Evidence mapPaperPMID 42123728Full record

ArticleInternational journal of molecular sciences2026

Inflammatory Proteomic Heterogeneity Beyond Glycemia Status in Severe Obesity.

Melissa M Milito, Mattia Chiesa, Alice Mallia, Giulia G Papaianni, Julia T Regalado, Claudio Tiribelli, Deborah Bonazza, Natalia Rosso, Silvia Palmisano, Cristina Banfi and 1 more

Abstract read
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Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Melissa M MilitoMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0009-0000-3431-1649
Mattia ChiesaBioinformatics and Artificial Intelligence Facility, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0001-7427-9954
Alice MalliaUnit of Functional Proteomics, Metabolomics, and Network Analysis, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-7088-9074
Giulia G PapaianniUnit of Functional Proteomics, Metabolomics, and Network Analysis, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0009-0005-3657-4043
Julia T RegaladoMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0009-0001-7323-0937
Claudio TiribelliMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0000-0001-6596-7595
Deborah BonazzaSurgical Pathology Unit, Cattinara Hospital, Azienda Sanitaria Universitaria Giuliano Isontina, 34149 Trieste, Italy.
Natalia RossoMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0000-0002-4251-3547
Silvia PalmisanoMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0000-0003-4749-4258
Cristina BanfiUnit of Functional Proteomics, Metabolomics, and Network Analysis, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0003-3346-9879
Pablo J GiraudiMetabolic Liver Disease Unit, Fondazione Italiana Fegato, 34012 Trieste, Italy.ORCID 0000-0003-2852-6648

Funding

European Union Grant 101095672Italian Ministry of Health Ricerca Corrente
6 · The paper itself

Abstract

Chronic low-grade inflammation is a key feature of obesity-associated dysglycemia, yet substantial heterogeneity exists in inflammatory responses among individuals with normoglycemia, prediabetes, and type 2 diabetes mellitus (T2DM). Whether circulating inflammatory protein profiles define distinct patient phenotypes beyond conventional glycemic classification remains incompletely understood. In this cross-sectional analysis of 142 individuals with severe obesity, plasma inflammatory proteins were quantified using Olink proximity extension assay technology. Subjects were stratified by glycemic status (noDM, normoglycemia; PreDM, prediabetes and T2DM) while maintaining comparable distributions of metabolic dysfunction-associated steatotic liver disease. Differential expression analyses were performed across glycemic groups, and unsupervised topological data analysis (TDA) was applied to identify inflammatory protein-based patient subgroups. Several inflammatory proteins were significantly upregulated in T2DM and PreDM compared with noDM, with interleukin-8 (IL-8), Fms-relatedlike tyrosine kinase 3 ligand (Flt3L), and CUB domain containing protein (CDCP1) showing the largest significant differences. NPX distributions of these proteins exhibited gradual increases across glycemic stages with substantial inter-individual variability. TDA identified seven clusters defined by distinct inflammatory protein signatures. One cluster was enriched for individuals with T2DM and characterized by coordinated upregulation of IL-8, Flt3L, CDCP1, and additional immune- and cytokine-related proteins, whereas other clusters displayed alternative inflammatory profiles that were not explained by glycemic status alone. Inflammatory proteomic profiling in severe obesity reveals both glycemia-associated protein changes and distinct inflammatory phenotypes that transcend conventional clinical classification. Integration of differential expression analysis with TDA highlights heterogeneity in inflammatory states, supporting a hypothesis-generating framework for future studies aimed at validating these proteomic patterns and clarifying their longitudinal relevance in obesity-related dysglycemia.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2InflammationObesity, MorbidProteomeProteomicsAdultBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrediabetic StateBiomarkersBlood GlucoseProteomeimmune phenotypesinflammatory proteomicslow-grade inflammationtopological data analysistype 2 diabetes

Identifiers

PMID42123728
PMCPMC13164250

What Socratic holds

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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.