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Watts EL, Perez-Cornago A, Fensom GK, Smith-Byrne K, Noor U, Andrews CD, Gunter MJ, Holmes MV, Martin RM, Tsilidis KK, Albanes D, Barricarte A, Bueno-de-Mesquita HB, Cohn BA, Deschasaux-Tanguy M, Dimou NL, Ferrucci L, Flicker L, Freedman ND, Giles GG, Giovannucci EL, Haiman CA, Hankey GJ, Holly JMP, Huang J, Huang WY, Hurwitz LM, Kaaks R, Kubo T, Le Marchand L, MacInnis RJ, Männistö S, Metter EJ, Mikami K, Mucci LA, Olsen AW, Ozasa K, Palli D, Penney KL, Platz EA, Pollak MN, Roobol MJ, Schaefer CA, Schenk JM, Stattin P, Tamakoshi A, Thysell E, Tsai CJ, Touvier M, Van Den Eeden SK, Weiderpass E, Weinstein SJ, Wilkens LR, Yeap BB. Circulating insulin-like growth factors and risks of overall, aggressive and early-onset prostate cancer: a collaborative analysis of 20 prospective studies and Mendelian randomization analysis. Int J Epidemiol 2023; 52:71-86. [PMID: 35726641 PMCID: PMC9908067 DOI: 10.1093/ije/dyac124] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Previous studies had limited power to assess the associations of circulating insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs) with clinically relevant prostate cancer as a primary endpoint, and the association of genetically predicted IGF-I with aggressive prostate cancer is not known. We aimed to investigate the associations of IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 concentrations with overall, aggressive and early-onset prostate cancer. METHODS Prospective analysis of biomarkers using the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset (up to 20 studies, 17 009 prostate cancer cases, including 2332 aggressive cases). Odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression. For IGF-I, two-sample Mendelian randomization (MR) analysis was undertaken using instruments identified using UK Biobank (158 444 men) and outcome data from PRACTICAL (up to 85 554 cases, including 15 167 aggressive cases). Additionally, we used colocalization to rule out confounding by linkage disequilibrium. RESULTS In observational analyses, IGF-I was positively associated with risks of overall (OR per 1 SD = 1.09: 95% CI 1.07, 1.11), aggressive (1.09: 1.03, 1.16) and possibly early-onset disease (1.11: 1.00, 1.24); associations were similar in MR analyses (OR per 1 SD = 1.07: 1.00, 1.15; 1.10: 1.01, 1.20; and 1.13; 0.98, 1.30, respectively). Colocalization also indicated a shared signal for IGF-I and prostate cancer (PP4: 99%). Men with higher IGF-II (1.06: 1.02, 1.11) and IGFBP-3 (1.08: 1.04, 1.11) had higher risks of overall prostate cancer, whereas higher IGFBP-1 was associated with a lower risk (0.95: 0.91, 0.99); these associations were attenuated following adjustment for IGF-I. CONCLUSIONS These findings support the role of IGF-I in the development of prostate cancer, including for aggressive disease.
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Affiliation(s)
- Eleanor L Watts
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Aurora Perez-Cornago
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Georgina K Fensom
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Karl Smith-Byrne
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Urwah Noor
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Colm D Andrews
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Michael V Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Richard M Martin
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Aurelio Barricarte
- Group of Epidemiology of Cancer and Other Chronic Diseases, Navarra Public Health Institute, Pamplona, Spain
- Group of Epidemiology of Cancer and Other Chronic Diseases, Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
| | - H Bas Bueno-de-Mesquita
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Utrecht, The Netherlands
| | - Barbara A Cohn
- Child Health and Development Studies, Public Health Institute, Berkeley, CA, USA
| | - Melanie Deschasaux-Tanguy
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center, University of Paris, Bobigny, France
| | - Niki L Dimou
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | | | - Leon Flicker
- WA Centre for Health & Ageing, Medical School, University of Western Australia, Perth, WA, Australia
- Western Australian Centre for Health and Ageing, University of Western Australia, Perth, WA, Australia
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
| | - Edward L Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Graham J Hankey
- WA Centre for Health & Ageing, Medical School, University of Western Australia, Perth, WA, Australia
| | - Jeffrey M P Holly
- IGFs & Metabolic Endocrinology Group, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jiaqi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lauren M Hurwitz
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tatsuhiko Kubo
- Department of Public Health and Health Policy, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | | | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
| | - Satu Männistö
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - E Jeffrey Metter
- Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kazuya Mikami
- Departmemt of Urology, Japanese Red Cross Kyoto Daiichi Hospital, Kyoto, Japan
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anja W Olsen
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Cancer Society, Research Center, Copenhagen, Denmark
| | - Kotaro Ozasa
- Departmemt of Epidemiology, Radiation Effects Research Foundation, Hiroshima, Japan
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network, Florence, Italy
| | - Kathryn L Penney
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Michael N Pollak
- Departments of Medicine and Oncology, McGill University, Montreal, QC, Canada
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Jeannette M Schenk
- Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Pär Stattin
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Akiko Tamakoshi
- Department of Public Health, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Elin Thysell
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Chiaojung Jillian Tsai
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mathilde Touvier
- Sorbonne Paris Nord University, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center, University of Paris, Bobigny, France
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
- Department of Urology, University of CaliforniaSan Francisco, San Francisco, CA, USA
| | - Elisabete Weiderpass
- Director’s Office, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Bu B Yeap
- WA Centre for Health & Ageing, Medical School, University of Western Australia, Perth, WA, Australia
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, WA, Australia
