Evidence map›Paper›PMID 39695759›Full record

ArticleCardiovascular diabetology2024

Sphingolipid profiling as a biomarker of type 2 diabetes risk: evidence from the MIDUS and PREDIMED studies.

Loni Berkowitz, Cristina Razquin, Cristian Salazar, Fiorella Biancardi, Ramón Estruch, Emilio Ros, Montserrat Fitó, Dolores Corella, Christopher L Coe, Carol D Ryff and 7 more

Registry-linked trialAbstract readMulticenter Study
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07287514 (Role of Linoleic Acid in Cardiometabolic Health Beyond Its Lipid-lowering Effects, and Its Dietary and Pathophysiological Implications), which is not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT07287514 narecruitingnot on this mapstarted 2025, after this paper: background citation

Role of Linoleic Acid in Cardiometabolic Health Beyond Its Lipid-lowering Effects, and Its Dietary and Pathophysiological Implications

TypeinterventionalSponsorPontificia Universidad Catolica de ChileRan2025 to 2026Enrolled120ConditionsInsulin Resistance, Metabolic DiseaseArmsLinoleic Acid-Rich Oil, Blend Oil
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Loni BerkowitzDepartment of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica of Chile, Diagonal Paraguay #362, Santiago, Chile. loniberko@gmail.com.
Cristina RazquinDepartment of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain.
Cristian SalazarDepartment of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica of Chile, Diagonal Paraguay #362, Santiago, Chile.
Fiorella BiancardiDepartment of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica of Chile, Diagonal Paraguay #362, Santiago, Chile.
Ramón EstruchDepartment of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
Emilio RosLipid Clinic, Department of Endocrinology and Nutrition, August Pi Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
Montserrat FitóSpanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition (CIBEROBN), Health Institute Carlos III, Madrid, Spain.
Dolores CorellaDepartment of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain.
Christopher L CoeDepartment of Psychology, University of Wisconsin-Madison, Madison, WI, USA.
Carol D RyffInstitute on Aging, University of Wisconsin-Madison, Madison, WI, USA.
Miguel Ruiz-CanelaDepartment of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain.
Jordi Salas-SalvadoSpanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition (CIBEROBN), Health Institute Carlos III, Madrid, Spain.
Daniel WangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Frank B HuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Amy DeikThe Broad Institute of Harvard and MIT, Boston, MA, USA.
Miguel A Martínez-GonzalezDepartment of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain.
Attilio RigottiDepartment of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica of Chile, Diagonal Paraguay #362, Santiago, Chile.

Funding

U19 MIDlife in the United States-Diversity Supplement-WellsU19AG051426 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI CAROL D. RYFF · 2016 to 2026
$74.8M
STATISTICS COREP01AG020166 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI RYFF, CAROL D. · 2002 to 2015
$50.6M
Integrative Pathways to Cognitive, Affective, and Brain HealthU01AG077928 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sterling C Johnson, MARGIE E LACHMAN · 2022 to 2026
$17.7M
Dietary Interventions, Metabolites, and Risk of Type 2 DiabetesR01DK102896 · NIDDK · HARVARD SCHOOL OF PUBLIC HEALTH · PI HU, FRANK B, MARTINEZ GONZALEZ, MIGUEL A. · 2014 to 2017
$1.9M
Agencia Nacional de Investigación y Desarrollo FONDECYT #3210391Instituto de Salud Carlos III RD 06/0045NIA NIH HHS P01 AG020166NIA NIH HHS P01-AG020166NIA NIH HHS U01 AG077928NIA NIH HHS U19 AG051426NIDDK NIH HHS R01 DK102896NIH HHS R01-DK-102896
6 · The paper itself

Abstract

backgroundType 2 diabetes (T2D) has become a worldwide pandemic. While ceramides may serve as intermediary between obesity-related lipotoxicity and T2D, the relationship with simple glycosphingolipids remains uncertain. The aim of this study was to characterize the associations between blood glycosphingolipid and ceramide species with T2D and to identify a circulating sphingolipid profile that could serve as novel biomarker for T2D risk.

methodsCross-sectional relationship between sphingolipid levels, insulin resistance, and T2D prevalence were evaluated in 2,072 American adults from MIDUS cohort. Prospectively, the association between sphingolipid species and the incidence of T2D was analyzed using a case-cohort design nested within the PREDIMED trial (250 cases and a random sample of 692 participants, with 3.8 years of median follow-up). Circulating levels of sphingolipid species in both populations were measured using LC/MS. Hazard ratios were estimated with weighted Cox regression models using Barlow weights.

resultsIn American adults, only CER18:0 and CER22:0 were linked to insulin resistance and a higher prevalence of T2D. Conversely, three lactosylceramides (LCER 14:0, 16:0, and 24:1) showed a strong inverse relationship with both insulin resistance and T2D. These findings led to development of two sphingolipid scores. In the prospective analysis, these scores consistently predicted a reduced risk of T2D incidence in PREDIMED (HR: 0.64, 95% CI 0.44 to 0.94 and 0.58, 0.40 to 0.85 respectively) between extreme quartiles, with 5-year absolute risk differences of 9.6% (95% CI: 0.3-20.5%) and 11.4% (1.0-21.6%). They were validated in the same trial with samples obtained after 1 year of follow-up.

conclusionsOur findings support the potential usefulness of circulating sphingolipid profiles as novel biomarkers for T2D risk. Moreover, this study opens the door for future research on the predictive value and possible protective roles of lactosylceramides in T2D.

Indexed as

BiomarkersCeramidesDiabetes Mellitus, Type 2Insulin ResistancePredictive Value of TestsAgedAged, 80 and overCross-Sectional StudiesFemaleHumansIncidenceLipidomicsMaleMiddle AgedPrevalenceProspective StudiesBiomarkersCeramidesSphingolipidsCeramidesInsulin resistanceLactosylceramidesSphingolipidsType 2 diabetes

Identifiers

PMID39695759
PMCPMC11657495

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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.