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Effects of Age and Estrogen on Skeletal Gene Expression in Humans as Assessed by RNA Sequencing.

Farr JN, Roforth MM, Fujita K, Nicks KM, Cunningham JM, Atkinson EJ, Therneau TM, McCready LK, Peterson JM, Drake MT, Monroe DG, Khosla S - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Division of Endocrinology, Department of Medicine, Mayo Clinic College of Medicine, Rochester, MN, 55905, United States of America; Robert and Arlene Kogod Center on Aging, Mayo Clinic College of Medicine, Rochester, MN, 55905, United States of America.

ABSTRACT

Unlabelled: 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.

Trial registration: ClinicalTrials.gov NCT02349113.

No MeSH data available.


Related in: MedlinePlus

Networks derived from age-related differentially expressed genes (DEGs) in bone.(A) Top 10 scoring networks and associated network functions derived from the 678 DEGs altered (median count ≥ 10, q < 0.10) in the young versus old dataset determined using the Ingenuity Pathway Analysis software (see Statistical Analysis). (B) Network of cell morphology, hematological system development and function, and protein synthesis (score = 33); key molecules implicated in bone metabolism include LEF1 and CDKN1A (p21). (C) Network of cardiovascular system development and function, cellular development, and organismal development (score = 31); key molecules implicated in bone metabolism include Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) and SEMA3A. Green indicates downregulated genes, and red indicates upregulated genes.
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pone.0138347.g003: Networks derived from age-related differentially expressed genes (DEGs) in bone.(A) Top 10 scoring networks and associated network functions derived from the 678 DEGs altered (median count ≥ 10, q < 0.10) in the young versus old dataset determined using the Ingenuity Pathway Analysis software (see Statistical Analysis). (B) Network of cell morphology, hematological system development and function, and protein synthesis (score = 33); key molecules implicated in bone metabolism include LEF1 and CDKN1A (p21). (C) Network of cardiovascular system development and function, cellular development, and organismal development (score = 31); key molecules implicated in bone metabolism include Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) and SEMA3A. Green indicates downregulated genes, and red indicates upregulated genes.

Mentions: We next utilized IPA to identify networks based on the 678 network-eligible molecules that were altered (median count ≥ 10, q < 0.10) in bone with aging S4 Table lists all identified networks, as well as their associated scores and network molecules). The top 10 highest scored networks are listed in Fig 3A. Particularly noteworthy, genes identified among the highest scored networks (Fig 3B) included LEF1, which plays an important role in Wnt/β-catenin signaling [22,23], as well as CDKN1A (p21), a key mediator of cellular senescence [24]. Other molecules implicated in bone metabolism identified among the highest scored networks were Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) (Fig 3C) and SEMA3A; the latter regulates bone metabolism via sensory innervations [25].


Effects of Age and Estrogen on Skeletal Gene Expression in Humans as Assessed by RNA Sequencing.

Farr JN, Roforth MM, Fujita K, Nicks KM, Cunningham JM, Atkinson EJ, Therneau TM, McCready LK, Peterson JM, Drake MT, Monroe DG, Khosla S - PLoS ONE (2015)

Networks derived from age-related differentially expressed genes (DEGs) in bone.(A) Top 10 scoring networks and associated network functions derived from the 678 DEGs altered (median count ≥ 10, q < 0.10) in the young versus old dataset determined using the Ingenuity Pathway Analysis software (see Statistical Analysis). (B) Network of cell morphology, hematological system development and function, and protein synthesis (score = 33); key molecules implicated in bone metabolism include LEF1 and CDKN1A (p21). (C) Network of cardiovascular system development and function, cellular development, and organismal development (score = 31); key molecules implicated in bone metabolism include Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) and SEMA3A. Green indicates downregulated genes, and red indicates upregulated genes.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4581624&req=5

pone.0138347.g003: Networks derived from age-related differentially expressed genes (DEGs) in bone.(A) Top 10 scoring networks and associated network functions derived from the 678 DEGs altered (median count ≥ 10, q < 0.10) in the young versus old dataset determined using the Ingenuity Pathway Analysis software (see Statistical Analysis). (B) Network of cell morphology, hematological system development and function, and protein synthesis (score = 33); key molecules implicated in bone metabolism include LEF1 and CDKN1A (p21). (C) Network of cardiovascular system development and function, cellular development, and organismal development (score = 31); key molecules implicated in bone metabolism include Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) and SEMA3A. Green indicates downregulated genes, and red indicates upregulated genes.
Mentions: We next utilized IPA to identify networks based on the 678 network-eligible molecules that were altered (median count ≥ 10, q < 0.10) in bone with aging S4 Table lists all identified networks, as well as their associated scores and network molecules). The top 10 highest scored networks are listed in Fig 3A. Particularly noteworthy, genes identified among the highest scored networks (Fig 3B) included LEF1, which plays an important role in Wnt/β-catenin signaling [22,23], as well as CDKN1A (p21), a key mediator of cellular senescence [24]. Other molecules implicated in bone metabolism identified among the highest scored networks were Notch signaling components (NOTCH3, NOTCH4, HEY1, JAG2, and DLL4) (Fig 3C) and SEMA3A; the latter regulates bone metabolism via sensory innervations [25].

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Division of Endocrinology, Department of Medicine, Mayo Clinic College of Medicine, Rochester, MN, 55905, United States of America; Robert and Arlene Kogod Center on Aging, Mayo Clinic College of Medicine, Rochester, MN, 55905, United States of America.

ABSTRACT

Unlabelled: 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.

Trial registration: ClinicalTrials.gov NCT02349113.

No MeSH data available.


Related in: MedlinePlus