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Han S, Yao J, Yamazaki H, Streicher SA, Rao J, Nianogo RA, Zhang Z, Huang BZ. Genetically Determined Circulating Lactase/Phlorizin Hydrolase Concentrations and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study. Nutrients 2024; 16:808. [PMID: 38542719 PMCID: PMC10975724 DOI: 10.3390/nu16060808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/06/2024] [Accepted: 03/10/2024] [Indexed: 04/01/2024] Open
Abstract
Previous research has found that milk is associated with a decreased risk of colorectal cancer (CRC). However, it is unclear whether the milk digestion by the enzyme lactase-phlorizin hydrolase (LPH) plays a role in CRC susceptibility. Our study aims to investigate the direct causal relationship of CRC risk with LPH levels by applying a two-sample Mendelian Randomization (MR) strategy. Genetic instruments for LPH were derived from the Fenland Study, and CRC-associated summary statistics for these instruments were extracted from the FinnGen Study, PLCO Atlas Project, and Pan-UK Biobank. Primary MR analyses focused on a cis-variant (rs4988235) for LPH levels, with results integrated via meta-analysis. MR analyses using all variants were also undertaken. This analytical approach was further extended to assess CRC subtypes (colon and rectal). Meta-analysis across the three datasets illustrated an inverse association between genetically predicted LPH levels and CRC risk (OR: 0.92 [95% CI, 0.89-0.95]). Subtype analyses revealed associations of elevated LPH levels with reduced risks for both colon (OR: 0.92 [95% CI, 0.89-0.96]) and rectal cancer (OR: 0.92 [95% CI, 0.87, 0.98]). Consistency was observed across varied analytical methods and datasets. Further exploration is warranted to unveil the underlying mechanisms and validate LPH's potential role in CRC prevention.
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Affiliation(s)
- Sihao Han
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (J.Y.); (J.R.); (R.A.N.); (Z.Z.)
| | - Jiemin Yao
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (J.Y.); (J.R.); (R.A.N.); (Z.Z.)
| | - Hajime Yamazaki
- Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto 606-8303, Japan;
- Center for Innovative Research for Communities and Clinical Excellence (CiRC2LE), Fukushima Medical University, Fukushima 960-1295, Japan
| | - Samantha A. Streicher
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI 96813, USA;
| | - Jianyu Rao
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (J.Y.); (J.R.); (R.A.N.); (Z.Z.)
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Roch A. Nianogo
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (J.Y.); (J.R.); (R.A.N.); (Z.Z.)
| | - Zuofeng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (J.Y.); (J.R.); (R.A.N.); (Z.Z.)
| | - Brian Z. Huang
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA;
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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Slurink IA, Corpeleijn E, Bakker SJ, Jongerling J, Kupper N, Smeets T, Soedamah-Muthu SS. Dairy consumption and incident prediabetes: prospective associations and network models in the large population-based Lifelines Study. Am J Clin Nutr 2023; 118:1077-1090. [PMID: 37813340 DOI: 10.1016/j.ajcnut.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 08/21/2023] [Accepted: 10/04/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND Evidence on associations between dairy consumption and incident prediabetes is inconsistent. One potential explanation for heterogeneity is that health behavior and food intake covary with the consumption of various high-fat and low-fat dairy types. OBJECTIVE The objective was to investigate the associations of total dairy and dairy types with incident prediabetes and to assess how dairy intake is linked with metabolic risk factors, lifestyle behaviors, and foods, as potential explanations for these associations. METHODS Overall, 74,132 participants from the prospective population-based Lifelines study were included (mean age, 45.5 ± 12.3 y; 59.7% female). Baseline dairy intake was measured using a validated food frequency questionnaire. Prediabetes at follow-up was defined based on the World Health Organization/International Expert Committee criteria as fasting plasma glucose of 110-125 mg/dL or glycated hemoglobin concentrations of 6.0%-6.5%. Associations were analyzed using Poisson regression models adjusted for social demographics, lifestyle behaviors, family history of diabetes, and food group intake. Interconnections were assessed with mixed graphical model networks. RESULTS At a mean follow-up of 4.1 ± 1.1 y, 2746 participants developed prediabetes (3.7%). In regression analyses, neutral associations were found for most dairy types. Intake of plain milk and low-fat milk were associated with a higher risk of prediabetes in the top compared with bottom quartiles (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.05, 1.30; P-trend = 0.04 and RR: 1.18; 95% CI: 1.06, 1.31; P-trend =0.01). Strong but nonsignificant effect estimates for high-fat yogurt in relation to prediabetes were found (RRservings/day: 0.80; 95% CI: 0.64, 1.01). The network analysis showed that low-fat milk clustered with energy-dense foods, including bread, meat, and high-fat cheese, whereas high-fat yogurt had no clear link with lifestyle risk factors and food intake. CONCLUSIONS In this large cohort of Dutch adults, low-fat milk intake was associated with higher prediabetes risk. Heterogeneous associations by dairy type and fat content might partly be attributed to confounding caused by behaviors and food intake related to dairy intake.
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Affiliation(s)
- Isabel Al Slurink
- Center of Research on Psychological disorders and Somatic diseases (CoRPS), Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands.
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stephan Jl Bakker
- Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Joran Jongerling
- Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands
| | - Nina Kupper
- Center of Research on Psychological disorders and Somatic diseases (CoRPS), Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands
| | - Tom Smeets
- Center of Research on Psychological disorders and Somatic diseases (CoRPS), Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands
| | - Sabita S Soedamah-Muthu
- Center of Research on Psychological disorders and Somatic diseases (CoRPS), Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands; Institute for Food, Nutrition and Health, University of Reading, Reading, United Kingdom
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Zhang S, Meng G, Zhang Q, Liu L, Wu H, Gu Y, Wang X, Zhang J, Sun S, Wang X, Zhou M, Jia Q, Song K, Borné Y, Sonestedt E, Ma L, Qi L, Niu K. Dairy intake and risk of type 2 diabetes: results of a large prospective cohort. Food Funct 2023; 14:9695-9706. [PMID: 37811566 DOI: 10.1039/d3fo02023a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Background and aims: Previous studies of primarily Western populations have consistently documented a lower risk of type 2 diabetes (T2D) among people with a higher yogurt intake, but an inconsistent association with milk intake. However, little is known about the association between dairy intake and risk of T2D among Chinese adults who consume considerably less dairy (mainly milk and yogurt) compared with Western populations. The aim is to investigate the associations of dairy intake with the risk of incident T2D in the general adult population in China. Methods: This cohort study consisted of 22 843 participants without prevalent cardiovascular disease, cancer, or diabetes at the baseline. Dietary data were collected using a validated food frequency questionnaire at the baseline (2013-2018); dairy intake was categorized into tertiles after zero consumers were taken as the reference. Incident T2D was ascertained by medical examinations and self-report of physician-diagnosed diabetes during follow-up visits. Cox proportional hazards models were performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results: In total, 735 incident T2D cases were recorded over a median follow-up of 4.0 years. Relative to zero consumers, the HRs (95% CIs) for incident T2D among participants in the highest tertiles were 0.70 (0.57, 0.87) for total dairy, 0.73 (0.60, 0.90) for milk, and 0.81 (0.66, 1.00) for yogurt. Such associations were slightly attenuated by additional adjustment for the body mass index. In addition, such inverse associations were robust in sensitivity analyses and consistent in most of the subgroups defined by baseline characteristics. Conclusion: Higher intakes of total dairy, milk, and yogurt were all associated with a lower risk of T2D among Chinese adults.
