Evidence map›Paper›PMID 30451909›Full record

ArticleScientific reports2018

Obesity shows preserved plasma proteome in large independent clinical cohorts.

Ornella Cominetti, Antonio Núñez Galindo, John Corthésy, Armand Valsesia, Irina Irincheeva, Martin Kussmann, Wim H M Saris, Arne Astrup, Ruth McPherson, Mary-Ellen Harper and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 6% 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

35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 69 citations in OpenAlex.

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  11. Precision Medicine for Obesity Treatment.Journal of the Endocrine Society · 2025
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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

13 authors at 7 institutions in 5 countries.

Ornella CominettiProteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Antonio Núñez GalindoProteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
John CorthésyProteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Armand ValsesiaNutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Irina IrincheevaNutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Martin KussmannProteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Wim H M SarisNUTRIM, School for Nutrition, Toxicology and Metabolism, Department of Human Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
Arne AstrupDepartment of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.
Ruth McPhersonRuddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada.
Mary-Ellen HarperDepartment of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada.
Robert DentOttawa Hospital Weight Management Clinic, The Ottawa Hospital, Ottawa, Canada.
Jörg HagerNutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Loïc DayonProteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland. loic.dayon@rd.nestle.com.ORCID http://orcid.org/0000-0002-8499-270X
Nestlé (Switzerland) · CHUniversity of Ottawa · CAMaastricht University Medical Centre · NLOttawa Hospital · CAUniversity of Auckland · NZUniversity of Bern · CHUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined "rectangular" design.

Indexed as

ProteomeAdultBlood ProteinsChromatography, LiquidCohort StudiesFemaleHumansMaleMiddle AgedObesityOverweightProteomicsReproducibility of ResultsTandem Mass SpectrometryBlood ProteinsProteome

Identifiers

PMID30451909
PMCPMC6242904
OpenAlexW2901443756

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.