Trial reportThe American journal of clinical nutrition2019
Plasma metabolites predict both insulin resistance and incident type 2 diabetes: a metabolomics approach within the Prevención con Dieta Mediterránea (PREDIMED) study.
Trial report in The American journal of clinical nutrition, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 40 citations in OpenAlex.
- Trial
- Plasma acylcarnitines and risk of lower-extremity functional impairment in older adults: a nested case-control study.Scientific reports · 2021Trial
- Compartment-specific Metabolic Alterations to Insulin Reflect Adiposity-driven Variation and Predict Type 2 Diabetes.The Journal of clinical endocrinology and metabolism · 2026Article
- Gene-Embedded Multi-Modal Networks for Population-Scale Multi-Omics Discovery.bioRxiv : the preprint server for biology · 2025Article
- Glycine receptor activation promotes pancreatic islet cell proliferation via the PI3K/mTORC1/p70S6K pathway.JCI insight · 2025Article
- Metabolomics uncovers the diabetes metabolic network: from pathophysiological mechanisms to clinical applications.Frontiers in endocrinology · 2025Review
- Type 2 diabetes metabolomics score and risk of progression to type 2 diabetes among women with a history of gestational diabetes mellitus.Diabetes/metabolism research and reviews · 2024Article
- Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study.Biomedicines · 2023Article
- Review
- Metabolite profiles of diabetes mellitus and response to intervention in anti-hyperglycemic drugs.Frontiers in endocrinology · 2023Review
- Presurgical blood metabolites and risk of postsurgical pelvic pain in young patients with endometriosis.Fertility and sterility · 2022Observational
- LC-MS-Based Lipidomic Analysis of Serum Samples from Patients with Type 2 Diabetes Mellitus (T2DM).Disease markers · 2022Article
- Impact of Different Durations of Fasting on Intestinal Autophagy and Serum Metabolome in Broiler Chicken.Animals : an open access journal from MDPI · 2021Article
- Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity.Metabolites · 2021Article
- Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes.Scientific reports · 2021Article
- Plasma Metabolomic Profiles of Glycemic Index, Glycemic Load, and Carbohydrate Quality Index in the PREDIMED Study.The Journal of nutrition · 2021Article
- Plasma Metabolomics Reveals Metabolic Profiling For Diabetic Retinopathy and Disease Progression.Frontiers in endocrinology · 2021Article
- Diminished Sphingolipid Metabolism, a Hallmark of Future Type 2 Diabetes Pathogenesis, Is Linked to Pancreatic β Cell Dysfunction.iScience · 2020Article
- Serum sphingolipids and incident diabetes in a US population with high diabetes burden: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).The American journal of clinical nutrition · 2020Article
- Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts.International journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
20 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundInsulin resistance is a complex metabolic disorder and is often associated with type 2 diabetes (T2D).
objectivesThe aim of this study was to test whether baseline metabolites can additionally improve the prediction of insulin resistance beyond classical risk factors. Furthermore, we examined whether a multimetabolite model predicting insulin resistance in nondiabetics can also predict incident T2D.
methodsWe used a case-cohort study nested within the Prevención con Dieta Mediterránea (PREDIMED) trial in subsets of 700, 500, and 256 participants without T2D at baseline and 1 and 3 y. Fasting plasma metabolites were semiquantitatively profiled with liquid chromatography-tandem mass spectrometry. We assessed associations between metabolite concentrations and the homeostasis model of insulin resistance (HOMA-IR) through the use of elastic net regression analysis. We subsequently examined associations between the baseline HOMA-IR-related multimetabolite model and T2D incidence through the use of weighted Cox proportional hazard models.
resultsWe identified a set of baseline metabolites associated with HOMA-IR. One-year changes in metabolites were also significantly associated with HOMA-IR. The area under the curve was significantly greater for the model containing the classical risk factors and metabolites together compared with classical risk factors alone at baseline [0.81 (95% CI: 0.79, 0.84) compared with 0.69 (95% CI: 0.66, 0.73)] and during a 1-y period [0.69 (95% CI: 0.66, 0.72) compared with 0.57 (95% CI: 0.53, 0.62)]. The variance in HOMA-IR explained by the combination of metabolites and classical risk factors was also higher in all time periods. The estimated HRs for incident T2D in the multimetabolite score (model 3) predicting high HOMA-IR (median value or higher) or HOMA-IR (continuous) at baseline were 2.00 (95% CI: 1.58, 2.55) and 2.24 (95% CI: 1.72, 2.90), respectively, after adjustment for T2D risk factors.
conclusionsThe multimetabolite model identified in our study notably improved the predictive ability for HOMA-IR beyond classical risk factors and significantly predicted the risk of T2D.
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