Open Access Identifying genetic networks underlying myometrial transition to labor
2005

Nathan Salomonis
Pharmaceutical Sciences and Pharmacogenomics Graduate Program
University of California
513 Parnassus Avenue94143San FranciscoCAUSA

Nathalie Cotte
Department of Medicine
Cardiovascular Research Institute
University of California
505 Parnassus Avenue94143San FranciscoCAUSA

Alexander C Zambon
Department of Medicine
Cardiovascular Research Institute
University of California
505 Parnassus Avenue94143San FranciscoCAUSA

Katherine S Pollard
Center for Biomolecular Science and Engineering
University of California
1156 High Street95064Santa CruzCAUSA

Karen Vranizan
Functional Genomics Laboratory
University of California
94720-3860BerkeleyCAUSA

Scott W Doniger
Gregory Dolganov
Department of Medicine
Cardiovascular Research Institute
University of California
505 Parnassus Avenue94143San FranciscoCAUSA

Bruce R Conklin email@example.com
Pharmaceutical Sciences and Pharmacogenomics Graduate Program
University of California
513 Parnassus Avenue94143San FranciscoCAUSA

† ‡¥
Department of Medicine
Cardiovascular Research Institute
University of California
505 Parnassus Avenue94143San FranciscoCAUSA

Cellular and Molecular Pharmacology
University of California
600 16th Street94143-2140San FranciscoCA

USA. Correspondence: Bruce R Conklin

Addresses: * Gladstone Institute of Cardiovascular Disease
1650 Owens Street94158San FranciscoCAUSA

Open Access Identifying genetic networks underlying myometrial transition to labor

Salomonis et al
62122005Genome Biology 2005, 6:R12 comment reviews reports deposited research refereed research interactions information Research Uterine gene-expression profiling at the onset of labor
A time course of gene expression at the onset of labor reveals transcriptional networks associated with activation of the uterine muscle and identifies targets for drugs to prevent premature labor.

Background: Early transition to labor remains a major cause of infant mortality, yet the causes are largely unknown. Although several marker genes have been identified, little is known about the underlying global gene expression patterns and pathways that orchestrate these striking changes.Results:We performed a detailed time-course study of over 9,000 genes in mouse myometrium at defined physiological states: non-pregnant, mid-gestation, late gestation, and postpartum. This dataset allowed us to identify distinct patterns of gene expression that correspond to phases of myometrial 'quiescence', 'term activation', and 'postpartum involution'. Using recently developed functional mapping tools (HOPACH (hierarchical ordered partitioning and collapsing hybrid) and GenMAPP 2.0), we have identified new potential transcriptional regulatory gene networks mediating the transition from quiescence to term activation.Conclusions:These results implicate the myometrium as an essential regulator of endocrine hormone (cortisol and progesterone synthesis) and signaling pathways (cyclic AMP and cyclic GMP stimulation) that direct quiescence via the transcripitional upregulation of both novel and previously associated regulators. With term activation, we observe the upregulation of cytoskeletal remodeling mediators (intermediate filaments), cell junctions, transcriptional regulators, and the coordinate downregulation of negative control checkpoints of smooth muscle contractile signaling. This analysis provides new evidence of multiple parallel mechanisms of uterine contractile regulation and presents new putative targets for regulating myometrial transformation and contraction.

Background

The initiation of mammalian labor is a complex physiological process that requires the expression and secretion of many factors, both maternal and fetal [1,2]. The majority of these factors exert their effect on the myometrium, the smooth muscle responsible for expelling the fetus from the uterus. While species differences in labor regulation have been observed, several common signaling pathways and factors have been implicated as key regulators across species. During mid to late gestation, myometrial quiescence is maintained by several contractile inhibitors, such as relaxin, adrenomedullin, nitric oxide, prostacyclin and progesterone [1,2]. A number of these regulators stimulate cyclic AMP (cAMP)and cGMP-mediated signaling pathways. Smooth muscle contraction is inhibited by the phosphorylation of myosin light-chain kinase by the cAMP-dependent protein kinase. This inhibition is believed to promote quiescence. In addition, the myometrium undergoes major structural changes throughout pregnancy that are required to generate the necessary contractile force for labor, including hypertrophy and hyperplasia of smooth muscle, connective tissue, focal adhesion, and cytoskeletal remodeling [3].

The transition to labor results in synchronous contractions of high amplitude and high frequency by the myometrium. Factors previously associated with the regulation of myometrial activation include the oxytocin receptor, gap junction protein connexin-43, voltage-gated calcium channels, prostaglandin receptor subtypes, estrogen, cortisol and transcription factors c-Jun and c-Fos. Most of these proteins participate in pathways that stimulate calcium release (for example, calciumcalmodulin G protein signaling) and the formation of intracellular junctions, leading to stimulation of contractions. Although several important components that regulate the initiation of labor have been identified, the mechanisms that guide this transition are poorly understood.

A difficult challenge in identifying the regulatory events that control the switch from myometrial quiescence to activation has been developing tools for examining whole-genome expression profiles in the context of known biology. Recent efforts to identify transcriptional changes from laboring and non-laboring human myometrium have proved valuable in identifying putative physiological regulators [4][5][6][7][8]; however, the lack of gestational time points examined has limited these approaches to interrogating only those genes with large foldchanges at term activation without exploring the global patterns of gene expression over the time-course of myometrial transformation. While gene profiling of the rodent uterus during gestation has proved fruitful in revealing some of the large-scale patterns of gene expression throughput pregnancy [5,9], there is still a critical need to improve the global view of myometrial gene expression with greater temporal resolution using newly developed bioinformatic tools.

To identify molecular mechanisms involved in the transition from myometrial quiescence to labor, we analyzed geneexpression changes in mouse myometrium at mid-gestation, throughout late gestation, and during the postpartum period. Our results reveal several novel patterns of expression occurring along the phases of myometrial quiescence to term activation and postpartum involution. Analysis of putative quiescence and term activation regulators in the context of well defined biological pathways revealed new putative functional roles for several previously unassociated genes in the suppression of contraction throughout gestation and activation of phase-dependent contractions at labor. This analysis further implicates the regulation of several novel pathways, including smooth muscle-extracellular matrix interactions throughout late gestation and cell junction-cytoskeletal interactions immediately before the onset of labor.

Results

Clustering of expression changes in gestational myometrium

Messenger RNA transcript levels were measured from isolated myometrium of 35 time-mated mice at four time-points of late gestation (14.5-18.5 days), at postpartum (6 and 24 hours after labor), and from a non-pregnant control group. In all, approximately 13,000 probe sets corresponding to around 9,000 unique cDNAs and expressed sequence tags (ESTs) were probed with oligonucleotide microarrays. About 35% of these transcripts were regulated throughout gestation and postpartum (14.5 days through 24 hours postpartum) using the criteria of p < 0.05 and a change in level of expression of more than 20% (fold-change 0.2).

Clustering of myometrial expression profiles with HOPACH Figure 1 (see following page) Clustering of myometrial expression profiles with HOPACH. Gene-expression profiles for 27 microarrays (vertical axis) and 4,510 probe sets (horizontal axis) are shown in the context of the HOPACH cluster map (non-pregnant data excluded). The array groups correspond to mid to late gestation (14.5, 16.5, 17.5 and 18.5 days) and postpartum (6 and 24 h). Eight clusters of genes are arranged vertically. Physiological phase groups are assigned on the basis of visual observation and association with previously associated regulators. MAPPFinder results are shown for the top-ranking distinct biological process, molecular function and cellular component groups based on a permuted p-value. Previously associated regulators of uterine quiescence and activation are indicated by a colored line next to the location of the corresponding gene probe set in the cluster map.  Analysis of these probe sets with HOPACH [10][11][12] revealed eight primary cluster groups and 133 subclusters. The majority of these clusters showed a clear association with known physiological phases of uterine gestation: quiescence (clusters 2, 3, 7 and 8), term activation (cluster 6), and postpartum involution (clusters 3, 4 and 7). In addition to these clusters, we observed two cluster groups with genes downregulated or upregulated throughout the analyzed time-course (clusters 1 and 5) (Figure 1).

