ArticleCell reports. Medicine2023
Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome.
Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
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Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.
- Effect of resting heart rate on the risk of metabolic syndrome in adults: a dose-response meta-analysis.Acta diabetologica · 2025Pooled it
- The MetaboHealth Score Enhances Insulin Resistance Metabotyping for Targeted Fat Loss: The PERSON Study.Obesity (Silver Spring, Md.) · 2026Trial
- Maternal hyperglycemia-induced O-GlcNAcylation of CaMKIIδ promotes mtDNA release and cardiac remodeling in offspring.Nature communications · 2026Article
- Metabolomic and lifestyle profiles refine BMI-metabolic phenotypes in older adults.Cell reports. Medicine · 2026Observational
- Artificial intelligence-driven integration of multi-biofluid omics and clinical phenotype enables stratification of endometrial cancer.Cell reports. Medicine · 2026Article
- Associations of dual-energy computed tomography-derived visceral adipose tissue quality and high-risk coronary plaque in patients with metabolic syndrome.Insights into imaging · 2026Article
- Polymeric anti-platelet carriers for the precision-targeting of age-related cardiovascular and cerebrovascular diseases.Materials today. Bio · 2026Review
- Lipemic Plasma Identified Blood Donors: Triglyceride Variability and Exploratory Machine Learning Analysis.Medical sciences (Basel, Switzerland) · 2026Article
- Article
- Dietary restriction genes as modulators of breast cancer risk through metabolic pathways.Lipids in health and disease · 2026Article
- A cooperative learning framework for the integration of metabolomic data from multiple cohorts and common phenotype identification.Computational and structural biotechnology journal · 2026Article
- Integrated metabolomics reveals lipid mediators and food-associated chemicals associated with metabolic syndrome.Frontiers in nutrition · 2026Article
- Omics-enhanced nanomedicine: integrating multi-omics for precision cancer diagnosis and therapy.Discover oncology · 2025Review
- Serum and urine metabolic fingerprints enable diagnosis and prognosis for IgA nephropathy.Materials today. Bio · 2025Article
- Review
- Interaction and biological pathway analysis of proteomic products in patients with premature coronary artery disease.Clinical proteomics · 2025Article
- Serum metabolic profiling enables diagnosis, prognosis, and monitoring for brainstem gliomas.Nature communications · 2025Article
- Targeting Regulation of Macrophage to Treat Metabolic Disease: Role of Phytochemicals.Cell proliferation · 2025Review
- Vessel-On-A-Chip Coupled Proteomics Reveal Pressure-Overload-Induced Vascular Remodeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Comparison of the predictive value of 17 anthropometric in-dices for the prevalence of metabolic syndrome among Chinese residents: a cross-sectional study.Diabetology & metabolic syndrome · 2025Article
Corrections and comments
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Direct diagnosis and accurate assessment of metabolic syndrome (MetS) allow for prompt clinical interventions. However, traditional diagnostic strategies overlook the complex heterogeneity of MetS. Here, we perform metabolomic analysis in 13,554 participants from the natural cohort and identify 26 hub plasma metabolic fingerprints (PMFs) associated with MetS and its early identification (pre-MetS). By leveraging machine-learning algorithms, we develop robust diagnostic models for pre-MetS and MetS with convincing performance through independent validation. We utilize these PMFs to assess the relative contributions of the four major MetS risk factors in the general population, ranked as follows: hyperglycemia, hypertension, dyslipidemia, and obesity. Furthermore, we devise a personalized three-dimensional plasma metabolic risk (PMR) stratification, revealing three distinct risk patterns. In summary, our study offers effective screening tools for identifying pre-MetS and MetS patients in the general community, while defining the heterogeneous risk stratification of metabolic phenotypes in real-world settings.
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Registered trials
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.