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Affiliation(s)
- Shunming Zhang
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
| | - Ge Meng
- School of Public Health of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Qing Zhang
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Li Liu
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Hongmei Wu
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yeqing Gu
- Nutrition and Radiation Epidemiology Research Center, Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Xuena Wang
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Juanjuan Zhang
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shaomei Sun
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Xing Wang
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Ming Zhou
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Qiyu Jia
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Kun Song
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
| | - Yan Borné
- Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Emily Sonestedt
- Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Le Ma
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kaijun Niu
- School of Public Health of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
- Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
- Nutrition and Radiation Epidemiology Research Center, Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
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Watling CZ, Kelly RK, Dunneram Y, Knuppel A, Piernas C, Schmidt JA, Travis RC, Key TJ, Perez-Cornago A. Associations of intakes of total protein, protein from dairy sources, and dietary calcium with risks of colorectal, breast, and prostate cancer: a prospective analysis in UK Biobank. Br J Cancer 2023; 129:636-647. [PMID: 37407836 PMCID: PMC10421858 DOI: 10.1038/s41416-023-02339-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 06/06/2023] [Accepted: 06/19/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Evidence concerning intakes of protein or sources of dairy protein and risks of colorectal, breast, and prostate cancers is inconclusive. METHODS Using a subsample of UK Biobank participants who completed ≥2 (maximum of 5) 24-h dietary assessments, we estimated intakes of total protein, protein from total dairy products, milk, and cheese, and dietary calcium in 114,217 participants. Hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using multivariable-adjusted Cox regression. RESULTS After a median of 9.4 years of follow-up, 1193 colorectal, 2024 female breast, and 2422 prostate cancer cases were identified. There were inverse associations of total dairy protein, protein from milk, and dietary calcium intakes with colorectal cancer incidence (HRQ4 vs Q1:0.80, 95% CI: 0.67-0.94; 0.79, 0.67-0.94; 0.71, 0.58-0.86, respectively). We also observed positive associations of milk protein and dietary calcium with prostate cancer risk (HRQ4 vs Q1:1.12, 1.00-1.26 and 1.16, 1.01-1.33, respectively). No significant associations were observed between intake of dairy protein and breast cancer risk. When insulin-like growth factor-I concentrations measured at recruitment were added to the multivariable-adjusted models, associations remained largely unchanged. Analyses were also similar when looking at total grams of dairy products, milk, and cheese. CONCLUSION Further research is needed to understand the mechanisms underlying the relationships of dairy products with cancer risk and the potential roles of dietary protein and calcium.
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Affiliation(s)
- Cody Z Watling
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
| | - Rebecca K Kelly
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yashvee Dunneram
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Anika Knuppel
- MRC Unit of Lifelong Health and Ageing, University College London, London, United Kingdom
| | - Carmen Piernas
- Nuffield Department of Primary Care, University of Oxford, Oxford, United Kingdom
| | - Julie A Schmidt
- Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Aurora Perez-Cornago
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
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Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res 2023; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.3] [Citation(s) in RCA: 150] [Impact Index Per Article: 150.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 08/08/2023] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
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Jensen CF, Timofeeva M, Berg-Beckhoff G. Milk consumption and the risk of type 2 diabetes: A systematic review of Mendelian randomization studies. Nutr Metab Cardiovasc Dis 2023; 33:1316-1322. [PMID: 37246077 DOI: 10.1016/j.numecd.2023.04.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 04/14/2023] [Accepted: 04/18/2023] [Indexed: 05/30/2023]
Abstract
AIMS Previously, no relationship between milk consumption and the risk of type 2 diabetes has been found in prospective cohorts. However, Mendelian randomization allows researchers to almost bypass much residual confounding, providing a more precise effect estimate. This systematic review aims to investigate the risk of type 2 diabetes and levels of HbA1c by assessing all Mendelian Randomization studies investigating this subject matter. DATA SYNTHESIS PubMed and EMBASE were searched from October 2021 through February 2023. Inclusion and exclusion criteria were formulated to filter out irrelevant studies. Studies were qualitatively assessed with STROBE-MR together with a list of five MR criteria. Six studies were identified, containing several thousand participants. All studies used the SNP rs4988235 as the main exposure and type 2 diabetes and/or HbA1c as the main outcome. Five studies were graded as "good" with STROBE-MR, with one graded as "fair". For the six MR criteria, five studies were graded "good" in four criteria, while two studies were graded "good" in two criteria. Overall, genetically predicted milk consumption did not seem to be associated with an increased risk of type 2 diabetes. CONCLUSIONS This systematic review found that genetically predicted milk consumption did not seem to increase the risk of type 2 diabetes. Future Mendelian randomization studies concerning this topic should consider conducting two-sample Mendelian Randomization studies, in order to derive a more valid effect estimate.
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Affiliation(s)
| | - Maria Timofeeva
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, Danish Institute of Advanced Study, University of Southern Denmark, Odense, Denmark
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Yuan S, Merino J, Larsson SC. Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges. Diabetologia 2023; 66:800-812. [PMID: 36786839 PMCID: PMC10036461 DOI: 10.1007/s00125-023-05879-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/04/2023] [Indexed: 02/15/2023]
Abstract
Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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Lumsden AL, Mulugeta A, Hyppönen E. Milk consumption and risk of twelve cancers: A large-scale observational and Mendelian randomisation study. Clin Nutr 2023; 42:1-8. [PMID: 36473423 DOI: 10.1016/j.clnu.2022.11.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 11/01/2022] [Accepted: 11/04/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND & AIMS Milk consumption is a modifiable lifestyle factor that has been associated with several cancer types in observational studies. Limited evidence exists regarding the causality of these relationships. Using a genetic variant (rs4988235) near the lactase gene (LCT) locus that proxies milk consumption, we conducted a comprehensive survey to assess potential causal relationships between milk consumption and 12 types of cancer. METHODS Our analyses were conducted using white British participants of the UK Biobank (n = up to 255,196), the FinnGen cohort (up to 260,405), and available cancer consortia. We included cancers with previous evidence of an association with milk consumption in observational studies, as well as cancers common in both UK Biobank and FinnGen populations (>1000 cases). We evaluated phenotypic associations of milk intake and cancer incidence in the UK Biobank, and then used a Mendelian randomisation (MR) approach to assess causality in the UK Biobank, FinnGen consortium, and combined analyses incorporating additional consortia data for five cancers. In MR meta-analyses, case numbers for cancers of breast, ovary, uterus, cervix, prostate, bladder and urinary tract, colorectum, and lung ranged between 6000 and 148,000 cases, and between 780 and 1342 cases for cancers of the liver, mouth, stomach and diffuse large B-cell lymphoma. RESULTS In observational analyses, milk consumption was associated with higher risk of bladder and urinary tract cancer (OR 1.23, 95% CI 1.03-1.47), but not with any other cancer. This association was not confirmed in the MR analysis, and genetically predicted milk consumption showed a significant association only with lower risk of colorectal cancer (0.89, 0.81-0.98 per additional 50 g/day). In the MR analyses conducted among individual cohorts, genetically predicted milk consumption provided evidence for an association with lower colorectal cancer in the FinnGen cohort (0.85, 0.74-0.97), and in the UK Biobank greater risk of female breast cancer (1.12, 1.03-1.23), and uterine cancer in pre-menopausal females (3.98, 1.48-10.7). CONCLUSION In a comprehensive survey of milk-cancer associations, we confirm of a protective role of milk consumption for colorectal cancer. Our analyses also provide some suggestion for higher risks of breast cancer and premenopausal uterine cancer, warranting further investigation.
