Elsevier

Journal of Proteomics

Volume 142, 16 June 2016, Pages 45-52
Journal of Proteomics

Quantitative proteomics and integrative network analysis identified novel genes and pathways related to osteoporosis

https://doi.org/10.1016/j.jprot.2016.04.044Get rights and content

Highlights

  • A total of 2058 proteins were identified in 33 samples by LC-nano-ESI-MSE.

  • A total of 30 unique proteins were identified as differentially expressed proteins (p < 0.05).

  • Differentially expressed genes: ITGA2B, GSN and RHOA played crucial roles in osteoporosis risk.

  • Pathways: “regulation of actin cytoskeleton” and “leukocyte transendothelial migration” are involved in osteoporosis.

  • The results were further verified in protein-RNA integrative analysis and genome wide association study.

Abstract

Osteoporosis is mainly characterized by low bone mineral density (BMD), and can be attributed to excessive bone resorption by osteoclasts. Migration of circulating monocytes from blood to bone is important for subsequent osteoclast differentiation and bone resorption. Identification of those genes and pathways related to osteoclastogenesis and BMD will contribute to a better understanding of the pathophysiological mechanisms of osteoporosis. In this study, we applied the LC-nano-ESI-MSE (Liquid Chromatograph-nano-Electrospray Ionization-Mass Spectrometry) for quantitative proteomic profiling in 33 female Caucasians with discordant BMD levels, with 16 high vs. 17 low BMD subjects. Protein quantitation was accomplished by label-free measurement of total ion currents collected from MSE data. Comparison of protein expression in high vs. low BMD subjects showed that ITGA2B (p = 0.0063) and GSN (p = 0.019) were up-regulated in the high BMD group. Additionally, our protein-RNA integrative analysis showed that RHOA (p = 0.00062) differentially expressed between high vs. low BMD groups. Network analysis based on multiple tools revealed two pathways: “regulation of actin cytoskeleton” (p = 1.13E−5, FDR = 3.34E−4) and “leukocyte transendothelial migration” (p = 2.76E−4, FDR = 4.71E−3) that are functionally relevant to osteoporosis. Consistently, ITGA2B, GSN and RHOA played crucial roles in these two pathways respectively. All together, our study strongly supported the contribution of the genes ITGA2B, GSN and RHOA and the two pathways to osteoporosis risk.

Biological significance

Mass spectrometry based quantitative proteomics study integrated with network analysis identified novel genes and pathways related to osteoporosis. The results were further verified in multiple level studies including protein-RNA integrative analysis and genome wide association studies.

Introduction

Osteoporosis is a global public health problem with a high heritability, and mainly characterized by low BMD [1]. Osteoporosis has become one of the most serious public health problems around the world, leading to millions of fractures annually [1], [2]. Among fractures at various skeletal sites, hip fracture is the most important owing to its high prevalence, high morbidity and mortality, and excessive therapeutic cost [3], [4].

Monocytes are bone marrow-derived circulating leukocytes that can further differentiate into various cell types like macrophages and dendritic cells [5]. The morphology of mature monocytes in the peripheral circulation is heterogeneous, and these cells constitute 5–10% of peripheral blood leukocytes in humans [6]. Human peripheral blood monocytes (PBMs) may serve as precursors of osteoclasts and produce cytokines important for osteoclast differentiation, activation, and apoptosis as well as acting as one of the most important target cells for sex hormones in bone metabolism [7], [8]. In the bone field, PBMs have already been well-established/accepted as a well working excellent cell model for studying gene/protein expression patterns and their regulation mechanisms in relation to osteoporosis risk in vivo in humans [9], [10], [11], [12], [13], [14]. Numerous studies highlighted the feasibility and utility of employing in vivo PBMs to study novel pathophysiological mechanisms during the process of osteoclastogenesis underlying osteoporosis risk [8], [12]. Therefore, PBMs are one major class of cells that are functionally relevant to the pathogenesis of osteoporosis and they have been successfully used for etiology studies in the bone field.

Network analysis can identify the correlation and topology between different proteins. Pathways/modules generated by network analysis may reflect the biological processes more comprehensively and objectively than single protein/gene analysis [15]. Based on the utilization of functional information and topological information, there are quite some approaches to perform gene enrichment analysis, pathway analysis, functional cluster analysis and network reconstruction analysis [16]. For instance, DAVID (Database for Annotation, Visualization and Integrated Discovery) is a popular knowledgebase including multiple online tools which can provide abundant functional information from multiple databases for a list of genes. However, the topological features generated from DAVID may be quite limited [16], [17]. In contrast, as a frequently-used platform for network analyses, the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database engine can provide more topological information [16], [18]. Furthermore, Cytoscape, an open source software project for data integration, network analysis and visualization [19], is a powerful tool with hundreds of comprehensive and timely-updated applications which can provide multiple functions of network analyses.

