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A metabolomics perspectiveon 2 years of high‑intensity training
in horses
L. Johansson 1, S. Ringmark 1, J. Bergquist 1,2, E. Skiöldebrand 3 & A. Jansson 1*
The plasma metabolomic profile of elite harness horses subjected to different training programmes
was explored. All horses had the same training programme from 1.5 until 2 years of age and thenhigh-intensity training was introduced, with horses divided into high and low training groups.
Morning blood samples were collected at 1.5, 2, 2.5 and 3.5 years of age. The plasma was analysedusing targeted absolute quantitative analysis and a combination of tandem mass spectrometry,flow-injection analysis and liquid chromatography. Differences between the two training groups wereobserved at 2 years of age, when 161 metabolites and sums and ratios were lower (e.g. ceramide andseveral triglycerides) and 51 were higher (e.g. aconitic acid, anserine, sum of PUFA cholesteryl esters
and solely ketogenic AAs) in High compared with low horses. The metabolites aconitic acid, anserine,
leucine, HArg synthesis and sum of solely ketogenic AAs increased over time, while beta alaninesynthesis, ceramides and indole decreased. Therefore high-intensity training promoted adaptations
linked to aerobic energy production and amino acid metabolism, and potentially also affectedpH-buffering and vascular and insulin responses.
Metabolomics studies on the effects of sport and exercise in humans have been performed for decades, e.g. abibliometric review published in 2022 located 122 relevant papers in databases using keywords associated with
exercise and m­ etabolomics1. However, the review showed that untargeted metabolomics studies and studies on
short-term effects of exercise have dominated and that improvements in study design, method standardisationand data interpretation are needed to improve the quality of metabolomics studies. Lack of high-quality studies
in this area was also highlighted in a study that identified a need for more cross-sectional and exercise training
studies to improve understanding of the response to chronic exercise w­ orkloads2.
In the review referred to a­ bove1, metabolomics studies were classified into short-term (≤ 1 week) and longterm (> 1 week). From a practical exercise perspective, these periods are remarkably short and the results obtainedin such studies may not accurately represent the effects achieved by the years of training commonly required
to become an elite athlete, both in human sports and in equine athletes. Race and harness horses are elite athletes, but there is a lack of metabolomics studies of horses in training covering periods longer than 12 ­weeks3–6.
Accordingly, there has been no longitudinal study on the metabolomics of horses subjected to true elite training,from the start of training until fit for racing. In addition, there have been no metabolomics studies to evaluate
different training programmes.
The aims of this study were thus to: (1) explore differences in the metabolomic profile in plasma of young
elite harness horses kept under standardised conditions and subjected to two different training programmes for
2 years; and (2) determine changes in the metabolomic profile over the training period. The starting hypotheses
were that the metabolic profile of horses differs between training programmes and that it changes substantiallyover time. Targeted metabolomics was performed and a hypothesis-generating approach was applied. To ourknowledge, this is the first absolute quantitative metabolomics study in race horses subjected to a long-term
exercise programme (2 years).

1

Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences,
P.O. Box 7011, 750 07 Uppsala, Sweden. 2Department of Chemistry‑BMC, Analytical Chemistry and
Neurochemistry, Uppsala University, P.O. Box 599, 751 24 Uppsala, Sweden. 3Department of Biomedical Sciences
and Veterinary Public Health, Swedish University of Agricultural Sciences, P.O. Box 7028, 750 07 Uppsala,Sweden. *email: anna.jansson@slu.se
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Material and methods

The study was performed at the Swedish National Centre for Trotting Education at Wången. The protocol wasapproved by the Ethics Committee, Umeå, Sweden (D.nr:A90-10, 2010-09-14) and all experiments were performed in accordance with relevant guidelines and regulations. The reporting of the experiments are in accordance with the ARRIVE guideline.

Horses and management

Sixteen Standardbred 1.5-year-old male horses from four breeders were included in the study. They entered thestudy in September 2010 and it ended in December 2012. All horses were castrated in December 2010 or January
2011. They were housed in individual boxes for about 16 h a day from Monday to Thursday/Friday, while for the
rest of the time they were kept in a paddock with shelter. Their diet consisted of haylage with known energy andnutrient content and both haylage and water were available ad libitum in the paddock and the box. The diet was
supplemented with pelleted lucerne (Krafft AB, Malmö, Sweden), a vitamin and mineral supplement (Krafft AB,
Malmö, Sweden) and NaCl to meet the nutrient requirements of horses of this age and training i­ ntensity7. Daily
intake of metabolisable energy was 123 ± 16 MJ/100 kg body weight (BW) and daily intake of crude protein was
decreased over time as the requirement for growth decreased (428–354, 373–321 and 321–234 g/100 kg BW as
1-, 2- and 3-year-olds, respectively). Results of all nutrient analyses of haylage and more data on feed, energy
and nutritional intake can be found in previous p­ ublications8,9. Body condition was scored every other monthand was 4.8–5.1 (9-point scale) throughout the s­ tudy9.

