Multi-omics and multi-stages integration identified a novel variant associated with silicosis risk.
Chunmeng JinXiaobo TaoWendi ZhangHuiwen XuYutong WuQiong ChenSiqi LiAnhui NingWei WangQiuyun WuMinjie ChuPublished in: Archives of toxicology (2024)
Assessing the association between candidate single-nucleotide polymorphisms (SNPs) identified by multi-omics approaches and susceptibility to silicosis. RNA-seq analysis was performed to screen the differentially expressed mRNAs in the fibrotic lung tissues of mice exposed to silica particles. Following this, we integrated the SNPs located in the above human homologenes with the silicosis-related genome-wide association study (GWAS) data to select the candidate SNPs. Then, expression quantitative trait locus (eQTL)-SNPs were identified by the GTEx database. Next, we validated the associations between the functional eQTL-SNPs and silicosis susceptibility by additional case-control study. And the contribution of the identified SNP and its host gene in the fibrosis process was further validated by functional experiments. A total of 12 eQTL-SNPs were identified in the screening stage. The results of the validation stage suggested that the variant T allele of rs419540 located in IL12RB1 significantly increased the risk of developing silicosis [additive model: odds ratio (OR) = 1.78, 95% confidence interval (CI) 1.11-2.85, P = 0.017]. Furthermore, the combination of GWAS and the results of validation stage also indicated that the variant T allele of rs419540 in IL12RB1 was associated with increased silicosis risk (additive model: OR = 2.07, 95% CI 1.38-3.12, P < 0.001). Additionally, after knockdown or overexpression of IL12RB1, the levels of pro-inflammatory factors, such as IL-12, IFN-γ, and other pro-inflammatory factors, were correspondingly decreased or increased. The novel eQTL-SNP, rs419540, might increase the risk of silicosis by modulating the expression levels of IL12RB1.
Keyphrases
- genome wide
- pulmonary fibrosis
- dna methylation
- rna seq
- genome wide association study
- single cell
- copy number
- poor prognosis
- genome wide association
- endothelial cells
- gene expression
- type diabetes
- high throughput
- adipose tissue
- emergency department
- cell proliferation
- systemic sclerosis
- machine learning
- data analysis
- artificial intelligence
- drug induced