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. 2016 May 29;594(17):5009–5023. doi: 10.1113/JP272177

Evidence of a broad histamine footprint on the human exercise transcriptome

Steven A Romero 1, Austin D Hocker 1, Joshua E Mangum 1, Meredith J Luttrell 1, Douglas W Turnbull 2, Adam J Struck 3, Matthew R Ely 1, Dylan C Sieck 1, Hans C Dreyer 1, John R Halliwill 1,✉
PMCID: PMC5009782  PMID: 27061420

Abstract

Key points

  • Histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors, in a variety of pathways that probably predate its more recent role in innate and adaptive immunity.

  • Although histamine is normally associated with pathological conditions or allergic and anaphylactic reactions, it may contribute beneficially to the normal changes that occur within skeletal muscle during the recovery from exercise.

  • We show that the human response to exercise includes an altered expression of thousands of protein‐coding genes, and much of this response appears to be driven by histamine.

  • Histamine may be an important molecular transducer contributing to many of the adaptations that accompany chronic exercise training.

Abstract

Histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors. In humans, aerobic exercise is followed by a post‐exercise activation of histamine H1 and H2 receptors localized to the previously exercised muscle. This could trigger a broad range of cellular adaptations in response to exercise. Thus, we exploited RNA sequencing to explore the effects of H1 and H2 receptor blockade on the exercise transcriptome in human skeletal muscle tissue harvested from the vastus lateralis. We found that exercise exerts a profound influence on the human transcriptome, causing the differential expression of more than 3000 protein‐coding genes. The influence of histamine blockade post‐exercise was notable for 795 genes that were differentially expressed between the control and blockade condition, which represents >25% of the number responding to exercise. The broad histamine footprint on the human exercise transcriptome crosses many cellular functions, including inflammation, vascular function, metabolism, and cellular maintenance.

Key points

  • Histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors, in a variety of pathways that probably predate its more recent role in innate and adaptive immunity.

  • Although histamine is normally associated with pathological conditions or allergic and anaphylactic reactions, it may contribute beneficially to the normal changes that occur within skeletal muscle during the recovery from exercise.

  • We show that the human response to exercise includes an altered expression of thousands of protein‐coding genes, and much of this response appears to be driven by histamine.

  • Histamine may be an important molecular transducer contributing to many of the adaptations that accompany chronic exercise training.

Abbreviations

CCL2

chemokine (c‐c motif) ligand 2

FGF2

fibroblast growth factor 2

HDC

histidine decarboxylase

HIF1A

hypoxia inducible factor 1α subunit

IL1RL1

interleukin 1 receptor‐like 1

IL‐6

interleukin 6

KDR

kinase insert domain receptor

KEGG

Kyoto encyclopedia of genes and genomes

MMP2

matrix metallopeptidase 2

NOD

nucleotide‐binding oligomerization domain

NOS3

nitric oxide synthase 3

NR4A1

nuclear receptor subfamily 4, group a, member 1

OTUD1

ovarian tumour deubiquitinase

PPARGC1A

peroxisome proliferator‐activated receptor γ, coactivator 1α

SLC2A3

solute carrier family 2 member 3

THBS1

thrombospondin 1

VEGF

vascular endothelial growth factor

Introduction

Histamine is a primordial signalling molecule. The existence of histamine as a signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors, appears to predate the origins of multicellular organisms (Csaba, 2012). As evidence, the ciliated protozoa Tehrahymena and mammals both express the same gene for histidine decarboxylase (HDC; the enzyme that produces histamine), and there is a high degree of conservation in the genetic sequence between humans and Tetrahymena (Hegyesi et al. 1999). This suggests that histaminergic signalling evolved prior to multicellular organisms, although after the divergence of eukaryotes from prokaryotes. Mast cells, with their characteristic histamine‐containing vesicles, arose later than histaminergic signalling, although they are probably more than 500 million years old, predating the chordates (Reite, 1965). Mast cells have been found in all vertebrate species (Crivellato & Ribatti, 2010). To date, a human lacking mast cells has never been documented (Wong et al. 2014). Histamine and histamine receptors predate the development of innate and adaptive immunity and, in Tetrahymena, histamine can stimulate a variety of cell functions, including phagocytosis, chemosensory behaviour, glucose uptake and cell division (Hegyesi et al. 1999), working through H1 and H2‐receptors (Csaba, 2012).

In mammalian species including humans, the potential of histamine to promote the growth of new blood vessels (angiogenesis) via up‐regulation of pro‐angiogenic signals, including vascular endothelial growth factor (VEGF), is widely recognized in the setting of wound healing, tumour growth and pregnancy (Sörbo et al. 1994; Ohtsu & Watanabe, 2003; Jensen et al. 2010; Francis et al. 2011). In other contexts, histamine receptor activation has been shown to up‐regulate genes associated with improved cardiovascular health, such as endothelial nitric oxide synthase (Li et al. 2003). These beneficial roles of histamine provide an interesting contrast to the deleterious roles of histamine typically associated with allergic and anaphylactic reactions, which are evolutionary newcomers.

In our studies in humans on the recovery of the cardiovascular system following aerobic exercise, we noted a prolonged relaxation of the blood vessels that carry blood to those skeletal muscle groups used during exercise. This post‐exercise vasodilatation lasts upwards of several hours after the end of exercise (Halliwill et al. 2013). Studies over the last decade have determined that localized activation of histamine H1 and H2 receptors is the primary cause of this sustained post‐exercise vasodilatation because administration of H1 and H2 receptor antagonists such as fexofenadine or ranitidine abolishes the response (Lockwood et al. 2005; McCord et al. 2006; McCord & Halliwill, 2006; Barrett‐O'Keefe et al. 2013). We have recently shown that this vasodilatation improves the availability of glucose to previously exercised muscle (Pellinger et al. 2010) and improves post‐exercise glucose uptake in some individuals (Emhoff et al. 2011), as well as insulin‐sensitivity (Pellinger et al. 2013). Thus, there are several lines of evidence demonstrating that, in humans and other mammals (Niijima‐Yaoita et al. 2012), histamine receptor activation is induced by exercise, and that mechanisms exist by which this could contribute to the long‐term beneficial adaptations associated with exercise training.

