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

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.

[1]  F. Blyth,et al.  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 , 2016, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[2]  G. Hunter,et al.  The effects of weight loss approaches on bone mineral density in adults: a systematic review and meta-analysis of randomized controlled trials , 2016, Osteoporosis International.

[3]  Matthew K Hoffman,et al.  Development and validation of a spontaneous preterm delivery predictor in asymptomatic women. , 2016, American journal of obstetrics and gynecology.

[4]  S. Cummings,et al.  Sex hormones, sex hormone binding globulin, and vertebral fractures in older men. , 2016, Bone.

[5]  Yi-Xiang J. Wang,et al.  High Serum SHBG Predicts Incident Vertebral Fractures in Elderly Men , 2016, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[6]  T. Ulmer,et al.  MMP-9 facilitates selective proteolysis of the histone H3 tail at genes necessary for proficient osteoclastogenesis , 2016, Genes & development.

[7]  J. A. Robbins,et al.  Soluble CD14 and fracture risk , 2016, Osteoporosis International.

[8]  P. Luppa,et al.  The biomarker sex hormone-binding globulin - from established applications to emerging trends in clinical medicine. , 2015, Best practice & research. Clinical endocrinology & metabolism.

[9]  Beth Wilmot,et al.  Edinburgh Explorer Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture , 2022 .

[10]  Gregor Bieri,et al.  β2-microglobulin is a systemic pro-aging factor that impairs cognitive function and neurogenesis , 2015, Nature Medicine.

[11]  Olli Simell,et al.  Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility , 2015, Diabetes.

[12]  Davide Heller,et al.  STRING v10: protein–protein interaction networks, integrated over the tree of life , 2014, Nucleic Acids Res..

[13]  Magda Tsolaki,et al.  Circulating Proteomic Signatures of Chronological Age , 2014, The journals of gerontology. Series A, Biological sciences and medical sciences.

[14]  A. Antonov,et al.  Characterization of novel markers of senescence and their prognostic potential in cancer , 2014, Cell Death and Disease.

[15]  Andreas Schmidt,et al.  Bioinformatic analysis of proteomics data , 2014, BMC Systems Biology.

[16]  Gordon W. Slysz,et al.  Advancing the High Throughput Identification of Liver Fibrosis Protein Signatures Using Multiplexed Ion Mobility Spectrometry* , 2014, Molecular & Cellular Proteomics.

[17]  R. Langer Postmenopausal Estrogen/Progestin Interventions Trial (PEPI) , 2014 .

[18]  Paul D Piehowski,et al.  Increasing Confidence of LC-MS Identifications by Utilizing Ion Mobility Spectrometry. , 2013, International journal of mass spectrometry.

[19]  Brian L. LaMarche,et al.  LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets , 2013, Bioinform..

[20]  R. Wolfe,et al.  LB014-SUN SERUM BIOMARKERS THAT PREDICT LEAN BODY MASS (LBM) LOSS OVER BEDREST (BR) IN OLDER ADULTS , 2013 .

[21]  John D Lambris,et al.  Does complement play a role in bone development and regeneration? , 2013, Immunobiology.

[22]  Richard D. Smith,et al.  Normalization and missing value imputation for label-free LC-MS analysis , 2012, BMC Bioinformatics.

[23]  S. Cummings,et al.  Change in hip bone mineral density and risk of subsequent fractures in older men , 2012, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[24]  Oddom Demontiero,et al.  Aging and bone loss: new insights for the clinician , 2012, Therapeutic advances in musculoskeletal disease.

[25]  Tracy R. Keeney,et al.  Age-dependent changes in the cerebrospinal fluid proteome by slow off-rate modified aptamer array. , 2012, The American journal of pathology.

[26]  J. Lambris,et al.  Complement C3a and C5a modulate osteoclast formation and inflammatory response of osteoblasts in synergism with IL‐1β , 2011, Journal of cellular biochemistry.

