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She Y, He Y, Wu J, Liu N. Association between the sarcopenia-related traits and Parkinson's disease: A bidirectional two-sample Mendelian randomization study. Arch Gerontol Geriatr 2024; 122:105374. [PMID: 38452652 DOI: 10.1016/j.archger.2024.105374] [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: 12/14/2023] [Revised: 01/28/2024] [Accepted: 02/19/2024] [Indexed: 03/09/2024]
Abstract
OBJECTIVE To explore the causal association between sarcopenia-related traits and Parkinson's disease by Mendelian randomization (MR) approach. METHODS A genome-wide association study (GWAS) of sarcopenia-related traits was done at the UK Biobank (UKB). The traits were appendicular lean mass, low hand grip strength (including the European Working Group on Sarcopenia in Older People (EWGSOP) and the Foundation for the National Institutes of Health (FNIH) criteria and usual walking pace. The International Parkinson's Disease Genomics Consortium (IPDGC) gave us GWAS data for Parkinson's disease (PD). We used three different types of MR analyses: including Inverse-variance weighted (IVW), Mendelian randomized Egger regression (MR-Egger), and weighted median methods (both weighted and simple modes). RESULTS The MR analysis showed that low hand grip strength was negatively associated with the risk of developing Parkinson's disease, including EWGSOP criterion (odds ratio (OR) = 0.734; 95% confidence interval (CI) = 0.575-0.937, P = 0.013) and FNIH criterion (OR = 0.619; 95% CI = 0.419-0.914, P = 0.016), and usual walking pace was also a risk factor for Parkinson's disease (OR = 3.307, 95% CI = 1.277-8.565, P = 0.014). CONCLUSIONS In European population, low hand grip strength is negatively associated with the risk of developing Parkinson's disease, and usual walking pace is also a risk factor for Parkinson's disease. Further exploration of the potential genetic mechanisms underlying hand grip strength and Parkinson's disease and the potential relationship between walking pace, balance, and falls in Parkinson's patients may help to reduce the burden of sarcopenia and Parkinson's disease.
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Affiliation(s)
- Yingqi She
- Kiang Wu Nursing College of Macau, Avenida do Hospital das Ilhas no.447, Coloane, RAEM, 999078, Macau, China
| | - Yaming He
- Kiang Wu Nursing College of Macau, Avenida do Hospital das Ilhas no.447, Coloane, RAEM, 999078, Macau, China
| | - Jianwei Wu
- Kiang Wu Nursing College of Macau, Avenida do Hospital das Ilhas no.447, Coloane, RAEM, 999078, Macau, China.
| | - Ning Liu
- Kiang Wu Nursing College of Macau, Avenida do Hospital das Ilhas no.447, Coloane, RAEM, 999078, Macau, China.
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Liu J, Richmond RC, Anderson EL, Bowden J, Barry CJS, Dashti HS, Daghlas IS, Lane JM, Kyle SD, Vetter C, Morrison CL, Jones SE, Wood AR, Frayling TM, Wright AK, Carr MJ, Anderson SG, Emsley RA, Ray DW, Weedon MN, Saxena R, Rutter MK, Lawlor DA. The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study. Sci Rep 2024; 14:14962. [PMID: 38942746 PMCID: PMC11213880 DOI: 10.1038/s41598-024-58007-9] [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: 07/14/2023] [Accepted: 03/25/2024] [Indexed: 06/30/2024] Open
Abstract
Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be 'objective' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.
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Affiliation(s)
- Junxi Liu
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Nuffield Department of Population Health, Oxford Population Health, University of Oxford, Oxford, UK.