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Affiliation(s)
- Amanda L Lumsden
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia.
| | - Anwar Mulugeta
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia; Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa, Ethiopia.
| | - Elina Hyppönen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia.
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Yuan S, Sun J, Lu Y, Xu F, Li D, Jiang F, Wan Z, Li X, Qin LQ, Larsson SC. Health effects of milk consumption: phenome-wide Mendelian randomization study. BMC Med 2022; 20:455. [PMID: 36424608 PMCID: PMC9694907 DOI: 10.1186/s12916-022-02658-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 11/09/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND We performed phenome-wide Mendelian randomization analysis (MR-PheWAS), two-sample MR analysis, and systemic review to comprehensively explore the health effects of milk consumption in the European population. METHODS Rs4988235 located upstream of the LCT gene was used as the instrumental variable for milk consumption. MR-PheWAS analysis was conducted to map the association of genetically predicted milk consumption with 1081 phenotypes in the UK Biobank study (n=339,197). The associations identified in MR-PheWAS were examined by two-sample MR analysis using data from the FinnGen study (n=260,405) and international consortia. A systematic review of MR studies on milk consumption was further performed. RESULTS PheWAS and two-sample MR analyses found robust evidence in support of inverse associations of genetically predicted milk consumption with risk of cataract (odds ratio (OR) per 50 g/day increase in milk consumption, 0.89, 95% confidence interval (CI), 0.84-0.94; p=3.81×10-5), hypercholesterolemia (OR, 0.91, 95% CI 0.86-0.96; p=2.97×10-4), and anal and rectal polyps (OR, 0.85, 95% CI, 0.77-0.94; p=0.001). An inverse association for type 2 diabetes risk (OR, 0.92, 95% CI, 0.86-0.97; p=0.003) was observed in MR analysis based on genetic data with body mass index adjustment but not in the corresponding data without body mass index adjustment. The systematic review additionally found evidence that genetically predicted milk consumption was inversely associated with asthma, hay fever, multiple sclerosis, colorectal cancer, and Alzheimer's disease, and positively associated with Parkinson's disease, renal cell carcinoma, metabolic syndrome, overweight, and obesity. CONCLUSIONS This study suggests several health effects of milk consumption in the European population.
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Affiliation(s)
- Shuai Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jing Sun
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Lu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Doudou Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fangyuan Jiang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongxiao Wan
- Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Li-Qiang Qin
- Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China.
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. .,Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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10
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Vissers LET, Sluijs I, Burgess S, Forouhi NG, Freisling H, Imamura F, Nilsson TK, Renström F, Weiderpass E, Aleksandrova K, Dahm CC, Perez-Cornago A, Schulze MB, Tong TYN, Aune D, Bonet C, Boer JMA, Boeing H, Chirlaque MD, Conchi MI, Imaz L, Jäger S, Krogh V, Kyrø C, Masala G, Melander O, Overvad K, Panico S, Sánches MJ, Sonestedt E, Tjønneland A, Tzoulaki I, Verschuren WMM, Riboli E, Wareham NJ, Danesh J, Butterworth AS, van der Schouw YT. Milk intake and incident stroke and CHD in populations of European descent: a Mendelian randomisation study. Br J Nutr 2022; 128:1789-1797. [PMID: 34670632 PMCID: PMC9592953 DOI: 10.1017/s0007114521004244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 07/01/2021] [Accepted: 09/22/2021] [Indexed: 12/29/2022]
Abstract
Higher milk intake has been associated with a lower stroke risk, but not with risk of CHD. Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29 328 participants (4611 stroke; 9828 CHD) of the European Prospective Investigation into Cancer and Nutrition (EPIC)-CVD (eight European countries) and European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL) case-cohort studies. rs4988235, a lactase persistence (LP) SNP which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777 024 participants (50 804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483 966 participants (61 612 cases) from CARDIoGRAM, UK Biobank, EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (β = 13·7 g/d; 95 % CI 8·4, 19·1) and EPIC-NL (36·8 g/d; 95 % CI 20·0, 53·5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/d 1·05; 95 % CI 0·94, 1·16) or CHD (1·02; 95 % CI 0·96, 1·08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (OR 1·02; 95 % CI 0·99, 1·05) or CHD (OR 0·99; 95 % CI 0·95, 1·03). Current Mendelian randomisation analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk.
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Affiliation(s)
- L. E. T. Vissers
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - I. Sluijs
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - S. Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - N. G. Forouhi
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - H. Freisling
- International Agency for Research on Cancer, Lyon, France
| | - F. Imamura
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - T. K. Nilsson
- Department of Medical Biosciences/Clinical Chemistry, Umeå University, Umeå, Sweden
| | - F. Renström
- Department of Biobank Research, Umeå University, Umeå, Sweden
- Division of Endocrinology and Diabetes, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - E. Weiderpass
- International Agency for Research on Cancer, Lyon, France
| | - K. Aleksandrova
- Germany Institute of Nutritional Sciences, University of Potsdam, Nuthetal, Germany
| | - C. C. Dahm
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - A. Perez-Cornago
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - M. B. Schulze
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Germany Institute of Nutritional Sciences, University of Potsdam, Nuthetal, Germany
| | - T. Y. N. Tong
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - D. Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Nutrition, Bjørknes University College, Oslo, Norway
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - C. Bonet
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain
| | - J. M. A. Boer
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H. Boeing
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - M. D. Chirlaque
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia University, Murcia, Spain
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - M. I. Conchi
- Navarra Public Health Institute – IdiSNA, Pamplona, Spain
- Research Network on Health Services in Chronic Diseases (REDISSEC), Pamplona, Spain
| | - L. Imaz
- Ministry of Health of the Basque Government, Public Health Division of Gipuzkoa, Donostia-San Sebastian, Spain
- Biodonostia Health Research Institute, Donostia-San Sebastian, Spain
| | - S. Jäger
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - V. Krogh
- Epidemiology and prevention Unit, Fondazione IRCCS Instituto Nazionale dei Tumori, Milano, Italy
| | - C. Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - G. Masala
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network – ISPRO, Florence, Italy
| | - O. Melander
- Lund University, Department of Clinical Sciences, Malmö, Sweden
| | - K. Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - S. Panico
- Dipartemento di medicina clinica e chirurgia, Federico II University, Naples, Italy
| | - M. J. Sánches
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Andalusian School of Public Health (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria de Granada, Granada, Spain
- Universidad de Granada, Granada, Spain
| | - E. Sonestedt
- Lund University, Department of Clinical Sciences, Malmö, Sweden
| | - A. Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - I. Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - W. M. M. Verschuren
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - E. Riboli
- School of Public Health, Imperial College London, UK
| | - N. J. Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - J. Danesh
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - A. S. Butterworth
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Y. T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
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11
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Wang H, Chen L, Cao Y, Xie K, Wang C, Pei P, Guo Y, Bragg F, Yu M, Chen Z, Li L. Association between frequency of dairy product consumption and hypertension: a cross-sectional study in Zhejiang Province, China. Nutr Metab (Lond) 2022; 19:67. [PMID: 36180916 PMCID: PMC9526303 DOI: 10.1186/s12986-022-00703-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Hypertension, a well-known risk factor, contributes to millions of deaths from cardiovascular and renal diseases worldwide. However, evidence on the association between frequency of dairy product consumption and hypertension is inconsistent. METHODS The data for the present study are from the Tongxiang baseline dataset of the China Kadoorie Biobank prospective study. A total of 53,916 participants aged 30-79 years were included in the final analysis. Multivariable logistic regression was utilized to evaluate the association of dairy product consumption with hypertension, and multiple linear regression was conducted to assess the association of dairy product consumption with systolic and diastolic blood pressure. RESULTS Of the 53,916 participants, 2.6% reported consuming dairy products weekly, and 44.4% had prevalent hypertension. After adjusting for socio-demographic status, lifestyle factors, BMI, waist circumference, sleep duration and snoring, when compared with participants who never consumed dairy products, the odds ratios (95% CI) for hypertension among those consuming dairy products less than once per week, and ≥ 1 time per week were 0.85 (0.77-0.95) and 0.74 (0.65-0.84), respectively. The corresponding odds ratios (95% CI) for men were 0.85 (0.71-1.02) and 0.75 (0.61-0.92), respectively (Ptrend = 0.001), and for women were 0.88 (0.76-1.01) and 0.77 (0.65-0.91), respectively. (Ptrend < 0.001). CONCLUSIONS In this large epidemiological study, higher frequency of dairy product consumption is associated with significantly lower odds of hypertension among Chinese adults.
