Proteomic analysis emphasizes the adaptation of energy metabolism in horses during endurance races
Endurance racing, as one of the most extreme and demanding equine sport disciplines, inevitably causes physiological changes and damage to the organism. Most horses finish the race successfully without obvious adverse effects on their health, while elimination from the race is mainly a consequence of poor metabolic status or lameness . A suitable training protocol, together with proper general care for the horse athlete, is crucial in successful training for an endurance race. Physical load during the race leads to systemic changes in the equine organism; blood flow redistribution causes hypoperfusion of visceral organs and hyperperfusion of the muscles  and skin  to meet metabolic needs and maintain effective thermoregulation. Sweating causes a major loss of water and electrolytes, but preventing electrolyte and acid‒base imbalance largely reduces the risk of exhaustion . Exhaustion is a multisystemic disorder resulting from dehydration, hypovolemia, hyperthermia, energy substrate deficiency, electrolyte loss and acid‒base balance disorders . Aerobic metabolism is activated in endurance races as a type of low-intensity and long-duration exercise. Energy metabolism during an endurance race is based on carbohydrates in the early stages of exercise and fatty acid oxidation in the later stages . Endurance training improves aerobic metabolism through the promotion of muscular capillarization and an increase in the number of mitochondria and enzymatic activity . As proteins execute most of the biological processes in an organism, proteomic analysis provides insight into their activity modifications, mutual relationships, and integration in biological process simulation models . Quantitative proteomics is a very sensitive and specific analytical method that allows the identification and quantification of numerous proteins through the analysis of only one sample. The application of this method could ensure proper development of the training schedule, planning of competitions, recovery period and eventual treatment . Proteomic studies on blood and muscle samples of endurance Arabian and Standardbred and Thoroughbred racehorses in training, proved to be a valuable aid in elucidating the biochemical events and facilitating the evaluation of training effects in racing horses. These studies showed that physical exercise influenced proteins expression of energy storage, inflammation, immune modulation, coagulation, oxidative capacity, cellular and vascular damage, ultimately impacting the overall metabolism of the horse . This study aimed to identify different proteins through global proteomics procedures to define the complex metabolic changes that occur during prolonged aerobic exercise. Our objective was to record changes in the pre- to post-race levels of proteins with the use of a bottom-up tandem mass tag (TMT)-based quantitative high-resolution proteomic approach. This research hypothesized that prolonged submaximal aerobic activity leads to several serum proteome changes that reflect the adaptation of horses to endurance exercise, mainly characterized by the modification of the blood lipid profile of horses that successfully finished an endurance race.   Horses This study included endurance horses competing at 80 km National Races. Enrolment in the study was voluntary, and each owner/rider signed a consent form before the first veterinary inspection of their horse at the competition site. All horses competing in 80 km endurance races were eligible for the study, and only horses that successfully passed the final veterinary inspection were included in further studies. There were 19 horses enrolled in the study, 13 of which met the inclusion criteria, since 6 horses did not finish the race (one retired, 5 eliminated: 4 lame, 1 metabolic). The average age of the horses was 7.5 (± 1.5 SEM) years. The breed composition included 8 Arabians and Arabian crosses and 5 warmbloods, 8 mares, 3 geldings and 2 stallions. Blood collection Blood samples for the serum analysis were collected by jugular venepuncture into vacuum tubes for a serum with gel using a vacutainer system (Vacutainer®, Becton Dickenson, USA) 1 h before the start and 30 min after the race. After collection, the samples were allowed to coagulate for 30 min and then centrifuged at 1096 × g for 15 min. The serum samples were transported in cooling bags to the laboratory, and within four hours after sampling aliquoted and stored at − 80 °C until further analyses. Proteomic analysis by LC–MS/MS Proteomic analysis of serum samples was performed by TMT-based quantitative approach, as previously published . In brief, BCA assay (Thermo Scientific, Rockford, USA) was used for the total