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma L Anderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Psychiatry, University College of London, London, UK
| | - Jack Bowden
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- College of Medicine and Health, The University of Exeter, Exeter, UK
| | - Ciarrah-Jane S Barry
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hassan S Dashti
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Iyas S Daghlas
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jacqueline M Lane
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Simon D Kyle
- Sir Jules Thorn Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Claire L Morrison
- Department of Psychology & Neuroscience and Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Samuel E Jones
- Institute for Molecular Medicine Finland, University of Helsinki, Uusimaa, Finland
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Alison K Wright
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Matthew J Carr
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- National Institute for Health Research (NIHR) Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, UK
| | - Simon G Anderson
- George Alleyne Chronic Disease Research Centre, Caribbean Institute of Health Research, University of the West Indies, Kingston, Jamaica
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Richard A Emsley
- Department of Biostatistics and Health Informatics, King's College London, London, UK
| | - David W Ray
- Oxford Centre for Diabetes, Endocrinology and Metabolism, and Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK
- NIHR Oxford Health Biomedical Research Centre, and NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, UK
| | - Michael N Weedon
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Richa Saxena
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Martin K Rutter
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Manchester, UK
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and The University of Bristol, Bristol, UK
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Weng C, Shao Z, Xiao M, Song M, Zhao Y, Li A, Pang Y, Huang T, Yu C, Lv J, Li L, Sun D. Association of sex hormones with non-alcoholic fatty liver disease: An observational and Mendelian randomization study. Liver Int 2024; 44:1154-1166. [PMID: 38345150 DOI: 10.1111/liv.15866] [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: 10/18/2023] [Revised: 01/20/2024] [Accepted: 01/28/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND AND AIMS Sex-specific associations of sex hormone-binding globulin (SHBG) and bioavailable testosterone (BAT) with NAFLD remain indeterminate. We aimed to explore observational and genetically determined relationships between each hormone and NAFLD. METHODS We included 187 395 men and 170 193 women from the UK Biobank. Linear and nonlinear Cox regression models and Mendelian randomization (MR) analysis were used to test the associations. RESULTS During 12.49 years of follow-up, 2209 male and 1886 female NAFLD cases were documented. Elevated SHBG levels were linearly associated with a lower risk of NAFLD in women (HR (95% CI), .71 (.63, .79)), but not in men (a "U" shape, pnon-linear < .001). Higher BAT levels were associated with a lower NAFLD risk in men (HR (95% CI), .81 (.71, .93)) but a higher risk in women (HR (95% CI): 1.25 (1.15, 1.36)). Genetically determined SHBG and BAT levels were linearly associated with NAFLD risk in women (OR (95% CI): .57 (.38, .87) and 2.21 (1.41, 3.26) respectively); in men, an "L-shaped" MR association between SHBG levels and NAFLD risk was found (pnon-linear = .016). The bidirectional MR analysis further revealed the effect of NAFLD on SHBG and BAT levels in both sexes. CONCLUSIONS Consistently, linear associations of lower SHBG and higher BAT levels with increased NAFLD risk were both conventionally and genetically found in women, while in men, SHBG acts in a nonlinear manner. In addition, NAFLD may affect SHBG and BAT levels.
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Affiliation(s)
- Chenghao Weng
- School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
| | - Zilun Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Meng Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Mingyu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuxuan Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Aolin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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Richmond RC, Howe LJ, Heilbron K, Jones S, Liu J, Wang X, Weedon MN, Rutter MK, Lawlor DA, Davey Smith G, Vetter C. Correlations in sleeping patterns and circadian preference between spouses. Commun Biol 2023; 6:1156. [PMID: 37957254 PMCID: PMC10643442 DOI: 10.1038/s42003-023-05521-7] [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: 02/14/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023] Open
Abstract
Spouses may affect each other's sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = -0.11; -0.12, -0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (-0.15; -0.26, -0.04) and snoring (-0.15; -0.27, -0.04). Findings support the notion that an individual's sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.
