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Yu L, Aziz AUR, Zhang X, Li W. Investigating the causal impact of different types of physical activity on psychiatric disorders across life stages: A Mendelian randomization study. J Affect Disord 2024; 365:606-613. [PMID: 39187204 DOI: 10.1016/j.jad.2024.08.160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 08/19/2024] [Accepted: 08/23/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND Psychiatric disorders, including attention-deficit hyperactivity disorder (ADHD), depression, anxiety disorders, and dementia, manifest differently across life stages, impacting cognitive, emotional, and behavioral health. Understanding the causal relationships between various types of physical activity and these disorders is crucial for developing targeted interventions. METHODS The summary level data from GWAS was utilized to conduct a two-sample Mendelian Randomization (MR) analysis. We assessed the potential causal relationships between different types of physical activity including light do it yourself (DIY) activities, heavy DIY activities, strenuous sports, and aerobic exercises/other exercises and the prevalence of psychiatric disorders (ADHD, depression, anxiety disorders, and dementia) across different life stages. RESULTS The MR analysis showed no causal relationship between light DIY activities and any of the psychiatric disorders studied. Heavy DIY activities showed a significant negative association with anxiety disorders but no links with ADHD, depression, or dementia. Strenuous sports did not demonstrate any causal relationship with the psychiatric disorders examined. Aerobic exercises were notably correlated with a reduced risk of depression, although no significant associations were found with ADHD, anxiety disorders, or dementia. CONCLUSIONS The findings indicate that heavy DIY activities might contribute to reducing anxiety disorders, while aerobic exercises potentially lower the risk of depression. These results emphasize the potential benefits of promoting specific types of physical activity to improve mental health outcomes across different life stages. Future research could further investigate the mechanisms underlying these relationships and consider diverse populations and objective measures of physical activity.
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Affiliation(s)
- Lan Yu
- Key Laboratory for Early Diagnosis and Biotherapy of Malignant Tumors in Children and Women, Dalian Women and Children's Medical Group, Dalian, Liaoning, China
| | - Aziz Ur Rehman Aziz
- Key Laboratory for Early Diagnosis and Biotherapy of Malignant Tumors in Children and Women, Dalian Women and Children's Medical Group, Dalian, Liaoning, China
| | - Xu Zhang
- The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Wangshu Li
- Key Laboratory for Early Diagnosis and Biotherapy of Malignant Tumors in Children and Women, Dalian Women and Children's Medical Group, Dalian, Liaoning, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
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Li Z, Liu Z, Shi W, Liang X, Xu C, Zhang K, Li H, Zhang H. Eligibility for knee arthroplasty is associated with increased risk of acquired hallux valgus - a Mendelian randomized study. BMC Musculoskelet Disord 2024; 25:311. [PMID: 38649911 PMCID: PMC11034105 DOI: 10.1186/s12891-024-07458-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 04/18/2024] [Indexed: 04/25/2024] Open
Abstract
OBJECTIVE Clinically, it has been found that patients undergoing knee replacement have a high incidence of concomitant hallux valgus. In this study, we analyzed whether patients with osteoarthritis who underwent surgery and those patient who did not have surgery had an increased risk of hallux valgus by Mendelian randomization and performed reverse causal analysis. DESIGN Genomewide association study (GWAS) data for osteoarthritis, categorized by knee arthritis with joint replacement, knee arthritis without joint replacement, hip arthritis with joint replacement, and hip arthritis without joint replacement.And acquired hallux valgus were downloaded for Mendelian randomized studies. MR analysis was performed using inverse variance-weighted (IVW), weighted median, and MR-Egger methods. MR-egger regression, MR pleiotropic residuals and outliers (MR-presso), and Cochran's Q statistical methods were used to evaluate heterogeneity and pleiotropy. RESULTS The IVW results indicate that, compared to healthy individuals, patients who meet the criteria for knee osteoarthritis joint replacement surgery have a significantly higher risk of acquired hallux valgus. There were no significant causal relationships found for the remaining results. No significant heterogeneity or multiplicity was observed in all the Mr analyses. CONCLUSION Our study supports the increased risk of acquired hallux valgus in patients eligible for knee replacement. There is necessary for clinicians to be concerned about the hallux valgus status of patients undergoing knee arthroplasty.