protein concentration determination. Thirty-five micrograms of total protein from the samples and an internal standard were diluted to a volume of 50 μL using 0.1 M triethyl ammonium bicarbonate (TEAB, Thermo Scientific, Rockford, USA), and then reduced by adding 2.5 μL of 200 mM dithiothreitol (60 min, 55 °C (Sigma Aldrich, St. Louis, MO, USA)), alkylated for 30 min in the dark (2.5 μL of 375 mM iodoacetamide, (Sigma Aldrich, St. Louis, MO, USA)) and acetone-precipitated overnight (300 μL, − 20 °C). After centrifugation (9000 × g, 4 °C), protein pellets were dissolved in 50 μL of 0.1 M TEAB and digested at 37 °C overnight (1 μL of trypsin, 1 mg/mL, Promega; trypsin-to-protein ratio 1:35). TMT sixplex reagents (Thermo Scientific, Rockford, IL, USA) were prepared according to the manufacturer's procedure. After addition of 19 μL of the TMT label to each sample, and 1-h incubation at room temperature, reactions were quenched by 5% hydroxylamine (Sigma-Aldrich, St. Louis, MO, USA), and labels were combined. High-resolution liquid chromatography coupled with tandem mass spectrometry (LC‒MS/MS) analysis of the TMT-labelled peptides was carried out using an Ultimate 3000 RSLCnano system (Dionex, Germering, Germany) coupled to a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). Peptides were dissolved in loading solvent (1% ACN, 0.1% formic acid), loaded onto a trap column (C18 PepMap100, 5 μm, 100A, 300 μm × 5 mm), and separated on an analytical column (PepMap™ RSLC C18, 50 cm × 75 μm) using a linear gradient of 5–45% mobile phase B (0.1% formic acid in 80% ACN) over 120 min. Mobile phase A consisted of 0.1% formic acid in water. Ionization was achieved using a nanospray Flex ion source (Thermo Fisher Scientific, Bremen, Germany) containing a 10 μm inner diameter silica tip emitter (New Objective, USA). The MS instrument was operated in positive ion mode using the DDA Top8 method. Full scan MS spectra were acquired in the range from m/z 350.0 to m/z 1800.0 with a resolution of 70,000, a 120 ms injection time, an AGC target of 1 × 10 6 , ± 2.0 Da isolation window and a dynamic exclusion of 30 s. HCD fragmentation was performed at step collision energies (29% and 35% NCE) with a resolution of 17,500 and an AGC target of 2 × 10 5 . Precursor ions with unassigned charge states or with charge states of + 1 or more than + 7 were excluded from fragmentation. Protein identification and quantification was performed using the SEQUEST algorithm implemented in Proteome Discoverer (version 2.0., Thermo Fisher Scientific). A database search against Canis lupus FASTA files (downloaded from the NCBI database on 04/04/2019, 172,083 sequences) was performed according to the following parameters: two trypsin missed cleavage sites, precursor mass tolerances of 10 ppm, fragment mass tolerances of 0.02 Da, fixed peptide modification: carbamidomethyl (C), dynamic modifications: oxidation (M), deamidation (N,Q) and TMT sixplex (K, peptide N-terminus). The false discovery rate (FDR) for peptide identification was calculated using the Percolator algorithm in the Proteome Discoverer workflow and was set at 1% FDR. At least two unique peptides and a 1% FDR were required for reporting confidently identified proteins. Validation of proteomic results Proteomic results were validated by enzyme-linked immunosorbent assay (ELISA) and biochemical assays using serum samples from the same horses used for proteomic analysis. Serum samples were analysed with horse-specific competitive ELISA for determination of apolipoprotein E (ApoE) (LSBio, LifeSpan BioSciences, Inc., Seattle, USA), whereas an automated spectrophotometric hemoglobin-HP binding assay was used for determination of the haptoglobin (HP) concentration as described by Eckersall et al.  and modified according to Brady et al. . For the analytical performance of the assays, the precision and accuracy of the assays were calculated as previously described . For intra-assay precision, the pool was prepared from different equine samples, and for interassay precision, the pool was divided into aliquots and stored in plastic vials at − 20 °C until analysis. The intra-assay coefficient of variation (CV) was calculated after analysis of the pool six times in a single assay run. Interassay CV was determined by analysis of the same sample in five separate runs carried out on different days. The accuracy of the assays was evaluated indirectly by linearity under dilution by comparing the measured concentrations of analyte with the expected levels. Briefly, the serum pool was serially diluted with the diluent provided with the kit and analysed. Statistical and bioinformatic analyses Statistical analysis was performed using R v3.2.2 . Proteins with missing data for an adequate paired sample were excluded from the