Thus, using a targeted approach, the initial goal of the present study was to determine whether the exercise‐induced activation of histamine H1 and H2 receptors contributes to the expression of pro‐angiogenic factors in humans undergoing a single 1 h session of aerobic exercise. We exploited RNA sequencing to pursue this primary goal, which also enabled us to explore the broader effects of H1 and H2 receptor blockade on the exercise transcriptome in humans using an agnostic approach. Samples obtained by percutaneous biopsy of the vastus lateralis muscle in humans at the end of a single session of leg exercise and at 3 h into recovery from exercise were compared with pre‐exercise samples under two conditions: (i) a control condition where subjects exercised without pharmacological intervention and (ii) a blockade condition where subjects exercised after oral administration of combined histamine H1/H2 receptor antagonism.

Methods

The present study was approved by the Institutional Review Board at the University of Oregon and was performed in accordance to the principles outlined by the Declaration of Helsinki. Sixteen healthy subjects (10 men and six women) participated in this study after written informed consent. No subjects were using over‐the‐counter or prescription medications at the time of the study, with the exception of oral contraceptives. Subjects were classified as recreationally active based on self‐reported physical activity levels in two standard physical activity questionnaires (Baecke et al. 1982; Kohl et al. 1988) and based on studies conducted previously in our laboratory comparing sustained post‐exercise vasodilatation in untrained and trained subjects (McCord & Halliwill, 2006). A screening visit was used to determine peak power output during a unilateral dynamic knee extension exercise test performed to volitional fatigue. Dynamic knee‐extension exercise was performed using a custom‐built knee extension ergometer as described previously (Barrett‐O'Keefe et al. 2013). Following the screening visit, subjects were randomly assigned to control or histamine receptor blockade conditions for the study. All subjects were required to abstain from caffeine, alcohol and exercise for 24 h prior to the study. Additionally, subjects reported to the laboratory 2 h postprandial. All subjects performed 60 min of unilateral dynamic knee extension exercise at 60% of peak power and a cadence of 45 kicks min−1. Power was ramped at the onset of exercise to 60% peak power over the first 5 min. Power output was recorded continuously throughout 60 min dynamic knee extension exercise. Skeletal muscle tissue was obtained via biopsy of the vastus lateralis before (Pre), immediately after (0 h Post) and 3 h after (3 h Post) dynamic knee extension exercise. Haemodynamic measurements were made prior to exercise and every 30 min throughout the 3 h recovery period. Room temperature remained thermoneutral (∼23°C) throughout the study.

Histamine receptor blockade

Histamine H1 and H2 receptors were blocked using 540 mg of fexofenadine and 300 mg of ranitidine. This combination of fexofenadine and ranitidine reduces sustained post‐exercise vasodilatation by ∼ 90% following unilateral dynamic knee extension exercise (Barrett‐O'Keefe et al. 2013). This dosage of oral fexofenadine has been shown to selectively block H1 receptors (a time to peak concentration of 1.15 h and a half‐life of 12 h), whereas the dose of oral ranitidine has been shown to selectively block H2 receptors (a time to peak plasma concentration of 2.2 h and a half‐life of 2.6 h) (Garg et al. 1985; Russell et al. 1998). Responses are inhibited by 90% within 1 h and remain inhibited 6 h after administration (Garg et al. 1985; Brunton et al. 2011). Fexofenadine and ranitidine do not appear to cross into the central nervous system or possess sedative actions (Brunton et al. 2011). Furthermore, these drugs do not have any direct cardiovascular effects in the absence of histamine receptor stimulation (i.e. when given under normal resting conditions, these drugs do not elicit any changes in heart rate, blood pressure or smooth muscle tone) (Lockwood et al. 2005; McCord et al. 2006; McCord & Halliwill, 2006; Barrett‐O'Keefe et al. 2013). Subjects ingested the histamine receptor antagonists with water 1 h prior to exercise.

Haemodynamic measurements

Haemodynamic measurements were made pre‐ and post‐exercise with the subjects in the supine position. Arterial blood pressure was measured in the right arm using an automated sphygmomanometer (Tango+; SunTech Medical, Raleigh, NC, USA). Heart rate was monitored using a three lead electrocardiograph (Tango+). Heart rate and blood pressure were also measured during 60 min of dynamic knee extension exercise. Femoral artery blood flow was measured with a linear‐array ultrasound transducer (9 MHz; iE33; Phillips, Andover, MA, USA) using standard methods for quantification (Buck et al. 2014; Romero et al. 2015). Femoral vascular conductance (ml min−1 mmHg−1) was calculated by dividing femoral blood flow by mean arterial pressures.

Skeletal muscle biopsy

All skeletal muscle biopsies were performed in the vastus lateralis under sterile technique. The skin and underlying fascia were anaesthetized using 1% lidocaine HCL (Hospira Worldwide, Lake Forest, IL, USA). Skeletal muscle was obtained at a depth of ∼2–3 cm using a 5 mm Bergström biopsy needle inserted through a small incision made in the skin and muscle fascia. Harvested skeletal muscle tissue was blotted, removed of any adipose tissue, and snap frozen in isopentane cooled with liquid nitrogen and stored at –80°C until analysis. Pre‐exercise biopsies were performed in the non‐exercised leg, whereas both post‐exercise biopsies were performed in the previously exercised leg. Post‐exercise tissue was harvested from the same incision site. However, care was taken to angle the Bergström needle such that the tissue was harvested from a distal site for the first sample and a proximal site for the second sample.

Gene expression

We utilized RNA sequencing (performed at the University of Oregon Genomics Core Facility) to probe gene expression on a transcriptome‐wide level (Wang et al. 2009), obtaining a comprehensive index of all of the transcripts related to acute exercise and histamine receptor activation. Although samples obtained using the percutaneous biopsy approach are blotted and cleared of adipose tissue, other components of skeletal muscle tissue (e.g. connective tissue, myocytes, adipocytes, fibroblasts, pericytes, vascular smooth muscle cells, endothelial cells, etc.) remain intact. Thus, our transcriptome‐wide analysis is inclusive of all cell types in the harvested sample of skeletal muscle tissue and does not differentiate between cell types.