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Affiliation(s)
- Hao Wang
- grid.433871.aDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, #3399 Binsheng road, Binjiang District, Hangzhou, Zhejiang Province China
| | - Lingli Chen
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Yuan Cao
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Kaixu Xie
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Chunmei Wang
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Pei Pei
- grid.11135.370000 0001 2256 9319Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yu Guo
- grid.415105.40000 0004 9430 5605National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Fiona Bragg
- grid.4991.50000 0004 1936 8948Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- grid.4991.50000 0004 1936 8948Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Min Yu
- grid.433871.aDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, #3399 Binsheng road, Binjiang District, Hangzhou, Zhejiang Province China
| | - Zhengming Chen
- grid.4991.50000 0004 1936 8948Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- grid.4991.50000 0004 1936 8948Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- grid.11135.370000 0001 2256 9319Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- grid.11135.370000 0001 2256 9319Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
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12
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Chen S, Zheng C, Chen T, Chen J, Pan Y, Chen S. Genetically Predicted Milk Intake Increased Femoral Neck Bone Mineral Density in Women But Not in Men. Front Endocrinol (Lausanne) 2022; 13:900109. [PMID: 35795146 PMCID: PMC9251187 DOI: 10.3389/fendo.2022.900109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background Cow milk contains more calcium, magnesium, potassium, zinc, and phosphorus minerals. For a long time, people have believed that increasing milk intake is beneficial to increasing bone density. Many confounding factors can affect milk consumption, and thus the association described to date may not be causal. We explored the causal relationship between genetically predicted milk consumption and Bone Mineral Density (BMD) of the femoral neck and lumbar spine based on 53,236 individuals from 27 studies of European ancestry using the Mendelian randomization (MR) study. 32,961 individuals of European and East Asian ancestry were used for sensitivity analysis. Methods A genetic instrument used for evaluating milk consumption is rs4988235, a locus located at 13,910 base pairs upstream of the LCT gene. A Mendelian randomization (MR) analysis was conducted to study the effect of selected single nucleotide polymorphisms (SNPs) and BMD. The summary-level data for BMD of the femoral neck and lumbar spine were obtained from two GWAS meta-analyses ['Data Release 2012' and 'Data Release 2015' in the GEnetic Factors for OSteoporosis Consortium (GEFOS)]. Results we found that genetically predicted milk consumption was not associated with FN-BMD(OR 1.007; 95% CI 0.991-1.023; P = 0.385), LS-BMD(OR 1.003; 95% CI 0.983-1.024; P = 0.743) by performing a meta-analysis of several different cohort studies. High levels of genetically predicted milk intake were positively associated with increased FN-BMD in Women. The OR for each additional milk intake increasing allele was 1.032 (95%CI 1.005-1.059; P = 0.014). However, no causal relationship was found between milk consumption and FN-BMD in men (OR 0.996; 95% CI 0.964-1.029; P = 0.839). Genetically predicted milk consumption was not significantly associated with LS-BMD in women (OR 1.017; 95% CI 0.991-1.043; P = 0.198) and men (OR 1.011; 95% CI 0.978-1.045; P = 0.523). Conclusion Our study found that women who consume more milk have a higher FN-BMD. When studying the effect of milk consumption on bone density in further studies, we need to pay more attention to women.
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Affiliation(s)
- Song Chen
- Department of Orthopedics, Fuzhou Second Hospital, Fuzhou, China
- Fujian Provincial Clinical Medical Research Center for First Aid and Rehabilitation in Orthopaedic Trauma (2020Y2014), Fuzhou, China
- Fuzhou Trauma Medical Center, Fuzhou, China
| | - Changhua Zheng
- Department of Cardiology Nursing, Fujian Medical University Union Hospital, Fuzhou, China
| | - Tianlai Chen
- The Third Department of Clinical Medicine, Fujian Medical University, Fuzhou, China
| | - Jinchen Chen
- Department of Orthopedics, Fuzhou Second Hospital, Fuzhou, China
- Fujian Provincial Clinical Medical Research Center for First Aid and Rehabilitation in Orthopaedic Trauma (2020Y2014), Fuzhou, China
- Fuzhou Trauma Medical Center, Fuzhou, China
| | - Yuancheng Pan
- Department of Orthopedics, Fuzhou Second Hospital, Fuzhou, China
- Fujian Provincial Clinical Medical Research Center for First Aid and Rehabilitation in Orthopaedic Trauma (2020Y2014), Fuzhou, China
- Fuzhou Trauma Medical Center, Fuzhou, China
| | - Shunyou Chen
- Department of Orthopedics, Fuzhou Second Hospital, Fuzhou, China
- Fujian Provincial Clinical Medical Research Center for First Aid and Rehabilitation in Orthopaedic Trauma (2020Y2014), Fuzhou, China
- Fuzhou Trauma Medical Center, Fuzhou, China
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13
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Pirastu N, McDonnell C, Grzeszkowiak EJ, Mounier N, Imamura F, Merino J, Day FR, Zheng J, Taba N, Concas MP, Repetto L, Kentistou KA, Robino A, Esko T, Joshi PK, Fischer K, Ong KK, Gaunt TR, Kutalik Z, Perry JRB, Wilson JF. Using genetic variation to disentangle the complex relationship between food intake and health outcomes. PLoS Genet 2022; 18:e1010162. [PMID: 35653391 PMCID: PMC9162356 DOI: 10.1371/journal.pgen.1010162] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 03/22/2022] [Indexed: 02/02/2023] Open
Abstract
Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.