Training

The training programmes were planned together with three professional trainers and was based on common
practise with respect to training methods and age of the horses. From autumn as 1.5-year-olds to spring as 2-yearolds, all horses were exposed to the same training programme, which began with breaking in the autumn andprogressed to trotting with a jog cart 4 times/week. Speed was gradually increased to 5.6 m/s and distance to
5–7 km. In the middle of March as 2-year-olds, high-intensity training (i.e. heart rate > 180 bpm, Polar CS600X,
Polar Electro, Finland) was introduced and the horses were divided into a High training group or a Low training
group. These groups were balanced with respect to breeder and parameters known to affect performance, such as
age in days, genetic potential (sire and mean pedigree index estimated with the Best Linear Unbiased Prediction(BLUP) method), percentage of French ancestry, inbreeding coefficient, height at withers, abnormal radiographic
findings, conformation and proportion of type IIA/type IIB muscle fi­ bres10. The High group underwent a training
programme designed by a group of professional trainers that consisted of two high-intensity training sessions
per week involving heat training, interval training or uphill interval training (Table 1), and 1–2 jogging sessions.
The Low group had the same training programme as the High group, but with 30% lower high-intensity training
distance. For example, during interval training horses in the High group performed six repetitions and horses
in the Low group performed only four repetitions (Table 1). Similar velocity was aimed for with both training
groups. More information about actual training distances and training sessions can be found in a previous­publication10. All horses were subjected to exercise tests and an improvement in the cardiovascular response
was observed as well as in the lactate threshold during the summer as 3-year-olds8,10.

Blood sample collection

Blood samples were collected on four different occasions between 2010 and 2012 (December as 1.5-year-olds,
July as 2-year-olds (14 weeks after high-intensity training was introduced), December as 2.5-year-olds, andDecember as 3.5-year-olds). All samples were collected in the morning (05.00–06.00 h, minimum 15 h after a
training session) in each horse’s box, using the vacutainer technique with blood extracted into lithium heparintubes (10 mL) from the jugular vein. Immediately after collection, all blood samples were centrifuged at room
temperature (10 min, 2700 rpm, 920×g) and then the plasma was frozen at − 20 °C for later analyses.

Metabolomics analysis using mass spectrometry

The samples were analysed at the Mass Spectrometry Based Metabolomics Facility in Uppsala, Sweden, in 2021.
The MxP® Quant 500 kit (Biocrates, Innsbruck, Austria) was used for targeted measurement of different classesof metabolites, following the manufacturer’s recommended protocols. This kit enables targeted absolute quantitative analysis of up to 630 metabolites, including amino acids (AA), biogenic amines, acylcarnitines, glycerophospholipids, sphingolipids and sum of hexoses, allowing for comprehensive assessment of a broad range ofanalytes and metabolic pathways in a single targeted assay. Sample analysis involved a combination of tandem

High group (n = 8)

Low group (n = 8)

Training type2 years old

3 years old

2 years old

3 years old

Heat

1–2*1600 m

2–3*1600 m

1–2*1100 m

2–3*1100 m

Interval

6*500–700 m

6*700 m

4*500–700 m

4*700 mUphill interval

6*600 m

4*600 mTable 1.  Weekly high-intensity training (heart rate > 180 bpm) sessions in Standardbred horses divided into
two training groups (high and low).