analysis. As most of the identified proteins did not follow a normal distribution, as tested by the Shapiro‒Wilk test, to examine the difference in protein abundance between groups (pre- to post-race), the Wilcoxon signed-rank test for paired samples was performed. False discovery rate (FDR) P value correction was applied, and proteins were considered statistically significant if the FDR was < 0.05. The fold change between two groups was calculated as the mean (after the race)/mean (before the race) and expressed on a log2 scale. A volcano plot was generated using the R package ggplot2 v3.1.1 , while the packages clusterProfiler v3.16.1  and ReactomePA v1.32.0  were used for functional enrichment analysis. For validation assays, statistical analysis was performed using GraphPad Prism 5 (GraphPad Software Inc., San Diego, CA). Differences in concentrations before and after the race were assessed by the Wilcoxon signed-rank test, and the data are presented as means, medians with interquartile ranges and standard deviations (SD). Differences with P values < 0.05 were considered to indicate statistical significance.   This study included endurance horses competing at 80 km National Races. Enrolment in the study was voluntary, and each owner/rider signed a consent form before the first veterinary inspection of their horse at the competition site. All horses competing in 80 km endurance races were eligible for the study, and only horses that successfully passed the final veterinary inspection were included in further studies. There were 19 horses enrolled in the study, 13 of which met the inclusion criteria, since 6 horses did not finish the race (one retired, 5 eliminated: 4 lame, 1 metabolic). The average age of the horses was 7.5 (± 1.5 SEM) years. The breed composition included 8 Arabians and Arabian crosses and 5 warmbloods, 8 mares, 3 geldings and 2 stallions.   Blood samples for the serum analysis were collected by jugular venepuncture into vacuum tubes for a serum with gel using a vacutainer system (Vacutainer®, Becton Dickenson, USA) 1 h before the start and 30 min after the race. After collection, the samples were allowed to coagulate for 30 min and then centrifuged at 1096 × g for 15 min. The serum samples were transported in cooling bags to the laboratory, and within four hours after sampling aliquoted and stored at − 80 °C until further analyses.   Proteomic analysis of serum samples was performed by TMT-based quantitative approach, as previously published . In brief, BCA assay (Thermo Scientific, Rockford, USA) was used for the total protein concentration determination. Thirty-five micrograms of total protein from the samples and an internal standard were diluted to a volume of 50 μL using 0.1 M triethyl ammonium bicarbonate (TEAB, Thermo Scientific, Rockford, USA), and then reduced by adding 2.5 μL of 200 mM dithiothreitol (60 min, 55 °C (Sigma Aldrich, St. Louis, MO, USA)), alkylated for 30 min in the dark (2.5 μL of 375 mM iodoacetamide, (Sigma Aldrich, St. Louis, MO, USA)) and acetone-precipitated overnight (300 μL, − 20 °C). After centrifugation (9000 × g, 4 °C), protein pellets were dissolved in 50 μL of 0.1 M TEAB and digested at 37 °C overnight (1 μL of trypsin, 1 mg/mL, Promega; trypsin-to-protein ratio 1:35). TMT sixplex reagents (Thermo Scientific, Rockford, IL, USA) were prepared according to the manufacturer's procedure. After addition of 19 μL of the TMT label to each sample, and 1-h incubation at room temperature, reactions were quenched by 5% hydroxylamine (Sigma-Aldrich, St. Louis, MO, USA), and labels were combined. High-resolution liquid chromatography coupled with tandem mass spectrometry (LC‒MS/MS) analysis of the TMT-labelled peptides was carried out using an Ultimate 3000 RSLCnano system (Dionex, Germering, Germany) coupled to a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). Peptides were dissolved in loading solvent (1% ACN, 0.1% formic acid), loaded onto a trap column (C18 PepMap100, 5 μm, 100A, 300 μm × 5 mm), and separated on an analytical column (PepMap™ RSLC C18, 50 cm × 75 μm) using a linear gradient of 5–45% mobile phase B (0.1% formic acid in 80% ACN) over 120 min. Mobile phase A consisted of 0.1% formic acid in water. Ionization was achieved using a nanospray Flex ion source (Thermo Fisher Scientific, Bremen, Germany) containing a 10 μm inner diameter silica tip emitter (New Objective, USA). The MS instrument was operated in positive ion mode using the DDA Top8 method. Full scan MS spectra were acquired in the range from m/z 350.0 to m/z 1800.0 with a resolution of 70,000, a 120 ms injection time, an AGC target of 1 × 10 6 , ± 2.0 Da isolation window and a dynamic exclusion of 30 s. HCD fragmentation was performed at step collision energies (29% and 35% NCE) with a resolution