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Watts EL, Perez‐Cornago A, Fensom GK, Smith‐Byrne K, Noor U, Andrews CD, Gunter MJ, Holmes MV, Martin RM, Tsilidis KK, Albanes D, Barricarte A, Bueno‐de‐Mesquita B, Chen C, Cohn BA, Dimou NL, Ferrucci L, Flicker L, Freedman ND, Giles GG, Giovannucci EL, Goodman GE, Haiman CA, Hankey GJ, Huang J, Huang W, Hurwitz LM, Kaaks R, Knekt P, Kubo T, Langseth H, Laughlin G, Le Marchand L, Luostarinen T, MacInnis RJ, Mäenpää HO, Männistö S, Metter EJ, Mikami K, Mucci LA, Olsen AW, Ozasa K, Palli D, Penney KL, Platz EA, Rissanen H, Sawada N, Schenk JM, Stattin P, Tamakoshi A, Thysell E, Tsai CJ, Tsugane S, Vatten L, Weiderpass E, Weinstein SJ, Wilkens LR, Yeap BB, Allen NE, Key TJ, Travis RC. Circulating free testosterone and risk of aggressive prostate cancer: Prospective and Mendelian randomisation analyses in international consortia. Int J Cancer 2022; 151:1033-1046. [PMID: 35579976 PMCID: PMC7613289 DOI: 10.1002/ijc.34116] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/18/2022] [Accepted: 02/28/2022] [Indexed: 11/30/2022]
Abstract
Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged <60 years 1.14, CI = 1.02-1.28; Phet = .0003: inverse association for older ages). Associations for free testosterone were positive for overall prostate cancer (MR: 1.20, 1.08-1.34; blood-based: 1.03, 1.01-1.05) and early-onset prostate cancer (MR: 1.37, 1.09-1.73; blood-based: 1.08, 0.98-1.19). SHBG and total testosterone were inversely associated with overall prostate cancer in blood-based analyses, with null associations in MR analysis. Our results support free testosterone, rather than total testosterone, in the development of prostate cancer, including aggressive subgroups.
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Affiliation(s)
- Eleanor L. Watts
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Aurora Perez‐Cornago
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Georgina K. Fensom
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Karl Smith‐Byrne
- Genomic Epidemiology BranchInternational Agency for Research on CancerLyonFrance
| | - Urwah Noor
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Colm D. Andrews
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Marc J. Gunter
- Section of Nutrition and MetabolismInternational Agency for Research on CancerLyonFrance
| | - Michael V. Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population HealthUniversity of OxfordOxfordUK
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUK
| | - Richard M. Martin
- Department of Population Health Sciences, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
- National Institute for Health Research (NIHR) Bristol Biomedical Research CentreUniversity Hospitals Bristol NHS Foundation Trust and Weston NHS Foundation Trust and the University of BristolBristolUK
| | - Konstantinos K. Tsilidis
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Aurelio Barricarte
- Navarra Public Health InstitutePamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
- CIBER Epidemiology and Public Health CIBERESPMadridSpain
| | - Bas Bueno‐de‐Mesquita
- Centre for Nutrition, Prevention and Health ServicesNational Institute for Public Health and the Environment (RIVM)The Netherlands
| | - Chu Chen
- Program in Epidemiology, Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleWashingtonUSA
- Department of Epidemiology, School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Department of Otolaryngology: Head and Neck Surgery, School of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Barbara A. Cohn
- Child Health and Development StudiesPublic Health InstituteBerkeleyCaliforniaUSA
| | - Niki L. Dimou
- Section of Nutrition and MetabolismInternational Agency for Research on CancerLyonFrance
| | | | - Leon Flicker
- Medical SchoolUniversity of Western AustraliaPerthWestern AustraliaAustralia
- Western Australian Centre for Health and AgeingUniversity of Western AustraliaPerthWestern AustraliaAustralia
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Graham G. Giles
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneVictoriaAustralia
- Precision Medicine, School of Clinical Sciences at Monash HealthMonash UniversityMelbourneVictoriaAustralia
| | - Edward L. Giovannucci
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Channing Division of Network MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
- Department of NutritionHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Gary E. Goodman
- Program in Epidemiology, Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of MedicineUniversity of Southern California/Norris Comprehensive Cancer CenterLos AngelesCaliforniaUSA
| | - Graeme J. Hankey
- Medical SchoolUniversity of Western AustraliaPerthWestern AustraliaAustralia
| | - Jiaqi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Wen‐Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Lauren M. Hurwitz
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Rudolf Kaaks
- Division of Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Paul Knekt
- Department of Public Health and WelfareNational Institute for Health and WelfareHelsinkiFinland
| | - Tatsuhiko Kubo
- Department of Public Health and Health Policy, Graduate School of Biomedical and Health SciencesHiroshima UniversityHiroshimaJapan
| | - Hilde Langseth
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
- Department of ResearchCancer Registry of NorwayOsloNorway
| | - Gail Laughlin
- Herbert Wertheim School of Public Health and Human Longevity ScienceUniversity of California San DiegoSan DiegoCaliforniaUSA
| | | | - Tapio Luostarinen
- Finnish Cancer RegistryInstitute for Statistical and Epidemiological Cancer ResearchHelsinkiFinland
| | - Robert J. MacInnis
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneVictoriaAustralia
| | - Hanna O. Mäenpää
- Department of OncologyHelsinki University Central HospitalHelsinkiFinland
| | - Satu Männistö
- Department of Public Health and WelfareFinnish Institute for Health and WelfareHelsinkiFinland
| | - E. Jeffrey Metter
- Department of NeurologyThe University of Tennessee Health Science Center, College of MedicineMemphisTennesseeUSA
| | - Kazuya Mikami
- Departmemt of UrologyJapanese Red Cross Kyoto Daiichi HospitalKyotoJapan
| | - Lorelei A. Mucci
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Anja W. Olsen
- Department of Public HealthAarhus UniversityAarhusDenmark
- Danish Cancer SocietyResearch CenterCopenhagenDenmark
| | - Kotaro Ozasa
- Departmemt of EpidemiologyRadiation Effects Research FoundationHiroshimaJapan
| | - Domenico Palli
- Cancer Risk Factors and Life‐Style Epidemiology Unit, Institute for Cancer ResearchPrevention and Clinical Network – ISPROFlorenceItaly
| | - Kathryn L. Penney
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Channing Division of Network MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Elizabeth A. Platz
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Harri Rissanen
- Department of Public Health and WelfareNational Institute for Health and WelfareHelsinkiFinland
| | - Norie Sawada
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Jeannette M. Schenk
- Cancer Prevention Program, Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Pär Stattin
- Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | | | - Elin Thysell
- Department of Medical BiosciencesUmeå UniversityUmeåSweden
| | - Chiaojung Jillian Tsai
- Department of Radiation OncologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Shoichiro Tsugane
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Lars Vatten
- Department of Public Health and Nursing, Faculty of MedicineNorwegian University of Science and TechnologyTrondheimNorway
