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Human hair follicle transcriptome profiling: a minimally invasive tool to assess molecular adaptations upon low‐volume, high‐intensity interval training

High‐intensity interval training (HIIT) has become a popular fitness training approach under both civilian and military settings. Consisting of brief and intense exercise intervals, HIIT requires less time commitment yet is able to produce the consistent targeted physical adaptations as conventional...

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Published in:Physiological reports 2017-12, Vol.5 (23), p.n/a
Main Authors: Zhang, Jing, Wallace, Sarah J., Shiu, Maria Y., Smith, Ingrid, Rhind, Shawn G., Langlois, Valerie S.
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description High‐intensity interval training (HIIT) has become a popular fitness training approach under both civilian and military settings. Consisting of brief and intense exercise intervals, HIIT requires less time commitment yet is able to produce the consistent targeted physical adaptations as conventional endurance training. To effectively characterize and monitor HIIT‐induced cellular and molecular responses, a highly accessible yet comprehensive biomarker discovery source is desirable. Both gene differential expression (DE) and gene set (GS) analyses were conducted using hair follicle transcriptome established from pre and postexercise subjects upon a 10‐day HIIT program by RNA‐Seq, Comparing between pre and posttraining groups, differentially expressed protein coding genes were identified. To interpret the functional significance of the DE results, a comprehensive GS analysis approach featuring multiple algorithms was used to enrich gene ontology (GO) terms and KEGG pathways. The GS analysis revealed enriched themes such as energy metabolism, cell proliferation/growth/survival, muscle adaptations, and cytokine–cytokine interaction, all of which have been previously proposed as HIIT responses. Moreover, related cell signaling pathways were also measured. Specifically, G‐protein‐mediated signal transduction, phosphatidylinositide 3‐kinases (PI3K) – protein kinase B (PKB) and Janus kinase (JAK) – Signal Transducer and Activator of Transcription (STAT) signaling cascades were over‐represented. Additionally, the RNA‐Seq analysis also identified several HIIT‐responsive microRNAs (miRNAs) that were involved in regulating hair follicle‐specific processes, such as miR‐99a. For the first time, this study demonstrated that both existing and new biomarkers like miRNA can be explored for HIIT using the transcriptomic responses exhibited by the hair follicle. We propose scalp hair follicle as a minimally invasive yet comprehensive biomarker discovery system to effectively characterize and monitor HIIT‐induced cellular and molecular responses. For the first time, this study demonstrated that both existing and new biomarkers like miRNA could be explored for HIIT using the transcriptomic responses exhibited by the hair follicle, providing a foundation for additional HIIT evaluation measures.
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Consisting of brief and intense exercise intervals, HIIT requires less time commitment yet is able to produce the consistent targeted physical adaptations as conventional endurance training. To effectively characterize and monitor HIIT‐induced cellular and molecular responses, a highly accessible yet comprehensive biomarker discovery source is desirable. Both gene differential expression (DE) and gene set (GS) analyses were conducted using hair follicle transcriptome established from pre and postexercise subjects upon a 10‐day HIIT program by RNA‐Seq, Comparing between pre and posttraining groups, differentially expressed protein coding genes were identified. To interpret the functional significance of the DE results, a comprehensive GS analysis approach featuring multiple algorithms was used to enrich gene ontology (GO) terms and KEGG pathways. The GS analysis revealed enriched themes such as energy metabolism, cell proliferation/growth/survival, muscle adaptations, and cytokine–cytokine interaction, all of which have been previously proposed as HIIT responses. Moreover, related cell signaling pathways were also measured. Specifically, G‐protein‐mediated signal transduction, phosphatidylinositide 3‐kinases (PI3K) – protein kinase B (PKB) and Janus kinase (JAK) – Signal Transducer and Activator of Transcription (STAT) signaling cascades were over‐represented. Additionally, the RNA‐Seq analysis also identified several HIIT‐responsive microRNAs (miRNAs) that were involved in regulating hair follicle‐specific processes, such as miR‐99a. For the first time, this study demonstrated that both existing and new biomarkers like miRNA can be explored for HIIT using the transcriptomic responses exhibited by the hair follicle. 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Consisting of brief and intense exercise intervals, HIIT requires less time commitment yet is able to produce the consistent targeted physical adaptations as conventional endurance training. To effectively characterize and monitor HIIT‐induced cellular and molecular responses, a highly accessible yet comprehensive biomarker discovery source is desirable. Both gene differential expression (DE) and gene set (GS) analyses were conducted using hair follicle transcriptome established from pre and postexercise subjects upon a 10‐day HIIT program by RNA‐Seq, Comparing between pre and posttraining groups, differentially expressed protein coding genes were identified. To interpret the functional significance of the DE results, a comprehensive GS analysis approach featuring multiple algorithms was used to enrich gene ontology (GO) terms and KEGG pathways. The GS analysis revealed enriched themes such as energy metabolism, cell proliferation/growth/survival, muscle adaptations, and cytokine–cytokine interaction, all of which have been previously proposed as HIIT responses. Moreover, related cell signaling pathways were also measured. Specifically, G‐protein‐mediated signal transduction, phosphatidylinositide 3‐kinases (PI3K) – protein kinase B (PKB) and Janus kinase (JAK) – Signal Transducer and Activator of Transcription (STAT) signaling cascades were over‐represented. Additionally, the RNA‐Seq analysis also identified several HIIT‐responsive microRNAs (miRNAs) that were involved in regulating hair follicle‐specific processes, such as miR‐99a. For the first time, this study demonstrated that both existing and new biomarkers like miRNA can be explored for HIIT using the transcriptomic responses exhibited by the hair follicle. We propose scalp hair follicle as a minimally invasive yet comprehensive biomarker discovery system to effectively characterize and monitor HIIT‐induced cellular and molecular responses. For the first time, this study demonstrated that both existing and new biomarkers like miRNA could be explored for HIIT using the transcriptomic responses exhibited by the hair follicle, providing a foundation for additional HIIT evaluation measures.</abstract><cop>United States</cop><pub>John Wiley &amp; Sons, Inc</pub><pmid>29212859</pmid><doi>10.14814/phy2.13534</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record>
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subjects 1-Phosphatidylinositol 3-kinase
Adaptation
Adaptation, Physiological
Adult
AKT protein
Biomarkers - metabolism
Cell proliferation
Cell survival
Cytokines
Endurance training
Energy metabolism
Gene expression
Gene Expression Profiling - methods
Hair
Hair Follicle - metabolism
High-Intensity Interval Training
Humans
Janus kinase
Janus Kinases - genetics
Janus Kinases - metabolism
Kinases
Male
miRNA
Molecular Diagnostic Techniques - methods
muscle contraction
Original Research
Phosphatidylinositol 3-Kinases - genetics
Phosphatidylinositol 3-Kinases - metabolism
Physical fitness
Physical training
Physiology
Proteins
Proto-Oncogene Proteins c-akt - genetics
Proto-Oncogene Proteins c-akt - metabolism
Receptors, G-Protein-Coupled - genetics
Receptors, G-Protein-Coupled - metabolism
RNA‐Seq
Signal Transduction
STAT Transcription Factors - genetics
STAT Transcription Factors - metabolism
Transcription
Transcriptome
title Human hair follicle transcriptome profiling: a minimally invasive tool to assess molecular adaptations upon low‐volume, high‐intensity interval training
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