ArticleLipids in health and disease2016
Lipidomic risk score independently and cost-effectively predicts risk of future type 2 diabetes: results from diverse cohorts.
Article in Lipids in health and disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.
- Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies.Diabetes care · 2022Pooled it
- Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial.The American journal of clinical nutrition · 2023Trial
- Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program.BMJ open diabetes research & care · 2021Trial
- Sphingolipids in human disease: organ-specific pathologies, chain-length-dependent effects, and translational implications.Journal of translational medicine · 2026Review
- Evolutionary Conservation of Lipid-Associated Epigenetic Signatures and Their Distinct Roles in Tissue Identity and Mammalian Aging.Biomedicines · 2026Article
- Plasma lipidomics and 15-year risk of incident diabetes: a coronary artery risk development in young adults study.Journal of lipid research · 2026Article
- Effects of short-term exercise on plasma metabolic and lipidomic profiles of individuals with type 2 diabetes.Experimental physiology · 2026Article
- Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic Response.Diabetes & metabolism journal · 2024Review
- A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.EBioMedicine · 2024Article
- Alveolar Epithelial Cell Dysfunction in Idiopathic Pulmonary Fibrosis Linked to Lipid Alterations: Therapeutic Implications.American journal of respiratory cell and molecular biology · 2024Article
- Circulating Sphingolipids in Insulin Resistance, Diabetes and Associated Complications.International journal of molecular sciences · 2023Review
- Review
- Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry.Journal of proteome research · 2023Article
- Integrated Analysis of Metabolomics and Lipidomics in Plasma of T2DM Patients with Diabetic Retinopathy.Pharmaceutics · 2022Article
- Serum lipidomics profiles reveal potential lipid markers for prediabetes and type 2 diabetes in patients from multiple communities.Frontiers in endocrinology · 2022Article
- Longitudinal Plasma Lipidome and Risk of Type 2 Diabetes in a Large Sample of American Indians With Normal Fasting Glucose: The Strong Heart Family Study.Diabetes care · 2021Article
- A Randomized Controlled Dietary Intervention Improved the Serum Lipid Signature towards a Less Atherogenic Profile in Patients with Rheumatoid Arthritis.Metabolites · 2021Article
- Lipid Traffic Analysis reveals the impact of high paternal carbohydrate intake on offsprings' lipid metabolism.Communications biology · 2021Article
- Multi-Omics Analysis Reveals Disturbance of Nanosecond Pulsed Electric Field in the Serum Metabolic Spectrum and Gut Microbiota.Frontiers in microbiology · 2021Article
- Dihydroceramides in Triglyceride-Enriched VLDL Are Associated with Nonalcoholic Fatty Liver Disease Severity in Type 2 Diabetes.Cell reports. Medicine · 2020Article
Corrections and comments
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Authors and funding
18 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundDetection of type 2 diabetes (T2D) is routinely based on the presence of dysglycemia. Although disturbed lipid metabolism is a hallmark of T2D, the potential of plasma lipidomics as a biomarker of future T2D is unknown. Our objective was to develop and validate a plasma lipidomic risk score (LRS) as a biomarker of future type 2 diabetes and to evaluate its cost-effectiveness for T2D screening.
methodsPlasma LRS, based on significantly associated lipid species from an array of 319 lipid species, was developed in a cohort of initially T2D-free individuals from the San Antonio Family Heart Study (SAFHS). The LRS derived from SAFHS as well as its recalibrated version were validated in an independent cohort from Australia--the AusDiab cohort. The participants were T2D-free at baseline and followed for 9197 person-years in the SAFHS cohort (n = 771) and 5930 person-years in the AusDiab cohort (n = 644). Statistically and clinically improved T2D prediction was evaluated with established statistical parameters in both cohorts. Modeling studies were conducted to determine whether the use of LRS would be cost-effective for T2D screening. The main outcome measures included accuracy and incremental value of the LRS over routinely used clinical predictors of T2D risk; validation of these results in an independent cohort and cost-effectiveness of including LRS in screening/intervention programs for T2D.
resultsThe LRS was based on plasma concentration of dihydroceramide 18:0, lysoalkylphosphatidylcholine 22:1 and triacyglycerol 16:0/18:0/18:1. The score predicted future T2D independently of prediabetes with an accuracy of 76%. Even in the subset of initially euglycemic individuals, the LRS improved T2D prediction. In the AusDiab cohort, the LRS continued to predict T2D significantly and independently. When combined with risk-stratification methods currently used in clinical practice, the LRS significantly improved the model fit (p < 0.001), information content (p < 0.001), discrimination (p < 0.001) and reclassification (p < 0.001) in both cohorts. Modeling studies demonstrated that LRS-based risk-stratification combined with metformin supplementation for high-risk individuals was the most cost-effective strategy for T2D prevention.
conclusionsConsidering the novelty, incremental value and cost-effectiveness of LRS it should be used for risk-stratification of future T2D.
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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 Socratic graph.