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Updated: Sep 11, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
Published on: March 1, 2024
Overlap between COPD genetic association results and transcriptional quantitative trait loci
Aabida Saferali1, Wonji Kim1, Robert P Chase1
1Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Abstract:
Genome-wide association studies (GWASs) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). Here, we identify SNPs that are associated with alternative splicing (splicing quantitative trait loci [sQTLs]) and gene expression (expression QTLs [eQTLs]) to identify functions for COPD-associated genetic variants. RNA sequencing on whole blood from 3,743 subjects in the COPDGene Study and from lung tissue of 1,241 subjects from the Lung Tissue Research Consortium (LTRC) was analyzed. Associations between all SNPs within 1,000 kb of a gene (cis-) and splice and gene expression quantifications were tested using tensorQTL. We assessed colocalization with COPD-associated SNPs from a published GWAS. After adjustment for multiple statistical testing, we identified 28,110 splice sites corresponding to 3,889 unique genes that were significantly associated with genotype in COPDGene whole blood and 58,258 splice sites corresponding to 10,307 unique genes associated with genotype in LTRC lung tissue. To determine what proportion of COPD-associated SNPs were associated with transcriptional splicing, we performed colocalization analysis between COPD GWAS and sQTL data and found that 38 genomic windows, corresponding to 33 COPD GWAS loci, had evidence of colocalization between QTLs and COPD. The top five colocalizations between COPD and lung sQTLs include Nephronectin (NPNT), F box protein 38 (FBXO38), Hedgehog interacting protein (HHIP), Netrin 4 (NTN4), and Betacellulin (BTC). Overall, a total of 38 COPD GWAS loci contain evidence of sQTLs, suggesting that analysis of sQTLs in whole blood and lung tissue can provide insights into disease mechanisms.
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