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Partial correlation network analysis identifies coordinated gene expression within a regional cluster of COPD genome-wide association signals.
- Source :
- PLoS Computational Biology; 10/17/2024, Vol. 20 Issue 10, p1-20, 20p
- Publication Year :
- 2024
-
Abstract
- Chronic obstructive pulmonary disease (COPD) is a complex disease influenced by well-established environmental exposures (most notably, cigarette smoking) and incompletely defined genetic factors. The chromosome 4q region harbors multiple genetic risk loci for COPD, including signals near HHIP, FAM13A, GSTCD, TET2, and BTC. Leveraging RNA-Seq data from lung tissue in COPD cases and controls, we estimated the co-expression network for genes in the 4q region bounded by HHIP and BTC (~70MB), through partial correlations informed by protein-protein interactions. We identified several co-expressed gene pairs based on partial correlations, including NPNT-HHIP, BTC-NPNT and FAM13A-TET2, which were replicated in independent lung tissue cohorts. Upon clustering the co-expression network, we observed that four genes previously associated to COPD: BTC, HHIP, NPNT and PPM1K appeared in the same network community. Finally, we discovered a sub-network of genes differentially co-expressed between COPD vs controls (including FAM13A, PPA2, PPM1K and TET2). Many of these genes were previously implicated in cell-based knock-out experiments, including the knocking out of SPP1 which belongs to the same genomic region and could be a potential local key regulatory gene. These analyses identify chromosome 4q as a region enriched for COPD genetic susceptibility and differential co-expression. Author summary: Complex diseases, such as chronic obstructive pulmonary disease (COPD), are characterized by multifactorial causes, including multiple genetic variants and a variety of molecular functions. A 70 megabase genomic region on chromosome 4 harbors some of the strongest genetic associations to COPD based on genome-wide association studies (GWAS). In this work we study the co-expression patterns of genes located in this genomic region. We developed a new approach to compute partial correlations between pairs of expressed genes, using prior information regarding the mediating genes from protein-protein interaction networks. We identified potential biological connections between several of the COPD-related GWAS genes in this region, including BTC, NPNT, PPM1K and HHIP, suggesting possible functional co-regulation. Furthermore, by comparing COPD cases and control subjects, we found multiple network edges whose co-expression changed between health and disease, particularly the edge between CXCL10 and CXCL11. Some of these genes were previously implicated in cell-based knock-out experiments, suggesting a common regulator, namely SPP1. These analyses provide insight into regional gene regulation of GWAS genes that may be related to COPD pathogenesis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 20
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 180332943
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1011079