MAPPFinder analysis

To characterize the major biological processes, molecular functions, and cellular components associated with the HOPACH pattern groups, we used MAPPFinder (a component of GenMAPP version 2.0) [13][14][15][16]. MAPPFinder produced a statistically ranked list (based on p-value) of Gene Ontology (GO) biological categories associated with each cluster, from which the most significant nonsynonymous groups are listed ( Figure 1, GO categories). In each cluster, several highly significant biological associations were identified (adjusted permutation p < 0.05).

Association of expression clusters with previously associated uterine quiescence and activation genes

Gene expression groups associated with the maintenance of pregnancy (quiescence) or induction of labor (activation) were confirmed by mapping lists of previously associated regulators of uterine quiescence and activation onto our HOPACH cluster map. Extensive literature searches for such regulators identified 66 genes, of which 23 were regulated in our dataset ( Figure 1, previously associated regulators). Genes hypothesized to regulate quiescence by transcriptional upregulation or secretion were largely associated with clusters 7 and 8 ('increased quiescence'), while putative activators of uterine activation were largely associated with cluster 6 ('increased term activation'). Although only three downregulated quiescence regulators were associated with HOPACH clusters, two of them mapped to cluster 2 ('decreased quiescence'), as predicted.

Functional analysis of quiescence and term activation pattern groups

To further elucidate specific genes and pathways linked to the regulation of uterine quiescence and the initiation of labor, we examined pattern groups linked to quiescence and term activation, in the context of GO categories, GenMAPP pathway maps and literature associations. While low-magnitude fold-changes have been included within these functional analyses to broaden our survey of biological groups, we have largely restricted our discussion to transcripts with foldchanges greater than two.

Upregulation of pathways of relaxation and remodeling during quiescence

Analysis of genes upregulated throughout gestation (increased quiescence) revealed a number of biological cate-gories associated with uterine quiescence. These categories contain a large number of highly regulated genes coupled to the inhibition of prostaglandin and cortisol synthesis, stimulation of cAMP and cGMP signaling pathways, extracellular matrix remodeling, cytolysis and regulation of cell growth ( Figure 2, Table 1). To explore the potential relationships between the products of these transcriptionally regulated genes, we mapped the data onto respective metabolic and signaling pathways (Figure 3a,b).

Besides well established quiescence regulators (Adm, Cgrp, Hsd11b2, Gnas, Cnn1 and Utg; see Tables 1, 2, 3 for full gene names), several genes previously unassociated with the maintenance of quiescence were identified along the same or related biological pathways. The most highly regulated of these genes were those implicated in the induction of cGMP and cAMP signaling pathways (Guca2b and Cmkor1), genes for calcium-dependent phospholipid binding proteins (Anxa1, Anxa2, Anxa3 and Anxa8), and for the Anxa2 dimerization partner S100A10 (Figure 3a). Other changes in expression from this pattern group were observed among cytolysis-inducing proteases (granzymes B-G), regulators of cell growth (Igfbp2 and Il1r2), and transcriptional regulation (Sfrp4 and Klf4). Several of these and other genes were found to have highly reproducible patterns of expression using quantitative real-time PCR (TaqMan), with typically larger fold-changes produced by TaqMan than by GeneChip (consistent with the more conservative fold-changes typically produced after robust multi-array average (RMA) normalization) (see Additional data file 1).

Several genes for cAMP-response element transcription factors were also found within the increased quiescence group (Atf4, Crebl1, and Creb3, see Figure 3b). These are all members of a larger group of basic leucine zipper (bZip) transcription factors not previously associated with quiescence, which also includes the CCAAT/enhancer binding protein Cebpd, the Maf protein Mafk, the nuclear factor, interleukin-3, regulated Nfil3, and the X-box binding protein Xbp1, also upregulated with quiescence.

Downregulation of mRNA processing and contractionassociated signaling during quiescence

MAPPFinder analysis of genes in the decreased quiescence group identified a wide variety of cell maintenance, transcription, and cell-signaling biological processes. Many of these GO categories were associated with the onset of labor (calcium-ion transport and protein tyrosine phosphatase activity) or myometrial postpartum involution (programmed cell death, collagen catabolism and ubiquitin-conjugating enzyme activity). These results are in accordance with the inhibition of contraction and suppression of cell death in late gestation. Unlike term-related biological processes, categories shared between the decreased quiescence and 'increased postpartum involution' group appear to be largely the result of a common transcript expression profile ( Figure  1, cluster 3; Figure 2).

Although similar numbers of genes were downregulated or upregulated with quiescence (approximately 480-520 genes), very few genes were downregulated more than twofold at 14.5 days of gestation ( Table 2). One of the most downregulated transcripts was the myosin light-chain gene Myl4; the Myl4 protein is the primary target for oxytocin-induced phosphorylation leading to uterine contraction at term. Several additional putative components of the oxytocin contractile signaling pathway (calcium-calmodulin signaling pathway) were also present in this expression group (Iptr1, Ryr3, Plcg1, and Atp2a2) (Figure 3b). Another large set of coordinately downregulated genes includes factors involved in RNA processing. Alternative splicing of putative quiescence and term activation regulators has been proposed to be a critical mechanism of the physiological switch to labor [17,18].

Transition from remodeling and relaxation to cell-cell signaling and transcriptional regulation with activation of the myometrium at term

A large percentage of genes regulated with quiescence continued to be highly regulated at term. This result emphasizes the importance of expression changes immediately before labor to counteract the effects of quiescence. Consistent with the number of upregulated genes, MAPPFinder analysis of the increased term activation group identified a smaller set of GO terms and pathways. Prominent among these were genes associated with the formation of cell junctions, kinesin complexes and endopeptidase inhibitors. In addition, functionally related transcription factors (members of the basic helixloop-helix (bHLH) family), ion transport proteins and ion transport regulators were coordinately upregulated at term.

Within these biological categories, several contractile regulators, both associated and unassociated with parturition, were highly upregulated. These genes include those for cell junction proteins (Cx43, Cx26, Ocln, and Dsp), the pulmonary smooth muscle contractile regulator and complement component C3, the estrogen signaling regulator Hsp70, the chloride conductance regulator Fxyd3 and the ryanodine receptor regulator Gsto1 (Table 3). These changes occurred in concert with the upregulation of signaling molecules, such as growth factors (Inhba, Inhbb), G-protein signaling components (Edg2, Gng12) ( Figure 3b) and collagen catabolism proteins (Pep4, Mmp7). On the whole, however, this pattern group was dominated by the upregulation of genes encoding proteins that are largely epithelial-cell specific. Most prominent among these are the genes for the cytokeratin intermediate filament proteins, Krt2-7, Krt2-8, Krt1-18, and Krt1-19, and for the cytokeratin transcriptional regulator Elf3, which are among the most highly upregulated genes at term. Figure 2 Association of quiescence and term activation pattern groups with biological pathways. Significant associations to GO classification groups and GenMAPP pathways were determined for each of the four expression pattern groups examined: Displayed are representative gene expression patterns for increased and decreased quiescence and term activation. (a) increased quiescence (yellow curve), increased activation (red curve); (b) decreased quiescence (green curve) and decreased activation (blue curve). GO terms and GenMAPP pathways highlighted by analysis with the program MAPPFinder are indicated by italicized blue text. Biological processes identified by literature association are indicated in black text. Parent biological categories are designated by bold text.