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mass spectrometry (MS/MS), flow-injection analysis (FIA) and ultra-high performance liquid chromatography(UPLC). To ensure accurate quantification, chemically homogenised and isotope-labelled internal standard
mixture (IS) was used. Sample preparation began with addition of 10 µL horse plasma to each well on a 96-wellplate containing IS dried under a nitrogen stream using a positive pressure manifold (Biostage, Uppsala, Sweden),together with 50 µL 5% phenyl isothiocyanate solution. The plate was incubated at room temperature for 1 h
and then dried again. To extract the metabolites, 300 µL 5 mM ammonium acetate in methanol were pipetted
onto a filter and incubated for 30 min. The extract was eluted into a new 96-well plate using positive pressure.
For further UPLC-MS/MS analyses, 150 µL extract were diluted with an equal volume of ultra-pure water. For
FIA-MS/MS analyses, 10 µL extract were diluted with 490 µL FIA solvent (provided by Biocrates). After dilution,
UPLC-MS/MS and FIA-MS/MS measurements were performed. For chromatographic separation, an UPLC
system coupled to a TQS mass spectrometer in electrospray ionisation (ESI) mode was used. Data were recorded
using the Analyst Mass Link software and transferred to the MetIDQ software (version Oxygen-DB110-3005),
which was used for further data processing. All metabolites were identified using isotopically labelled internal
standards and by multiple reaction monitoring (MRM) using optimised MS conditions as provided by Biocrates.
Concentrations of metabolites were quantified using a seven-point calibration curve, depending on the metaboliteclass. The metabolites were used to calculate different sums and ratios and are listed in Supplementary Material
SM1 and SM2. The total plasma protein concentration was analysed in all samples prior to the metabolomics
analysis, in order to ensure that freeze drying had not occurred during storage.

Statistical analyses

Metabolites, sums and ratios of metabolites which were below the limit of detection (LOD) for all horses andtime points were excluded from the analysis. For metabolites which were below LOD for one time point but weredetectable at another time point, a value corresponding to 10% of the LOD cut-off value was used. Sums andratios of metabolites which had fewer than four values above LOD per training group (in analyses of training
groups) or per age (in analyses of change over time) were removed. In analyses of training group, a linear model
which included the effect of training group was used and the four different ages were run separately. In analyses ofchanges over time, a linear model which included the effect of training group and age was used and the samplingages (2, 2.5 and 3.5 years) were compared with the age at which horses entered the study (1.5 years). A total of 624
metabolites and 196 sums and ratios (n = 820) were analysed. All statistical analyses were performed in R (v4.1.2,
R Core Team, 2022). Differences were considered significant at p < 0.05. All values were log-transformed. The pvalues were adjusted using the false recovery rate (FDR) m­ ethod11, where all p values were ranked in ascendingorder and assigned a ranking number, and then the adjusted p value was calculated as: p value x (Total number oftests/Ranking number). A volcano plot was made by plotting − ­log10(Adjusted p value) on the y-axis and l­ og2(Foldchange) on the x-axis. Fold change was calculated for each metabolite by dividing mean value for the High groupby mean value for the Low group. All p values presented below are adjusted p values unless otherwise stated.

Results

Differences between training groups

Quantitative MS analyses of the 820 metabolites, ratios and sums of metabolites revealed significant differences
between the training groups when the horses were 2 years old, but not at other ages (Table 2). At 2 years of age,
161 metabolites had lower values and 51 had higher values in the High group compared with the Low group(Fig. 1). Quantitative measures for all metabolites, ratios and sums of metabolites included in statistical analyses
can be found in SM1.
The 10 most significant metabolites with higher concentrations in the High group compared with the Low
group included two metabolites related to AA, two cholesteryl esters (CEs), one carboxylic acid, one triglyceride(TG), and four sums and ratios. The 10 most significant metabolites with lower values in the High group compared with the Low group comprised of one ceramide (Cer) and nine TG metabolites (Table 3).

Differences between time points

Compared with age 1.5 years (before the high-intensity training started), multiple metabolites differed significantly in concentration at 2, 2.5 and 3.5 years of age (Table 4). At 2 years of age, 133 metabolites had higher values
and 129 had lower values than at 1.5 years of age (Fig. 2A). At 2.5 years of age, 176 metabolites had higher values
and 218 had lower values than at 1.5 years of age (Fig. 2B). At 3.5 years of age, 143 metabolites had higher values
and 314 had lower values than at 1.5 years of age (Fig. 2C). Quantitative measures for all metabolites, ratios andsums of metabolites included in the statistical analyses can be found in SM2.

No. of metabolites included in statistical analyses
Age

No. analysed

1.5 years old

2 years old

2.5 years old

3.5 years old

Metabolites

624

532

532

532

532

Sums and ratios

196

136

128

134

134

0

212

0

0

FDR-adjusted p values < 0.05

Table 2.  Number of metabolites and sums and ratios of metabolites included in statistical analyses for thedifferent sampling ages, and number that were significantly different (FDR-adjusted p < 0.05) at different ages.

