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Brennan L, de Roos B. Role of metabolomics in the delivery of precision nutrition. Redox Biol 2023; 65:102808. [PMID: 37423161 PMCID: PMC10461186 DOI: 10.1016/j.redox.2023.102808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/14/2023] [Accepted: 07/04/2023] [Indexed: 07/11/2023] Open
Abstract
Precision nutrition aims to deliver personalised dietary advice to individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies for furthering the field of precision nutrition. Metabolomics in particular is highly attractive as measurement of metabolites can capture information on food intake, levels of bioactive compounds and the impact of diets on endogenous metabolism. These aspects contain useful information for precision nutrition. Furthermore using metabolomic profiles to identify subgroups or metabotypes is attractive for the delivery of personalised dietary advice. Combining metabolomic derived metabolites with other parameters in prediction models is also an exciting avenue for understanding and predicting response to dietary interventions. Examples include but not limited to role of one carbon metabolism and associated co-factors in blood pressure response. Overall, while evidence exists for potential in this field there are also many unanswered questions. Addressing these and clearly demonstrating that precision nutrition approaches enable adherence to healthier diets and improvements in health will be key in the near future.
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Affiliation(s)
- Lorraine Brennan
- Institute of Food and Health and Conway Institute, UCD School of Agriculture and Food Science, UCD, Belfield, Dublin 4, Ireland.
| | - Baukje de Roos
- The Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, United Kingdom
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Zhang T, Naudin S, Hong HG, Albanes D, Männistö S, Weinstein SJ, Moore SC, Stolzenberg-Solomon RZ. Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations. J Nutr 2023; 153:2389-2400. [PMID: 37328109 PMCID: PMC10493471 DOI: 10.1016/j.tjnut.2023.06.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/02/2023] [Accepted: 06/07/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles. OBJECTIVES Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles. METHODS We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts. RESULTS Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED. CONCLUSIONS Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.
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Affiliation(s)
- Ting Zhang
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Sabine Naudin
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States; Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Hyokyoung G Hong
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Satu Männistö
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Stephanie J Weinstein
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Steven C Moore
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Rachael Z Stolzenberg-Solomon
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States.
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Tian P, Liu Y, Wang J, Xing L, Liu P. Psycho-Cardiological Disease in COVID-19 Era. Rev Cardiovasc Med 2023; 24:239. [PMID: 39076704 PMCID: PMC11266770 DOI: 10.31083/j.rcm2408239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/27/2023] [Accepted: 03/03/2023] [Indexed: 07/31/2024] Open
Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, panic and public health responses, including self-monitored quarantine and lockdown of the city, have severely impacted mental health and caused depression or anxiety in citizens. Psycho-cardiology indicates that psychological factor plays an important role in coronary heart disease (CHD). COVID-19, depression and CHD can co-exist and deleteriously affect each other, leading to worse progression and prognosis. Delays in medical consultation and treatment have become more common than before the pandemic, inducing more cardiovascular (CV) events and sequelae. COVID-19 survivors have been identified to have more psycho-cardiological symptoms compared with non-COVID-19 controls. Undoubtedly, diet alterations and sedentary lifestyles during the pandemic will cause and aggravate psycho-cardiological diseases. Some frequently used cardiovascular drugs were found to associate with changes in depression. With the advent of the post-pandemic era, although the acute damage of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is gradually declining, the psycho-cardiological diseases related to the novel coronavirus are becoming increasingly prominent. So it is an important issue for us to explore the pathogenesis, clinical manifestations and corresponding preventive measures of this aspect.
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Affiliation(s)
- Peiqing Tian
- Department of Cardiology, The Second Hospital of Shandong University, 250033 Jinan, Shandong, China
| | - Yixuan Liu
- School of Clinical and Basic Medicine, Shandong First Medical University, 250117 Taian, Shandong, China
| | - Jiayu Wang
- Department of Cardiology, The Second Hospital of Shandong University, 250033 Jinan, Shandong, China
| | - Liyun Xing
- Department of Cardiology, The Second Hospital of Shandong University, 250033 Jinan, Shandong, China
| | - Ping Liu
- Department of Cardiology, The Second Hospital of Shandong University, 250033 Jinan, Shandong, China
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Han X, Lains I, Li J, Li J, Chen Y, Yu B, Qi Q, Boerwinkle E, Kaplan R, Thyagarajan B, Daviglus M, Joslin CE, Cai J, Guasch-Ferré M, Tobias DK, Rimm E, Ascherio A, Costenbader K, Karlson E, Mucci L, Eliassen AH, Zeleznik O, Miller J, Vavvas DG, Kim IK, Silva R, Miller J, Hu F, Willett W, Lasky-Su J, Kraft P, Richards JB, MacGregor S, Husain D, Liang L. Integrating genetics and metabolomics from multi-ethnic and multi-fluid data reveals putative mechanisms for age-related macular degeneration. Cell Rep Med 2023; 4:101085. [PMID: 37348500 PMCID: PMC10394104 DOI: 10.1016/j.xcrm.2023.101085] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/22/2023] [Accepted: 05/22/2023] [Indexed: 06/24/2023]
Abstract
Age-related macular degeneration (AMD) is a leading cause of blindness in older adults. Investigating shared genetic components between metabolites and AMD can enhance our understanding of its pathogenesis. We conduct metabolite genome-wide association studies (mGWASs) using multi-ethnic genetic and metabolomic data from up to 28,000 participants. With bidirectional Mendelian randomization analysis involving 16,144 advanced AMD cases and 17,832 controls, we identify 108 putatively causal relationships between plasma metabolites and advanced AMD. These metabolites are enriched in glycerophospholipid metabolism, lysophospholipid, triradylcglycerol, and long chain polyunsaturated fatty acid pathways. Bayesian genetic colocalization analysis and a customized metabolome-wide association approach prioritize putative causal AMD-associated metabolites. We find limited evidence linking urine metabolites to AMD risk. Our study emphasizes the contribution of plasma metabolites, particularly lipid-related pathways and genes, to AMD risk and uncovers numerous putative causal associations between metabolites and AMD risk.
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Affiliation(s)
- Xikun Han
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Ines Lains
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jinglun Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yiheng Chen
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada; Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis, MN, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Charlotte E Joslin
- Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alberto Ascherio
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Karen Costenbader
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth Karlson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lorelei Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - A Heather Eliassen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T.H. 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
| | - Oana Zeleznik
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - John Miller
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Demetrios G Vavvas
- Retina Service, Ines and Fredrick Yeatts Retinal Research Laboratory, Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Ivana K Kim
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Rufino Silva
- Ophthalmology Unit, Centro Hospitalar e Universitário de Coimbra (CHUC), Coimbra, Portugal; University Clinic of Ophthalmology, Faculty of Medicine, University of Coimbra (FMUC), Coimbra, Portugal; Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal
| | - Joan Miller
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Frank Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Walter Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessica Lasky-Su
- Systems Genetics and Genomics Unit, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada; Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, McGill University, Montréal, QC, Canada; Department of Twin Research, King's College London, London, UK; Five Prime Sciences Inc, Montréal, QC, Canada
| | - Stuart MacGregor
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Deeba Husain
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA.
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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Yang J, Lu J, Miao J, Li J, Zhu M, Dai J, Ma H, Jin G, Hang D. Development and validation of a blood biomarker score for predicting mortality risk in the general population. J Transl Med 2023; 21:471. [PMID: 37454089 PMCID: PMC10349520 DOI: 10.1186/s12967-023-04334-w] [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: 12/21/2022] [Accepted: 07/09/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Blood biomarkers for multiple pathways, such as inflammatory response, lipid metabolism, and hormonal regulation, have been suggested to influence the risk of mortality. However, few studies have systematically evaluated the combined predictive ability of blood biomarkers for mortality risk. METHODS We included 267,239 participants from the UK Biobank who had measurements of 28 blood biomarkers and were free of cardiovascular disease (CVD) and cancer at baseline (2006-2010). We developed sex-specific blood biomarker scores for predicting all-cause mortality risk in a training set of 247,503 participants from England and Wales, and validated the results in 19,736 participants from Scotland. Cox and LASSO regression analyses were performed to identify independent predictors for men and women separately. Discrimination and calibration were evaluated by C-index and calibration plots, respectively. We also assessed mediating effects of the biomarkers on the association between traditional risk factors (current smoking, obesity, physical inactivity, hypertension, diabetes) and mortality. RESULTS A total of 13 independent predictive biomarkers for men and 17 for women were identified and included in the score development. Compared to the lowest tertile of the score, the highest tertile showed a hazard ratio of 5.36 (95% confidence interval [CI] 5.04-5.71) in men and 4.23 (95% CI 3.87-4.62) in women for all-cause mortality. In the validation set, the score yielded a C-index of 0.73 (95% CI 0.72-0.75) in men and 0.70 (95% CI 0.68-0.73) in women for all-cause mortality; it was also predictive of CVD (C-index of 0.76 in men and 0.79 in women) and cancer (C-index of 0.70 in men and 0.67 in women) mortality. Moreover, the association between traditional risk factors and all-cause mortality was largely mediated by cystatin C, C-reactive protein, 25-hydroxyvitamin D, and hemoglobin A1c. CONCLUSIONS We established sex-specific blood biomarker scores for predicting all-cause and cause-specific mortality in the general population, which hold the potential to identify high-risk individuals and improve targeted prevention of premature death.
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Affiliation(s)
- Jing Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
| | - Jiayi Lu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
| | - Junyan Miao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
| | - Jiacong Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China.
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Wang Y, Li X, Qi M, Li X, Zhang F, Wang Y, Wu J, Shu L, Fan S, Li Y, Li Y. Pharmacological effects and mechanisms of YiYiFuZi powder in chronic heart disease revealed by metabolomics and network pharmacology. Front Mol Biosci 2023; 10:1203208. [PMID: 37426419 PMCID: PMC10327484 DOI: 10.3389/fmolb.2023.1203208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/12/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction: YiYiFuZi powder (YYFZ) is a classical formula in Chinese medicine, which is commonly used clinically for the treatment of Chronic Heart Disease (CHD), but it's pharmacological effects and mechanism of action are currently unclear. Methods: An adriamycin-induced CHD model rat was established to evaluate the pharmacological effects of YYFZ on CHD by the results of inflammatory factor level, histopathology and echocardiography. Metabolomic studies were performed on rat plasma using UPLC-Q-TOF/MS to screen biomarkers and enrich metabolic pathways; network pharmacology analysis was also performed to obtain the potential targets and pathways of YYFZ for the treatment of CHD. Results: The results showed that YYFZ significantly reduced the levels of TNF-α and BNP in the serum of rats, alleviated the disorder of cardiomyocyte arrangement and inflammatory cell infiltration, and improved the cardiac function of rats with CHD. The metabolomic analysis identified a total of 19 metabolites, related to amino acid metabolism, fatty acid metabolism, and other metabolic pathways. Network pharmacology showed that YYFZ acts through PI3K/Akt signaling pathway, MAPK signaling pathway and Ras signaling pathway. Discussion: YYFZ treatment of CHD modulates blood metabolic pattern and several protein phosphorylation cascades but importance specific changes for therapeutic effect require further studies.
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Affiliation(s)
- Yuming Wang
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xue Li
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Min Qi
- TIPRHUYA Advancing Innovative Medicines Ltd., Tianjin, China
| | - Xiaokai Li
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Fangfang Zhang
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yuyu Wang
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Junke Wu
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lexin Shu
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Simiao Fan
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yunfei Li
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yubo Li
- School of Chinese Materia, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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Deng K, Gupta DK, Shu XO, Lipworth L, Zheng W, Thomas VE, Cai H, Cai Q, Wang TJ, Yu D. Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease among Low-Income Black and White Americans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.24.23289055. [PMID: 37163035 PMCID: PMC10168489 DOI: 10.1101/2023.04.24.23289055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background and Aims Life's Essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals. Methods In a nested case-control study of coronary heart disease (CHD) among 598 Black and 596 White low-income Americans, we estimated LE8 score, conducted untargeted plasma metabolites profiling, and used elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. Mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 598 Chinese adults. Results Higher LE8 score was associated with lower CHD risk [standardized OR (95% CI)=0.61 (0.53-0.69)]. The identified MetaSig, consisting of 133 metabolites, showed strong correlation with LE8 score ( r =0.61) and inverse association with CHD risk [OR (95% CI)=0.57 (0.49-0.65)], robust to adjustment for LE8 score and across participants with different sociodemographic and health status (ORs: 0.42-0.69; all P <0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%) ( P <0.001). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort [ r =0.49; OR (95% CI)=0.57 (0.46-0.69)]. Conclusions Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective and comprehensive measure of LE8 score and its metabolic phenotype relevant to CHD prevention among diverse populations.
