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      Temporal dynamics of the multi-omic response to endurance exercise training

      research-article
      MoTrPAC Study Group 1 , Lead Analysts, MoTrPAC Study Group
      Nature
      Nature Publishing Group UK
      Transcriptomics, Proteomics, Epigenetics, Metabolomics

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          Abstract

          Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood 13 . Here, the Molecular Transducers of Physical Activity Consortium 4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/).

          Abstract

          Temporal multi-omic analysis of tissues from rats undergoing up to eight weeks of endurance exercise training reveals widespread shared, tissue-specific and sex-specific changes, including immune, metabolic, stress response and mitochondrial pathways.

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          Most cited references38

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          Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease

          Metabolomics studies hold promise for discovery of pathways linked to disease processes. Cardiovascular disease (CVD) represents the leading cause of death and morbidity worldwide. A metabolomics approach was used to generate unbiased small molecule metabolic profiles in plasma that predict risk for CVD. Three metabolites of the dietary lipid phosphatidylcholine, namely choline, trimethylamine N-oxide (TMAO), and betaine, were identified and then shown to predict risk for CVD in an independent large clinical cohort. Dietary supplementation of mice with choline, TMAO or betaine promoted up-regulation of multiple macrophage scavenger receptors linked to atherosclerosis, and supplementation with choline or TMAO promoted atherosclerosis. Studies using germ-free mice confirmed a critical role for dietary choline and gut flora in TMAO production, augmented macrophage cholesterol accumulation and foam cell formation. Suppression of intestinal microflora in atherosclerosis-prone mice inhibited dietary choline-enhanced atherosclerosis. Genetic variations controlling expression of flavin monooxygenases (FMOs), an enzymatic source of TMAO, segregated with atherosclerosis in hyperlipidemic mice. Discovery of a relationship between gut flora-dependent metabolism of dietary phosphatidylcholine and CVD pathogenesis provides opportunities for development of both novel diagnostic tests and therapeutic approaches for atherosclerotic heart disease.
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            Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease

            Crohn’s disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry with rising prevalence in other populations 1 . Genome-wide association studies (GWAS) and subsequent meta-analyses of CD and UC 2,3 as separate phenotypes implicated previously unsuspected mechanisms, such as autophagy 4 , in pathogenesis and showed that some IBD loci are shared with other inflammatory diseases 5 . Here we expand knowledge of relevant pathways by undertaking a meta-analysis of CD and UC genome-wide association scans, with validation of significant findings in more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional and balancing selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe striking overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.
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              Exercise as medicine - evidence for prescribing exercise as therapy in 26 different chronic diseases.

              This review provides the reader with the up-to-date evidence-based basis for prescribing exercise as medicine in the treatment of 26 different diseases: psychiatric diseases (depression, anxiety, stress, schizophrenia); neurological diseases (dementia, Parkinson's disease, multiple sclerosis); metabolic diseases (obesity, hyperlipidemia, metabolic syndrome, polycystic ovarian syndrome, type 2 diabetes, type 1 diabetes); cardiovascular diseases (hypertension, coronary heart disease, heart failure, cerebral apoplexy, and claudication intermittent); pulmonary diseases (chronic obstructive pulmonary disease, asthma, cystic fibrosis); musculo-skeletal disorders (osteoarthritis, osteoporosis, back pain, rheumatoid arthritis); and cancer. The effect of exercise therapy on disease pathogenesis and symptoms are given and the possible mechanisms of action are discussed. We have interpreted the scientific literature and for each disease, we provide the reader with our best advice regarding the optimal type and dose for prescription of exercise.
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                Author and article information