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TG.18.1_36.3.
TG.18.1_36.2.

−log10(Adjusted P−values)

7.5

5.0

TG.20.1_34.2.
TG.18.2_35.2.
TG.18.1_35.2. TG.18.2_32.2. TG.16.1_34.2.

Anserine CE.18.2.
CE.18.1.
AconAcid TG.18.1_38.5.
Anserine.Synthesis
Sum.of.PUFA.CEs
Met.SO
Sum.of.Solely.Ketogenic.AAs

Cer.d18.2.22.0.
TG.16.0_38.2.
TG.17.1_34.2.

Ratio.of.Glycosyl.Cer.to.Cer

2.5

0.0

−5

log2(Fold Change)0

Figure 1.  Volcano plot of plasma metabolites present in higher (red), lower (blue) and unchanged (black)concentrations in plasma samples from the High group compared with the Low group of 16 Standardbred
horses at 2 years of age. Upper left quadrant contains adjusted p values < 0.05 and fold change < − 0.5, upper rightquadrant adjusted p values < 0.05 and fold change > 0.5. Abbreviations: aconitic acid (AconAcid), cholesterylester (CE), methionine-sulfoxide (Met.SO), ceramides (Cer), polyunsaturated fatty acids (PUFA), amino acids(AA), triglyceride (TG).

Higher in high group

Lower in high group

Metabolite

FDR p value

Metabolite

FDR p value

Aconitic acid

1.5e−04

Cer.d18.2.22.0

1.5e−04

Anserine

1.4e−04

TG.16.0_38.2

1.4e−04

Anserine Synthesis

1.8e−04

TG.16.1_34.2

1.5e−04

CE.18.1

1.5e−04

TG.17.1_34.2

1.5e−04

CE.18.2

1.4e−04

TG.18.1_35.2

1.5e−04

Methionine-Sulfoxide

3.0e−04

TG.18.1_36.2

3.0e−09

Ratio of Glycosyl Cer to Cer

3.7e−04

TG.18.1_36.3

2.2e−09

Sum of PUFA CEs

2.0e−04

TG.18.2_32.2

1.4e−04

Sum of Solely Ketogenic AAs

3.0e−04

TG.18.2_35.2

1.4e−04

TG.18.1_38.5

2.0e−04

TG.20.1_34.2

1.4e−04

Table 3.  Plasma metabolites with the most significant FDR-adjusted p values for the difference in meanvalues for 16 2-year-old Standardbred horses divided into two different training groups (High and Low). CE
Cholesteryl ester, Cer ceramides, PUFA polyunsaturated fatty acids, AA amino acids, TG triglyceride.

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No. of metabolites included in statistical analyses
Age

No. analysed

2 years old

2.5 years old

3.5 years old

Metabolites

624

524

510

509

Sums and ratios

196

137

132

133

262

394

457

FDR-adjusted p values < 0.05

Table 4.  Number of metabolites and sums and ratios of metabolites included in statistical analyses ofthe different sampling ages (2, 2.5 and 3.5 years) compared with 1.5 years of age, and number that weresignificantly different (FDR-adjusted p < 0.05) at different ages.

The 10 most significant metabolites with higher concentrations at 2, 2.5 and 3.5 years of age compared with
1.5 years of age are shown in Table 5. At 2 years of age, nine TG metabolites and one carboxylic acid showed
higher values than at 1.5 years of age. At 2.5 years of age, one AA, one AA-related compound, one carboxylicacid, three TG metabolites and four sums and ratios of metabolites had higher values than at 1.5 years of age. At
3.5 years of age, one AA, one AA-related compound, one carboxylic acid, one TG metabolite, one carnitine andfive sums and ratios of metabolites had higher values than at 1.5 years of age.
The 10 most significant metabolites with lower concentrations at 2, 2.5 and 3.5 years of age compared with
1.5 years of age are shown in Table 6. At 2 years of age, one carboxylic acid, one biogenic amine, one diglyceride(DG), two phosphatidylcholines (PC), one AA and four sums and ratios of metabolites showed lower values thanat 1.5 years of age. At 2.5 years of age, two CE, two Cer, one DG, one indole, three TG and one ratio of metabolites
had lower values than at 1.5 years of age. At 3.5 years of age, two CE, two Cer, one DG, one indole, one ratio of
metabolites, two TG and one fatty acid (FA) had lower values than at 1.5 years of age.