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Zhang J, Fang XY, Leng R, Chen HF, Qian TT, Cai YY, Zhang XH, Wang YY, Mu M, Tao XR, Leng RX, Ye DQ. Metabolic signature of healthy lifestyle and risk of rheumatoid arthritis: observational and Mendelian randomization study. Am J Clin Nutr 2023:S0002-9165(23)48892-2. [PMID: 37127109 DOI: 10.1016/j.ajcnut.2023.04.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/10/2023] [Accepted: 04/26/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND While substantial evidence reveals that healthy lifestyle behaviors are associated with a lower risk of rheumatoid arthritis (RA), the underlying metabolic mechanisms remain unclear. OBJECTIVES This study aimed to identify the metabolic signature reflecting a healthy lifestyle and investigate its observational and genetic linkage with RA risk. METHODS This study included 87,258 UK Biobank participants (557 cases of incident RA) aged 37 to 73 years with complete lifestyle, genotyping and nuclear magnetic resonance (NMR) metabolomics data. A healthy lifestyle was assessed based on five factors: healthy diet, regular exercise, not smoking, moderate alcohol consumption, and normal body mass index. The metabolic signature was developed by summing selected metabolites' concentrations weighted by the coefficients using elastic net regression. We used multivariate Cox model to assess the associations between metabolic signatures and RA risk, and examined the mediating role of the metabolic signature in the impact of a healthy lifestyle on RA. We performed genome-wide association analysis (GWAS) to obtain genetic variants associated with the metabolic signature, then conducted Mendelian randomization (MR) analyses to detect causality. RESULTS The metabolic signature comprised of 81 metabolites, robustly correlated with healthy lifestyle ( r = 0.45, P = 4.2 × 10-15). The metabolic signature was inversely associated with RA risk (HR per SD increment: 0.76, 95% CI: 0.70-0.83), and largely explained protective effects of healthy lifestyle on RA with 64% (95%CI: 50.4-83.3) mediation proportion. One and two-sample MR analyses also consistently showed the associations of genetically inferred per SD increment in metabolic signature with a reduction in RA risk (HR: 0.84, 95% CI: 0.75-0.94, P = 0.002 and OR: 0.84, 95% CI: 0.73-0.97, P = 0.02 respectively). CONCLUSION Our findings implicate the metabolic signature reflecting healthy lifestyle as a potential causal mediator in the development of RA, highlighting the importance of early lifestyle intervention and metabolic tracking for precise prevention of RA.
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Affiliation(s)
- Jie Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xin-Yu Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Rui Leng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Hai-Feng Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Ting-Ting Qian
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Yu-Yu Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xin-Hong Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Yi-Yu Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Min Mu
- School of Public Health, Anhui University of Science and Technology, Huainan, Anhui, 232001, China
| | - Xin-Rong Tao
- School of Public Health, Anhui University of Science and Technology, Huainan, Anhui, 232001, China
| | - Rui-Xue Leng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China.
| | - Dong-Qing Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China; School of Public Health, Anhui University of Science and Technology, Huainan, Anhui, 232001, China.
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Xie R, Ning Z, Xiao M, Li L, Liu M, Zhang Y. Dietary inflammatory potential and biological aging among US adults: a population-based study. Aging Clin Exp Res 2023; 35:1273-1281. [PMID: 37186209 DOI: 10.1007/s40520-023-02410-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/10/2023] [Indexed: 05/17/2023]
Abstract
OBJECTIVES The rate of biological aging is influenced by various factors such as genetics, environment, and diet. The dietary inflammatory index (DII) is strongly associated with various chronic diseases. The aim of this study was to investigate the association between DII and biological aging in US adults using quantitative indicators. METHODS Based on data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018, weighted multiple linear regression models, generalized weighted models, and smoothed fitted curves were used to investigate the linear and nonlinear relationships of DII with four biological markers of aging (biological age, phenotypic age, telomere length, and serum klotho concentration). RESULTS A total of 35,575 adult participants with complete data were included in the study. After adjusting for all confounders, significant positive correlations were found between DII with biological age [0.070 (0.045, 0.095)] and phenotypic age [0.421 (0.371, 0.471)], with an increase of 0.07 and 0.42 years in biological age and phenotypic age, respectively, for each increase in DII score. The negative correlations between DII with telomere length [ - 0.005 ( - 0.008, - 0.002)] and klotho [ - 3.874 ( - 7.409, - 0.338)] were significant only in partially adjusted models and differed across subgroups. CONCLUSIONS In the current study, higher DII scores (greater pro-inflammatory dietary potential) were associated with biological aging. These findings may contribute to the development of aging prevention strategies through dietary interventions.
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Affiliation(s)
- Ruijie Xie
- Department of Hand & Microsurgery, Hengyang Medical School, The Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, China
| | - Zhongxing Ning
- Department of Intensive Care Unit, The People's Hospital of Guangxi Zhuang Autonomous Region & Research Center of Intensive Care Unit, Nanning, 530021, China
| | - Mengde Xiao
- Department of Quality Evaluation Office, Hengyang Medical School, The Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, China
| | - Lihong Li
- Department of Gland Surgery, Hengyang Medical School, The Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, China
| | - Mingjiang Liu
- Department of Hand & Microsurgery, Hengyang Medical School, The Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, China.
| | - Ya Zhang
- Department of Gland Surgery, Hengyang Medical School, The Affiliated Nanhua Hospital, University of South China, Hengyang, 421002, China.
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60
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Konečný L, Hrubša M, Karlíčková J, Carazo A, Javorská L, Matoušová K, Krčmová LK, Šmahelová A, Blaha V, Bláha M, Mladěnka P. The Effect of 4-Methylcatechol on Platelets in Familial Hypercholesterolemic Patients Treated with Lipid Apheresis and/or Proprotein Convertase Subtilisin Kexin 9 Monoclonal Antibodies. Nutrients 2023; 15:nu15081842. [PMID: 37111061 PMCID: PMC10143685 DOI: 10.3390/nu15081842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/30/2023] [Accepted: 04/05/2023] [Indexed: 04/29/2023] Open
Abstract
Elevated low-density lipoprotein (LDL) cholesterol levels lead to atherosclerosis and platelet hyperaggregability, both of which are known culprits of arterial thrombosis. Normalization of LDL cholesterol in familial hypercholesterolemia (FH) is not an easy task and frequently requires specific treatment, such as regularly performed lipid apheresis and/or novel drugs such as proprotein convertase subtilisin kexin 9 monoclonal antibodies (PCSK9Ab). Moreover, a high resistance rate to the first-line antiplatelet drug acetylsalicylic acid (ASA) stimulated research of novel antiplatelet drugs. 4-methylcatechol (4-MC), a known metabolite of several dietary flavonoids, may be a suitable candidate. The aim of this study was to analyse the antiplatelet effect of 4-MC in FH patients and to compare its impact on two FH treatment modalities via whole-blood impedance aggregometry. When compared to age-matched, generally healthy controls, the antiplatelet effect of 4-MC against collagen-induced aggregation was higher in FH patients. Apheresis itself improved the effect of 4-MC on platelet aggregation and blood from patients treated with this procedure and pretreated with 4-MC had lower platelet aggregability when compared to those solely treated with PCKS9Ab. Although this study had some inherent limitations, e.g., a low number of patients and possible impact of administered drugs, it confirmed the suitability of 4-MC as a promising antiplatelet agent and also demonstrated the effect of 4-MC in patients with a genetic metabolic disease for the first time.
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Affiliation(s)
- Lukáš Konečný
- The Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Marcel Hrubša
- The Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Jana Karlíčková
- The Department of Pharmacognosy and Pharmaceutical Botany, Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Alejandro Carazo
- The Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Lenka Javorská
- The Department of Clinical Biochemistry and Diagnostics, University Hospital Hradec Králové, 50005 Hradec Králové, Czech Republic
| | - Kateřina Matoušová
- The Department of Clinical Biochemistry and Diagnostics, University Hospital Hradec Králové, 50005 Hradec Králové, Czech Republic
| | - Lenka Kujovská Krčmová
- The Department of Clinical Biochemistry and Diagnostics, University Hospital Hradec Králové, 50005 Hradec Králové, Czech Republic
| | - Alena Šmahelová
- The 3rd Department of Internal Medicine-Metabolic Care and Gerontology, University Hospital and Faculty of Medicine in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Vladimír Blaha
- The 3rd Department of Internal Medicine-Metabolic Care and Gerontology, University Hospital and Faculty of Medicine in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Milan Bláha
- The 3rd Department of Internal Medicine-Metabolic Care and Gerontology, University Hospital and Faculty of Medicine in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
| | - Přemysl Mladěnka
- The Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic
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61
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Sellem L, Eichelmann F, Jackson KG, Wittenbecher C, Schulze MB, Lovegrove JA. Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial. Am J Clin Nutr 2023:S0002-9165(23)46314-9. [PMID: 37062359 DOI: 10.1016/j.ajcnut.2023.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 04/18/2023] Open
Abstract
BACKGROUND The effects of replacing dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) and/or polyunsaturated fatty acids (PUFAs) on the plasma lipidome in relation to the cardiometabolic disease (CMD) risk are poorly understood. OBJECTIVES We aimed to assess the impact of substituting dietary SFAs with unsaturated fatty acids (UFAs) on the plasma lipidome and examine the relationship between lipid metabolites modulated by diet and CMD risk. METHODS Plasma fatty acid (FA) concentrations among 16 lipid classes (within-class FAs) were measured in a subgroup from the Dietary Intervention and VAScular function (DIVAS) parallel randomized controlled trial (n = 113/195), which consisted of three 16-wk diets enriched in SFAs (target SFA:MUFA:n-6PUFA ratio = 17:11:4% total energy [TE]), MUFAs (9:19:4% TE), or a MUFA/PUFA mixture (9:13:10% TE). Similar lipidomics analyses were conducted in the European investigation into Cancer and Nutrition (EPIC)-Potsdam prospective cohort study (specific case/cohorts: n = 775/1886 for type 2 diabetes [T2D], n = 551/1671 for cardiovascular disease [CVD]). Multiple linear regression and multivariable Cox models identified within-class FAs sensitive to replacement of dietary SFA with UFA in DIVAS and their association with CMD risk in EPIC-Potsdam. Elastic-net regression models identified within-class FAs associated with changes in CMD risk markers post-DIVAS interventions. RESULTS DIVAS high-UFA interventions reduced plasma within-class FAs associated with a higher CVD risk in EPIC-Potsdam, especially SFA-containing glycerolipids and sphingolipids (e.g., diacylglycerol (20:0) z-score = -1.08; SE = 0.17; P value < 10-8), whereas they increased those inversely associated with CVD risk. The results on T2D were less clear. Specific sphingolipids and phospholipids were associated with changes in markers of endothelial function and ambulatory blood pressure, whereas higher low-density lipoprotein cholesterol concentrations were characterized by higher plasma glycerolipids containing lauric and stearic acids. CONCLUSIONS These results suggest a mediating role of plasma lipid metabolites in the association between dietary fat and CMD risk. Future research combining interventional and observational findings will further our understanding of the role of dietary fat in CMD etiology. This trial was registered in ClinicalTrials.gov as NCT01478958.
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Affiliation(s)
- Laury Sellem
- Hugh Sinclair Unit of Human Nutrition, and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Science, University of Reading, Whiteknights, Pepper Lane, Harry Nursten Building, Reading, UK
| | - Fabian Eichelmann
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Kim G Jackson
- Hugh Sinclair Unit of Human Nutrition, and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Science, University of Reading, Whiteknights, Pepper Lane, Harry Nursten Building, Reading, UK
| | - Clemens Wittenbecher
- Division of Food Science and Nutrition, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition, and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Science, University of Reading, Whiteknights, Pepper Lane, Harry Nursten Building, Reading, UK.
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Sobiecki JG, Imamura F, Davis CR, Sharp SJ, Koulman A, Hodgson JM, Guevara M, Schulze MB, Zheng JS, Agnoli C, Bonet C, Colorado-Yohar SM, Fagherazzi G, Franks PW, Gundersen TE, Jannasch F, Kaaks R, Katzke V, Molina-Montes E, Nilsson PM, Palli D, Panico S, Papier K, Rolandsson O, Sacerdote C, Tjønneland A, Tong TYN, van der Schouw YT, Danesh J, Butterworth AS, Riboli E, Murphy KJ, Wareham NJ, Forouhi NG. A nutritional biomarker score of the Mediterranean diet and incident type 2 diabetes: Integrated analysis of data from the MedLey randomised controlled trial and the EPIC-InterAct case-cohort study. PLoS Med 2023; 20:e1004221. [PMID: 37104291 PMCID: PMC10138823 DOI: 10.1371/journal.pmed.1004221] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 03/15/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Self-reported adherence to the Mediterranean diet has been modestly inversely associated with incidence of type 2 diabetes (T2D) in cohort studies. There is uncertainty about the validity and magnitude of this association due to subjective reporting of diet. The association has not been evaluated using an objectively measured biomarker of the Mediterranean diet. METHODS AND FINDINGS We derived a biomarker score based on 5 circulating carotenoids and 24 fatty acids that discriminated between the Mediterranean or habitual diet arms of a parallel design, 6-month partial-feeding randomised controlled trial (RCT) conducted between 2013 and 2014, the MedLey trial (128 participants out of 166 randomised). We applied this biomarker score in an observational study, the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study, to assess the association of the score with T2D incidence over an average of 9.7 years of follow-up since the baseline (1991 to 1998). We included 22,202 participants, of whom 9,453 were T2D cases, with relevant biomarkers from an original case-cohort of 27,779 participants sampled from a cohort of 340,234 people. As a secondary measure of the Mediterranean diet, we used a score estimated from dietary-self report. Within the trial, the biomarker score discriminated well between the 2 arms; the cross-validated C-statistic was 0.88 (95% confidence interval (CI) 0.82 to 0.94). The score was inversely associated with incident T2D in EPIC-InterAct: the hazard ratio (HR) per standard deviation of the score was 0.71 (95% CI: 0.65 to 0.77) following adjustment for sociodemographic, lifestyle and medical factors, and adiposity. In comparison, the HR per standard deviation of the self-reported Mediterranean diet was 0.90 (95% CI: 0.86 to 0.95). Assuming the score was causally associated with T2D, higher adherence to the Mediterranean diet in Western European adults by 10 percentiles of the score was estimated to reduce the incidence of T2D by 11% (95% CI: 7% to 14%). The study limitations included potential measurement error in nutritional biomarkers, unclear specificity of the biomarker score to the Mediterranean diet, and possible residual confounding. CONCLUSIONS These findings suggest that objectively assessed adherence to the Mediterranean diet is associated with lower risk of T2D and that even modestly higher adherence may have the potential to reduce the population burden of T2D meaningfully. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12613000602729 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=363860.