[27]  J. Kaufman,et al.  Dipeptidyl Peptidase 4 Is a Novel Adipokine Potentially Linking Obesity to the Metabolic Syndrome , 2011, Diabetes.

[28]  M. Dombrowski,et al.  Proteomic identification of serum peptides predicting subsequent spontaneous preterm birth. , 2011, American journal of obstetrics and gynecology.

[29]  J. Kaye,et al.  The ageing systemic milieu negatively regulates neurogenesis and cognitive function , 2011 .

[30]  M. Sughrue,et al.  The complement cascade as a mediator of tissue growth and regeneration , 2010, Inflammation Research.

[31]  Yehia M. Ibrahim,et al.  Characterization of an Ion Mobility-Multiplexed Collision Induced Dissociation-Tandem Time-of-Flight Mass Spectrometry Approach. , 2010, International journal of mass spectrometry.

[32]  S. Kahn,et al.  Interactions of sex hormone-binding globulin with target cells , 2010, Molecular and Cellular Endocrinology.

[33]  L. Xing,et al.  Functions of nuclear factor κB in bone , 2010, Annals of the New York Academy of Sciences.

[34]  J. Cauley,et al.  Sex steroid hormones in older men: longitudinal associations with 4.5-year change in hip bone mineral density--the osteoporotic fractures in men study. , 2010, The Journal of clinical endocrinology and metabolism.

[35]  S. Cummings,et al.  Loss of Hip BMD in Older Men: The Osteoporotic Fractures in Men (MrOS) Study , 2009, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[36]  E. Barrett-Connor,et al.  The effects of serum testosterone, estradiol, and sex hormone binding globulin levels on fracture risk in older men. , 2009, The Journal of clinical endocrinology and metabolism.

[37]  M. Cooper,et al.  Bone loss in inflammatory disorders. , 2009, The Journal of endocrinology.

[38]  Antoine M. van Oijen,et al.  Real-time single-molecule observation of rolling-circle DNA replication , 2009, Nucleic acids research.

[39]  S. Cummings,et al.  Successful Skeletal Aging: A Marker of Low Fracture Risk and Longevity. The Study of Osteoporotic Fractures (SOF) , 2009, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[40]  Brad T. Sherman,et al.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists , 2008, Nucleic acids research.

[41]  N L Fazzalari,et al.  Gene expression profile of the bone microenvironment in human fragility fracture bone. , 2009, Bone.

[42]  Navdeep Jaitly,et al.  Decon2LS: An open-source software package for automated processing and visualization of high resolution mass spectrometry data , 2009, BMC Bioinformatics.

[43]  C. Ding,et al.  Circulating levels of inflammatory markers predict change in bone mineral density and resorption in older adults: a longitudinal study. , 2008, The Journal of clinical endocrinology and metabolism.

[44]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[45]  D. Heinegård,et al.  COMP Acts as a Catalyst in Collagen Fibrillogenesis* , 2007, Journal of Biological Chemistry.

[46]  R. Paschke,et al.  Tissue inhibitor of metalloproteinase-1 predicts adiposity in humans. , 2007, European journal of endocrinology.

[47]  M. Kenward,et al.  An Introduction to the Bootstrap , 2007 .

[48]  Richard D. Smith,et al.  Advances in proteomics data analysis and display using an accurate mass and time tag approach. , 2006, Mass spectrometry reviews.

[49]  E. Petricoin,et al.  Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold. , 2005, The Journal of clinical investigation.

[50]  H. Jersmann Time to abandon dogma: CD14 is expressed by non‐myeloid lineage cells , 2005, Immunology and cell biology.

[51]  S. Cummings,et al.  Design and baseline characteristics of the osteoporotic fractures in men (MrOS) study--a large observational study of the determinants of fracture in older men. , 2005, Contemporary clinical trials.

[52]  P. Cawthon,et al.  Overview of recruitment for the osteoporotic fractures in men study (MrOS). , 2005, Contemporary clinical trials.