Association of quiescence and term activation pattern groups with biological pathways

Downregulation of pathways of calcium mobilization and G-protein signaling in term myometrium

HOPACH analysis with a metric that disregarded the direction of fold-change (see Additional data file 2) revealed a small number of downregulated genes at term that mirror the increased term activation group. Among these, we observed two highly downregulated genes: regulator of G-protein signaling 2 (Rgs2), a potent inactivator of Gαq-GTP bound activity, and inhibitor of DNA binding 2 (Idb2), a bHLH factor that heterodimerizes with other HLH proteins to inhibit their function. Rgs2 is one of the most downregulated genes throughout the gestation-postpartum time-course, in addition to being highly expressed in non-pregnant myometrium and throughout gestation. Additional term-downregulated G-protein signaling proteins that act to antagonize calcium-calmodulin signaling are illustrated in Figure 3b.

Global mechanisms of transcriptional regulation

One of the most prominent observations in this dataset is the highly significant correlation in the expression and genomic position of genes for eight serine-type endopeptidases (Gzmb through Gzmg, Mcpt8 and Ctsg) during the phase of quiescence. Genes within this multigene cluster undergo tight coordinate regulation in response to cell stimulation [19,20]. Examination of this expression cluster group in the context of genomic position reveals a novel pattern of positional gene regulation, where relative fold-change in expression Only upregulated genes with a relative fold-change of 2 or more versus non-pregnant mice at 14.5 days gestation and linked to biological categories highlighted by the expression analysis are shown. Full gene lists can be obtained online (see Additional data file 6). increases from the peripheral members in the cluster to the center of the gene cluster (Figure 4a).

To determine whether other gene clusters exhibit a similar form of positional co-regulation, we developed a program to identify genomic intervals containing several coexpressed genes. Searching for regions with three or more members in a broad genomic interval (500 kilobases (kb)), we identified 11 clusters of genes that are co-localized and co-regulated (the same HOPACH cluster) [21]. Among these, we were able to identify at least one other gene cluster that possessed a genomic pattern of gene expression similar to that of the granzyme cluster, with genes maximally upregulated postpartum (Figure 4b). These genes, which encode several of the collagen catabolism matrix metalloproteinases, Mmp3, Mmp10, Mmp12 and Mmp13, are among the most highly upregulated genes postpartum. Because we do not have data from full genome arrays, it is difficult to determine if these co-regulated clusters of genes occur more frequently. However, these co-regulated gene clusters suggest coordinated gene regulation by an unknown mechanism.

Discussion

This time-course analysis provides the first global view of gene-expression changes in mouse myometrium from uterine quiescence through the activation of the myometrium before labor and to its postpartum involution. Examination of multiple time points, the use of replicates, robust array normalization and powerful clustering tools enabled us to delineate and characterize unique patterns of gene expression throughout this physiological process. In addition to partitioning clusters of genes, analysis with the program HOPACH also provides us with a continuum of expression changes that reveals an overall transition in the expression of genes from one cluster group to another (Figure 1). Annotation of these clusters with GO terms provides a bird's eye view of the major processes regulating each of these pattern groups. These  results support the hypothesis that mid-to-late gestation is dominated by changes in the expression of genes related to cell growth and extracellular-matrix remodeling (cluster 7), term gestation by changes in the content of cell junctions (cluster 6), and postpartum by targeted protein degradation, collagen digestion and apoptosis (clusters 3 and 4). Furthermore, results from genes upregulated throughout gestation and through postpartum suggest a continual local uterine immune response throughout this process (cluster 5). To help visualize the large-scale gene-expression changes in the context of myometrial physiology, we have depicted the data in an animation (see Additional data file 3) that summarizes our major findings.

A number of studies emphasize the importance of fetal regulation of the switch from quiescence to term activation, particularly increased cortisol and estrogen output from the fetal adrenal gland [1,2]. Interestingly, our studies provide evidence of a dynamic interplay between the myometrium and the fetus, particularly at the level of cortisol and progesterone synthesis (Figure 3a). Genes highly upregulated with quiescence include Hsd11b, which encodes an enzyme that converts cortisol to the inactive cortisone, and Cyp11a1, encoding an enzyme that promotes the synthesis of progesterone. Conversely, Hsd11a, coding for an enzyme that catalyzes the synthesis of cortisol, increased expression from 11to 18-fold throughout gestation, suggesting that local regulation of cortisol levels are important for myometrial activation.

While we observed the upregulation of the estrogen signaling regulator Hsp70, with term activation, downstream markers of estrogen action are among the most highly upregulated genes with term activation, supporting the role of the fetus in myometrial activation.

Examination of highly upregulated putative quiescence and term activation genes revealed several novel changes within important associated pathways for quiescence and activation (cAMP and cGMP signaling, calcium and calmodulin signaling and prostaglandin synthesis). Proteins encoded by these genes include Guca2b (uroguanylin), Anxa3, and Anxa8 with quiescence, and C3, Edg2, Gsto1 and Fxyd3 during activation (see Figure 3). These factors may represent novel targets for controlling the length of gestation. This is evidenced by the parallel observed upregulation of Guca2b from a recent microarray analysis of rat uterine gestation, where this factor has also been proposed to be a crucial regulator of cGMPmediated smooth muscle relaxation throughout late pregnancy [9,22]. We have validated the expression patterns of a number of these genes using quantitative real-time PCR (see Additional data file 1). In addition to the candidates mentioned here, a number of other highly upregulated genes, whose functions have not been elucidated are also found in these two expression groups (see Additional data file 6).

Although a number of genes upregulated with quiescence or with term activation can be clearly implicated in the regula- Only upregulated genes with a relative fold-change of 2 or more versus non-pregnant mice at 18.5 days gestation and linked to biological categories highlighted by the expression analysis are shown. Full gene lists can be obtained online (see Additional data file 6). tion of contractile pathways or uterine growth, several more groups of genes with little known functional connection to these processes were coordinately expressed. Highlighted among these groups are serine endopeptidases (granzymes) and bZip transcription factors, upregulated during quiescence, and endopeptidase inhibitors and bHLH factors, upregulated with term activation. In addition to its role in cytolysis, granzyme expression and secretion by T lymphocytes has been associated with the breakdown of extracellular matrix proteins in the uterus during pregnancy [18,23,24]. Interestingly, the upregulation of serine endopeptidases appears to be antagonized before the onset of labor by the upregulation of several serine endopeptidase inhibitors with term activation. A similar antagonistic relationship may also exist for bHLH factors upregulated at term with inhibitors of HLH function that are upregulated with quiescence and become downregulated at term.

Although the myometrium is considered to be relatively homogeneous, many of the largest changes in gene expression at term occurred in genes that are not normally associated with muscle, such as the keratins, tight junction and desmosome junction proteins. Indeed, altered gene expression due to changes in cell-type distribution or the invasion of the myometrium by the decidua and endometrium would not be distinguished if those changes occur consistently between gestational myometrium preparations. Further inspection of the literature reveals that the cytokeratins, which compose the bulk of this group, are expressed within smooth muscle and probably function as components of intermediate filaments of the cytoskeleton [25][26][27][28]. Furthermore, several components of desmosome spot junctions and hemidesmosomes, which interact with keratin intermediate filaments and the extracellular matrix to impart tensile strength between cells, are also upregulated with term activation (see Additional data file 3). These data suggest that an increase in rigidity-imparting cell junctions and remodeling of the cytoskeleton immediately before labor may promote coordinate contractions. However, further studies are needed to determine if cytokeratin expression at term occurs within resident or infiltrating cells.

