A Pilot Metabolomic Study for Diagnosing Aspergillus Infection in Immunocompromised Pediatric Cancer Patients

Fungal infection caused by invasive <i>Aspergillus</i> is a life-threatening complication in immunocompromised pediatric cancer patients. However, the early diagnosis of invasive infection remains a clinical challenge due to the lack of specific, non-invasive biomarkers. The current study investigates plasma metabolomic profiling integrated with an AI-derived fungal secondary metabolite database to identify potential biomarkers for rapid, non-invasive detection of Aspergillus infection. Plasma samples from thirteen pediatric oncology patients were analyzed using untargeted metabolomics based on UHPLC-MS/MS. Based on galactomannan assay results, three patients were classified as Aspergillus-Infected (AIC) and ten as non-infected controls (NPCs). An in-house custom database for secondary metabolites of fungi was incorporated to enhance metabolite annotation. Eight metabolites were found to be candidate biomarkers based on statistical significance, fold change, and biological relevance. In the AIC cohort, aflatoxin B1, aspergillimide, fumifungin, and uridine were found to be significantly elevated while citric acid presented a decrease. Multivariate analysis utilizing PCA and PLSDA showed distinct group separation. Moreover, sample size estimation indicates that a minimum of 25 participants would be needed in future studies for appropriate statistical power.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-06-20
DOI
https://doi.org/10.3390/ijms26135926
Citations
2
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
1.61

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article

A Pilot Metabolomic Study for Diagnosing Aspergillus Infection in Immunocompromised Pediatric Cancer Patients

Nada Youssef, Lobna Shalaby, Mervat M. El‐Enany, Eman Abd El-Mordy Elsayed Ahmed et al.
2 citations
International Journal of Molecular Sciences
Metabolomics and Mass Spectrometry Studies
1.61
article

A Pilot Metabolomic Study for Diagnosing Aspergillus Infection in Immunocompromised Pediatric Cancer Patients

Nada Youssef, Lobna Shalaby, Mervat M. El‐Enany, Eman Abd El-Mordy Elsayed Ahmed, Aya Osama, Taghreed Khaled Abdelmoneim, Sameh Magdeldin, Asmaa Salama, Ahmed Kamel, Ahmed Hesham, Maha Mokhtar, Mark Zaki, Ahmed Karam, Asmaa Ramzy, Nabila Sabar
article en
2 citations

Abstract

Fungal infection caused by invasive <i>Aspergillus</i> is a life-threatening complication in immunocompromised pediatric cancer patients. However, the early diagnosis of invasive infection remains a clinical challenge due to the lack of specific, non-invasive biomarkers. The current study investigates plasma metabolomic profiling integrated with an AI-derived fungal secondary metabolite database to identify potential biomarkers for rapid, non-invasive detection of Aspergillus infection. Plasma samples from thirteen pediatric oncology patients were analyzed using untargeted metabolomics based on UHPLC-MS/MS. Based on galactomannan assay results, three patients were classified as Aspergillus-Infected (AIC) and ten as non-infected controls (NPCs). An in-house custom database for secondary metabolites of fungi was incorporated to enhance metabolite annotation. Eight metabolites were found to be candidate biomarkers based on statistical significance, fold change, and biological relevance. In the AIC cohort, aflatoxin B1, aspergillimide, fumifungin, and uridine were found to be significantly elevated while citric acid presented a decrease. Multivariate analysis utilizing PCA and PLSDA showed distinct group separation. Moreover, sample size estimation indicates that a minimum of 25 participants would be needed in future studies for appropriate statistical power.

International Journal of Molecular SciencesVol. 26(13)
Suez Canal University (EG), Cairo University (EG), Children Cancer Hospital (EG)
Science and Technology Development Fund
Good health and well-being
Openalex Percentile: Top 16%
Metabolomics and Mass Spectrometry Studies
1.61
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