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Affiliation(s)
- Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, UK.
| | - Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, UK
| | - Karl Heilbron
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Samuel Jones
- Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Junxi Liu
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, UK
- Oxford Population Health, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xin Wang
- 23andMe, Inc., 223 N Mathilda Avenue, Sunnyvale, CA, USA
| | - Michael N Weedon
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Martin K Rutter
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, UK
- National Institute of Health Research Biomedical Research Centre, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, UK
- National Institute of Health Research Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Céline Vetter
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
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Loh NY, Rosoff D, Noordam R, Christodoulides C. Investigating the impact of metabolic syndrome traits on telomere length: a Mendelian randomization study. Obesity (Silver Spring) 2023; 31:2189-2198. [PMID: 37415075 PMCID: PMC10658743 DOI: 10.1002/oby.23810] [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: 08/10/2022] [Revised: 04/23/2023] [Accepted: 04/26/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVE Observational studies have reported bidirectional associations between metabolic syndrome (MetS) traits and short leukocyte telomere length (LTL), a TL marker in somatic tissues and a proposed risk factor for age-related degenerative diseases. However, in Mendelian randomization studies, longer LTL has been paradoxically associated with higher MetS risk. This study investigated the hypothesis that shorter LTL might be a consequence of metabolic dysfunction. METHODS This study undertook univariable and multivariable Mendelian randomization. As instrumental variables for MetS traits, all of the genome-wide significant independent signals identified in genome-wide association studies for anthropometric, glycemic, lipid, and blood pressure traits conducted in European individuals were used. Summary-level data for LTL were obtained from a genome-wide association study conducted in the UK Biobank. RESULTS Higher BMI was associated with shorter LTL (β = -0.039, 95% CI: -0.058 to -0.020, p = 5 × 10-5 ) equivalent to 1.70 years of age-related LTL change. In contrast, higher low-density lipoprotein cholesterol was associated with longer LTL (β = 0.022, 95% CI: 0.007 to 0.037, p = 0.003) equivalent to 0.96 years of age-related LTL change. Mechanistically, increased low-grade systemic inflammation, as measured by circulating C-reactive protein, and lower circulating linoleic acid levels might link higher BMI to shorter LTL. CONCLUSIONS Overweight and obesity might promote the development of aging-related degenerative diseases by accelerating telomere shortening.
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Affiliation(s)
- Nellie Y. Loh
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
| | - Daniel Rosoff
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Section on Clinical Genomics and Experimental TherapeuticsNational Institute on Alcohol Abuse and Alcoholism, National Institutes of HealthBethesdaMarylandUSA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and GeriatricsLeiden University Medical CenterLeidenthe Netherlands
| | - Constantinos Christodoulides
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- National Institute for Health Research, Oxford Biomedical Research CentreOxford University Hospitals National Health Service Foundation TrustOxfordUK
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Liu J, Xu H, Cupples LA, O' Connor GT, Liu CT. The impact of obesity on lung function measurements and respiratory disease: A Mendelian randomization study. Ann Hum Genet 2023; 87:174-183. [PMID: 37009668 PMCID: PMC10293090 DOI: 10.1111/ahg.12506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 02/27/2023] [Accepted: 03/02/2023] [Indexed: 04/04/2023]
Abstract
INTRODUCTION Observational studies have shown that body mass index (BMI) and waist-to-hip ratio (WHR) are both inversely associated with lung function, as assessed by forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). However, observational data are susceptible to confounding and reverse causation. METHODS We selected genetic instruments based on their relevant large-scale genome-wide association studies. Summary statistics of lung function and asthma came from the UK Biobank and SpiroMeta Consortium meta-analysis (n = 400,102). After examining pleiotropy and removing outliers, we applied inverse-variance weighting to estimate the causal association of BMI and BMI-adjusted WHR (WHRadjBMI) with FVC, FEV1, FEV1/FVC, and asthma. Sensitivity analyses were performed using weighted median, MR-Egger, and MRlap methods. RESULTS We found that BMI was inversely associated with FVC (effect estimate, -0.167; 95% confidence interval (CI), -0.203 to -0.130) and FEV1 (effect estimate, -0.111; 95%CI, -0.149 to -0.074). Higher BMI was associated with higher FEV1/FVC (effect estimate, 0.079; 95%CI, 0.049 to 0.110) but was not significantly associated with asthma. WHRadjBMI was inversely associated with FVC (effect estimate, -0.132; 95%CI, -0.180 to -0.084) but has no significant association with FEV1. Higher WHR was associated with higher FEV1/FVC (effect estimate, 0.181; 95%CI, 0.130 to 0.232) and with increased risk of asthma (effect estimate, 0.027; 95%CI, 0.001 to 0.053). CONCLUSION We found significant evidence that increased BMI is suggested to be causally related to decreased FVC and FEV1, and increased BMI-adjusted WHR could lead to lower FVC value and higher risk of asthma. Higher BMI and BMI-adjusted WHR were suggested to be causally associated with higher FEV1/FVC.
