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Power GM, Sanderson E, Pagoni P, Fraser A, Morris T, Prince C, Frayling TM, Heron J, Richardson TG, Richmond R, Tyrrell J, Warrington N, Davey Smith G, Howe LD, Tilling KM. Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review. Eur J Epidemiol 2024; 39:501-520. [PMID: 37938447 PMCID: PMC7616129 DOI: 10.1007/s10654-023-01032-1] [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: 05/16/2023] [Accepted: 07/21/2023] [Indexed: 11/09/2023]
Abstract
Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.
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Affiliation(s)
- Grace M Power
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Panagiota Pagoni
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tim Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Claire Prince
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jon Heron
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Jessica Tyrrell
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Nicole Warrington
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Frazer Institute, University of Queensland, Woolloongabba, Queensland, Australia
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- NIHR Bristol Biomedical Research Centre Bristol, University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Kate M Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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Steinbuch SC, Lüß AM, Eltrop S, Götte M, Kiesel L. Endometriosis-Associated Ovarian Cancer: From Molecular Pathologies to Clinical Relevance. Int J Mol Sci 2024; 25:4306. [PMID: 38673891 PMCID: PMC11050613 DOI: 10.3390/ijms25084306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/08/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
Endometriosis is a chronic condition affecting reproductive-aged women, characterized by the growth of ectopic endometrial tissue. Despite being benign, endometriosis is associated with an increased risk of certain cancers, including endometriosis-associated ovarian cancer (EAOC). Ovarian cancer is rare, but more common in women with endometriosis, particularly endometrioid and clear-cell carcinomas. Factors such as hormonal imbalance, reproductive history, environmental exposures, and genetic predisposition contribute to the malignant transformation of endometriosis. Thus, understanding potential risk factors causing malignancy is crucial. Over the past few decades, various genetic mutations, microRNAs, as well as tumor microenvironmental factors have been identified, impacting pathways like PI3K/AKT/mTOR, DNA repair mechanisms, oxidative stress, and inflammation. Thus, this review aims to summarize molecular studies involved in EAOC pathogenesis as potential therapeutic targets. However, further research is needed to better understand the molecular and environmental factors driving EAOC development, to target the susceptibility of endometriotic lesions to malignant progression, and to identify effective therapeutic strategies.
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Affiliation(s)
- Sophie Charlotte Steinbuch
- Department of Obstetrics and Gynecology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Anne-Marie Lüß
- Department of Obstetrics and Gynecology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Stephanie Eltrop
- Department of Obstetrics and Gynecology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Martin Götte
- Department of Obstetrics and Gynecology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
- Cells-in-Motion Interfaculty Centre (CiMIC), University of Münster, 48149 Münster, Germany
| | - Ludwig Kiesel
- Department of Obstetrics and Gynecology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
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Zhao B, Wang Z, Liu D, Zhang S. Genetically predicted serum testosterone and risk of gynecological disorders: a Mendelian randomization study. Front Endocrinol (Lausanne) 2023; 14:1161356. [PMID: 38075074 PMCID: PMC10710168 DOI: 10.3389/fendo.2023.1161356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 11/06/2023] [Indexed: 12/18/2023] Open
Abstract
Background Testosterone plays a key role in women, but the associations of serum testosterone level with gynecological disorders risk are inconclusive in observational studies. Methods We leveraged public genome-wide association studies to analyze the effects of four testosterone related exposure factors on nine gynecological diseases. Causal estimates were calculated by inverse variance-weighted (IVW), MR-Egger and weighted median methods. The heterogeneity test was performed on the obtained data through Cochrane's Q value, and the horizontal pleiotropy test was performed on the data through MR-Egger intercept and MR-PRESSO methods. "mRnd" online analysis tool was used to evaluate the statistical power of MR estimates. Results The results showed that total testosterone and bioavailable testosterone were protective factors for ovarian cancer (odds ratio (OR) = 0.885, P = 0.012; OR = 0.871, P = 0.005) and endometriosis (OR = 0.805, P = 0.020; OR = 0.842, P = 0.028) but were risk factors for endometrial cancer (OR = 1.549, P < 0.001; OR = 1.499, P < 0.001) and polycystic ovary syndrome (PCOS) (OR = 1.606, P = 0.019; OR = 1.637, P = 0.017). dehydroepiandrosterone sulfate (DHEAS) is a protective factor against endometriosis (OR = 0.840, P = 0.016) and premature ovarian failure (POF) (OR = 0.461, P = 0.046) and a risk factor for endometrial cancer (OR= 1.788, P < 0.001) and PCOS (OR= 1.970, P = 0.014). sex hormone-binding globulin (SHBG) is a protective factor against endometrial cancer (OR = 0.823, P < 0.001) and PCOS (OR = 0.715, P = 0.031). Conclusion Our analysis suggested causal associations between serum testosterone level and ovarian cancer, endometrial cancer, endometriosis, PCOS, POF.