In addition to the capability to group and annotate clusters of genes, pattern analysis with HOPACH can be used to interrogate gene clusters in the context of genomic location. For this analysis, we developed a program to isolate gene clusters that are likely to be co-regulated on the basis of genomic location, similar to other reported methods [29][30][31][32]. Using this program, we identified genomic regions that undergo correlated changes in gene expression associated with specific phases of the myometrial time-course. These groups highlight novel forms of gene regulation during quiescence and postpartum to coordinate cell responses (serine-protease activation and collagen catabolism). The prominent co-regulation among members of these two gene clusters further suggests that immune-cell trafficking and activation also play important roles in the progression towards labor and recovery from pregnancy.

Conclusions

We have identified several highly regulated genes not previously associated with myometrial quiescence or activation, in addition to families of genes co-regulated at different phases  of the myometrial time-course. In addition to providing new hypotheses about how the switch from quiescence to term activation may be facilitated ( Figure 5), these data highlight several proteins that may serve as new candidate pharmacological targets for regulating myometrial contraction and thus the onset of labor. Such analyses will also be useful in predicting and correlating gene-expression changes in human pregnancy, where several time-points are often difficult to obtain [4][5][6][7][8]. Similar studies in other species using complementary methods of transcript measurement will also be necessary to validate these changes and understand the species-specific and regional myometrium transcriptional differences that probably occur. A detailed examination of the precise physiological roles of these regulators and mechanisms of regulation will be essential for developing a more detailed view of the regulation of labor.

Materials and methods

Tissue harvesting

FVB/N mice (Jackson Laboratory) were sacrificed in the morning (10 to noon) at 14.5 (n = 3), 16.5 (n = 4), 17.5 (n = 5), or 18.5 days (n = 7) after timed mating, and 6 (n = 4) or 24 h (n = 4) after delivery. Control myometrium was harvested from non-pregnant littermate females (n = 8) 1 day after timed mating with a vasectomized male. After dissection of both uterine horns, the tissue closest to the cervix was removed. Each horn was washed with PBS and opened longitudinally. Pups and placenta were discarded, and the decidua was removed by blunt dissection. The myometrium from each horn was then immediately frozen in liquid nitrogen and stored at -80°C.

Sample preparation and microarray data normalization

For each sample, labeled cRNA was prepared from 20 µg purified total RNA and hybridized to Affymetrix Mu11k A and B arrays according to the manufacturer's instructions. Tissue from each mouse was hybridized individually to one array set.

Microarrays were scanned at a photomultiplier tube (PMT) setting of 100%. Resulting .cel files were generated with Affymetrix Microarray Suite 5.0 and analyzed with RMA [33].

Statistical analysis

To identify transcripts differing in mean expression across the seven experimental groups, p-values were calculated from a permutation test with the F-statistic function from the multtest package of Bioconductor [12,34]. Fold-changes in transcript levels were calculated from the mean log 2 expression values of each time-point group versus the mean of non-preg-  nant controls. For cluster analysis, the dataset was filtered for probe sets with a p < 0.05 across the full expression timecourse and a greater than 20% change in level of expression (positive or negative) for at least one time-point group versus non-pregnant controls. Additional filters were used downstream of clustering for genes related to uterine quiescence and term activation. For clusters related to quiescence and term activation, a change of more than 20% was required for the midgestation (14.5 days) and term (18.5 days) time points, respectively, versus non-pregnant controls.

Clustering and pattern analysis

Gene expression clustering for 4,510 significant probe sets was performed using the program HOPACH (hierarchical ordered partitioning and collapsing hybrid), with uncentered correlation distance [10][11][12]. HOPACH produced a tree with six levels of clusters (eight primary level clusters and 133 main clusters). To examine expression patterns independently of the direction of the fold change, HOPACH was re-run with absolute uncentered correlation distance. Associations with GO biological process, molecular function, cellular component groups, and GenMAPP biological pathways were obtained with MAPPFinder 2.0, a part of the GenMAPP 2.0 application package [13][14][15][16]. A permuted p-value was calculated by MAPPFinder 2.0 to adjust for multiple hypothesis testing (see Additional data file 7). Because of the highly redundant nature of the oligonucleotide arrays used, redundant probe sets corresponding to a single gene were identified from the Affymetrix NetAFFX website [35].

Real-time PCR validation of microarray data

Real-time reverse transcription PCR (RT-PCR) was used to validate the expression patterns of several highly regulated genes associated with specific phases of myometrium gestation. Gene-specific primers for multiplex real-time RT-PCR were designed for each gene of interest (n = 18) using Primer Express software (Perkin Elmer) and based on sequencing data from the National Center for Biotechnology Information (NCBI) databases and purchased from Biosearch Technologies. Sequence data for all oligos are available online [36]. Total RNA concentration and quality was assessed using the Agilent Bioanalyzer 2001. First-strand cDNA synthesis was performed using total cellular RNA (BD Biosciences Clontech), Powerscript reverse transcriptase (BD Biosciences Clontech), and random hexamer primers. Finally, an equivalent of 10 ng of total RNA from the first-strand cDNA synthesis reaction was used in 10 µl of each TaqMan gene quantification in 384-well format. Universal Master Mix for real-time PCR was purchased from Invitrogen Life Technologies. Raw data from an ABI Prism 7900 (Applied Biosystems) were processed into Excel spreadsheets and conversion of raw Ct values to relative gene copy numbers (GCN) was done as described previously [37]. Gene-expression analysis requires proper internal control genes for normalization. By using an endogenous control as an active reference, quantification of an mRNA target can be normalized for differences in the amount of total RNA added to each reaction. For this purpose, we used four mouse housekeeping genes -PPIA, GAPDH, PGK1 and S9. Moreover, using GeNorm [38], we selected PGK1 and GAPDH as the two most stable housekeeping genes across all 12 specimens and used their geometric means for normalization. Normalized data were graphed and compared to the data generated on similar specimens via microarrays. Genes could be broken down into the following groups: 13 genes with concordant microarray-TaqMan patterns; one false-negative result by microarray (Acta2); three genes with high TaqMan variability (Mmp9, Krt19, Id1); and one gene with evidence of alternative splicing (Csb) (see Additional data file 1). It should be noted that Acta2 baseline expression was relatively high for both microarray and Taq-Man results. As both of these techniques probed different regions of the Acta2 gene, we cannot exclude the possibility of alternative splicing.

Chromosomal localization analysis

We constructed a program to link HOPACH expression data to chromosome transcription start-site location and strand orientation, obtained from the Ensembl database [39]. Colocalized clusters of genes were identified as those genes clustered within a 500-kb genomic interval, belonging to the same HOPACH cluster, with a z-score >1.96, and an average pairwise Pearson correlation among cluster members of r >0.65 (see Additional data file 7 for calculation details and [21] for the full supplemental chromosome cluster lists).