Skeletal muscle tissue (∼15 mg) was homogenized in Eppendorf RNase‐free tubes containing 1 ml of TRI reagent, separated using 0.2 ml of chloroform and precipitated with 0.5 ml of isopropanol. The resulting RNA pellet was washed twice in 75% alcohol, dried and dissolved in 1.5 μl 0.1 mm EDTA per 1 mg of initial skeletal muscle tissue. An isolation procedure was used to ensure that the sample was not contaminated with non‐polyadenylated mRNA (e.g. ribosomal). Pure mRNA was isolated from the total RNA preparation using a commercially available kit (Dynabeads® mRNA Purification Kit; Life Technologies, Eugene, OR, USA). Input RNA yield and integrity were analysed prior to library construction via automated capillary electrophoresis (Fragment Analyser; Advanced Analytical Technologies, Inc., Ames, IA, USA) coupled with a High Sensitivity RNA Analysis Kit (DNF‐491; Advanced Analytical Technologies, Inc.). Illumina sequencing libraries were made from purified mRNA samples using a commercially available kit (KAPA Stranded RNA‐Seq Library Preparation Kit; Kapa Biosystems, Boston, MA, USA). Constructed libraries were validated using the High Sensitivity NGS Fragment Analysis Kit (DNF‐486; Advanced Analytical Technologies, Inc.) and quantitated using a Qubit 2.0 fluorometer coupled with a High Sensitivity DNA assay kit (Life Technologies). RNA‐seq libraries were sequenced with an Illumina HiSeq 2500 sequencer (Illumina, San Diego CA, USA) using high output single‐read flowcells at a read length of 100 nucleotides. Raw fastq data files were aligned to the human reference genome from ENSEMBL (http://www.ensembl.org) using STAR aligner 2.4.0i following adapter sequence removal (Dobin et al. 2013).

Statistical analysis

Select genes of interest that are associated with histamine receptor activation, exercise and angiogenesis were identified a priori and are shown in Table 1. Transcripts for these genes were explored using a traditional hypothesis‐driven approach. Preliminary statistical analysis indicated that our primary haemodynamic outcome variables did not vary by sex. As such, all subsequent analyses were performed after grouping data for both men and women. Primary haemodynamic outcome variables and expression of a priori genes of interest were analysed using a two‐way mixed model analysis of variance with repeated measures and a priori contrasts to examine specific condition‐time interactions (JMP Pro 10; SAS Institute Inc. Cary, NC, USA). P < 0.05 was considered statistically significant. Data are reported as the mean ± SEM, unless otherwise indicated.

Table 1.

Select genes of interest

EntrezID Symbol Name
3067 HDC Histidine decarboxylase
3164 NR4A1 Nuclear receptor subfamily 4, group a, member 1
3091 HIF1A Hypoxia inducible factor 1α subunit
10891 PPARGC1A Peroxisome proliferator‐activated receptor γ, coactivator 1α
6347 CCL2 CCL2 chemokine (c‐c motif) ligand 2
7057 THBS1 Thrombospondin 1
4313 MMP2 Matrix metallopeptidase 2
2247 FGF2 Fibroblast growth factor 2 (basic)
4846 NOS3 Nitric oxide synthase 3 (endothelial cell)
7422 VEGFA Vascular endothelial growth factor A
3791 KDR Kinase insert domain receptor
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The 11 protein‐coding genes were identified a priori for hypothesis testing. EntrezID: Entrez gene identification number; Symbol: HGNC unique symbol; Name: Gene name.

A transcriptome‐wide bioinformatics approach was used to ‘cast a wide net’ and investigate relationships not limited to our hypothesis. The initial step in the transcriptome‐wide analysis was to identify differentially expressed protein‐coding genes using Bioconductor R package DESeq2, version 1.6.3 (Love et al. 2014). In brief, the Wald test for significance of the generalized linear model coefficients was used to test for differential expression between each post‐exercise time point and pre‐exercise, as well as between control and blockade groups at each time point, with the criteria for differential expression of P < 0.10 applied to the Benjamini–Hockberg adjusted P‐value. Further analysis of the genes that were differentially expressed with histamine blockade at 3 h postexercise included over‐representation analysis conducted in DAVID, version 6.7 (Huang et al. 2009 a, 2009 b), restricted to Gene Ontology molecular function and pathways included in the Kyoto encyclopedia of genes and genomes (KEGG), Panther and Reactome databases (Kaneshia & Goto, 2000; Mi & Thomas, 2009; Fabregat et al. 2015; Kanehisa et al. 2016; Mi et al. 2016).

Study data

Both the original sequence data and counts for protein‐coding genes for this study have been deposited in the NCBI Gene Expression Omnibus website (GEO, http://www.ncbi.nlm.nih.gov/geo) and are accessible through GEO Series accession number GSE71972. In addition, lists of the protein‐coding genes that were differentially expressed in the present study are available in the Supporting information.

Results

Subject physical characteristics and data obtained during the screening visit are shown in Table 2. Subject characteristics are similar to those obtained previously in our laboratory in young healthy subjects and are consistent with recreationally active individuals. Power output during steady state dynamic knee extension exercise did not differ between control (17.1 ± 1.4 W) and H1/H2 blockade conditions (21.6 ± 2.9 W; P = 0.17). Power output for each condition was within 1 W of the estimated 60% workload for the control condition (17.7 W) and the H1/H2 blockade condition (22.2 W). The percentage change in femoral blood flow from pre‐exercise to 60 min of exercise recovery was greater for the control condition (Δ 19.6 ± 7.9%) compared to the H1/H2 blockade condition (Δ –4.4 ± 3.4%; P < 0.05). Similarly, the percentage change in femoral vascular conductance from pre‐exercise to 60 min of exercise recovery was greater for the control condition (Δ 22.2 ± 8.4%) compared to the H1/H2 blockade condition (Δ −3.5 ± 4.1%; P < 0.05), which is consistent with prior studies using this model (Barrett‐O'Keefe et al. 2013).

Table 2.

Subject characteristics

Control H1/H2 blockade
Number 8 8
Age (years) 23.0 ± 4.4 24.5 ± 5.4
Height (cm) 169 ± 9 175 ± 4
Weight (kg) 68.1 ± 10.1 75.9 ± 6.3
Body mass index (kg m⁻2) 23.7 ± 2.0 24.7 ± 1.9
Baecke sport index (arbitrary units) 3.4 ± 0.8 2.8 ± 0.9
Physical activity index (MET h⁻1 week⁻1) 49 ± 22 38 ± 25
Peak power output (W) 29.4 ± 7.1 38.4 ± 10.8
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Subjects were young healthy and sedentary to recreationally active. There were no differences between control and blockade. Values are the mean ± SD. MET, metabolic equivalents.

