Evidence map›Paper›PMID 40855528›Full record

ArticleBMC infectious diseases2025

Potential of microRNAs as diagnostic markers for distinguishing malaria severity in samples from an Indian cohort.

Aditi Gupta, Kushagri Arora, Sneha Bhandari, Ruhi Sikka, Samuel C Wassmer, Praveen Kumar Bharti, Himanshu Gupta

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Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Aditi GuptaDepartment of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, 281406, India.
Kushagri AroraDepartment of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, 281406, India.
Sneha BhandariIndian Council of Medical Research - National Institute of Research in Environment Health (ICMR-NIREH), Bhopal, Madhya Pradesh, India.
Ruhi SikkaDepartment of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, 281406, India.
Samuel C WassmerDepartment of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK.
Praveen Kumar BhartiICMR- National Institute of Malaria Research (ICMR-NIMR), Dwarka, New Delhi, India.
Himanshu GuptaDepartment of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, 281406, India. himanshu.gupta@gla.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCerebral malaria (CM) is a subcategory of severe malaria (SM) and a major cause of death in Plasmodium falciparum infections, driven by the sequestration of infected red blood cells in the microvasculature of host vital organs. Identifying early biomarkers of CM is crucial for timely intervention. This study assessed the potential of microRNAs, produced upon organ injury, as biomarkers of CM.

methodsPlasma levels of six microRNAs were quantified in patients with CM (n = 43), severe non-CM (SNCM; n = 50), uncomplicated malaria (UM; n = 79), asymptomatic malaria (AM; n = 80), and non-malarial febrile illnesses (nMFI; n = 69) using TaqMan-RT-qPCR.

resultsPlasma levels of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p correlated with SM (p < 0.0005) and CM patients (p < 0.0005), as determined by the Mann-Whitney U test and logistic regression models, with a study power of > 80%. A random forest machine learning (ML) model predicted CM patients on admission using a combination of three microRNA levels, achieving 83% sensitivity, 100% specificity, and 92% balanced accuracy.

conclusionsThe combined use of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p microRNAs may offer a powerful, non-invasive approach for early CM diagnosis, potentially improving clinical outcomes and patient survival.

Indexed as

Malaria, CerebralMalaria, FalciparumMicroRNAsAdolescentAdultBiomarkersChildCohort StudiesFemaleHumansIndiaMaleMiddle AgedPlasmodium falciparumSensitivity and SpecificitySeverity of Illness IndexBiomarkersMicroRNAsMIRN21 microRNA, humanBiomarkersCerebral malariaMachine learningMalariamicroRNAsPlasmodium

Identifiers

PMID40855528
PMCPMC12376405

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