Evidence map›Paper›PMID 41013857›Full record

ArticleCardiovascular diabetology. Endocrinology reports2025

Cluster analysis reveals distinct inflammatory phenotypes in cardiometabolic disease.

Jaqueline Bianchi, Fernanda Oliveira Duarte, Luciana Camillo, Krissia Franco de Godoy, Joice Margareth de Almeida Rodolpho, Bruna Dias de Lima Fragelli, Maria Clara Cavalcante Espósito, Leticia Americano Branco, Carlos Speglich, Meliza Goi Roscani and 2 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology. Endocrinology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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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

12 authors.

Jaqueline BianchiLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil. jaqueline_bianchi@yahoo.com.br.
Fernanda Oliveira DuarteLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Luciana CamilloLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Krissia Franco de GodoyLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Joice Margareth de Almeida RodolphoLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Bruna Dias de Lima FragelliCenter for Development of Functional Materials, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Maria Clara Cavalcante EspósitoDepartment of Medicine, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Leticia Americano BrancoDepartment of Medicine, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Carlos SpeglichLeopoldo Américo Miguez de Mello Research Center CENPES/Petrobras, Rio de Janeiro, Brazil.
Meliza Goi RoscaniDepartment of Medicine, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Henrique PottDepartment of Medicine, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.
Fernanda de Freitas AnibalLaboratory of Inflammation and Infectious Diseases, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, SP, Brazil.

Funding

Petrobras 2022/00220-0
6 · The paper itself

Abstract

backgroundCardiovascular disease and type 2 diabetes mellitus share inflammatory pathways; however, their combined effect on systemic inflammation remains unclear. Although chronic low-grade inflammation is recognized in both conditions, the heterogeneity of inflammatory responses in patients with comorbidities has not been systematically characterized. This study aimed to identify distinct inflammatory phenotypes in patients with CVD, T2DM, or both and evaluate their clinical and biomarker profiles.

methodsWe conducted a cross-sectional study of 240 outpatients from Brazilian cardiology clinics, who were categorized into three groups: CVD + T2DM+ (n = 51), CVD + T2DM- (n = 95), and controls without either condition (n = 94). Serum levels of IL-6, IL-1β, TNF-α, and cardiac biomarkers (CK-MB, NT-proBNP, D-dimer) were measured using chemiluminescence immunoassays. Gaussian Mixture Models identified inflammatory clusters, which were validated using silhouette analysis. Statistical comparisons were performed using Kruskal-Wallis tests for continuous variables and chi-square tests for categorical variables, with ridge regression to assess phenotype predictors.

resultsAnalysis revealed three distinct inflammatory phenotypes: Phenotype 1 (n = 74) showed the lowest inflammatory markers (IL-6:2.00 pg/mL; CRP: 3.22 mg/L) and CVD prevalence (32.4%). Phenotype 2 (n = 83) had the highest CVD burden (81.9%) but unexpectedly low TNF-α (6.37 pg/mL) despite elevated D-dimer (0.76 µg/mL). Phenotype 3 (n = 83) exhibited the most severe inflammation (TNF-α: 12.90 pg/mL; hs-CRP: 5.00 mg/L) and the highest comorbidity rate (25.3% CVD + T2DM+). Phenotype 3 also showed significantly higher CK-MB (2.46 vs. 1.00 ng/mL, p < 0.001) and IL-8 (12.6 vs. 10.85 pg/mL, p < 0.001) levels than the other groups. Regression analysis identified age (OR = 2.24, 95% CI: 1.69-3.00) and CVD (OR = 1.47, 95% CI: 1.04-2.04) as significant phenotype predictors.

conclusionThis study identified three clinically distinct inflammatory phenotypes in cardiometabolic diseases, with T2DM exacerbating systemic inflammation in patients with pre-existing CVD. The discordant phenotype (high CVD burden but low TNF-α levels) challenges current inflammatory models and suggests alternative pathways in some patients. These findings support the need for phenotype-specific approaches for risk stratification and targeted anti-inflammatory therapies in high-risk subgroups.

Indexed as

Cardiovascular diseaseGaussian mixture modelsInflammatory phenotypesSystemic inflammationType 2 diabetes mellitus

Identifiers

PMID41013857
PMCPMC12320283

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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 OpenQuestion graph.