| | - Elisabete Weiderpass
- Director Office, International Agency for Research on CancerWorld Health OrganizationLyonFrance
| | - Stephanie J. Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | | | - Bu B. Yeap
- Medical SchoolUniversity of Western AustraliaPerthWestern AustraliaAustralia
- Department of Endocrinology and DiabetesFiona Stanley HospitalPerthWestern AustraliaAustralia
| | | | | | | | | | | | - Naomi E. Allen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population HealthUniversity of OxfordOxfordUK
- UK Biobank LtdStockportUK
| | - Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
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Dimou NL, Papadimitriou N, Mariosa D, Johansson M, Brennan P, Peters U, Chanock SJ, Purdue M, Bishop DT, Gago‐Dominquez M, Giles GG, Moreno V, Platz EA, Tangen CM, Wolk A, Zheng W, Wu X, Campbell PT, Giovannucci E, Lin Y, Gunter MJ, Murphy N. Circulating adipokine concentrations and risk of five obesity-related cancers: A Mendelian randomization study. Int J Cancer 2021; 148:1625-1636. [PMID: 33038280 PMCID: PMC7894468 DOI: 10.1002/ijc.33338] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 08/27/2020] [Accepted: 09/17/2020] [Indexed: 12/20/2022]
Abstract
Obesity is considered a chronic inflammatory state characterized by continued secretion of adipokines and cytokines. Experimental and epidemiological evidence indicates that circulating adipokines may be associated with the development of obesity-related cancers, but it is unclear if these associations are causal or confounded. We examined potential causal associations of specific adipokines (adiponectin, leptin, soluble leptin receptor [sOB-R] and plasminogen activator inhibitor-1 [PAI-1]) with five obesity-related cancers (colorectal, pancreatic, renal cell carcinoma [RCC], ovarian and endometrial) using Mendelian randomization (MR) methods. We used summary-level data from large genetic consortia for 114 530 cancer cases and 245 284 controls. We constructed genetic instruments using 18 genetic variants for adiponectin, 2 for leptin and 4 for both sOB-R and PAI-1 (P value for inclusion<5 × 10-8 ). Causal estimates were obtained using two-sample MR methods. In the inverse-variance weighted models, we found an inverse association between adiponectin and risk of colorectal cancer (odds ratio per 1 μg/mL increment in adiponectin concentration: 0.90 [95% confidence interval = 0.84-0.97]; P = .01); but, evidence of horizontal pleiotropy was detected and the association was not present when this was taken into consideration. No association was found for adiponectin and risks of pancreatic cancer, RCC, ovarian cancer and endometrial cancer. Leptin, sOB-R and PAI-1 were also similarly unrelated to risk of obesity-related cancers. Despite the large sample size, our MR analyses do not support causal effects of circulating adiponectin, leptin, sOB-R and PAI-1 concentrations on the development of five obesity-related cancers.
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Affiliation(s)
- Niki L. Dimou
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Nikos Papadimitriou
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Daniela Mariosa
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Paul Brennan
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Ulrike Peters
- Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Mark Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | | | - Manuela Gago‐Dominquez
- Fundación Gallega de Medicina Genómica, Grupo de Genéticadel CáncerInstituto de Investigación Sanitaria de Santiago IDISComplejo Hospitalario Univ. Santiago‐CHUS, SERGAS, Santiago de CompostelaSpain
- Moores Cancer CenterUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Graham G. Giles
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneVictoriaAustralia
- Precision MedicineSchool of Clinical Sciences at Monash Health, Monash UniversityClaytonVictoriaAustralia
| | - Victor Moreno
- Oncology Data Analytics ProgramCatalan Institute of Oncology‐IDIBELL, L'Hospitalet de LlobregatBarcelonaSpain
- CIBER Epidemiología y SaludPública (CIBERESP)MadridSpain
- Department of Clinical Sciences, Faculty of MedicineUniversity of BarcelonaBarcelonaSpain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de LlobregatBarcelonaSpain
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Catherine M. Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska InstitutetStockholmSweden
- Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt‐Ingram Cancer CenterVanderbilt UniversityNashvilleTennesseeUSA
| | - Xifeng Wu
- Department of EpidemiologyThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- Department of Precision Health and Data Science, School of Public Health and the Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Peter T. Campbell
- Behavioral and Epidemiology Research Group, American Cancer SocietyAtlantaGeorgiaUSA
| | - Edward Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public HealthHarvard UniversityBostonMassachusettsUSA
- Department of NutritionT.H. Chan School of Public HealthBostonMassachusettsUSA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | | | - Marc J. Gunter
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
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Trajanoska K, Dimou NL, Karasik D, Rivadeneira F, Consirtia G. Leveraging data from bivariate genome-wide association meta-analysis to unravel novel pleitropic pathways of bone-muscle crosstalk. Bone Rep 2020. [DOI: 10.1016/j.bonr.2020.100652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Kontou PI, Braliou GG, Dimou NL, Nikolopoulos G, Bagos PG. Antibody Tests in Detecting SARS-CoV-2 Infection: A Meta-Analysis. Diagnostics (Basel) 2020; 10:E319. [PMID: 32438677 PMCID: PMC7278002 DOI: 10.3390/diagnostics10050319] [Citation(s) in RCA: 166] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 05/13/2020] [Accepted: 05/14/2020] [Indexed: 01/03/2023] Open
Abstract
The emergence of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 made imperative the need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. However, individual studies are usually inconclusive, thus, a comparison of different tests is needed. We performed a systematic review and meta-analysis in PubMed, medRxiv and bioRxiv. We used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay (ELISA), Chemiluminescence Enzyme Immunoassays (CLIA), Fluorescence Immunoassays (FIA), and the Lateral Flow Immunoassays (LFIA). We identified 38 studies containing data from 7848 individuals. Tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones and show better sensitivity when the samples were taken longer after the onset of symptoms. Moreover, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody alone. All methods yield high specificity with some of them (ELISA and LFIA) reaching levels around 99%. ELISA- and CLIA-based methods perform better in terms of sensitivity (90%-94%) followed by LFIA and FIA with sensitivities ranging from 80% to 89%. ELISA tests could be a safer choice at this stage of the pandemic. LFIA tests are more attractive for large seroprevalence studies but show lower sensitivity, and this should be taken into account when designing and performing seroprevalence studies.
