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Lv Z, Cui J, Zhang J, He L. Lifestyle factors and subacromial impingement syndrome of the shoulder: potential associations in finnish participants. BMC Musculoskelet Disord 2024; 25:220. [PMID: 38504237 PMCID: PMC10949643 DOI: 10.1186/s12891-024-07345-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/07/2024] [Indexed: 03/21/2024] Open
Abstract
BACKGROUND Emerging evidence has indicated the associations between subacromial impingement syndrome (SIS) of shoulder and lifestyle factors. However, whether unhealthy lifestyle factors causally increase SIS risk is not determined. This study aims to evaluate whether lifestyle factors are the risk factors of SIS. METHODS A two-sample Mendelian randomization (MR) study was designed to evaluate the effect of 11 lifestyle factors on SIS risk. Causality was determined using the inverse-variance weighted method to calculate the odds ratio (OR) and establish a 95% confidence interval (CI). Weighted median method, MR-Egger method and MR-PRESSO method were conducted as sensitivity analysis. RESULTS Four lifestyle factors were identified causally associated with an increased risk of SIS using the IVW method: insomnia (OR: 1.66 95% CI 1.38, 2.00; P = 8.86 × 10- 8), short sleep duration (OR: 1.53 95% CI 1.14, 2.05: P = 0.0043), mobile phone usage (OR: 4.65, 95% CI 1.59, 13.64; P = 0.0051), and heavy manual or physical work (OR: 4.24, 95% CI 2.17, 8.26; P = 2.20 × 10- 5). Another causal but weak association was found between smoking initiation on SIS (OR: 1.17, 95% CI 1.01, 1.35; P = 3.50 × 10- 2). Alcohol, coffee consumption, physical activity, sedentary behavior, sleep duration and computer usage were not found to be causally associated with an increased risk of SIS. Sensitivity analyses indicated that the MR estimates were robust and no heterogeneity and pleiotropy were identified in these MR analyses. CONCLUSION Sleep habits and shoulder usage were identified as causal factors for SIS. This evidence supports the development of strategies aimed at improving sleep behaviors and optimizing shoulder usage patterns as effective measures to prevent SIS.
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Affiliation(s)
- Zhengtao Lv
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jiarui Cui
- Clinical Innovation & Research Center (CIRC), Shenzhen Hospital, Southern Medical University, Shenzhen, 518100, China
| | - Jiaming Zhang
- Clinical Innovation & Research Center (CIRC), Shenzhen Hospital, Southern Medical University, Shenzhen, 518100, China
| | - Li He
- Department of Traumatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095#, Jie-Fang Avenue, Qiaokou District, Wuhan, 430030, China.
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2
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Richardson TG, Leyden GM, Davey Smith G. Time-varying and tissue-dependent effects of adiposity on leptin levels: A Mendelian randomization study. eLife 2023; 12:e84646. [PMID: 37878001 PMCID: PMC10599655 DOI: 10.7554/elife.84646] [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: 11/02/2022] [Accepted: 10/08/2023] [Indexed: 10/26/2023] Open
Abstract
Background Findings from Mendelian randomization (MR) studies are conventionally interpreted as lifelong effects, which typically do not provide insight into the molecular mechanisms underlying the effect of an exposure on an outcome. In this study, we apply two recently developed MR approaches (known as 'lifecourse' and 'tissue-partitioned' MR) to investigate lifestage-specific effects and tissues of action in the relationship between adiposity and circulating leptin levels. Methods Genetic instruments for childhood and adult adiposity were incorporated into a multivariable MR (MVMR) framework to estimate lifestage-specific effects on leptin levels measured during early life (mean age: 10 y) in the Avon Longitudinal Study of Parents and Children and in adulthood (mean age: 55 y) using summary-level data from the deCODE Health study. This was followed by partitioning body mass index (BMI) instruments into those whose effects are putatively mediated by gene expression in either subcutaneous adipose or brain tissues, followed by using MVMR to simultaneously estimate their separate effects on childhood and adult leptin levels. Results There was strong evidence that childhood adiposity has a direct effect on leptin levels at age 10 y in the lifecourse (β = 1.10 SD change in leptin levels, 95% CI = 0.90-1.30, p=6 × 10-28), whereas evidence of an indirect effect was found on adulthood leptin along the causal pathway involving adulthood body size (β = 0.74, 95% CI = 0.62-0.86, p=1 × 10-33). Tissue-partitioned MR analyses provided evidence to suggest that BMI exerts its effect on leptin levels during both childhood and adulthood via brain tissue-mediated pathways (β = 0.79, 95% CI = 0.22-1.36, p=6 × 10-3 and β = 0.51, 95% CI = 0.32-0.69, p=1 × 10-7, respectively). Conclusions Our findings demonstrate the use of lifecourse MR to disentangle direct and indirect effects of early-life exposures on time-varying complex outcomes. Furthermore, by integrating tissue-specific data, we highlight the etiological importance of appetite regulation in the effect of adiposity on leptin levels. Funding This work was supported by the Integrative Epidemiology Unit, which receives funding from the UK Medical Research Council and the University of Bristol (MC_UU_00011/1).
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Affiliation(s)
- Tom G Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield GroveBristolUnited Kingdom
| | - Genevieve M Leyden
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield GroveBristolUnited Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield GroveBristolUnited Kingdom
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Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res 2023; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.3] [Citation(s) in RCA: 180] [Impact Index Per Article: 180.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 08/08/2023] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
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4
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Spiga F, Gibson M, Dawson S, Tilling K, Davey Smith G, Munafò MR, Higgins JPT. Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review. Int J Epidemiol 2023; 52:227-249. [PMID: 35900265 PMCID: PMC9908059 DOI: 10.1093/ije/dyac149] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 06/29/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies. METHODS We systematically searched MEDLINE, Embase, the Web of Science, preprints servers and Google Scholar for articles containing tools for assessing, conducting and/or reporting MR studies. We also searched for systematic reviews and protocols of systematic reviews of MR studies. From eligible articles we collected data on tool characteristics and content, as well as details of narrative description of bias assessment. RESULTS Our searches retrieved 2464 records to screen, from which 14 tools, 35 systematic reviews and 38 protocols were included in our review. Seven tools were designed for assessing risk of bias/quality of evidence in MR studies and evaluation of their content revealed that all seven tools addressed the three core assumptions of instrumental variable analysis, violation of which can potentially introduce bias in MR analysis estimates. CONCLUSION We present an overview of tools and methods to assess risk of bias/quality of evidence in MR analysis. Issues commonly addressed relate to the three standard assumptions of instrumental variables analyses, the choice of genetic instrument(s) and features of the population(s) from which the data are collected (particularly in two-sample MR), in addition to more traditional non-MR-specific epidemiological biases. The identified tools should be tested and validated for general use before recommendations can be made on their widespread use. Our findings should raise awareness about the importance of bias related to MR analysis and provide information that is useful for assessment of MR studies in the context of systematic reviews.
