Effects of Age and Estrogen on Skeletal Gene Expression in Humans as Assessed by RNA Sequencing
PLoS One. 2015-09-24;10(9):e0138347.
- Abstract
- Precise delineation of the specific genes and pathways altered with aging and estrogen (E) therapy may lead to new skeletal biomarkers and the development of novel bone therapeutics. Previous human bone studies, however, have been limited by only examining pre-specified genes and pathways. High-throughput RNA sequencing (RNAseq), on the other hand, offers an unbiased approach to examine the entire transcriptome. Here we present an RNAseq analysis of human bone samples, obtained from iliac crest needle biopsies, to yield the first in vivo interrogation of all genes and pathways that may be altered in bone with aging and E therapy in humans. 58 healthy women were studied, including 19 young women (mean age ± SD, 30.3 ± 5.4 years), 19 old women (73.1 ± 6.6 years), and 20 old women treated with 3 weeks of E therapy (70.5 ± 5.2 years). Using generally accepted criteria (false discovery rate [q] < 0.10), aging altered a total of 678 genes and 12 pathways, including a subset known to regulate bone metabolism (e.g., Notch). Interestingly, the LEF1 transcription factor, which is a classical downstream target of the Wnt/β-catenin signaling pathway, was significantly downregulated in the bones from the old versus young women; consistent with this, LEF1 binding sites were significantly enriched in the promoter regions of the differentially expressed genes in the old versus young women, suggesting that aging was associated with alterations in Wnt signaling in bone. Further, of the 21 unique genes altered in bone by E therapy, the expression of INHBB (encoding for the inhibin, beta B polypeptide), which decreased with aging (by 0.6-fold), was restored to young adult levels in response to E therapy. In conclusion, our data demonstrate that aging alters a substantial portion of the skeletal transcriptome, whereas E therapy appears to have significant, albeit less wide-ranging effects. These data provide a valuable resource for the potential identification of novel biomarkers associated with age-related bone loss and also highlight potential pathways that could be targeted to treat osteoporosis.
- Consortium data used in this publication
- GSE72815
- Datasets
- DSR024FUI, DSR844MAY, DSR471ACH, DSR286HVJ, DSR217BIU, DSR449CGF, DSR446STD, DSR093HMO, DSR800OMM, DSR160FPZ, DSR731OJF, DSR543TLP, DSR395WCC, DSR085VSC, DSR732XNC, DSR257XFZ, DSR525KVK, DSR482ABP, DSR327AMQ, DSR338XWJ, DSR682LYO, DSR861CHC, DSR717HEW, DSR411JDQ, DSR166IGC, DSR352WAP, DSR087VNI, DSR880ZJA, DSR469YNM, DSR748VHL, DSR095XBT, DSR665NXO, DSR016PUQ, DSR227HTL, DSR493NJD, DSR890OBE, DSR043JUX, DSR682GBK, DSR782IFB, DSR279KUW, DSR635JSL, DSR588VGL, DSR672APM, DSR366GTU, DSR409FEP, DSR455JFO, DSR986PKD, DSR523QEP, DSR469SOD, DSR279UXS, DSR780RGH, DSR335KMF, DSR068HDL, DSR987VJL, DSR236SGL, DSR030NTB, DSR651MKM, DSR638LSD, DSR661JAG, DSR436VDI, DSR172QFA, DSR603GHK