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Affiliation(s)
- Panagiota I. Kontou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, 35131 Lamia, Greece; (P.I.K.); (G.G.B.)
| | - Georgia G. Braliou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, 35131 Lamia, Greece; (P.I.K.); (G.G.B.)
| | - Niki L. Dimou
- International Agency for Research on Cancer, 69372 Lyon, France;
| | | | - Pantelis G. Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, 35131 Lamia, Greece; (P.I.K.); (G.G.B.)
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Jiang X, Dimou NL, Zhu Z, Bonilla C, Lewis SJ, Lindström S, Kraft P, Tsilidis KK, Martin RM. Allergy, asthma, and the risk of breast and prostate cancer: a Mendelian randomization study. Cancer Causes Control 2020; 31:273-282. [PMID: 32006205 DOI: 10.1007/s10552-020-01271-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 01/21/2020] [Indexed: 12/23/2022]
Abstract
PURPOSE The relationship of allergic diseases, such as asthma, hay fever, and eczema, with cancer is under debate. Observational studies have reported conflicting findings, but such studies are susceptible to confounding and reverse causation. Understanding the potential role of allergy in carcinogenesis may shed new light on the biological mechanisms underpinning intrinsic immunity and cancer. METHODS We conducted a Mendelian randomization study, using germline genetic variants as instrumental variables, to determine the causal relevance of allergic disease and on two most common malignancies: breast cancer and prostate cancer. We used the summary statistics from the largest ever genome-wide association studies conducted on allergic disease (ncase = 180,129), asthma (ncase = 14,085), breast (ncase = 122,977), and prostate cancer (ncase = 79,148) and calculated odds ratios (ORs) and 95% confidence intervals (CIs) of cancer for allergic disease. RESULTS We did not observe any evidence to support a causal association between allergic disease and risk of breast cancer overall [OR 1.00 (95% CI 0.96-1.04), p = 0.95] or by subtype (estrogen receptor (ER)+ [0.99 (0.95-1.04), p = 0.71], ER- [1.05 (0.99-1.10), p = 0.11]). We also did not find any evidence for an association with prostate cancer [1.00 (0.94-1.05), p = 0.93] or advanced subtype [0.97 (0.90-1.05), p = 0.46]. Sensitivity analyses did not reveal directional pleiotropy. CONCLUSION Our study does not support a causal effect of allergic disease on the risk of breast or prostate cancer. Future studies may be conducted to focus on understanding the causal role of allergic disease in cancer prognosis or drug responses (e.g., immunotherapy).
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Affiliation(s)
- Xia Jiang
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 677 Huntington avenue, Boston, MA, 02115, USA.
- Department of Clinical Neurosciences, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden.
| | - Niki L Dimou
- Section of Nutrition and Metabolism, International Agency for Research On Cancer, Lyon, France
| | - Zhaozhong Zhu
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 677 Huntington avenue, Boston, MA, 02115, USA
| | - Carolina Bonilla
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Departamento de Medicina Preventiva, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Sarah J Lewis
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Public Health Science Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 677 Huntington avenue, Boston, MA, 02115, USA
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Richard M Martin
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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Jiang X, Dimou NL, Al-Dabhani K, Lewis SJ, Martin RM, Haycock PC, Gunter MJ, Key TJ, Eeles RA, Muir K, Neal D, Giles GG, Giovannucci EL, Stampfer M, Pierce BL, Schildkraut JM, Warren Andersen S, Thompson D, Zheng W, Kraft P, Tsilidis KK. Circulating vitamin D concentrations and risk of breast and prostate cancer: a Mendelian randomization study. Int J Epidemiol 2019; 48:1416-1424. [PMID: 30597039 PMCID: PMC6934026 DOI: 10.1093/ije/dyy284] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Observational studies have suggested an association between circulating vitamin D concentrations [25(OH)D] and risk of breast and prostate cancer, which was not supported by a recent Mendelian randomization (MR) analysis comprising 15 748 breast and 22 898 prostate-cancer cases. Demonstrating causality has proven challenging and one common limitation of MR studies is insufficient power. METHODS We aimed to determine whether circulating concentrations of vitamin D are causally associated with the risk of breast and prostate cancer, by using summary-level data from the largest ever genome-wide association studies conducted on vitamin D (N = 73 699), breast cancer (Ncase = 122 977) and prostate cancer (Ncase = 79 148). We constructed a stronger instrument using six common genetic variants (compared with the previous four variants) and applied several two-sample MR methods. RESULTS We found no evidence to support a causal association between 25(OH)D and risk of breast cancer [OR per 25 nmol/L increase, 1.02 (95% confidence interval: 0.97-1.08), P = 0.47], oestrogen receptor (ER)+ [1.00 (0.94-1.07), P = 0.99] or ER- [1.02 (0.90-1.16), P = 0.75] subsets, prostate cancer [1.00 (0.93-1.07), P = 0.99] or the advanced subtype [1.02 (0.90-1.16), P = 0.72] using the inverse-variance-weighted method. Sensitivity analyses did not reveal any sign of directional pleiotropy. CONCLUSIONS Despite its almost five-fold augmented sample size and substantially improved statistical power, our MR analysis does not support a causal effect of circulating 25(OH)D concentrations on breast- or prostate-cancer risk. However, we can still not exclude a modest or non-linear effect of vitamin D. Future studies may be designed to understand the effect of vitamin D in subpopulations with a profound deficiency.
