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Sun S, Hara A, Johnstone L, Hallmark B, Watkins JC, Thomson CA, Schembre SM, Sergeant S, Umans JG, Yao G, Zhang HH, Chilton FH. Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans Following Omega-3 Fatty Acid Supplementation. Nutrients 2024; 16:2933. [PMID: 39275249 DOI: 10.3390/nu16172933] [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: 07/30/2024] [Revised: 08/16/2024] [Accepted: 08/24/2024] [Indexed: 09/16/2024] Open
Abstract
Conflicting clinical trial results on omega-3 highly unsaturated fatty acids (n-3 HUFA) have prompted uncertainty about their cardioprotective effects. While the VITAL trial found no overall cardiovascular benefit from n-3 HUFA supplementation, its substantial African American (AfAm) enrollment provided a unique opportunity to explore racial differences in response to n-3 HUFA supplementation. The current observational study aimed to simulate randomized clinical trial (RCT) conditions by matching 3766 AfAm and 15,553 non-Hispanic White (NHW) individuals from the VITAL trial utilizing propensity score matching to address the limitations related to differences in confounding variables between the two groups. Within matched groups (3766 AfAm and 3766 NHW), n-3 HUFA supplementation's impact on myocardial infarction (MI), stroke, and cardiovascular disease (CVD) mortality was assessed. A weighted decision tree analysis revealed belonging to the n-3 supplementation group as the most significant predictor of MI among AfAm but not NHW. Further logistic regression using the LASSO method and bootstrap estimation of standard errors indicated n-3 supplementation significantly lowered MI risk in AfAm (OR 0.17, 95% CI [0.048, 0.60]), with no such effect in NHW. This study underscores the critical need for future RCT to explore racial disparities in MI risk associated with n-3 HUFA supplementation and highlights potential causal differences between supplementation health outcomes in AfAm versus NHW populations.
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Affiliation(s)
- Shudong Sun
- Department of Mathematics, University of Arizona, Tucson, AZ 85721, USA
- Statistics Interdisciplinary Program, University of Arizona, Tucson, AZ 85721, USA
| | - Aki Hara
- School of Nutritional Sciences and Wellness, College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ 85719, USA
| | - Laurel Johnstone
- School of Nutritional Sciences and Wellness, College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ 85719, USA
| | - Brian Hallmark
- BIO5 Institute, University of Arizona, Tucson, AZ 85719, USA
- Center for Precision Nutrition and Wellness, University of Arizona, Tucson, AZ 85719, USA
| | - Joseph C Watkins
- Department of Mathematics, University of Arizona, Tucson, AZ 85721, USA
- Statistics Interdisciplinary Program, University of Arizona, Tucson, AZ 85721, USA
| | - Cynthia A Thomson
- Department of Health Promotion Sciences, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85724, USA
| | - Susan M Schembre
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, USA
| | - Susan Sergeant
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Jason G Umans
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC 20057, USA
| | - Guang Yao
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA
| | - Hao Helen Zhang
- Department of Mathematics, University of Arizona, Tucson, AZ 85721, USA
- Statistics Interdisciplinary Program, University of Arizona, Tucson, AZ 85721, USA
| | - Floyd H Chilton
- School of Nutritional Sciences and Wellness, College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ 85719, USA
- BIO5 Institute, University of Arizona, Tucson, AZ 85719, USA
- Center for Precision Nutrition and Wellness, University of Arizona, Tucson, AZ 85719, USA
- Escuela de Medicina y Ciencias de la Salud, Tecnologico de Monterrey, Monterrey 64710, Mexico
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Quarta S, Santarpino G, Carluccio MA, Calabriso N, Cardetta F, Siracusa L, Strano T, Palamà I, Leccese G, Visioli F, Massaro M. Cardiac fat adipocytes: An optimized protocol for isolation of ready-to-use mature adipocytes from human pericardial adipose tissue. J Mol Cell Cardiol 2024; 196:12-25. [PMID: 39214497 DOI: 10.1016/j.yjmcc.2024.08.006] [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: 05/03/2024] [Revised: 08/23/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024]
Abstract
A better understanding of the pathophysiology of cardiac fat depots is crucial to describe their role in the development of cardiovascular diseases. To this end, we have developed a method to isolate mature fat cells from the pericardial adipose tissue (PAT), the most accessible cardiac fat depot during cardiac surgery. Using enzymatic isolation, we were able to successfully obtain mature fat cells together with the corresponding cells of the stromal vascular fraction (SVF). We subjected the PAT adipocytes to thorough morphological and molecular characterization, including detailed fatty acid profiling, and simultaneously investigated their reactivity to external stimuli. Our approach resulted in highly purified fat cells with sustained viability for up to 72 h after explantation. Remarkably, these adipocytes responded to multiple challenges, including pro-inflammatory and metabolic stimuli, indicating their potential to trigger a pro-inflammatory response and modulate endothelial cell behavior. Furthermore, we have created conditions to maintain whole PAT in culture and preserve their viability and reactivity to external stimuli. The efficiency of cell recovery combined with minimal dedifferentiation underscores the promise for future applications as a personalized tool for screening and assessing individual patient responses to drugs and supplements or nutraceuticals.
