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Long Noncoding RNA Analyses for Osteoporosis Risk in Caucasian Women

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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.

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Acknowledgements

The investigators of this work were partially supported by Grants from the National Institutes of Health [AR069055, U19 AG055373, R01 MH104680, R01AR059781, and P20GM109036], and the Edward G. Schlieder Endowment as well as the Drs. W. C. Tsai and P. T. Kung Professorship in Biostatistics from Tulane University.

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Authors and Affiliations

  1. Center of Genomics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA

    Yu Zhou, Chao Xu, Wei Zhu, Hao He, Lan Zhang, Yong Zeng, Qing Tian & Hong-Wen Deng

  2. Department of Cell and Molecular Biology, Tulane University, New Orleans, LA, 70118, USA

    Yu Zhou

  3. Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, LA, 70112, USA

    Chao Xu, Wei Zhu, Hao He, Lan Zhang, Yong Zeng, Qing Tian & Hong-Wen Deng

  4. School of Basic Medical Science, National Clinical Research Center for Geriatric Diseases, **angya Hospital, Central South University, Changsha, 410078, Hunan, China

    Beisha Tang & Hong-Wen Deng

  5. 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

    Hong-Wen Deng

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Authors Yu Zhou, Chao Xu, Wei Zhu, Hao He, Lan Zhang, Beisha Tang, Yong Zeng, Qing Tian, and Hong-Wen Deng have declared that no conflict of interest exists.

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All the methods were conducted in accordance with the regulations and guidelines of the Institutional Review Boards of University of Missouri Kansas City and Tulane University. The Institutional Review Boards of University of Missouri Kansas City and Tulane University approved the study. Written informed consent was obtained from all participants before inclusion in the study.

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Zhou, Y., Xu, C., Zhu, W. et al. Long Noncoding RNA Analyses for Osteoporosis Risk in Caucasian Women. Calcif Tissue Int 105, 183–192 (2019). https://doi.org/10.1007/s00223-019-00555-8

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