Hypothesis‐driven tests for genes of interest (targeted approach)

As shown in Fig. 1, expression of HDC mRNA was increased at 3 h post‐exercise (P < 0.05) and was unaffected by blockade (P = 0.70). The average fold‐increase was 2.60 ± 0.50 from pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.99 for interaction). The results of our select genes of interest reported herein are grouped according to their mechanistic role in promoting angiogenesis (i.e. transcription factors, growth factors, endothelial factors).

Figure 1. Histidine decarboxylase expression .

Figure 1

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Expression of mRNA for HDC in samples obtained before exercise (Pre), immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post), shown as raw counts (left) and the fold‐change relative to Pre (right). Yellow bars denote the control condition; green bars denote the blockade condition. * P < 0.05 vs. Pre. Data are the mean ± SE.

Transcription factors

Figure 2 shows the expression of mRNA for the transcription factors nuclear receptor subfamily 4, group a, member 1 (NR4A1), hypoxia inducible factor 1α subunit (HIF1A) and peroxisome proliferator‐activated receptor γ (PPARGC1A). NR4A1 expression was increased after exercise (P < 0.05), without differences between end‐exercise and 3 h post‐exercise (P = 0.56), and was unaffected by blockade (P = 0.86). The average fold‐increase was 8.63 ± 0.83 from pre‐exercise (P < 0.05) and was unaffected by blockade (P = 0.17 for interaction). HIF1A expression was increased at 3 h post‐exercise (P < 0.05) and was unaffected by blockade (P = 0.18). At 3 h post‐exercise, expression was 2.22 ± 0.25‐fold higher than pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.19 for interaction). PPARGC1A expression was increased at 3 h post‐exercise (P < 0.05) and was unaffected by blockade (P = 0.95). At 3 h post‐exercise, expression was 11.63 ± 1.87‐fold higher than pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.80 for interaction).

Figure 2. Transcription factor expression .

Figure 2

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Expression of mRNA for the transcription factors NR4A1, HIF1A and PPARGC1A in samples obtained before exercise (Pre), immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post), shown as raw counts (left) and the fold‐change relative to Pre (right). Yellow bars denote the control condition; green bars denote the blockade condition. * P < 0.05 vs. Pre. Data are the mean ± SE.

Growth factors

Figure 3 shows the expression of mRNA for the growth factors chemokine (c‐c motif) ligand 2 (CCL2), thrombospondin 1 (THBS1), matrix metallopeptidase 2 (MMP2) and fibroblast growth factor 2 (FGF2). CCL2 expression was increased at 3 h post‐exercise (P < 0.05) with a trend for attenuation by blockade (P = 0.07 for interaction). At 3 h post‐exercise, expression was 44.52 ± 16.13‐fold higher than pre‐exercise levels (P < 0.05) with a trend for attenuation by blockade (P = 0.14 for interaction). THBS1 expression was increased at 3 h post‐exercise (P < 0.05), although the rise was attenuated by blockade (P < 0.05 for interaction). At 3 h post‐exercise, expression was 57.84 ± 15.78‐fold higher than pre‐exercise levels under control conditions (P < 0.05). The rise was attenuated by blockade (P < 0.05 vs. control) and was not higher than pre‐exercise (16.30 ± 8.05‐fold; P = 0.10 blockade vs. pre‐exercise). MMP2 expression tended to increase early and decrease late after exercise (P = 0.09) and was unaffected by blockade (P = 0.91). FGF2 expression was increased at 3 h post‐exercise (P < 0.05), although the rise was attenuated by blockade (P = 0.06 for interaction). At the end of exercise, expression was not elevated under control conditions (P = 0.89) but was elevated 1.71 ± 0.27‐fold under the blockade condition (P < 0.05 vs. control; P < 0.05 vs. pre‐exercise). At 3 h post‐exercise, expression was 1.61 ± 0.20‐fold higher than pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.85).

Figure 3. Growth factor expression .

Figure 3

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Expression of mRNA for the growth factors CCL2, THBS1, MMP2 and FGF2 in samples obtained before exercise (Pre), immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post), shown as raw counts (left) and the fold‐change relative to Pre (right). Yellow bars denote the control condition; green bars denote the blockade condition. * P < 0.05 vs. Pre. † P < 0.05 vs. control. Data are the mean ± SE.

Endothelium‐related factors

Figure 4 shows the expression of mRNA for the endothelium‐related factors nitric oxide synthase 3 (NOS3), VEGFA and kinase insert domain receptor (KDR). NOS3 expression was increased at 3 h post‐exercise (P < 0.05), although the rise was attenuated by blockade (P < 0.05 for interaction). At 3 h post‐exercise, expression was 4.93 ± 1.20‐fold higher than pre‐exercise levels under control conditions (P < 0.05). The rise was reduced to 2.80 ± 0.58‐fold (P < 0.05 vs. control) but was still higher than pre‐exercise (P < 0.05 vs. pre‐exercise). VEGFA expression was increased after exercise (P < 0.05), with 3 h post‐exercise being greater than end‐exercise (P < 0.05), and was unaffected by blockade (P = 0.61). At 3 h post‐exercise, expression was 3.62 ± 0.57‐fold higher than pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.73 for interaction). KDR expression was increased at 3 h post‐exercise (P < 0.05) and was unaffected by blockade (P = 0.28). At 3 h post‐exercise, expression was 2.92 ± 0.26‐fold higher than pre‐exercise levels (P < 0.05) and was unaffected by blockade (P = 0.66 for interaction).

Figure 4. Endothelium‐related factor expression .

Figure 4

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Expression of mRNA for the endothelium‐related factors NOS3, VEGFA and KDR in samples obtained before exercise (Pre), immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post), shown as raw counts (left) and the fold‐change relative to Pre (right). Yellow bars denote the control condition; green bars denote the blockade condition. * P < 0.05 vs. Pre. † P < 0.05 vs. control. Data are the mean ± SE.