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Affiliation(s)
- Francesca Spiga
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Mark Gibson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Sarah Dawson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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5
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Hartley AE, Power GM, Sanderson E, Smith GD. A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field. JBMR Plus 2022; 6:e10675. [PMID: 36248277 PMCID: PMC9549705 DOI: 10.1002/jbm4.10675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 08/08/2022] [Indexed: 11/10/2022] Open
Abstract
Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- April E Hartley
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - Grace M Power
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - Eleanor Sanderson
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - George Davey Smith
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
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6
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Sadik A, Dardani C, Pagoni P, Havdahl A, Stergiakouli E, Khandaker GM, Sullivan SA, Zammit S, Jones HJ, Davey Smith G, Dalman C, Karlsson H, Gardner RM, Rai D. Parental inflammatory bowel disease and autism in children. Nat Med 2022; 28:1406-1411. [PMID: 35654906 PMCID: PMC9307481 DOI: 10.1038/s41591-022-01845-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 04/28/2022] [Indexed: 01/30/2023]
Abstract
Evidence linking parental inflammatory bowel disease (IBD) with autism in children is inconclusive. We conducted four complementary studies to investigate associations between parental IBD and autism in children, and elucidated their underlying etiology. Conducting a nationwide population-based cohort study using Swedish registers, we found evidence of associations between parental diagnoses of IBD and autism in children. Polygenic risk score analyses of the Avon Longitudinal Study of Parents and Children suggested associations between maternal genetic liability to IBD and autistic traits in children. Two-sample Mendelian randomization analyses provided evidence of a potential causal effect of genetic liability to IBD, especially ulcerative colitis, on autism. Linkage disequilibrium score regression did not indicate a genetic correlation between IBD and autism. Triangulating evidence from these four complementary approaches, we found evidence of a potential causal link between parental, particularly maternal, IBD and autism in children. Perinatal immune dysregulation, micronutrient malabsorption and anemia may be implicated.
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Affiliation(s)
- Aws Sadik
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon and Wiltshire Partnership NHS Mental Health Trust, Bath, UK
| | - Christina Dardani
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Panagiota Pagoni
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Alexandra Havdahl
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diakonale Hospital, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Evie Stergiakouli
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Golam M Khandaker
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon and Wiltshire Partnership NHS Mental Health Trust, Bath, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Sarah A Sullivan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Stan Zammit
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Hannah J Jones
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Christina Dalman
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
- Centre for Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Håkan Karlsson
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Renee M Gardner
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Dheeraj Rai
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Avon and Wiltshire Partnership NHS Mental Health Trust, Bath, UK
- National Institute of Health and Care Research Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
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7
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Howe LJ, Tudball M, Davey Smith G, Davies NM. Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment. Int J Epidemiol 2022; 51:948-957. [PMID: 34570226 PMCID: PMC9189950 DOI: 10.1093/ije/dyab208] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Mendelian randomization has been previously used to estimate the effects of binary and ordinal categorical exposures-e.g. Type 2 diabetes or educational attainment defined by qualification-on outcomes. Binary and categorical phenotypes can be modelled in terms of liability-an underlying latent continuous variable with liability thresholds separating individuals into categories. Genetic variants influence an individual's categorical exposure via their effects on liability, thus Mendelian-randomization analyses with categorical exposures will capture effects of liability that act independently of exposure category. METHODS AND RESULTS We discuss how groups in which the categorical exposure is invariant can be used to detect liability effects acting independently of exposure category. For example, associations between an adult educational-attainment polygenic score (PGS) and body mass index measured before the minimum school leaving age (e.g. age 10 years), cannot indicate the effects of years in full-time education on this outcome. Using UK Biobank data, we show that a higher educational-attainment PGS is strongly associated with lower smoking initiation and higher odds of glasses use at age 15 years. These associations were replicated in sibling models. An orthogonal approach using the raising of the school leaving age (ROSLA) policy change found that individuals who chose to remain in education to age 16 years before the reform likely had higher liability to educational attainment than those who were compelled to remain in education to age 16 years after the reform, and had higher income, lower pack-years of smoking, higher odds of glasses use and lower deprivation in adulthood. These results suggest that liability to educational attainment is associated with health and social outcomes independently of years in full-time education. CONCLUSIONS Mendelian-randomization studies with non-continuous exposures should be interpreted in terms of liability, which may affect the outcome via changes in exposure category and/or independently.
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Affiliation(s)
- Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Matthew Tudball
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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8
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Wade KH, Yarmolinsky J, Giovannucci E, Lewis SJ, Millwood IY, Munafò MR, Meddens F, Burrows K, Bell JA, Davies NM, Mariosa D, Kanerva N, Vincent EE, Smith-Byrne K, Guida F, Gunter MJ, Sanderson E, Dudbridge F, Burgess S, Cornelis MC, Richardson TG, Borges MC, Bowden J, Hemani G, Cho Y, Spiller W, Richmond RC, Carter AR, Langdon R, Lawlor DA, Walters RG, Vimaleswaran KS, Anderson A, Sandu MR, Tilling K, Davey Smith G, Martin RM, Relton CL. Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer. Cancer Causes Control 2022; 33:631-652. [PMID: 35274198 PMCID: PMC9010389 DOI: 10.1007/s10552-022-01562-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 02/10/2022] [Indexed: 02/08/2023]
Abstract
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.
