Early inflammation as a footprint of increased mortality risk in infants living with HIV from three African countries

In this work our aim was to identify early biomarkers in plasma samples associated with mortality in children with perinatal HIV treated early in life, to potentially inform early intervention targeting this vulnerable group. 20/215 children (9.3%) with perinatal HIV, enrolled within 3 months of age died prematurely within the first year of the study, despite early ART initiation. Using a propensity score, we selected 40 alive study participants having similar clinical and virological records compared to the deceased group. 13 HIV unexposed (HU) healthy children were additionally used as controls. Baseline plasma samples were analyzed using a targeted proteomic approach, and to assess pathogen-associated and damage-associated molecular patterns (PAMPs, DAMPs) levels. Data from deceased participants were compared to both control groups, with multivariate logistic regression models used to evaluate the association between mortality and plasma proteins. We developed a machine learning model to predict mortality risk, finding that IL-6 and CXCL11 not only were higher in deceased children than Matched-children with HIV (p < 0.001 and p = 0.0034) but also predictive of mortality (accuracy of 77%); levels of PAMPs were higher in deceased children (p = 0.0016). Thus, measuring early inflammatory biomarkers, particularly IL-6, could help mortality risk prediction and potentially guide targeted interventions.

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Publication Details

Journal
Scientific Reports
Published
2024-10-28
DOI
https://doi.org/10.1038/s41598-024-74066-4
Citations
1
Primary Topic
HIV-related health complications and treatments
Type
article
Field-Weighted Citation Impact
0.69

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article

Early inflammation as a footprint of increased mortality risk in infants living with HIV from three African countries

Savita Pahwa, Nigel Klein, Maria Raffaella Petrara, William D. James et al.
1 citations
Scientific Reports
HIV-related health complications and treatments
0.69
article

Early inflammation as a footprint of increased mortality risk in infants living with HIV from three African countries

Savita Pahwa, Nigel Klein, Maria Raffaella Petrara, William D. James, Tacilta Nhampossa, Elisa López, Lesley de Armas, Mark Fredric Cotton, Holly L. Peay, Sara Domínguez‐Rodríguez, Kennedy Otwombe, Silvia Faggion, Mathias Lichterfeld, Andrew J. Yates, Elena Morrocchi, Inger Lindfors Rossi, Vincent Cálvez, Deborah Persaud, Eleni Nastouli, Paola Zangari, Kathleen Gärtner, Giuseppe Rubens Pascucci, Osee Behuhuma, Annalisa Landi, Moira J. Spyer, Shaun Barnabas, Carlo Giaquinto, Philip Goulder, Anne‐Geneviève Marcelin, Pablo Rojo, Mariam Sylla, Chiara Pighi, Viviana Giannuzzi, Alessandra Nardone, Almoustapha Issiaka Maïga, Alfredo Tagarro, C Paganin, Louise Kuhn, Ofer Levy, Maria Grazia Lain, Paolo Rossi, Andrea Oletto, Adriana Ceci, Daniel Gomez Pena, Carlota Miranda, Denise Naniche, Oumar Dolo, Anita De Rossi, Francesca Mazzetto, Sheila Martínez Fernández, Paula Vaz, Theresa Smit, Cissy Kityo, Federica D’Ambrosio, Caroline Foster, Nicola Cotugno, Musakanya Ching’andu, Thanyawee Puthanakit
article en
1 citations

Abstract

In this work our aim was to identify early biomarkers in plasma samples associated with mortality in children with perinatal HIV treated early in life, to potentially inform early intervention targeting this vulnerable group. 20/215 children (9.3%) with perinatal HIV, enrolled within 3 months of age died prematurely within the first year of the study, despite early ART initiation. Using a propensity score, we selected 40 alive study participants having similar clinical and virological records compared to the deceased group. 13 HIV unexposed (HU) healthy children were additionally used as controls. Baseline plasma samples were analyzed using a targeted proteomic approach, and to assess pathogen-associated and damage-associated molecular patterns (PAMPs, DAMPs) levels. Data from deceased participants were compared to both control groups, with multivariate logistic regression models used to evaluate the association between mortality and plasma proteins. We developed a machine learning model to predict mortality risk, finding that IL-6 and CXCL11 not only were higher in deceased children than Matched-children with HIV (p < 0.001 and p = 0.0034) but also predictive of mortality (accuracy of 77%); levels of PAMPs were higher in deceased children (p = 0.0016). Thus, measuring early inflammatory biomarkers, particularly IL-6, could help mortality risk prediction and potentially guide targeted interventions.

Scientific ReportsVol. 14(1)
University of Rome Tor Vergata (IT), Brigham and Women's Hospital (US), Boston Children's Hospital (US), University of Padua (IT), Johns Hopkins University (US), University of Miami (US), Imperial College Healthcare NHS Trust (GB), Chulalongkorn University (TH), RTI International (US), University of the Witwatersrand (ZA), Stellenbosch University (ZA), Columbia University Irving Medical Center (US), Great Ormond Street Hospital (GB), Ragon Institute of MGH, MIT and Harvard (US), University of Bamako (ML), Fundação Ariel Glaser Contra o SIDA Pediátrico (MZ), Research Institute Hospital 12 de Octubre (ES), PENTA Foundation (IT), Istituto Oncologico Veneto (IT), Université des Sciences, des Techniques et des Technologies de Bamako (ML), Manhiça Health Research Centre (MZ), Bambino Gesù Children's Hospital (IT), Africa Health Research Institute (ZA), Fondazione per la Ricerca Farmacologica Gianni Benzi Onlus (IT), Barcelona Institute for Global Health (ES), Perinatal HIV Research Unit (ZA), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Umkhuseli Innovation and Research Management (ZA), Hospital Universitario Infanta Sofía (ES), Joint Clinical Research Centre (UG), University College London (GB), Universitat de Barcelona (ES), Columbia University (US), Universidad Europea de Madrid (ES)
ViiV Healthcare
Good health and well-being
Openalex Percentile: Top 25%
HIV-related health complications and treatments
0.69
DOIOpen Access PDFOpenAlex
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