Dataset Information

Integrating Transcriptome-Wide Association Study and mRNA Expression Profiling Identifies Novel Genes Associated With Osteonecrosis of the Femoral Head.

ABSTRACT:

Objective

This study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).

Methods

A transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH.

Results

TWAS totally identified 564 genes that were with P _TWAS value <0.05 for MS and blood, such as CBX1 (P _TWAS = 0.0001 for MS), SRPK2 (P _TWAS = 0.0002 for blood), and MYO5A (P _TWAS = 0.0005 for blood). After comparing the genes detected by TWAS with the differentially expressed genes identified by mRNA expression profiling, we detected 59 overlapped genes, such as STEAP4 [P _TWAS = 0.0270, FC (fold change)_mRNA = 7.03], RABEP1 (P _TWAS = 0.010, FC_mRNA = 2.22), and MORC3 (P _TWAS = 0.0053, FC_mRNA = 2.92). The GO analysis of TWAS-identified genes discovered 53 GO terms for ON. Further comparing the GO results of TWAS and mRNA expression profiling identified four overlapped GO terms, including cysteine-type endopeptidase activity (P _TWAS = 0.0006, P _mRNA = 0.0227), extracellular space (P _TWAS = 0.0342, P _mRNA = 0.0012), protein binding (P _TWAS = 0.0112, P _mRNA = 0.0106), and ATP binding (P _TWAS = 0.0464, P _mRNA = 0.0033).

Conclusion

Several ONFH-associated genes and GO terms were identified by integrating TWAS and mRNA expression profiling. It provides novel clues to reveal the pathogenesis of ONFH.

SUBMITTER: Ma M

PROVIDER: S-EPMC8215574 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:In this study, we integrated large-scale GWAS summary data and used the predicted transcriptome-wide association study method to discover novel genes associated with osteoporosis. We identified 204 candidate genes, which provide novel clues for understanding the genetic mechanism of osteoporosis and indicate potential therapeutic targets.IntroductionOsteoporosis is a highly polygenetic disease characterized by low bone mass and deterioration of the bone microarchitecture. Our objective was to discover novel candidate genes associated with osteoporosis.MethodsTo identify potential causal genes of the associated loci, we investigated trait-gene expression associations using the transcriptome-wide association study (TWAS) method. This method directly imputes gene expression effects from genome-wide association study (GWAS) data using a statistical prediction model trained on GTEx reference transcriptome data. We then performed a colocalization analysis to evaluate the posterior probability of biological patterns: associations characterized by a single causal variant or multiple distinct causal variants. Finally, a functional enrichment analysis of gene sets was performed using the VarElect and CluePedia tools, which assess the causal relationships between genes and a disease and search for potential gene's functional pathways. The osteoporosis-associated genes were further confirmed based on the differentially expressed genes profiled from mRNA expression data of bone tissue.ResultsOur analysis identified 204 candidate genes, including 154 genes that have been previously associated with osteoporosis, 50 genes that have not been previously discovered. A biological function analysis found that 20 of the candidate genes were directly associated with osteoporosis. Further analysis of multiple gene expression profiles showed that 15 genes were differentially expressed in patients with osteoporosis. Among these, SLC11A2, MAP2K5, NFATC4, and HSP90B1 were enriched in four pathways, namely, mineral absorption pathway, MAPK signaling pathway, Wnt signaling pathway, and PI3K-Akt signaling pathway, which indicates a causal relationship with the occurrence of osteoporosis.ConclusionsWe demonstrated that transcriptome fine-mapping identifies more osteoporosis-related genes and provides key insight into the development of novel targeted therapeutics for the treatment of osteoporosis.

Project description:BackgroundOsteoarthritis (OA) is a common skeletal system disease that has been partially attributed to genetic factors. The hand is frequently affected, which seriously affects the patient's quality of life. However, the pathogenetic mechanism of hand osteoarthritis (hand OA) is still elusive.MethodsA genome-wide association study (GWAS) summary of hand OA was obtained from the UK Biobank dataset, which contains data from a total of 452,264 White British individuals, including 37,782 OA patients. The transcriptome-wide association study (TWAS) of hand OA was performed using FUnctional Summary-based ImputatiON (FUSION) with the skeletal muscle and blood as gene expression references. The significant genes identified by TWAS were further subjected to gene set enrichment analysis (GSEA) with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. Furthermore, we compared the genes and gene sets identified by our TWAS with that of a knee OA mRNA expression profile to detect the genes and gene sets shared by TWAS and mRNA expression profiles in OA. The mRNA expression profiles of 18 normal knee cartilages and 20 OA knee cartilages were acquired from the Gene Expression Omnibus database (accession number: GSE114007).ResultsTWAS identified 177 genes with P < 0.05 for the skeletal muscle, including ANKRD44 (P = 0.0001), RIC3 (P = 0.0003), and AC005154.6 (P = 0.0004). TWAS identified 423 genes with P < 0.05 for the blood, including CRIM1 (P = 0.0002), ZNF880 (P = 0.0002), and NCKIPSD (P = 0.0003). After comparing the results of the TWAS to those of the mRNA expression profiling of OA, we identified 5 common genes, including DHRS3 (log2fold = - 1.85, P = 3.31 × 10- 9) and SKP2 (log2fold = 1.36, P = 1.62 × 10- 8). GSEA of TWAS identified 51 gene ontology (GO) terms for hand OA, for example, protein binding (P = 0.0003) and cytosol (P = 0.0020). We also detected 6 common GO terms shared by TWAS and mRNA expression profiling, including protein binding (PTWAS = 2.54 × 10- 4, PmRNA = 3.42 × 10- 8), extracellular exosome (PTWAS = 0.02, PmRNA = 1.18 × 10- 4), and cytoplasm (PTWAS = 0.0183, PmRNA = 0.0048).ConclusionIn this study, we identified 5 candidate genes and 6 GO terms related to hand OA, which may help to uncover the pathogenesis of hand OA. It should be noted that the possible difference in the gene expression profiles between hand OA and knee OA may affect our study results, which should be interpreted with caution.