A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

• Published in: American journal of human genetics Vol. 111; no. 6; pp. 1100 - 1113
• Main Authors: Gao, Guimin, McClellan, Julian, Barbeira, Alvaro N., Fiorica, Peter N., Li, James L., Mu, Zepeng, Olopade, Olufunmilayo I., Huo, Dezheng, Im, Hae Kyung
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 06.06.2024
• Subjects: alternative splicing; breast cancer; Breast Neoplasms - genetics; Female; Gene Expression Profiling; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; intron excision; Introns - genetics; joint analysis; multi-tissue; Polymorphism, Single Nucleotide; Quantitative Trait Loci; RNA Splicing - genetics; susceptibility genes; Transcriptome; transcriptome-wide association studies; multi-tissue; alternative splicing; susceptibility genes; intron excision; breast cancer; transcriptome-wide association studies; joint analysis
• ISSN: 0002-9297; 1537-6605; 1537-6605
• DOI: 10.1016/j.ajhg.2024.04.010

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events. Investigating alternative splicing could provide new insight into the genetic etiology of breast cancer. By a multi-tissue, joint splicing-based transcriptome-wide association study (TWAS) that integrates signals of multiple excised introns in a gene, the authors identified 88 breast cancer susceptibility genes that have not been reported in previous TWASs.