enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, among nominally significant genes from the maternal analyses (false discovery rate p-values: 0.016 to 9.37×10). Enriched biological pathways varied across pregnancy. Though additional research is necessary, these results indicate that diverse biological pathways are likely to impact GWG, with their influence varying by tissue and weeks of gestation.
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Affiliation(s)
| | | | | | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center
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Yazdanpanah M, Yazdanpanah N, Gamache I, Ong K, Perry JRB, Manousaki D. Metabolome-wide Mendelian randomization for age at menarche and age at natural menopause. Genome Med 2024; 16:69. [PMID: 38802955 PMCID: PMC11131236 DOI: 10.1186/s13073-024-01322-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/22/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND The role of metabolism in the variation of age at menarche (AAM) and age at natural menopause (ANM) in the female population is not entirely known. We aimed to investigate the causal role of circulating metabolites in AAM and ANM using Mendelian randomization (MR). METHODS We combined MR with genetic colocalization to investigate potential causal associations between 658 metabolites and AAM and between 684 metabolites and ANM. We extracted genetic instruments for our exposures from four genome-wide association studies (GWAS) on circulating metabolites and queried the effects of these variants on the outcomes in two large GWAS from the ReproGen consortium. Additionally, we assessed the mediating role of the body mass index (BMI) in these associations, identified metabolic pathways implicated in AAM and ANM, and sought validation for selected metabolites in the Avon Longitudinal Study of Parents and Children (ALSPAC). RESULTS Our analysis identified 10 candidate metabolites for AAM, but none of them colocalized with AAM. For ANM, 76 metabolites were prioritized (FDR-adjusted MR P-value ≤ 0.05), with 17 colocalizing, primarily in the glycerophosphocholines class, including the omega-3 fatty acid and phosphatidylcholine (PC) categories. Pathway analyses and validation in ALSPAC mothers also highlighted the role of omega and polyunsaturated fatty acids levels in delaying age at menopause. CONCLUSIONS Our study suggests that metabolites from the glycerophosphocholine and fatty acid families play a causal role in the timing of both menarche and menopause. This underscores the significance of specific metabolic pathways in the biology of female reproductive longevity.
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Affiliation(s)
- Mojgan Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Nahid Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Isabel Gamache
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Ken Ong
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - John R B Perry
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Metabolic Research Laboratory, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Despoina Manousaki
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada.
- Departments of Pediatrics, Biochemistry and Molecular Medicine, Université de Montréal, Montreal, Canada.
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Cui J, Fu S, Zhu L, Li P, Song C. Mendelian randomization shows causal effects of birth weight and childhood body mass index on the risk of frailty. Front Public Health 2024; 12:1270698. [PMID: 38855449 PMCID: PMC11158621 DOI: 10.3389/fpubh.2024.1270698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 05/08/2024] [Indexed: 06/11/2024] Open
Abstract
Background The association between birth weight and childhood body mass index (BMI) and frailty has been extensively studied, but it is currently unclear whether this relationship is causal. Methods We utilized a two-sample Mendelian randomization (MR) methodology to investigate the causal effects of birth weight and childhood BMI on the risk of frailty. Instrumental variables (p < 5E-08) strongly associated with own birth weight (N = 298,142 infants), offspring birth weight (N = 210,267 mothers), and childhood BMI (N = 39,620) were identified from large-scale genomic data from genome-wide association studies (GWAS). The frailty status was assessed using the frailty index, which was derived from comprehensive geriatric assessments of older adults within the UK Biobank and the TwinGene database (N = 175,226). Results Genetically predicted one standard deviation (SD) increase in own birth weight, but not offspring birth weight (maternal-specific), was linked to a decreased frailty index (β per SD increase = -0.068, 95%CI = -0.106 to -0.030, p = 3.92E-04). Conversely, genetically predicted one SD increase in childhood BMI was associated with an elevated frailty index (β per SD increase = 0.080, 95%CI = 0.046 to 0.114, p = 3.43E-06) with good statistical power (99.8%). The findings remained consistent across sensitivity analyses and showed no horizontal pleiotropy (p > 0.05). Conclusion This MR study provides evidence supporting a causal relationship between lower birth weight, higher childhood BMI, and an increased risk of frailty.