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Affiliation(s)
- Zhijun Li
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Zhengxuan Liu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Wei Shi
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Xinyu Liang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Chunlei Xu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Kai Zhang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China
| | - Hui Li
- Department of Orthopedics, Tianjin Hospital of ITCWM Nankai Hospital, Tianjin, 300052, P. R. China
| | - Huafeng Zhang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, P. R. China.
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3
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Xu Y, Guo Y. Platelet indices and blood pressure: a multivariable mendelian randomization study. Thromb J 2023; 21:31. [PMID: 36941692 PMCID: PMC10026509 DOI: 10.1186/s12959-023-00475-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/10/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Platelet indices are blood-based parameters reflecting the activation of platelets. Previous studies have identified an association between platelet indices and blood pressure (BP). However, causal inferences are prone to bias by confounding effects and reverse causation. We performed a Mendelian randomization (MR) study to compare the causal roles between genetically determined platelet indices and BP levels. METHODS Single-nucleotide polymorphisms (SNPs) associated with platelet count (PLT), plateletcrit (PCT), mean platelet volume (MPV), platelet distribution width (PDW), and BP at the level of genome-wide significance (p < 5 × 10- 8) in the UK Biobank were used as instrumental variables. In bidirectional univariable MR analyses, inverse variance-weighted (IVW), MR‒Egger, and weighted median methods were used to obtain estimates for individual causal power. In addition, heterogeneity and sensitivity analyses were performed to examine the pleiotropy of effect estimates. Finally, multivariable MR analyses were undertaken to disentangle the comparative effects of four platelet indices on BP. RESULTS In the univariable MR analyses, increased levels of PLT and PCT were associated with higher BP, and PDW was associated with higher DBP alone. In the reverse direction, SBP had a minor influence on PLT and PCT. In multivariable MR analysis, PDW and PLT revealed an independent effect, whereas the association for PCT and MPV was insignificant after colinear correction. CONCLUSION These findings suggest that platelets and BP may affect each other. PDW and PLT are independent platelet indices influencing BP. Increased platelet activation and aggregation may be involved in the pathogenesis of hypertension, which may provide insights into evaluating thromboembolic events in people with high BP. The necessity of initiating antiplatelet therapy among hypertension groups needs further investigation.
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Affiliation(s)
- Yuhan Xu
- School of Medicine, Southeast University, Nanjing, Jiangsu Province, 210009, China
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Yijing Guo
- School of Medicine, Southeast University, Nanjing, Jiangsu Province, 210009, China.
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China.
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4
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Wade KH, Yarmolinsky J, Giovannucci E, Lewis SJ, Millwood IY, Munafò MR, Meddens F, Burrows K, Bell JA, Davies NM, Mariosa D, Kanerva N, Vincent EE, Smith-Byrne K, Guida F, Gunter MJ, Sanderson E, Dudbridge F, Burgess S, Cornelis MC, Richardson TG, Borges MC, Bowden J, Hemani G, Cho Y, Spiller W, Richmond RC, Carter AR, Langdon R, Lawlor DA, Walters RG, Vimaleswaran KS, Anderson A, Sandu MR, Tilling K, Davey Smith G, Martin RM, Relton CL. Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer. Cancer Causes Control 2022; 33:631-652. [PMID: 35274198 PMCID: PMC9010389 DOI: 10.1007/s10552-022-01562-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 02/10/2022] [Indexed: 02/08/2023]
Abstract
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.