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Affiliation(s)
- Kaitlin H Wade
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
| | - James Yarmolinsky
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Edward Giovannucci
- Departments of Nutrition and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Sarah J Lewis
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marcus R Munafò
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Fleur Meddens
- Department of Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Kimberley Burrows
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Joshua A Bell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Neil M Davies
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Daniela Mariosa
- International Agency for Research On Cancer (IARC), Lyon, France
| | | | - Emma E Vincent
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Cellular and Molecular Medicine, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Karl Smith-Byrne
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Florence Guida
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Marc J Gunter
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Eleanor Sanderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Tom G Richardson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Jack Bowden
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Research Innovation Learning and Development (RILD) Building, University of Exeter Medical School, Exeter, UK
| | - Gibran Hemani
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Yoonsu Cho
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Wes Spiller
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Alice R Carter
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Ryan Langdon
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Annie Anderson
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, Scotland, UK
| | - Meda R Sandu
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre, Bristol, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Richard M Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Caroline L Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
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9
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Vabistsevits M, Davey Smith G, Sanderson E, Richardson TG, Lloyd-Lewis B, Richmond RC. Deciphering how early life adiposity influences breast cancer risk using Mendelian randomization. Commun Biol 2022; 5:337. [PMID: 35396499 PMCID: PMC8993830 DOI: 10.1038/s42003-022-03272-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 03/14/2022] [Indexed: 12/17/2022] Open
Abstract
Studies suggest that adiposity in childhood may reduce the risk of breast cancer in later life. The biological mechanism underlying this effect is unclear but is likely to be independent of body size in adulthood. Using a Mendelian randomization framework, we investigate 18 hypothesised mediators of the protective effect of childhood adiposity on later-life breast cancer, including hormonal, reproductive, physical, and glycaemic traits. Our results indicate that, while most of the hypothesised mediators are affected by childhood adiposity, only IGF-1 (OR: 1.08 [1.03: 1.15]), testosterone (total/free/bioavailable ~ OR: 1.12 [1.05: 1.20]), age at menopause (OR: 1.05 [1.03: 1.07]), and age at menarche (OR: 0.92 [0.86: 0.99], direct effect) influence breast cancer risk. However, multivariable Mendelian randomization analysis shows that the protective effect of childhood body size remains unaffected when accounting for these traits (ORs: 0.59-0.67). This suggests that none of the investigated potential mediators strongly contribute to the protective effect of childhood adiposity on breast cancer risk individually. It is plausible, however, that several related traits could collectively mediate the effect when analysed together, and this work provides a compelling foundation for investigating other mediating pathways in future studies.
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Affiliation(s)
- Marina Vabistsevits
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Eleanor Sanderson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tom G Richardson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Novo Nordisk Research Centre, Headington, Oxford, OX3 7FZ, UK
| | - Bethan Lloyd-Lewis
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, Bristol, BS8 1TD, UK
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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10
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Sanderson E, Glymour MM, Holmes MV, Kang H, Morrison J, Munafò MR, Palmer T, Schooling CM, Wallace C, Zhao Q, Smith GD. Mendelian randomization. NATURE REVIEWS. METHODS PRIMERS 2022; 2:6. [PMID: 37325194 PMCID: PMC7614635 DOI: 10.1038/s43586-021-00092-5] [Citation(s) in RCA: 467] [Impact Index Per Article: 233.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/21/2021] [Indexed: 06/17/2023]
Abstract
Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.
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Affiliation(s)
- Eleanor Sanderson
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Michael V. Holmes
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hyunseung Kang
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Jean Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Marcus R. Munafò
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR), Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Tom Palmer
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - C. Mary Schooling
- School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- School of Public Health, City University of New York, New York, USA
| | - Chris Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK
| | - Qingyuan Zhao
- Statistical Laboratory, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- Medical Research Council (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), Biomedical Research Centre, University of Bristol, Bristol, UK
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11
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Dardani C, Riglin L, Leppert B, Sanderson E, Rai D, Howe LD, Davey Smith G, Tilling K, Thapar A, Davies NM, Anderson E, Stergiakouli E. Is genetic liability to ADHD and ASD causally linked to educational attainment? Int J Epidemiol 2022; 50:2011-2023. [PMID: 34999873 PMCID: PMC8743131 DOI: 10.1093/ije/dyab107] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 05/09/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND The association patterns of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) with educational attainment (EA) are complex; children with ADHD and ASD are at risk of poor academic outcomes, and parental EA has been associated with risk of ADHD/ASD in the offspring. Little is known on the causal links between ADHD, ASD, EA and the potential contribution of cognitive ability. METHODS Using the latest genome-wide association studies (GWAS) summary data on ADHD, ASD and EA, we applied two-sample Mendelian randomization (MR) to assess the effects of genetic liability to ADHD and ASD on EA. Reverse direction analyses were additionally performed. Multivariable MR was performed to estimate any effects independent of cognitive ability. RESULTS Genetic liability to ADHD had a negative effect on EA, independently of cognitive ability (MVMRIVW: -1.7 months of education per doubling of genetic liability to ADHD; 95% CI: -2.8 to -0.7), whereas genetic liability to ASD a positive effect (MVMRIVW: 30 days per doubling of the genetic liability to ASD; 95% CI: 2 to 53). Reverse direction analyses suggested that genetic liability to higher EA had an effect on lower risk of ADHD, independently of cognitive ability (MVMRIVWOR: 0.33 per SD increase; 95% CI: 0.26 to 0.43) and increased risk of ASD (MRIVWOR: 1.51 per SD increase; 95% CI: 1.29 to 1.77), which was partly explained by cognitive ability (MVMRIVWOR per SD increase: 1.24; 95%CI: 0.96 to 1.60). CONCLUSIONS Genetic liability to ADHD and ASD is likely to affect educational attainment, independently of underlying cognitive ability.
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Affiliation(s)
- Christina Dardani
- Centre of Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Beate Leppert
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleanor Sanderson
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Dheeraj Rai
- Centre of Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Laura D Howe
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Emma Anderson
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Evie Stergiakouli
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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12
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Abstract
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol BS1 3NU, United Kingdom
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13
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Skrivankova VW, Richmond RC, Woolf BAR, Yarmolinsky J, Davies NM, Swanson SA, VanderWeele TJ, Higgins JPT, Timpson NJ, Dimou N, Langenberg C, Golub RM, Loder EW, Gallo V, Tybjaerg-Hansen A, Davey Smith G, Egger M, Richards JB. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement. JAMA 2021; 326:1614-1621. [PMID: 34698778 DOI: 10.1001/jama.2021.18236] [Citation(s) in RCA: 1125] [Impact Index Per Article: 375.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Importance Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation. Objective To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guideline for the reporting of MR studies. Design, Setting, and Participants The development of the STROBE-MR Statement followed the Enhancing the Quality and Transparency of Health Research (EQUATOR) framework guidance and used the STROBE Statement as a starting point to draft a checklist tailored to MR studies. The project was initiated in 2018 by reviewing the literature on the reporting of instrumental variable and MR studies. A group of 17 experts, including MR methodologists, MR study design users, developers of previous reporting guidelines, and journal editors, participated in a workshop in May 2019 to define the scope of the Statement and draft the checklist. The draft checklist was published as a preprint in July 2019 and discussed on the preprint platform, in social media, and at the 4th Mendelian Randomization Conference. The checklist was then revised based on comments, further refined through 2020, and finalized in July 2021. Findings The STROBE-MR checklist is organized into 6 sections (Title and Abstract, Introduction, Methods, Results, Discussion, and Other Information) and includes 20 main items and 30 subitems. It covers both 1-sample and 2-sample MR studies that assess 1 or multiple exposures and outcomes, and addresses MR studies that follow a genome-wide association study and are reported in the same article. The checklist asks authors to justify why MR is a helpful method to address the study question and state prespecified causal hypotheses. The measurement, quality, and selection of genetic variants must be described and attempts to assess validity of MR-specific assumptions should be well reported. An item on data sharing includes reporting when the data and statistical code required to replicate the analyses can be accessed. Conclusions and Relevance STROBE-MR provides guidelines for reporting MR studies. Improved reporting of these studies could facilitate their evaluation by editors, peer reviewers, researchers, clinicians, and other readers, and enhance the interpretation of their results.