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Affiliation(s)
- Jiayan Liu
- Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Hanfei Xu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - George T O' Connor
- Pulmonary Center, School of Medicine, Boston University, Boston, Massachusetts, USA
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, Massachusetts, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
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Zhang X, Yang X, Zhang T, Yin X, Man J, Lu M. Association of educational attainment with esophageal cancer, Barrett's esophagus, and gastroesophageal reflux disease, and the mediating role of modifiable risk factors: A Mendelian randomization study. Front Public Health 2023; 11:1022367. [PMID: 37056646 PMCID: PMC10086429 DOI: 10.3389/fpubh.2023.1022367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 02/28/2023] [Indexed: 03/30/2023] Open
Abstract
BackgroundObservational studies have reported that educational attainment has been related to the risk of esophageal cancer (EC) and its precancerous lesions. However, the causal relationship remains controversial. We aimed to apply the Mendelian randomization (MR) design to determine the causal associations between genetically predicted educational attainment and EC, Barrett's esophagus (BE), and gastroesophageal reflux disease (GERD), and to explore whether modifiable risk factors play a mediating role.MethodsUsing summary statistics from genome-wide association studies (GWASs) based on European ancestry individuals of several years in education (EduYears, primary analysis, n = 293,723), college completion (College, secondary analysis, n = 95,427), EC (n = 420,531), BE (n = 361,194), and GERD (n = 420,531), genetic associations between two education phenotypes and EC, BE, and GERD were tested by two-sample MR analyses. Then, two-step MR mediation analyses were used to assess the proportion of the aforementioned association that might be mediated by body mass index (BMI), major depressive disorder (MDD), smoking, drinking, carbohydrates, fat, and protein intake.ResultsGenetically predicted EduYears was negatively associated with the risk of EC, BE, and GERD {odds ratio (OR), 0.64 [95% confidence interval (CI) 0.44–0.94], 0.86 (95% CI, 0.75–0.99), and 0.62 (95%CI, 0.58–0.67)}. EduYears was negatively associated with BMI, MDD, and smoking (range of OR: 0.76–0.84). There were positive associations between BMI, smoking with EC, BE, and GERD, as well as between MDD with GERD (range of OR: 1.08–1.50). For individual mediating effect, BMI and smoking mediated 15.75 and 14.15% of the EduYears-EC association and 15.46 and 16.85% of the EduYears-BE association. BMI, MDD, and smoking mediated 5.23, 4.98, and 4.49% of the EduYears-GERD association. For combined mediation, the aforementioned mediators explained 26.62, 28.38, and 11.48% of the effect of EduYears on EC, BE, and GERD. The mediating effects of drinking and dietary composition were not significant in the effect of education on EC, BE, and GERD.ConclusionOur study supports that genetically predicted higher educational attainment has a protective effect on EC, BE, and GERD, and is partly mediated by reducing adiposity, smoking, and depression.