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Affiliation(s)
- Kaitlin H Wade
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
| | - James Yarmolinsky
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Edward Giovannucci
- Departments of Nutrition and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Sarah J Lewis
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marcus R Munafò
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Fleur Meddens
- Department of Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Kimberley Burrows
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Joshua A Bell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Neil M Davies
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Daniela Mariosa
- International Agency for Research On Cancer (IARC), Lyon, France
| | | | - Emma E Vincent
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Cellular and Molecular Medicine, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Karl Smith-Byrne
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Florence Guida
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Marc J Gunter
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Eleanor Sanderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Tom G Richardson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Jack Bowden
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Research Innovation Learning and Development (RILD) Building, University of Exeter Medical School, Exeter, UK
| | - Gibran Hemani
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Yoonsu Cho
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Wes Spiller
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Alice R Carter
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Ryan Langdon
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Annie Anderson
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, Scotland, UK
| | - Meda R Sandu
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre, Bristol, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Richard M Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Caroline L Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
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Zheng J, Zhang Y, Rasheed H, Walker V, Sugawara Y, Li J, Leng Y, Elsworth B, Wootton RE, Fang S, Yang Q, Burgess S, Haycock PC, Borges MC, Cho Y, Carnegie R, Howell A, Robinson J, Thomas LF, Brumpton BM, Hveem K, Hallan S, Franceschini N, Morris AP, Köttgen A, Pattaro C, Wuttke M, Yamamoto M, Kashihara N, Akiyama M, Kanai M, Matsuda K, Kamatani Y, Okada Y, Walters R, Millwood IY, Chen Z, Davey Smith G, Barbour S, Yu C, Åsvold BO, Zhang H, Gaunt TR. Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease. Int J Epidemiol 2022; 50:1995-2010. [PMID: 34999880 PMCID: PMC8743120 DOI: 10.1093/ije/dyab203] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 09/01/2021] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included. RESULTS Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2. CONCLUSIONS Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.
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Affiliation(s)
- Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Yuemiao Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Key Laboratory of Renal Disease, Ministry of Health of China, Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, P. R. China
| | - Humaira Rasheed
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Venexia Walker
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yuka Sugawara
- Division of Nephrology and Endocrinology, The University of Tokyo Hospital, Tokyo, Japan
| | - Jiachen Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, P. R. China
| | - Yue Leng
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Benjamin Elsworth
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Si Fang
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Qian Yang
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Philip C Haycock
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Yoonsu Cho
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Rebecca Carnegie
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Amy Howell
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Jamie Robinson
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Laurent F Thomas
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ben Michael Brumpton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Thoracic Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Andrew P Morris
- Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg, Freiburg, Germany
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg, Freiburg, Germany
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization and Tohoku University Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Naoki Kashihara
- Department of Nephrology and Hypertension, Kawasaki Medical School, Kurashiki, Okayama, Japan
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masahiro Kanai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Robin Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Sean Barbour
- Division of Nephrology, University of British Columbia, Vancouver, British Columbia, Canada
- British Columbia Provincial Renal Agency, Vancouver, British Columbia, Canada
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, P. R. China
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Key Laboratory of Renal Disease, Ministry of Health of China, Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, P. R. China
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
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6
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Tall AR, Thomas DG, Gonzalez-Cabodevilla AG, Goldberg IJ. Addressing dyslipidemic risk beyond LDL-cholesterol. J Clin Invest 2022; 132:e148559. [PMID: 34981790 PMCID: PMC8718149 DOI: 10.1172/jci148559] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Despite the success of LDL-lowering drugs in reducing cardiovascular disease (CVD), there remains a large burden of residual disease due in part to persistent dyslipidemia characterized by elevated levels of triglyceride-rich lipoproteins (TRLs) and reduced levels of HDL. This form of dyslipidemia is increasing globally as a result of the rising prevalence of obesity and metabolic syndrome. Accumulating evidence suggests that impaired hepatic clearance of cholesterol-rich TRL remnants leads to their accumulation in arteries, promoting foam cell formation and inflammation. Low levels of HDL may associate with reduced cholesterol efflux from foam cells, aggravating atherosclerosis. While fibrates and fish oils reduce TRL, they have not been uniformly successful in reducing CVD, and there is a large unmet need for new approaches to reduce remnants and CVD. Rare genetic variants that lower triglyceride levels via activation of lipolysis and associate with reduced CVD suggest new approaches to treating dyslipidemia. Apolipoprotein C3 (APOC3) and angiopoietin-like 3 (ANGPTL3) have emerged as targets for inhibition by antibody, antisense, or RNAi approaches. Inhibition of either molecule lowers TRL but respectively raises or lowers HDL levels. Large clinical trials of such agents in patients with high CVD risk and elevated levels of TRL will be required to demonstrate efficacy of these approaches.