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Affiliation(s)
- Jakub G. Sobiecki
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Courtney R. Davis
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - Stephen J. Sharp
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Nutritional Biomarker Laboratory, National Institute for Health Research Biomedical Research Centre, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Jonathan M. Hodgson
- Nutrition & Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- Medical School, University of Western Australia, Perth, Australia
| | - Marcela Guevara
- Navarra Public Health Institute, Pamplona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Ju-Sheng Zheng
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy
| | - Catalina Bonet
- Unit of Nutrition and Cancer, Catalan Institute of Oncology—ICO, L’Hospitalet de Llobregat, Barcelona, Spain
- Nutrition and Cancer Group, Bellvitge Biomedical Research Institute—IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain
| | - Sandra M. Colorado-Yohar
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Insitute of Health, Strassen, Luxembourg
- Center of Epidemiology and Population Health UMR 1018, Inserm, Paris South—Paris Saclay University, Gustave Roussy Institute, Villejuif, France
| | - Paul W. Franks
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Franziska Jannasch
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Esther Molina-Montes
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Institute of Nutrition and Food Technology (INYTA) ‘José Mataix’, Biomedical Research Centre, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- Department of Nutrition and Food Science, University of Granada, Granada, Spain
| | | | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network—ISPRO, Florence, Italy
| | - Salvatore Panico
- Department of Mental, Physical Health and Preventive Medicine, University “L. Vanvitelli”, Naples, Italy
| | - Keren Papier
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Olov Rolandsson
- Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, Umeå, Sweden
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital, Turin, Italy
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tammy Y. N. Tong
- Department of Mental, Physical Health and Preventive Medicine, University “L. Vanvitelli”, Naples, Italy
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke’s Hospital, Cambridge, United Kingdom
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- Health Data Research UK Cambridge, University of Cambridge, Cambridge, United Kingdom
| | - Adam S. Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Elio Riboli
- School of Public Health, Imperial College London, London, United Kingdom
| | - Karen J. Murphy
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
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Qiu S, Cai Y, Yao H, Lin C, Xie Y, Tang S, Zhang A. Small molecule metabolites: discovery of biomarkers and therapeutic targets. Signal Transduct Target Ther 2023; 8:132. [PMID: 36941259 PMCID: PMC10026263 DOI: 10.1038/s41392-023-01399-3] [Citation(s) in RCA: 99] [Impact Index Per Article: 99.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 03/22/2023] Open
Abstract
Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.
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Affiliation(s)
- Shi Qiu
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China
| | - Ying Cai
- Graduate School, Heilongjiang University of Chinese Medicine, Harbin, 150040, China
| | - Hong Yao
- First Affiliated Hospital, Harbin Medical University, Harbin, 150081, China
| | - Chunsheng Lin
- Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, 150001, China
| | - Yiqiang Xie
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
| | - Songqi Tang
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
| | - Aihua Zhang
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
- Graduate School, Heilongjiang University of Chinese Medicine, Harbin, 150040, China.
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64
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Jin Q, Shi N, Lee DH, Rexrode KM, Manson JE, Balasubramanian R, Zhang X, Neuhouser ML, Lopez-Pentecost M, Thomson CA, Zick SM, Felix AS, Stover DG, Sardesai SD, Esnakula A, Mo X, Clinton SK, Tabung FK. Hyperinsulinemic and Pro-Inflammatory Dietary Patterns and Metabolomic Profiles Are Associated with Increased Risk of Total and Site-Specific Cancers among Postmenopausal Women. Cancers (Basel) 2023; 15:1756. [PMID: 36980642 PMCID: PMC10046106 DOI: 10.3390/cancers15061756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/02/2023] [Accepted: 03/08/2023] [Indexed: 03/15/2023] Open
Abstract
We evaluated associations of the Empirical Dietary Index for Hyperinsulinemia (EDIH), Empirical Dietary Inflammatory Pattern (EDIP) and Healthy Eating Index (HEI2015) and their metabolomics profiles with the risk of total and site-specific cancers. We used baseline food frequency questionnaires to calculate dietary scores among 112,468 postmenopausal women in the Women's Health Initiative. We used multivariable-adjusted Cox regression to estimate hazard ratios (HR) and 95% confidence intervals for cancer risk estimation. Metabolomic profile scores were derived using elastic-net regression with leave-one-out cross validation. In over 17.8 years, 18,768 incident invasive cancers were adjudicated. Higher EDIH and EDIP scores were associated with greater total cancer risk, and higher HEI-2015 with lower risk: HRQ5vsQ1(95% CI): EDIH, 1.10 (1.04-1.15); EDIP, 1.08 (1.02-1.15); HEI-2015, 0.93 (0.89-0.98). The multivariable-adjusted incidence rate difference(Q5vsQ1) for total cancer was: +52 (EDIH), +41 (EDIP) and -49 (HEI-2015) per 100,000 person years. All three indices were associated with colorectal cancer, and EDIH and EDIP with endometrial and breast cancer risk. EDIH was further associated with luminal-B, ER-negative and triple negative breast cancer subtypes. Dietary patterns contributing to hyperinsulinemia and inflammation were associated with greater cancer risk, and higher overall dietary quality, with lower risk. The findings warrant the testing of these dietary patterns in clinical trials for cancer prevention among postmenopausal women.
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Affiliation(s)
- Qi Jin
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
| | - Ni Shi
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Dong Hoon Lee
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Sport Industry Studies, Yonsei University, Seoul 03722, Republic of Korea
| | - Kathryn M. Rexrode
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts at Amherst, Amherst, MA 01003, USA
| | - Xuehong Zhang
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Marian L. Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Melissa Lopez-Pentecost
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Cynthia A. Thomson
- Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85721, USA
| | - Suzanna M. Zick
- Department of Family Medicine, Michigan Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ashley S. Felix
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
| | - Daniel G. Stover
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Sagar D. Sardesai
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Ashwini Esnakula
- Department of Pathology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Xiaokui Mo
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Steven K. Clinton
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Fred K. Tabung
- Interdisciplinary Ph.D. Program in Nutrition, The Ohio State University, Columbus, OH 43210, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
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Domínguez-López I, Arancibia-Riveros C, Marhuenda-Muñoz M, Tresserra-Rimbau A, Toledo E, Fitó M, Ros E, Estruch R, Lamuela-Raventós RM. Association of microbiota polyphenols with cardiovascular health in the context of a Mediterranean diet. Food Res Int 2023; 165:112499. [PMID: 36869451 DOI: 10.1016/j.foodres.2023.112499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 01/04/2023] [Accepted: 01/20/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND AND AIMS The Mediterranean diet (MedDiet) is rich in polyphenols, phytochemicals that are beneficial for cardiovascular health. Phenolic compounds have poor bioavailability but they are extensively metabolized by the gut microbiota. Therefore, we aimed to assess the association of microbial phenolic metabolites (MPM) with adherence to the MedDiet, and their relationship with ideal cardiovascular health (ICVH) and cardiovascular risk factors. METHODS AND RESULTS This cross-sectional substudy within the PREDIMED trial included 200 participants from the Barcelona-Clinic recruitment center. Five MPM were identified and quantified using a novel method based on liquid chromatography coupled to mass spectrometry: protocatechuic acid (PCA), enterodiol glucuronide (EDG), enterolactone glucuronide (ELG), vanillic acid glucuronide (VAG) and urolithin B glucuronide (UBG). Multivariable-adjusted regressions were used to evaluate the associations between MPM and MedDiet adherence, ICVH score, biochemical parameters, and blood pressure. Additionally, an MPM score was calculated as the weighted sum of MedDiet adherence and ICVH and found to be directly associated. Among individual polyphenols, UBG was inversely associated with LDL-cholesterol. CONCLUSIONS A score of urinary MPM was associated with higher adherence to the MedDiet and ICVH, and individual MPM were related to better cardiovascular health. These findings suggest that the MedDiet may affect gut microbiota, whose metabolites are linked with cardiovascular health.
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Affiliation(s)
- Inés Domínguez-López
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona (UB), Av. de Joan XXII, 27-31, 08028 Barcelona, Spain; Institut de Nutrició i Seguretat Alimentària (INSA), Universitat de Barcelona (UB), Santa Coloma de Gramanet, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Camila Arancibia-Riveros
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona (UB), Av. de Joan XXII, 27-31, 08028 Barcelona, Spain; Institut de Nutrició i Seguretat Alimentària (INSA), Universitat de Barcelona (UB), Santa Coloma de Gramanet, Spain
| | - María Marhuenda-Muñoz
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona (UB), Av. de Joan XXII, 27-31, 08028 Barcelona, Spain; Institut de Nutrició i Seguretat Alimentària (INSA), Universitat de Barcelona (UB), Santa Coloma de Gramanet, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Anna Tresserra-Rimbau
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona (UB), Av. de Joan XXII, 27-31, 08028 Barcelona, Spain; Institut de Nutrició i Seguretat Alimentària (INSA), Universitat de Barcelona (UB), Santa Coloma de Gramanet, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Estefanía Toledo
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain; Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31008 Pamplona, Spain
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain; Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas (IMIM), 08007 Barcelona, Spain
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain; Department of Endocrinology, Hospital Clinic, IDIBAPS, Barcelona, Spain
| | - Ramon Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain; Department of Internal Medicine, Hospital Clinic, Institut d'Investigació Biomèdica August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Rosa M Lamuela-Raventós
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Universitat de Barcelona (UB), Av. de Joan XXII, 27-31, 08028 Barcelona, Spain; Institut de Nutrició i Seguretat Alimentària (INSA), Universitat de Barcelona (UB), Santa Coloma de Gramanet, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
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Bhave VM, Ament Z, Patki A, Gao Y, Kijpaisalratana N, Guo B, Chaudhary NS, Garcia Guarniz AL, Gerszten R, Correa A, Cushman M, Judd S, Irvin MR, Kimberly WT. Plasma Metabolites Link Dietary Patterns to Stroke Risk. Ann Neurol 2023; 93:500-510. [PMID: 36373825 PMCID: PMC9974740 DOI: 10.1002/ana.26552] [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: 06/09/2022] [Revised: 11/04/2022] [Accepted: 11/12/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE While dietary intake is linked to stroke risk, surrogate markers that could inform personalized dietary interventions are lacking. We identified metabolites associated with diet patterns and incident stroke in a nested cohort from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. METHODS Levels of 162 metabolites were measured in baseline plasma from stroke cases (n = 1,198) and random controls (n = 904). We examined associations between metabolites and a plant-based diet pattern previously linked to reduced stroke risk in REGARDS. Secondary analyses included 3 additional stroke-associated diet patterns: a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Southern diet. Metabolites were tested using Cox proportional hazards models with incident stroke as the outcome. Replication was performed in the Jackson Heart Study (JHS). Inverse odds ratio-weighted mediation was used to determine whether metabolites mediated the association between a plant-based diet and stroke risk. RESULTS Metabolites associated with a plant-based diet included the gut metabolite indole-3-propionic acid (β = 0.23, 95% confidence interval [CI] [0.14, 0.33], p = 1.14 × 10-6 ), guanosine (β = -0.13, 95% CI [-0.19, -0.07], p = 6.48 × 10-5 ), gluconic acid (β = -0.11, 95% CI [-0.18, -0.04], p = 2.06 × 10-3 ), and C7 carnitine (β = -0.16, 95% CI [-0.24, -0.09], p = 4.14 × 10-5 ). All of these metabolites were associated with both additional diet patterns and altered stroke risk. Mediation analyses identified guanosine (32.6% mediation, p = 1.51 × 10-3 ), gluconic acid (35.7%, p = 2.28 × 10-3 ), and C7 carnitine (26.2%, p = 1.88 × 10-2 ) as mediators linking a plant-based diet to reduced stroke risk. INTERPRETATION A subset of diet-related metabolites are associated with risk of stroke. These metabolites could serve as surrogate markers that inform dietary interventions. ANN NEUROL 2023;93:500-510.