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Affiliation(s)
- Stefano Quarta
- Institute of Clinical Physiology (IFC), National Research Council (CNR), 73100 Lecce, Italy.
| | - Giuseppe Santarpino
- Department of Clinical and Experimental Medicine, Magna Graecia University of Catanzaro, Italy; Department of Cardiac Surgery, Città di Lecce Hospital, GVM Care&Research, Lecce, Italy; Department of Cardiac Surgery, Paracelsus Medical University, Nuremberg, Germany.
| | | | - Nadia Calabriso
- Institute of Clinical Physiology (IFC), National Research Council (CNR), 73100 Lecce, Italy.
| | - Francesco Cardetta
- Department of Cardiac Surgery, University "Campus Biomedico", Rome, Italy.
| | - Laura Siracusa
- Institute of Biomolecular Chemistry (ICB), National Research Council (CNR), Catania section, Via Paolo Gaifami 18, 95126 Catania, Italy.
| | - Tonia Strano
- Institute of Biomolecular Chemistry (ICB), National Research Council (CNR), Catania section, Via Paolo Gaifami 18, 95126 Catania, Italy.
| | - Ilaria Palamà
- Institute Nanotechnology Institute, CNR-NANOTEC, 73100 Lecce, Italy.
| | - Gabriella Leccese
- Institute Nanotechnology Institute, CNR-NANOTEC, 73100 Lecce, Italy.
| | | | - Marika Massaro
- Institute of Clinical Physiology (IFC), National Research Council (CNR), 73100 Lecce, Italy.
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Cheng H, Miller D, Southwell N, Fischer JL, Taylor I, Salbaum JM, Kappen C, Hu F, Yang C, Gross SS, D'Aurelio M, Chen Q. Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575105. [PMID: 38370710 PMCID: PMC10871215 DOI: 10.1101/2024.01.10.575105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of structurally identified and yet-undefined metabolites across tissue cryosections. While numerous software packages enable pixel-by-pixel imaging of individual metabolites, the research community lacks a discovery tool that images all metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs informs discovery of unanticipated molecules contributing to shared metabolic pathways, uncovers hidden metabolic heterogeneity across cells and tissue subregions, and indicates single-timepoint flux through pathways of interest. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling and instrument drift, markedly enhances spatial image resolution, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
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Zhan C, Tang T, Wu E, Zhang Y, He M, Wu R, Bi C, Wang J, Zhang Y, Shen B. From multi-omics approaches to personalized medicine in myocardial infarction. Front Cardiovasc Med 2023; 10:1250340. [PMID: 37965091 PMCID: PMC10642346 DOI: 10.3389/fcvm.2023.1250340] [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: 06/30/2023] [Accepted: 10/17/2023] [Indexed: 11/16/2023] Open
Abstract
Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.
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Affiliation(s)
- Chaoying Zhan
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Tong Tang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Erman Wu
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yuxin Zhang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- KeyLaboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
| | - Mengqiao He
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Rongrong Wu
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Cheng Bi
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- KeyLaboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
| | - Jiao Wang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yingbo Zhang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Bairong Shen
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
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