ArticleMetabolomics : Official journal of the Metabolomic Society2024
Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia.
Article in Metabolomics : Official journal of the Metabolomic Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring Human Sperm Metabolism and Male Infertility: A Systematic Review of Genomics, Proteomics, Metabolomics, and Imaging Techniques.International journal of molecular sciences · 2025Pooled it
- Trimethylamine N-Oxide and Impaired Spermatogenesis in the Gut-Testis Axis: A Focused Review of Current Evidence.Biology · 2026Review
- Identification of salivary lipid biomarkers for noninvasive diagnosis of reflux esophagitis via UHPLC-MS-based lipidomics.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Article
- Extracellular vesicles from human semen induce unique tolerogenic phenotypes in vaginal dendritic cells and regulatory T lymphocytes.Frontiers in immunology · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundDespite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia.
methodsSeminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model.
resultsLipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0).
conclusionsLPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.
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