Discussion

This study evaluated the metabolic profile in horses subjected to two different long-term training programmes
until fit to race as 3.5-year-olds. To our knowledge, this is the first long-term evaluation of the metabolic profile
in young harness horses exposed to long-term training.
Comparison of the two training groups (High and Low) revealed significant differences in metabolic profileat 2 years of age. This was approximately 3.5 months after the horses had started high-intensity training, in which
the Low group was subjected to 30% shorter distances compared with the High group, and it coincided withobservations of significant differences in cardiovascular responses between training g­ roups10. At 2 years of age,leucine and solely ketogenic AA (leucine plus lysine) levels were significantly higher in the High group comparedwith the Low group (SM1) and significantly higher over time at all ages compared with 1.5 years of age (SM2).
This is in agreement with pre-exercise results from a 12-week high-intensity training study by Klein et al.4 However, in another study with 18 weeks of high to moderate training intensity, no effect on plasma leucine levels at
rest was ­observed12. This difference may be due to different training intensities or to high training intensity being
required for this change to be manifested. Branched-chain amino acids (BCAA) are involved in aerobic energy
metabolism in skeletal muscle although only as a minor contributor, i.e. about 1–15% during ­exercise13. It has
also been shown that leucine stimulates protein synthesis in skeletal muscles by hyperphosphorylating proteins
involved in mRNA translation, which leads to both an increase in activity and synthesis of these ­proteins14. It
is also possible that leucine stimulates glycogen ­synthesis15, which is of relevance for tissue development and­performance16. The results in the present study support the claim that leucine is an important metabolite forexercise performance, since it was altered depending on training group and also over time.
Anserine and anserine synthesis (anserine divided by carnosine) levels were significantly higher in the Highgroup compared with the Low group. The levels of both also increased significantly over time (SM2), indicating aneffect of both intensity and training period. Anserine is a methylated variant of carnosine and in horses anserineand carnosine can be found in neuronal tissue and skeletal and heart ­muscle17. It is believed that carnosine andanserine play a major role in maintaining intracellular buffering and pH-balance17,18, but it may also have antioxidant, anti-glycation and anti-lipoxidation f­ unctions17. All of these activities could be of relevance for exercise
performance. There is an obvious need for pH-buffering in the exercising Standardbred horse, because duringhigh-intensity exercise lactic acid is produced by the skeletal muscle, resulting in high muscle and plasma lactate
levels (> 70 mmol/kg and > 30 mmol/L, ­respectively19), as well as lowered plasma pH during exercise at the lactate­threshold20. The importance of lactate and proton removal from muscle has been s­ tudied21 and in Standardbred
horses efficient (monocarboxylate) transporters have been identified in both muscle and red blood ­cells22. Whiletransport of lactate into red blood cells is a passive means (sink) to increase the muscle-plasma concentration
gradient, oxidation of lactate in the liver and inactive muscles is more e­ fficient22. Lactate is oxidized to pyruvate,
which can be metabolized through the tricarboxylic acid cycle or converted to glucose through gluconeogenesis. The role of lactate in the delivery of oxidative and gluconeogenic substrates and for cellular signalling (thelactate shuttle ­concept23) is probably of major importance for the development and performance of race horses.
Several of the changes in aerobic energy metabolism detected could in principle be triggered by lactate, but thatneeds further investigation. There was no significant difference in carnosine itself in this study, but there wasa significant decrease in beta alanine and beta alanine synthesis (beta alanine divided by carnosine) levels in
the High group (SM1) and over time (SM2). Beta alanine is the rate-limiting factor for synthesis of carnosine
within muscle, and in humans beta alanine supplementation has positive effects on exercise performance inScientific Reports |(2024) 14:2139 |https://doi.org/10.1038/s41598-024-52188-z

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Figure 2.  Volcano plot of plasma metabolites with Higher (red), lower (blue) and unchanged (black) valuesat (A) 2 years of age, (B) 2.5 years of age and (C) 3.5 years of age compared with 1.5 years of age for 16
Standardbred horses in training. Upper left quadrant contains adjusted p values < 0.05 and fold change < − 0.5,
upper right quadrant adjusted p values < 0.05 and fold change > 0.5. Note different scale on the y-axis in panel
A (0–10) compared with B and C (0–40). AconAcid aconitic acid, AA amino acids, AABA alpha-aminobutyricacid, b.Ala beta alanine, C0 carnitine, Cer ceramides, CE cholesteryl ester, DG diglyceride, ADMA asymmetric
dimethylarginine, DiCA dodecanedioic acid, FA fatty acid, HexCer hexosylceramides, HArg homoarginine, Leu
leucine, PC phosphatidylcholines, SDMA symmetric dimethylarginine, TG triglyceride, Val valine.
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2 years of age