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Affiliation(s)
| | | | | | - Songling Zhang
- Department of Obstetrics and Gynecology, The First Hospital of Jilin University, Changchun, China
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McGrath IM, Montgomery GW, Mortlock S. Insights from Mendelian randomization and genetic correlation analyses into the relationship between endometriosis and its comorbidities. Hum Reprod Update 2023; 29:655-674. [PMID: 37159502 PMCID: PMC10477944 DOI: 10.1093/humupd/dmad009] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 04/10/2023] [Indexed: 05/11/2023] Open
Abstract
BACKGROUND Endometriosis remains a poorly understood disease, despite its high prevalence and debilitating symptoms. The overlap in symptoms and the increased risk of multiple other traits in women with endometriosis is becoming increasingly apparent through epidemiological data. Genetic studies offer a method of investigating these comorbid relationships through the assessment of causal relationships with Mendelian randomization (MR), as well as identification of shared genetic variants and genes involved across traits. This has the capacity to identify risk factors for endometriosis as well as provide insight into the aetiology of disease. OBJECTIVE AND RATIONALE We aim to review the current literature assessing the relationship between endometriosis and other traits using genomic data, primarily through the methods of MR and genetic correlation. We critically examine the limitations of these studies in accordance with the assumptions of the utilized methods. SEARCH METHODS The PubMed database was used to search for peer-reviewed original research articles using the terms 'Mendelian randomization endometriosis' and '"genetic correlation" endometriosis'. Additionally, a Google Scholar search using the terms '"endometriosis" "mendelian randomization" "genetic correlation"' was performed. All relevant publications (n = 21) published up until 7 October 2022 were included in this review. Upon compilation of all traits with published MR and/or genetic correlation with endometriosis, additional epidemiological and genetic information on their comorbidity with endometriosis was sourced by searching for the trait in conjunction with 'endometriosis' on Google Scholar. OUTCOMES The association between endometriosis and multiple pain, gynaecological, cancer, inflammatory, gastrointestinal, psychological, and anthropometric traits has been assessed using MR analysis and genetic correlation analysis. Genetic correlation analyses provide evidence that genetic factors contributing to endometriosis are shared with multiple traits: migraine, uterine fibroids, subtypes of ovarian cancer, melanoma, asthma, gastro-oesophageal reflux disease, gastritis/duodenitis, and depression, suggesting the involvement of multiple biological mechanisms in endometriosis. The assessment of causality with MR has revealed several potential causes (e.g. depression) and outcomes (e.g. ovarian cancer and uterine fibroids) of a genetic predisposition to endometriosis; however, interpretation of these results requires consideration of potential violations of the MR assumptions. WIDER IMPLICATIONS Genomic studies have demonstrated that there is a molecular basis for the co-occurrence of endometriosis with other traits. Dissection of this overlap has identified shared genes and pathways, which provide insight into the biology of endometriosis. Thoughtful MR studies are necessary to ascertain causality of the comorbidities of endometriosis. Given the significant diagnostic delay of endometriosis of 7-11 years, determining risk factors is necessary to aid diagnosis and reduce the disease burden. Identification of traits for which endometriosis is a risk factor is important for holistic treatment and counselling of the patient. The use of genomic data to disentangle the overlap of endometriosis with other traits has provided insights into the aetiology of endometriosis.
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Affiliation(s)
- Isabelle M McGrath
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Grant W Montgomery
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Sally Mortlock
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
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McGrath IM, Montgomery GW, Mortlock S. Genomic characterisation of the overlap of endometriosis with 76 comorbidities identifies pleiotropic and causal mechanisms underlying disease risk. Hum Genet 2023; 142:1345-1360. [PMID: 37410157 PMCID: PMC10449967 DOI: 10.1007/s00439-023-02582-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/23/2023] [Indexed: 07/07/2023]
Abstract
Comorbid conditions can be driven by underlying pleiotropic and causal mechanisms that can provide insights into shared molecular and biological processes contributing to disease risk. Endometriosis is a chronic condition affecting one in nine women of reproductive age and poses many challenges including lengthy diagnostic delays and limited treatment efficacy owing to poor understanding of disease aetiology. To shed light on the underlying biological mechanisms and to identify potential risk factors, we examine the epidemiological and genomic relationship between endometriosis and its comorbidities. In the UK Biobank 292 ICD10 codes were epidemiologically correlated with endometriosis diagnosis, including gynaecological, immune, infection, pain, psychiatric, cancer, gastrointestinal, urinary, bone and cardiovascular traits. A subset of the identified comorbidities (n = 76) underwent follow-up genetic analysis. Whilst Mendelian randomisation suggested causality was not responsible for most comorbid relationships, 22 traits were genetically correlated with endometriosis, including pain, gynaecological and gastrointestinal traits, suggestive of a shared genetic background. Pleiotropic genetic variants and genes were identified using gene-based and colocalisation analysis. Shared genetic risk factors and potential target genes suggest a diverse collection of biological systems are involved in these comorbid relationships including coagulation factors, development of the female reproductive tract and cell proliferation. These findings highlight the diversity of traits with epidemiological and genomic overlap with endometriosis and implicate a key role for pleiotropy in the comorbid relationships.
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Affiliation(s)
- Isabelle M McGrath
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Grant W Montgomery
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Sally Mortlock
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
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