Additional data files

The following additional data are available with the online version of this article. Additional data file 1 is a figure showing the TaqMan vs GeneChip gene expression patterns. Relative fold changes (log base 2) are shown for 18 genes identified by these GeneChip studies to be differentially regulated throughout the myometrium gestation time-course. Combined standard errors are shown for each gestational time-point as compared to the non-pregnant control group. Additional data file 2 is a figure showing the HOPACH Absolute Value Pearson Correlation of Myometrial Expression Data. Gene expression data used for Pearson correlation HOPACH was used to generate a new set of clusters with a metric that disregards the direction of fold-change. Genes downregulated with term are identified based on association with genes upregulated at term from the non-absolute HOPACH analysis. Additional data file 3 is an animation of the summary and results, with a cartoon representation of myometrial transformation, general experimental design, results and conclusions. Additional data files 4 and 5 are Excel tables listing the MAPPFinder results. Nonsynonymous MAPPFinder GO categories for each expression pattern group are provided. Reanalysis with Gen-MAPP version 2.0 is required to visualize the genes that associate with each GO term. To download GenMAPP version 2.0, go to [16]. Additional data file 6 is a set of tables of cluster groups with annotations. Expression data, statistics, and bio-

Figure 1
1(see legend on previous page)

Genome
Biology 2005, 6:R12 Analysis of pathways of uterine smooth muscle contraction Figure 3 Analysis of pathways of uterine smooth muscle contraction. (a) Prostaglandin synthesis and (b) G-protein signaling pathways in the myometrium are overlaid with gene-expression color criterion and fold-changes from the program GenMAPP. Interactions suggested by results of this microarray analysis are included in these figures. Detailed gene-expression data, statistics and full gene annotations are available on the GenMAPP interactive version of these pathways online [40].

of genomic localization with co-regulation of expression Figure 4 Association of genomic localization with co-regulation of expression. (a,b) Chromosomal gene clusters contain highly correlated expression changes among multiple members. Global patterns of gene expression within these genomic intervals are visualized by representing mean log expression for four of the myometrium time-point groups (non-pregnant, 14.5 and 18.5 days gestation, and 24 h postpartum), versus relative gene position on the chromosome.Gene strand orientation and position is designated by the orientation of arrows. Gene symbols above and below arrows are shown, where italicized black text indicates co-regulated genes (same HOPACH cluster) and italicized gray genes not co-regulated for (a) increased quiescence and (b) increased postpartum involution. Non-italicized gray text indicates genes not probed by the arrays.

maternal model of uterine-directed contractile regulation Figure 5Proposed maternal model of uterine-directed contractile regulation. Theoretical model based on the major gene-expression pattern groups for quiescence, term activation and postpartum involution (light gray box outline). Arrows next to gene processes and functional groups indicate the predominant direction of fold-change as indicated by HOPACH analysis. This model proposes new roles for transcriptional regulators, regulators of mRNA processing, local hormone regulation, protease activity and cell junction formation in the control of both contractile signaling and contraction propagation in the myometrium during pregnancy. A model of postpartum involution is also presented, based on additional data (see Additional data files 4-6).

Table 1 (
1Continued)Genes upregulated with quiescence

Table 2
2Genes downregulated with quiescenceOnly downregulated genes with a relative fold-change of 2 or more versus non-pregnant mice at 14.5 days gestation and linked to biological categories highlighted by the expression analysis are shown. Full gene lists can be obtained online (see Additional data file 6).Decreased gestation pattern group
Gene symbol
Fold-change at 14 days

Regulation of cell growth

Myosin light chain, alkali, cardiac atria
Myl4
-2.8

N-myc downstream regulated 2
Ndr2
-2.7

Actin, beta, cytoplasmic
Actb
-2.2

Calmodulin signaling

MARCKS-like protein
Mlp
-2.2

Proteolysis

Matrix metalloproteinase 3
Mmp3
-2.2

Ion channels

Expressed sequence AW538430
Kctd12
-2.9

Transcriptional regulation

SRY-box containing gene 4
Sox4
-2.9

Homeobox protein Meis2
Mrg1
-2.5

Special AT-rich sequence binding protein 1
Satb1
-2.1

D site albumin promoter binding protein
Dbp
-2.1

RIKEN cDNA 1110033A15 gene
1110033A15Rik
-2.1

Myeloid ecotropic viral integration site 1
Meis1
-2.0

Regulation of alternative splicing

CDC-like kinase
Clk
-2.1

Table 3
3Genes upregulated with term activationGene symbol
Fold-change at 18 days

Table 3 (
3Continued)Genes upregulated with term activation

R12.6 Genome Biology 2005, Volume 6, Issue 2, Article R12
AcknowledgementsWe thank Chris Barker, Kristina Hanspers, Yanxia Hao, and Anita Chow from the Gladstone Genomics Core, and Michael McMaster for his assistance with uterine dissections. We thank Susan Fisher, Janet A. Warrington, Gary Howard, Bethany Taylor and members of the Conklin lab for helpful discussions and editorial assistance. This work is supported by the J. David Gladstone Institutes and grants from the National Institutes of Health: NHLBI, R01-HL61689 (B.R.C.) NHGRI R01-HG002766 (B.R.C) and SBIR 1R44DK53325-01 (Janet A. Warrington and B.R.C.), and T32 GM07175 (N.S.).logical groupings based on Gene Ontology annotations (via MAPPFinder analysis) and the literature are provided for 'Quiescence', 'Activation', and Postpartum 'Involution' gene lists. Additional data file 7 contains additional details of methods. Additional data file 8 contains the full expression dataset as an Excel file and Additional data file 9 is a GenMAPP format GEX file for use with GenMAPP format pathway maps (MAPP files). MAPP files can be downloaded from[16]. Click here for additional data file Additional data file 6 A set of tables of cluster groups with annotations A set of tables of cluster groups with annotations Click here for additional data file Additional data file 7 Additional details of methods Additional details of methods Click here for additional data file Additional data file 8 The full expression dataset as an Excel file The full expression dataset as an Excel file Click here for additional data file Additional data file 9 A GenMAPP format GEX file for use with GenMAPP format path-way maps (MAPP files) A GenMAPP format GEX file for use with GenMAPP format path-way maps (MAPP files) Click here for additional data file
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The effect of a cold beverage during an exercise session combining both strength and energy systems development training on core temperature and markers of performance

Danielle Lafata
Amanda Carlson-Phillips
Stacy T Sims
Elizabeth M Russell
The effect of a cold beverage during an exercise session combining both strength and energy systems development training on core temperature and markers of performance
R E S E A R C H A R T I C L E Open Access
Background: Although studies have investigated the effects of hydration on performance measures, few studies have investigated how the temperature of the ingested liquid affects performance and core temperature during an exercise session. The hypothesis of the present study was that cold water would improve thermoregulation and performance as measured by bench repetitions to fatigue, broad jump for force and power and total time to exhaustion for cardiovascular fitness Methods: Forty-five, physically fit, adult males (30.28 ± 5.4 yr, 1.77 ± 7.8 m, 83.46 ± 11.5 kg; 13.7 ± 4.8 %BF; 49.8 ± 6.3 ml/kg/min V02) completed two 60-minute exercise sessions. Subjects consumed either COLD (4°C) or room temperature (RT) water (22°C) in randomized order. Core temperature was measured every 15 minutes throughout each trial using a digestible thermometer. Three performance tests were performed upon completion of the exercise session: bench press to fatigue, standing broad jump, and bicycle time to exhaustion Results: Although both groups significantly increased their core temperature (p<0.001) over the course of the exercise session and presented a significant decline in hydration status (p<0.001), participants in the COLD water trial had a significantly (p=0.024) smaller rise in core temperature (0.83°) over the duration of the trial in comparison to RT (1.13°). The participants in the COLD water trial were able to delay their increase in core body temperature for at least 30 minutes, whereas participants in the RT trial increased body temperature from baseline after 15 minutes. There was no significant difference between the COLD or the RT trials in broad jump and TTE performance tests. Bench press showed a small, albeit significant (p=0.046), decrease in performance when drinking COLD Conclusion: Drinking cold water can significantly mediate and delay the increase in core body temperature during an exercise session in a moderate climate with euhydrated subjects. The ingestion of COLD improved performance for 49% and 51% of the participants in the broad jump and TTE performance tests respectively, but did not reach statistical significance. Moreover, although minimal, subjects experienced a decrease in performance on the bench press during the COLD.

