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Featured Article: Transcriptional landscape analysis identifies differently expressed genes involved in follicle-stimulating hormone induced postmenopausal osteoporosis

Maasalu, K., Laius, O., Zhytnik, L., Kõks, S., Prans, E., Reimann, E. and Märtson, A. (2017) Featured Article: Transcriptional landscape analysis identifies differently expressed genes involved in follicle-stimulating hormone induced postmenopausal osteoporosis. Experimental Biology and Medicine, 242 (2). pp. 203-213.

Link to Published Version: https://doi.org/10.1177/1535370216679899
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Abstract

Osteoporosis is a disorder associated with bone tissue reorganization, bone mass, and mineral density. Osteoporosis can severely affect postmenopausal women, causing bone fragility and osteoporotic fractures. The aim of the current study was to compare blood mRNA profiles of postmenopausal women with and without osteoporosis, with the aim of finding different gene expressions and thus targets for future osteoporosis biomarker studies. Our study consisted of transcriptome analysis of whole blood serum from 12 elderly female osteoporotic patients and 12 non-osteoporotic elderly female controls. The transcriptome analysis was performed with RNA sequencing technology. For data analysis, the edgeR package of R Bioconductor was used. Two hundred and fourteen genes were expressed differently in osteoporotic compared with non-osteoporotic patients. Statistical analysis revealed 20 differently expressed genes with a false discovery rate of less than 1.47 × 10−4 among osteoporotic patients. The expression of 10 genes were up-regulated and 10 down-regulated. Further statistical analysis identified a potential osteoporosis mRNA biomarker pattern consisting of six genes: CACNA1G, ALG13, SBK1, GGT7, MBNL3, and RIOK3. Functional ingenuity pathway analysis identified the strongest candidate genes with regard to potential involvement in a follicle-stimulating hormone activated network of increased osteoclast activity and hypogonadal bone loss. The differentially expressed genes identified in this study may contribute to future research of postmenopausal osteoporosis blood biomarkers.

Item Type: Journal Article
Publisher: SAGE Publications
Copyright: © 2016 by the Society for Experimental Biology and Medicine
URI: http://researchrepository.murdoch.edu.au/id/eprint/51437
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