of 17,500 and an AGC target of 2 × 10 5 . Precursor ions with unassigned charge states or with charge states of + 1 or more than + 7 were excluded from fragmentation. Protein identification and quantification was performed using the SEQUEST algorithm implemented in Proteome Discoverer (version 2.0., Thermo Fisher Scientific). A database search against Canis lupus FASTA files (downloaded from the NCBI database on 04/04/2019, 172,083 sequences) was performed according to the following parameters: two trypsin missed cleavage sites, precursor mass tolerances of 10 ppm, fragment mass tolerances of 0.02 Da, fixed peptide modification: carbamidomethyl (C), dynamic modifications: oxidation (M), deamidation (N,Q) and TMT sixplex (K, peptide N-terminus). The false discovery rate (FDR) for peptide identification was calculated using the Percolator algorithm in the Proteome Discoverer workflow and was set at 1% FDR. At least two unique peptides and a 1% FDR were required for reporting confidently identified proteins.   Proteomic results were validated by enzyme-linked immunosorbent assay (ELISA) and biochemical assays using serum samples from the same horses used for proteomic analysis. Serum samples were analysed with horse-specific competitive ELISA for determination of apolipoprotein E (ApoE) (LSBio, LifeSpan BioSciences, Inc., Seattle, USA), whereas an automated spectrophotometric hemoglobin-HP binding assay was used for determination of the haptoglobin (HP) concentration as described by Eckersall et al.  and modified according to Brady et al. . For the analytical performance of the assays, the precision and accuracy of the assays were calculated as previously described . For intra-assay precision, the pool was prepared from different equine samples, and for interassay precision, the pool was divided into aliquots and stored in plastic vials at − 20 °C until analysis. The intra-assay coefficient of variation (CV) was calculated after analysis of the pool six times in a single assay run. Interassay CV was determined by analysis of the same sample in five separate runs carried out on different days. The accuracy of the assays was evaluated indirectly by linearity under dilution by comparing the measured concentrations of analyte with the expected levels. Briefly, the serum pool was serially diluted with the diluent provided with the kit and analysed.   Statistical analysis was performed using R v3.2.2 . Proteins with missing data for an adequate paired sample were excluded from the analysis. As most of the identified proteins did not follow a normal distribution, as tested by the Shapiro‒Wilk test, to examine the difference in protein abundance between groups (pre- to post-race), the Wilcoxon signed-rank test for paired samples was performed. False discovery rate (FDR) P value correction was applied, and proteins were considered statistically significant if the FDR was < 0.05. The fold change between two groups was calculated as the mean (after the race)/mean (before the race) and expressed on a log2 scale. A volcano plot was generated using the R package ggplot2 v3.1.1 , while the packages clusterProfiler v3.16.1  and ReactomePA v1.32.0  were used for functional enrichment analysis. For validation assays, statistical analysis was performed using GraphPad Prism 5 (GraphPad Software Inc., San Diego, CA). Differences in concentrations before and after the race were assessed by the Wilcoxon signed-rank test, and the data are presented as means, medians with interquartile ranges and standard deviations (SD). Differences with P values < 0.05 were considered to indicate statistical significance.   Serum analysis identified and quantified 1525 proteins, 1246 of which were excluded from the analysis because they did not meet the set criteria (2 unique peptides and 5% FDR) (Supplemental Table 1). The final number of identified proteins was 279, and 191 proteins fulfilled the conditions for paired sample analysis (no missing data for all 13 horses before and after the race; Supplemental Table 2). Statistical analysis of serum samples revealed 10 master proteins with significant p value differences between pre- and post-race values. Table presents the FDR-corrected p values of the significant proteins and their protein abundances before and after the race. The abundances of microfibril-associated glycoprotein 4, transferrin, antithrombin III and apolipoproteins A4 and E increased, while the abundances of haptoglobin, alpha-1-microglobulin/bikunin precursor (AMBP) protein and apolipoproteins C2, C3 and R decreased. A volcano plot (Fig. ) was generated to graphically represent the different proteomic responses of the horses before and after the race. The blue dots represent downregulated proteins, while the red dots represent upregulated proteins