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Affiliation(s)
- Xia Jiang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Cardiovascular Epidemiology Unit, Department of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Niki L Dimou
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
| | - Kawthar Al-Dabhani
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - Sarah J Lewis
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Richard M Martin
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Philip C Haycock
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Marc J Gunter
- Nutritional Epidemiology Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rosalind A Eeles
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Institute of Cancer Research, Royal Marsden NHS Foundation Trust, London, UK
| | - Kenneth Muir
- Institute of Population Health, University of Manchester, Manchester, UK
| | - David Neal
- Nuffield Department of Surgery, University of Oxford, Oxford, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Graham G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Edward L Giovannucci
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Meir Stampfer
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Brandon L Pierce
- Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA
- Department of Human Genetics, Comprehensive Cancer Center, The University of Chicago, Chicago, IL, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Shaneda Warren Andersen
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Deborah Thompson
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, UK
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
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Dimou NL, Papadimitriou N, Gill D, Christakoudi S, Murphy N, Gunter MJ, Travis RC, Key TJ, Fortner RT, Haycock PC, Lewis SJ, Muir K, Martin RM, Tsilidis KK. Sex hormone binding globulin and risk of breast cancer: a Mendelian randomization study. Int J Epidemiol 2019; 48:807-816. [PMID: 31143958 PMCID: PMC6659370 DOI: 10.1093/ije/dyz107] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/09/2019] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND There are observational data suggesting an inverse association between circulating concentrations of sex hormone binding globulin (SHBG) and risk of postmenopausal breast cancer. However, causality is uncertain and few studies have investigated this association by tumour receptor status. We aimed to investigate these associations under the causal framework of Mendelian randomization (MR). METHODS We used summary association estimates extracted from published genome-wide association study (GWAS) meta-analyses for SHBG and breast cancer, to perform two-sample MR analyses. Summary statistics were available for 122 977 overall breast cancer cases, of which 69 501 were estrogen receptor positive (ER+ve) and 21 468 were ER-ve, and 105 974 controls. To control for potential horizontal pleiotropy acting via body mass index (BMI), we performed multivariable inverse-variance weighted (IVW) MR as the main analysis, with the robustness of this approach further tested in sensitivity analyses. RESULTS The multivariable IVW MR analysis indicated a lower risk of overall (odds ratio [OR]: 0.94; 95% confidence interval [CI]: 0.90, 0.98; P: 0.006) and ER+ve (OR: 0.92; 95% CI: 0.87, 0.97; P: 0.003) breast cancer, and a higher risk of ER-ve disease (OR: 1.09; 95% CI: 1.00, 1.18; P: 0.047) per 25 nmol/L higher SHBG levels. Sensitivity analyses were consistent with the findings of the main analysis. CONCLUSIONS We corroborated the previous literature evidence coming from observational studies for a potentially causal inverse association between SHBG concentrations and risk of ER+ve breast cancer, but our findings also suggested a potential novel positive association with ER-ve disease that warrants further investigation, given the low prior probability of being true.
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Affiliation(s)
- Niki L Dimou
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Nikos Papadimitriou
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Transplantation, King's College London, London, UK
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Tim J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Renee T Fortner
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Philip C Haycock
- Bristol Medical School, Department of Population Health, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Sarah J Lewis
- Bristol Medical School, Department of Population Health, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester, UK and
| | - Richard M Martin
- Bristol Medical School, Department of Population Health, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, and the University of Bristol, Bristol, UK
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
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Pagoni P, Dimou NL, Murphy N, Stergiakouli E. Using Mendelian randomisation to assess causality in observational studies. Evid Based Ment Health 2019; 22:67-71. [PMID: 30979719 PMCID: PMC10270458 DOI: 10.1136/ebmental-2019-300085] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Mendelian randomisation (MR) is a technique that aims to assess causal effects of exposures on disease outcomes. The paper aims to present the main assumptions that underlie MR, the statistical methods used to estimate causal effects and how to account for potential violations of the key assumptions. METHODS We discuss the key assumptions that should be satisfied in an MR setting. We list the statistical methodologies used in two-sample MR when summary data are available to estimate causal effects (ie, Wald ratio estimator, inverse-variance weighted and maximum likelihood method) and identify/adjust for potential violations of MR assumptions (ie, MR-Egger regression and weighted Median approach). We also present statistical methods and graphical tools used to evaluate the presence of heterogeneity. RESULTS We use as an illustrative example of a published two-sample MR study, investigating the causal association of body mass index with three psychiatric disorders (ie, bipolar disorder, schizophrenia and major depressive disorder). We highlight the importance of assessing the results of all available methods rather than each method alone. We also demonstrate the impact of heterogeneity in the estimation of the causal effects. CONCLUSIONS MR is a useful tool to assess causality of risk factors in medical research. Assessment of the key assumptions underlying MR is crucial for a valid interpretation of the results.
