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Article

Genetic determinants of metabolic-inflammatory dysregulation and machine learning prediction of COVID-19.

Frontiers in cellular and infection microbiology - 1 Jan 2026

Sydorchuk Larysa, Sokolenko Maksym, Sydorchuk Ruslan, Sokolenko Alina, Kamyshna Iryna, Sokolenko Ludmila, Moroz Petro, Sydorchuk Andrii, Sokolenko Oleksandr, Halabitska Iryna, Petakh Pavlo, Kamyshnyi Oleksandr

Abstract excerpt

The aim of this study was to identify genetic variations that influence the metabolic-inflammatory profile of coronavirus disease and to evaluate the performance of modern machine learning models for the classification and prediction of COVID-19 severity. Real-time polymerase chain reaction was used to genotype the polymorphism of FGB (rs1800790), NOS3 (rs2070744) and TMPRSS2 (rs12329760) genes. Model performance...

Topics

Humans
COVID-19

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Machine Learning

Serine Endopeptidases

Nitric Oxide Synthase Type III

SARS-CoV-2

Genotype

Severity of Illness Index

Inflammation

Predictive Learning Models

Biomarkers

ROC Curve

Polymorphism, Single Nucleotide

Genetic Predisposition to Disease

Source

Open in PubMed Open full text

Identifiers

PMID: 42620529
DOI: 10.3389/fcimb.2026.1874596
PMCID: PMC13485526

Genes

TMPRSS2
FGB
NOS3

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 29 Aug 2026. Prepared record publication-42620529-2026-08-29.1. Manifest publication-graph-cohort-2026-08-29.1.

Source receipt: PubMed via Helena Literature Corpus, retrieved 29 Aug 2026.

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