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Affiliation(s)
- Xuening Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
| | - Xiaorong Yang
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
- Clinical Research Center, Qilu Hospital of Shandong University, Jinan, China
| | - Tongchao Zhang
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
- Clinical Research Center, Qilu Hospital of Shandong University, Jinan, China
| | - Xiaolin Yin
- Department of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
| | - Jinyu Man
- Department of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
| | - Ming Lu
- Department of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
- Clinical Research Center, Qilu Hospital of Shandong University, Jinan, China
- *Correspondence: Ming Lu
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Karageorgiou V, Tyrrell J, Mckinley TJ, Bowden J. Weak and pleiotropy robust sex-stratified Mendelian randomization in the one sample and two sample settings. Genet Epidemiol 2023; 47:135-151. [PMID: 36682072 DOI: 10.1002/gepi.22512] [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: 03/11/2022] [Revised: 09/06/2022] [Accepted: 11/28/2022] [Indexed: 01/23/2023]
Abstract
BACKGROUND Mendelian randomization (MR) leverages genetic data as an instrumental variable to provide estimates for the causal effect of an exposure X on a health outcome Y that is robust to confounding. Unfortunately, horizontal pleiotropy-the direct association of a genetic variant with multiple phenotypes-is highly prevalent and can easily render a genetic variant an invalid instrument. METHODS Building on existing work, we propose a simple method for leveraging sex-specific genetic associations to perform weak and pleiotropy-robust MR analysis. This is achieved by constructing an MR estimator in which pleiotropy is perfectly removed by cancellation, while placing it within the powerful machinery of the robust adjusted profile score (MR-RAPS) method. Pleiotropy cancellation has the attractive property that it removes heterogeneity and therefore justifies a statistically efficient fixed effects model. We extend the method from the typical two-sample summary-data MR setting to the one-sample setting by adapting the technique of Collider-Correction. Simulation studies and applied examples are used to assess how the sex-stratified MR-RAPS estimator performs against other common approaches. RESULTS The sex-stratified MR-RAPS method is shown to be robust to pleiotropy even in cases where all genetic variants violated the standard Instrument Strength Independent of Direct Effect assumption. In some cases where the strength of the pleiotropic effect additionally varied by sex (and so perfect cancellation was not achieved), over-dispersed MR-RAPS implementations can still consistently estimate the true causal effect. In applied analyses, we investigate the causal effect of waist-hip ratio (WHR), an important marker of central obesity, on a range of downstream traits. While the conventional approaches suggested paradoxical links between WHR and height and body mass index, the sex-stratified approach obtained a more realistic null effect. Nonzero effects were also detected for systolic and diastolic blood pressure as well as high-density and low-density lipoprotein cholesterol. DISCUSSION We provide a simple but attractive method for weak and pleiotropy robust causal estimation of sexually dimorphic traits on downstream outcomes, by combining several existing approaches in a novel fashion.
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Affiliation(s)
- Vasilios Karageorgiou
- Exeter Diabetes Group (ExCEED), College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jess Tyrrell
- Exeter Diabetes Group (ExCEED), College of Medicine and Health, University of Exeter, Exeter, UK
| | - Trevelyan J Mckinley
- Exeter Diabetes Group (ExCEED), College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jack Bowden
- Exeter Diabetes Group (ExCEED), College of Medicine and Health, University of Exeter, Exeter, UK
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9
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Lin BD, Pries LK, Sarac HS, van Os J, Rutten BPF, Luykx J, Guloksuz S. Nongenetic Factors Associated With Psychotic Experiences Among UK Biobank Participants: Exposome-Wide Analysis and Mendelian Randomization Analysis. JAMA Psychiatry 2022; 79:857-868. [PMID: 35857297 PMCID: PMC9301596 DOI: 10.1001/jamapsychiatry.2022.1655] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Importance Although hypothesis-driven research has identified several factors associated with psychosis, this one-exposure-to-one-outcome approach fails to embrace the multiplicity of exposures. Systematic approaches, similar to agnostic genome-wide analyses, are needed to identify genuine signals. Objective To systematically investigate nongenetic correlates of psychotic experiences through data-driven agnostic analyses and genetically informed approaches to evaluate associations. Design, Setting, Participants This cohort study analyzed data from the UK Biobank Mental