Hypothesis‐generation (agnostic approach)

At 3 h post‐exercise, more than 3000 protein‐coding genes were differentially expressed compared to pre‐exercise under control conditions (Fig. 5 A). Of these, two‐thirds were up‐regulated and one‐third were down‐regulated (see Supporting information, Tables S1 and S2). However, these responses were markedly reduced when histamine H1/H2 receptors were blocked, in that only ∼1000 genes were differentially expressed following exercise under blockade conditions (see Supporting information, Tables S3 and S4). Of the many genes affected by blockade, a few (n = 99) were expressed at a higher level, whereas the majority (n = 696) were expressed at lower levels with blockade. Of those that were expressed more with blockade, 44 represent the up‐regulation of genes that were not elevated by exercise alone and 55 represent genes that went down less in response to exercise in the blockade vs. control condition. Of the large number that were expressed less with blockade, most (n = 563) represent genes that went up less in response to exercise with blockade than with control and some (n = 127) represent genes that went down in response to exercise with blockade but had not with control. A few changed from going up to going down (n = 5) with blockade compared to control, and one represents a gene that went down in response to exercise and blockade but had not been altered by exercise in control conditions.

Figure 5. Effect of histamine receptor blockade on differentially expressed protein‐coding genes after exercise .

Figure 5

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A, the number of genes that were up‐ or down‐regulated under each condition immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post). Yellow bars denote the number of genes up‐regulated or down‐regulated in control condition relative to pre‐exercise; green bars denote the blockade condition relative to pre‐exercise; grey bars denote the differentially expressed genes in the blockade condition relative to control condition at the same time point. B, differential expression level (log2 fold) in control condition vs. blockade condition at 3 h post‐exercise. Grey symbols denote genes that were differentially expressed relative to pre‐exercise in both control and blockade conditions; yellow symbols denote genes that were differentially expressed relative to pre‐exercise in only the control condition; green symbols denote genes that were differentially expressed relative to pre‐exercise in only the blockade condition; black edges denote genes that were differentially expressed between the control and blockade conditions. C, expression of mRNA for IL‐6, SLC2A3, IL1RL1 and OTUD1 in samples obtained before exercise (Pre), immediately after exercise (0 h Post) and at 3 h post‐exercise (3 h Post), shown as raw counts (left) and the fold‐change relative to Pre (right). Yellow bars denote the control condition; green bars the denote blockade condition. * P < 0.05 vs. Pre. † P < 0.05 vs. control. Data are the mean ± SE.

Histamine receptor blockade had no effect prior to exercise, and minimal influence at 0‐h post‐exercise on gene expression (see Supporting information, Table S5). By contrast, the influence of histamine receptor blockade at 3 h post‐exercise was notable for 795 genes that were differentially expressed between the control and blockade conditions (see Supporting information, Table S6), which represents >25% of the number responding to exercise. Of those genes affected by blockade, the majority (88%) were expressed at lower levels with blockade. There was substantial (83%) overlap of the histamine receptor footprint on the exercise transcriptome (Fig. 5 B). The top four genes showing the largest influence of histamine blockade hint at a variety of important cell functions, including paracrine signalling [e.g. interleukin 6 (IL‐6) and interleukin 1 receptor‐like 1 (IL1RL1)], metabolism [e.g. solute carrier family 2 member 3 (SLC2A3), a facilitated glucose transporter] and cellular maintenance (e.g. OTU deubiquitinase; OTUD1) (Fig. 5 C). The top fifty genes showing influence of histamine blockade (excerpted from the Supporting information, Table S6) are shown in Table 3.

Table 3.