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Affiliation(s)
- Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Human Technopole, Milan, Italy
- * E-mail:
| | - Ciara McDonnell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Eryk J. Grzeszkowiak
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ninon Mounier
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Fumiaki Imamura
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jordi Merino
- Diabetes Unit and Centre for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Felix R. Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Nele Taba
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Maria Pina Concas
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Katherine A. Kentistou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Antonietta Robino
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Krista Fischer
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Zoltán Kutalik
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - John R. B. Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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14
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BROWN ANDREWW, ASLIBEKYAN STELLA, BIER DENNIS, DA SILVA RAFAELFERREIRA, HOOVER ADAM, KLURFELD DAVIDM, LOKEN ERIC, MAYO-WILSON EVAN, MENACHEMI NIR, PAVELA GREG, QUINN PATRICKD, SCHOELLER DALE, TEKWE CARMEN, VALDEZ DANNY, VORLAND COLBYJ, WHIGHAM LEAHD, ALLISON DAVIDB. Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo. Crit Rev Food Sci Nutr 2021; 63:3150-3167. [PMID: 34678079 PMCID: PMC9023609 DOI: 10.1080/10408398.2021.1985427] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
To date, nutritional epidemiology has relied heavily on relatively weak methods including simple observational designs and substandard measurements. Despite low internal validity and other sources of bias, claims of causality are made commonly in this literature. Nutritional epidemiology investigations can be improved through greater scientific rigor and adherence to scientific reporting commensurate with research methods used. Some commentators advocate jettisoning nutritional epidemiology entirely, perhaps believing improvements are impossible. Still others support only normative refinements. But neither abolition nor minor tweaks are appropriate. Nutritional epidemiology, in its present state, offers utility, yet also needs marked, reformational renovation. Changing the status quo will require ongoing, unflinching scrutiny of research questions, practices, and reporting-and a willingness to admit that "good enough" is no longer good enough. As such, a workshop entitled "Toward more rigorous and informative nutritional epidemiology: the rational space between dismissal and defense of the status quo" was held from July 15 to August 14, 2020. This virtual symposium focused on: (1) Stronger Designs, (2) Stronger Measurement, (3) Stronger Analyses, and (4) Stronger Execution and Reporting. Participants from several leading academic institutions explored existing, evolving, and new better practices, tools, and techniques to collaboratively advance specific recommendations for strengthening nutritional epidemiology.
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Affiliation(s)
- ANDREW W. BROWN
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | | | - DENNIS BIER
- Baylor College of Medicine, Houston, Texas, USA
| | | | - ADAM HOOVER
- Clemson University, Clemson, South Carolina, USA
| | - DAVID M. KLURFELD
- United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, USA
| | - ERIC LOKEN
- University of Connecticut, Storrs, Connecticut, USA
| | - EVAN MAYO-WILSON
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - NIR MENACHEMI
- Indiana University Fairbanks School of Public Health at IUPUI, Indianapolis, Indiana, USA
| | - GREG PAVELA
- University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - PATRICK D. QUINN
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - DALE SCHOELLER
- University of Wisconsin-Madison Biotechnology Center, Madison, Wisconsin, USA
| | - CARMEN TEKWE
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - DANNY VALDEZ
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - COLBY J. VORLAND
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - LEAH D. WHIGHAM
- University of Texas Health Science Center School of Public Health, El Paso, Texas, USA
| | - DAVID B. ALLISON
- Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
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15
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Chen Z, Ahmed M, Ha V, Jefferson K, Malik V, Ribeiro PAB, Zuchinali P, Drouin-Chartier JP. Dairy Product Consumption and Cardiovascular Health: a Systematic Review and Meta-Analysis of Prospective Cohort Studies. Adv Nutr 2021; 13:S2161-8313(22)00071-0. [PMID: 34550320 PMCID: PMC8970833 DOI: 10.1093/advances/nmab118] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The association between dairy product consumption and cardiovascular health remains highly debated. We quantitatively synthesized prospective cohort evidence on the associations between dairy consumption and risk of hypertension (HTN), coronary heart disease (CHD) and stroke. We systematically searched PubMed, Embase, and Web of Science through August 1st, 2020 to retrieve prospective cohort studies that reported on dairy consumption and risk of HTN, CHD or stroke. We used random-effects models to calculate the pooled relative risk (RR) and 95% confidence interval (CI) for the highest vs the lowest category of intake and for 1 serving/day increase in consumption. We rated the quality of evidence using NutriGrade. Fifty-five studies were included. Total dairy consumption was associated with a lower risk of HTN (RR for highest vs lowest level of intake: 0.91, 95% CI: 0.86-0.95, I2 = 73.5%; RR for 1 serving/day increase: 0.96, 95% CI: 0.94-0.97, I2 = 66.5%), CHD (highest vs lowest level of intake: 0.96, 95% CI: 0.92-1.00, I2 = 46.6%; 1 serving/day increase: 0.98, 95% CI: 0.95-1.00, I2 = 56.7%), and stroke (highest vs lowest level of intake: 0.90, 95% CI: 0.85-0.96, I2 = 60.8%; 1 serving/day increase: 0.96, 95% CI: 0.93-0.99, I2 = 74.7%). Despite moderate to considerable heterogeneity, these associations remained consistent across multiple subgroups. Evidence on the relationship between total dairy and risk of HTN and CHD were of moderate quality and of low quality for stroke. Low-fat dairy consumption was associated with lower risk of HTN and stroke, and high-fat dairy with a lower risk of stroke. Milk, cheese, or yogurt consumption showed inconsistent associations with the cardiovascular outcomes in high vs. low intake and dose-response meta-analyses. Total dairy consumption was associated with a modestly lower risk of hypertension, CHD and stroke. Moderate to considerable heterogeneity was observed in the estimates and the overall quality of the evidence was low to moderate.
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Affiliation(s)
- Zhangling Chen
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Mavra Ahmed
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada,Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, ON, Canada
| | - Vanessa Ha
- School of Medicine, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada
| | | | - Vasanti Malik
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Paula A B Ribeiro
- Montreal Behavioural Medicine Centre, CIUSSS du Nord-de-l’Île-de-Montréal, Montréal, QC, Canada,Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Priccila Zuchinali
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
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Zhang Z, Wang M, Yuan S, Larsson SC, Liu X. Genetically Predicted Milk Intake and Risk of Neurodegenerative Diseases. Nutrients 2021; 13:nu13082893. [PMID: 34445060 PMCID: PMC8398304 DOI: 10.3390/nu13082893] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/18/2021] [Accepted: 08/21/2021] [Indexed: 01/07/2023] Open
Abstract
Milk intake has been associated with risk of neurodegenerative diseases in observational studies. Nevertheless, whether the association is causal remains unknown. We adopted Mendelian randomization design to evaluate the potential causal association between milk intake and common neurodegenerative diseases, including multiple sclerosis (MS), Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson’s disease (PD). Genetic associations for neurodegenerative diseases were obtained from the International Multiple Sclerosis Genetics Consortium (n = 80,094), FinnGen consortium (n = 176,899), AD GWAS (n = 63,926), Web-Based Study of Parkinson’s Disease (n = 308,518), PDGene (n = 108,990), and ALS GWAS (n = 80,610). Lactase persistence variant rs4988235 (LCT-13910 C > T) was used as the instrumental variable for milk intake. Genetically predicted higher milk intake was associated with a decreased risk of MS and AD and with an increased risk of PD. For each additional milk intake increasing allele, the odds ratios were 0.94 (95% confidence intervals [CI]: 0.91–0.97; p = 1.51 × 10−4) for MS, 0.97 (0.94–0.99; p = 0.019) for AD and 1.09 (95%CI: 1.06–1.12, p = 9.30 × 10−9) for PD. Genetically predicted milk intake was not associated with ALS (odds ratio: 0.97, 95%CI: 0.94–1.01, p = 0.135). Our results suggest that genetically predicted milk intake is associated with a decreased risk of MS and AD but with an increased risk of PD. Further investigations are needed to clarify the underlying mechanisms.
