Literature DB >> 21452281

Molecular disease map of bone characterizing the postmenopausal osteoporosis phenotype.

Rune Jemtland1, Marit Holden, Sjur Reppe, Ole K Olstad, Finn P Reinholt, Vigdis T Gautvik, Hilde Refvem, Arnoldo Frigessi, Brian Houston, Kaare M Gautvik.   

Abstract

Genome-wide gene expressions in bone biopsies from patients with postmenopausal osteoporosis and healthy controls were profiled, to identify osteoporosis candidate genes. All osteoporotic patients (n = 27) in an unbiased cohort of Norwegian women presented with bone mineral density (BMD) T-scores of less than -2.5 SD and one or more confirmed low-energy fracture(s). A validation group (n = 18) had clinical and laboratory parameters intermediate to the control (n = 39) and osteoporosis groups. RNA from iliac crest bone biopsies were analyzed by Affymetrix microarrays and real-time reverse-transcriptase polymerase chain reaction (RT-PCR). Differentially expressed genes in osteoporosis versus control groups were identified using the Bayesian ANOVA for microarrays (BAMarray) method, whereas the R-package Limma (Linear Models for Microarray Data) was used to determine whether these transcripts were explained by disease, age, body mass index (BMI), or combinations thereof. Laboratory tests showed normal ranges for the cohort. A total of 609 transcripts were differentially expressed in osteoporotic patients relative to controls; 256 transcripts were confirmed for disease when controlling for age or BMI. Most of the osteoporosis susceptibility genes (80%) also were confirmed to be regulated in the same direction in the validation group. Furthermore, 217 of 256 transcripts were correlated with BMD (adjusted for age and BMI) at various skeletal sites (|r| > 0.2, p < .05). Among the most distinctly expressed genes were Wnt antagonists DKK1 and SOST, the transcription factor SOX4, and the bone matrix proteins MMP13 and MEPE, all reduced in osteoporosis versus control groups. Our results identify potential osteoporosis susceptibility candidate genes adjusted for confounding factors (ie, age and BMI) with or without a significant correlation with BMD.
Copyright © 2011 American Society for Bone and Mineral Research.

Entities:  

Mesh:

Year:  2011        PMID: 21452281     DOI: 10.1002/jbmr.396

Source DB:  PubMed          Journal:  J Bone Miner Res        ISSN: 0884-0431            Impact factor:   6.741


  30 in total

1.  Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry.

Authors:  Yi-Hsiang Hsu; Karol Estrada; Evangelos Evangelou; Cheryl Ackert-Bicknell; Kristina Akesson; Thomas Beck; Suzanne J Brown; Terence Capellini; Laura Carbone; Jane Cauley; Ching-Lung Cheung; Steven R Cummings; Stefan Czerwinski; Serkalem Demissie; Michael Econs; Daniel Evans; Charles Farber; Kaare Gautvik; Tamara Harris; Candace Kammerer; John Kemp; Daniel L Koller; Annie Kung; Debbie Lawlor; Miryoung Lee; Mattias Lorentzon; Fiona McGuigan; Carolina Medina-Gomez; Braxton Mitchell; Anne Newman; Carrie Nielson; Claes Ohlsson; Munro Peacock; Sjur Reppe; J Brent Richards; John Robbins; Gunnar Sigurdsson; Timothy D Spector; Kari Stefansson; Elizabeth Streeten; Unnur Styrkarsdottir; Jonathan Tobias; Katerina Trajanoska; André Uitterlinden; Liesbeth Vandenput; Scott G Wilson; Laura Yerges-Armstrong; Mariel Young; M Carola Zillikens; Fernando Rivadeneira; Douglas P Kiel; David Karasik
Journal:  J Bone Miner Res       Date:  2019-03-19       Impact factor: 6.741

Review 2.  Bone composition: relationship to bone fragility and antiosteoporotic drug effects.

Authors:  Adele L Boskey
Journal:  Bonekey Rep       Date:  2013-12-04

Review 3.  SOXopathies: Growing Family of Developmental Disorders Due to SOX Mutations.

Authors:  Marco Angelozzi; Véronique Lefebvre
Journal:  Trends Genet       Date:  2019-07-06       Impact factor: 11.639

4.  Serum levels of the bone turnover markers dickkopf-1, sclerostin, osteoprotegerin, osteopontin, osteocalcin and 25-hydroxyvitamin D in Swedish geriatric patients aged 75 years or older with a fresh hip fracture and in healthy controls.

Authors:  P Wanby; R Nobin; S-P Von; L Brudin; M Carlsson
Journal:  J Endocrinol Invest       Date:  2016-02-05       Impact factor: 4.256

Review 5.  Regulation of bone-renal mineral and energy metabolism: the PHEX, FGF23, DMP1, MEPE ASARM pathway.

Authors:  Peter S N Rowe
Journal:  Crit Rev Eukaryot Gene Expr       Date:  2012       Impact factor: 1.807

6.  SPR4-peptide alters bone metabolism of normal and HYP mice.

Authors:  Lesya V Zelenchuk; Anne-Marie Hedge; Peter S N Rowe
Journal:  Bone       Date:  2014-11-22       Impact factor: 4.398

7.  Age dependent regulation of bone-mass and renal function by the MEPE ASARM-motif.

Authors:  Lesya V Zelenchuk; Anne-Marie Hedge; Peter S N Rowe
Journal:  Bone       Date:  2015-06-04       Impact factor: 4.398

Review 8.  SOXC Genes and the Control of Skeletogenesis.

Authors:  Véronique Lefebvre; Pallavi Bhattaram
Journal:  Curr Osteoporos Rep       Date:  2016-02       Impact factor: 5.096

Review 9.  The chicken or the egg: PHEX, FGF23 and SIBLINGs unscrambled.

Authors:  Peter S N Rowe
Journal:  Cell Biochem Funct       Date:  2012-05-09       Impact factor: 3.685

10.  Gene Expression and RNA Splicing Imputation Identifies Novel Candidate Genes Associated with Osteoporosis.

Authors:  Yong Liu; Hui Shen; Jonathan Greenbaum; Anqi Liu; Kuan-Jui Su; Li-Shu Zhang; Lei Zhang; Qing Tian; Hong-Gang Hu; Jin-Sheng He; Hong-Wen Deng
Journal:  J Clin Endocrinol Metab       Date:  2020-12-01       Impact factor: 5.958

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