Difference between blockade and control at 3 h post‐exercise

Entrez ID Symbol Name Log2 fold
3569 IL‐6 Interleukin 6 [Source:HGNC Symbol;Acc:HGNC:6018] −1.5
6515 SLC2A3 Solute carrier family 2 (facilitated glucose transporter) member 3 [Source:HGNC Symbol;Acc:HGNC:11007] −1.5
9173 IL1RL1 Interleukin 1 receptor‐like 1 [Source:HGNC Symbol;Acc:HGNC:5998] −1.4
220213 OTUD1 OTU deubiquitinase 1 [Source:HGNC Symbol;Acc:HGNC:27346] −1.4
23135 KDM6B Lysine (K)‐specific demethylase 6B [Source:HGNC Symbol;Acc:HGNC:29012] −1.4
1839 HBEGF heparin‐binding EGF‐like Growth factor [Source:HGNC Symbol;Acc:HGNC:3059] −1.4
54206 ERRFI1 ERBB receptor feedback inhibitor 1 [Source:HGNC Symbol;Acc:HGNC:18185] −1.4
6401 SELE Selectin E [Source:HGNC Symbol;Acc:HGNC:10718] −1.4
5743 PTGS2 Prostaglandin‐endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase) [Source:HGNC Symbol;Acc:HGNC:9605] −1.4
4616 GADD45B Growth arrest and DNA‐damage‐inducible β [Source:HGNC Symbol;Acc:HGNC:4096] −1.4
9052 GPRC5A G protein‐coupled receptor class C group 5 member A [Source:HGNC Symbol;Acc:HGNC:9836] −1.4
6279 S100A8 S100 calcium binding protein A8 [Source:HGNC Symbol;Acc:HGNC:10498] −1.4
3383 ICAM1 Intercellular adhesion molecule 1 [Source:HGNC Symbol;Acc:HGNC:5344] −1.4
30817 EMR2 egf‐like module containing mucin‐like hormone receptor‐like 2 [Source:HGNC Symbol;Acc:HGNC:3337] −1.4
9308 CD83 CD83 molecule [Source:HGNC Symbol;Acc:HGNC:1703] −1.4
1441 CSF3R Colony stimulating factor 3 receptor (granulocyte) [Source:HGNC Symbol;Acc:HGNC:2439] −1.3
1439 CSF2RB Colony stimulating factor 2 receptor β low‐affinity (granulocyte‐macrophage) [Source:HGNC Symbol;Acc:HGNC:2436] −1.3
2627 GATA6 GATA binding protein 6 [Source:HGNC Symbol;Acc:HGNC:4174] −1.3
2920 CXCL2 Chemokine (C‐X‐C motif) ligand 2 [Source:HGNC Symbol;Acc:HGNC:4603] −1.3
55740 ENAH Enabled homolog (Drosophila) [Source:HGNC Symbol;Acc:HGNC:18271] −1.3
2354 FOSB FBJ murine osteosarcoma viral oncogene homolog B [Source:HGNC Symbol;Acc:HGNC:3797] −1.3
6781 STC1 Stanniocalcin 1 [Source:HGNC Symbol;Acc:HGNC:11373] −1.3
4332 MNDA Myeloid cell nuclear differentiation antigen [Source:HGNC Symbol;Acc:HGNC:7183] −1.3
688 KLF5 Kruppel‐like factor 5 (intestinal) [Source:HGNC Symbol;Acc:HGNC:6349] −1.3
166929 SGMS2 Sphingomyelin synthase 2 [Source:HGNC Symbol;Acc:HGNC:28395] −1.3
728 C5AR1 Complement component 5a receptor 1 [Source:HGNC Symbol;Acc:HGNC:1338] −1.3
64386 MMP25 Matrix metallopeptidase 25 [Source:HGNC Symbol;Acc:HGNC:14246] −1.3
5430 POLR2A Polymerase (RNA) II (DNA directed) polypeptide A 220 kDa [Source:HGNC Symbol;Acc:HGNC:9187] −1.3
6556 SLC11A1 Solute carrier family 11 (proton‐coupled divalent metal ion transporter) member 1 [Source:HGNC Symbol;Acc:HGNC:10907] −1.3
6813 STXBP2 Syntaxin binding protein 2 [Source:HGNC Symbol;Acc:HGNC:11445] −1.3
7056 THBD Thrombomodulin [Source:HGNC Symbol;Acc:HGNC:11784] −1.3
80183 KIAA0226L KIAA0226‐like [Source:HGNC Symbol;Acc:HGNC:20420] −1.3
7850 IL1R2 Interleukin 1 receptor type II [Source:HGNC Symbol;Acc:HGNC:5994] −1.3
221079 ARL5B ADP‐ribosylation factor‐like 5B [Source:HGNC Symbol;Acc:HGNC:23052] −1.3
84159 ARID5B AT rich interactive domain 5B (MRF1‐like) [Source:HGNC Symbol;Acc:HGNC:17362] −1.3
116844 LRG1 Leucine‐rich α‐2‐glycoprotein 1 [Source:HGNC Symbol;Acc:HGNC:29480] −1.3
6347 CCL2 Chemokine (C‐C motif) ligand 2 [Source:HGNC Symbol;Acc:HGNC:10618] −1.3
27289 RND1 Rho family GTPase 1 [Source:HGNC Symbol;Acc:HGNC:18314] −1.3
467 ATF3 Activating transcription factor 3 [Source:HGNC Symbol;Acc:HGNC:785] −1.3
6622 SNCA Synuclein α (non A4 component of amyloid precursor) [Source:HGNC Symbol;Acc:HGNC:11138] −1.3
6402 SELL selectin L [Source:HGNC Symbol;Acc:HGNC:10720] −1.3
54210 TREM1 Triggering receptor expressed on myeloid cells 1 [Source:HGNC Symbol;Acc:HGNC:17760] −1.2
7538 ZFP36 ZFP36 ring finger protein [Source:HGNC Symbol;Acc:HGNC:12862] −1.2
342510 CD300E CD300e molecule [Source:HGNC Symbol;Acc:HGNC:28874] −1.2
1844 DUSP2 Dual specificity phosphatase 2 [Source:HGNC Symbol;Acc:HGNC:3068] −1.2
597 BCL2A1 BCL2‐related protein A1 [Source:HGNC Symbol;Acc:HGNC:991] −1.2
8061 FOSL1 FOS‐like antigen 1 [Source:HGNC Symbol;Acc:HGNC:13718] −1.2
2919 CXCL1 Chemokine (C‐X‐C motif) ligand 1 (melanoma growth stimulating activity α) [Source:HGNC Symbol;Acc:HGNC:4602] −1.2
5023 P2RX1 Purinergic receptor P2X ligand gated ion channel 1 [Source:HGNC Symbol;Acc:HGNC:8533] −1.2
5329 PLAUR Plasminogen activator urokinase receptor [Source:HGNC Symbol;Acc:HGNC:9053] −1.2
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The top 50 of 795 differentially expressed protein‐coding genes are shown for H1/H2 blockade vs. control at 3 h post‐exercise. The table is excerpted from the Supporting information (Table S6) and sorted by a descending order of magnitude of change. EntrezID: Entrez gene identification number; Symbol: HGNC unique symbol; Name: Gene name; Log2 fold: Log2 fold change in expression relative to control group. All are P (adjusted) ≤ 0.001.

A Gene Ontology over‐expression analysis of the genes that were differentially expressed with histamine blockade at 3 h post‐exercise identified 33 molecular function categories (Table 4) that were influenced by histamine blockade. Furthermore, pathway over‐expression analysis identified 22 pathways (Table 5) that were influenced by histamine blockade. The top five KEGG pathways showing the largest influence of histamine blockade were cytokine–cytokine receptor interaction, the chemokine signalling pathway, the nucleotide‐binding oligomerization domain (NOD)‐like receptor signalling pathway, haematopoietic cell lineage, and the Toll‐like receptor signalling pathway.

Table 4.

Gene Ontology enrichment analysis for difference between blockade and control at 3 h post‐exercise

Molecular function category % genes involved Fold enrichment P (adjusted)
GO:0005515 protein binding 59.2 1.3 0.00
GO:0005102 receptor binding 9.7 1.9 0.00
GO:0004896 cytokine receptor activity 1.9 5.9 0.00
GO:0005125 cytokine activity 3.7 3.2 0.00
GO:0005488 binding 78.9 1.1 0.00
GO:0030247 polysaccharide binding 3.0 3.4 0.00
GO:0001871 pattern binding 3.0 3.4 0.00
GO:0008009 chemokine activity 1.5 5.7 0.00
GO:0042379 chemokine receptor binding 1.5 5.3 0.00
GO:0019838 growth factor binding 2.1 3.5 0.00
GO:0019955 cytokine binding 2.1 3.4 0.00
GO:0001664 G‐protein‐coupled receptor binding 2.1 3.3 0.00
GO:0005539 glycosaminoglycan binding 2.4 3.0 0.01
GO:0004908 interleukin‐1 receptor activity 0.6 15.5 0.01
GO:0008083 growth factor activity 2.5 2.7 0.01
GO:0005516 calmodulin binding 2.3 2.8 0.01
GO:0004871 signal transducer activity 17.4 1.3 0.02
GO:0060089 molecular transducer activity 17.4 1.3 0.02
GO:0005178 integrin binding 1.4 4.1 0.02
GO:0019899 enzyme binding 5.3 1.7 0.03
GO:0019966 interleukin‐1 binding 0.6 10.9 0.04
GO:0030246 carbohydrate binding 3.9 1.9 0.04
GO:0046625 sphingolipid binding 0.5 14.5 0.07
GO:0032403 protein complex binding 2.5 2.2 0.07
MF00005 cytokine receptor 1.9 4.2 0.00
MF00018 chemokine 1.4 5.2 0.00
MF00016 signalling molecule 7.3 1.7 0.00
MF00039 other transcription factor 4.0 2.1 0.01
MF00006 interleukin receptor 1.1 5.3 0.01
MF00001 receptor 11.4 1.4 0.05
MF00234 other cytokine 0.8 6.3 0.06
MF00017 cytokine 1.5 2.7 0.08
MF00093 select regulatory molecule 8.7 1.4 0.09
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The 795 differentially expressed protein‐coding genes for H1/H2 blockade vs. control at 3 h post‐exercise were mapped to 24 Gene Ontology molecular function categories and nine Panther molecular function categories. P (adjusted): Benjamini–Hockberg P‐value.

