Evidence map›Paper›PMID 27153759›Full record

ArticleJournal of proteomics2016

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

Yong Zeng, Lan Zhang, Wei Zhu, Chao Xu, Hao He, Yu Zhou, Yao-Zhong Liu, Qing Tian, Ji-Gang Zhang, Fei-Yan Deng and 3 more

Erratum issuedOpen access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. P4 medicine and osteoporosis: a systematic review.Wiener klinische Wochenschrift · 2016
    Pooled it
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. IMPC-based screening revealed thatFrontiers in cell and developmental biology · 2024
    Article
  13. Article
  14. Article
  15. Observational
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 2 countries.

Yong ZengCollege of Life Sciences and Bioengineering, Beijing Jiao Tong University, Beijing 100044, China; Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Lan ZhangCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Wei ZhuCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA; College of Life Sciences, Hunan Normal University, Changsha 410081, Hunan, China.
Chao XuCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Hao HeCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Yu ZhouCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Yao-Zhong LiuCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Qing TianCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Ji-Gang ZhangCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA.
Fei-Yan DengCenter for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA; Laboratory of Proteins and Proteomics, Department of Epidemiology, Soochow University School of Public Health, Suzhou 205123, Jiangsu, China.
Hong-Gang HuCollege of Life Sciences and Bioengineering, Beijing Jiao Tong University, Beijing 100044, China.
Li-Shu ZhangCollege of Life Sciences and Bioengineering, Beijing Jiao Tong University, Beijing 100044, China.
Hong-Wen DengCollege of Life Sciences and Bioengineering, Beijing Jiao Tong University, Beijing 100044, China; Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans 70112, LA, USA. Electronic address: hdeng2@tulane.edu.
Tulane University · USBeijing Jiaotong University · CNSoochow University · CN

Funding

Proteome-wide Expression Study of Osteogenic CellsP50AR055081 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2012
$5.0M
ROBUST AND POWERFUL TEST OF CANDIDATE GENES TO BONE MASSR01AR050496 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2004 to 2013
$3.8M
Epigenomewide DNA Methylation Study for Osteoporosis RiskR01AR059781 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2012 to 2016
$3.1M
Identification of Proteins Important for Male OsteoporosisR01AR057049 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2009 to 2013
$2.4M
Genomic search for bone mass QTLsR01AG026564 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2010
$2.3M
Proteomics Study of Peripheral Blood Monocytes on OsteroporsisR21AG027110 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2006 to 2007
$367k
NIAMS NIH HHS P50 AR055081NIAMS NIH HHS R01 AR050496NIAMS NIH HHS R01 AR057049NIAMS NIH HHS R01 AR059781NIA NIH HHS R01 AG026564NIA NIH HHS R21 AG027110
6 · The paper itself

Abstract

unlabelledOsteoporosis 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-MS(E) (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 MS(E) 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.

Indexed as

Bone DensityGenome-Wide Association StudyActin CytoskeletonFemaleGelsolinHumansIntegrin alpha2Metabolic Networks and PathwaysMiddle AgedMonocytesOsteoporosisProteomeProteomicsrhoA GTP-Binding ProteinTransendothelial and Transepithelial MigrationGelsolinIntegrin alpha2ITGA2B protein, humanProteomerhoA GTP-Binding ProteinRHOA protein, humanNetwork analysisOsteoporosisPathwaysPeripheral blood monocytesQuantitative proteomics

Identifiers

PMID27153759
PMCPMC5362378
OpenAlexW2345989376

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.