A road map for understanding molecular and genetic determinants of osteoporosis

骨质疏松症 基因组学 表观遗传学 计算生物学 医学 疾病 全基因组关联研究 表观基因组 组学 蛋白质组学 生物信息学 生物 基因组 遗传学 病理 基因 DNA甲基化 单核苷酸多态性 基因表达 基因型
作者
Tie‐Lin Yang,Hui Shen,Anqi Liu,Shan‐Shan Dong,Lei Zhang,Fei‐Yan Deng,Qi Zhao,Hong‐Wen Deng
出处
期刊:Nature Reviews Endocrinology [Nature Portfolio]
卷期号:16 (2): 91-103 被引量:293
标识
DOI:10.1038/s41574-019-0282-7
摘要

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in ‘systems genetics and genomics’. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans. In this Review, the authors highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis, which is a highly heritable condition. They also summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis.
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