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Affiliation(s)
| | - Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Amit Patki
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Naruchorn Kijpaisalratana
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Boyi Guo
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Ninad S. Chaudhary
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
- The University of Texas Health Science Center at Houston, Houston, TX
| | | | - Robert Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Adolfo Correa
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Suzanne Judd
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - M. Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - W. Taylor Kimberly
- Harvard Medical School, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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67
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Chen L, Dai J, Fei Z, Liu X, Zhu Y, Rahman ML, Lu R, Mitro SD, Yang J, Hinkle SN, Chen Z, Song Y, Zhang C. Metabolomic biomarkers of the mediterranean diet in pregnant individuals: A prospective study. Clin Nutr 2023; 42:384-393. [PMID: 36753781 PMCID: PMC10029322 DOI: 10.1016/j.clnu.2023.01.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/14/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
BACKGROUND AND AIMS Metabolomic profiling is a systematic approach to identifying biomarkers for dietary patterns. Yet, metabolomic markers for dietary patterns in pregnant individuals have not been investigated. The aim of this study was to identify plasma metabolomic markers and metabolite panels that are associated with the Mediterranean diet in pregnant individuals. METHODS This is a prospective study of 186 pregnant individuals who had both dietary intake and metabolomic profiles measured from the Fetal Growth Studies-Singletons cohort. Dietary intakes during the peri-conception/1st trimester and the second trimester were accessed at 8-13 and 16-22 weeks of gestation, respectively. Adherence to the Mediterranean diet was measured by the alternate Mediterranean Diet (aMED) score. Fasting plasma samples were collected at 16-22 weeks and untargeted metabolomics profiling was performed using the mass spectrometry-based platforms. Metabolites individually or jointly associated with aMED scores were identified using linear regression and least absolute shrinkage and selection operator (LASSO) regression models with adjustment for potential confounders, respectively. RESULTS Among 459 annotated metabolites, 64 and 41 were individually associated with the aMED scores of the diet during the peri-conception/1st trimester and during the second trimester, respectively. Fourteen metabolites were associated with the Mediterranean diet in both time windows. Most Mediterranean diet-related metabolites were lipids (e.g., acylcarnitine, cholesteryl esters (CEs), linoleic acid, long-chain triglycerides (TGs), and phosphatidylcholines (PCs), amino acids, and sugar alcohols. LASSO regressions also identified a 10 metabolite-panel that were jointly associated with aMED score of the diet during the peri-conception/1st trimester (AUC: 0.74; 95% CI: 0.57, 0.91) and a 3 metabolites-panel in the 2nd trimester (AUC: 0.68; 95% CI: 0.50, 0.86). CONCLUSION We identified plasma metabolomic markers for the Mediterranean diet among pregnant individuals. Some of them have also been reported in previous studies among non-pregnant populations, whereas others are novel. The results from our study warrant replication in pregnant individuals by future studies. CLINICAL TRIAL REGISTRATION NUMBER This study was registered at ClinicalTrials.gov.
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Affiliation(s)
- Liwei Chen
- Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Jin Dai
- Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Zhe Fei
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Xinyue Liu
- Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Yeyi Zhu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA.
| | - Mohammad L Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA.
| | - Ruijin Lu
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD, USA.
| | - Susanna D Mitro
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD, USA.
| | - Jiaxi Yang
- Global Center for Asian Women's Health, and Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, 117549, Singapore; Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, 119228, Singapore.
| | - Stefanie N Hinkle
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Zhen Chen
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD, USA.
| | - Yiqing Song
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA.
| | - Cuilin Zhang
- Global Center for Asian Women's Health, and Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, 117549, Singapore; Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, 119228, Singapore.
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Chen P, Yang Z, Fan Z, Wang B, Tang Y, Xiao Y, Chen X, Luo D, Xiao S, Li J, Xie H, Shen M. Associations of adherence to Mediterranean-like diet pattern with incident rosacea: A prospective cohort study of government employees in China. Front Nutr 2023; 10:1092781. [PMID: 36819686 PMCID: PMC9932686 DOI: 10.3389/fnut.2023.1092781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Background Despite of growing evidence on gastrointestinal comorbidities of rosacea, there was a lack of literatures regarding the role of diet on rosacea. Objectives To investigate the relationship between adherence to a Mediterranean-like diet pattern and the risk of incident rosacea. Methods This was a prospective cohort study of government employees aged >20 years conducted between January 2018 and December 2021 from five cities of Hunan province of China. At baseline, participants completed a food frequency questionnaire and participated in a skin examination. Presence of rosacea was determined by certified dermatologists. Subsequent skin examinations during follow-up were performed every one-year interval since the entry of the study. The Mediterranean diet score (MDS) was generated based on seven food groups (whole grains, red meats, fish, raw vegetables, legumes, fruits and nuts). Binary logistic regression models adjusted for potential confounders were used to estimate risks for incident rosacea. Results Of the 3,773 participants who completed at least two consecutive skin examinations, 3,496 were eligible for primary analyses. With a total follow-up of 8,668 person-years, we identified 83 incident rosacea cases. After full adjustments for covariates, the MDS was associated a decreased risk of incident rosacea (aOR: 0.84, 95% CI: 0.72, 0.99; P trend = 0.037 for 1-point increment of MDS). In subgroup analyses by body mass index (BMI), this inverse association was consistently observed in the lowest and medium tertiles of BMI (<24.5 kg/m2), but not in the highest tertile of BMI (≥24.5 kg/m2), with a significant interaction effect (P < 0.001). Conclusions Our results suggested that adherence to a Mediterranean-like diet pattern might reduce the risk of incident rosacea among non-overweight individuals.
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Affiliation(s)
- Peng Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Ziye Yang
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhihua Fan
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Ben Wang
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Yan Tang
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Yi Xiao
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiang Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Furong Laboratory, Changsha, China
| | - Dan Luo
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Hongfu Xie
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
| | - Minxue Shen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.,Furong Laboratory, Changsha, China.,Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China
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69
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Crea F. New facets of prevention: diet assessment, childhood adversity, influenza vaccination, and guideline implementation. Eur Heart J 2023; 44:537-540. [PMID: 36780922 DOI: 10.1093/eurheartj/ehad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/15/2023] Open
Affiliation(s)
- Filippo Crea
- Department of Cardiovascular Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.,Department of Cardiovascular and Pulmonary Sciences, Catholic University of the Sacred Heart, Rome, Italy
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Shah RV, Steffen LM, Nayor M, Reis JP, Jacobs DR, Allen NB, Lloyd-Jones D, Meyer K, Cole J, Piaggi P, Vasan RS, Clish CB, Murthy VL. Dietary metabolic signatures and cardiometabolic risk. Eur Heart J 2023; 44:557-569. [PMID: 36424694 PMCID: PMC10169425 DOI: 10.1093/eurheartj/ehac446] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 06/23/2022] [Accepted: 07/28/2022] [Indexed: 11/27/2022] Open
Abstract
AIMS Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. METHODS AND RESULTS In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. CONCLUSION Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.
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Affiliation(s)
- Ravi V Shah
- Vanderbilt University Medical Center, Vanderbilt Clinical and Translational Research Center (VTRACC), Nashville, TN, USA
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Matthew Nayor
- Cardiology Division, Boston University School of Medicine, Boston, MA, USA
| | - Jared P Reis
- Epidemiology Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Norrina B Allen
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Katie Meyer
- Nutrition Department, UNC Chapel Hill, Chapel Hill, NC, USA
| | - Joanne Cole
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Paolo Piaggi
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Ramachandran S Vasan
- Sections of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, and Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Clary B Clish
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Venkatesh L Murthy
- Department of Medicine and Radiology, University of Michigan, 1338 Cardiovascular Center, Ann Arbor, MI 48109-5873, USA
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Glenn AJ, Aune D, Freisling H, Mohammadifard N, Kendall CWC, Salas-Salvadó J, Jenkins DJA, Hu FB, Sievenpiper JL. Nuts and Cardiovascular Disease Outcomes: A Review of the Evidence and Future Directions. Nutrients 2023; 15:911. [PMID: 36839269 PMCID: PMC9964942 DOI: 10.3390/nu15040911] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 02/15/2023] Open
Abstract
Nuts are nutrient-rich foods that contain many bioactive compounds that are beneficial for cardiovascular health. Higher consumption of nuts has been associated with a reduced risk of several cardiovascular diseases (CVD) in prospective cohort studies, including a 19% and 25% lower risk of CVD incidence and mortality, respectively, and a 24% and 27% lower risk of coronary heart disease incidence and mortality, respectively. An 18% lower risk of stroke mortality, a 15% lower risk of atrial fibrillation, and a 19% lower risk of total mortality have also been observed. The role of nuts in stroke incidence, stroke subtypes, peripheral arterial disease and heart failure has been less consistent. This narrative review summarizes recommendations for nuts by clinical practice guidelines and governmental organizations, epidemiological evidence for nuts and CVD outcomes, nut-containing dietary patterns, potential mechanisms of nuts and CVD risk reduction, and future research directions, such as the use of biomarkers to help better assess nut intake. Although there are still some uncertainties around nuts and CVD prevention which require further research, as summarized in this review, there is a substantial amount of evidence that supports that consuming nuts will have a positive impact on primary and secondary prevention of CVD.
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Affiliation(s)
- Andrea J. Glenn
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
| | - Dagfinn Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2AZ, UK
- Department of Nutrition, Oslo New University College, 0372 Oslo, Norway
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, 0586 Oslo, Norway
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), 69366 Lyon, France
| | - Noushin Mohammadifard
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Cyril W. C. Kendall
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
| | - Jordi Salas-Salvadó
- Department of Biochemistry & Biotechnology, School of Medicine, Institut d’Investigacions Sanitàries Pere i Virgili, Rovira i Virgili University, 43204 Reus, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - David J. A. Jenkins
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1T8, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - John L. Sievenpiper
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1T8, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, St. Michael’s Hospital, Toronto, ON M5C 2T2, Canada
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
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Mi MY, Gajjar P, Walker ME, Miller P, Xanthakis V, Murthy VL, Larson MG, Vasan RS, Shah RV, Lewis GD, Nayor M. Association of Healthy Dietary Patterns and Cardiorespiratory Fitness in the Community. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.09.23285714. [PMID: 36798343 PMCID: PMC9934801 DOI: 10.1101/2023.02.09.23285714] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Aims To evaluate the associations of dietary indices and quantitative CRF measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology. Methods Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO 2 ) and completed semi-quantitative FFQs. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. Results In 2380 FHS participants (54±9 years, 54% female, BMI 28±5 kg/m 2 ), 1-SD higher AHEI and MDS were associated with 5.1% (1.2 ml/kg/min, p<0.0001) and 4.4% (1.0 ml/kg/min, p<0.0001) greater peak VO 2 in linear models adjusted for age, sex, total energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N=1154), 24 metabolites were concordantly associated with both dietary indices and peak VO 2 in multivariable-adjusted linear models (FDR<5%). These metabolites included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, which were higher with lower CRF and poorer dietary quality and are known markers of insulin resistance and cardiovascular risk. Conversely, C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens were associated with higher CRF and favorable dietary quality and may link to lower cardiometabolic risk. Conclusion Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favorable effects on health.
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Yuan Y, Zhu Y, Li Y, Li X, Jiao R, Bai W. Cholesterol-Lowering Activity of Vitisin A Is Mediated by Inhibiting Cholesterol Biosynthesis and Enhancing LDL Uptake in HepG2 Cells. Int J Mol Sci 2023; 24:ijms24043301. [PMID: 36834719 PMCID: PMC9961218 DOI: 10.3390/ijms24043301] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 01/01/2023] [Accepted: 01/18/2023] [Indexed: 02/10/2023] Open
Abstract
Pyranoanthocyanins have been reported to possess better chemical stability and bioactivities than monomeric anthocyanins in some aspects. The hypocholesterolemic activity of pyranoanthocyanins is unclear. In view of this, this study was conducted to compare the cholesterol-lowering activities of Vitisin A with the anthocyanin counterpart Cyanidin-3-O-glucoside(C3G) in HepG2 cells and to investigate the interaction of Vitisin A with the expression of genes and proteins associated with cholesterol metabolism. HepG2 cells were incubated with 40 μM cholesterol and 4 μM 25-hydroxycholeterol with various concentrations of Vitisin A or C3G for 24 h. It was found that Vitisin A decreased the cholesterol levels at the concentrations of 100 μM and 200 μM with a dose-response relationship, while C3G exhibited no significant effect on cellular cholesterol. Furthermore, Vitisin A could down-regulate 3-hydroxy-3-methyl-glutaryl coenzyme A reductase (HMGCR) to inhibit cholesterol biosynthesis through a sterol regulatory element-binding protein 2 (SREBP2)-dependent mechanism, and up-regulate low-density lipoprotein receptor (LDLR) and blunt the secretion of proprotein convertase subtilisin/kexin type 9 (PCSK9) protein to promote intracellular LDL uptake without LDLR degradation. In conclusion, Vitisin A demonstrated hypocholesterolemic activity, by inhibiting cholesterol biosynthesis and enhancing LDL uptake in HepG2 cells.
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Yang M, Zhu C, Du L, Huang J, Lu J, Yang J, Tong Y, Zhu M, Song C, Shen C, Dai J, Lu X, Xu Z, Li N, Ma H, Hu Z, Gu D, Jin G, Hang D, Shen H. A Metabolomic Signature of Obesity and Risk of Colorectal Cancer: Two Nested Case-Control Studies. Metabolites 2023; 13:metabo13020234. [PMID: 36837854 PMCID: PMC9965372 DOI: 10.3390/metabo13020234] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 02/08/2023] Open
Abstract
Obesity is a leading contributor to colorectal cancer (CRC) risk, but the metabolic mechanisms linking obesity to CRC are not fully understood. We leveraged untargeted metabolomics data from two 1:1 matched, nested case-control studies for CRC, including 223 pairs from the US Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and 190 pairs from a prospective Chinese cohort. We explored serum metabolites related to body mass index (BMI), constructed a metabolomic signature of obesity, and examined the association between the signature and CRC risk. In total, 72 of 278 named metabolites were correlated with BMI after multiple testing corrections (p FDR < 0.05). The metabolomic signature was calculated by including 39 metabolites that were independently associated with BMI. There was a linear positive association between the signature and CRC risk in both cohorts (p for linear < 0.05). Per 1-SD increment of the signature was associated with 38% (95% CI: 9-75%) and 28% (95% CI: 2-62%) higher risks of CRC in the US and Chinese cohorts, respectively. In conclusion, we identified a metabolomic signature for obesity and demonstrated the association between the signature and CRC risk. The findings offer new insights into the underlying mechanisms of CRC, which is critical for improved CRC prevention.
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Affiliation(s)
- Mingjia Yang
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Chen Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China
| | - Lingbin Du
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China
| | - Jianv Huang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Jiayi Lu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Jing Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Ye Tong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
| | - Ci Song
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
| | - Chong Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Zekuan Xu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
| | - Dongfeng Gu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Guangfu Jin
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- Correspondence: (G.J.); (D.H.)
