Affiliation:
1. LAGA, CNRS, UMR 7539, Laboratoire D’excellence Inflamex, Université Sorbonne Paris Nord, F-93430 Villetaneuse, France
2. Department of Genetics, University of Malaga, MLiMO, 29010 Málaga, Spain
Abstract
In complex diseases, the interactions among genes are commonly elucidated through the lens of graphs. Amongst these genes, certain ones form bi-functional modules within the graph, contingent upon their (anti)correlation with a specific functional state, such as susceptibility to a genetic disorder of non-Mendelian traits. Consequently, a disease can be delineated by a finite number of these discernible modules. Within each module, there exist allelic variants that pose a genetic risk, thus qualifying as genetic risk factors. These factors precipitate a permissive state, which if all other modules also align in the same permissive state, can ultimately lead to the onset of the disease in an individual. To gain a deeper insight into the incidence of a disease, it becomes imperative to acquire a comprehensive understanding of the genetic transmission of these factors. In this work, we present a non-linear model for this transmission, drawing inspiration from the classic theory of the Bell experiment. This model aids in elucidating the variances observed in SNP interactions concerning the risk of disease.
Funder
National Research Association
Consejería de Universidades, Ciencias y Desarrollo, fondos FEDER de la Junta de Andalucía
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference42 articles.
1. Epistasis and evolution: Recent advances and an outlook for prediction;Johnson;BMC Biol.,2023
2. eQTL mapping identifies insertion- and deletion-specific eQTLs in multiple tissues;Huang;Nat. Commun.,2015
3. Assessment of protein domain fusions in human protein interaction networks prediction: Application to the human kinetochore model;Morilla;New Biotechnol.,2010
4. Mathematical deconvolution uncovers the genetic regulatory signal of cancer cellular heterogeneity on resistance to paclitaxel;Morilla;Mol. Genet. Genom.,2017
5. Integrative Network-based Analysis of Colonic Detoxification Gene Expression in Ulcerative Colitis According to Smoking Status;Ding;J. Crohn’s Colitis,2016