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Affiliation(s)
- Junhao Cui
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, Henan, China
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Littleton SH, Trang KB, Volpe CM, Cook K, DeBruyne N, Maguire JA, Weidekamp MA, Hodge KM, Boehm K, Lu S, Chesi A, Bradfield JP, Pippin JA, Anderson SA, Wells AD, Pahl MC, Grant SFA. Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3' UTR of FAIM2. CELL GENOMICS 2024; 4:100556. [PMID: 38697123 PMCID: PMC11099382 DOI: 10.1016/j.xgen.2024.100556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 03/21/2024] [Accepted: 04/08/2024] [Indexed: 05/04/2024]
Abstract
The ch12q13 locus is among the most significant childhood obesity loci identified in genome-wide association studies. This locus resides in a non-coding region within FAIM2; thus, the underlying causal variant(s) presumably influence disease susceptibility via cis-regulation. We implicated rs7132908 as a putative causal variant by leveraging our in-house 3D genomic data and public domain datasets. Using a luciferase reporter assay, we observed allele-specific cis-regulatory activity of the immediate region harboring rs7132908. We generated isogenic human embryonic stem cell lines homozygous for either rs7132908 allele to assess changes in gene expression and chromatin accessibility throughout a differentiation to hypothalamic neurons, a key cell type known to regulate feeding behavior. The rs7132908 obesity risk allele influenced expression of FAIM2 and other genes and decreased the proportion of neurons produced by differentiation. We have functionally validated rs7132908 as a causal obesity variant that temporally regulates nearby effector genes and influences neurodevelopment and survival.
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Affiliation(s)
- Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Khanh B Trang
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Christina M Volpe
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kieona Cook
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Nicole DeBruyne
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jean Ann Maguire
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mary Ann Weidekamp
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kenyaita M Hodge
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sumei Lu
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jonathan P Bradfield
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Quantinuum Research LLC, San Diego, CA 92101, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Stewart A Anderson
- Department of Child and Adolescent Psychiatry, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
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Vizzuso S, Torto AD, Fiore G, Carugo S, Zuccotti G, Verduci E. Tri-ponderal mass index and left ventricular hypertrophy in a cohort of caucasian children and adolescents with obesity. Ital J Pediatr 2024; 50:75. [PMID: 38637874 PMCID: PMC11027303 DOI: 10.1186/s13052-024-01634-9] [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: 05/11/2023] [Accepted: 03/23/2024] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND Pediatric obesity is a global emerging burden for society; among its health-related consequences there are hypertension (HTN) and left ventricular hypertrophy (LVH). Several anthropometric indices have been investigated for the early identification of cardiovascular risk in children. The aim of the present study was to assess whether tri-ponderal mass index (TMI) was associated with LVH in a cohort of Caucasian children and adolescents with obesity. METHODS In this observational study, 63 children and adolescents with obesity aged 7-to-16 years were enrolled. During outpatient visits, adiposity, and cardio-metabolic indices (BMI z-score, WHR, TMI, ABSI) were collected. All subjects underwent a 24-hour ambulatory blood pressure monitoring (ABPM) and transthoracic echocardiography. RESULTS Children and adolescents with obesity with LVH had significantly higher BMI z-score (p = 0.009), WHR (p = 0.006) and TMI (p = 0.026) compared to children without LVH. WC and WHR were the only indices significantly associated with left ventricular mass index (LVMI). CONCLUSION Left ventricular remodeling is associated with the cardio-metabolic risk markers WC and WHR, but not with the adiposity index TMI among children with obesity.
