摘要
Osteoporosis is a prevalent multifactorial bone disease with a strong genetic contribution.The heritability of traits that contribute to osteoporosis(bone mass,bone mineral density(BMD),bone size,bone loss and fractures)ranges from 50 to 85%,suggesting that a comprehensive understanding of the genetic basis may help identify new therapeutic targets.1 However,the genetic characteristics remain obscure,and the existing drug targets are associated with various challenges.Numerous studies have demonstrated that high-throughput sequencing data analysis is fruitful for identifying novel targets of human diseases.2 We therefore integrated GWAS and transcriptome analyses through Multi-marker Analysis of GenoMic Annotation(MAGMA)and weighted gene co-expression network analysis3(WGCNA)to identify new network modules and potential therapeutic genes for osteoporosis.As an illustration,the flow chart presenting the process of the present study was shown in Figure S1.
基金
supported by the Natural Science Foundation of China(No.82072106,81700784 and 32101055)
China Postdoctoral Science Foundation(No.2020M683573 and 2017M613196
the Natural Science Foundation of Shaanxi Province(No.2021JQ-128)
the Key R&D Projects in Shaanxi Province(No.2021SF-242)
the Fundamental Research Funds for the Central Universities(No.D5000210746).