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Affiliation(s)
- Zhizhong Zhang
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China;
| | - Mengmeng Wang
- Department of Neurology, The First People’s Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou 213004, China;
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden; (S.Y.); (S.C.L.)
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden; (S.Y.); (S.C.L.)
| | - Xinfeng Liu
- Department of Neurology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China;
- Correspondence:
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Ibsen DB, Jakobsen MU, Halkjær J, Tjønneland A, Kilpeläinen TO, Parner ET, Overvad K. Replacing Red Meat with Other Nonmeat Food Sources of Protein is Associated with a Reduced Risk of Type 2 Diabetes in a Danish Cohort of Middle-Aged Adults. J Nutr 2021; 151:1241-1248. [PMID: 33693801 DOI: 10.1093/jn/nxaa448] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 09/10/2020] [Accepted: 12/22/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Few cohort studies have modelled replacements of red meat with other sources of protein on subsequent risk of type 2 diabetes using dietary changes. OBJECTIVES To determine whether replacing red meat with other food sources of protein is associated with a lower risk of type 2 diabetes. METHODS We used data from the Danish Diet, Cancer, and Health cohort (n = 39,437) of middle-aged (55-72 years old) men and women who underwent 2 dietary assessments roughly 5 years apart to investigate dietary changes. The pseudo-observation method was used to model the average exposure effect of decreasing the intake of red meat while increasing the intake of either poultry, fish, eggs, milk, yogurt, cheese, whole grains, or refined grains on the subsequent 10-year risk of developing type 2 diabetes, compared with no changes in the intakes of these foods. RESULTS Replacing 1 serving/day (100 g/day) of red meat with 1 serving/day of eggs [risk difference (RD), -2.7%; 95% CI: -4.0 to -1.1%; serving size: 50 g/day], milk (RD, -1.2%; 95% CI: -2.1 to -0.4%; 200 g/day), yogurt (RD, -1.5%; 95% CI: -2.4 to -0.7%; 70 g/day), whole grains (RD, -1.7%; 95% CI: -2.5 to -0.9%; 30 g/day), or refined grains (RD, -1.2%; 95% CI: -2.0 to -0.3%; 30 g/day) was associated with a reduced risk of type 2 diabetes. Analyses of replacements with poultry or cheese, but not fish, also suggested a lower risk, but with wide CIs. After further adjustment for potential mediators (BMI, waist circumference, and history of hypertension or hypercholesterolemia), only the replacement with eggs was associated with a reduced risk (RD, -1.7%; 95% CI: -3.0 to -0.5%; 50 g/day). CONCLUSIONS Replacing red meat with eggs in middle-aged adults may reduce the risk of type 2 diabetes. In models not adjusted for potential mediators, replacing red meat with milk, yogurt, whole grains, or refined grains was also associated with a reduced risk of type 2 diabetes.
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Affiliation(s)
- Daniel B Ibsen
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Marianne U Jakobsen
- National Food Institute, Division for Diet, Disease Prevention and Toxicology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Jytte Halkjær
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark.,Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Erik T Parner
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark.,Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
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18
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Changes in intake of dairy product subgroups and risk of type 2 diabetes: modelling specified food substitutions in the Danish Diet, Cancer and Health cohort. Eur J Nutr 2021; 60:3449-3459. [PMID: 33661378 DOI: 10.1007/s00394-021-02524-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 02/19/2021] [Indexed: 12/26/2022]
Abstract
PURPOSE We investigated the association between an increased intake of one dairy product subgroup at the expense of another within a 5-year period and the subsequent 10-year risk of type 2 diabetes. METHODS The cohort included 39,393 adults with two measurements of diet assessed using food frequency questionnaires (FFQ) administered in 1993-1997 and 1999-2003. Dairy products were milk (skimmed, semi-skimmed, whole fat), buttermilk, low-fat yogurt, whole-fat yogurt, cheese and butter. Type 2 diabetes cases were ascertained from the Danish National Diabetes Register. The pseudo-observation method was used to calculate risk differences (RD) with 95% confidence intervals (CI). The data were analysed in age strata to fulfil the assumption of independent entry. RESULTS Among participants aged 56-59 years at completion of the follow-up FFQ, increased intake of whole-fat yogurt in place of skimmed, semi-skimmed or whole-fat milk was associated with a reduced risk (RD% [95% CI]: - 0.8% [- 1.3, - 0.2]; - 0.6% [- 1,1, - 0.1]; - 0.7 [- 1.2, - 0.1]; per 50 g/d, respectively). Among participants aged 60-64 and 65-72, substitution of skimmed milk for semi-skimmed milk was associated with an increased risk of type 2 diabetes (0.5% [0.2, 0.7]; 0.4% [0.1, 0.7]; per 50 g/d, respectively). Similar patterns of associations were found after adjustment for potential mediators. CONCLUSION Our results suggest that substitution of whole-fat yogurt for milk among those aged 56-59 decreases risk of type 2 diabetes and substitution of skimmed milk for semi-skimmed milk may increase the risk among those aged 60-64 and 65-72.
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Abstract
PURPOSE OF REVIEW The current review describes the fundamentals of the Mendelian randomization framework and its current application for causal inference in human nutrition and metabolism. RECENT FINDINGS In the Mendelian randomization framework, genetic variants that are strongly associated with the potential risk factor are used as instrumental variables to determine whether the risk factor is a cause of the disease. Mendelian randomization studies are less susceptible to confounding and reverse causality compared with traditional observational studies. The Mendelian randomization study design has been increasingly used in recent years to appraise the causal associations of various nutritional factors, such as milk and alcohol intake, circulating levels of micronutrients and metabolites, and obesity with risk of different health outcomes. Mendelian randomization studies have confirmed some but challenged other nutrition-disease associations recognized by traditional observational studies. Yet, the causal role of many nutritional factors and intermediate metabolic changes for health and disease remains unresolved. SUMMARY Mendelian randomization can be used as a tool to improve causal inference in observational studies assessing the role of nutritional factors and metabolites in health and disease. There is a need for more large-scale genome-wide association studies to identify more genetic variants for nutritional factors that can be utilized for Mendelian randomization analyses.