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Affiliation(s)
- Sara Vizzuso
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy.
| | | | - Giulia Fiore
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Health Sciences, University of Milan, Milan, Italy
| | - Stefano Carugo
- Department of Internal Medicine, Cardiology Unity, University of Milan, Fondazione Ospedale Maggiore IRCCS Policlinico Milano, Milano, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Elvira Verduci
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Health Sciences, University of Milan, Milan, Italy
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Hui D, Dudek S, Kiryluk K, Walunas TL, Kullo IJ, Wei WQ, Tiwari HK, Peterson JF, Chung WK, Davis B, Khan A, Kottyan L, Limdi NA, Feng Q, Puckelwartz MJ, Weng C, Smith JL, Karlson EW, Jarvik GP, Ritchie MD. Risk factors affecting polygenic score performance across diverse cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.05.10.23289777. [PMID: 38645167 PMCID: PMC11030495 DOI: 10.1101/2023.05.10.23289777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.
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Affiliation(s)
- Daniel Hui
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Scott Dudek
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University, NY, New York
| | - Theresa L. Walunas
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Hemant K. Tiwari
- Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY
| | - Brittney Davis
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University, NY, New York
| | - Leah Kottyan
- The Center for Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Nita A. Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Qiping Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Megan J. Puckelwartz
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Johanna L. Smith
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Elizabeth W. Karlson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | | | - Gail P. Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, WA
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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Keatley J, Law MH, Seviiri M, Olsen CM, Pandeya N, Ong JS, MacGregor S, Whiteman DC, Dusingize JC. Genetic predisposition to childhood obesity does not influence the risk of developing skin cancer in adulthood. Sci Rep 2024; 14:7854. [PMID: 38570581 PMCID: PMC10991302 DOI: 10.1038/s41598-024-58418-8] [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: 10/27/2023] [Accepted: 03/28/2024] [Indexed: 04/05/2024] Open
Abstract
The relationship between body mass index (BMI) and melanoma and other skin cancers remains unclear. The objective of this study was to employ the Mendelian randomization (MR) approach to evaluate the effects of genetically predicted childhood adiposity on the risk of developing skin cancer later in life. Two-sample MR analyses were conducted using summary data from genome-wide association study (GWAS) meta-analyses of childhood BMI, melanoma, cutaneous squamous cell carcinoma (cSCC), and basal cell carcinoma (BCC). We used the inverse-variance-weighted (IVW) methods to obtain a pooled estimate across all genetic variants for childhood BMI. We performed multiple sensitivity analyses to evaluate the potential influence of various assumptions on our findings. We found no evidence that genetically predicted childhood BMI was associated with risks of developing melanoma, cSCC, or BCC in adulthood (OR, 95% CI: melanoma: 1.02 (0.93-1.13), cSCC 0.94 (0.79-1.11), BCC 0.97 (0.84-1.12)). Our findings do not support the conclusions from observational studies that childhood BMI is associated with increased risks of melanoma, cSCC, or BCC in adulthood. Intervening on childhood adiposity will not reduce the risk of common skin cancers later in life.