when comparing protein abundances before and after the race. The results of the Gene Ontology analysis are shown in Fig. . Serum proteins with significantly differential abundances before and after the race were involved in triglyceride and acylglycerol homeostasis, regulation of lipid localization, triglyceride catabolic process and others (Fig. A). The molecular functions of proteins with significantly differential abundances were enzyme inhibitor activity, cholesterol binding, sterol binding, antioxidant activity, and others (Fig. B). In terms of cellular components, the identified proteins were associated with blood microparticles, chylomicron, and collagen-containing extracellular matrix (Fig. C). Reactome pathway analysis (FDR corrected P -values < 0.05) revealed that most of the proteins differing in abundance are involved in plasma lipoprotein assembly, binding, and uptake of ligands by scavenger receptors, remodelling, and clearance, high-density lipoproteins (HDL) remodelling and other pathways (Fig. ). All assays evaluated in the present study showed adequate precision with intra- and inter-assay CVs lower than 15%, the limit of the objective analytic performance standard for precision (FDA 2001). For the accuracy of the assays, ordinary linear regression analysis resulted in linear regression equations with a coefficient close to 1.0 ( R 2 > 0.98 for all assays). The tested analytes, haptoglobin, and ApoE, showed significant differences between horses before and after the race (Fig. ). ApoE concentrations were significantly higher after the race (median, interquartile range: 109.3 µg/ml, 88.95 – 125.40 µg/ml) compared to concentrations before the race (76.10 µg/ml, 57.95 – 98.40 µg/ml; p = 0.006). The concentrations of haptoglobin were significantly lower after the race (0.49 g/L, 0.37 – 0.71 g/L) than before the race (0.70 g/L, 0.55 – 0.83 g/L; p = 0.006). Altogether, both proteins validated with immunoassays confirmed consistency with proteomic results.   Distinct alterations were observed in several proteins’ abundances in the horse's serum in response to an 80 km endurance race. Changes in protein abundance after prolonged aerobic exercise reflect various undergoing metabolic pathways indicating adaptation mechanisms to exercise. Serum proteomics analysis demonstrated that of 279 identified proteins, 10 proteins showed significantly different post-race values. Protein abundances after the race showed an increase in the apolipoproteins group: ApoA IV and E, MFAP4, transferrin, antithrombin-III, and a decrease of the apolipoproteins C-II, C-III and R, protein AMBP and haptoglobin abundance comparing to values before the race. The proteins discriminating the profile pre- and post-race were involved mainly in lipid metabolism. The influence of endurance race on equine homeostasis has also been noted in previous research  using blood metabolomics, transcriptomics and miRNomics to evaluate the response to 160 km endurance race on physiological adaptations necessary for homeostasis and performance. The research revealed complex interactions with several biochemical pathways such as energy and oxygen sensing, oxidative stress, and inflammation. As evidenced by GO and pathway analysis, the most significant changes are related to apolipoproteins, including processes such as plasma lipoprotein assembly, remodelling, and clearance. The present study recorded a higher abundance of post-race ApoA-IV. Apolipoprotein A-IV is synthesized in the alimentary tract, and its upregulation mostly follows increased long-chained fatty acids absorption. In the presence of the ApoC-II, ApoA-IV promotes lipoprotein-lipase (LPL) activity which hydrolyses triglycerides to free fatty acids used as an energy substrate in muscle tissue or energy storage in fat tissue . In vitro research recorded the anti-apoptotic properties of the ApoA-IV, inhibiting apoptosis mediated by oxidants . Many studies have noted an increase in reactive oxygen species induced by endurance races  which implies that ApoA-IV could have this property in vivo as well. The decrease of the ApoC-II abundance in the present research can be explained by LPL activation. Release of the ApoA-IV and binding of the ApoC-II on the lipoproteins leads to an increased LPL activity . Activation of the LPL in the process of triglyceride hydrolysis in the chylomicrons requires binding of the ApoC-II on the enzyme which results in the downregulation of circulating ApoC-II . During endurance exercise in the present study, there was an increase in fat utilization as an energy substrate that consequently caused the noted decrease of ApoC-II abundance in equine athletes. Interestingly, a study on human elite marathon runners noted a correlation between their performance levels and a