2.5 years of age

3.5 years of age

Metabolite

FDR p value

Metabolite

FDR p value

Metabolite

FDR p value

DiCA.12.0

1.1e−08

Aconitic acid

9.4e−13

Aconitic acid4.8e−15

TG.16.0_34.2

1.7e−08

Anserine

5.2e−12Anserine

8.6e−16

TG.18.0_34.3

1.1e−08

Anserine synthesis

1.1e−12Carnitine

6.0e−13

TG.18.0_36.3

1.1e−08

HArg synthesis

3.5e−14

HArg synthesis

1.2e−16

TG.18.1_38.5

6.6e−08

Leucine2.9e−32

Leucine4.0e−37

TG.18.2_32.0

1.1e−08

Ratio of HArg to ADMA

1.9e−13

Ratio of glycosyl Cer to Cer

1.9e−11

TG.18.3_32.0

1.1e−08

Ratio of HArg to SDMA

5.4e−12

Ratio of HArg to ADMA

1.2e−14

TG.18.3_34.0

1.1e−08

TG.18.1_38.5

3.0e−13

Ratio of HexCer to Cer

6.0e−12

TG.18.3_36.1

6.6e−08

TG.18.3_32.1

2.2e−11

Sum of solely ketogenic AAs

6.9e−13

TG.20.3_34.1

5.9e−08

TG.20.1_32.1

4.9e−12

TG.18.1_38.5

1.5e−12

Table 5.  Plasma metabolites found in significantly higher concentrations (most significant FDR-adjusted
p values for the difference between means) in 16 Standardbred horses in training at ages 2, 2.5 and 3.5 years
compared with 1.5 years of age. AA amino acids, ADMA asymmetric dimethylarginine, DiCA dodecanedioic
acid, HexCer hexosylceramides, HArg homoarginine, Cer ceramides, SDMA symmetric dimethylarginine, TG
triglyceride.

2 years of age

2.5 years of age

3.5 years of age

Metabolite

FDR p value

Metabolite

FDR p value

Metabolite

FDR p value

Alpha-aminobutyric acid3.0e−06

Beta alanine synthesis

1.8e−22

Beta alanine synthesis

1.9e−25

Beta alanine synthesis

7.5e−07

CE.14.1

1.5e−24

CE.14.1

1.1e−24

Beta alanine

4.3e−06

CE.17.1

1.4e−21

CE.17.1

9.5e−22

Betaine synthesis

4.4e−06

Cer.d18.1.20.0.OH

2.7e−21

Cer.d16.1.22.0

9.3e−25

DG.18.1_20.3

2.1e−06

Cer.d18.2.24.0

7.9e−30

Cer.d18.2.24.0

8.3e−30

PC.aa.C36.5

1.7e−08

DG.18.1_20.3

1.4e−21

DG.18.1_20.3

9.5e−22

PC.aa.C36.6

1.7e−06

Indole1.8e−31FA.18.2

9.5e−22

Sum of aminobutyric acids

4.9e−06

TG.17.0_36.4

4.1e−25

Indole1.8e−31

Sum of betaine and rel. metab

3.7e−06

TG.18.2_36.0

5.5e−21

TG.14.0_36.3

7.5e−28

Valine3.7e−06

TG.20.2_32.0

7.7e−21

TG.16.0_38.3

3.6e−22

Table 6.  Plasma metabolites found in significantly lower concentrations (most significant FDR-adjusted
p values for the difference between means) in 16 Standardbred horses in training at 2, 2.5 and 3.5 years ofage compared with 1.5 years of age. Cer ceramides, CE cholesteryl ester, DG diglyceride, FA fatty acid, PC
phosphatidylcholines, TG triglyceride.