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Affiliation(s)
- Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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20
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Evidence for a causal association between milk intake and cardiometabolic disease outcomes using a two-sample Mendelian Randomization analysis in up to 1,904,220 individuals. Int J Obes (Lond) 2021; 45:1751-1762. [PMID: 34024907 PMCID: PMC8310799 DOI: 10.1038/s41366-021-00841-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 04/08/2021] [Accepted: 04/26/2021] [Indexed: 02/04/2023]
Abstract
BACKGROUND High milk intake has been associated with cardio-metabolic risk. We conducted a Mendelian Randomization (MR) study to obtain evidence for the causal relationship between milk consumption and cardio-metabolic traits using the lactase persistence (LCT-13910 C > T, rs4988235) variant as an instrumental variable. METHODS We tested the association of LCT genotype with milk consumption (for validation) and with cardio-metabolic traits (for a possible causal association) in a meta-analysis of the data from three large-scale population-based studies (1958 British Birth Cohort, Health and Retirement study, and UK Biobank) with up to 417,236 participants and using summary statistics from consortia meta-analyses on intermediate traits (N = 123,665-697,307) and extended to cover disease endpoints (N = 86,995-149,821). RESULTS In the UK Biobank, carriers of 'T' allele of LCT variant were more likely to consume milk (P = 7.02 × 10-14). In meta-analysis including UK Biobank, the 1958BC, the HRS, and consortia-based studies, under an additive model, 'T' allele was associated with higher body mass index (BMI) (Pmeta-analysis = 4.68 × 10-12) and lower total cholesterol (TC) (P = 2.40 × 10-36), low-density lipoprotein cholesterol (LDL-C) (P = 2.08 × 10-26) and high-density lipoprotein cholesterol (HDL-C) (P = 9.40 × 10-13). In consortia meta-analyses, 'T' allele was associated with a lower risk of coronary artery disease (OR:0.86, 95% CI:0.75-0.99) but not with type 2 diabetes (OR:1.06, 95% CI:0.97-1.16). Furthermore, the two-sample MR analysis showed a causal association between genetically instrumented milk intake and higher BMI (P = 3.60 × 10-5) and body fat (total body fat, leg fat, arm fat and trunk fat; P < 1.37 × 10-6) and lower LDL-C (P = 3.60 × 10-6), TC (P = 1.90 × 10-6) and HDL-C (P = 3.00 × 10-5). CONCLUSIONS Our large-scale MR study provides genetic evidence for the association of milk consumption with higher BMI but lower serum cholesterol levels. These data suggest no need to limit milk intakes with respect to cardiovascular disease risk, with the suggested benefits requiring confirmation in further studies.
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21
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Larsson SC, Mason AM, Kar S, Vithayathil M, Carter P, Baron JA, Michaëlsson K, Burgess S. Genetically proxied milk consumption and risk of colorectal, bladder, breast, and prostate cancer: a two-sample Mendelian randomization study. BMC Med 2020; 18:370. [PMID: 33261611 PMCID: PMC7709312 DOI: 10.1186/s12916-020-01839-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 11/03/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Observational studies have shown that milk consumption is inversely associated with colorectal, bladder, and breast cancer risk, but positively associated with prostate cancer. However, whether the associations reflect causality remains debatable. We investigated the potential causal associations of milk consumption with the risk of colorectal, bladder, breast, and prostate cancer using a genetic variant near the LCT gene as proxy for milk consumption. METHODS We obtained genetic association estimates for cancer from the UK Biobank (n = 367,643 women and men), FinnGen consortium (n = 135,638 women and men), Breast Cancer Association Consortium (n = 228,951 women), and Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium (n = 140,254 men). Milk consumption was proxied by a genetic variant (rs4988235 or rs182549) upstream of the gene encoding lactase, which catalyzes the breakdown of lactose. RESULTS Genetically proxied milk consumption was associated with a reduced risk of colorectal cancer. The odds ratio (OR) for each additional milk intake increasing allele was 0.95 (95% confidence interval [CI] 0.91-0.99; P = 0.009). There was no overall association of genetically predicted milk consumption with bladder (OR 0.99; 95% CI 0.94-1.05; P = 0.836), breast (OR 1.01; 95% CI 1.00-1.02; P = 0.113), and prostate cancer (OR 1.01; 95% CI 0.99-1.02; P = 0.389), but a positive association with prostate cancer was observed in the FinnGen consortium (OR 1.07; 95% CI 1.01-1.13; P = 0.026). CONCLUSIONS Our findings strengthen the evidence for a protective role of milk consumption on colorectal cancer risk. There was no or limited evidence that milk consumption affects the risk of bladder, breast, and prostate cancer.
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Affiliation(s)
- Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 17177, Stockholm, Sweden.
| | - Amy M Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Paul Carter
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - John A Baron
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Karl Michaëlsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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22
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Byberg L, Warensjö Lemming E. Milk Consumption for the Prevention of Fragility Fractures. Nutrients 2020; 12:E2720. [PMID: 32899514 PMCID: PMC7551481 DOI: 10.3390/nu12092720] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/01/2020] [Accepted: 09/03/2020] [Indexed: 12/17/2022] Open
Abstract
Results indicating that a high milk intake is associated with both higher and lower risks of fragility fractures, or that indicate no association, can all be presented in the same meta-analysis, depending on how it is performed. In this narrative review, we discuss the available studies examining milk intake in relation to fragility fractures, highlight potential problems with meta-analyses of such studies, and discuss potential mechanisms and biases underlying the different results. We conclude that studies examining milk and dairy intakes in relation to fragility fracture risk need to study the different milk products separately. Meta-analyses should consider the doses in the individual studies. Additional studies in populations with a large range of intake of fermented milk are warranted.
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Affiliation(s)
- Liisa Byberg
- Department of Surgical Sciences, Orthopaedics, Uppsala University, SE-751 85 Uppsala, Sweden;
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23
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Villaverde P, Lajous M, MacDonald CJ, Fagherazzi G, Boutron-Ruault MC, Bonnet F. Dairy product consumption and hypertension risk in a prospective French cohort of women. Nutr J 2020; 19:12. [PMID: 32024524 PMCID: PMC7003316 DOI: 10.1186/s12937-020-0527-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 01/27/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Among potentially modifiable factors, dairy product consumption has been inconsistently associated with hypertension risk. The objective of this study was to investigate the relation between dairy product consumption and the risk of hypertension among middle-aged women. METHODS In a prospective cohort of 40,526 French women, there were 9340 new cases of hypertension after an average 12.2 years of follow up. Consumptions of milk, yogurt, and types of cheese were assessed at baseline using a validated dietary questionnaire. Hazard ratios (HRs) and 95% confidence intervals (95% CI) for hypertension were estimated with multivariate Cox models with age as the time scale. RESULTS The mean dairy consumption was 2.2 + 1.2 servings/day, as cottage cheese (0.2 + 0.2 servings/day), yogurt (0.6 + 0.5 servings/day), milk (0.4 + 0.7 servings/day), and cheese (1.1 + 0.8 servings/day). There was no association between risk of hypertension and total dairy consumption (multivariate HR for the fifth vs. first quintile HR5vs.1 = 0.97 [0.91; 1.04]). There was no association with any specific type of dairy, except for a positive association between processed cheese consumption and hypertension (multivariate HR4vs.1 = 1.12 [1.06; 1.18]; p trend = < 0.003). CONCLUSIONS In this large prospective cohort of French women, overall consumption of dairy products was not associated with the risk of hypertension. Results regarding processed cheese must be further confirmed.
