Application of untargeted plasma metabolomics and machine learning to construct a diagnostic model for hypertrophic cardiomyopathy: a case-control study
Plasma metabolite diagnostic model including KAPA, γ-linolenoyl ethanolamid, nitrilotriacetic acid, D-quinovose and NAA can effectively and accurately screen HCM patients. Metabolomics combined with ML algorithm showed that alanine, aspartate and glutamate metabolism may be the pathogenic pathway leading to the occurrence of HCM with NAA as the central target.
Authors
- 博之 中山 (ORCID: https://orcid.org/0009-0002-4431-0302)
- Ruoxuan Li (ORCID: https://orcid.org/0000-0001-6095-7945)
- Yiming Yuan (ORCID: https://orcid.org/0009-0001-6978-3619)
- Lei Fan (ORCID: https://orcid.org/0000-0002-9368-4987)
- Mao Sun (ORCID: https://orcid.org/0000-0003-1379-6573)
- Xin’an Li
- Nan Kang
- Shengjun Ta
- Hongjing Zheng
- Bo Wang
- Huiyi Wang
- Fan Yang
- Jing Wang
- Liwen Liu
- Jia Zhao
Institutions
- Xijing Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- Metabolomics
- Published
- 2026-03-07
- DOI
- https://doi.org/10.1007/s11306-026-02412-w
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00