                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                1 May 2024
                1 May 2024
                2024
                : 629
                : 8010
                : 174-183
                Affiliations
                [1 ]Department of Medicine, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [2 ]Department of Genetics, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [3 ]Proteomics Platform, Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [4 ]Department of Internal Medicine, University of Iowa, ( https://ror.org/036jqmy94) Iowa City, IA USA
                [5 ]Department of Quantitative Health Sciences, Mayo Clinic, ( https://ror.org/02qp3tb03) Rochester, MN USA
                [6 ]Metabolomics Platform, Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [7 ]Department of Internal Medicine, University of Michigan, ( https://ror.org/00jmfr291) Ann Arbor, MI USA
                [8 ]School of Chemistry and Biochemistry, Georgia Institute of Technology, ( https://ror.org/01zkghx44) Atlanta, GA USA
                [9 ]Department of Medicine, Duke University, ( https://ror.org/00py81415) Durham, NC USA
                [10 ]Duke Molecular Physiology Institute, Duke University, ( https://ror.org/00py81415) Durham, NC USA
                [11 ]Emory Integrated Metabolomics and Lipidomics Core, Emory University, ( https://ror.org/03czfpz43) Atlanta, GA USA
                [12 ]BRCF Metabolomics Core, University of Michigan, ( https://ror.org/00jmfr291) Ann Arbor, MI USA
                [13 ]Division of Endocrinology, Nutrition, and Metabolism, Mayo Clinic, ( https://ror.org/02qp3tb03) Rochester, MN USA
                [14 ]Department of Neurology, Icahn School of Medicine at Mount Sinai, ( https://ror.org/04a9tmd77) New York, NY USA
                [15 ]Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, ( https://ror.org/05h992307) Richland, WA USA
                [16 ]Department of Pathology and Laboratory Medicine, University of Vermont, ( https://ror.org/0155zta11) Burlington, VT USA
                [17 ]Department of Pathology, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [18 ]Department of Biostatistics and Data Science, Wake Forest University School of Medicine, ( https://ror.org/0207ad724) Winston-Salem, NC USA
                [19 ]Biological Sciences Division, Pacific Northwest National Laboratory, ( https://ror.org/05h992307) Richland, WA USA
                [20 ]Department of Biochemistry, Emory University, ( https://ror.org/03czfpz43) Atlanta, GA USA
                [21 ]Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, ( https://ror.org/0280a3n32) Boston, MA USA
                [22 ]Department of Human Genetics, University of Michigan, ( https://ror.org/00jmfr291) Ann Arbor, MI USA
                [23 ]Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, ( https://ror.org/04a9tmd77) New York, NY USA
                [24 ]Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, ( https://ror.org/04a9tmd77) New York, NY USA
                [25 ]Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, ( https://ror.org/035z6xf33) Oklahoma City, OK USA
                [26 ]Department of Physiology and Aging, University of Florida, ( https://ror.org/02y3ad647) Gainesville, FL USA
                [27 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Orthopaedic Surgery, School of Medicine, , University of California, San Diego, ; La Jolla, CA USA
                [28 ]Department of Biomedical Data Science, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [29 ]Department of Biostatistics, University of Alabama at Birmingham, ( https://ror.org/008s83205) Birmingham, AL USA
                [30 ]Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, ( https://ror.org/04drvxt59) Boston, MA USA
                [31 ]Division of Public Health Sciences, Wake Forest University School of Medicine, ( https://ror.org/0207ad724) Winston-Salem, NC USA
                [32 ]Department of Medicine, Mayo Clinic, ( https://ror.org/02qp3tb03) Rochester, MN USA
                [33 ]Department of Statistics, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [34 ]Department of Biomedical Data Sciences, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [35 ]Department of Aging and Geriatric Research, University of Florida, ( https://ror.org/02y3ad647) Gainesville, FL USA
                [36 ]Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, ( https://ror.org/0207ad724) Winston-Salem, NC USA
                [37 ]Department of Health and Exercise Science, Wake Forest University School of Medicine, ( https://ror.org/0207ad724) Winston-Salem, NC USA
                [38 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, National Institute on Aging, , National Institutes of Health, ; Bethesda, MD USA
                [39 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, National Institute of Diabetes and Digestive and Kidney Diseases, , National Institutes of Health, ; Bethesda, MD USA
                [40 ]Applied Physiology and Kinesiology, University of Florida, ( https://ror.org/02y3ad647) Gainesville, FL USA