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Affiliation(s)
- Panagiota Pagoni
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Niki L Dimou
- International Agency for Research on Cancer, Lyon, France
| | - Neil Murphy
- International Agency for Research on Cancer, Lyon, France
| | - Evie Stergiakouli
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
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Abstract
Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.
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Affiliation(s)
- Niki L Dimou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.,Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Katerina G Pantavou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Georgia G Braliou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Pantelis G Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.
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11
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Tsiara CG, Nikolopoulos GK, Dimou NL, Pantavou KG, Bagos PG, Mensah B, Talias M, Braliou GG, Paraskeva D, Bonovas S, Hatzakis A. Interleukin gene polymorphisms and susceptibility to HIV-1 infection: a meta-analysis. J Genet 2018; 97:235-251. [PMID: 29666343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Some subjects are repeatedly exposed to human immunodeficiency virus (HIV), yet they remain uninfected. This suggests the existence of host-resistance mechanisms. The current study synthesizes the evidence regarding the association between interleukin (IL) gene polymorphisms and HIV susceptibility. Medline, Scopus and the Web of Science databases were systematically searched, and a meta-analysis of case-control studies was conducted. Univariate and bivariate methods were used. The literature search identified 42 eligible studies involving 15,727 subjects. Evidence was obtained on eight single-nucleotide polymorphisms (SNPs): IL1A -889 C>T (rs1800587), IL1B +3953/4 C>T (rs1143634), IL4 -589/90 C>T (rs2243250), IL6 -174 G>C (rs1800795), IL10 -592 C>A (rs1800872), IL10-1082 A>G (rs1800896), IL12B -1188 A>C (rs3212227) and IL28B C>T (rs12979860). The IL1B +3953/4 C>T variant appears to increase the risk of HIV acquisition, under the assumption of a recessive genetic model (odds ratio (OR): 4.47, 95% CI: 2.35-8.52). The AA homozygotes of the IL10 -592 C>A SNP had an increased, marginally nonsignificant, risk (OR: 1.39, 95% CI: 0.97-2.01). It reached, however, significance in sub analyses (OR: 1.49, 95% CI: 1.04-2.12). Finally, the well-studied hepatitis C virus (HCV) infection IL28B (rs12979860) CT/TT genotypes were associated with a 27% decrease in HIV infection risk, especially in populations infected with HCV (OR: 0.73, 95% CI: 0.57-0.95). Interleukin signalling is perhaps important in HIV infection and some interleukin genetic variants may affect the risk of HIV acquisition. Approaches targeting specific genes and genome wide association studies should be conducted to decipher the effect of these polymorphisms.
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Affiliation(s)
- Chrissa G Tsiara
- Hellenic Centre for Disease Control and Prevention, 15123 Athens, Greece. ,
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12
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Abstract
Mendelian randomization (MR) is becoming a popular approach to estimate the causal effect of an exposure on an outcome overcoming limitations of observational epidemiology. The advent of genome-wide association studies and the increasing accumulation of summarized data from large genetic consortia make MR a powerful technique. In this review, we give a primer in MR methodology, describe efficient MR designs and analytical strategies, and focus on methods and practical guidance for conducting an MR study using summary association data. We show that the analysis is straightforward utilizing either the MR-base platform or available packages in R. However, further research is required for the development of specialized methodology to assess MR assumptions.
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Affiliation(s)
- Niki L Dimou
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. .,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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13
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Dimitrakopoulou VI, Tsilidis KK, Haycock PC, Dimou NL, Al-Dabhani K, Martin RM, Lewis SJ, Gunter MJ, Mondul A, Shui IM, Theodoratou E, Nimptsch K, Lindström S, Albanes D, Kühn T, Key TJ, Travis RC, Vimaleswaran KS, Kraft P, Pierce BL, Schildkraut JM. Circulating vitamin D concentration and risk of seven cancers: Mendelian randomisation study. BMJ 2017; 359:j4761. [PMID: 29089348 PMCID: PMC5666592 DOI: 10.1136/bmj.j4761] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/26/2017] [Indexed: 12/12/2022]
Abstract
Objective To determine if circulating concentrations of vitamin D are causally associated with risk of cancer.Design Mendelian randomisation study.Setting Large genetic epidemiology networks (the Genetic Associations and Mechanisms in Oncology (GAME-ON), the Genetic and Epidemiology of Colorectal Cancer Consortium (GECCO), and the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortiums, and the MR-Base platform).Participants 70 563 cases of cancer (22 898 prostate cancer, 15 748 breast cancer, 12 537 lung cancer, 11 488 colorectal cancer, 4369 ovarian cancer, 1896 pancreatic cancer, and 1627 neuroblastoma) and 84 418 controls.Exposures Four single nucleotide polymorphisms (rs2282679, rs10741657, rs12785878 and rs6013897) associated with vitamin D were used to define a multi-polymorphism score for circulating 25-hydroxyvitamin D (25(OH)D) concentrations.Main outcomes measures The primary outcomes were the risk of incident colorectal, breast, prostate, ovarian, lung, and pancreatic cancer and neuroblastoma, which was evaluated with an inverse variance weighted average of the associations with specific polymorphisms and a likelihood based approach. Secondary outcomes based on cancer subtypes by sex, anatomic location, stage, and histology were also examined.Results There was little evidence that the multi-polymorphism score of 25(OH)D was associated with risk of any of the seven cancers or their subtypes. Specifically, the odds ratios per 25 nmol/L increase in genetically determined 25(OH)D concentrations were 0.92 (95% confidence interval 0.76 to 1.10) for colorectal cancer, 1.05 (0.89 to 1.24) for breast cancer, 0.89 (0.77 to 1.02) for prostate cancer, and 1.03 (0.87 to 1.23) for lung cancer. The results were consistent with the two different analytical approaches, and the study was powered to detect relative effect sizes of moderate magnitude (for example, 1.20-1.50 per 25 nmol/L decrease in 25(OH)D for most primary cancer outcomes. The Mendelian randomisation assumptions did not seem to be violated.Conclusions There is little evidence for a linear causal association between circulating vitamin D concentration and risk of various types of cancer, though the existence of causal clinically relevant effects of low magnitude cannot be ruled out. These results, in combination with previous literature, provide evidence that population-wide screening for vitamin D deficiency and subsequent widespread vitamin D supplementation should not currently be recommended as a strategy for primary cancer prevention.
