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Ma S, Morris MC, Hubal MJ, Ross LM, Huffman KM, Vann CG, Moore N, Hauser ER, Bareja A, Jiang R, Kummerfeld E, Barberio MD, Houmard JA, Bennett WB, Johnson JL, Timmons JA, Broderick G, Kraus VB, Aliferis CF, Kraus WE. Sex-Specific Skeletal Muscle Gene Expression Responses to Exercise Reveal Novel Direct Mediators of Insulin Sensitivity Change. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.07.24313236. [PMID: 39281755 PMCID: PMC11398589 DOI: 10.1101/2024.09.07.24313236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
BACKGROUND Understanding the causal pathways, systems, and mechanisms through which exercise impacts human health is complex. This study explores molecular signaling related to whole-body insulin sensitivity (Si) by examining changes in skeletal muscle gene expression. The analysis considers differences by biological sex, exercise amount, and exercise intensity to identify potential molecular targets for developing pharmacologic agents that replicate the health benefits of exercise. METHODS The study involved 53 participants from the STRRIDE I and II trials who completed eight months of aerobic training. Skeletal muscle gene expression was measured using Affymetrix and Illumina technologies, while pre- and post-training Si was assessed via an intravenous glucose tolerance test. A novel gene discovery protocol, integrating three literature-derived and data-driven modeling strategies, was employed to identify causal pathways and direct causal factors based on differentially expressed transcripts associated with exercise intensity and amount. RESULTS In women, the transcription factor targets identified were primarily influenced by exercise amount and were generally inhibitory. In contrast, in men, these targets were driven by exercise intensity and were generally activating. Transcription factors such as ATF1, CEBPA, BACH2, and STAT1 were commonly activating in both sexes. Specific transcriptional targets related to exercise-induced Si improvements included TACR3 and TMC7 for intensity-driven effects, and GRIN3B and EIF3B for amount-driven effects. Two key signaling pathways mediating aerobic exercise-induced Si improvements were identified: one centered on estrogen signaling and the other on phorbol ester (PKC) signaling, both converging on the epidermal growth factor receptor (EGFR) and other relevant targets. CONCLUSIONS The signaling pathways mediating Si improvements from aerobic exercise differed by sex and were further distinguished by exercise intensity and amount. Transcriptional adaptations in skeletal muscle related to Si improvements appear to be causally linked to estrogen and PKC signaling, with EGFR and other identified targets emerging as potential skeletal muscle-specific drug targets to mimic the beneficial effects of exercise on Si.
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Affiliation(s)
- S Ma
- Institute for Health Informatics (IHI), Academic Health Center, University of Minnesota, Minneapolis, MN 55455
| | - M C Morris
- Center for Clinical Systems Biology, Rochester General Hospital, Rochester, NY 14621
| | - M J Hubal
- Department of Kinesiology, Indiana University - Indianapolis, Indianapolis IN 46202
| | - L M Ross
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - K M Huffman
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - C G Vann
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - N Moore
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - E R Hauser
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
- Department of Head and Neck Surgery & Communication Sciences, Duke University School of Medicine, Durham, NC 27701
| | - A Bareja
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - R Jiang
- Department of Head and Neck Surgery & Communication Sciences, Duke University School of Medicine, Durham, NC 27701
| | - E Kummerfeld
- Institute for Health Informatics (IHI), Academic Health Center, University of Minnesota, Minneapolis, MN 55455
| | - M D Barberio
- Department of Exercise and Nutrition Sciences, George Washington University, Washington DC 20052
| | - J A Houmard
- Department of Kinesiology, ECU, Greenville, NC 27858
| | - W B Bennett
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - J L Johnson
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - J A Timmons
- School of Medicine and Dentistry, Queen Mary University of London, UK
| | - G Broderick
- Center for Clinical Systems Biology, Rochester General Hospital, Rochester, NY 14621
| | - V B Kraus
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
| | - C F Aliferis
- Institute for Health Informatics (IHI), Academic Health Center, University of Minnesota, Minneapolis, MN 55455
| | - W E Kraus
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701
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Vashishtha S, Broderick G, Craddock TJA, Barnes ZM, Collado F, Balbin EG, Fletcher MA, Klimas NG. Leveraging Prior Knowledge to Recover Characteristic Immune Regulatory Motifs in Gulf War Illness. Front Physiol 2020; 11:358. [PMID: 32411011 PMCID: PMC7198798 DOI: 10.3389/fphys.2020.00358] [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: 01/21/2019] [Accepted: 03/27/2020] [Indexed: 11/13/2022] Open
Abstract
Potentially linked to the basic physiology of stress response, Gulf War Illness (GWI) is a debilitating condition presenting with complex immune, endocrine and neurological symptoms. Here we interrogate the immune response to physiological stress by measuring 16 blood-borne immune markers at 8 time points before, during and after maximum exercise challenge in n = 12 GWI veterans and n = 11 healthy veteran controls deployed to the same theater. Immune markers were combined into functional sets and the dynamics of their joint expression described as classical rate equations. These empirical networks were further informed structurally by projection onto prior knowledge networks mined from the literature. Of the 49 literature-informed immune signaling interactions, 21 were found active in the combined exercise response data. However, only 4 signals were common to both subject groups while 7 were uniquely active in GWI and 10 uniquely active in healthy veterans. Feedforward mediation of IL-23 and IL-17 by IL-6 and IL-10 emerged as distinguishing control elements that were characteristically active in GWI versus healthy subjects. Simulated restructuring of the regulatory circuitry in GWI as a result of applying an IL-6 receptor antagonist in combination with either a Th1 (IL-2, IFNγ, and TNFα) or IL-23 receptor antagonist predicted a partial rescue of immune response elements previously associated with illness severity. Overall, results suggest that pharmacologically altering the topology of the immune response circuitry identified as active in GWI can inform on strategies that while not curative, may nonetheless deliver a reduction in symptom burden. A lasting and more complete remission in GWI may therefore require manipulation of a broader physiology, namely one that includes endocrine oversight of immune function.
