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Article

Machine learning models incorporating genotype and ancestry improve severe asthma risk prediction.

Scientific reports - 17 Nov 2025

Tahmin Nahian, Chinthala Lokesh K, Marsico Franco Leonel, Buonaiuto Silvia, Mohammed Akram, Carlisle Annette, Gautam Yadu, Colonna Vincenza, Mersha Tesfaye B, Davis Robert L, Khojandi Anahita

Abstract excerpt

This study proposes a novel machine learning (ML)-based stacking technique that integrates Single Nucleotide Polymorphisms (SNPs) and inferred local ancestry (LA) to improve predictive accuracy in clinical outcomes. Asthma, particularly severe asthma (SA) with poor response to inhaled corticosteroids (ICS), serves as the case study to illustrate this approach. Using data from the Biorepository and Integrative...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 41249357
DOI: 10.1038/s41598-025-24080-x
PMCID: PMC12623762

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