Multi-omics landscape and machine learning predictors of acute and chronic coronary syndrome diagnosis in young patients
Advanced blood and microbiome analysis detects heart attacks in young adults with chest pain far better than standard methods, addressing a genuine diagnostic gap.
This prospective multi-omics study (n=206) of young adults with chest pain integrated transcriptomics, metabolomics, and gut metagenomics to achieve near-perfect ACS diagnostic AUCs (0.95-0.99), identifying novel biomarkers including the gut bacterium Streptococcus parasanguinis as a potential atherogenic pathogen. The findings address a genuine unmet need in young CHD diagnosis but require external validation and regulatory consideration before clinical use.
What the study was
- Study design
- Prospective cohort; multi-omics integration (transcriptomics, serum metabolomics, stool metabolomics, gut metagenomics); ML diagnostic model development
- Population
- Young chest pain patients aged 18-45 years; Shenzhen People's Hospital, China
- Sample size
- 206
- Category
- Diagnostics
- Maturity
- Exploratory
- Journal
- Journal of Advanced Research
Why it surfaced
Novel multi-omics approach for young ACS; AUC values near 1.0 warrant skepticism about overfitting but address real unmet need. Single-center Chinese cohort; external validation essential.
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