Background

It is well known that exercising in hot environments can increase core temperature especially if dehydrated [1][2][3][4]. Dehydration impairs thermoregulation as well as cardiovascular, metabolic and central nervous system functions. Elevated core temperature has been reported to affect cognitive ability, elevate sympathetic nervous system activity, increase central fatigue, and ultimately lead to heat exhaustion/stroke if left unattended [5]. When considering that prolonged exercise in the heat has been shown to primarily be limited by thermoregulatory and fluid balance factors, it can be said that these physiological strains can negatively impact one's ability to perform intense physical work [6]. Therefore, maintenance of a normal body temperature of 37°C, and hydration status during training is important for the success of an individual participating in physical activity. As a result, previous research has investigated the impact of water temperature on performance measures as well as core temperature regulation to determine the ideal fluid choice for optimal exercise performance. Currently, four studies have shown that there is a beneficial influence from beverage temperature on endurance exercise performance [2,3,7,8]. However, different exercise protocols and environmental conditions were used. Of the four studies, two reported large and significant improvement of endurance exercise performance (13% vs. 22%, respectively) in hot and humid conditions [2,3]. In contrast to these two studies, other investigations have reported that ingesting cold beverages during exercise in a cool to moderate environment does not improve endurance performance [7,9].

There is conflicting research on the impact of cold water consumption on thermoregulation. While some studies have failed to find a correlation between cold water consumption and decreases in core temperature, others have shown a link [2,8,9]. Reasons for this discrepancy include: (1) the fluid ingestion protocols differed greatly across all studies such that some required ad libitum vs. standardized at a bolus amount (900 ml before exercise and 100 ml every 10 minutes during); (2) The low exercise intensity protocol used in some of the studies may not have produced enough heat load to raise core body temperature to the level required to achieve a statistically significant difference between the treatment groups;

(3) environmental conditions varied across all studies from 25°C to 40°C. It is important to note, studies conveying a decrease in core temperature through cold beverage consumption were conducted in hot and/or humid environments, and included the consumption of large intermittent bolus' of cold water [3,5,10].

Due to the presence of conflicting research on cold water consumption's impact on thermoregulation, the limited amount of studies investigating the influence of cold water consumption on exercise performance (especially strength and power measures) and limited general population data, it can be argued that more research on these topics is needed to determine the ideal hydration choice for the average general population exerciser.

It is the intent of the authors to investigate the effects of COLD (4°C) in comparison to room temperature (RT) water consumption (22°C) in physically fit males during a total body muscular strength and cardiovascular exercise session. To date, there is no literature investigating these effects in this population on this type of physical activity.

Methods

Subjects and screening

Subjects were recruited through a recruitment email and word of mouth to family and friends. Interested subjects that passed the screening questions were asked to attend a consent meeting. At this meeting, interested subjects learned about the study and had the opportunity to sign the consent form or decline involvement. Members of the research team facilitated the consent process. Each member of the research team had training in the protection of human subjects. They also signed a HIPAA form at this meeting and were given a copy of both the consent and the HIPAA for their records. All applicable institutional and governmental regulations concerning the ethical use of human volunteers were followed during this research.

All participants reported exercising at least five times per week with at least a six-week history of strength training three times per week. Participants were excluded for any of the following: known cardiac disease, uncontrolled hypertension, uncontrolled thyroid disease, uncontrolled diabetes, taking medications that could impair exercise performance (beta blockers), medical contraindications to exercise, an injury that prevented them from being able to complete movements in an exercise program, a doctor told them they cannot exercise or a VO2 below 35 mL/kg/min. Fifty-two healthy, physically fit males volunteered for the study. Data of seven subjects had to be removed as they started at least one exercise session in a dehydrated state. Therefore, 45 participants completed the trial (30.28 ± 5.4 yr, 1.77 ± 7.8 m, 83.46 ± 11.5 kg; 13.7 ± 4.8%BF; 49.8 ± 6.3 ml/kg/min V02) ( Table 1).

The study was approved by Compass Institutional Review Board (Mesa, Arizona) and written informed consent was obtained from each participant before enrollment.

Experimental design

The study was conducted in a cross-over, randomized design. The null hypothesis that cold water will not impact core temperature or performance measures was tested via a repeated measures analysis of variance and the criterion for significance for all tests was set at p < 0.05. Participants undertook two experimental trials that were administered in simple blocks, randomized, crossover order, followed by three performance tests: (1) 60% 1RM bench press to fatigue, (2) broad jump, and (3) time to exhaustion (TTE) on a stationary Keiser bike. As participant blinding to drink temperature is impossible, the subjects were informed that that the study outcome of interest was body temperature not performance. Participants, in randomized fashion, were given either cold (COLD) 4°C, or room temperature (RT) 22°C water provided in vacuum insulated hydration bottles with Thermos W technology during the exercise protocols and were given 12 ml/kg in equal aliquots to be consumed during the rest period between sets of exercises and to be completed before the end of the exercise session and before the first performance test. In the subsequent exercise session the participants were given the exact amount of water they consumed during the first trial. The trials were separated by a minimum of four days and no more than 21 days. Participants were asked to refrain from strenuous activity and abstain from alcohol and caffeine consumption 48 hours prior to both exercise sessions. Participants were then asked to consume 8 ml/kg body weight of water to ensure euhydration starting at 3 hours priors to training session and to be finished~45 min before arriving to facility. Each trial commenced at the same time each day to control for the effect of circadian rhythm on body temperature. The day of the exercise session, the participants were asked to ingest a biodegradable temperature sensor pill (CoreTemp capsule, Mini Mitter Co. Inc., Bend, Oregon, USA), with a small meal, 6-8 hours prior to the exercise session to allow adequate time for motility into the small intestine and to minimize the effects of swallowing cold liquids on temperature readings. Core temperature was monitored using a VitalSense telemetric physiological monitoring system (Mini Mitter Co. Inc., Bend, Oregon, USA). To control for the effect of diet and hydration on exercise performance the participants were asked to arrive at the training facility 1.5 hours prior to their scheduled exercise sessions to receive a standardized meal of 1.0 g carbohydrate/kg body weight and 0.4 g protein per kg lean body mass in the form of a shake to be finished within ½hour prior to commencing the exercise session. Upon arrival to the training facility, 1.5 before commencing exercise session, the participants were asked to provide a urine sample cup for urine specific gravity analysis (USG) using Roche USG 10 urine strips. If a participant was dehydrated they were instructed to continue the 8 ml/kg body fluid protocol and re-test 45 minutes later to confirm they were hydrated. Core temperature was taken at baseline and every 15 minutes with the VitalSense telemetric physiologic monitoring system (Mini Mitter Co. Inc., Bend, Oregon, USA). Body weight and USG were taken prior to the exercise session and immediately after performing the TTE test.

During both trials, each participant was assigned an identification number which was placed on their own vacuum insulated individual Thermos W brand bottle. They were instructed to only drink from their own Thermos W brand bottle. During the cold trial, the drinks were cooled using a domestic refrigerator and maintained at 4°C. During the RT trial, drinks were maintained at 22°C. Temperature of the water was measured using a standard long glass mercury thermometer (Indigo W Instruments, Waterloo, ON, Canada). After the initial exercise session was completed, participants were given a five minute rest before commencing the performance tests. The performance tests were administered by the same person/investigator to avoid potential bias when providing encouragement. The performance tests included: flat bench to fatigue at 60% of one rep max (RM) to determine muscular endurance [11], broad jump to determine force and power production [12] and time to exhaustion (TTE) on stationary bicycle to determine cardiovascular endurance. For the broad jump test the subjects were asked to jump as far as they could horizontally on a flat surface 2 times. Both jumps were averaged. The endurance test (TTE) was administered using a modified McArdle (1973) bike protocol. The protocol was based on the use of the Keiser stationary bike. The watts are based on the gear and the participants had to hold 80 rpms at each gear. The ramping was adjusted to fit the gearing designed of the Keiser stationary bike. We used it as a sub max test based on maintaining 80 rpms. If the participants could not keep above 80 rpm then the participant was instructed to stop and gear, time and Core temperature were recorded.