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Affiliation(s)
- Jay Keatley
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Matthew H Law
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Mathias Seviiri
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Catherine M Olsen
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nirmala Pandeya
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jue-Sheng Ong
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Stuart MacGregor
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - David C Whiteman
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jean Claude Dusingize
- Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
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Li Z, Wu X, Li H, Bi C, Zhang C, Sun Y, Yan Z. Complex interplay of neurodevelopmental disorders (NDDs), fractures, and osteoporosis: a mendelian randomization study. BMC Psychiatry 2024; 24:232. [PMID: 38539137 PMCID: PMC10967110 DOI: 10.1186/s12888-024-05693-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/18/2024] [Indexed: 12/11/2024] Open
Abstract
BACKGROUND Neurodevelopmental disorders (NDDs), such as Attention-Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and Tourette Syndrome (TS), have been extensively studied for their multifaceted impacts on social and emotional well-being. Recently, there has been growing interest in their potential relationship with fracture risks in adulthood. This study aims to explore the associations between these disorders and fracture rates, in order to facilitate better prevention and treatment. METHODS Employing a novel approach, this study utilized Mendelian randomization (MR) analysis to investigate the complex interplay between ADHD, ASD, TS, and fractures. The MR framework, leveraging extensive genomic datasets, facilitated a systematic examination of potential causal relationships and genetic predispositions. RESULTS The findings unveil intriguing bidirectional causal links between ADHD, ASD, and specific types of fractures. Notably, ADHD is identified as a risk factor for fractures, with pronounced associations in various anatomical regions, including the skull, trunk, and lower limbs. Conversely, individuals with specific fractures, notably those affecting the femur and lumbar spine, exhibit an increased genetic predisposition to ADHD and ASD. In this research, no correlation was found between TS and fractures, or osteoporosis.These results provide a genetic perspective on the complex relationships between NDDs and fractures, emphasizing the importance of early diagnosis, intervention, and a holistic approach to healthcare. CONCLUSION This research sheds new light on the intricate connections between NDDs and fractures, offering valuable insights into potential risk factors and causal links. The bidirectional causal relationships between ADHD, ASD, and specific fractures highlight the need for comprehensive clinical approaches that consider both NDDs and physical well-being.
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Affiliation(s)
- Zefang Li
- Department of The First Clinical medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xueqiang Wu
- Department of Health Science, Shandong University of Traditional Chinese Medicine, Jinan, China.
| | - Hanzheng Li
- Department of The First Clinical medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Cong Bi
- Department of Vascular Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Can Zhang
- School of Biomedical Sciences, Shandong First Medical University, Jinan, China
| | - Yiqing Sun
- Department of The First Clinical medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhaojun Yan
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
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Qing W, Qian Y. Childhood obesity and risk of Alzheimer's disease: a Mendelian randomization study. Arch Public Health 2024; 82:39. [PMID: 38500220 PMCID: PMC10949616 DOI: 10.1186/s13690-024-01271-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/12/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Midlife obesity is a modifiable risk factor for Alzheimer's disease. However, the association between childhood obesity and Alzheimer's disease remains largely unknown. Therefore, we conducted a mendelian randomization analysis (MR) to assess the causal link between childhood obesity and Alzheimer's disease. METHODS Using summary statistics from publicly available genome-wide association studies (GWAS) database, we explored the genetic link between childhood obesity and Alzheimer's disease through a two-sample MR. The primary analysis employed the inverse-variance weighted (IVW) method. To complement our findings, we also employed MR-Egger, weighted median, simple model, and weighted model methods for MR estimates. Furthermore, we conducted Cochrane's Q-statistic test, Egger intercept test, and a leave-one-out sensitivity test to ensure the robustness and reliability of our results. RESULTS The IVW analysis yielded non-significant results, indicating no significant genetic association between childhood obesity and Alzheimer's disease (OR = 0.958, 95% CI = 0.910-1.008, p = 0.095). Consistent with this, the results from MR-Egger, the weighted median, simple model, and weighted model approaches all supported these findings. Furthermore, we did not detect any signs of heterogeneity or pleiotropy, and our leave-one-out analysis confirmed that no single nucleotide polymorphisms had a substantial impact on the reliability of our results. CONCLUSIONS The evidence from our MR analyses suggests that there is no causal effect of childhood obesity on the risk of Alzheimer's disease.
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Affiliation(s)
- Wenxiang Qing
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, China
| | - Yujie Qian
- Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, 410008, China.
