Integrating genome-wide association and transcriptome predicted model identify novel target genes with osteoporosis

Abstract

Osteoporosis (OP) is a highly polygenetic disease which is usually characterized by low bone mineral density. Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with bone mineral density. However, the biological mechanisms of these loci remain elusive. To identify potential causal genes of the associated loci, we detected trait-gene expression associations by transcriptome-wide association study (TWAS) method. It directly imputes gene expression effects from GWAS data, using a statistical prediction model trained on GTEx reference transcriptome data, with blood and skeletal tissues data. Then we performed a colocalization analysis to evaluate the posterior probability of biological patterns: association characterized by a single shared causal variant or two distinct causal variants. The ultimate analysis identified 276 candidate genes, including 3 novel loci, 204 novel candidate genes and 69 replicated from GWAS. The 3 novel loci located at chr6: 72417543, chr15: 69601206, chr21: 30530692, mapping to gene RIMS1, SPESP1, MAP3K7CL. The results of colocalization analysis indicated that 142 of them showing strong evidence of a single shared causal variant and 134 of them showing evidence of joint causal variants. Their biological function was directly or indirectly associated with the occurrence of OP validated by VarElect tool. Several important OP-associated pathways were detected by protein-protein interaction and pathway enrichment analysis. Target genes were further enriched for differential expression genes in osteoblasts expression profiles, e.g. IBSP, affecting calcium and hydroxyapatite binding, and CD44, regulating alternative splicing of gene transcription. Transcriptome fine-mapping identifies more disease-related genes and provide additional insight into the development of novel targeted therapeutics to treat OP.