Preliminary measurements

Subjects completed the baseline testing at least four days prior to their first testing day. After the completion of the baseline testing, subjects were briefed on the study design and the drinking and exercise protocol. They Values represent mean ± standard deviation.

were also able to familiarize themselves with the performance tests that they were to perform at the end of their exercise sessions. On their first trip to the facility, the participants' weight, height, and 7-site skin fold thickness were measured. Skin fold thickness measurements were taken at seven sites (triceps, subscapula, chest, mid-axillary, abdominal, iliac create, front thigh) using calipers (Lange Skin fold Caliper, Beta Technology, Santa Cruz, CA). Percent body fat was determined using the Siri equation and body density was calculated with the Jackson-Pollock equation. After anthropometrics were taken participants proceeded to the flat bench press to determine the bench press 1RM performance test. Subjects were asked to bench press 60% of their 1RM as many times as they could. During the test subjects had a spotter behind them to take the weight once the subject fatigued. The participants were also fitted and assigned a stationary bike for the time to exhaustion performance test. Lastly, estimated peak oxygen consumption was assessed to determine fitness levels using a treadmill (Woodway, Waukesha, WI) via an 8-12 minute ramping protocol during which the American College of Sports Medicine graded walking equation was applied (American College of Sports Medicine, 2010). During the submaximal protocol, heart rate and ventilation were measured using the iMett system (Woodway, Waukesha, WI). Ventilation was measured with a flow meter and mask (Hans Rudolph) from which a ventilatory threshold was determined. Adjusted ACSM max norms to 95%, as a submax test was administered. A VO2 of ≥35 ml/kg/min was considered moderately fit and approved to participate in the study.

Exercise protocol

Subjects partook in an exercise session that combined both strength and aerobic exercise. The exercise session was supervised and led by a Performance Specialist at Athletes' Performance. The subject to trainer ratio did not exceed 10: During the exercise session, subjects were asked to drink their assigned beverage during rest periods between exercise sets. Consumption of water during the exercise session was ad libitum and the participants were instructed to completely finish the water by the end of the exercise session. If water was left-over it was recorded (only four participants did not consume all water). Core temperatures were measured every 15 minutes during the session via the VitalSense telemetric physiologic monitoring system (Mini Mitter Co. Inc., Bend, Oregon, USA) the researcher held near the subject's body.

Environmental conditions

Wet and dry bulb temperatures were taken during each trial. Wet bulb temp averaged 14.9°C and 15°C (p=0.6273) for both RT and COLD trials respectively and dry bulb temp averaged 24°C and 24.2°C (p=0.1179).

Statistics

A statistical analysis was performed by the authors. Data were ensemble averaged across all 45 participants and standard deviations were calculated. The study design was a randomized cross-over study. Paired t-tests were used to compare performance between conditions and to compare the absolute change in body temperature from the pre-exercise session to the post-exercise session. A repeated measures analysis of variance was used to test for a significant effect of group, time and the interaction between the two during the hour of exercise. Tukeys post-hoc tests were used to determine significant differences between time points. Criterion for statistical significance was set at p<0.05.

Results

Body temperature in the COLD condition changed 2% from baseline to post-exercise session (37.06 ± 0.72°C to 37.79 ± 1.16°C). Body temperature from baseline to post-exercise session changed 3% in the RT condition (36.85 ± 0.98°C to 37.94 ± 0.82°C). Although both groups significantly increased their core temperature over the course of the training and testing session (p<0.001), participants in the COLD water trial had a significantly (p=0.024) smaller rise in core temperature (0.83°± 0.63°) over the duration of the trial in comparison to RT (1.13°± 0.78°) Table 2.

There was a significant effect for time such that body temperature increased in both groups over the course of the 60-minute exercise session (p<0.001). There were no significant interactions between condition and time (p=0.380) such that subjects behaved similarly to the effect of exercise over time, regardless of water temperature condition. The post-hoc analysis of changes in body temperature over time indicates that, when drinking RT water, a significant increase in body temperature was observed after 15 minutes. In the COLD condition, the increase in body temperature was delayed until 45 minutes. There were no significant interactions between condition and time (p=0.141) such that subjects behaved similarly to the effect of exercise over time, regardless of water temperature condition. Figure 1 shows the change in core temperature from baseline at each 15-minute time point.

There were no significant differences between the groups (during the RT condition and COLD condition) in body mass (p=0.919). There was, however, a significant effect of time (p<0.001) such that body mass significantly decreased from the pre-exercise to post-exercise time point in both groups. In the COLD condition body mass decreased from 85.2 ± 11.6 kg to 84.8 ± 11.3 kg and in the RT condition body mass decreased from 85.2 ± 11.6 kg to 84.7 ± 11.3 kg. There were no significant interactions (p=0.223) and subjects did not behave differently to the conditions at the time points.

Additionally, there were no significant differences in hydration status between the COLD and RT conditions at either the baseline time point (p=0.549) or the postexercise time point (p=0.368). Since atmospheric conditions were also held constant, the authors can infer that water intake was not different between COLD and RT conditions. Both groups experienced a significant decrease in hydration status from beginning of the exercise session to post-exercise session in both conditions (p<0.0001). There were also no significant interactions between groups and the pre to post-training time point (p=0.209) Table 3.

When investigating measures of performance, there were no significant differences between COLD and RT groups for two of the three performance tests: broad jump (p=0.465) or TTE (p=0.735). Subjects performed broad jumps of 2.17 ± 0.27 m and 2.15 ± 0.25 m in the COLD and RT conditions, respectively. TTE was 638 ± 187 seconds and 643 ± 189 seconds for the COLD and RT conditions, respectively. However, even though there was not a significant improvement demonstrated, 49% of the participants improved in the broad jump and 51% in the TTE respectively during the COLD. Subjects participating in the RT condition were able to perform significantly more bench press repetitions to failure than when they participated in the COLD condition (p=0.046). During the COLD condition 22 ± 3.5 repetitions (range: 15-30) were performed and during the RT condition 22.7 ± 3.2 repetitions (range: 17-31) were performed. This was a small, albeit significant, improvement; however, a calculation of an effect size [11] indicates that this would be a negligible to small effect (d=0.2) Table 4.

Discussion

Current literature reports that a rise in core temperature can significantly impede performance [1]. Endurance exercise capacity has specifically been found to be affected by a hot environment, which leads to a rise in core temperature and increased dehydration [13][14][15]. Burdon et al., found that consuming cold beverages according to the ACSM guidelines, in euhydrated subjects, enhanced endurance performance in a hot environment [1]. In this study subjects consumed, at each separate trial, a sports drink at the following temperatures and times: 37°C and 4°C consumed every 10 minutes (2.3 mL/kg) and 30 mL ice puree (−1.0°C) every 5 minutes with holding it in the mouth for at least 30 seconds before swallowing during the 90 minute exercise session. Even though this study concluded that there was an improvement in exercise performance with the cold beverage and ice puree, this study has a confounding factor in that it used a sports drink instead of plain water. One could hypothesize that the extra fuel (carbohydrate) and electrolytes acted as ergogenic aids and combined with being cold or alone enhanced performance.

Most studies have addressed a rise in core temperature with a dehydrated population during hot and/or humid conditions over a longer period of time [7,8]. It is important for the elite and physically fit individuals alike to maintain a normal body temperature (37°C). Some literature suggests that consuming large amounts of cold fluid during exercise would allow the body to have increased capacity to store heat (i.e. heat sink), thereby reducing heat gain during exercise.