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Wu X, Li Z, Cui Y, Yan Z, Lu T, Cui S. Neurodevelopmental disorders as a risk factor for temporomandibular disorder: evidence from Mendelian randomization studies. Front Genet 2024; 15:1365596. [PMID: 38525244 PMCID: PMC10957778 DOI: 10.3389/fgene.2024.1365596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 02/20/2024] [Indexed: 03/26/2024] Open
Abstract
Objective: This study aims to clarify the incidence rate of temporomandibular joint disease in patients with mental disorders. Methods: Data extracted from the Psychiatric Genomics Consortium and FinnGen databases employed the Mendelian Randomization (MR) method to assess the associations of three neurodevelopmental disorders (NDDs)-Attention-Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and Tourette's Disorder (TD)-as exposure factors with Temporomandibular Disorder (TMD). The analysis used a two-sample MR design, employing the Inverse Variance Weighted (IVW) method to evaluate the relationships between these disorders and Temporomandibular Disorder. Sensitivity analysis and heterogeneity assessments were conducted. Potential confounding factors like low birth weight, childhood obesity, and body mass index were controlled for. Results: The study found that ADHD significantly increased the risks for TMD (OR = 1.2342, 95%CI (1.1448-1.3307), p < 0.00001), TMD (including avohilmo) (OR = 1.1244, 95%CI (1.0643-1.1880), p = 0.00003), TMD-related pain (OR = 1.1590, 95%CI (1.0964-1.2252), p < 0.00001), and TMD-related muscular pain associated with fibromyalgia (OR = 1.1815, 95%CI (1.1133-1.2538), p < 0.00001), while other disorders did not show significant causal relationships. Conclusion: This study reveals the elevated risk of various TMD aspects due to ADHD. Furthermore, we discuss the link between low vitamin D levels ADHD and TMD. Future research should address these limitations and delve further into the complex interactions between ADHD, ASD, TD, and TMD.
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Affiliation(s)
- Xueqiang Wu
- Department of Health Science, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zefang Li
- Department of the First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yiping Cui
- Department of the First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhaojun Yan
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Tingting Lu
- Department of the First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Song Cui
- Department of the First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
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Liu C, Zhao Y, Liu J, Zhao Q. The causal effect of obesity on concomitant exotropia: A lifecourse Mendelian randomization study. Medicine (Baltimore) 2024; 103:e37348. [PMID: 38428888 PMCID: PMC10906616 DOI: 10.1097/md.0000000000037348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/02/2024] [Indexed: 03/03/2024] Open
Abstract
Obesity is now a significant global public health issue. Limited understanding exists regarding the association between obesity and concomitant exotropia. Our objective was to identify the causal relationship between lifecourse obesity, including birth weight, childhood body mass index (BMI), and adult BMI, and the risk of concomitant exotropia. We used a two-sample Mendelian randomization (MR) strategy to examine the causal relationship with inverse-variance weighted method as the primary MR analysis. We carried out sensitivity analyses to evaluate the accuracy and robustness of our findings. Also, we performed reverse-direction MR analysis to eliminate the possibility of reverse causality. Childhood BMI, as opposed to birth weight or adult BMI, had a significant impact on the risk of concomitant exotropia (odds ratio = 1.40, 95% confidence interval (CI): 1.08-1.81, P = .01). This significance persisted even after accounting for birth weight and adult BMI using multivariable MR analysis (odds ratio = 1.35, 95% CI: 1.04-1.75, P = .02). There was no significant heterogeneity or pleiotropy observed in sensitivity analyses (P > .05). Multivariable MR analysis further confirmed the absence of pleiotropic effects of some risk factors including prematurity, maternal smoking around birth and refractive error. Reverse causality did not affect the causal relationship (beta = -0.0244, 95% CI: -0.0545 to 0.0056, P = .11). Genetic predisposition to higher childhood BMI was found to be causally linked to an increased risk of concomitant exotropia.