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Affiliation(s)
- Saurabh Vashishtha
- Department of Medicine, University of Alberta, Edmonton, AB, Canada.,Center for Clinical Systems Biology, Rochester General Hospital, Rochester, NY, United States
| | - Gordon Broderick
- Center for Clinical Systems Biology, Rochester General Hospital, Rochester, NY, United States.,Department of Biomedical Engineering, Kate Gleason College of Engineering, Rochester Institute of Technology, Rochester, NY, United States
| | - Travis J A Craddock
- Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.,Departments of Psychology & Neuroscience, Computer Science and Clinical Immunology, Nova Southeastern University, Fort Lauderdale, FL, United States
| | - Zachary M Barnes
- Diabetes Research Institute, University of Miami, Miami, FL, United States.,Miami Veterans Affairs Medical Center, Miami, FL, United States
| | - Fanny Collado
- Miami Veterans Affairs Medical Center, Miami, FL, United States
| | - Elizabeth G Balbin
- Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.,Miami Veterans Affairs Medical Center, Miami, FL, United States
| | - Mary Ann Fletcher
- Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.,Departments of Psychology & Neuroscience, Computer Science and Clinical Immunology, Nova Southeastern University, Fort Lauderdale, FL, United States.,Miami Veterans Affairs Medical Center, Miami, FL, United States
| | - Nancy G Klimas
- Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.,Departments of Psychology & Neuroscience, Computer Science and Clinical Immunology, Nova Southeastern University, Fort Lauderdale, FL, United States.,Miami Veterans Affairs Medical Center, Miami, FL, United States
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Serin EAR, Nijveen H, Hilhorst HWM, Ligterink W. Learning from Co-expression Networks: Possibilities and Challenges. FRONTIERS IN PLANT SCIENCE 2016; 7:444. [PMID: 27092161 PMCID: PMC4825623 DOI: 10.3389/fpls.2016.00444] [Citation(s) in RCA: 186] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 03/21/2016] [Indexed: 05/18/2023]
Abstract
Plants are fascinating and complex organisms. A comprehensive understanding of the organization, function and evolution of plant genes is essential to disentangle important biological processes and to advance crop engineering and breeding strategies. The ultimate aim in deciphering complex biological processes is the discovery of causal genes and regulatory mechanisms controlling these processes. The recent surge of omics data has opened the door to a system-wide understanding of the flow of biological information underlying complex traits. However, dealing with the corresponding large data sets represents a challenging endeavor that calls for the development of powerful bioinformatics methods. A popular approach is the construction and analysis of gene networks. Such networks are often used for genome-wide representation of the complex functional organization of biological systems. Network based on similarity in gene expression are called (gene) co-expression networks. One of the major application of gene co-expression networks is the functional annotation of unknown genes. Constructing co-expression networks is generally straightforward. In contrast, the resulting network of connected genes can become very complex, which limits its biological interpretation. Several strategies can be employed to enhance the interpretation of the networks. A strategy in coherence with the biological question addressed needs to be established to infer reliable networks. Additional benefits can be gained from network-based strategies using prior knowledge and data integration to further enhance the elucidation of gene regulatory relationships. As a result, biological networks provide many more applications beyond the simple visualization of co-expressed genes. In this study we review the different approaches for co-expression network inference in plants. We analyse integrative genomics strategies used in recent studies that successfully identified candidate genes taking advantage of gene co-expression networks. Additionally, we discuss promising bioinformatics approaches that predict networks for specific purposes.
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Affiliation(s)
- Elise A. R. Serin
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen UniversityWageningen, Netherlands
| | - Harm Nijveen
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen UniversityWageningen, Netherlands
- Laboratory of Bioinformatics, Wageningen UniversityWageningen, Netherlands
| | - Henk W. M. Hilhorst
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen UniversityWageningen, Netherlands
| | - Wilco Ligterink
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen UniversityWageningen, Netherlands
- *Correspondence: Wilco Ligterink
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