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- Correspondence: (G.J.); (D.H.)
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China
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Lu Q, Chen J, Li R, Wang Y, Tu Z, Geng T, Liu L, Pan A, Liu G. Healthy lifestyle, plasma metabolites, and risk of cardiovascular disease among individuals with diabetes. Atherosclerosis 2023; 367:48-55. [PMID: 36642660 DOI: 10.1016/j.atherosclerosis.2022.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND AIMS Lifestyle management is a fundamental aspect of diabetes care to prevent cardiovascular disease (CVD); however, the underlying metabolic mechanism is not well established. We aimed to identify metabolites associated with different lifestyle factors, and estimate their mediating roles between lifestyle and CVD risk among people with diabetes. METHODS Lifestyle and metabolomic data were available for 5072 participants with diabetes who were free of CVD at baseline in the UK Biobank. The healthy level of 5 lifestyle factors was defined as non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet. A total of 44 biomarkers across 7 metabolic pathways including lipoprotein particles, fatty acids, amino acids, fluid balance, inflammation, ketone bodies, and glycolysis were quantified by nuclear magnetic resonance (NMR) spectroscopy. RESULTS All 44 assayed metabolites were significantly associated with at least one lifestyle factor. Approximately half of metabolites, which were mostly lipoprotein particles and fatty acids, showed a mediating effect between at least one lifestyle factor and CVD risk. NMR metabolites jointly mediated 43.4%, 30.0%, 16.8%, 43.4%, and 65.5% of the association of non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet with lower CVD risk, respectively. In general, though metabolites that significantly associated with lifestyle were mostly different across the 5 lifestyle factors, the pattern of association was consistent between fatty acids and all 5 lifestyle factors. Further, fatty acids showed significant mediating effects in the association between all 5 lifestyle factors and CVD risk with mediation proportion ranging from 12.2% to 26.8%. CONCLUSIONS There were large-scale differences in circulating NMR metabolites between individuals with diabetes who adhered to a healthy lifestyle and those did not. Differences in metabolites, especial fatty acids, could partially explain the association between adherence to multiple healthy lifestyle and lower CVD risk among people with diabetes.
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Affiliation(s)
- Qi Lu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety (Huazhong University of Science and Technology), Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junxiang Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Li
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety (Huazhong University of Science and Technology), Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhouzheng Tu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tingting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liegang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety (Huazhong University of Science and Technology), Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety (Huazhong University of Science and Technology), Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Mohammadi-Shemirani P, Sood T, Paré G. From 'Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators. Curr Atheroscler Rep 2023; 25:55-65. [PMID: 36595202 PMCID: PMC9807989 DOI: 10.1007/s11883-022-01078-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE OF REVIEW 'Omics studies provide a comprehensive characterisation of a biological entity, such as the genome, epigenome, transcriptome, proteome, metabolome, or microbiome. This review covers the unique properties of these types of 'omics and their roles as causal mediators in cardiovascular disease. Moreover, applications and challenges of integrating multiple types of 'omics data to increase predictive power, improve causal inference, and elucidate biological mechanisms are discussed. RECENT FINDINGS Multi-omics approaches are growing in adoption as they provide orthogonal evidence and overcome the limitations of individual types of 'omics data. Studies with multiple types of 'omics data have improved the diagnosis and prediction of disease states and afforded a deeper understanding of underlying pathophysiological mechanisms, beyond any single type of 'omics data. For instance, disease-associated loci in the genome can be supplemented with other 'omics to prioritise causal genes and understand the function of non-coding variants. Alternatively, techniques, such as Mendelian randomisation, can leverage genetics to provide evidence supporting a causal role for disease-associated molecules, and elucidate their role in disease pathogenesis. As technologies improve, costs for 'omics studies will continue to fall and datasets will become increasingly accessible to researchers. The intrinsically unbiased nature of 'omics data is well-suited to exploratory analyses that discover causal mediators of disease, and multi-omics is an emerging discipline that leverages the strengths of each type of 'omics data to provide insights greater than the sum of its parts.
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Affiliation(s)
- Pedrum Mohammadi-Shemirani
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, ON Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, ON Canada
| | - Tushar Sood
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, ON Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, ON Canada
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON Canada
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Mediterranean diet related metabolite profiles and cognitive performance. Clin Nutr 2023; 42:173-181. [PMID: 36599272 DOI: 10.1016/j.clnu.2022.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND & AIMS Evidence suggests that adherence to the Mediterranean diet (MedDiet) affects human metabolism and may contribute to better cognitive performance. However, the underlying mechanisms are not clear. OBJECTIVE We generated a metabolite profile for adherence to MedDiet and evaluated its cross-sectional association with aspects of cognitive performance. METHODS A total of 1250 healthy Greek middle-aged adults from the Epirus Health Study cohort were included in the analysis. Adherence to the MedDiet was assessed using the 14-point Mediterranean Diet Adherence Screener (MEDAS); cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. A targeted metabolite profiling (n = 250 metabolites) approach was applied, using a high-throughput nuclear magnetic resonance platform. We used elastic net regularized regressions, with a 10-fold cross-validation procedure, to identify a metabolite profile for MEDAS. We evaluated the associations of the identified metabolite profile and MEDAS with cognitive tests, using multivariable linear regression models. RESULTS We identified a metabolite profile composed of 42 metabolites, mainly lipoprotein subclasses and fatty acids, significantly correlated with MedDiet adherence (Pearson r = 0.35, P-value = 5.5 × 10-37). After adjusting for known risk factors and accounting for multiple testing, the metabolite profile and MEDAS were not associated with the cognitive tests. CONCLUSIONS A plasma metabolite profile related to better adherence to the MedDiet was not associated with the tested aspects of cognitive performance, in a middle-aged Mediterranean population.
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A Causal and Inverse Relationship between Plant-Based Diet Intake and in a Two-Sample Mendelian Randomization Study. Foods 2023; 12:foods12030545. [PMID: 36766075 PMCID: PMC9914273 DOI: 10.3390/foods12030545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 01/20/2023] [Accepted: 01/21/2023] [Indexed: 01/28/2023] Open
Abstract
A plant-based diet (PBD) has been reported to be linked to metabolic syndrome (MetS) risk in observational studies, but not in causal association studies. We aimed to examine the hypothesis that high PBD exhibited a causal and inverse association with MetS and its components using two-sample Mendelian randomization (MR). PBD was clustered according to food intake, which was assessed by semi-quantitative food frequency questionnaires using a principal component analysis. The instrumental variables were generated using the genome-wide association study (GWAS) of a High-PBD group (≥67th percentiles) after adjusting for the covariates related to MetS, with a significance level of p < 5 × 10-5 and linkage disequilibrium (r2 < 0.001), in a city hospital-based cohort (n = 58,701). The causal association of the PBD intake with MetS risk was examined with a two-sample MR approach in the rural plus Ansan/Ansung cohorts (n = 13,598). The High-PBD group showed higher energy, fat, protein, cholesterol, fiber, sodium, calcium, vitamin C and D, and flavonoid intake than the Low-PBD group. The High-PBD group showed a lower risk of MetS, waist circumference, hyperglycemia, hypo-HDL-cholesterolemia, and hypertriglyceridemia using an inverse-variance weighted method (p < 0.05). Low-PBD intake significantly elevated only waist circumference in weighted-median analysis (p < 0.05). No heterogeneity, horizontal pleiotropy, or single genetic variant influenced the causal relationship. In conclusion, low PBD appeared to be causally positively related to MetS risk and its components, but not hypertension. Therefore, Korean-style PBD may be beneficial for decreasing MetS risk in Asian adults.
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Multi-omics analysis of the effects of dietary changes and probiotics on diet-induced obesity. Curr Res Food Sci 2023; 6:100435. [PMID: 36691590 PMCID: PMC9860293 DOI: 10.1016/j.crfs.2023.100435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/01/2023] [Accepted: 01/05/2023] [Indexed: 01/07/2023] Open
Abstract
The consumption of a healthy diet is critical for maintaining and promoting human health. In the context of the rapid transformation from a high-fat diet (HFD) to a Mediterranean diet (MD) leading to major systemic changes, we explored the necessity of a transitional standard diet (TSD) between these two varied diets and the adjuvant effect of probiotics. HFD-fed mice were used for studying the changes and benefits of a dietary intervention and probiotic treatment. By measuring multiple systemic alterations such as weight (group B vs. group E, P < 0.05), liver function (AST, group C vs. group E, P < 0.001), and histopathology, we found that an MD, TSD and Bifidobacterium longum all contribute to alleviating lipid deposition and liver injury. The downregulation of IL-17 (group B vs. group E, P < 0.01) and MIP-1α (group B vs. group E, P < 0.001) also demonstrated the anti-inflammatory effects of the TSD. Moreover, we performed multi-omics analysis combined with the 16S sequencing, transcriptome and metabolome results and found that the TSD increased the abundance of the Lactobacillus genus (group C vs. group E, P < 0.01) and effectively lowered lipid accumulation and systemic inflammation. Furthermore, B. longum played an important role in the synergistic effect. The results showed that a TSD might be useful for HFD-induced obesity before drastic dietary changes, and probiotics were also beneficial.
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Mattei J, Díaz-Alvarez CB, Alfonso C, O’Neill HJ, Ríos-Bedoya CF, Malik VS, Godoy-Vitorino F, Cheng C, Spiegelman D, Willett WC, Hu FB, Rodríguez-Orengo JF. Design and Implementation of a Culturally-Tailored Randomized Pilot Trial: Puerto Rican Optimized Mediterranean-Like Diet. Curr Dev Nutr 2023; 7:100022. [PMID: 37181130 PMCID: PMC10100940 DOI: 10.1016/j.cdnut.2022.100022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 11/23/2022] [Accepted: 12/05/2022] [Indexed: 12/25/2022] Open
Abstract
Background Adhering to a Mediterranean Diet (MedDiet) is associated with a healthier cardiometabolic profile. However, there are limited studies on the MedDiet benefits for non-Mediterranean racial/ethnic minorities, for whom this diet may be unfamiliar and inaccessible and who have a high risk of chronic diseases. Objectives To describe the study design of a pilot trial testing the efficacy of a MedDiet-like tailored to adults in Puerto Rico (PR). Methods The Puerto Rican Optimized Mediterranean-like Diet (PROMED) was a single-site 4-mo parallel two-arm randomized pilot trial among a projected 50 free-living adults (25-65 y) living in PR with at least two cardiometabolic risk factors (clinicaltrials.gov registration #NCT03975556). The intervention group received 1 individual nutritional counseling session on a portion-control culturally-tailored MedDiet. Daily text messages reinforced the counseling content for 2 mo, and we supplied legumes and vegetable oils. Participants in the control group received cooking utensils and one standard portion-control nutritional counseling session that was reinforced with daily texts for 2 mo. Text messages for each group were repeated for two more months. Outcome measures were assessed at baseline, 2 and 4 m. The primary outcome was a composite cardiometabolic improvement score; secondary outcomes included individual cardiometabolic factors; dietary intake, behaviors, and satisfaction; psychosocial factors; and the gut microbiome. Results PROMED was designed to be culturally appropriate, acceptable, accessible, and feasible for adults in PR. Strengths of the study include applying deep-structure cultural components, easing structural barriers, and representing a real-life setting. Limitations include difficulty with blinding and with monitoring adherence, and reduced timing and sample size. The COVID-19 pandemic influenced implementation, warranting replication. Conclusions If PROMED is proven efficacious in improving cardiometabolic health and diet quality, the findings would strengthen the evidence on the healthfulness of a culturally-appropriate MedDiet and support its wider implementation in clinical and population-wide disease-prevention programs.
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Affiliation(s)
- Josiemer Mattei
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- FDI Clinical Research, San Juan, PR, USA
| | | | - Charmaine Alfonso
- College of Nutritionists and Dietitians of Puerto Rico, San Juan, PR, USA
- School of Health Sciences, Ana G. Méndez University, Gurabo Campus, Gurabo, PR, USA
| | - H June O’Neill
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Carlos F. Ríos-Bedoya
- FDI Clinical Research, San Juan, PR, USA
- McLaren Health Care, Graduate Medical Education, Grand Blanc, MI, USA
| | - Vasanti S. Malik
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Nutritional Sciences, University of Toronto, Ontario, Canada
| | - Filipa Godoy-Vitorino
- Department of Microbiology, School of Medicine, University of Puerto Rico Medical Sciences Campus, San Juan, PR, USA
| | - Chao Cheng
- Department of Biostatistics and Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, USA
| | - Donna Spiegelman
- Department of Biostatistics and Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, USA
| | - Walter C. Willett
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Frank B. Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - José F. Rodríguez-Orengo
- FDI Clinical Research, San Juan, PR, USA
- Department of Biochemistry, School of Medicine, University of Puerto Rico Medical Sciences Campus, San Juan, PR, USA
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Barbe V, de Toro-Martín J, San-Cristobal R, Garneau V, Pilon G, Couture P, Roy D, Couillard C, Marette A, Vohl MC. A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption. Front Nutr 2023; 10:1104685. [PMID: 37125033 PMCID: PMC10130762 DOI: 10.3389/fnut.2023.1104685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/06/2023] [Indexed: 05/02/2023] Open
Abstract
Background Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood. Methods In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the intervention was first evaluated. A second PLS-DA followed by hierarchical clustering was used to classify individuals into response subgroups. Clinical immune and metabolic outcomes, including insulin resistance (HOMA-IR) and sensitivity (Matsuda, QUICKI) indices, during the intervention were assessed and compared between response subgroups. Results Two subgroups of participants, type 1 responders (n = 17) and type 2 responders (n = 5), were identified based on plasma metabolite levels measured during the intervention. Type 1 responders showed neutral to negative effects on immune-metabolic clinical parameters after raspberry consumption, and type 2 responders showed positive effects on the same parameters. Changes in waist circumference, waist-to-hip ratio, fasting plasma apolipoprotein B, C-reactive protein and insulin levels as well as Matsuda, HOMA-IR and QUICKI were significantly different between the two response subgroups. A deleterious effect of two carotenoid metabolites was also observed in type 1 responders but these variables were significantly associated with beneficial changes in the QUICKI index and in fasting insulin levels in type 2 responders. Increased 3-ureidopropionate levels were associated with a decrease in the Matsuda index in type 2 responders, suggesting that this metabolite is associated with a decrease in insulin sensitivity for those subjects, whereas the opposite was observed for type 1 responders. Conclusion The beneficial effects associated with red raspberry consumption are subject to inter-individual variability. Metabolomics-based clustering appears to be an effective way to assess adherence to a nutritional intervention and to classify individuals according to their immune-metabolic responsiveness to the intervention. This approach may be replicated in future studies to provide a better understanding of how interindividual variability impacts the effects of nutritional interventions on immune-metabolic health.