decrease in blood triglyceride values . We recorded an increase in apolipoprotein E abundance after the race. This increase can be explained as an increase in the free fraction of ApoE consequently to increased lipid metabolism and very-low-density lipoprotein (VLDL) utilization. Acute physical exercise (30 min. at ~75% VO 2max ) effects on ApoE-VLDL plasma fraction research in people did not record any changes in APoE concentration following exercise. Increased ApoE concentration in that research was recorded 4, 6 and 8 h after the end of exercise . The activity of the LPL in people showed increased values during prolonged physical activity of lower intensity which leads to depletion of the glycogen storage . Apolipoprotein C-III belongs to the apolipoprotein C family and is closely associated with triglyceride metabolism by inhibiting LPL . ApoC-III is present in high-density lipoproteins (HDL), low-density lipoproteins (LDL), and very-low-density lipoproteins (VLDL) , while the abundance of apolipoprotein affects lipoprotein functions . In this study, a decrease in serum apolipoprotein C-III (ApoC-III) abundance was found after racing. In contrast to our study, Klein et al.  found no change in ApoC-III plasma levels after exercise, but an increased concentration of ApoC- III in the ApoE-rich VLDL fraction. The decreased amount of ApoC-III in serum in this study may be explained by the increased energy demand of muscles. The decreased ApoC-III probably contributes to the redirection of triglyceride-rich lipoproteins to the muscles to meet energy demands instead of storing them in the liver or adipose tissue. It is known that muscle LPL activity increases during exercise . Several apolipoprotein changes were noted in the present study, highlighting lipid consumption as a source of energy during an endurance race. Utilization of fat as an energy source results in a decrease of the ApoC-II, ApoC-III and an increase of the ApoE. Increased fat ingestion leads to an increase of their resorption, which together with the onset of oxidative stress leads to an increase of the ApoA-IV. In endurance horses, a fat-supplemented diet is often used with the goal of reducing starch with concurrent maintenance of caloric intake, reducing heat production, and calming effect on horses . Similarly, Mycka et al.  noted significant dysregulation (both upregulation and downregulation) of genes responsible for lipids metabolism in a group of Arabian horses competing in a 120 km endurance race. Arabian and Arabian crosses have inherited endurance capacity consistent with most of the horses in the present study. Reactome pathway analysis also revealed changes in binding and uptake of ligands by scavenger receptors, highlighting two key proteins: AMBP and haptoglobin. The AMBP protein is the precursor protein of bikunin, the simplest described proteoglycan found in cartilage . In response to prolonged exercise, we noted a decrease in levels of AMBC protein, which could indicate consequently increased synthesis of bikunin. Joint homeostasis can be influenced by compressive and shared forces during exercise . Higher glycosaminoglycan content at locations under higher load has been noted in carpal articular cartilage in horses after high-intensity treadmill training exercise comparted to the group performing a low-intensity exercise . A decrease in the HP abundance was recorded in this research after the race. Our results are in accordance with different studies evaluating HP values after endurance races . Haptoglobin represents one of the negative acute-phase reaction proteins in horses with a role in binding the free haemoglobin during haemolysis . As potential causes of exercise-induced intravascular haemolysis, mechanical force during the impact on the ground, repetitive muscle contraction and visceral vasoconstriction are mentioned. Plausible contributing factors are also hyperthermia, dehydration, electrolyte, and acid–base balance disorders . Exercise-induced intravascular haemolysis is a common consequence of strenuous exercise that can be detected by a dark discolouration of urine, however, in the present research urine was not analysed. An increase in the free haemoglobin concentration leads to a decrease in the HP and is often used for an estimation of exercise-induced haemolysis . Free haemoglobin is auto-oxidated to dimers, that in the presence of the hydrogen peroxide produce oxyferryl group and release iron ions , while its binding to haptoglobin inhibits the generation of reactive oxygen species (ROS) and oxidative tissue injury . A decrease in haptoglobin abundance could also be attributed to myoglobin released from damaged muscle fibres . An increase in levels of muscle damage markers has been recorded in horses successfully finishing