Table 5.

Gene Ontology enrichment analysis for difference between blockade and control at 3 h post‐exercise

Molecular function category % genes involved Fold enrichment P (adjusted)
hsa04060 Cytokine‐cytokine receptor interaction 5.3 2.9 0.00
hsa04062 Chemokine signalling pathway 4.0 3.1 0.00
hsa04621 NOD‐like receptor signalling pathway 1.9 4.3 0.00
hsa04640 Haematopoietic cell lineage 2.1 3.5 0.00
hsa04620 Toll‐like receptor signalling pathway 2.3 3.2 0.00
hsa04670 Leukocyte transendothelial migration 2.3 2.7 0.01
hsa04510 Focal adhesion 3.0 2.1 0.01
hsa04210 Apoptosis 1.8 2.9 0.02
hsa05120 Epithelial cell signalling in Helicobacter pylori infection 1.5 3.2 0.02
hsa04662 B cell receptor signalling pathway 1.5 2.9 0.04
hsa04010 MAPK signalling pathway 3.4 1.8 0.04
hsa04810 Regulation of actin cytoskeleton 2.9 1.9 0.04
hsa04610 Complement and coagulation cascades 1.4 2.9 0.05
hsa04630 Jak‐STAT signalling pathway 2.3 2.1 0.05
hsa04650 Natural killer cell mediated cytotoxicity 2.0 2.2 0.06
hsa05200 Pathways in cancer 3.8 1.6 0.07
REACT_604 Haemostasis 4.8 3.0 0.00
REACT_13552 Integrin cell surface interactions 2.3 4.2 0.00
REACT_6900 Signalling in immune system 3.9 2.0 0.00
P00031 Inflammation mediated by chemokine and cytokine signalling pathway 5.1 2.0 0.00
P00010 B cell activation 1.9 2.7 0.04
P00054 Toll receptor signalling pathway 1.5 2.9 0.07
Open in a new tab

The 795 differentially expressed protein‐coding genes for H1/H2 blockade vs. control at 3 h post‐exercise were mapped to 16 KEGG pathways, three Panther pathways and three Reactome pathways. P (adjusted): Benjamini–Hockberg P‐value.

Discussion

Although the initial purpose of the present study was to determine whether activation of histamine H1 and H2 receptors contributes to the expression of pro‐angiogenic factors during the recovery from acute aerobic exercise, we have found a broad histamine footprint on the human exercise transcriptome that crosses many cellular functions, including inflammation, vascular function, metabolism and cellular maintenance.

Histamine is synthesized de novo through decarboxylation of l‐histidine by histidine decarboxylase, and can function in a paracrine or endocrine fashion, or can be stored in mast cells. We present evidence showing that histidine decarboxylase is up‐regulated following exercise in humans (Fig. 1), which has also been observed in rodents (Endo et al. 1998; Ayada et al. 2000; Niijima‐Yaoita et al. 2012). It is also possible that exercise induces the release of histamine from pre‐existing stores in mast cells. Furthermore, the up‐regulation of histidine decarboxylase may subserve the replenishment of pre‐existing mast cell stores. There are four known histamine receptors (H1 to H4), although our focus has been on subtypes H1 and H2, which are located within skeletal muscle tissue and have been demonstrated to mediate a sustained post‐exercise vasodilatation in humans (Lockwood et al. 2005; McCord et al. 2006; McCord & Halliwill, 2006; Barrett‐O'Keefe et al. 2013). Histamine H1 and H2 receptors are G‐coupled protein receptors that, when activated, stimulate inositol triphosphate and adenylyl cyclase dependent signalling mechanisms, ultimately augmenting mRNA expression through transcriptional activation (Ghosh et al. 2001; Qin et al. 2013). Many of the pleiotropic responses identified in the present study appear to be directly mediated by activation of histamine receptors, as a result of the tight coupling of responses (e.g. IL‐6, CCL2, THBS1), whereas others may be responding secondarily to those primary histamine‐mediated changes, or even may be indirectly modulated by changes in perfusion, shear stress, nitric oxide, metabolism or other physiological responses elicited by histamine receptor activation following exercise (Egginton, 2009, 2011 a, 2011 b). Thus, it is difficult to determine the precise mechanism responsible for a given change in gene expression in the present study. However, and more importantly, it should be noted that our findings represent the integrated response to post‐exercise histamine receptor activation and sustained post‐exercise vasodilatation. Future studies are needed to determine the precise contribution of histamine signalling and other mechanisms that may contribute to the overall response following aerobic exercise.