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Affiliation(s)
- Valentin Barbe
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
| | - Juan de Toro-Martín
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
| | - Rodrigo San-Cristobal
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
| | - Véronique Garneau
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
| | - Geneviève Pilon
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- Québec Heart and Lung Institute (IUCPQ) Research Center, Québec City, QC, Canada
| | - Patrick Couture
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- Endocrinology and Nephrology Unit, CHU de Quebec Research Center, Québec City, QC, Canada
| | - Denis Roy
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
| | - Charles Couillard
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
| | - André Marette
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- Québec Heart and Lung Institute (IUCPQ) Research Center, Québec City, QC, Canada
| | - Marie-Claude Vohl
- Centre Nutrition, santé et société (NUTRISS), Université Laval, Québec City, QC, Canada
- Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
- School of Nutrition, Université Laval, Québec City, QC, Canada
- *Correspondence: Marie-Claude Vohl,
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Extensive Summary of the Important Roles of Indole Propionic Acid, a Gut Microbial Metabolite in Host Health and Disease. Nutrients 2022; 15:nu15010151. [PMID: 36615808 PMCID: PMC9824871 DOI: 10.3390/nu15010151] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 12/22/2022] [Accepted: 12/26/2022] [Indexed: 12/30/2022] Open
Abstract
Increasing evidence suggests that metabolites produced by the gut microbiota play a crucial role in host-microbe interactions. Dietary tryptophan ingested by the host enters the gut, where indole-like metabolites such as indole propionic acid (IPA) are produced under deamination by commensal bacteria. Here, we summarize the IPA-producing bacteria, dietary patterns on IPA content, and functional roles of IPA in various diseases. IPA can not only stimulate the expression of tight junction (TJ) proteins to enhance gut barrier function and inhibit the penetration of toxic factors, but also modulate the immune system to exert anti-inflammatory and antioxidant effects to synergistically regulate body physiology. Moreover, IPA can act on target organs through blood circulation to form the gut-organ axis, which helps maintain systemic homeostasis. IPA shows great potential for the diagnosis and treatment of various clinical diseases, such as NAFLD, Alzheimer's disease, and breast cancer. However, the therapeutic effect of IPA depends on dose, target organ, or time. In future studies, further work should be performed to explore the effects and mechanisms of IPA on host health and disease to further improve the existing treatment program.
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Soldevila-Domenech N, Pastor A, Sala-Vila A, Lázaro I, Boronat A, Muñoz D, Castañer O, Fagundo B, Corella D, Fernández-Aranda F, Martínez-González MÁ, Salas-Salvadó J, Fitó M, de la Torre R. Sex differences in endocannabinoids during 3 years of Mediterranean diet intervention: Association with insulin resistance and weight loss in a population with metabolic syndrome. Front Nutr 2022; 9:1076677. [PMID: 36532543 DOI: 10.3389/fnut.2022.1076677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022] Open
Abstract
BackgroundExcess circulating endocannabinoids (eCBs) and imbalanced N-acylethanolamines (NAEs) related eCBs abundance could influence dietary weight loss success. We aimed to examine sex differences in the impact of a 3-years Mediterranean diet (MedDiet) intervention on circulating eCBs, NAEs and their precursor fatty acids, and to analyze the interplay between changes in eCBs or NAEs ratios, insulin resistance and the achievement of clinically meaningful weight reductions.MethodsProspective cohort study in a subsample of N = 105 participants (54.3% women; 65.6 ± 4.6 years) with overweight or obesity and metabolic syndrome that underwent a 3-years MedDiet intervention (PREDIMED-Plus study). Plasma eCBs and NAEs, including 2-arachidonoylglycerol (2-AG), anandamide (AEA), oleoylethanolamide (OEA) and palmitoylethanolamide (PEA), fatty acids, diet, glycemic homeostasis (including the assessment of insulin resistance-HOMA-IR), and cardiovascular risk markers were monitored (at 0-6-12-36 months).ResultsMediterranean diet adherence increased in both sexes and remained high during the 3 years of follow-up. Reductions in body weight, glycemic and cardiovascular parameters were larger in men than in women. Women presented higher concentrations of NAEs than men throughout the study. In both sexes, AEA and other NAEs (including OEA, and PEA) decreased after 6 months (for AEA: −4.9%), whereas the ratio OEA/AEA increased after 1 year (+5.8%). Changes in 2-AG (−3.9%) and the ratio OEA/PEA (+8.2%) persisted over the 3 years of follow-up. In women, 6-months changes in AEA (OR = 0.65) and the ratio OEA/AEA (OR = 3.28) were associated with the achievement of 8% weight reductions and correlated with HOMA-IR changes (r = 0.29 and r = −0.34). In men, OEA/PEA changes were associated with 8% weight reductions (OR = 2.62) and correlated with HOMA-IR changes (r = −0.32).ConclusionA 3-years MedDiet intervention modulated plasma concentrations of eCBs and NAEs. Changes in AEA and in the relative abundance of NAEs were associated with clinically meaningful weight reductions. However, marked sex differences were identified in eCBs and NAEs, as well as in the efficacy of the intervention in terms of glycemic and cardiovascular parameters, which could be related to post-menopause alterations in glucose metabolism. These findings support a sex-balanced research strategy for a better understanding of the mechanisms underlying the regulation of body weight loss.
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Affiliation(s)
- Natalia Soldevila-Domenech
- Integrative Pharmacology and Systems Neurosciences Research Group, Neuroscience Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Antoni Pastor
- Integrative Pharmacology and Systems Neurosciences Research Group, Neuroscience Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Aleix Sala-Vila
- Cardiovascular Risk and Nutrition Research Group, Epidemiology and Public Health Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Fatty Acid Research Institute, Sioux Falls, SD, United States
| | - Iolanda Lázaro
- Cardiovascular Risk and Nutrition Research Group, Epidemiology and Public Health Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Anna Boronat
- Integrative Pharmacology and Systems Neurosciences Research Group, Neuroscience Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Daniel Muñoz
- Cardiovascular Risk and Nutrition Research Group, Epidemiology and Public Health Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Olga Castañer
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group, Epidemiology and Public Health Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Endocrinology Service, Hospital del Mar, Barcelona, Spain
| | - Beatriz Fagundo
- Integrative Pharmacology and Systems Neurosciences Research Group, Neuroscience Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Physiotherapy, Fundació Universitària del Bages, Manresa, Spain
| | - Dolores Corella
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, Valencia, Spain
| | - Fernando Fernández-Aranda
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, University Hospital of Bellvitge-IDIBELL, Barcelona, Spain
- Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
- Psychoneurobiology of Eating and Addictive Behaviours Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Miguel Ángel Martínez-González
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra's Health Research Institute (IdiSNA), Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Jordi Salas-Salvadó
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain
| | - Montserrat Fitó
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group, Epidemiology and Public Health Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Rafael de la Torre
- Integrative Pharmacology and Systems Neurosciences Research Group, Neuroscience Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Fisiopatología Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
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84
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Arsenault BJ. From the garden to the clinic: how Mendelian randomization is shaping up atherosclerotic cardiovascular disease prevention strategies. Eur Heart J 2022; 43:4447-4449. [PMID: 35869924 DOI: 10.1093/eurheartj/ehac394] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Benoit J Arsenault
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval Y-3106, Pavillon Marguerite D'Youville, 2725 chemin Ste-Foy, Québec, QC G1V 4G5, Canada.,Department of Medicine, Faculty of Medicine, Université Laval, 2325 rue de l'Université, Québec, QC G1V 0A6, Canada
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85
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Handakas E, Chang K, Khandpur N, Vamos EP, Millett C, Sassi F, Vineis P, Robinson O. Metabolic profiles of ultra-processed food consumption and their role in obesity risk in British children. Clin Nutr 2022; 41:2537-2548. [PMID: 36223715 DOI: 10.1016/j.clnu.2022.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/11/2022] [Accepted: 09/05/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND & AIMS Higher consumption of ultra-processed foods (UPF) has been associated with childhood obesity, but underlying mechanisms remain unclear. We investigated plasma nuclear magnetic resonance metabolic profiles of higher UPF consumption and their role in obesity risk in the British ALSPAC cohort. METHODS We performed cross-sectional and prospective metabolome wide association analyses of UPF, calculated from food diaries using the NOVA classification. In cross-sectional analysis, we tested the association between UPF consumption and metabolic profile at 7 years (N = 4528), and in the prospective analysis we tested the association between UPF consumption at 13 years and metabolic profile at 17 years (N = 3086). Effects of UPF-associated metabolites at 7 years on subsequent fat mass accumulation were assessed using growth curve models. RESULTS At 7 years, UPF was associated with 115 metabolic traits including lower levels of branched-chain and aromatic amino acids and higher levels of citrate, glutamine, and monounsaturated fatty acids, which were also associated with greater fat mass accumulation. Reported intake of nutrients mediated associations with most metabolites, except for citrate. CONCLUSIONS UPF consumption among British children is associated with perturbation of multiple metabolic traits, many of which contribute to child obesity risk.
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Affiliation(s)
- Evangelos Handakas
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Kiara Chang
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom
| | - Neha Khandpur
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, U. S. A
| | - Eszter P Vamos
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom
| | - Christopher Millett
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom; Comprehensive Health Research Center and Public Health Research Centre, National School of Public Health, NOVA University Lisbon, Portugal
| | - Franco Sassi
- Centre for Health Economics & Policy Innovation, Department of Economics & Public Policy, Imperial College Business School, South Kensington Campus, London, United Kingdom
| | - Paolo Vineis
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Oliver Robinson
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom; Mohn Centre for Children's Health and Well-being, School of Public Health, Imperial College London, United Kingdom.
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86
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Martínez-González MÁ, Martín-Calvo N, Bretos-Azcona T, Carlos S, Delgado-Rodríguez M. Mediterranean Diet and Cardiovascular Prevention: Why Analytical Observational Designs Do Support Causality and Not Only Associations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13653. [PMID: 36294233 PMCID: PMC9603524 DOI: 10.3390/ijerph192013653] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/15/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
Causal reductions in cardiovascular disease (CVD) with the Mediterranean diet (MedDiet) are supported by randomized trials, but the ability of nonrandomized studies to provide causal inferences in nutritional epidemiology is questioned. The "Seguimiento Universidad de Navarra" (SUN) project, conducted during 1999-2019 with 18,419 participants, was used to try to refute non-causal explanations for the inverse association found between adherence to the MedDiet and reduced CVD risk. A framework of different analytical strategies is proposed: alternative definitions of the exposure, exploration of residual confounding, resampling methods, depiction of absolute risks across the follow-up period, trial emulation, and negative controls. Additionally, we calculated the rate advancement period (RAP). We found that one standard deviation increase in the most frequently used MedDiet score was associated with a 29% relative reduction in CVD risk (95% Confidence Interval [CI] 14-41%), which is almost identical to that found in 2 randomized trials. The RAP of CVD would be postponed by an average of 7.9 years (95% CI: 1.6 to 14.2 years) by switching from low (MDS = 0 to2) to high (MDS = 7 to 9) adherence to the MedDiet in the fully adjusted model. Sensitivity analyses, graphical representations of absolute risks, trial emulation, and negative controls also supported causality. In conclusion, a framework of analytical approaches supported the causal effect of the MedDiet on CVD prevention using observational data. Similar methodology could be applied for causal inferences regarding other hypotheses.
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Affiliation(s)
- Miguel Ángel Martínez-González
- Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, 31008 Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, 28029 Madrid, Spain
| | - Nerea Martín-Calvo
- Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, 31008 Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, 28029 Madrid, Spain
| | - Telmo Bretos-Azcona
- Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, 31008 Pamplona, Spain
| | - Silvia Carlos
- Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, 31008 Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
| | - Miguel Delgado-Rodríguez
- Department of Health Sciences, University of Jaén, Área de Medicina Preventiva y Ciencias de la Salud, 23071 Jaén, Spain
- CIBER Epidemiología y Salud Pública, 28029 Madrid, Spain
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Yang Q, Gao S, Lin J, Lyu K, Wu Z, Chen Y, Qiu Y, Zhao Y, Wang W, Lin T, Pan H, Chen M. A machine learning-based data mining in medical examination data: a biological features-based biological age prediction model. BMC Bioinformatics 2022; 23:411. [PMID: 36192681 PMCID: PMC9528174 DOI: 10.1186/s12859-022-04966-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022] Open
Abstract
Background Biological age (BA) has been recognized as a more accurate indicator of aging than chronological age (CA). However, the current limitations include: insufficient attention to the incompleteness of medical data for constructing BA; Lack of machine learning-based BA (ML-BA) on the Chinese population; Neglect of the influence of model overfitting degree on the stability of the association results. Methods and results Based on the medical examination data of the Chinese population (45–90 years), we first evaluated the most suitable missing interpolation method, then constructed 14 ML-BAs based on biomarkers, and finally explored the associations between ML-BAs and health statuses (healthy risk indicators and disease). We found that round-robin linear regression interpolation performed best, while AutoEncoder showed the highest interpolation stability. We further illustrated the potential overfitting problem in ML-BAs, which affected the stability of ML-Bas’ associations with health statuses. We then proposed a composite ML-BA based on the Stacking method with a simple meta-model (STK-BA), which overcame the overfitting problem, and associated more strongly with CA (r = 0.66, P < 0.001), healthy risk indicators, disease counts, and six types of disease. Conclusion We provided an improved aging measurement method for middle-aged and elderly groups in China, which can more stably capture aging characteristics other than CA, supporting the emerging application potential of machine learning in aging research. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04966-7.