[53]  J. Eisman,et al.  Femoral Neck Bone Loss Predicts Fracture Risk Independent of Baseline BMD , 2005, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[54]  C. Lewis,et al.  Voluntary weight reduction in older men increases hip bone loss: the osteoporotic fractures in men study. , 2005, The Journal of clinical endocrinology and metabolism.

[55]  Keiichi Sasaki,et al.  Osteoblasts and osteocytes express MMP2 and -8 and TIMP1, -2, and -3 along with extracellular matrix molecules during appositional bone formation. , 2004, The anatomical record. Part A, Discoveries in molecular, cellular, and evolutionary biology.

[56]  D. Collen,et al.  Deficiency of tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) impairs nutritionally induced obesity in mice , 2003, Thrombosis and Haemostasis.

[57]  John D. Storey A direct approach to false discovery rates , 2002 .

[58]  E. Petricoin,et al.  Use of proteomic patterns in serum to identify ovarian cancer , 2002, The Lancet.

[59]  G. Rice,et al.  Proteomic analysis of human plasma: Failure of centrifugal ultrafiltration to remove albumin and other high molecular weight proteins , 2001, Proteomics.

[60]  S. Cummings,et al.  Rate of Bone Loss Is Associated with Mortality in Older Women: A Prospective Study , 2000, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[61]  P. D. Di Cesare,et al.  Molecular cloning, sequencing, and tissue and developmental expression of mouse cartilage oligomeric matrix protein (COMP) , 2000, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[62]  E. Balint,et al.  Role of interleukin-6 in beta2-microglobulin-induced bone mineral dissolution. , 2000, Kidney international.

[63]  M. Raida,et al.  Liquid chromatography and electrospray mass spectrometric mapping of peptides from human plasma filtrate , 1999, Journal of the American Society for Mass Spectrometry.

[64]  R. Parker,et al.  Early Changes in Biochemical Markers of Bone Turnover Predict the Long‐Term Response to Alendronate Therapy in Representative Elderly Women: A Randomized Clinical Trial , 1998, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[65]  S. Kitano,et al.  Functional role of endogenous CD14 in lipopolysaccharide‐stimulated bone resorption , 1997, Journal of cellular physiology.

[66]  Z. Werb,et al.  Matrix metalloproteinases regulate morphogenesis, migration and remodeling of epithelium, tongue skeletal muscle and cartilage in the mandibular arch. , 1997, Development.

[67]  T. Miyata,et al.  Advanced glycation of beta 2-microglobulin in the pathogenesis of bone lesions in dialysis-associated amyloidosis. , 1996, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[68]  A. Olsen,et al.  Pseudoachondroplasia and multiple epiphyseal dysplasia due to mutations in the cartilage oligomeric matrix protein gene , 1995, Nature Genetics.

[69]  L. Avioli,et al.  Expression of metalloproteinases and tissue inhibitors of metalloproteinases in human osteoblast-like cells: differentiation is associated with repression of metalloproteinase biosynthesis. , 1994, Endocrinology.

[70]  B. Spiegelman,et al.  Adipsin and complement factor D activity: an immune-related defect in obesity , 1989, Science.

[71]  Jun Shao,et al.  The Efficiency and Consistency of Approximations to the Jackknife Variance Estimators , 1989 .

[72]  B. Spiegelman,et al.  Severely impaired adipsin expression in genetic and acquired obesity. , 1987, Science.

[73]  P. Bornstein,et al.  Interactions of thrombospondin with extracellular matrix proteins: selective binding to type V collagen , 1984, The Journal of cell biology.

[74]  W. Ward,et al.  Protein purification: Principles and practice , 1984 .

[75]  R. Hynes,et al.  Analysis of platelet adhesion with a radioactive chemical crosslinking reagent: Interaction of thrombospondin with fibronectin and collagen , 1982, Cell.

[76]  W. Greene Sample Selection Bias as a Specification Error: Comment , 1981 .

[77]  J. Heckman Sample selection bias as a specification error , 1979 .