An approach for searching genes in signaling pathways or gene-gene interaction networks related to Hypertension in the Mexican population.

Gene

Centro de Investigación en Políticas, Población y Salud (CIPPS), Universidad Nacional Autónoma de México (UNAM), Ciudad de México 04510, México. Electronic address:

Published: February 2024

Introduction: The selection of single nucleotide polymorphisms (SNPs) to evaluate the genetic susceptibility in complex traits is often conducted in isolation, without considering the entire set of genes. Incorporating signaling pathways or gene-gene interaction search may provide a more comprehensive approach to selecting SNP candidates for further study.

Objective: To propose a systematic procedure for identifying SNPs candidates with complex traits such as hypertension and blood pressure.

Methods: Sequential stages to SNPs selection: 1) literature review to identify SNPs, following the PRISMA methodology, 2) identification and selection of signaling pathways and selection of gene-gene interaction networks using the STRING software, and 3) application of specific criteria for SNPs candidates, including: a) SNPs with minor allele frequency > 5% in the target population, b) SNPs located within genes involved in three or more signaling pathways, and c) SNPs that are not in linkage disequilibrium, with a D'or r value < 0.8.

Results: Stage 1) A total of 44 publications were selected, providing information on 230 genes evaluated with blood pressure. Stage 2) Using the STRING software, we selected 7 signaling pathways with a false discovery rate < 0.0001 and strength ≥ 0.8; and we identified 16 genes belonging to gene-gene interaction networks, six of them share ≥ 3 signaling pathways. Stage 3) Finally, 7 SNPs were selected for genotyping in the Health Workers Cohort Study. We observed a positive association between SNPs with hypertension incidence in males (rs1130214, rs3807989) and females (rs5051, rs2493123).

Conclusion: Our methodological proposal may be a reliable way for selecting SNPs candidates to study complex traits.

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Source
http://dx.doi.org/10.1016/j.gene.2023.147973DOI Listing

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