With sensitive LC-nano-ESI-MSE (Liquid Chromatograph-nano-Electrospray Ionization-Mass Spectrometry) based quantitative proteomic analysis, we identified a number of proteins that contribute to the pathogenesis of osteoporosis individually. Different kinds of tools were then used for network analysis to maximize the coverage of significant biological information related to bone metabolism. DAVID was used for the preliminary functional annotation and gene enrichment analysis. STRING and Cytoscape were applied for comprehensive network reconstruction and visualization. Additionally, in order to add more evidence to the results from our quantitative proteomic study, an in silico replication study was performed at genome-wide level.

Section snippets

Human subjects

Our study was approved by Institutional Review Boards of University of Missouri Kansas City and Tulane University. All the subjects signed consent forms before being enrolled into this study. All subjects were self-identified as European Caucasian females. 33 subjects were recruited in this study. The lumbar spine BMD (g/cm2) and hip BMD (which is the combined value of three regions including femoral neck, trochanter and interchochanter) were measured by using Hologic 4500 W dual energy X-ray

Proteomic profiling

In this study, a total of 2058 proteins were identified in 33 samples by LC-nano-ESI-MSE. To reduce false proteins detection, 1142 out of 2058 proteins, which were detected in 5 or more subjects were used for further analyses [12] (Supplemental Table 1). Furthermore, a global normalization method was applied for data quality control in order to minimize the variability due to sample preparation or equipment conditions. We applied log2 transformation of our data for further analyses.

Identification of differentially-expressed proteins (DEPs)

We applied

Discussion

With its potential to differentiate into osteoclasts and the production of potent pro-inflammatory and anti-inflammatory cytokines, PBMs are likely to play broad and critical roles in bone metabolism [30], [31]. Abnormal behavior in PBM formation, migration, differentiation, functional activity, and apoptosis may be closely related to the development of human skeletal disorders [24]. In particular, it has now been well established by numerous studies that multi-omics and molecular studies using

Conclusions

In our study, label-free based quantitative proteomics integrated with network analysis strongly supported the contribution of the genes ITGA2B, GSN and RHOA and the pathways “regulation of actin cytoskeleton” and “leukocyte transendothelial migration” to osteoporosis risk. The results were further verified in multiple level studies including protein-RNA integrative analysis and genome wide association study.

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Acknowledgement

This study was partially supported by grants from NIH (P50AR055081, R21AG27110, R01AR057049, R01AR050496, and R01AG026564), Franklin D. Dickson/Missouri Endowment and Edward G. Schlieder Endowment. The study also benefited from the National Natural Science Foundation of China (31371194) and the Fundamental Research Funds from the Central Universities (2013JBM098).

References (53)

  • Y.J. Liu et al.

    Molecular genetic studies of gene identification for osteoporosis: a 2004 update

    J. Bone Miner. Res.

    (2006)
  • J.A. Cauley et al.

    Risk of mortality following clinical fractures

    Osteoporos. Int.

    (2000)
  • F. Geissmann et al.

    Development of monocytes, macrophages, and dendritic cells

    Science

    (2010)
  • S. Gordon et al.

    Monocyte and macrophage heterogeneity

    Nat. Rev. Immunol.

    (2005)
  • E. Narni-Mancinelli et al.

    Inflammatory monocytes and neutrophils are licensed to kill during memory responses in vivo

    PLoS Pathog.

    (2011)
  • J.P. Bonjour et al.

    The importance and relevance of peak bone mass in the prevalence of osteoporosis

    Salud Publica Mex.

    (2009)
  • L.M. Reynolds et al.

    Age-related variations in the methylome associated with gene expression in human monocytes and T cells

    Nat. Commun.

    (2014)
  • R.P. Talens et al.

    Epigenetic variation during the adult lifespan: cross-sectional and longitudinal data on monozygotic twin pairs

    Aging Cell

    (2012)
  • F.Y. Deng et al.

    Peripheral blood monocyte-expressed ANXA2 gene is involved in pathogenesis of osteoporosis in humans

    Mol. Cell. Proteomics

    (2011)
  • Y. Liu et al.

    Methylomics of gene expression in human monocytes

    Hum. Mol. Genet.

    (2013)
  • S.H. Ralston et al.

    Loci for regulation of bone mineral density in men and women identified by genome wide linkage scan: the FAMOS study

    Hum. Mol. Genet.

    (2005)
  • H.L. Swa et al.

    Mass spectrometry based quantitative proteomics and integrative network analysis accentuates modulating roles of annexin-1 in mammary tumorigenesis

    Proteomics

    (2014)
  • X. Wu et al.

    Pathway and network analysis in proteomics

    J. Theor. Biol.

    (2014)
  • B.T. Sherman et al.

    DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

    BMC Bioinf.

    (2007)
  • A. Franceschini et al.

    STRING v9.1: protein-protein interaction networks, with increased coverage and integration

    Nucleic Acids Res.

    (2013)
  • P. Shannon et al.

    Cytoscape: a software environment for integrated models of biomolecular interaction networks

    Genome Res.

    (2003)
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    All authors state that they have no conflicts of interest.

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