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Affiliation(s)
- Vasiliki I Dimitrakopoulou
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
- School of Mathematics and Statistics, University College Dublin, Dublin, Ireland
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Philip C Haycock
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Niki L Dimou
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
| | - Kawthar Al-Dabhani
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Nutritional Biomedical Research Unit, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Sarah J Lewis
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Marc J Gunter
- International Agency for Research on Cancer, Lyon, France
| | - Alison Mondul
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Irene M Shui
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Evropi Theodoratou
- Centre of Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburg, Edinburgh, UK
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Centre for Molecular Medicine (MDC), Berlin, Germany
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Karani Santhanakrishnan Vimaleswaran
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, UK
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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Dimou NL, Pantavou KG, Bagos PG. Apolipoprotein E Polymorphism and Left Ventricular Failure in Beta-Thalassemia: A Multivariate Meta-Analysis. Ann Hum Genet 2017; 81:213-223. [DOI: 10.1111/ahg.12203] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2016] [Accepted: 06/05/2017] [Indexed: 01/06/2023]
Affiliation(s)
- Niki L. Dimou
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
| | - Katerina G. Pantavou
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
| | - Pantelis G. Bagos
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
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15
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Dimou NL, Tsirigos KD, Elofsson A, Bagos PG. GWAR: Robust Analysis and Meta-Analysis of Genome-Wide Association Studies. Bioinformatics 2017; 33:1521-1527. [DOI: 10.1093/bioinformatics/btx008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 01/10/2017] [Indexed: 11/12/2022] Open
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16
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Kontou PI, Pavlopoulou A, Dimou NL, Pavlopoulos GA, Bagos PG. Network analysis of genes and their association with diseases. Gene 2016; 590:68-78. [PMID: 27265032 DOI: 10.1016/j.gene.2016.05.044] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 05/20/2016] [Accepted: 05/30/2016] [Indexed: 12/21/2022]
Abstract
A plethora of network-based approaches within the Systems Biology universe have been applied, to date, to investigate the underlying molecular mechanisms of various human diseases. In the present study, we perform a bipartite, topological and clustering graph analysis in order to gain a better understanding of the relationships between human genetic diseases and the relationships between the genes that are implicated in them. For this purpose, disease-disease and gene-gene networks were constructed from combined gene-disease association networks. The latter, were created by collecting and integrating data from three diverse resources, each one with different content covering from rare monogenic disorders to common complex diseases. This data pluralism enabled us to uncover important associations between diseases with unrelated phenotypic manifestations but with common genetic origin. For our analysis, the topological attributes and the functional implications of the individual networks were taken into account and are shortly discussed. We believe that some observations of this study could advance our understanding regarding the etiology of a disease with distinct pathological manifestations, and simultaneously provide the springboard for the development of preventive and therapeutic strategies and its underlying genetic mechanisms.
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Affiliation(s)
- Panagiota I Kontou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece
| | - Athanasia Pavlopoulou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece
| | - Niki L Dimou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece
| | - Georgios A Pavlopoulos
- Lawrence Berkeley Lab, Joint Genome Institute, United States Department of Energy, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA
| | - Pantelis G Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece.
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17
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Dimou NL, Adam M, Bagos PG. A multivariate method for meta-analysis and comparison of diagnostic tests. Stat Med 2016; 35:3509-23. [DOI: 10.1002/sim.6919] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Revised: 01/10/2016] [Accepted: 01/31/2016] [Indexed: 11/08/2022]
Affiliation(s)
- Niki L. Dimou
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
| | - Maria Adam
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
| | - Pantelis G. Bagos
- Department of Computer Science and Biomedical Informatics; University of Thessaly; Papasiopoulou 2-4 Lamia 35100 Greece
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18
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Tsiara CG, Nikolopoulos GK, Dimou NL, Bagos PG, Saroglou G, Velonakis E, Hatzakis A. Effect of hepatitis C virus on immunological and virological responses in HIV-infected patients initiating highly active antiretroviral therapy: a meta-analysis. J Viral Hepat 2013; 20:715-24. [PMID: 24010646 DOI: 10.1111/jvh.12101] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2012] [Accepted: 02/27/2013] [Indexed: 01/25/2023]
Abstract
Co-infection of human immunodeficiency virus (HIV) with hepatitis C virus (HCV) is rather common. In the era of highly active antiretroviral therapy (HAART), viral hepatitis could result in adverse outcomes in HIV+ patients. The current meta-analysis aims to evaluate the impact of HCV on immunological and virological responses after HAART initiation in HIV/HCV co-infected individuals by synthesizing the existing scientific evidence. A comprehensive search of electronic databases was performed. Eligible studies were analysed using univariate and multivariate meta-analytic methods. Totally, 21 studies involving 22533 individuals were eligible. The estimated summary difference in CD4 cell counts increase between HIV and HIV/HCV co-infected subjects after 3-12 months on HAART was 34.86 cells/mm(3) [95% confidence interval (CI): 16.82-52.89]. The difference was more prominent in patients with baseline CD4 counts below 350 cells/mm(3) (38.97, 95% CI: 20.00-57.93) and attenuated 2 years later (13.43, 95% CI: 0.83-26.04). The analysis of ratio measures yielded similar findings. The virological control remained unaffected by the presence of HCV (adjusted Hazard Ratio for co-infected patients vs those with HIV alone: 0.99, 95% CI: 0.91-1.07). The bivariate meta-analytic method confirmed the results of the univariate approaches. This meta-analysis supports the adverse effect of HCV on immune recovery of HIV+ patients initiating HAART, especially of those with initially impaired immunologic status. Although this effect diminishes over time, early administration of HAART in the setting of co-infection seems to be justified.