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Affiliation(s)
- Paola Villaverde
- Center for Research on Population Health, INSP (Instituto Nacional de Salud Pública), Cuernavaca, Mexico.,Université Paris-Saclay, Villejuif, France.,Université Paris-Sud, Villejuif, France.,Center for Research in Epidemiology and Population Health (CESP), Institut Gustave Roussy, INSERM (Institut National de la Santé et de la Recherche Médicale) U1018, Villejuif, France
| | - Martin Lajous
- Center for Research on Population Health, INSP (Instituto Nacional de Salud Pública), Cuernavaca, Mexico.,Université Paris-Saclay, Villejuif, France.,Université Paris-Sud, Villejuif, France.,Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Conor-James MacDonald
- Université Paris-Saclay, Villejuif, France.,Université Paris-Sud, Villejuif, France.,Center for Research in Epidemiology and Population Health (CESP), Institut Gustave Roussy, INSERM (Institut National de la Santé et de la Recherche Médicale) U1018, Villejuif, France
| | - Guy Fagherazzi
- Université Paris-Saclay, Villejuif, France.,Université Paris-Sud, Villejuif, France.,Center for Research in Epidemiology and Population Health (CESP), Institut Gustave Roussy, INSERM (Institut National de la Santé et de la Recherche Médicale) U1018, Villejuif, France.,Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Marie-Christine Boutron-Ruault
- Université Paris-Saclay, Villejuif, France. .,Université Paris-Sud, Villejuif, France. .,Center for Research in Epidemiology and Population Health (CESP), Institut Gustave Roussy, INSERM (Institut National de la Santé et de la Recherche Médicale) U1018, Villejuif, France.
| | - Fabrice Bonnet
- Université Paris-Saclay, Villejuif, France.,Université Paris-Sud, Villejuif, France.,Center for Research in Epidemiology and Population Health (CESP), Institut Gustave Roussy, INSERM (Institut National de la Santé et de la Recherche Médicale) U1018, Villejuif, France.,Groupe hospitalier Paris St-Joseph, Paris, France
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24
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Machado-Fragua MD, Struijk EA, Caballero FF, Ortolá R, Lana A, Banegas JR, Rodríguez-Artalejo F, Lopez-Garcia E. Dairy consumption and risk of falls in 2 European cohorts of older adults. Clin Nutr 2020; 39:3140-3146. [PMID: 32075745 DOI: 10.1016/j.clnu.2020.01.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 01/25/2020] [Accepted: 01/28/2020] [Indexed: 11/19/2022]
Abstract
BACKGROUND & AIMS Some previous evidence have linked dairy products with greater muscle mass, bone mineral density and lower risk of osteoporosis. However, there is also evidence of a detrimental effect of milk on the risk of hip fracture. The aim of this study was to assess the prospective association between dairy consumption and risk of falls in older adults. METHODS We used data from 2 cohorts of community-dwellers aged ≥60y: the Seniors-ENRICA cohort with 2981 individuals, and the UK Biobank cohort with 8927 participants. In the Seniors-ENRICA, dairy consumption was assessed with a validated diet history in 2008-10, and falls were ascertained up to 2015. In the UK Biobank study, dairy consumption was obtained with 3-5 multiple-pass 24-h food records in 2006-10, and falls were assessed up to 2016. RESULTS A total of 801 individuals in the Seniors-ENRICA and 201 in the UK Biobank experienced ≥1 fall. After adjustment for potential confounders, dairy products were not associated with risk of falls in the Seniors-ENRICA [hazard ratio (95% confidence interval) per 1-serving increment in total dairy consumption: 1.02 (0.93-1.11), milk: 0.93 (0.85-1.01), yogurt: 1.05 (0.96-1.15), and cheese: 0.96 (0.88-1.05)]. Corresponding figures in the UK Biobank were: total dairy: 1.19 (1.00-1.41), milk: 1.53 (1.13-2.08), yogurt: 1.10 (0.90-1.31), and cheese: 1.02 (0.87-1.22). CONCLUSIONS These results suggest a null association between habitual dairy consumption and the risk of falling in older adults. Whether milk consumption may increase the risk of falls, as observed in the UK Biobank cohort, merits further study.
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Affiliation(s)
- Marcos D Machado-Fragua
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Ellen A Struijk
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Francisco Félix Caballero
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Rosario Ortolá
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Alberto Lana
- Department of Medicine, School of Medicine and Health Sciences, Universidad de Oviedo / ISPA, Spain
| | - José R Banegas
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain
| | - Fernando Rodríguez-Artalejo
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Esther Lopez-Garcia
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid IdiPaz (Instituto de Investigación Sanitaria Hospital Universitario La Paz) CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain; IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain.
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Soedamah-Muthu SS, Guo J. Dairy consumption and cardiometabolic diseases: Evidence from prospective studies. MILK AND DAIRY FOODS 2020:1-28. [DOI: 10.1016/b978-0-12-815603-2.00001-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
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Drouin-Chartier JP, Li Y, Ardisson Korat AV, Ding M, Lamarche B, Manson JE, Rimm EB, Willett WC, Hu FB. Changes in dairy product consumption and risk of type 2 diabetes: results from 3 large prospective cohorts of US men and women. Am J Clin Nutr 2019; 110:1201-1212. [PMID: 31504094 PMCID: PMC6821541 DOI: 10.1093/ajcn/nqz180] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 07/10/2019] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Whether changes in dairy product consumption are related to subsequent risk of type 2 diabetes (T2D) remains unknown. OBJECTIVE We evaluated the association of long-term changes in dairy product consumption with subsequent risk of T2D among US men and women. METHODS We followed up 34,224 men in the Health Professionals Follow-Up Study (1986-2012), 76,531 women in the Nurses' Health Study (1986-2012), and 81,597 women in the Nurses' Health Study II (1991-2013). Changes in dairy consumption were calculated from consecutive quadrennial FFQs. Multivariable Cox proportional regression models were used to calculate HRs for T2D associated with changes in dairy product consumption. Results of the 3 cohorts were pooled using an inverse variance-weighted, fixed-effect meta-analysis. RESULTS During 2,783,210 person-years, we documented 11,906 incident T2D cases. After adjustment for initial and changes in diet and lifestyle covariates, decreasing total dairy intake by >1.0 serving/d over a 4-y period was associated with an 11% (95% CI: 3%, 19%) higher risk of T2D in the subsequent 4 y compared with maintaining a relatively stable consumption (i.e., change in intake of ±1.0 serving/wk). Increasing yogurt consumption by >0.5 serving/d was associated with an 11% (95% CI: 4%, 18%) lower T2D risk, whereas increasing cheese consumption by >0.5 serving/d was associated with a 9% (95% CI: 2%, 16%) higher risk compared with maintaining stable intakes. Substituting 1 serving/d of yogurt or reduced-fat milk for cheese was associated with a 16% (95% CI: 10%, 22%) or 12% (95% CI: 8%, 16%) lower T2D risk, respectively. CONCLUSIONS Increasing yogurt consumption was associated with a moderately lower risk of T2D, whereas increasing cheese consumption was associated with a moderately higher risk among US men and women. Our study suggests that substituting yogurt or reduced-fat milk for cheese is associated with a lower risk of T2D.
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Affiliation(s)
- Jean-Philippe Drouin-Chartier
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Address correspondence to J-PD-C e-mail:
| | - Yanping Li
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Andres Victor Ardisson Korat
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ming Ding
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Benoît Lamarche
- School of Nutrition and Institute of Nutrition and Functional Foods, Laval University, Quebec City, Quebec, Canada
| | - JoAnn E Manson
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA,Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric B Rimm
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Walter C Willett
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA,Address correspondence to FBH e-mail:
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