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Affiliation(s)
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Benjamin A R Woolf
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Department of Psychological Science, University of Bristol, Bristol, United Kingdom
| | - James Yarmolinsky
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Norway
| | - Sonja A Swanson
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - Tyler J VanderWeele
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Niki Dimou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Robert M Golub
- JAMA , Chicago, Illinois
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Elizabeth W Loder
- Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- BMJ , London, United Kingdom
| | - Valentina Gallo
- Campus Fryslân, University of Groningen, Leeuwarden, the Netherlands
- Institute of Population Health Sciences, Queen Mary, University of London, London, United Kingdom
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Anne Tybjaerg-Hansen
- Section for Molecular Genetics, Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Matthias Egger
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - J Brent Richards
- Departments of Medicine, Human Genetics, Epidemiology, & Biostatistics, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, University of London, London, United Kingdom
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14
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Wang J, Zhao Q, Bowden J, Hemani G, Davey Smith G, Small DS, Zhang NR. Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments. PLoS Genet 2021; 17:e1009575. [PMID: 34157017 PMCID: PMC8301661 DOI: 10.1371/journal.pgen.1009575] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 07/23/2021] [Accepted: 05/04/2021] [Indexed: 12/25/2022] Open
Abstract
Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.
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Affiliation(s)
- Jingshu Wang
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - Qingyuan Zhao
- Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, United Kingdom
| | - Jack Bowden
- College of Medicine and Health, University of Exeter, Exeter, United Kingdom
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Dylan S. Small
- Department of Statistics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Nancy R. Zhang
- Department of Statistics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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15
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García-Rodríguez MH, Peña-Espinoza BI, de Los Angeles Granados-Silvestre M, Ortiz-López MG, Menjivar M. Association of the T130I Variant of the HNF4A Gene with Metabolic Syndrome and Its Components in Mexican Children. Metab Syndr Relat Disord 2020; 18:479-484. [PMID: 32857684 DOI: 10.1089/met.2020.0024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Background: Metabolic syndrome (MetS), a cluster of risk factors, leads to cardiovascular disease (CVD) and type 2 diabetes (T2D). The second leading cause of mortality in Mexico is T2D. Genetic factors participate in the pathogenesis of MetS. The HNFA gene encodes a transcription factor that plays a crucial role in energy homeostasis by regulating the metabolism of glucose and lipids. This study aimed to investigate the association of the T130I variant of the HNF4A gene in Mexican children with MetS and its constituent components. Methods: The study was performed in 477 children from elementary schools. MetS was classified according to the de Ferranti definition. Biochemical parameters were measured and genotyping was performed. Logistic regression under a dominant genetic model was used to analyze the association of the T130I variant of the HNF4A gene with MetS and with its components separately. Results: The prevalence of MetS was 25.4%, and 18.9% in children who presented insulin resistance. Interestingly, this is the first time that a significant association between the T130I variant of the HNF4A gene and MetS has been reported [odds ratios (OR) = 2.31; 95% confidence interval (CI) 1.10-4.83; P = 0.026]. Moreover, carriers of the risk allele show higher abdominal obesity (OR = 1.20; 95% CI 1.09-4.50; P = 0.029). These findings highlight the active role of genetic variants in the pathogenesis of MetS in Mexican children. Conclusions: The high prevalence of children with MetS and insulin resistance places this population at an elevated risk of early CVD and T2D. The Clinical Trial Registration Number is HJM2315/14C.
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Affiliation(s)
| | - Barbara Itzel Peña-Espinoza
- Laboratorio de Genómica de la Diabetes, Unidad Académica de Ciencias y Tecnología de la UNAM en Yucatán, Yucatán, México
| | | | | | - Marta Menjivar
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México, Ciudad de México, México
- Laboratorio de Genómica de la Diabetes, Unidad Académica de Ciencias y Tecnología de la UNAM en Yucatán, Yucatán, México
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16
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Worthman CM, Dockray S, Marceau K. Puberty and the Evolution of Developmental Science. JOURNAL OF RESEARCH ON ADOLESCENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR RESEARCH ON ADOLESCENCE 2019; 29:9-31. [PMID: 30869841 PMCID: PMC6961839 DOI: 10.1111/jora.12411] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
In recent decades, theoretical and methodological advances have operated synergistically to advance understanding of puberty and prompt increasingly comprehensive models that engage with the temporal, psychosocial, and biological dimensions of this maturational milepost. This integrative overview discusses these theoretical and methodological advances and their implications for research and intervention to promote human development in the context of changing maturational schedules and massive ongoing social transformations.
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17
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Did family size affect differences in body height in non-urbanized societies? Evidence from the Lemko community in Poland in the late 19th and early 20th centuries. J Biosoc Sci 2019; 51:669-682. [PMID: 30632477 DOI: 10.1017/s0021932018000421] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this study was to examine the effect of economic changes in the Polish territories under Austrian partition at the end of the 19th and the beginning of the 20th centuries on the trend in adult body height, and to examine the effect of number of children in a family, as a socioeconomic factor, on the differences in heights of males and females. Data collected in a 1939 survey for a group of 350 Lemkos living in Polish lands under the Austrian partition were obtained from archive material. Individual data were obtained for body height and number of siblings, to calculate family size. Linear regression analysis confirmed an increase in body height in males by about 1.2 cm per decade over the period 1860 to 1922. The number of children in a family did not appear to influence the mean body height of men and women. The observed positive mean body height trend probably resulted from the improvement in the economic conditions in the Austrian sector over the survey period.
