Persistent homology analysis of type 2 diabetes genome-wide association studies in protein–protein interaction networks

Frontiers in Genetics

Genetics

Euijun Song¹ 

[1] Yonsei University College of Medicine, Seoul, Republic of Korea;Present: Independent Researcher, Gyeonggi, Republic of Korea;

关键词: persistent homology;    topological data analysis;    disease module;    genome-wide association study;    network medicine;    systems biology;    algebraic topology algorithms;   

DOI  :  10.3389/fgene.2023.1270185

 received in 2023-08-01, accepted in 2023-09-12,  发布年份 2023

来源: Frontiers

【 摘 要 】

Genome-wide association studies (GWAS) involving increasing sample sizes have identified hundreds of genetic variants associated with complex diseases, such as type 2 diabetes (T2D); however, it is unclear how GWAS hits form unique topological structures in protein–protein interaction (PPI) networks. Using persistent homology, this study explores the evolution and persistence of the topological features of T2D GWAS hits in the PPI network with increasing p-value thresholds. We define an n-dimensional persistent disease module as a higher-order generalization of the largest connected component (LCC). The 0-dimensional persistent T2D disease module is the LCC of the T2D GWAS hits, which is significantly detected in the PPI network (196 nodes and 235 edges, P<0.05). In the 1-dimensional homology group analysis, all 18 1-dimensional holes (loops) of the T2D GWAS hits persist over all p-value thresholds. The 1-dimensional persistent T2D disease module comprising these 18 persistent 1-dimensional holes is significantly larger than that expected by chance (59 nodes and 83 edges, P<0.001), indicating a significant topological structure in the PPI network. Our computational topology framework potentially possesses broad applicability to other complex phenotypes in identifying topological features that play an important role in disease pathobiology.

【 授权许可】

Unknown   
Copyright © 2023 Song.