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Zhang Y, Zhao H, Zhao J, Lv W, Jia X, Lu X, Zhao X, Xu G. Quantified Metabolomics and Lipidomics Profiles Reveal Serum Metabolic Alterations and Distinguished Metabolites of Seven Chronic Metabolic Diseases. J Proteome Res 2024; 23:3076-3087. [PMID: 38407022 DOI: 10.1021/acs.jproteome.3c00760] [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] [Indexed: 02/27/2024]
Abstract
The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.
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Affiliation(s)
- Yuqing Zhang
- School of Chemistry, Dalian University of Technology, Dalian 116024, P. R. China
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Hui Zhao
- Department of the Health Checkup Center, The Second Hospital of Dalian Medical University, Dalian 116023, P. R. China
| | - Jinhui Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
| | - Xueni Jia
- Department of the Health Checkup Center, The Second Hospital of Dalian Medical University, Dalian 116023, P. R. China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Guowang Xu
- School of Chemistry, Dalian University of Technology, Dalian 116024, P. R. China
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
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Wen X, Fretts AM, Miao G, Malloy KM, Zhang Y, Umans JG, Cole SA, Best LG, Fiehn O, Zhao J. Plasma lipidomic markers of diet quality are associated with incident coronary heart disease in American Indian adults: the Strong Heart Family Study. Am J Clin Nutr 2024; 119:748-755. [PMID: 38160800 PMCID: PMC11347812 DOI: 10.1016/j.ajcnut.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/15/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05. RESULTS Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43). CONCLUSIONS In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.
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Affiliation(s)
- Xiaoxiao Wen
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Kimberly M Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jason G Umans
- Biomarker, Biochemistry, and Biorepository Core, MedStar Health Research Institute, Hyattsville, MD, United States; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, United States
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Lyle G Best
- Missouri Breaks Industries Research, Timber Lake, SD, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States.
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Miao G, Pechlaner R, Fiehn O, Malloy KM, Zhang Y, Umans JG, Mayr M, Willeit J, Kiechl S, Zhao J. Longitudinal Lipidomic Signature of Coronary Heart Disease in American Indian People. J Am Heart Assoc 2024; 13:e031825. [PMID: 38293910 PMCID: PMC11056164 DOI: 10.1161/jaha.123.031825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/14/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND Dyslipidemia is an independent risk factor for coronary heart disease (CHD). Standard lipid panel cannot capture the complexity of the blood lipidome (ie, all molecular lipids in the blood). To date, very few large-scale epidemiological studies have assessed the full spectrum of the blood lipidome on risk of CHD, especially in a longitudinal setting. METHODS AND RESULTS Using an untargeted liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species from 1835 unique American Indian participants who attended 2 clinical visits (≈5.5 years apart) and followed up to 17.8 years in the Strong Heart Family Study (SHFS). We first identified baseline lipid species associated with risk of CHD, followed by replication in a European population. The model adjusted for age, sex, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, estimated glomerular filtration rate, education, and physical activity at baseline. We then examined the longitudinal association between changes in lipid species and changes in cardiovascular risk factors during follow-up. Multiple testing was controlled by the false discovery rate. We found that baseline levels of multiple lipid species (eg, phosphatidylcholines, phosphatidylethanolamines, and ceramides) were associated with the risk of CHD and improved the prediction accuracy over conventional risk factors in American Indian people. Some identified lipids in American Indian people were replicated in European people. Longitudinal changes in multiple lipid species (eg, acylcarnitines, phosphatidylcholines, and triacylglycerols) were associated with changes in cardiovascular risk factors. CONCLUSIONS Baseline plasma lipids and their longitudinal changes over time are associated with risk of CHD. These findings provide novel insights into the role of dyslipidemia in CHD.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of MedicineUniversity of FloridaGainesvilleFL
- Center for Genetic Epidemiology and BioinformaticsUniversity of FloridaGainesvilleFL
| | | | - Oliver Fiehn
- West Coast Metabolomics CenterUniversity of CaliforniaDavisCA
| | - Kimberly M. Malloy
- Department of Biostatistics and EpidemiologyUniversity of Oklahoma Health Sciences CenterOklahoma CityOK
| | - Ying Zhang
- Department of Biostatistics and EpidemiologyUniversity of Oklahoma Health Sciences CenterOklahoma CityOK
| | | | - Manuel Mayr
- National Heart & Lung InstituteImperial CollegeLondonUK
| | - Johann Willeit
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
| | - Stefan Kiechl
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Research Centre on Vascular Ageing and StrokeInnsbruckAustria
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of MedicineUniversity of FloridaGainesvilleFL
- Center for Genetic Epidemiology and BioinformaticsUniversity of FloridaGainesvilleFL
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