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18
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Huang JY, King NB. Epigenetics Changes Nothing: What a New Scientific Field Does and Does Not Mean for Ethics and Social Justice. Public Health Ethics 2017; 11:69-81. [PMID: 30619507 DOI: 10.1093/phe/phx013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Recently, ethicists have posited that consideration of epigenetic mechanisms presents novel challenges to concepts of justice and equality of opportunity, such as elevating the importance of environments in bioethics and providing a counterpoint to gross genetic determinism. We argue that new findings in epigenetic sciences, including those regarding intergenerational health effects, do not necessitate reconceptualization of theories of justice or the environment. To the contrary, such claims reflect a flawed understanding of epigenetics and its relation to genetics that may unintentionally undermine appeals to social justice. We provide a brief summary of epigenetic sciences, focusing on phenomena central to the current ethical discourse. We identify three fallacious modes of reasoning arising from the emergent literature on the ethical and policy implications of epigenetics, including mischaracterization, undue extrapolation, and exceptionalism. We end by discussing how these issues may work against mobilizing health equity policies and present a more modest claim regarding the value of new epigenetic knowledge to health justice by setting this discourse within the context of known themes in biomedical ethics and health policy.
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Affiliation(s)
- Jonathan Y Huang
- Institute for Health and Social Policy, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University
| | - Nicholas B King
- Department of Epidemiology, Biostatistics, and Occupational Health, Department of the Social Studies of Medicine, Biomedical Ethics Unit, McGill University
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Patton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, Arora M, Azzopardi P, Baldwin W, Bonell C, Kakuma R, Kennedy E, Mahon J, McGovern T, Mokdad AH, Patel V, Petroni S, Reavley N, Taiwo K, Waldfogel J, Wickremarathne D, Barroso C, Bhutta Z, Fatusi AO, Mattoo A, Diers J, Fang J, Ferguson J, Ssewamala F, Viner RM. Our future: a Lancet commission on adolescent health and wellbeing. Lancet 2016; 387:2423-78. [PMID: 27174304 PMCID: PMC5832967 DOI: 10.1016/s0140-6736(16)00579-1] [Citation(s) in RCA: 1763] [Impact Index Per Article: 220.4] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- George C Patton
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Centre for Adolescent Health, Royal Children's Hospital, Parkville, Melbourne, VIC, Australia.
| | - Susan M Sawyer
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Centre for Adolescent Health, Royal Children's Hospital, Parkville, Melbourne, VIC, Australia; Murdoch Childrens Research Institute, Columbia University, New York, NY, USA
| | - John S Santelli
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - David A Ross
- World Health Organization, Geneva, Switzerland; London School of Hygiene & Tropical Medicine, London, UK
| | - Rima Afifi
- Department of Health Promotion and Community Health, American University of Beirut, Beirut, Lebanon
| | - Nicholas B Allen
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia; University of Oregon, Eugene, OR, USA
| | - Monika Arora
- Public Health Foundation of India, New Delhi, India
| | - Peter Azzopardi
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Centre for Adolescent Health, Royal Children's Hospital, Parkville, Melbourne, VIC, Australia
| | | | | | - Ritsuko Kakuma
- School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | | | | | - Terry McGovern
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ali H Mokdad
- Institute of Health Metrics and Evaluation, University of Washinton, Seattle, WA, USA
| | - Vikram Patel
- London School of Hygiene & Tropical Medicine, London, UK; Public Health Foundation of India, New Delhi, India
| | - Suzanne Petroni
- International Centre for Research on Women, Washington, DC, USA
| | - Nicola Reavley
- School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | | | - Jane Waldfogel
- School of Social Work, Columbia University, New York, NY, USA
| | | | | | - Zulfiqar Bhutta
- University of Toronto, Toronto, ON, Canada; Aga Khan University, Karachi, Pakistan
| | | | - Amitabh Mattoo
- Australia India Centre, University of Melbourne, Melbourne, VIC, Australia; Jawaharlal Nehru University, New Delhi, India
| | | | - Jing Fang
- Kunming Medical University, Kunming, China
| | - Jane Ferguson
- London School of Hygiene & Tropical Medicine, London, UK
| | | | - Russell M Viner
- Institute of Child Health, University College London, London, UK
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Abstract
In this review, the potential causes and consequences of adult height, a measure of cumulative net nutrition, in modern populations are summarized. The mechanisms linking adult height and health are examined, with a focus on the role of potential confounders. Evidence across studies indicates that short adult height (reflecting growth retardation) in low- and middle-income countries is driven by environmental conditions, especially net nutrition during early years. Some of the associations of height with health and social outcomes potentially reflect the association between these environmental factors and such outcomes. These conditions are manifested in the substantial differences in adult height that exist between and within countries and over time. This review suggests that adult height is a useful marker of variation in cumulative net nutrition, biological deprivation, and standard of living between and within populations and should be routinely measured. Linkages between adult height and health, within and across generations, suggest that adult height may be a potential tool for monitoring health conditions and that programs focused on offspring outcomes may consider maternal height as a potentially important influence.
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Affiliation(s)
- Jessica M Perkins
- J.M. Perkins is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; the Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and the Massachusetts General Hospital Center for Global Health, Boston, Massachusetts, USA. S.V. Subramanian is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; and the Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. G. Davey Smith is with the MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. E. Özaltin is with the Health, Nutrition and Population Global Practice, The World Bank, Washington, DC, USA.
| | - S V Subramanian
- J.M. Perkins is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; the Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and the Massachusetts General Hospital Center for Global Health, Boston, Massachusetts, USA. S.V. Subramanian is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; and the Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. G. Davey Smith is with the MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. E. Özaltin is with the Health, Nutrition and Population Global Practice, The World Bank, Washington, DC, USA.
| | - George Davey Smith
- J.M. Perkins is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; the Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and the Massachusetts General Hospital Center for Global Health, Boston, Massachusetts, USA. S.V. Subramanian is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; and the Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. G. Davey Smith is with the MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. E. Özaltin is with the Health, Nutrition and Population Global Practice, The World Bank, Washington, DC, USA
| | - Emre Özaltin
- J.M. Perkins is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; the Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and the Massachusetts General Hospital Center for Global Health, Boston, Massachusetts, USA. S.V. Subramanian is with the Harvard Center for Population and Development Studies, Cambridge, Massachusetts, USA; and the Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. G. Davey Smith is with the MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. E. Özaltin is with the Health, Nutrition and Population Global Practice, The World Bank, Washington, DC, USA.