Seven studies have investigated the effect of beverage temperature on core body temperature during exercise [2,3,[6][7][8][9][10], however, the methodologies and protocols vary widely. Four of the seven studies concluded that consuming a cold beverage during exercise resulted in a lower core temperature at the end of the exercise session compared to consuming a warm beverage. Our study was unique in that at the time the trial started there had not been a published paper on the effects of COLD vs. RT water during a traditional exercise session (60 minutes) in physically fit individuals, in a moderate climate. No studies have investigated the effect of cold water on thermoregulation and a traditional exercise session combining both strength and endurance training in physically fit individuals.

In our study we found that while ingesting the COLD water, subjects were able to significantly mediate their rise in core temperature over the entire duration of the study (ie, when comparing the magnitude of the change in core temperature, subjects who drank COLD water had a significantly lower change in core body temperature than subjects who drank RT water (p=0.024)). Subjects finished their water allotment at the end of the exercise session before commencing the performance tests and the core temperature mediation continued in the COLD trial through the end of the performance tests (p=0.024). Although there was not a statistically significant improvement in the broad jump or TTE performance tests while drinking the cold water, approximately 50% of the subjects performed better during the COLD trial in both tests. As for the bench press performance test, even though participants were randomized, of the 45 participants, 26 performed the bench press under the RT condition on their second exercise session. The significantly better results during the RT may have been skewed due to the fact that this was their second time performing this type of test during the RT condition and may have known more about what to expect and were motivated to improve their reps to fatigue from their previous test. Another possible explanation for the bench press results is that the calculated effect size was low. However, for both athletes and physically fit individuals, the ability to train longer and harder is important. For athletes, a few seconds can mean the difference between first and second and one last burst of power can mean scoring the winning points. Therefore, the improvements for the subjects are relevant to their environments.

The temperature of the COLD water trial was chosen to be representative of water stored in a general household refrigerator and RT was chosen to be representative of the room temperature. We found that the COLD water trial resulted in significantly less of a change in body temperature from pre-exercise session to postperformance testing after a 60 minute exercise (p=0.024). The change was 1.1°C (±0.8) in the RT condition and 0.8°(±0.6) in the COLD condition; therefore, we have found that ingestion of a cold beverage significantly improves the body's ability to maintain core temperature. These findings are similar to that of   [6,9,10], however, these studies were conducted in the heat at 40°C, 35°C and 40°C, respectively. Although there was not a significant benefit of COLD water in the performance tests measured, the COLD water clearly helped the participants to maintain core body temperature during exercises, which may have other positive impacts. Current literature also reports that a rise in core temperature can significantly impede performance [1].

There is debate as to the core temperature threshold where a decrease in performance starts to occur. Core temperatures at fatigue have been reported to be between 38.4°C and 40°C [2,16]; however, many studies report that exhaustion occurs well below 40°C and that the variability may be due to training status, body composition, or various core temperature collection methods [2]. Burdon et al., evaluated performance during a 90 minute steady state exercise session in the heat and reported final rectal temperatures of 38.3°C for their COLD group and 38.5°C for their thermoneutral group [1]. In our study, the maximum core temperature readings were at 37.98°C ± .51 and 37.89°C ± .64 for the RT and COLD groups respectively, which are lower than studies done in the heat and below previously reported thresholds for fatigue. Although core temperature was significantly different from pre-exercise session to post-testing, a possible reason why we did not find significant improvements in performance measures may be due to the fact that the participant's core temperatures did not reach a high enough temperature for the COLD water to create a performance impact. Therefore, the impact of COLD on performance measures may be more evident at higher temperatures.

Most studies have addressed rise in core temperature with a dehydrated population during hot and/or humid conditions over a longer period of time [6,7]. Future research may address the effects of a cold water trial in a 90-120 minute exercise session on rise in core temperature. Even though there was not a significant improvement for subjects when drinking COLD water prior to performance tests, overall performance measures may not be sensitive enough to measure the small changes that COLD water may have. Moreover, if the same study was done with dehydrated subjects or in a hot/humid environment, there may have been a greater performance benefit exhibited.

The repeated measures analysis of variance showed no significant interactions (p=0.286), indicating that subjects did not perform significantly different over time in one condition than in the other. There was also no significant effect of group (p=0.619). There was, however, a significant effect of time (p<0.001).

There were two limitations to this study. Environmental conditions of temperature and humidity were controlled throughout the study at a constant value. Secondly, the total duration of the study was less than 90 minutes. COLD water may provide the most benefits in stressful environmental conditions (higher temperatures and humidity levels and/or longer duration of exercise) [1], but the current study did not test these independent variables.

Conclusion

This study found that drinking COLD water during a traditional exercise program in a moderate climate can have a significant impact on the body's ability to maintain core temperature. The benefits for reducing the rise in core temperature did not translate to significant improvements in power, aerobic endurance, and muscular endurance-based exercises. Secondary to the significant impact of the COLD water on the body's ability to maintain core temperature, it is still recommended that both, athletes and physically fit individuals, consume COLD beverages during exercise. Delaying a rise in core temp may have positive impact on exercises not investigated in this study, but it's unlikely to have negative effects. It is recommended that further work be done to further investigate the impact of COLD water consumption on strength and power performance in an extreme environment, with dehydrated subjects, or specific exercise bouts of longer duration.

Competing interests

This study was funded by Thermos L.L.C. (Schaumburg, IL, USA).

Figure 1
1Comparison of core temperature increase over the duration of the trial. a p<0.05.

Table 1
1Summary of participant characteristicsVariable

Age
30.28 + 5.4

Anthropometric characteristics

Height (m)
1.77±7.8

Mass (kg)
83.46±1.5

Body Composition

Body fat %
13.7±4.8

Fitness

Estimated Peak VO 2 (ml/kg/min)
49.69±6.3

Table 2
2Core temperature over duration of the trialCore temperature (°C)

Table 3
3Hydration status during training Values represent mean ± standard deviation. b p < .05. Criterion for statistical significance was set at p<0.05. et al., Lee et al. and Szlyk et al.COLD
RT

Table 4
4Summary of performance test resultsValues represent mean ± standard deviation. p< 0.05. Criterion for statistical significance was set at p<0.05.Test
COLD a
RT a
% of subjects who had improved
performance during COLD

Bench (reps)
22 ± 3.5
22.73 ± 3.2 b
14%

Broad Jump (m)
2.17 ± 0.27
2.15 ± 0.25
49%

TTE (seconds)
638 ± 187
643 ± 189
51%

a

b

http://www.jissn.com/content/9/1/44
AcknowledgementsWe would like to thank the participants that participated in this study as well as our fellow colleagues, at Athletes' Performance who assisted with data collection. This study was funded by Thermos L.L.C., (Schaumburg, IL, USA). All researchers involved independently collected, analyzed, and interpreted the results from this study and have no financial interests concerning the outcome of this investigation. The results from this study do not constitute endorsement by the authors.Authors' contributions DL was the study coordinator and was involved in research design, data collection and analysis, as well as manuscript preparation. ACP and was involved in research design, analysis and manuscript preparation. SS assisted in research design. ER assisted in data analysis and manuscript development. All authors read and approved the final manuscript.
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Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution. Lafata, Journal of the International Society of Sports Nutrition. 944The effect of a cold beverage during an exercise session combining both strength and energy systems development training on core temperature and markers of performance. Submit your manuscript at www.biomedcentral.com/submitCite this article as: LaFata et al.: The effect of a cold beverage during an exercise session combining both strength and energy systems development training on core temperature and markers of performance. Journal of the International Society of Sports Nutrition 2012 9:44. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit