Literature DB >> 28316103

Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics.

Carrie M Nielson1,2, Jack Wiedrick3, Jian Shen2, Jon Jacobs4, Erin S Baker4, Aaron Baraff5, Paul Piehowski4, Christine G Lee6, Arie Baratt7, Vladislav Petyuk4, Shannon McWeeney7, Jeong Youn Lim5, Douglas C Bauer8, Nancy E Lane9, Peggy M Cawthon10, Richard D Smith4, Jodi Lapidus3, Eric S Orwoll2,11.   

Abstract

Serum proteomics analysis may lead to the discovery of novel osteoporosis biomarkers. The Osteoporotic Fractures in Men (MrOS) study comprises men ≥65 years old in the US who have had repeated BMD measures and have been followed for incident fracture. High-throughput quantitative proteomic analysis was performed on baseline fasting serum samples from non-Hispanic white men using a multidimensional approach coupling liquid chromatography, ion-mobility separation, and mass spectrometry (LC-IMS-MS). We followed the participants for a mean of 4.6 years for changes in femoral neck bone mineral density (BMD) and for incident hip fracture. Change in BMD was determined from mixed effects regression models taking age and weight into account. Participants were categorized into three groups: BMD maintenance (no decline; estimated change ≥0 g/cm2 , n = 453); expected loss (estimated change 0 to 1 SD below the estimated mean change, -0.034 g/cm2 for femoral neck, n = 1184); and accelerated loss (estimated change ≥1 SD below mean change, n = 237). Differential abundance values of 3946 peptides were summarized by meta-analysis to determine differential abundance of each of 339 corresponding proteins for accelerated BMD loss versus maintenance. Using this meta-analytic standardized fold change at cutoffs of ≥1.1 or ≤0.9 (p < 0.10), 20 proteins were associated with accelerated BMD loss. Associations of those 20 proteins with incident hip fracture were tested using Cox proportional hazards models with age and BMI adjustment in 2473 men. Five proteins were associated with incident hip fracture (HR between 1.29 and 1.41 per SD increase in estimated protein abundance). Some proteins have been previously associated with fracture risk (eg, CD14 and SHBG), whereas others have roles in cellular senescence and aging (B2MG and TIMP1) and complement activation and innate immunity (CO7, CO9, CFAD). These findings may inform development of biomarkers for future research in bone biology and fracture prediction.
© 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.

Entities:  

Keywords:  BIOCHEMICAL MARKERS OF BONE TURNOVER; GENERAL POPULATION STUDIES; OSTEOPOROSIS

Mesh:

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Year:  2017        PMID: 28316103      PMCID: PMC5489383          DOI: 10.1002/jbmr.3125

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


  68 in total

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4.  Design and baseline characteristics of the osteoporotic fractures in men (MrOS) study--a large observational study of the determinants of fracture in older men.

Authors:  Eric Orwoll; Janet Babich Blank; Elizabeth Barrett-Connor; Jane Cauley; Steven Cummings; Kristine Ensrud; Cora Lewis; Peggy M Cawthon; Robert Marcus; Lynn M Marshall; Joan McGowan; Kathy Phipps; Sherry Sherman; Marcia L Stefanick; Katie Stone
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Journal:  Am J Obstet Gynecol       Date:  2016-02-11       Impact factor: 8.661

6.  Femoral neck bone loss predicts fracture risk independent of baseline BMD.

Authors:  Tuan V Nguyen; Jacqueline R Center; John A Eisman
Journal:  J Bone Miner Res       Date:  2005-02-21       Impact factor: 6.741

Review 7.  Interactions of sex hormone-binding globulin with target cells.

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Journal:  Mol Cell Endocrinol       Date:  2009-08-19       Impact factor: 4.102

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Authors:  S Amano; K Kawakami; H Iwahashi; S Kitano; S Hanazawa
Journal:  J Cell Physiol       Date:  1997-12       Impact factor: 6.384

9.  Progressive Temporal Change in Serum SHBG, But Not in Serum Testosterone or Estradiol, Is Associated With Bone Loss and Incident Fractures in Older Men: The Concord Health and Ageing in Men Project.

Authors:  Benjumin Hsu; Markus J Seibel; Robert G Cumming; Fiona M Blyth; Vasi Naganathan; Kerrin Bleicher; David G Le Couteur; Louise M Waite; David J Handelsman
Journal:  J Bone Miner Res       Date:  2016-07-26       Impact factor: 6.741

10.  MMP-9 facilitates selective proteolysis of the histone H3 tail at genes necessary for proficient osteoclastogenesis.

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Journal:  Genes Dev       Date:  2016-01-07       Impact factor: 11.361

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4.  Proteomic studies of bone and skeletal health outcomes.

Authors:  Carrie M Nielson; Jon M Jacobs; Eric S Orwoll
Journal:  Bone       Date:  2019-04-04       Impact factor: 4.398

Review 5.  Bone health in ageing men.

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6.  Analysis of Serum Proteome after Treatment of Osteoporosis with Anabolic or Antiresorptive Drugs.

Authors:  Alvaro Del Real; Sergio Ciordia; Carolina Sañudo; Carmen Garcia-Ibarbia; Adriel Roa-Bautista; Javier G Ocejo-Viñals; Fernando Corrales; Jose A Riancho
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7.  Proteomic assessment of serum biomarkers of longevity in older men.

Authors:  Eric S Orwoll; Jack Wiedrick; Carrie M Nielson; Jon Jacobs; Erin S Baker; Paul Piehowski; Vladislav Petyuk; Yuqian Gao; Tujin Shi; Richard D Smith; Douglas C Bauer; Steven R Cummings; Jodi Lapidus
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8.  Proteomics Profiling of Osteoporosis and Osteopenia Patients and Associated Network Analysis.

Authors:  Mysoon M Al-Ansari; Shereen M Aleidi; Afshan Masood; Eman A Alnehmi; Mai Abdel Jabar; Maha Almogren; Mohammed Alshaker; Hicham Benabdelkamel; Anas M Abdel Rahman
Journal:  Int J Mol Sci       Date:  2022-09-05       Impact factor: 6.208

9.  High-throughput serum proteomics for the identification of protein biomarkers of mortality in older men.

Authors:  Eric S Orwoll; Jack Wiedrick; Jon Jacobs; Erin S Baker; Paul Piehowski; Vladislav Petyuk; Yuqian Gao; Tujin Shi; Richard D Smith; Douglas C Bauer; Steven R Cummings; Carrie M Nielson; Jodi Lapidus
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