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Ferraro KF, Schafer MH, Wilkinson LR. Childhood Disadvantage and Health Problems in Middle and Later Life: Early Imprints on Physical Health? AMERICAN SOCIOLOGICAL REVIEW 2016; 81:107-133. [PMID: 27445413 PMCID: PMC4950981 DOI: 10.1177/0003122415619617] [Citation(s) in RCA: 169] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Drawing from cumulative inequality theory, we examine the relationship between childhood disadvantage and health problems in adulthood. Using two waves of data from Midlife Development in the United States, we investigate whether childhood disadvantage is associated with adult disadvantage, including fewer social resources, and the effect of lifelong disadvantage on health problems measured at the baseline survey and a 10-year follow-up. Findings reveal that childhood socioeconomic disadvantage and frequent abuse by parents are generally associated with fewer adult social resources and more lifestyle risks. Health problems, in turn, are affected by childhood disadvantage and by lifestyle risks, especially smoking and obesity. Not only was early disadvantage related to health problems at the baseline survey, but childhood socioeconomic disadvantage and frequent abuse also were related to the development of new health problems at the follow-up survey. These findings reveal the imprint of early disadvantage on health decades later and suggest greater attention to resources, even during midlife, can interrupt the chain of risks.
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Gage SH, Munafò MR, Davey Smith G. Causal Inference in Developmental Origins of Health and Disease (DOHaD) Research. Annu Rev Psychol 2015; 67:567-85. [PMID: 26442667 DOI: 10.1146/annurev-psych-122414-033352] [Citation(s) in RCA: 108] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Studies of the developmental origins of health and disease (DOHaD) often rely on prospective observational data, from which associations between developmental exposures and outcomes in later life can be identified. Typically, conventional statistical methods are used in an attempt to mitigate problems inherent in observational data, such as confounding and reverse causality, but these have serious limitations. In this review, we discuss a variety of methods that are increasingly being used in observational epidemiological studies to help strengthen causal inference. These methods include negative controls, cross-contextual designs, instrumental variables (including Mendelian randomization), family-based studies, and natural experiments. Applications within the DOHaD framework, and in relation to behavioral, psychiatric, and psychological domains, are considered, and the considerable potential for expanding the use of these methods is outlined.
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Affiliation(s)
- Suzanne H Gage
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol BS8 2BN, United Kingdom; .,UK Center for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, United Kingdom
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol BS8 2BN, United Kingdom; .,UK Center for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol BS8 1TU, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol BS8 2BN, United Kingdom;
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23
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Gowland RL. Entangled lives: Implications of the developmental origins of health and disease hypothesis for bioarchaeology and the life course. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2015; 158:530-40. [DOI: 10.1002/ajpa.22820] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Revised: 07/04/2015] [Accepted: 07/07/2015] [Indexed: 01/02/2023]
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Relton CL, Hartwig FP, Davey Smith G. From stem cells to the law courts: DNA methylation, the forensic epigenome and the possibility of a biosocial archive. Int J Epidemiol 2015; 44:1083-93. [PMID: 26424516 PMCID: PMC5279868 DOI: 10.1093/ije/dyv198] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The growth in epigenetics continues to attract considerable cross-disciplinary interest, apparently representing an opportunity to move beyond genomics towards the goal of understanding phenotypic variability from molecular through organismal to the societal level. The epigenome may also harbour useful information about life-time exposures (measured or unmeasured) irrespective of their influence on health or disease, creating the potential for a person-specific biosocial archive . Furthermore such data may prove of use in providing identifying information, providing the possibility of a future forensic epigenome . The mechanisms involved in ensuring that environmentally induced epigenetic changes perpetuate across the life course remain unclear. Here we propose a potential role of adult stem cells in maintaining epigenetic states provides a useful basis for formulating such epidemiologically-relevant concepts.
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Affiliation(s)
- Caroline L Relton
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
| | | | - George Davey Smith
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
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26
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Affiliation(s)
- Caroline L Relton
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK and Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
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Richmond RC, Simpkin AJ, Woodward G, Gaunt TR, Lyttleton O, McArdle WL, Ring SM, Smith ADAC, Timpson NJ, Tilling K, Davey Smith G, Relton CL. Prenatal exposure to maternal smoking and offspring DNA methylation across the lifecourse: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC). Hum Mol Genet 2014; 24:2201-17. [PMID: 25552657 PMCID: PMC4380069 DOI: 10.1093/hmg/ddu739] [Citation(s) in RCA: 259] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Maternal smoking during pregnancy has been found to influence newborn DNA methylation in genes involved in fundamental developmental processes. It is pertinent to understand the degree to which the offspring methylome is sensitive to the intensity and duration of prenatal smoking. An investigation of the persistence of offspring methylation associated with maternal smoking and the relative roles of the intrauterine and postnatal environment is also warranted. In the Avon Longitudinal Study of Parents and Children, we investigated associations between prenatal exposure to maternal smoking and offspring DNA methylation at multiple time points in approximately 800 mother–offspring pairs. In cord blood, methylation at 15 CpG sites in seven gene regions (AHRR, MYO1G, GFI1, CYP1A1, CNTNAP2, KLF13 and ATP9A) was associated with maternal smoking, and a dose-dependent response was observed in relation to smoking duration and intensity. Longitudinal analysis of blood DNA methylation in serial samples at birth, age 7 and 17 years demonstrated that some CpG sites showed reversibility of methylation (GFI1, KLF13 and ATP9A), whereas others showed persistently perturbed patterns (AHRR, MYO1G, CYP1A1 and CNTNAP2). Of those showing persistence, we explored the effect of postnatal smoke exposure and found that the major contribution to altered methylation was attributed to a critical window of in utero exposure. A comparison of paternal and maternal smoking and offspring methylation showed consistently stronger maternal associations, providing further evidence for causal intrauterine mechanisms. These findings emphasize the sensitivity of the methylome to maternal smoking during early development and the long-term impact of such exposure.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Andrew J Simpkin
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Geoff Woodward
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Oliver Lyttleton
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Wendy L McArdle
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Susan M Ring
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Andrew D A C Smith
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Kate Tilling
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK and Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne NE1 3BZ, UK
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Aalen OO, Valberg M, Grotmol T, Tretli S. Understanding variation in disease risk: the elusive concept of frailty. Int J Epidemiol 2014; 44:1408-21. [PMID: 25501685 PMCID: PMC4588855 DOI: 10.1093/ije/dyu192] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2014] [Indexed: 01/10/2023] Open
Abstract
The concept of frailty plays a major role in the statistical field of survival analysis. Frailty variation refers to differences in risk between individuals which go beyond known or measured risk factors. In other words, frailty variation is unobserved heterogeneity. Although understanding frailty is of interest in its own right, the literature on survival analysis has demonstrated that existence of frailty variation can lead to surprising artefacts in statistical estimation that are important to examine. We present literature that demonstrates the presence and significance of frailty variation between individuals. We discuss the practical content of frailty variation, and show the link between frailty and biological concepts like (epi)genetics and heterogeneity in disease risk. There are numerous suggestions in the literature that a good deal of this variation may be due to randomness, in addition to genetic and/or environmental factors. Heterogeneity often manifests itself as clustering of cases in families more than would be expected by chance. We emphasize that apparently moderate familial relative risks can only be explained by strong underlying variation in disease risk between families and individuals. Finally, we highlight the potential impact of frailty variation in the interpretation of standard epidemiological measures such as hazard and incidence rates.