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Affiliation(s)
- Alan R. Tall
- Division of Molecular Medicine, Department of Medicine, Columbia University, New York, New York, USA
| | - David G. Thomas
- Division of Molecular Medicine, Department of Medicine, Columbia University, New York, New York, USA
| | - Ainara G. Gonzalez-Cabodevilla
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA
| | - Ira J. Goldberg
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA
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So HC, Chau CKL, Cheng YY, Sham PC. Causal relationships between blood lipids and depression phenotypes: a Mendelian randomisation analysis. Psychol Med 2021; 51:2357-2369. [PMID: 32329708 DOI: 10.1017/s0033291720000951] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The etiology of depression remains poorly understood. Changes in blood lipid levels were reported to be associated with depression and suicide, however study findings were mixed. METHODS We performed a two-sample Mendelian randomisation (MR) analysis to investigate the causal relationship between blood lipids and depression phenotypes, based on large-scale GWAS summary statistics (N = 188 577/480 359 for lipid/depression traits respectively). Five depression-related phenotypes were included, namely major depression (MD; from PGC), depressive symptoms (DS; from SSGAC), longest duration and number of episodes of low mood, and history of deliberate self-harm (DSH)/suicide (from UK Biobank). MR was conducted with inverse-variance weighted (MR-IVW), Egger and Generalised Summary-data-based MR (GSMR) methods. RESULTS There was consistent evidence that triglyceride (TG) is causally associated with DS (MR-IVW β for one-s.d. increase in TG = 0.0346, 95% CI 0.0114-0.0578), supported by MR-IVW and GSMR and multiple r2 clumping thresholds. We also observed relatively consistent associations of TG with DSH/suicide (MR-Egger OR = 2.514, CI 1.579-4.003). There was moderate evidence for positive associations of TG with MD and the number of episodes of low mood. For HDL-c, we observed moderate evidence for causal associations with DS and MD. LDL-c and TC did not show robust causal relationships with depression phenotypes, except for weak evidence that LDL-c is inversely related to DSH/suicide. We did not detect significant associations when depression phenotypes were treated as exposures. CONCLUSIONS This study provides evidence to a causal relationship between TG, and to a lesser extent, altered cholesterol levels with depression phenotypes. Further studies on its mechanistic basis and the effects of lipid-lowering therapies are warranted.
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Affiliation(s)
- Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong, Hong Kong, China
- CUHK Shenzhen Research Institute, Shenzhen, China
- Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong
- Margaret K.L. Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Carlos Kwan-Long Chau
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yu-Ying Cheng
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Pak C Sham
- Depeartment of Psychiatry, University of Hong Kong, Pok Fu Lam, Hong Kong
- Center for Genomic Sciences, University of Hong Kong, Pok Fu Lam, Hong Kong
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Prats-Uribe A, Sayols-Baixeras S, Fernández-Sanlés A, Subirana I, Carreras-Torres R, Vilahur G, Civeira F, Marrugat J, Fitó M, Hernáez Á, Elosua R. High-density lipoprotein characteristics and coronary artery disease: a Mendelian randomization study. Metabolism 2020; 112:154351. [PMID: 32891675 DOI: 10.1016/j.metabol.2020.154351] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/25/2020] [Accepted: 08/31/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND To assess whether genetically determined quantitative and qualitative HDL characteristics were independently associated with coronary artery disease (CAD). METHODS We designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I levels, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al. study, n = 24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, n = 184,305). We validated these results by defining our genetic variables in another database (METSIM, n = 8372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits and minimize potential pleiotropy, we used the Multi-trait-based Conditional & Joint analysis. RESULTS Genetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β = 0.27 [95%CI = 0.19; 0.35]), cholesterol levels in very large HDLs (β = 0.29 [95%CI = 0.17; 0.40]), and triglyceride content in very large HDLs (β = 0.14 [95%CI = 0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β = -0.076 [95%CI = -0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. CONCLUSIONS Some qualitative HDL characteristics (related to size, particle distribution, and cholesterol and triglyceride content) are related to CAD risk while HDL cholesterol levels are not.