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Affiliation(s)
- Changyang Liu
- Department of Ophthalmology, the Second Hospital of Dalian Medical University, Dalian, China
| | - Yaxin Zhao
- Department of Ophthalmology, the Second Hospital of Dalian Medical University, Dalian, China
| | - Jiasu Liu
- Department of Ophthalmology, the Second Hospital of Dalian Medical University, Dalian, China
| | - Qi Zhao
- Department of Ophthalmology, the Second Hospital of Dalian Medical University, Dalian, China
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Qiu S, Sun Y, Guo J, Zhang Y, Hu Y. Genome-wide analysis reveals extensive genetic overlap between childhood phenotypes and later-life type 2 diabetes. Comput Biol Med 2024; 171:108065. [PMID: 38387379 DOI: 10.1016/j.compbiomed.2024.108065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/26/2023] [Accepted: 01/27/2024] [Indexed: 02/24/2024]
Abstract
Observational studies have indicated a potential influence of childhood phenotypes on the later development of type 2 diabetes (T2D). However, the underlying biological mechanisms remain unclear. In this study, we conducted a comprehensive genome-wide analysis to investigate the shared genetic architecture and genetic loci between nine childhood phenotypes (N = 4202-620,26) and later-life T2D (N = 80,154) using genetic correlation, mendelian randomization (MR), and conjunctional false discovery rate (conjFDR) statistical frameworks. Our findings demonstrated substantial genetic correlations and pleiotropic enrichment between childhood obesity, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and later-life T2D. Childhood obesity exhibited a significant association with increased later-life T2D risk through 10 mediators, 6 of which were adulthood obesity-related phenotypes. Additionally, we identified 69, 83, 3, 5, 10, 5, 3, and 7 loci shared between childhood obesity, BMI, SBP, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and T2D at conjFDR <0.05, with the majority of these loci being novel discoveries. Overall, our study reveals extensive genetic overlap between childhood obesity-related phenotypes and T2D with concordant effect directions, shedding new light on variants and phenotypes with lifelong effects.
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Affiliation(s)
- Shizheng Qiu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China
| | - Yige Sun
- Department of Radiology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jiahe Guo
- School of Future Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Yu Zhang
- Beidahuang Industry Group General Hospital, Harbin, 150088, China.
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China.
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Zhang H, Zhang Q, Song Y, Wang L, Cai M, Bao J, Yu Q. Separating the effects of life course adiposity on diabetic nephropathy: a comprehensive multivariable Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1285872. [PMID: 38390197 PMCID: PMC10881683 DOI: 10.3389/fendo.2024.1285872] [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: 08/30/2023] [Accepted: 01/19/2024] [Indexed: 02/24/2024] Open
Abstract
Aims Previous Mendelian randomization (MR) of obesity and diabetic nephropathy (DN) risk used small sample sizes or focused on a single adiposity metric. We explored the independent causal connection between obesity-related factors and DN risk using the most extensive GWAS summary data available, considering the distribution of adiposity across childhood and adulthood. Methods To evaluate the overall effect of each obesity-related exposure on DN (Ncase = 3,676, Ncontrol = 283,456), a two-sample univariate MR (UVMR) analysis was performed. The independent causal influence of each obesity-related feature on DN was estimated using multivariable MR (MVMR) when accounting for confounding variables. It was also used to examine the independent effects of adult and pediatric obesity, adjusting for their interrelationships. We used data from genome-wide association studies, including overall general (body mass index, BMI) and abdominal obesity (waist-to-hip ratio with and without adjustment for BMI, i.e., WHR and WHRadjBMI), along with childhood obesity (childhood BMI). Results UVMR revealed a significant association between adult BMI (OR=1.24, 95%CI=1.03-1.49, P=2.06×10-2) and pediatric BMI (OR=1.97, 95%CI=1.59-2.45, P=8.55×10-10) with DN risk. At the same time, adult WHR showed a marginally significant increase in DN (OR =1.27, 95%CI = 1.01-1.60, P=3.80×10-2). However, the outcomes were adverse when the influence of BMI was taken out of the WHR (WHRadjBMI). After adjusting for childhood BMI, the causal effects of adult BMI and adult abdominal obesity (WHR) on DN were significantly attenuated and became nonsignificant in MVMR models. In contrast, childhood BMI had a constant and robust independent effect on DN risk(adjusted for adult BMI: IVW, OR=1.90, 95% CI=1.60-2.25, P=2.03×10-13; LASSO, OR=1.91, 95% CI=1.65-2.21, P=3.80×10-18; adjusted for adult WHR: IVW, OR=1.80, 95% CI=1.40-2.31, P=4.20×10-6; LASSO, OR=1.90, 95% CI=1.56-2.32, P=2.76×10-10). Interpretation Our comprehensive analysis illustrated the hazard effect of obesity-related exposures for DN. In addition, we showed that childhood obesity plays a separate function in influencing the risk of DN and that the adverse effects of adult obesity (adult BMI and adult WHR) can be substantially attributed to it. Thus, several obesity-related traits deserve more attention and may become a new target for the prevention and treatment of DN and warrant further clinical investigation, especially in childhood obesity.