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Affiliation(s)
- Odd O Aalen
- Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway and Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
| | - Morten Valberg
- Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway and
| | - Tom Grotmol
- Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
| | - Steinar Tretli
- Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
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Richmond RC, Al-Amin A, Smith GD, Relton CL. Approaches for drawing causal inferences from epidemiological birth cohorts: a review. Early Hum Dev 2014; 90:769-80. [PMID: 25260961 PMCID: PMC5154380 DOI: 10.1016/j.earlhumdev.2014.08.023] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Large-scale population-based birth cohorts, which recruit women during pregnancy or at birth and follow up their offspring through infancy and into childhood and adolescence, provide the opportunity to monitor and model early life exposures in relation to developmental characteristics and later life outcomes. However, due to confounding and other limitations, identification of causal risk factors has proved challenging and published findings are often not reproducible. A suite of methods has been developed in recent years to minimise problems afflicting observational epidemiology, to strengthen causal inference and to provide greater insights into modifiable intra-uterine and early life risk factors. The aim of this review is to describe these causal inference methods and to suggest how they may be applied in the context of birth cohorts and extended along with the development of birth cohort consortia and expansion of "omic" technologies.
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Affiliation(s)
- Rebecca C Richmond
- Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK.
| | - Aleef Al-Amin
- University of Bristol Medical School, University of Bristol, Bristol, UK.
| | - George Davey Smith
- Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK.
| | - Caroline L Relton
- Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK; Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
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Kowal P, Towers A, Byles J. Ageing across the Tasman Sea: the demographics and health of older adults in Australia and New Zealand. Aust N Z J Public Health 2014; 38:377-83. [PMID: 24750537 DOI: 10.1111/1753-6405.12194] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2012] [Revised: 02/01/2013] [Accepted: 11/01/2013] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE The demographic and health aspects of ageing populations in Australia and New Zealand (NZ) are described. These data are relevant to compare impacts of policy and context in each country. METHODS Secondary analysis of international (Organization for Economic Co-operation and Development, United Nations and World Health Organization) and domestic population and health data. RESULTS Both countries will experience a greater than 80% increase in the population aged 60-plus years between 2013 and 2050. The increase in the 80-plus population will be 200% or higher, resulting in 2.8 million Australians and more than 510,000 New Zealanders in this age group by 2050. The speed of ageing in both countries is higher than the average rate of increase in developed countries. Average life expectancy at birth and age 60 is higher in Australia than NZ, with the differences increasing slightly by 2050, and gaps between men and women consistently smaller in NZ than in Australia. However, a higher proportion of older Australians report living with a disability (53%) than older New Zealanders (45%). CONCLUSIONS Australia and NZ are well aged in the context of a youthful Oceania region, with more similarities than differences between the countries. IMPLICATIONS Both countries need to continue to monitor health trends, unravel the major population attributable risks, and identify preventative and other interventions that can stimulate and support declines in disability in older populations in the future, particularly for non-indigenous older persons.
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Affiliation(s)
- Paul Kowal
- World Health Organization Study on global AGEing and adult health (SAGE), Switzerland; University of Newcastle Research Centre on Gender, Health and Ageing (Hunter Medical Research Institute), New South Wales
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Abstract
During the latter half of the twentieth century, an explosion of research elucidated a growing number of causes of disease and contributors to health. Biopsychosocial models that accounted for the wide range of factors influencing health began to replace outmoded and overly simplified biomedical models of disease causation. More recently, models of lifecourse health development (LCHD) have synthesized research from biological, behavioral and social science disciplines, defined health development as a dynamic process that begins before conception and continues throughout the lifespan, and paved the way for the creation of novel strategies aimed at optimization of individual and population health trajectories. As rapid advances in epigenetics and biological systems research continue to inform and refine LCHD models, our healthcare delivery system has struggled to keep pace, and the gulf between knowledge and practice has widened. This paper attempts to chart the evolution of the LCHD framework, and illustrate its potential to transform how the MCH system addresses social, psychological, biological, and genetic influences on health, eliminates health disparities, reduces chronic illness, and contains healthcare costs. The LCHD approach can serve to highlight the foundational importance of MCH, moving it from the margins of national debate to the forefront of healthcare reform efforts. The paper concludes with suggestions for innovations that could accelerate the translation of health development principles into MCH practice.
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Affiliation(s)
- Neal Halfon
- UCLA Center for Healthier Children, Families, and Communities, 10990 Wilshire Blvd, Suite 900, Los Angeles, CA, 90024, USA,
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Vik KL, Romundstad P, Carslake D, Smith GD, Nilsen TIL. Comparison of father-offspring and mother-offspring associations of cardiovascular risk factors: family linkage within the population-based HUNT Study, Norway. Int J Epidemiol 2013; 43:760-71. [PMID: 24366488 DOI: 10.1093/ije/dyt250] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Cardiovascular risk factors are transmitted from parents to offspring; however, the relative contributions of fathers and mothers remain unclear. If maternal exposures during pregnancy influence offspring through the intrauterine environment, associations between mothers and offspring are expected to be stronger than between fathers and offspring. In this family linkage study we compared father-offspring and mother-offspring associations of several cardiovascular risk factors. METHODS The study population consisted of 36,528 father-mother-offspring trios who participated at one or more surveys of the HUNT Study, Norway in 1984-86, 1995-97 and 2006-08. Parent-offspring associations were assessed using unstandardized and standardized residuals from linear regression analysis, and possible non-paternity was accounted for in sensitivity analyses. RESULTS Age- and sex-adjusted parent-offspring associations for anthropometric factors, blood pressure, blood lipids, blood glucose and resting heart rate were largely similar between fathers and mothers. Use of standardized values and analyses adjusted for non-paternity further emphasized this similarity. CONCLUSIONS This study found largely similar father-offspring and mother-offspring associations across all cardiovascular risk factors under study, arguing against strong maternal effects transmitted through intrauterine mechanisms.