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Affiliation(s)
- Albert Prats-Uribe
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Preventive Medicine and Public Health Unit, Parc de Salut Mar-Universitat Pompeu Fabra-ISGLOBAL, Barcelona, Spain; Centre for Statistics in Medicine, Botnar Research Centre, NDORMS, University of Oxford, Oxford, United Kingdom.
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Isaac Subirana
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Robert Carreras-Torres
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain.
| | - Gemma Vilahur
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Program-ICCC, Research Institute-Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain.
| | - Fernando Civeira
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Lipid Unit, Hospital Universitario Miguel Servet, IIS Aragon, Zaragoza, Spain.
| | - Jaume Marrugat
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Girona Heart Registre Research Group (REGICOR), IMIM, Barcelona, Spain.
| | - Montserrat Fitó
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Álvaro Hernáez
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Risk, Nutrition, and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Blanquerna School of Life Sciences, Universitat Ramon Llull, Barcelona, Spain.
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Medicine Department, Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain.
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9
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D Adams C. Circulating sphingomyelins on estrogen receptor-positive and estrogen receptor-negative breast cancer-specific survival. BREAST CANCER MANAGEMENT 2020. [DOI: 10.2217/bmt-2020-0002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Aim: This study aims to determine whether a causal relationship exists between circulating sphingomyelins and breast cancer-specific survival, since, if one does, sphingomyelins could be studied as a therapeutic target in the management of breast cancer. Patients/materials & methods: Mendelian randomization is used here to investigate whether higher levels of circulating sphingomyelins impact breast cancer-specific survival for estrogen receptor-negative (ER–) and estrogen receptor-positive (ER+) patients. Results: The results suggest a null effect of sphingomyelins for ER– breast cancer-specific survival and a protective effect for ER+ breast cancer-specific survival. Sensitivity analyses implicate low-density lipoprotein cholesterol as a potential confounder. Conclusion: Future studies should replicate and triangulate the present findings with other methods and tease out the roles of sphingomyelins and low-density lipoprotein cholesterol on breast cancer-specific survival.
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Affiliation(s)
- Charleen D Adams
- City of Hope, Beckman Research Institute, 1500 E. Duarte Road, Duarte, CA 91010, USA
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Kennedy OJ, Pirastu N, Poole R, Fallowfield JA, Hayes PC, Grzeszkowiak EJ, Taal MW, Wilson JF, Parkes J, Roderick PJ. Coffee Consumption and Kidney Function: A Mendelian Randomization Study. Am J Kidney Dis 2019; 75:753-761. [PMID: 31837886 DOI: 10.1053/j.ajkd.2019.08.025] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 08/20/2019] [Indexed: 12/21/2022]
Abstract
RATIONALE & OBJECTIVE Chronic kidney disease (CKD) is a leading cause of morbidity and mortality worldwide, with limited strategies for prevention and treatment. Coffee is a complex mixture of chemicals, and consumption has been associated with mostly beneficial health outcomes. This work aimed to determine the impact of coffee consumption on kidney function. STUDY DESIGN Genome-wide association study (GWAS) and Mendelian randomization. SETTING & PARTICIPANTS UK Biobank baseline data were used for a coffee consumption GWAS and included 227,666 participants. CKDGen Consortium data were used for kidney outcomes and included 133,814 participants (12,385 cases of CKD) of mostly European ancestry across various countries. EXPOSURE Coffee consumption. OUTCOMES Estimated glomerular filtration rate (eGFR), CKD GFR categories 3 to 5 (G3-G5; eGFR<60mL/min/1.73m2), and albuminuria. ANALYTICAL APPROACH GWAS to identify single-nucleotide polymorphisms (SNPs) associated with coffee consumption in UK Biobank