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Study 20 of 24L-Carnitine (Levocarnitine) literatureComparative biochemistry and physiology. Part D, Genomics & proteomics · Observational2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

This study identifies long-chain acylcarnitines as potential biomarkers for ovarian aging in hens, which could help in understanding reproductive performance in poultry.

Read at Comparative biochemistry and physiology. Part D, Genomics & proteomicsAdd to compare

Where it sits

this study against the rest of the l-carnitine (levocarnitine) corpus
5
Preclinical
15
Observational · this one
0
Open-label
2
Randomised
2
Reviews

Summary and findings

This study measured metabolic profiles and identified biomarkers of ovarian aging in Taihe silky fowls at different laying stages. The analysis was conducted using untargeted LC-MS/MS metabolomics and machine learning algorithms. Six core biomarkers were identified, including four long-chain acylcarnitines.

How much of this paper we could read: full text read (0.70). We had a clear abstract, so the summary below closely tracks the paper. What this means →
Not reported in abstract.2026

Abstract

The authors’ words, as Comparative biochemistry and physiology. Part D, Genomics & proteomics supplied them

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Background

The decline in ovarian function during the late laying period is a significant issue for the poultry industry, impacting economic efficiency. Previous studies have not fully elucidated the metabolic mechanisms or identified reliable biomarkers for ovarian aging. This study aims to fill that gap by employing advanced metabolomics and machine learning techniques to identify potential biomarkers in hens.

Methods

The study utilized untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at two stages: peak laying (30 weeks) and late laying (50 weeks). An ensemble machine learning strategy incorporating LASSO, random forest, and support vector machine algorithms was used to identify biomarkers. Gene expression analysis was also conducted to validate potential mechanisms.

Results

The study found significant differences in metabolic profiles between the two laying stages. Six core biomarkers were identified, with four being long-chain acylcarnitines. The downregulation of genes in the carnitine shuttle system was associated with impaired mitochondrial function and increased oxidative stress.

Interpretation

These findings contribute to the understanding of ovarian aging in poultry, highlighting long-chain acylcarnitines as potential biomarkers. However, the clinical significance of these biomarkers remains unclear, and the study's focus on a specific breed may limit broader applicability. The results suggest a need for further research to explore these mechanisms in diverse populations.

Key findings

  • Metabolic profiles of ovarian tissues differed significantly between peak laying (30 weeks) and late laying (50 weeks) stages.
  • A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines.
  • Downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation.
  • Excessive oxidative stress was triggered, compromising ovarian endocrine function.

Limitations

  • Focus on a specific breed limits generalizability.
  • No quantitative results reported in the abstract.
  • Further research needed to confirm findings in other populations.

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