Yu Zhou1,2, Chao Xu1,3, Wei Zhu1,3, Hao He1,3, Lan Zhang1,3, Beisha Tang4, Yong Zeng1,3, Qing Tian1,3, Hong-Wen Deng5,6,7,8. 1. Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA. 2. Department of Cell and Molecular Biology, Tulane University, New Orleans, LA, 70118, USA. 3. Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA. 4. School of Basic Medical Science, National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China. 5. Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA. hdeng2@tulane.edu. 6. Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA. hdeng2@tulane.edu. 7. School of Basic Medical Science, National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China. hdeng2@tulane.edu. 8. Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St., RM 1619F, New Orleans, LA, 70112, USA. hdeng2@tulane.edu.
Abstract
INTRODUCTION: Osteoporosis is a prevalent bone metabolic disease characterized by bone fragility. As a key pathophysiological mechanism, the disease is caused by excessive bone resorption (by osteoclasts) over bone formation (by osteoblasts). Peripheral blood monocytes (PBMs) is a major systemic cell model for bone metabolism by serving as progenitors of osteoclasts and producing cytokines important for osteoclastogenesis. Protein-coding genes for osteoporosis have been widely studied by mRNA analyses of PBMs in high versus low hip bone mineral density (BMD) subjects. However, long noncoding RNAs (lncRNAs), which account for a large proportion of human transcriptome, have seldom been studied. METHODS: In this study, microarray analyses of monocytes were performed using Affymetrix exon 1.0 ST arrays in 73 Caucasian females (age: 47-56). LncRNA profile was generated by re-annotating exon array for lncRNAs detection, which yielded 12,007 lncRNAs mapped to the human genome. RESULTS: 575 lncRNAs were differentially expressed between the two groups. In the high BMD subjects, 309 lncRNAs were upregulated and 266 lncRNAs were downregulated (nominally significant, raw p-value < 0.05). To investigate the relationship between mRNAs and lncRNAs, we used two approaches to predict the target genes of lncRNAs and found that 26 candidate lncRNAs might regulate mRNA expression. The majority of these lncRNAs were further validated to be potentially correlated with BMD by GWAS analysis. CONCLUSION: Overall, our findings for the first time reported the lncRNAs profiles for osteoporosis and suggested the potential regulatory mechanism of lncRNAs on protein-coding genes in bone metabolism.
INTRODUCTION: Osteoporosis is a prevalent bone metabolic disease characterized by bone fragility. As a key pathophysiological mechanism, the disease is caused by excessive bone resorption (by osteoclasts) over bone formation (by osteoblasts). Peripheral blood monocytes (PBMs) is a major systemic cell model for bone metabolism by serving as progenitors of osteoclasts and producing cytokines important for osteoclastogenesis. Protein-coding genes for osteoporosis have been widely studied by mRNA analyses of PBMs in high versus low hip bone mineral density (BMD) subjects. However, long noncoding RNAs (lncRNAs), which account for a large proportion of human transcriptome, have seldom been studied. METHODS: In this study, microarray analyses of monocytes were performed using Affymetrix exon 1.0 ST arrays in 73 Caucasian females (age: 47-56). LncRNA profile was generated by re-annotating exon array for lncRNAs detection, which yielded 12,007 lncRNAs mapped to the human genome. RESULTS: 575 lncRNAs were differentially expressed between the two groups. In the high BMD subjects, 309 lncRNAs were upregulated and 266 lncRNAs were downregulated (nominally significant, raw p-value < 0.05). To investigate the relationship between mRNAs and lncRNAs, we used two approaches to predict the target genes of lncRNAs and found that 26 candidate lncRNAs might regulate mRNA expression. The majority of these lncRNAs were further validated to be potentially correlated with BMD by GWAS analysis. CONCLUSION: Overall, our findings for the first time reported the lncRNAs profiles for osteoporosis and suggested the potential regulatory mechanism of lncRNAs on protein-coding genes in bone metabolism.
Entities:
Keywords:
Bone mineral density; Gene expression; Osteoporosis; Systems genetics; lncRNAs
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