Health Survey from January 1 to June 1, 2021. An exposome-wide association study was performed in 2 equal-sized split discovery and replication data sets. Variables associated with psychotic experiences in the exposome-wide analysis were tested in a multivariable model. For the variables associated with psychotic experiences in the final multivariable model, the single-nucleotide variant-based heritability and genetic overlap with psychotic experiences using linkage disequilibrium score regression were estimated, and mendelian randomization (MR) approaches were applied to test potential causality. The significant associations observed in 1-sample MR analyses were further tested in multiple sensitivity tests, including collider-correction MR, 2-sample MR, and multivariable MR analyses. Exposures After quality control based on a priori criteria, 247 environmental, lifestyle, behavioral, and economic variables. Main Outcomes and Measures Psychotic experiences. Results The study included 155 247 participants (87 896 [57%] female; mean [SD] age, 55.94 [7.74] years). In the discovery data set, 162 variables (66%) were associated with psychotic experiences. Of these, 148 (91%) were replicated. The multivariable analysis identified 36 variables that were associated with psychotic experiences. Of these, 28 had significant genetic overlap with psychotic experiences. One-sample MR analyses revealed forward associations with 3 variables and reverse associations with 3. Forward associations with ever having experienced sexual assault and pleiotropy of risk-taking behavior and reverse associations without pleiotropy of experiencing a physically violent crime as well as cannabis use and the reverse association with pleiotropy of worrying too long after embarrassment were confirmed in sensitivity tests. Thus, associations with psychotic experiences were found with both well-studied and unexplored multiple correlated variables. For several variables, the direction of the association was reversed in the final multivariable and MR analyses. Conclusions and Relevance The findings of this study underscore the need for systematic approaches and triangulation of evidence to build a knowledge base from ever-growing observational data to guide population-level prevention strategies for psychosis.
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Affiliation(s)
- Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,Brainclinics foundation, Nijmegen, the Netherlands.,Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Lotta-Katrin Pries
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Halil Suat Sarac
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands.,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jurjen Luykx
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,Brainclinics foundation, Nijmegen, the Netherlands.,Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands.,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,GGNet Mental Health, Apeldoorn, the Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
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10
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Denault WRP, Bohlin J, Page CM, Burgess S, Jugessur A. Cross-fitted instrument: A blueprint for one-sample Mendelian randomization. PLoS Comput Biol 2022; 18:e1010268. [PMID: 36037248 PMCID: PMC9462731 DOI: 10.1371/journal.pcbi.1010268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 09/09/2022] [Accepted: 05/31/2022] [Indexed: 11/18/2022] Open
Abstract
Bias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a new approach to handling weak instrument bias through the application of a new type of instrumental variable coined 'Cross-Fitted Instrument' (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. These estimates are then used to perform an IVR on each partition. We adapt CFI to the Mendelian randomization (MR) setting and term this adaptation 'Cross-Fitting for Mendelian Randomization' (CFMR). We show that, even when using weak instruments, CFMR is, at worst, biased towards the null, which makes it a conservative one-sample MR approach. In particular, CFMR remains conservative even when the two samples used to perform the MR analysis completely overlap, whereas current state-of-the-art approaches (e.g., MR RAPS) display substantial bias in this setting. Another major advantage of CFMR lies in its use of all of the available data to select genetic instruments, which maximizes statistical power, as opposed to traditional two-sample MR where only part of the data is used to select the instrument. Consequently, CFMR is able to enhance statistical power in consortia-led meta-analyses by enabling a conservative one-sample MR to be performed in each cohort prior to a meta-analysis of the results across all the cohorts. In addition, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in meta-analyses where the participating cohorts may have different ethnicities. To our knowledge, none of the current MR approaches can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are either rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.