and use of those SNPs in Mendelian randomization analyses of coffee consumption and kidney outcomes in CKDGen. RESULTS 2,126 SNPs were associated with coffee consumption (P<5×10-8), 25 of which were independent and available in CKDGen. Drinking an extra cup of coffee per day conferred a protective effect against CKD G3-G5 (OR, 0.84; 95% CI, 0.72-0.98; P=0.03) and albuminuria (OR, 0.81; 95% CI, 0.67-0.97; P=0.02). An extra cup was also associated with higher eGFR (β=0.022; P=1.6×10-6) after removal of 3 SNPs responsible for significant heterogeneity (Cochran Q P = 3.5×10-15). LIMITATIONS Assays used to measure creatinine and albumin varied between studies that contributed data and a sex-specific definition was used for albuminuria rather than KDIGO guideline recommendations. CONCLUSIONS This study provides evidence of a beneficial effect of coffee on kidney function. Given widespread coffee consumption and limited interventions to prevent CKD incidence and progression, this could have significant implications for global public health in view of the increasing burden of CKD worldwide.
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Affiliation(s)
- Oliver J Kennedy
- Primary Care & Population Sciences Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Robin Poole
- Primary Care & Population Sciences Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Jonathan A Fallowfield
- University of Edinburgh Centre for Inflammation Research, Queen's Medical Research Institute, Edinburgh BioQuarter, Edinburgh, United Kingdom
| | - Peter C Hayes
- University of Edinburgh Centre for Inflammation Research, Queen's Medical Research Institute, Edinburgh BioQuarter, Edinburgh, United Kingdom
| | - Eryk J Grzeszkowiak
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Maarten W Taal
- Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Nottingham, United Kingdom
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom; MRC Human Genetic Unit, Institute of Genetic and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Julie Parkes
- Primary Care & Population Sciences Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Paul J Roderick
- Primary Care & Population Sciences Faculty of Medicine, University of Southampton, Southampton, United Kingdom
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11
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Gill D, Monori G, Georgakis MK, Tzoulaki I, Laffan M. Genetically Determined Platelet Count and Risk of Cardiovascular Disease. Arterioscler Thromb Vasc Biol 2018; 38:2862-2869. [PMID: 30571169 PMCID: PMC6250250 DOI: 10.1161/atvbaha.118.311804] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 09/24/2018] [Indexed: 12/21/2022]
Abstract
Objective- Cardiovascular disease, including coronary artery disease (CAD) and ischemic stroke, is the leading cause of death worldwide. This Mendelian randomization study uses genetic variants as instruments to investigate whether there is a causal effect of genetically determined platelet count on CAD and ischemic stroke risk. Approach and Results- A genome-wide association study of 166 066 subjects was used to identify instruments and genetic association estimates for platelet count. Genetic association estimates for CAD and ischemic stroke were obtained from genome-wide association studies, including 60 801 CAD cases and 123 504 controls, and 60 341 ischemic stroke cases and 454 450 controls, respectively. The inverse-variance weighted meta-analysis of ratio method Mendelian randomization estimates was the main method used to obtain estimates for the causal effect of genetically determined platelet count on risk of cardiovascular outcomes. We found no significant Mendelian randomization effect of genetically determined platelet count on risk of CAD (odds ratio of CAD per SD unit increase in genetically determined platelet count, 1.01; 95% CI, 0.98-1.04; P=0.60). However, higher genetically determined platelet count was causally associated with an increased risk of ischemic stroke (odds ratio, 1.07; 95% CI, 1.04-1.11; P<1×10-5), including all major ischemic stroke subtypes. Similar results were obtained in sensitivity analyses more robust to the inclusion of pleiotropic genetic variants. Conclusions- This Mendelian randomization study found evidence that higher genetically determined platelet count is causally associated with higher risk of ischemic stroke.