which acidosis contributes to ­fatigue24. These results suggest that the duration of high-intensity training in eachtraining session may be important for development of pH-buffering capacity.
Another AA involved in reducing oxidative stress is m
­ ethionine25, which is easily oxidised to methionine
sulfoxide. The concentration of this metabolite was higher in the High group than in the Low group. However,there was no consistent change over time, with both an increase (2 years old) and a decrease (3.5 years old)compared with 1.5 years of age (SM2).
The levels of several triglyceride metabolites significantly decreased in the High group compared with the
Low group. However, over time there was an increase in the levels of most triglyceride metabolites, which isin agreement with findings in a longitudinal study of horses in a 12-week training p­ rogramme4. This could be
because fat is an important source of energy during exercise in Standardbred horses. It is known that the activityof 3-hydroxyacyl-CoA-dehydrogenase, the last step in beta-oxidation, may increase with training in Standardbred­horses26 and also that it is associated with increased p­ erformance27. Our results also showed that aconitic acidlevels were higher in the High group compared with the Low group, and were higher at 2.5 and 3.5 years of age
compared with 1.5 years of age. Aconitic acid is an intermediate in the citric cycle. It is well known that training increases the activity of citrate synthase (catalyses the first reaction in the citric cycle) in the gluteus muscleof ­horses26–29 and our results indicate increased activity of the citric cycle. Altogether, our findings support thesuggestion by Klein et al.4 that metabolites related to amino acid and lipid metabolism play pivotal roles in the
response of equine skeletal muscle to training.
The levels of ceramide metabolites were significantly lower in the High group compared with the Low group,
and also decreased over time compared with 1.5 years of age. There are few previous studies on the effects ofceramide levels in response to exercise, but our finding of a decrease over time is in agreement with observations in obese humans undergoing a 12-week training programme with high to moderate training i­ntensity30.