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Affiliation(s)
- William R. P. Denault
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jon Bohlin
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Method Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M. Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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11
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Hernáez Á, Wootton RE, Page CM, Skåra KH, Fraser A, Rogne T, Magnus P, Njølstad PR, Andreassen OA, Burgess S, Lawlor DA, Magnus MC. Smoking and infertility: multivariable regression and Mendelian randomization analyses in the Norwegian Mother, Father and Child Cohort Study. Fertil Steril 2022; 118:180-190. [PMID: 35562204 PMCID: PMC7612999 DOI: 10.1016/j.fertnstert.2022.04.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 12/22/2022]
Abstract
OBJECTIVE To investigate the association between smoking and infertility. DESIGN Prospective study. SETTING Nationwide cohort. PATIENTS 28,606 women and 27,096 men with questionnaire and genotype information from the Norwegian Mother, Father, and Child Cohort Study. INTERVENTION Self-reported information on smoking (having ever smoked [both sexes], age at initiation [women only], cessation [women only], and cigarettes/week in current smokers [both sexes]) was gathered. Genetically predetermined levels or likelihood of presenting these traits were estimated for Mendelian randomization. MAIN OUTCOME MEASURE Infertility (time-to-pregnancy ≥12 months). RESULTS Having ever smoked was unrelated to infertility in women or men. Higher smoking intensity in women was associated with greater infertility odds (+1 standard deviation [SD, 48 cigarettes/week]: odds ratio [OR]crude, 1.19; 95% confidence interval [CI] 1.11-1.28; ORadjusted 1.12; 95% CI, 1.03-1.21), also after adjusting for the partner's tobacco use. Later smoking initiation (+1 SD [3.2 years]: ORcrude, 0.94; 95% CI, 0.88-0.99; ORadjusted 0.89; 95% CI, 0.84-0.95) and smoking cessation (vs. not quitting: ORcrude, 0.83; 95% CI, 0.75-0.91; ORadjusted, 0.83; 95% CI, 0.75-0.93) were linked to decreased infertility in women. Nevertheless, Mendelian randomization results were not directionally consistent for smoking intensity and cessation and were estimated imprecisely in the 2-sample approach. In men, greater smoking intensity was not robustly associated with infertility in multivariable regression and Mendelian randomization. CONCLUSIONS We did not find robust evidence of an effect of smoking on infertility. This may be due to a true lack of effect, weak genetic instruments, or other kinds of confounding.
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Affiliation(s)
- Álvaro Hernáez
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain; Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain.
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Mathematics, University of Oslo, Oslo, Norway
| | - Karoline H Skåra
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; The National Institute for Health Research Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Tormod Rogne
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, Connecticut; Department of Circulation and Medical Imaging, Gemini Center for Sepsis Research, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Pål R Njølstad
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway; Children and Adolescent Clinic, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research, NORMENT, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Stephen Burgess
- Medical Research Council, Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; The National Institute for Health Research Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Maria Christine Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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12
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Lee H, Han B. A theory-based practical solution to correct for sex-differential participation bias. Genome Biol 2022; 23:138. [PMID: 35761388 PMCID: PMC9238114 DOI: 10.1186/s13059-022-02703-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 06/13/2022] [Indexed: 11/24/2022] Open
Abstract
Most genomic cohorts are retrospective where the exposures and outcomes are predetermined prior to sample collection. Therefore, a spurious association between an exposure and an outcome can arise if both variables affect study participation. Such concerns were raised in previous studies questioning the representativeness of the UK Biobank. Recently, a genome-wide association study (GWAS) on biological sex found many autosomal hits and non-negligible autosomal heritability which the authors attribute to selection bias. In this study, we propose a simple and a practical method that can overcome sex-driven selection bias based on theoretical analysis and simulations.
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Affiliation(s)
- Hanbin Lee
- Department of Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
| | - Buhm Han
- Department of Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Department of Biomedical Sciences, BK21 Plus Biomedical Science Project, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, 08826, Republic of Korea.
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13
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Liu Z, Luo Y, Su Y, Wei Z, Li R, He L, Yang L, Pei Y, Ren J, Peng X, Hu X. Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization: an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study. Sleep 2022; 45:6509040. [PMID: 35034128 PMCID: PMC8807236 DOI: 10.1093/sleep/zsac003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 12/15/2021] [Indexed: 02/05/2023] Open
Abstract
Study Objectives Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes. Methods Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Beta values and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods. Results In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR=1.24, 95% CI=1.02-1.5; daytime napping [sometimes vs. never]: RR=1.12, 95% CI=1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR= 1.04, 95% CI=1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes. Conclusions Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.