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Affiliation(s)
- Dipender Gill
- From the Department of Biostatistics and Epidemiology (D.G., G.M.), School of Public Health, Imperial College London, United Kingdom
| | - Grace Monori
- From the Department of Biostatistics and Epidemiology (D.G., G.M.), School of Public Health, Imperial College London, United Kingdom
| | - Marios K. Georgakis
- Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University (LMU), Munich, Germany (M.K.G.)
| | - Ioanna Tzoulaki
- MRC-PHE Centre for Environment (I.T.), School of Public Health, Imperial College London, United Kingdom
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece (I.T.)
| | - Mike Laffan
- Centre for Haematology, Imperial College London, United Kingdom (M.L.)
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12
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Gill D, Monori G, Tzoulaki I, Dehghan A. Iron Status and Risk of Stroke. Stroke 2018; 49:2815-2821. [PMID: 30571402 PMCID: PMC6257507 DOI: 10.1161/strokeaha.118.022701] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 09/06/2018] [Accepted: 09/24/2018] [Indexed: 01/22/2023]
Abstract
Background and Purpose- Both iron deficiency and excess have been associated with stroke risk in observational studies. However, such associations may be attributable to confounding from environmental factors. This study uses the Mendelian randomization technique to overcome these limitations by investigating the association between genetic variants related to iron status and stroke risk. Methods- A study of 48 972 subjects performed by the Genetics of Iron Status consortium identified genetic variants with concordant relations to 4 biomarkers of iron status (serum iron, transferrin saturation, ferritin, and transferrin) that supported their use as instruments for overall iron status. Genetic estimates from the MEGASTROKE consortium were used to investigate the association between the same genetic variants and stroke risk. The 2-sample ratio method Mendelian randomization approach was used for the main analysis, with the MR-Egger and weighted median techniques used in sensitivity analyses. Results- The main results, reported as odds ratio (OR) of stroke per SD unit increase in genetically determined iron status biomarker, showed a detrimental effect of increased iron status on stroke risk (serum iron OR, 1.07; 95% CI, 1.01-1.14; [log-transformed] ferritin OR, 1.18; 95% CI, 1.02-1.36; and transferrin saturation OR, 1.06; 95% CI, 1.01-1.11). A higher transferrin, indicative of lower iron status, was also associated with decreased stroke risk (OR, 0.92; 95% CI, 0.86-0.99). Examining ischemic stroke subtypes, we found the detrimental effect of iron status to be driven by cardioembolic stroke. These results were supported in statistical sensitivity analyses more robust to the inclusion of pleiotropic variants. Conclusions- This study provides Mendelian randomization evidence that higher iron status is associated with increased stroke risk and, in particular, cardioembolic stroke. Further work is required to investigate the underlying mechanism and whether this can be targeted in preventative strategies.
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Affiliation(s)
- Dipender Gill
- From the Department of Biostatistics and Epidemiology (D.G., G.M., I.T., A.D.), Imperial College London, United Kingdom
- School of Public Health, and Department of Stroke Medicine (D.G.), Imperial College London, United Kingdom
| | - Grace Monori
- From the Department of Biostatistics and Epidemiology (D.G., G.M., I.T., A.D.), Imperial College London, United Kingdom
| | - Ioanna Tzoulaki
- From the Department of Biostatistics and Epidemiology (D.G., G.M., I.T., A.D.), Imperial College London, United Kingdom
- MRC-PHE Centre for Environment (I.T., A.D.), Imperial College London, United Kingdom
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece (I.T.)
| | - Abbas Dehghan
- From the Department of Biostatistics and Epidemiology (D.G., G.M., I.T., A.D.), Imperial College London, United Kingdom
- MRC-PHE Centre for Environment (I.T., A.D.), Imperial College London, United Kingdom
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