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Affiliation(s)
| | | | | | | | | | | | - Qing Yu
- Department of Nephrology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Chen X, Cheng Z, Xu J, Wang Q, Zhao Z, Jiang Q. Causal effects of life course adiposity on temporomandibular disorders: A Mendelian randomization study. J Oral Rehabil 2024; 51:278-286. [PMID: 37830131 DOI: 10.1111/joor.13607] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/08/2023] [Accepted: 09/29/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Previous studies investigated the associations between obesity and temporomandibular disorders (TMDs), but the evidence for the causal inferences was unclear. OBJECTIVE We aimed to investigate the causal link between life course adiposity and TMDs. METHODS Mendelian randomization (MR) studies were performed using genetic instruments for birth weight (BW) (N = 261 932), childhood body mass index (BMI) (N = 39 620), childhood body size (N = 454 718), adult BMI (N = 99 998), body fat percentage (N = 454 633) and TMDs (N = 211 023). We assessed the overall effect of each life course adiposity factor via inverse-variance weighted (IVW), weighted median, and MR-Egger methods and performed extensive sensitivity analyses. Additionally, multivariable MR was conducted to evaluate the direct and indirect effects of childhood BMI on TMDs while accounting for BW and adult BMI, and vice versa. RESULTS Univariable MR analyses revealed a causal effect of low childhood adiposity on an increased risk of TMDs (childhood BMI: IVW OR: 0.65, 95% CI: 0.54-0.78, p < .001; childhood body size: IVW OR: 0.56, 95% CI: 0.43-0.73, p < .001). No causal association existed between genetically predicted BW, adult BMI, or body fat percentage and TMDs. In the multivariable MR analyses, the effects of childhood BMI on TMDs occurrence remained significant and direct, even after adjusting for BW and adult BMI (multivariable IVW OR: 0.78, 95% CI: 0.61-0.99, p = .048). No pleiotropy and heterogeneity were detected (p > .05). CONCLUSION Low childhood BMI might causally increase the risk of TMDs through a direct pathway.
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Affiliation(s)
- Xin Chen
- Department of Oral and Maxillofacial Surgery, Jiangyin People's Hospital Affiliated to Nantong University, Jiangyin, China
| | - Zheng Cheng
- Department of Oral and Maxillofacial Surgery, Jiangyin People's Hospital Affiliated to Nantong University, Jiangyin, China
| | - Junyu Xu
- Department of Oral and Maxillofacial Surgery, Jiangyin People's Hospital Affiliated to Nantong University, Jiangyin, China
| | - Qianyi Wang
- Department of Cardiology, Jiangyin People's Hospital Affiliated to Nantong University, Jiangyin, China
| | - Zhibai Zhao
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
| | - Qianglin Jiang
- Department of Oral and Maxillofacial Surgery, Jiangyin People's Hospital Affiliated to Nantong University, Jiangyin, China
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