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Ceramides are bioactive molecules important in e.g. inflammatory processes and apoptosis, and high levels havebeen linked to insulin ­resistance31. In horses, it has been suggested that high plasma ceramide concentrations
indicate insulin d­ ysregulation32. Exercise and training can improve insulin resistance in young h­ umans33 andthere is evidence of a similar response in h
­ orses34,35, although conflicting observations have been ­reported36.
In the High group, HArg and HArg synthesis (HArg divided by the sum of arginine and lysine) levels
increased compared with the Low group (SM1) and also increased over time at all ages compared with 1.5 yearsof age. The ratio of HArg to asymmetric dimethylarginine (ADMA) was also higher in the High group compared with the Low group (SM2) and both the ratio of HArg to ADMA and the ratio of HArg to symmetric
dimethylarginine (SDMA) were higher for all ages compared with 1.5 years of age. HArg is suggested to be oneof the substrates for nitric oxide (NO) synthesis and ADMA as an inhibitor of NO synthesis, but little is known
about this as ­yet37,38. Nitric oxide is one of the smallest signalling molecules and has several biological functions,
including as a potent ­vasodilator38. There is evidence that physical activity enhances NO production and also that
NO improves performance and promotes r­ ecovery39. An altered vascular response is in line with the significant
changes (improvements) in cardiovascular responses in the High group, by 2.5 years of age and throughout therest of the study, which we reported previously in these h­ orses10.
Indole is produced when tryptophan is metabolised in the gut by bacterial tryptophanases and is thenabsorbed to the ­circulation40. Indole is suggested to have beneficial effects on human health by influencing
e.g. oxidative stresses and intestinal i­ nflammation41. However, it appears to have dual effects on the h­ ost42. For
example, indole seems to have beneficial effects on the intestinal mucosa, but high levels have negative impacts
on emotional behaviour and ­anxiety42,43. In the present study, indole concentrations were not affected by training
group, but the concentrations were lower at age 2.5 and 3.5 years compared with 1.5 years of age. This contradicts findings for humans, where increases in microbiome-derived tryptophan metabolites has been reported
in soldiers subjected to an 80-day training ­programme44. The reason for this discrepancy in results is unclear,but could be due to diet and changes in body composition i.e. weight loss in the study on ­humans45 and growth
but maintained body fat content in our ­study9. Another explanation is simply that the reduction in our study
was due to the decrease in crude protein intake (and thereby tryptophan), as the crude protein requirement for
growth decreased over t­ ime9.
Cholesteryl ester is an esterified variant of cholesterol which is either stored in the cell or released into the­blood46. Cholesterol is involved in cell membrane structure and function, and also in binding numerous transmembrane ­proteins46. It is difficult to draw any firm conclusions about cholesteryl esters based on the results inthe present study, because there were both significant increases and decreases in the High group compared with
the Low group (SM1) and the same was true for changes over time (SM2).
In this study, differences between the training groups were only observed at 2 years of age, although the different training programmes were followed throughout the study until age 3.5 years. A likely explanation, and alimitation of this study, is that strict compliance with the training programme was not possible during the latterpart of the study, especially in the High group, due to variations in the fit-to-train status. Horses which were not
fit to train according to the trainer were allowed to skip a training session and this resulted in horses in the Highgroup missing more training than horses in the Low group. From July as 2-year-olds until June as 3-year-olds the
Low group performed 4–5 more training sessions per 3-month period compared to the High group and during
the last 6 months of the study, the Low group had ~2 more sessions per 3-month p­ eriod10. Consequently, from theage of 2.5 years the horses in the High training group received on average the same volume of training as horses
in the Low g­ roup47. Still, each training session performed by the High group had longer duration/distance thanin the Low group and differences in the metabolic adaption could therefore potentially be expected. However,knowledge of the importance of variations in frequency and duration of training sessions is limited in horses. As
mentioned earlier, this study is unique in the exploration of the effect of different training programs for young
horses over a period relevant to true race training conditions.
Another limitation of this study is the lack of a non-trained control group, i.e. a group subjected to no training at all. The main aim of the study was to explore differences in the metabolomic profile in response to two
different training programmes, where the High group could be considered the control treatment (comparable tostandard ­practise9). In the absence of significant differences between training programmes during the latter partof the study, a design with a third, non-exercised control group would have been of great academic interest. Thiswas part of the initial experimental plans but turned out to be a too complex and expensive design. Accordingly,
for several metabolites we observed significant differences over time, but were unable to discriminate potentialtraining effects from effects caused by changes related to age or growth. However, a study by Roneus et al.29
showed that training, not growth, is the main factor inducing high oxidative capacity in muscle of Standardbred
horses in training. Another potential limitation in this study is that the samples analysed had been frozen for
9–11 years, which may have affected the results if metabolites oxidise or water evaporates. However, the levels
observed for numerous metabolites (e.g. AAs and triglycerides) were within the range reported previously forhorses at ­rest12,48,49 (our horses had been at rest for at least 15 h when blood samples were collected), which
implies that these metabolites were well preserved during storage.
The strength of this study is the selected study population of elite performance horses training for competition under ‘real world’ conditions. Information about the metabolic profile of the individuals included in thepresent study can be used for future studies on profiles of importance for athletic performance and longevity.
We have earlier shown that the proportion of experimental horses that raced as 3-year-olds was equal to that of
their siblings, and greater than the proportion of cohort ­geldings50. We also know that four horses were not active
after the 3-year-old season and that the rest were fit to race until at least 8 ± 2 years of age.
In conclusion, the training programmes applied in the present study promoted physiological adaptations
linked to aerobic energy production, induced changes in amino acid metabolism and potentially also affectedpH-buffering and vascular and insulin responses. An increase in the distance covered in high-intensity exercise
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seemed to stimulate these changes even more. Further studies are needed to link the metabolic profile of young
horses in training to performance and longevity.

Data availability

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
Received: 9 October 2023; Accepted: 15 January 2024

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Acknowledgements

This work was supported by the Mass Spectrometry Based Metabolomics Facility in Uppsala. A special thanks to
Dr Kumari Ubhayasekera for help with the mass spectrometry analyses and method writing and to Mary McAfee
for language help. The authors would also like to thank all staff and students at Wången; the reference group of
trainers, Stig H Johansson, Thomas Uhrberg and Jan Halberg, for help with designing the training programmes;
and Trioplast AB, Dow Chemicals, Scandivet, Thermobar AB, the Swedish Trotting Association, the Swedish
Horse Racing Totalisator Board and the Swedish Horse Council Foundation for financial or material support.

Author contributions

A.J. and S.R. planned the experiment and collected the blood samples. J.B. managed and supervised the metabolomic analysis. A.J. wrote abstract, introduction and discussion. L.J. wrote all parts of the main text, performed
the statistical analyses and prepared the tables and figures. All authors collaborated on interpreting the results
and reviewed the manuscript.

Funding

Open access funding provided by Swedish University of Agricultural Sciences.

Competing interests

The authors declare no competing interests.

Additional information

Supplementary Information The online version contains supplementary material available at https://​doi.​org/​
10.​1038/​s41598-​024-​52188-z.
Correspondence and requests for materials should be addressed to A.J.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps andinstitutional affiliations.

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