                [41 ]Department of Biomedical Sciences, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [42 ]Department of Medical Pharmacology and Physiology, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [43 ]Department of Nutrition and Exercise Physiology, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [44 ]Dalton Cardiovascular Research Center, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [45 ]Department of Kinesiology and Health Education, University of Texas, ( https://ror.org/00hj54h04) Austin, TX USA
                [46 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Medicine, Division of Endocrinology and Diabetes, , University of California, ; Los Angeles, CA USA
                [47 ]Center for Public Health Genomics, University of Virginia School of Medicine, ( https://ror.org/0153tk833) Charlottesville, VA USA
                [48 ]Section on Clinical, Behavioral, and Outcomes Research, Joslin Diabetes Center, ( https://ror.org/0280a3n32) Boston, MA USA
                [49 ]Department of Molecular Physiology and Biophysics, Vanderbilt University, ( https://ror.org/02vm5rt34) Nashville, TN USA
                [50 ]Department of Health Sciences, Stetson University, ( https://ror.org/01efrfk30) Deland, FL USA
                [51 ]Department of Medicine, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [52 ]NextGen Precision Health, University of Missouri, ( https://ror.org/02ymw8z06) Columbia, MO USA
                [53 ]GRID grid.412016.0, ISNI 0000 0001 2177 6375, Cell Biology and Physiology, Internal Medicine, , University of Kansas Medical Center, ; Kansas City, KS USA
                [54 ]Center for Skeletal Muscle Research at Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, ( https://ror.org/0153tk833) Charlottesville, VA USA
                [55 ]Department of Medicine, University of Virginia School of Medicine, ( https://ror.org/0153tk833) Charlottesville, VA USA
                [56 ]Department of Pharmacology, University of Virginia School of Medicine, ( https://ror.org/0153tk833) Charlottesville, VA USA
                [57 ]Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, ( https://ror.org/0153tk833) Charlottesville, VA USA
                [58 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Fralin Biomedical Research Institute, , Center for Exercise Medicine Research at Virginia Tech Carilion, ; Roanoke, VA USA
                [59 ]Department of Human Nutrition, Foods, and Exercise, College of Agriculture and Life Sciences, Virginia Tech, ( https://ror.org/02smfhw86) Blacksburg, VA USA
                [60 ]Department of Computational and Systems Biology, University of Pittsburgh, ( https://ror.org/01an3r305) Pittsburgh, PA USA
                [61 ]Petit Institute of Bioengineering and Biosciences, Georgia Institute of Technology, ( https://ror.org/01zkghx44) Atlanta, GA USA
                [62 ]Department of Medicine, Emory University, ( https://ror.org/03czfpz43) Atlanta, GA USA
                [63 ]Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, ( https://ror.org/008s83205) Birmingham, AL USA
                [64 ]Department of Medicine, University of Colorado Anschutz Medical Campus, ( https://ror.org/03wmf1y16) Aurora, CO USA
                [65 ]Department of Medicine, University of Alabama at Birmingham, ( https://ror.org/008s83205) Birmingham, AL USA
                [66 ]Human Performance Laboratory, Ball State University, ( https://ror.org/00k6tx165) Muncie, IN USA
                [67 ]GRID grid.414935.e, ISNI 0000 0004 0447 7121, Translational Research Institute, , AdventHealth, ; Orlando, FL USA
                [68 ]GRID grid.266093.8, ISNI 0000 0001 0668 7243, Department of Pediatrics, , University of California, ; Irvine, CA USA
                [69 ]Pennington Biomedical Research Center, ( https://ror.org/040cnym54) Baton Rouge, LA USA
                [70 ]College of Nursing, University of Colorado Anschutz Medical Campus, ( https://ror.org/03wmf1y16) Aurora, CO USA
                [71 ]Department of Medicine, Cedars-Sinai Medical Center, ( https://ror.org/02pammg90) Los Angeles, CA USA
                [72 ]Population and Public Health, Pennington Biomedical Research Center, ( https://ror.org/040cnym54) Baton Rouge, LA USA
                [73 ]GRID grid.468222.8, Biochemistry and Structural Biology, Center for Metabolic Health, Barshop Institute for Longevity and Aging Studies, , University of Texas Health Science Center, ; San Antonio, TX USA
                [74 ]GRID grid.468222.8, Barshop Institute for Longevity and Aging Studies, , University of Texas Health Science Center, ; San Antonio, TX USA
                Article
                6877
                10.1038/s41586-023-06877-w
                11062907
                38693412
                7a541048-7321-4d03-94a7-b8d507d8822d
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 September 2022
                : 16 November 2023
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                © Springer Nature Limited 2024

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                transcriptomics,proteomics,epigenetics,metabolomics
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                transcriptomics, proteomics, epigenetics, metabolomics

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