Evidence map›Paper›PMID 38007148›Full record

ArticleMetabolism: clinical and experimental2024

Plasma metabolite predictors of metabolic syndrome incidence and reversion.

Zhila Semnani-Azad, Estefanía Toledo, Nancy Babio, Miguel Ruiz-Canela, Clemens Wittenbecher, Cristina Razquin, Fenglei Wang, Courtney Dennis, Amy Deik, Clary B Clish and 11 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Metabolism: clinical and experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Trial
  2. Article
  3. Metabolic syndrome and a broken heart: trust your gut or risk your heart.American journal of physiology. Heart and circulatory physiology · 2026
    Review
  4. Article
  5. Article
  6. Review
  7. Human plasma metabolomics reveals metabolic targets for intervention in salt-sensitive hypertension.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
    Article
  8. Review
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

21 authors at 10 institutions in 4 countries.

Zhila Semnani-AzadDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: zsemnaniazad@hsph.harvard.edu.
Estefanía ToledoDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: etoledo@unav.es.
Nancy BabioCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain. Electronic address: nancy.babio@urv.cat.
Miguel Ruiz-CanelaDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: mcanela@unav.es.
Clemens WittenbecherDivision of Food and Nutrition Sciences, Department of Biology, Chalmers University of Technology, Gothenburg, Sweden. Electronic address: clemens.wittenbecher@chalmers.se.
Cristina RazquinDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: crazquin@unav.es.
Fenglei WangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: fengleiwang@g.harvard.edu.
Courtney DennisMetabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: cdennis@broadinstitute.org.
Amy DeikMetabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: adeik@broadinstitute.org.
Clary B ClishMetabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: clary@broadinstitute.org.
Dolores CorellaCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain. Electronic address: dolores.corella@uv.es.
Montserrat FitóCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; IMIM Hospital del Mar Medical Research Institute, Grup de Risc Cardiovascular i Nutrició, Barcelona, Spain. Electronic address: MFito@imim.es.
Ramon EstruchCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. Electronic address: restruch@clinic.cat.
Fernando ArósCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain. Electronic address: lfaborau@gmail.com.
Emilio RosLipid Clinic, Department of Endocrinology and Nutrition, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. Electronic address: EROS@clinic.cat.
Jesús García-GavilanCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain. Electronic address: jesusfrancisco.garcia@iispv.cat.
Liming LiangDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: lliang@hsph.harvard.edu.
Jordi Salas-SalvadóCentro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain. Electronic address: jordi.salas@urv.cat.
Miguel A Martínez-GonzálezDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: mamartinez@unav.es.
Frank B HuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: fhu@hsph.harvard.edu.
Marta Guasch-FerréDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen, Copenhagen, Denmark. Electronic address: mguasch@hsph.harvard.edu.
Harvard University · USBroad Institute · USSpanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition · ESInstituto de Salud Carlos III · ESNavarre Institute of Health Research · ESUniversitat de Barcelona · ESChalmers University of Technology · SEHospital del Mar Research Institute · ESHospital Universitario Araba · ESUniversitat de València · ES

Funding

ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · MASSACHUSETTS GENERAL HOSPITAL · 1994 to 2025
$6.0M
Mediterranean diet, Metabolites, and Cardiovascular DiseaseR01HL118264 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · 2023 to 2025
$1.0M
NHLBI NIH HHS R01 HL118264NIDDK NIH HHS P30 DK040561NIDDK NIH HHS R01 DK102896
6 · The paper itself

Abstract

backgroundMetabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion.

methodsThe study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors.

resultsOf the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids.

conclusionWe identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.

Indexed as

Cardiovascular DiseasesMetabolic SyndromeAmino Acids, Branched-ChainGlycerophospholipidsHumansIncidenceLipidsRisk FactorsAmino Acids, Branched-ChainGlycerophospholipidsLipidsMetabolic syndromeMetabolic syndrome incidenceMetabolic syndrome reversionMetabolomicsPREDIMED

Identifiers

PMID38007148
PMCPMC10872312
OpenAlexW4388974337

What Socratic holds

Textmetadata
LicenceTDM
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Registered trials

None linked

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.