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Affiliation(s)
- Qing Yang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Sunan Gao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, China
| | - Junfen Lin
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Ke Lyu
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zexu Wu
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yuhao Chen
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yinwei Qiu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Yanrong Zhao
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Wei Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Tianxiang Lin
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Huiyun Pan
- The First Affiliated Hospital of School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Ming Chen
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China. .,The First Affiliated Hospital of School of Medicine, Zhejiang University, Hangzhou, 310058, China.
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Hu J, Yao J, Deng S, Balasubramanian R, Jiménez MC, Li J, Guo X, Cruz DE, Gao Y, Huang T, Zeleznik OA, Ngo D, Liu S, Rosal MC, Nassir R, Paynter NP, Albert CM, Tracy RP, Durda P, Liu Y, Taylor KD, Johnson WC, Sun Q, Rimm EB, Eliassen AH, Rich SS, Rotter JI, Gerszten RE, Clish CB, Rexrode KM. Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts. Circ Res 2022; 131:601-615. [PMID: 36052690 PMCID: PMC9473718 DOI: 10.1161/circresaha.121.320134] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 08/13/2022] [Accepted: 08/21/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.
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Affiliation(s)
- Jie Hu
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jie Yao
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, University of Massachusetts – Amherst (R.B.)
| | - Monik C. Jiménez
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jun Li
- Division of Preventive Medicine (J.L., N.P.P.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Daniel E. Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
| | - Yan Gao
- Department of Medicine, University of Mississippi Medical Center, Jackson (Y.G.)
| | - Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
| | - Oana A. Zeleznik
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
| | - Debby Ngo
- Brigham and Women’s Hospital and Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (D.N.), Harvard Medical School, Boston, MA
| | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI (S.L.)
- Division of Endocrinology, Department of Medicine, Warren Alpert Medical School of Brown University, Providence, RI (S.L.)
| | - Milagros C. Rosal
- Division of Preventive and Behavioral Medicine, Department of Population and Quantitative Sciences, University of Massachusetts Medical School, Worcester (M.C.R.)
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura University, Saudi Arabia (R.N.)
| | - Nina P. Paynter
- Division of Preventive Medicine (J.L., N.P.P.), Harvard Medical School, Boston, MA
| | - Christine M. Albert
- Department of Cardiology, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA (C.M.A.)
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine (R.P.T., P.D.), Larner College of Medicine, University of Vermont, Burlington
- Department of Biochemistry (R.P.T.), Larner College of Medicine, University of Vermont, Burlington
| | - Peter Durda
- Department of Pathology and Laboratory Medicine (R.P.T., P.D.), Larner College of Medicine, University of Vermont, Burlington
| | - Yongmei Liu
- Divisions of Cardiology and Neurology, Department of Medicine, Duke University Medical Center, Durham, NC (Y.L.)
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle (W.C.J.)
| | - Qi Sun
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Eric B. Rimm
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - A. Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville (S.S.R.)
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge (R.E.G., C.B.C.)
| | - Clary B. Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge (R.E.G., C.B.C.)
| | - Kathryn M. Rexrode
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
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89
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Zhou Q, Zhang F, Kerbl-Knapp J, Korbelius M, Kuentzel KB, Vujić N, Akhmetshina A, Hörl G, Paar M, Steyrer E, Kratky D, Madl T. Phosphatidylethanolamine N-Methyltransferase Knockout Modulates Metabolic Changes in Aging Mice. Biomolecules 2022; 12:1270. [PMID: 36139111 PMCID: PMC9496051 DOI: 10.3390/biom12091270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/02/2022] [Accepted: 09/06/2022] [Indexed: 12/11/2022] Open
Abstract
Phospholipid metabolism, including phosphatidylcholine (PC) biosynthesis, is crucial for various biological functions and is associated with longevity. Phosphatidylethanolamine N-methyltransferase (PEMT) is a protein that catalyzes the biosynthesis of PC, the levels of which change in various organs such as the brain and kidneys during aging. However, the role of PEMT for systemic PC supply is not fully understood. To address how PEMT affects aging-associated energy metabolism in tissues responsible for nutrient absorption, lipid storage, and energy consumption, we employed NMR-based metabolomics to study the liver, plasma, intestine (duodenum, jejunum, and ileum), brown/white adipose tissues (BAT and WAT), and skeletal muscle of young (9-10 weeks) and old (91-132 weeks) wild-type (WT) and PEMT knockout (KO) mice. We found that the effect of PEMT-knockout was tissue-specific and age-dependent. A deficiency of PEMT affected the metabolome of all tissues examined, among which the metabolome of BAT from both young and aged KO mice was dramatically changed in comparison to the WT mice, whereas the metabolome of the jejunum was only slightly affected. As for aging, the absence of PEMT increased the divergence of the metabolome during the aging of the liver, WAT, duodenum, and ileum and decreased the impact on skeletal muscle. Overall, our results suggest that PEMT plays a previously underexplored, critical role in both aging and energy metabolism.
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Affiliation(s)
- Qishun Zhou
- Research Unit Integrative Structural Biology, Division of Molecular Biology and Biochemistry, Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8010 Graz, Austria
| | - Fangrong Zhang
- Research Unit Integrative Structural Biology, Division of Molecular Biology and Biochemistry, Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8010 Graz, Austria
- Key Laboratory of Gastrointestinal Cancer, Fujian Medical University, Ministry of Education, Fuzhou 350122, China
| | - Jakob Kerbl-Knapp
- Research Unit Integrative Structural Biology, Division of Molecular Biology and Biochemistry, Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8010 Graz, Austria
| | - Melanie Korbelius
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
| | - Katharina Barbara Kuentzel
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
| | - Nemanja Vujić
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
| | - Alena Akhmetshina
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
| | - Gerd Hörl
- Otto-Loewi Research Center, Division of Medicinal Chemistry, Medical University of Graz, 8010 Graz, Austria
| | - Margret Paar
- Otto-Loewi Research Center, Division of Medicinal Chemistry, Medical University of Graz, 8010 Graz, Austria
| | - Ernst Steyrer
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
| | - Dagmar Kratky
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
| | - Tobias Madl
- Research Unit Integrative Structural Biology, Division of Molecular Biology and Biochemistry, Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
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90
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Hou XW, Wang Y, Wu Q, Ke C, Pan CW. A review of study designs and data analyses in metabolomics studies in myopia. Anal Biochem 2022; 655:114850. [PMID: 35970413 DOI: 10.1016/j.ab.2022.114850] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 07/15/2022] [Accepted: 08/03/2022] [Indexed: 11/25/2022]
Abstract
Metabolomics analyzes the entire range of small molecule metabolites in biological systems to reveal the response signals that are transmitted from "genetics and environment", which could help us understand complex phenotypes of diseases. Metabolomics has been successfully applied to the study of eye diseases including age-related macular degeneration, glaucoma, and diabetic retinopathy. In this review, we summarize the findings of myopic metabolomics and discuss them from a design and analysis perspective. Finally, we provide new ideas for the future development of myopia metabolomics research based on the broader ocular metabolomics study.
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Affiliation(s)
- Xiao-Wen Hou
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Ying Wang
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Qian Wu
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Chaofu Ke
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Chen-Wei Pan
- School of Public Health, Medical College of Soochow University, Suzhou, China.
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91
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Li C, Imamura F, Wedekind R, Stewart ID, Pietzner M, Wheeler E, Forouhi NG, Langenberg C, Scalbert A, Wareham NJ. Development and validation of a metabolite score for red meat intake: an observational cohort study and randomized controlled dietary intervention. Am J Clin Nutr 2022; 116:511-522. [PMID: 35754192 PMCID: PMC9348983 DOI: 10.1093/ajcn/nqac094] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/04/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Self-reported meat consumption is associated with disease risk but objective assessment of different dimensions of this heterogeneous dietary exposure in observational and interventional studies remains challenging. OBJECTIVES We aimed to derive and validate scores based on plasma metabolites for types of meat consumption. For the most predictive score, we aimed to test whether the included metabolites varied with change in meat consumption, and whether the score was associated with incidence of type 2 diabetes (T2D) and other noncommunicable diseases. METHODS We derived scores based on 781 plasma metabolites for red meat, processed meat, and poultry consumption assessed with 7-d food records among 11,432 participants in the EPIC-Norfolk (European Prospective Investigation into Cancer and Nutrition-Norfolk) cohort. The scores were then tested for internal validity in an independent subset (n = 853) of the same cohort. In focused analysis on the red meat metabolite score, we examined whether the metabolites constituting the score were also associated with meat intake in a randomized crossover dietary intervention trial of meat (n = 12, Lyon, France). In the EPIC-Norfolk study, we assessed the association of the red meat metabolite score with T2D incidence (n = 1478) and other health endpoints. RESULTS The best-performing score was for red meat, comprising 139 metabolites which accounted for 17% of the explained variance of red meat consumption in the validation set. In the intervention, 11 top-ranked metabolites in the red meat metabolite score increased significantly after red meat consumption. In the EPIC-Norfolk study, the red meat metabolite score was associated with T2D incidence (adjusted HR per SD: 1.17; 95% CI: 1.10, 1.24). CONCLUSIONS The red meat metabolite score derived and validated in this study contains metabolites directly derived from meat consumption and is associated with T2D risk. These findings suggest the potential for objective assessment of dietary components and their application for understanding diet-disease associations.The trial in Lyon, France, was registered at clinicaltrials.gov as NCT03354130.
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Affiliation(s)
- Chunxiao Li
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Roland Wedekind
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Isobel D Stewart
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Maik Pietzner
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Eleanor Wheeler
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Augustin Scalbert
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
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92
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Kang JH, Zeleznik O, Frueh L, Lasky-Su J, Eliassen AH, Clish C, Rosner BA, Pasquale LR, Wiggs JL. Prediagnostic Plasma Metabolomics and the Risk of Exfoliation Glaucoma. Invest Ophthalmol Vis Sci 2022; 63:15. [PMID: 35951322 PMCID: PMC9386645 DOI: 10.1167/iovs.63.9.15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Purpose The etiology of exfoliation glaucoma (XFG) is poorly understood. We aimed to identify a prediagnostic plasma metabolomic signature associated with XFG. Methods We conducted a 1:1 matched case-control study nested within the Nurses' Health Study and Health Professionals Follow-up Study. We collected blood samples in 1989-1990 (Nurses' Health Study) and 1993-1995 (Health Professionals Follow-up Study). We identified 205 incident XFG cases through 2016 (average time to diagnosis from blood draw = 11.8 years) who self-reported glaucoma and were confirmed as XFG cases with medical records. We profiled plasma metabolites using liquid chromatography-mass spectrometry. We evaluated 379 known metabolites (transformed for normality using probit scores) using multiple conditional logistic models. Metabolite set enrichment analysis was used to identify metabolite classes associated with XFG. To adjust for multiple comparisons, we used number of effective tests (NEF) and the false discovery rate (FDR). Results Mean age of cases (n = 205) at diagnosis was 71 years; 85% were women and more than 99% were Caucasian; controls (n = 205) reported eye examinations as of the matched cases' index date. Thirty-three metabolites were nominally significantly associated with XFG (P < 0.05), and 4 metabolite classes were FDR-significantly associated. We observed positive associations for lysophosphatidylcholines (FDR = 0.02) and phosphatidylethanolamine plasmalogens (FDR = 0.004) and inverse associations for triacylglycerols (FDR < 0.0001) and steroids (FDR = 0.03). In particular, the multivariable-adjusted odds ratio with each 1 standard deviation higher plasma cortisone levels was 0.49 (95% confidence interval, 0.32-0.74; NEF = 0.05). Conclusions In plasma from a decade before diagnosis, lysophosphatidylcholines and phosphatidylethanolamine plasmalogens were positively associated and triacylglycerols and steroids (e.g., cortisone) were inversely associated with XFG risk.