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Affiliation(s)
- Kirsti L Vik
- Department of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UKDepartment of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Pål Romundstad
- Department of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - David Carslake
- Department of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - George Davey Smith
- Department of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Tom I L Nilsen
- Department of Human Movement Science, Norwegian University of Science and Technology, Trondheim, Norway, Liaison Committee between the Central Norway Regional Health Authority (RHA), Stjørdal, and the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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Potter C, McKay J, Groom A, Ford D, Coneyworth L, Mathers JC, Relton CL. Influence of DNMT genotype on global and site specific DNA methylation patterns in neonates and pregnant women. PLoS One 2013; 8:e76506. [PMID: 24098518 PMCID: PMC3788139 DOI: 10.1371/journal.pone.0076506] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2013] [Accepted: 08/27/2013] [Indexed: 01/11/2023] Open
Abstract
This study examines the relationship between common genetic variation within DNA methyltransferase genes and inter-individual variation in DNA methylation. Eleven polymorphisms spanning DNMT1 and DNMT3B were genotyped. Global and gene specific (IGF2, IGFBP3, ZNT5) DNA methylation was quantified by LUMA and bisulfite Pyrosequencing assays, respectively, in neonatal cord blood and in maternal peripheral blood. Associations between maternal genotype and maternal methylation (n (≈) 333), neonatal genotype and neonatal methylation (n (≈) 454), and maternal genotype and neonatal methylation (n (≈) 137) were assessed. The findings of this study provide some support to the hypothesis that genetic variation in DNA methylating enzymes influence DNA methylation at global and gene-specific levels; however observations were not robust to correction for multiple testing. More comprehensive analysis of the influence of genetic variation on global and site specific DNA methylation is warranted.
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Affiliation(s)
- Catherine Potter
- Human Nutrition Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - Jill McKay
- Human Nutrition Research Centre, Institute of Health and Society, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - Alexandra Groom
- Human Nutrition Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - Dianne Ford
- Human Nutrition Research Centre, Institute for Cell and Molecular Biology, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - Lisa Coneyworth
- Human Nutrition Research Centre, Institute for Cell and Molecular Biology, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - John C. Mathers
- Human Nutrition Research Centre, Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
| | - Caroline L. Relton
- Human Nutrition Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
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Krieger N. History, biology, and health inequities: emergent embodied phenotypes and the illustrative case of the breast cancer estrogen receptor. Am J Public Health 2013; 103:22-7. [PMID: 23153126 PMCID: PMC3518369 DOI: 10.2105/ajph.2012.300967] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/19/2012] [Indexed: 12/29/2022]
Abstract
How we think about biology--in historical, ecological, and societal context--matters for framing causes of and solutions to health inequities. Drawing on new insights from ecological evolutionary developmental biology and ecosocial theory, I question dominant gene-centric and ultimately static approaches to conceptualizing biology, using the example of the breast cancer estrogen receptor (ER). Analyzed in terms of its 4 histories--societal, individual (life course), tumor (cellular pathology), and evolutionary--the ER is revealed as a flexible characteristic of cells, tumors, individuals, and populations, with magnitudes of health inequities tellingly changing over time. This example suggests our science will likely be better served by conceptualizing disease and its biomarkers, along with changing magnitudes of health inequities, as embodied history--that is, emergent embodied phenotype, not innate biology.
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Affiliation(s)
- Nancy Krieger
- Department of Society, Human Development, and Health, School of Public Health, Harvard University, Boston, MA 02115, USA.
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Krieger N. Who and what is a "population"? Historical debates, current controversies, and implications for understanding "population health" and rectifying health inequities. Milbank Q 2012; 90:634-81. [PMID: 23216426 PMCID: PMC3530737 DOI: 10.1111/j.1468-0009.2012.00678.x] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
CONTEXT The idea of "population" is core to the population sciences but is rarely defined except in statistical terms. Yet who and what defines and makes a population has everything to do with whether population means are meaningful or meaningless, with profound implications for work on population health and health inequities. METHODS In this article, I review the current conventional definitions of, and historical debates over, the meaning(s) of "population," trace back the contemporary emphasis on populations as statistical rather than substantive entities to Adolphe Quetelet's powerful astronomical metaphor, conceived in the 1830s, of l'homme moyen (the average man), and argue for an alternative definition of populations as relational beings. As informed by the ecosocial theory of disease distribution, I then analyze several case examples to explore the utility of critical population-informed thinking for research, knowledge, and policy involving population health and health inequities. FINDINGS Four propositions emerge: (1) the meaningfulness of means depends on how meaningfully the populations are defined in relation to the inherent intrinsic and extrinsic dynamic generative relationships by which they are constituted; (2) structured chance drives population distributions of health and entails conceptualizing health and disease, including biomarkers, as embodied phenotype and health inequities as historically contingent; (3) persons included in population health research are study participants, and the casual equation of this term with "study population" should be avoided; and (4) the conventional cleavage of "internal validity" and "generalizability" is misleading, since a meaningful choice of study participants must be in relation to the range of exposures experienced (or not) in the real-world societies, that is, meaningful populations, of which they are a part. CONCLUSIONS To improve conceptual clarity, causal inference, and action to promote health equity, population sciences need to expand and deepen their theorizing about who and what makes populations and their means.
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Affiliation(s)
- Nancy Krieger
- Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA 02115, USA.
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Naess O, Stoltenberg C, Hoff DA, Nystad W, Magnus P, Tverdal A, Davey Smith G. Cardiovascular mortality in relation to birth weight of children and grandchildren in 500 000 Norwegian families. Eur Heart J 2012; 34:3427-36. [DOI: 10.1093/eurheartj/ehs298] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Relton CL, Davey Smith G. Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease. Int J Epidemiol 2012; 41:161-76. [PMID: 22422451 DOI: 10.1093/ije/dyr233] [Citation(s) in RCA: 327] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
The burgeoning interest in the field of epigenetics has precipitated the need to develop approaches to strengthen causal inference when considering the role of epigenetic mediators of environmental exposures on disease risk. Epigenetic markers, like any other molecular biomarker, are vulnerable to confounding and reverse causation. Here, we present a strategy, based on the well-established framework of Mendelian randomization, to interrogate the causal relationships between exposure, DNA methylation and outcome. The two-step approach first uses a genetic proxy for the exposure of interest to assess the causal relationship between exposure and methylation. A second step then utilizes a genetic proxy for DNA methylation to interrogate the causal relationship between DNA methylation and outcome. The rationale, origins, methodology, advantages and limitations of this novel strategy are presented.
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Affiliation(s)
- Caroline L Relton
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
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Davey Smith G. Epigenetics for the masses: more than Audrey Hepburn and yellow mice? Int J Epidemiol 2012. [DOI: 10.1093/ije/dys030] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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