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Affiliation(s)
- C G Tsiara
- Hellenic Centre for Disease Control and Prevention, Athens, Greece
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19
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Nikolopoulos GK, Masgala A, Tsiara C, Limitsiou OK, Karnaouri AC, Dimou NL, Bagos PG. Cytokine gene polymorphisms in multiple sclerosis: a meta-analysis of 45 studies including 7379 cases and 8131 controls. Eur J Neurol 2011; 18:944-51. [PMID: 21299734 DOI: 10.1111/j.1468-1331.2011.03355.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- G K Nikolopoulos
- Hellenic Centre for Diseases Control and Prevention, Athens, Greece
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20
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Dimou NL, Nikolopoulos GK, Hamodrakas SJ, Bagos PG. Fcgamma receptor polymorphisms and their association with periodontal disease: a meta-analysis. J Clin Periodontol 2010; 37:255-65. [PMID: 20149216 DOI: 10.1111/j.1600-051x.2009.01530.x] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
AIM A systematic review and a meta-analysis were conducted in order to investigate the potential association of Fcgamma receptor (FcgammaR) polymorphisms with susceptibility to aggressive and chronic periodontal disease. MATERIALS AND METHODS A database search yielded a total of 17 studies involving 1685 cases and 1570 controls. Three polymorphisms were included in the meta-analysis: FcgammaRIIA H131R (rs1801274), FcgammaRIIIA F158V (rs396991) and FcgammaRIIIB NA1/NA2. Random-effect models were used in the analysis. Odds ratios (ORs) along with their 95% confidence intervals (CIs) were computed to compare the distribution of alleles and genotypes between cases and controls. RESULTS AND CONCLUSIONS The FcgammaRIIIB NA1/NA2 polymorphism was associated with both aggressive (per-allele OR 2.005, 95% CI: 1.044, 3.851) and chronic periodontitis (recessive contrast NA2NA2 versus NA1NA1+NA1NA2 OR 1.397, 95% CI: 1.039, 1.878). The analysis showed weak evidence for association between the FcgammaRIIA H131R polymorphism and aggressive periodontitis in Asians (R versus H allele OR 1.579, 95% CI: 1.025, 2.432). On the contrary, no relationship was identified between FcgammaRIIIA F158V and periodontal disease. Accumulating evidence from basic research makes the suggested association between FcgammaRIIIB NA1/NA2 polymorphism and periodontitis biologically plausible. Further research, however, is needed in order to assess possible gene-gene or gene-environment interactions (i.e. with smoking).
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Affiliation(s)
- Niki L Dimou
- Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens, Greece
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21
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Ioannidis A, Ikonomi E, Dimou NL, Douma L, Bagos PG. Polymorphisms of the insulin receptor and the insulin receptor substrates genes in polycystic ovary syndrome: a Mendelian randomization meta-analysis. Mol Genet Metab 2010; 99:174-83. [PMID: 19926323 DOI: 10.1016/j.ymgme.2009.10.013] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2009] [Revised: 10/17/2009] [Accepted: 10/18/2009] [Indexed: 01/21/2023]
Abstract
Polycystic ovary syndrome (PCOS) is a heterogeneous condition with unknown aetiology which is considered to be the most common endocrine disorder in women of reproductive age. In this work we investigated the association of insulin receptor (IotaNSR) and insulin receptor substrates (IRSs) polymorphisms with the risk of developing PCOS. The meta-analysis of eleven studies (889 cases, 1303 controls) yielded a significant association for IRS-1 Gly972Arg (G972R) polymorphism concerning the GR vs. GG genotype (OR: 1.77, 95% CI: 1.28, 2.45), with no between-studies heterogeneity. Concerning IotaNSR His1058 C/T, the meta-analysis of eight studies (795 cases, 576 controls) found no significant evidence for association with PCOS (OR for the TT+CT vs. CC comparison equal to 1.28 with 95% CI: 0.88, 1.85) and a moderate between studies variability (I(2)=44.6%). No evidence for publication bias was found in these meta-analyses. Following a multivariate Mendelian randomization approach, the overall OR was unaffected but the overall mean difference of fasting insulin levels between carriers of GR and RR genotypes in controls was significant (2.18, 95% CI: 0.36, 4.01). These results suggest that IRS-1 Gly972Arg polymorphism is significantly associated with the risk of developing PCOS and that this association is primarily mediated by increasing the levels of fasting insulin. The particular polymorphism is located in a region nearby two phosphorylation sites that interact physically with INSR and PI 3-kinase and there is enough evidence from the literature suggesting that the Arg972 variant is associated with decreased PI 3-kinase activity and impaired insulin-stimulated signaling.
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Affiliation(s)
- Anastasios Ioannidis
- Department of Computer Science and Biomedical Informatics, University of Central Greece, Papasiopoulou 2-4, 351 00 Lamia, Greece
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Nikolopoulos GK, Dimou NL, Hamodrakas SJ, Bagos PG. Cytokine gene polymorphisms in periodontal disease: a meta-analysis of 53 studies including 4178 cases and 4590 controls. J Clin Periodontol 2008; 35:754-67. [DOI: 10.1111/j.1600-051x.2008.01298.x] [Citation(s) in RCA: 134] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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