Comments on: ‘Exercise‐specific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring’

We read with interest the study by Grzedzicka et al.: 'Exercisespecific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring' published recently in Equine Veterinary Journal. 1 Molecular techniques give an opportunity for deeper insight into physiological and pathological processes; sometimes we are even lucky enough to find a new biomarker or a new mechanism.Grzedzicka and colleagues stated that on the basis of equine plasma proteomic profiles during training and racing, they aimed to identify novel plasma biomarkers of training adaptation and peak load.Their additional aim was to discover candidate biomarkers linked to training status, oxidative stress, inflammation and metabolic remodelling.While we respect Grzedzicka's lab's extensive work, we would like to address the fundamental concern regarding the composition of the study population.This combined horses of markedly different breeds, ages and sex into a single analytical group.In our opinion based on published literature data and our experiences with performance horses, this composition poses the severe limitation that can reduce interpretability, increase confounding and weaken confidence in attributing observed proteomic changes specifically to the training stage.Thus, it severely limits the ability to draw meaningful and clinically relevant conclusions regarding training and isolate them from other biologically relevant sources of variation.

Authors

Institutions

Publication Details

Journal
Equine Veterinary Journal
Published
2026-10-13
DOI
https://doi.org/10.1002/evj.70343
Primary Topic
Veterinary Equine Medical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comments on: ‘Exercise‐specific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring’

Ewa Szarska, Anna Cywińska, Katarzyna Strzelec
Equine Veterinary Journal
Veterinary Equine Medical Research
article

Comments on: ‘Exercise‐specific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring’

Ewa Szarska, Anna Cywińska, Katarzyna Strzelec
article en

Abstract

We read with interest the study by Grzedzicka et al.: 'Exercisespecific plasma proteomic signatures in racehorses: Candidates for training adaptation and peak load monitoring' published recently in Equine Veterinary Journal. 1 Molecular techniques give an opportunity for deeper insight into physiological and pathological processes; sometimes we are even lucky enough to find a new biomarker or a new mechanism.Grzedzicka and colleagues stated that on the basis of equine plasma proteomic profiles during training and racing, they aimed to identify novel plasma biomarkers of training adaptation and peak load.Their additional aim was to discover candidate biomarkers linked to training status, oxidative stress, inflammation and metabolic remodelling.While we respect Grzedzicka's lab's extensive work, we would like to address the fundamental concern regarding the composition of the study population.This combined horses of markedly different breeds, ages and sex into a single analytical group.In our opinion based on published literature data and our experiences with performance horses, this composition poses the severe limitation that can reduce interpretability, increase confounding and weaken confidence in attributing observed proteomic changes specifically to the training stage.Thus, it severely limits the ability to draw meaningful and clinically relevant conclusions regarding training and isolate them from other biologically relevant sources of variation.

Equine Veterinary Journal
University of Life Sciences in Lublin (PL), Nicolaus Copernicus University (PL)
Openalex Percentile: Top 10%
Veterinary Equine Medical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.