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Affiliation(s)
- Zheran Liu
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Yaxin Luo
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Yonglin Su
- West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | | | - Ruidan Li
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Ling He
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Lianlian Yang
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Yiyan Pei
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Jianjun Ren
- Department of Otolaryngology-Head and Neck Surgery, West China Biomedical Big Data Center, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China
| | - Xingchen Peng
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan,China
| | - Xiaolin Hu
- West China School of Nursing, West China Hospital, Sichuan University, Chengdu, Sichuan,China
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14
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Liu J, Richmond RC, Bowden J, Barry C, Dashti HS, Daghlas I, Lane JM, Jones SE, Wood AR, Frayling TM, Wright AK, Carr MJ, Anderson SG, Emsley RA, Ray DW, Weedon MN, Saxena R, Lawlor DA, Rutter MK. Assessing the Causal Role of Sleep Traits on Glycated Hemoglobin: A Mendelian Randomization Study. Diabetes Care 2022; 45:772-781. [PMID: 35349659 PMCID: PMC9114722 DOI: 10.2337/dc21-0089] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 11/18/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To examine the effects of sleep traits on glycated hemoglobin (HbA1c). RESEARCH DESIGN AND METHODS This study triangulated evidence across multivariable regression (MVR) and one- (1SMR) and two-sample Mendelian randomization (2SMR) including sensitivity analyses on the effects of five self-reported sleep traits (i.e., insomnia symptoms [difficulty initiating or maintaining sleep], sleep duration, daytime sleepiness, napping, and chronotype) on HbA1c (in SD units) in adults of European ancestry from the UK Biobank (for MVR and 1SMR analyses) (n = 336,999; mean [SD] age 57 [8] years; 54% female) and in the genome-wide association studies from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) (for 2SMR analysis) (n = 46,368; 53 [11] years; 52% female). RESULTS Across MVR, 1SMR, 2SMR, and their sensitivity analyses, we found a higher frequency of insomnia symptoms (usually vs. sometimes or rarely/never) was associated with higher HbA1c (MVR 0.05 SD units [95% CI 0.04-0.06]; 1SMR 0.52 [0.42-0.63]; 2SMR 0.24 [0.11-0.36]). Associations remained, but point estimates were somewhat attenuated after excluding participants with diabetes. For other sleep traits, there was less consistency across methods, with some but not all providing evidence of an effect. CONCLUSIONS Our results suggest that frequent insomnia symptoms cause higher HbA1c levels and, by implication, that insomnia has a causal role in type 2 diabetes. These findings could have important implications for developing and evaluating strategies that improve sleep habits to reduce hyperglycemia and prevent diabetes.
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Affiliation(s)
- Junxi Liu
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Rebecca C. Richmond
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Jack Bowden
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- College of Medicine and Health, University of Exeter, Exeter, U.K
| | - Ciarrah Barry
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Hassan S. Dashti
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA
| | - Iyas Daghlas
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA
| | - Jacqueline M. Lane
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA
| | - Samuel E. Jones
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Andrew R. Wood
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
| | - Alison K. Wright
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
| | - Matthew J. Carr
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
- Manchester Academic Health Science Centre, University of Manchester, Manchester, U.K
- National Institute for Health Research (NIHR) Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, U.K
| | - Simon G. Anderson
- George Alleyne Chronic Disease Research Centre, Caribbean Institute of Health Research, University of the West Indies, Kingston, Jamaica
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
| | - Richard A. Emsley
- Department of Biostatistics and Health Informatics, King’s College London, London, U.K
| | - David W. Ray
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | - Michael N. Weedon
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
| | - Richa Saxena
- Centre for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Deborah A. Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service (NHS) Foundation Trust, University of Bristol, Bristol, U.K
| | - Martin K. Rutter
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, U.K
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