The top differentially expressed protein‐coding gene downregulated by histamine receptor blockade was IL‐6, which has emerged recently as a putative exercise myokine. A cytokine released from skeletal muscle tissue that is capable of exerting autocrine, paracrine and endocrine responses is referred to as a myokine (Pedersen & Febbraio, 2008; Pedersen, 2013). IL‐6 was the first myokine identified in which plasma and muscle interstitial concentrations significantly rose during muscle contractions, and it was subsequently confirmed that the source was active skeletal muscle (Hiscock et al. 2004; Rosendal et al. 2005; Pedersen, 2013). IL‐6 is exquisitely linked to metabolism and its formation appears to be partially dependent on muscle glycogen content (Steensberg et al. 2001). Our findings suggest that IL‐6 mRNA expression is partially dependent on activation of histamine H1 and H2 receptors. Given the link between histamine receptor activation and IL‐6 mRNA expression, it is not surprising that our Gene Ontology enrichment analysis revealed a marked influence of histamine receptor blockade on molecular functions related to cytokine/chemokine signalling. Moreover, of the top 50 differentially expressed protein‐coding genes, a fair number have classifications related to cytokine signalling. Thus, a clear pattern has emerged relating histamine receptor activation to cytokine/chemokine signalling. Although a mechanistic link between histamine receptor activation and IL‐6 mRNA expression and the physiological consequence of this relationship within the context of exercise is unclear at present, these data add an intriguing level of complexity to our understanding of the skeletal muscle response to aerobic exercise, and would suggest that histamine is modulating a broad array of immune system signals and is a key player in the cycle of inflammation associated with exercise.

Furthermore, KEGG pathway analysis (Table 5) revealed a significant influence of histamine receptor blockade on the Jak‐STAT signalling pathway and its downstream targets (e.g. FOS, MYC, JUNB, SOCS3) (see Supporting information, Table S6), which are important contributors to muscle repair, satellite cell proliferation and myogenic differentiation (Wang et al. 2008; Yang et al. 2009; Trenerry et al. 2011). Thus, conditioning of the skeletal muscle phenotype by exercise may be directly modulated by histamine receptor activation (Osna et al. 2001) or indirectly through myokine/cytokine signalling (Serrano et al. 2008). Given the tight coupling between IL‐6 and glycogen and fat oxidation in skeletal muscle (Febbraio et al. 2003; Carey et al. 2006; Pedersen, 2013), histamine receptor blockade may also influence substrate metabolism acutely during exercise or with chronic exercise training. Systemic changes in substrate metabolism or production may be influenced indirectly by anti‐histamine use as a result of IL‐6 mediated hepatic glucose production (Febbraio et al. 2004). Finally, we established that histamine receptor blockade blunts the gene expression of thrombospondin 1 (THBS1) (Fig. 3) and endothelial NOS3 (Fig. 4) within skeletal muscle. Although the effect of histamine on thrombospondin (Qin et al. 2013) and endothelial nitric oxide synthase (Lantoine et al. 1998; Li et al. 2003) mRNA expression is well understood, we have now extended this relationship to the skeletal muscle of humans. Given the potent effect of thrombospondin as an anti‐angiogenic factor and endothelial nitric oxide synthase as a both a vasodilator substance and as a proangiogenic factor, it is possible that the well‐known vascular adaptations (Lloyd et al. 2003; Prior et al. 2004; Laughlin & Roseguini, 2008; Egginton, 2009; Olfert & Birot, 2011; Haas et al. 2012) that accompany exercise training may be influenced with chronic anti‐histamine use.

We have highlighted only a small fraction of the genes and associated signalling pathways influenced by histamine receptor activation during the recovery from exercise. Dissecting the phenotypic conditioning induced by exercise and influenced by histamine receptor activation remains an exciting area for future research. Moreover, extending these observations from young healthy humans to conditions associated with cardiometabolic diseases is needed. These observations also question whether the chronic use of anti‐histamines blunts the positive adaptations accompanying aerobic exercise training. Almost one‐half of Americans suffer from nasal allergy symptoms (e.g. rhinitis) that are attributable to seasonal allergies (Nathan et al. 2008). Similarly, ∼20% of Americans suffer from gastroesophageal reflux disease (El‐Serag et al. 2004). Histamine H1 and H2 receptor blockers (e.g. fexofenadine HCL and ranitidine HCL) are usually the first line of defence in the treatment of nasal symptoms associated with seasonal allergies and for acid reflux disease. The availability of these anti‐histamines as over‐the‐counter medications may further increase their widespread use. Thus, it is possible that anyone who participates in an exercise training program when taking histamine H1 and H2 receptor blockers for histamine‐mediated disorders may have a blunted expression of some of the beneficial adaptations that are associated with exercise.

Taken as a whole, these data provide novel evidence that histamine, a biological amine normally associated with pathological or anaphylactic conditions, may contribute beneficially to the normal changes that occur within skeletal muscle during the recovery from exercise and perhaps be an important mechanism contributing to many of the adaptations that accompany chronic exercise training. This is consistent with the perspective that histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors, in a variety of pathways that probably predate its more recent role in innate and adaptive immunity.

Additional information

Competing interests

The authors declare that they have no competing interests.

Author contributions

SAR, ADH, MJL, DWT, HCD and JRH contributed to conception or design of the study. SAR, ADH, JEM, MJL, DWT, AJS, MRE, DCS, HCD and JRH were responsible for the acquisition, analysis or interpretation of data. All authors drafted the work or revised it critically for important intellectual content. All authors approved the final version of the manuscript, agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved, and all persons designated as authors qualify for authorship, and all those who qualify for authorship are listed.

Funding

This research was funded by an American Heart Association Grant‐in‐Aid 11GRNT5490000 and the National Institutes of Health Grant HL115027.

Supporting information

Table S1. Control differential expression at 0 h post‐exercise.

Table S2. Control differential expression at 3 h post‐exercise.

Table S3. Blockade differential expression at 0 h post‐exercise.

Table S4. Blockade differential expression at 3 h post‐exercise.

Table S5. Difference between blockade and control at 0 h post‐exercise.

Table S6. Difference between blockade and control at 3 h post‐exercise.

Click here for additional data file. (561.7KB, xlsx)

Acknowledgements

The present study was conducted by Steven A. Romero in partial fulfillment of the requirements for a doctoral degree at the University of Oregon. We would like to thank the subjects who cheerfully participated in this research study. We would also like to thank Molly J. Geiger for study co‐ordination, as well as Kris Johnson and Cliff Dax for their engineering expertise.

This is an Editor&s Choice article from the 1 September 2016 issue.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1. Control differential expression at 0 h post‐exercise.

Table S2. Control differential expression at 3 h post‐exercise.

Table S3. Blockade differential expression at 0 h post‐exercise.

Table S4. Blockade differential expression at 3 h post‐exercise.

Table S5. Difference between blockade and control at 0 h post‐exercise.

Table S6. Difference between blockade and control at 3 h post‐exercise.

Click here for additional data file. (561.7KB, xlsx)

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