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Affiliation(s)
- Jae H Kang
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Oana Zeleznik
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Lisa Frueh
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - A Heather Eliassen
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Clary Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, United States
| | - Bernard A Rosner
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Louis R Pasquale
- Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Janey L Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
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93
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Yun H, Sun L, Wu Q, Luo Y, Qi Q, Li H, Gu W, Wang J, Ning G, Zeng R, Zong G, Lin X. Lipidomic Signatures of Dairy Consumption and Associated Changes in Blood Pressure and Other Cardiovascular Risk Factors Among Chinese Adults. Hypertension 2022; 79:1617-1628. [PMID: 35469422 DOI: 10.1161/hypertensionaha.122.18981] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Omics data may provide a unique opportunity to discover dairy-related biomarkers and their linked cardiovascular health. METHODS Dairy-related lipidomic signatures were discovered in baseline data from a Chinese cohort study (n=2140) and replicated in another Chinese study (n=212). Dairy intake was estimated by a validated food-frequency questionnaire. Lipidomics was profiled by high-coverage liquid chromatography-tandem mass spectrometry. Associations of dairy-related lipids with 6-year changes in cardiovascular risk factors were examined in the discovery cohort, and their causalities were analyzed by 2-sample Mendelian randomization using available genome-wide summary data. RESULTS Of 350 lipid metabolites, 4 sphingomyelins, namely sphingomyelin (OH) C32:2, sphingomyelin C32:1, sphingomyelin (2OH) C30:2, and sphingomyelin (OH) C38:2, were identified and replicated to be positively associated with total dairy consumption (β=0.130 to 0.148; P<1.43×10-4), but not or weakly with nondairy food items. The score of 4 sphingomyelins showed inverse associations with 6-year changes in systolic (-2.68 [95% CI, -4.92 to -0.43]; P=0.019), diastolic blood pressures (-1.86 [95% CI, -3.12 to -0.61]; P=0.004), and fasting glucose (-0.25 [95% CI, -0.41 to -0.08]; P=0.003). Mendelian randomization analyses further revealed that genetically inferred sphingomyelin (OH) C32:2 was inversely associated with systolic (-0.57 [95% CI, -0.85 to -0.28]; P=9.16×10-5) and diastolic blood pressures (-0.39 [95% CI, -0.59 to -0.20]; P=7.09×10-5). CONCLUSIONS The beneficial effects of dairy products on cardiovascular health might be mediated through specific sphingomyelins among Chinese with overall low dairy consumption.
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Affiliation(s)
- Huan Yun
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Liang Sun
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qingqing Wu
- CAS Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, China (Q.W., R.Z.)
| | - Yaogan Luo
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (Q.Q.)
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Jiqiu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Rong Zeng
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,CAS Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, China (Q.W., R.Z.)
| | - Geng Zong
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xu Lin
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
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Tackling Atherosclerosis via Selected Nutrition. Int J Mol Sci 2022; 23:ijms23158233. [PMID: 35897799 PMCID: PMC9368664 DOI: 10.3390/ijms23158233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/22/2022] [Accepted: 07/23/2022] [Indexed: 12/02/2022] Open
Abstract
The development and pathogenesis of atherosclerosis are significantly influenced by lifestyle, particularly nutrition. The modern level of science and technology development promote personalized nutrition as an efficient preventive measure against atherosclerosis. In this survey, the factors were revealed that contribute to the formation of an individual approach to nutrition: genetic characteristics, the state of the microbiota of the gastrointestinal tract (GIT) and environmental factors (diets, bioactive components, cardioprotectors, etc.). In the course of the work, it was found that in order to analyze the predisposition to atherosclerosis associated with nutrition, genetic features affecting the metabolism of nutrients are significant. The genetic features include the presence of single nucleotide polymorphisms (SNP) of genes and epigenetic factors. The influence of telomere length on the pathogenesis of atherosclerosis and circadian rhythms was also considered. Relatively new is the study of the relationship between chrono-nutrition and the development of metabolic diseases. That is, to obtain the relationship between nutrition and atherosclerosis, a large number of genetic markers should be considered. In this relation, the question arises: “How many genetic features need to be analyzed in order to form a personalized diet for the consumer?” Basically, companies engaged in nutrigenetic research and choosing a diet for the prevention of a number of metabolic diseases use SNP analysis of genes that accounts for lipid metabolism, vitamins, the body’s antioxidant defense system, taste characteristics, etc. There is no set number of genetic markers. The main diets effective against the development of atherosclerosis were considered, and the most popular were the ketogenic, Mediterranean, and DASH-diets. The advantage of these diets is the content of foods with a low amount of carbohydrates, a high amount of vegetables, fruits and berries, as well as foods rich in antioxidants. However, due to the restrictions associated with climatic, geographical, material features, these diets are not available for a number of consumers. The way out is the use of functional products, dietary supplements. In this approach, the promising biologically active substances (BAS) that exhibit anti-atherosclerotic potential are: baicalin, resveratrol, curcumin, quercetin and other plant metabolites. Among the substances, those of animal origin are popular: squalene, coenzyme Q10, omega-3. For the prevention of atherosclerosis through personalized nutrition, it is necessary to analyze the genetic characteristics (SNP) associated with the metabolism of nutrients, to assess the state of the microbiota of the GIT. Based on the data obtained and food preferences, as well as the individual capabilities of the consumer, the optimal diet can be selected. It is topical to exclude nutrients of which their excess consumption stimulates the occurrence and pathogenesis of atherosclerosis and to enrich the diet with functional foods (FF), BAS containing the necessary anti-atherosclerotic, and stimulating microbiota of the GIT nutrients. Personalized nutrition is a topical preventive measure and there are a number of problems hindering the active use of this approach among consumers. The key factors include weak evidence of the influence of a number of genetic features, the high cost of the approach, and difficulties in the interpretation of the results. Eliminating these deficiencies will contribute to the maintenance of a healthy state of the population through nutrition.
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95
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Wang F, Baden MY, Guasch-Ferré M, Wittenbecher C, Li J, Li Y, Wan Y, Bhupathiraju SN, Tobias DK, Clish CB, Mucci LA, Eliassen AH, Costenbader KH, Karlson EW, Ascherio A, Rimm EB, Manson JE, Liang L, Hu FB. Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes. Diabetologia 2022; 65:1119-1132. [PMID: 35391539 PMCID: PMC9810389 DOI: 10.1007/s00125-022-05692-8] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 01/24/2022] [Indexed: 01/07/2023]
Abstract
AIMS/HYPOTHESIS Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes. METHODS Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified. RESULTS We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05). CONCLUSIONS/INTERPRETATION Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.
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Affiliation(s)
- Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Megu Y Baden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yanping Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yi Wan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Shilpa N Bhupathiraju
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - A Heather Eliassen
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Karen H Costenbader
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth W Karlson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alberto Ascherio
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric B Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - JoAnn E Manson
- Channing Division of Network 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
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Mary Horrigan Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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96
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Chen GC, Chai JC, Xing J, Moon JY, Shan Z, Yu B, Mossavar-Rahman Y, Sotres-Alvarez D, Li J, Mattei J, Daviglus ML, Perkins DL, Burk RD, Boerwinkle E, Kaplan RC, Hu FB, Qi Q. Healthful eating patterns, serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos. Diabetologia 2022; 65:1133-1144. [PMID: 35357561 PMCID: PMC9890970 DOI: 10.1007/s00125-022-05690-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/25/2022] [Indexed: 02/03/2023]
Abstract
AIMS/HYPOTHESIS We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes. METHODS We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors. RESULTS We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RRper SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (pinteraction = 0.0001), HEI-2015 (pinteraction = 0.020) or hPDI (pinteraction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively. CONCLUSIONS/INTERPRETATION Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.
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Affiliation(s)
- Guo-Chong Chen
- Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jin Choul Chai
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jiaqian Xing
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Zhilei Shan
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yasmin Mossavar-Rahman
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jun Li
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Josiemer Mattei
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - David L Perkins
- Department of Medicine, University of Illinois, Chicago, IL, USA
| | - Robert D Burk
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Department of Microbiology and Immunology, Department of Obstetrics, Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
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97
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Genome-Wide Studies in Ischaemic Stroke: Are Genetics Only Useful for Finding Genes? Int J Mol Sci 2022; 23:ijms23126840. [PMID: 35743317 PMCID: PMC9224543 DOI: 10.3390/ijms23126840] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 02/07/2023] Open
Abstract
Ischaemic stroke is a complex disease with some degree of heritability. This means that heritability factors, such as genetics, could be risk factors for ischaemic stroke. The era of genome-wide studies has revealed some of these heritable risk factors, although the data generated by these studies may also be useful in other disciplines. Analysis of these data can be used to understand the biological mechanisms associated with stroke risk and stroke outcome, to determine the causality between stroke and other diseases without the need for expensive clinical trials, or to find potential drug targets with higher success rates than other strategies. In this review we will discuss several of the most relevant studies regarding the genetics of ischaemic stroke and the potential use of the data generated.
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98
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Chen F, Zhang Y, Chen S, Si A, Hu W. Cardiovascular Disease Mortality Attributable to Low Whole-Grain Intake in CHINA: An Age-Period-Cohort and Joinpoint Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19127096. [PMID: 35742345 PMCID: PMC9222971 DOI: 10.3390/ijerph19127096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 05/31/2022] [Accepted: 06/08/2022] [Indexed: 11/21/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide. Low whole-grain intake is found to be one of the most important risk factors for cardiovascular disease development and progression. In this study, we focused on exploring the long-term trends of low whole-grain intake attributed to cardiovascular disease mortality in China during 1990–2019 and relative gender differences. Study data were obtained from the Global Burden of Disease (GBD) 2019 study. We used the age-period-cohort model to estimate the adjusted effect of age, period, and cohorts. Annual and average annual percentage changes were estimated by joinpoint regression analysis. We observed an increasing trend with a net drift of 1.208% for males and 0.483% for males per year. The longitudinal age curve suggested that the attributed rate increased for both genders. Period and cohort effects all suggested that the risk for males showed an increased trend that was higher than that of females. Our findings suggest that males and senior-aged people were at a higher risk of cardiovascular disease mortality attributed to low whole-grain intake. Effective strategies are needed to enhance people’s health consciousness, and increasing whole-grain intake may achieve a better preventive effect for cardiovascular disease.
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Affiliation(s)
- Fangyao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76 Yanta Xilu Road, Xi’an 710061, China; (Y.Z.); (S.C.); (A.S.); (W.H.)
- Department of Radiology, First Affiliated Hospital of Xi’an Jiaotong University, No. 277, Yanta Xilu Road, Yanta District, Xi’an 710061, China
- Correspondence: ; Tel.: +86-29-82655104-202
| | - Yuxiang Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76 Yanta Xilu Road, Xi’an 710061, China; (Y.Z.); (S.C.); (A.S.); (W.H.)
| | - Shiyu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76 Yanta Xilu Road, Xi’an 710061, China; (Y.Z.); (S.C.); (A.S.); (W.H.)
| | - Aima Si
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76 Yanta Xilu Road, Xi’an 710061, China; (Y.Z.); (S.C.); (A.S.); (W.H.)
| | - Weiwei Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76 Yanta Xilu Road, Xi’an 710061, China; (Y.Z.); (S.C.); (A.S.); (W.H.)
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99
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Duan H, Pan J, Guo M, Li J, Yu L, Fan L. Dietary strategies with anti-aging potential: dietary patterns and supplements. Food Res Int 2022; 158:111501. [DOI: 10.1016/j.foodres.2022.111501] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/05/2022] [Accepted: 06/09/2022] [Indexed: 11/04/2022]
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100
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Smith E, Ericson U, Hellstrand S, Orho-Melander M, Nilsson PM, Fernandez C, Melander O, Ottosson F. A healthy dietary metabolic signature is associated with a lower risk for type 2 diabetes and coronary artery disease. BMC Med 2022; 20:122. [PMID: 35443726 PMCID: PMC9022292 DOI: 10.1186/s12916-022-02326-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 03/08/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The global burden of cardiovascular disease and type 2 diabetes could be decreased by improving dietary factors, but identification of groups suitable for interventional approaches can be difficult. Reporting of dietary intake is prone to errors, and measuring of metabolites has shown promise in determining habitual dietary intake. Our aim is to create a metabolic signature that is associated with healthy eating and test if it associates with type 2 diabetes and coronary artery disease risk. METHODS Using plasma metabolite data consisting of 111 metabolites, partial least square (PLS) regression was used to identify a metabolic signature associated with a health conscious food pattern in the Malmö Offspring Study (MOS, n = 1538). The metabolic signature's association with dietary intake was validated in the Malmö Diet and Cancer study (MDC, n = 2521). The associations between the diet-associated metabolic signature and incident type 2 diabetes and coronary artery disease (CAD) were tested using Cox regression in MDC and logistic regression in Malmö Preventive Project (MPP, n = 1083). Modelling was conducted unadjusted (model 1), adjusted for potential confounders (model 2) and additionally for potential mediators (model 3). RESULTS The metabolic signature was associated with lower risk for type 2 diabetes in both MDC (hazard ratio: 0.58, 95% CI 0.52-0.66, per 1 SD increment of the metabolic signature) and MPP (odds ratio: 0.54, 95% CI 0.44-0.65 per 1 SD increment of the metabolic signature) in model 2. The results were attenuated but remained significant in model 3 in both MDC (hazard ratio 0.73, 95% CI 0.63-0.83) and MPP (odds ratio 0.70, 95% CI 0.55-0.88). The diet-associated metabolic signature was also inversely associated with lower risk of CAD in both MDC and MPP in model 1, but the association was non-significant in model 3. CONCLUSIONS In this proof-of-concept study, we identified a healthy diet-associated metabolic signature, which was inversely associated with future risk for type 2 diabetes and coronary artery disease in two different cohorts. The association with diabetes was independent of traditional risk factors and might illustrate an effect of health conscious dietary intake on cardiometabolic health.
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Affiliation(s)
- Einar Smith
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden.
| | - Ulrika Ericson
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden
| | - Sophie Hellstrand
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden
| | - Marju Orho-Melander
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden
| | - Peter M Nilsson
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden.,Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Céline Fernandez
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden.,Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Filip Ottosson
- Department of Clinical Sciences, Lund University, Jan Waldenströms gata 35, 91-12-027, SE-214 28, Malmö, Sweden.,Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
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