endurance races . A study on 15 Standardbreds racing 1600 m also reported a significant decrease in the HP after the race . Contrary to our results, Cywinska et al.  found no changes in the HP concentration after 36 to 160 km endurance races. The decrease in HP abundance and concentration in our study was confirmed by both the proteomic approach and colorimetric assay, suggesting the reliability of these findings. The main biological function of serum transferrin is the transport of iron between cells and tissues . In the present study, an increase in transferrin levels has been noted after the race. Similar findings have been described after both maximal and submaximal exercise in people . Our results could be a consequence of the previously mentioned exercise-induced intravascular haemolysis and subsequent release of iron in the serum. In the present study, antithrombin III levels increased after the race indicating a possible inhibition of coagulation. The effect of exercise on haemostasis has been evaluated in several human studies, however, stimulation of both coagulation and fibrinolytic cascades has been noted . Ferguson et al. (1987)  in their study on the effect of maximal treadmill exercise on different categories of human athletes recorded increased levels of antithrombin III. A study evaluating thromboelastometry in horses noted reduced coagulability in Standardbred racehorses after exercise . Microfibril-associated glycoprotein 4 (MFAP4), an extracellular matrix (ECM) glycoprotein, is an important elastic fibre component . It is produced by vascular smooth muscle cells densely found in the blood vessels mostly in the heart and lung. Although the exact function of MFAP4 is still unknown, it has been proposed and researched mostly as a potential biomarker of hepatic and pulmonary fibrosis , chronic obstructive pulmonary disease , prostate , ovarian  and mammary cancers , and even dilatative heart disease in dogs . A study on the influence of physical activity on serum MFAP4 levels in people showed an increase in its concentration after a submaximal exercise in healthy individuals . Similar results in horses were found in our study where a rise in serum MFAP4 levels was detected in serum samples taken after the race. These results implicate caution when interpreting MFAP4 serum rise as a specific disease biomarker, since it shows significant variations influenced by physical activity. Participation in this research study was voluntary and can therefore be considered a limiting factor. Moreover, limited information about the horses was available (feeding, management, travel to the race, etc.). The studied population, even though relatively uniform, was small. As sample collection took place during the race, strict limitations regarding work and data collection were met. Obligatory veterinary checks before, during and after the race do not provide a thorough clinical examination, possibly overlooking some clinically significant changes. Furthermore, no data on the training regime, previous health problems, possible urine discolouration, or feed supplements were collected during the race. The lack of correction of variables for possible haemoconcentration after the race also represents a possible study limitation.   The present study highlights different physiological adaptive responses to endurance exercise in horses. Prolonged submaximal aerobic exercise caused several homeostatic disbalances: increased synthesis of proteoglycans, decreased haptoglobin abundance indicating acute phase injury and increased binding of haemoglobin that together with increased levels of transferrin could indicate exercise-induced intravascular haemolysis. Changes in different apolipoprotein abundances accentuate increased fat utilisation to meet energy requirements for skeletal muscle during endurance races. Described responses can elucidate pathophysiological mechanisms of metabolic and orthopaedic diseases characteristic for endurance horses.   Supplementary Material 1. List of all identified and quantified proteins in serum samples – the search output from Proteome Discoverer. Supplementary Table 1 represents Raw data of all 1525 identified proteins. Acquired MS/MS spectra were used for identification and quantification of the proteins. Spectra were analysed with Sequest algorithm implemented in Proteome Discoverer (version 2.0., ThermoFisher Scientific). Supplementary Material 2. Statistical analysis of proteins eligible for paired sample analysis. Description: Supplementary Table 2 is representing 191 proteins eligible for paired samples analysis (two Unique Peptides and 1% FDR). Results obtained with Wilcoxon signed-rank test reveal 10 Master proteins with statistically significant p -value differences before and after the race.   