Evidence map›Paper›PMID 41986953›Full record

ArticleClinical and experimental pediatrics2026

Serum metabolomic profile in children with sepsis-associated acute kidney injury.

Nisha Chaudhary, Praveen Singh, Abhijeet Saha, Shantanu Sengupta

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Article in Clinical and experimental pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Nisha Chaudhary *Division of Pediatric Nephrology, Department of Pediatrics, Lady Hardinge Medical College & Kalawati Saran Children's Hospital, New Delhi, India.
Praveen Singh *Genomic and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.
Abhijeet SahaDivision of Pediatric Nephrology, Department of Pediatrics, Lady Hardinge Medical College & Kalawati Saran Children's Hospital, New Delhi, India. drabhijeetsaha@yahoo.com.
Shantanu SenguptaGenomic and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis-associated acute kidney injury (SA-AKI) contributes to high morbidity and mortality rates in children; however, current diagnostic tools (serum creatinine and urine output) lack sensitivity for early detection. Metabolomics can be used to discover novel metabolic markers to enable early diagnosis and prognosis and provide therapeutic targets for SA-AKI. Purpose: This study was aimed to identify the differentially expressed serum metabolites in children with SA-AKI. Methods: We conducted an untargeted serum metabolomic analysis using liquid chromatography-mass spectroscopy (LC-MS) in 75 children: 45 with sepsis and acute kidney injury (AKI) (15 each in Kidney Disease Improving Global Outcomes [KDIGO] stages 1-3), 15 with sepsis without AKI, and 15 healthy controls. Fasting blood samples were collected and centrifuged. Supernatant serum was stored at -80°C and subjected to untargeted metabolomic analysis using LC-MS. Reverse-phase and hydrophilic liquid interaction chromatographic separation was performed in positive and negative ion scan modes, while metabolite identification was performed using the SCIEX All-In-One HR-MS/MS Library with National Institute of Standards and Technology 2017 Library bundle. Results: The significantly altered metabolites in AKI stage 3 were lipids belonging to the glycerophosphoethanolamine subgroup of the phospholipid class. Eighteen metabolites were differentially expressed in patients with SA-AKI versus healthy controls, with phosphoethanolamines (e.g., 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine) showing a consistent association with AKI stage. Thirty-one metabolites were significantly altered in severe AKI (KDIGO stages 2-3), of which only 4 could be annotated and increased proportionally with AKI severity. A pathway analysis revealed significant enrichment of glycerophospholipid, linoleic acid, and alpha-linolenic acid metabolism in stage 3 SA-AKI. Conclusion: Serum metabolomics is a feasible approach to identifying novel biomarkers of SA-AKI. Phosphoethanolamine metabolites both distinguished AKI from sepsis controls and were correlated with clinical severity (estimated glomerular filtration rate decline), suggesting its potential prognostic value. However, its diagnostic feasibility requires preliminary validation in larger multicenter cohorts.

Indexed as

ChildMetabolitesMetabolomicsSepsis-associated acute kidney injury

Identifiers

PMID41986953
PMCPMC13337310

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