Evidence map›Paper›PMID 41131087›Full record

ArticleCommunications medicine2025

Metabolomics for searching non-invasive biomarkers of metabolic dysfunction-associated steatotic liver disease in youth with vertical HIV.

Silvia Chafino, Laura Tarancon-Diez, Jara Hurtado-Gallego, Marina Flores-Piñas, Sonia Alcolea, Antonio Olveira, María Luisa Navarro, Salvador Fernández-Arroyo, Consuelo Viladés, Maria Luisa Montes and 4 more

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

14 authors.

Silvia ChafinoCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID http://orcid.org/0000-0001-9679-0622
Laura Tarancon-DiezCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID http://orcid.org/0000-0002-9528-4098
Jara Hurtado-GallegoCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID http://orcid.org/0000-0003-2509-857X
Marina Flores-PiñasInfection and Immunity Research Group (INIM), Institut Investigació Sanitària Pere Virgili (IISPV), Hospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain.ORCID http://orcid.org/0009-0001-4021-7701
Sonia AlcoleaCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID http://orcid.org/0000-0003-1233-1723
Antonio OlveiraGastroenterology and Hepatology Department, Hospital Universitario La Paz, Madrid, Spain.
María Luisa NavarroCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Salvador Fernández-ArroyoEurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences, Joint Unit Eurecat-Universitat Rovira i Virgili, Unique Scientific and Technical Infrastructure (ICTS), 43204, Reus, Spain.ORCID http://orcid.org/0000-0003-0147-1712
Consuelo ViladésCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Maria Luisa MontesHIV Unit, Internal Medicine Department Hospital Universitario La Paz y La Paz Research Institute (IdiPAZ), Madrid, Spain.ORCID http://orcid.org/0000-0003-1748-813X
Francesc VidalCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Joaquim PeraireCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID http://orcid.org/0000-0001-7808-5479
Anna RullCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain. anna.rull@iispv.cat.ORCID http://orcid.org/0000-0002-8907-7754
Talía SainzCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain. talia.sainz@uam.es.ORCID http://orcid.org/0000-0002-5301-0945

Funding

Government of Catalonia | Agència de Gestió d'Ajuts Universitaris i de Recerca (Agency for Management of University and Research Grants) 2021SGR01404Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) CB21/13/00077Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) CP19/00146, PI20/00326, PI23/0080Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) CP23/00009Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) FI24/00034Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI19/01337Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI23/0080, CB21/13/00020
6 · The paper itself

Abstract

backgroundIn adults living with HIV, non-invasive biomarkers have been described for the early identification of metabolic dysfunction-associated steatotic liver diseases (MASLD). However, this issue remains unexplored in children and young people with vertical HIV (YWVH), among whom MASLD prevalence is around 30%.

methodsTo identify biomarkers associated with MASLD in YWVH under sustained viral suppression with antiretroviral therapy, we analysed plasma lipid species, plasma bile acid profile, and gut microbiome composition in a cross-sectional cohort of 10 YWVH with MASLD and 19 YWVH without clinical evidence of MASLD (control).

resultsHere we show that YWVH with MASLD have significantly increased circulating levels of eight specific lipid molecules and one bile acid, ursodeoxycholic acid (UDCA). UDCA and two triglycerides (TG54:5 and TG56:7) are identified as key biomolecules with strong discriminatory potential. The regression model incorporating these markers, along with hepatic steatosis index (HSI) and triglycerides-glucose index (TyG), demonstrates the highest predictive accuracy for MASLD (AUC of 0.932). UDCA correlates positively with Blautia and Collinsella genus (p = 0.040 and p = 0.021, respectively), and negatively with Faecalibacterium (p = 0.030). Notably, principal component analysis based on bile acid levels reveals two possible subpopulations within the control group, one potentially at higher risk for MASLD.

conclusionsCombining UDCA, TG54:5 and TG56:7 with the validated HSI score provides a potential model with high specificity and sensitivity for predicting MASLD in YWVH. Moreover, early alterations in the bile acid profile may help identify YWVH at risk of developing MASLD.

Identifiers

PMID41131087
PMCPMC12549917

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.