Evidence map›Paper›PMID 42941180›Full record

ReviewMetabolites2026

Metabolomics for Athlete Monitoring: An Evidence-Readiness Framework for Contextual Validation.

Donghai Lin, Yifen Chen, Caihua Huang, Zhiyun Zou

Abstract readReview
In one paragraph

Review in Metabolites, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Donghai LinKey Laboratory for Chemical Biology of Fujian Province, High-Field NMR Research Center, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.ORCID 0000-0002-2318-2033
Yifen ChenKey Laboratory for Chemical Biology of Fujian Province, High-Field NMR Research Center, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.
Caihua HuangResearch and Communication Center of Exercise and Health, Xiamen University of Technology, Xiamen 361024, China.ORCID 0000-0001-5134-0169
Zhiyun ZouKey Laboratory for Chemical Biology of Fujian Province, High-Field NMR Research Center, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.

Funding

key project of the national key research and development plan " Active health and population aging technology response " No. 2025YFC3610200National Natural Science Foundation of China Nos. 32271496, 31971357Research Foundation for Middle-aged and Young Scientists of Fujian Province No. 2021ZQN
6 · The paper itself

Abstract

Metabolomics can place the metabolic consequences of training, competition, recovery, nutrition, and environmental exposure in a physiological context. However, an exercise-responsive metabolite should not be regarded as decision-ready on the basis of a pre-post association alone, because interpretation depends on the biological matrix, sampling time, analytical performance, athlete characteristics, and intended monitoring question. This structured narrative review examines the requirements for translating metabolomic findings into athlete monitoring. English-language, peer-reviewed studies were identified through structured searches of PubMed, Scopus, and Web of Science from 1 January 2020 through 31 July 2026. We distinguish source-evidence directness from validation maturity, which comprises discovery, analytical validation with independent replication, within-athlete longitudinal validation, and implementation testing against prespecified sport-relevant outcomes. We consider pathway-level interpretation of signals related to substrate use, recovery, and physiological stress, together with the metadata, repeated sampling, analytical quality control, and comparative testing required to establish value beyond established monitoring measures. Wearable biochemical sensing, continuous glucose monitoring, artificial intelligence, and multi-omics approaches may provide contextual information, but require analyte-specific calibration, transparent modeling, external validation, and demonstrated practical value. Metabolomics should therefore function as an explanatory layer in multimodal athlete monitoring while individual panels are evaluated in clearly defined sport and decision contexts.

Indexed as

athlete monitoringbiomarker panelslongitudinal metabolomicsrecoverysports metabolomicstraining adaptation

Identifiers

PMID42941180
PMCPMC13706814

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.