IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0147475.html
   My bibliography  Save this article

Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women

Author

Listed:
  • Hao He
  • Shaolong Cao
  • Tianhua Niu
  • Yu Zhou
  • Lan Zhang
  • Yong Zeng
  • Wei Zhu
  • Yu-ping Wang
  • Hong-wen Deng

Abstract

Background: Existing microarray studies of bone mineral density (BMD) have been critical for understanding the pathophysiology of osteoporosis, and have identified a number of candidate genes. However, these studies were limited by their relatively small sample sizes and were usually analyzed individually. Here, we propose a novel network-based meta-analysis approach that combines data across six microarray studies to identify functional modules from human protein-protein interaction (PPI) data, and highlight several differentially expressed genes (DEGs) and a functional module that may play an important role in BMD regulation in women. Methods: Expression profiling studies were identified by searching PubMed, Gene Expression Omnibus (GEO) and ArrayExpress. Two meta-analysis methods were applied across different gene expression profiling studies. The first, a nonparametric Fisher’s method, combined p-values from individual experiments to identify genes with large effect sizes. The second method combined effect sizes from individual datasets into a meta-effect size to gain a higher precision of effect size estimation across all datasets. Genes with Q test’s p-values 50% were assessed by a random effects model and the remainder by a fixed effects model. Using Fisher’s combined p-values, functional modules were identified through an integrated analysis of microarray data in the context of large protein–protein interaction (PPI) networks. Two previously published meta-analysis studies of genome-wide association (GWA) datasets were used to determine whether these module genes were genetically associated with BMD. Pathway enrichment analysis was performed with a hypergeometric test. Results: Six gene expression datasets were identified, which included a total of 249 (129 high BMD and 120 low BMD) female subjects. Using a network-based meta-analysis, a consensus module containing 58 genes (nodes) and 83 edges was detected. Pathway enrichment analysis of the 58 module genes revealed that these genes were enriched in several important KEGG pathways including Osteoclast differentiation, B cell receptor signaling pathway, MAPK signaling pathway, Chemokine signaling pathway and Insulin signaling pathway. The importance of module genes was replicated by demonstrating that most module genes were genetically associated with BMD in the GWAS data sets. Meta-analyses were performed at the individual gene level by combining p-values and effect sizes. Five candidate genes (ESR1, MAP3K3, PYGM, RAC1 and SYK) were identified based on gene expression meta-analysis, and their associations with BMD were also replicated by two BMD meta-analysis studies. Conclusions: In summary, our network-based meta-analysis not only identified important differentially expressed genes but also discovered biologically meaningful functional modules for BMD determination. Our study may provide novel therapeutic targets for osteoporosis in women.

Suggested Citation

  • Hao He & Shaolong Cao & Tianhua Niu & Yu Zhou & Lan Zhang & Yong Zeng & Wei Zhu & Yu-ping Wang & Hong-wen Deng, 2016. "Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-16, January.
  • Handle: RePEc:plo:pone00:0147475
    DOI: 10.1371/journal.pone.0147475
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147475
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0147475&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0147475?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Adaikalavan Ramasamy & Adrian Mondry & Chris C Holmes & Douglas G Altman, 2008. "Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets," PLOS Medicine, Public Library of Science, vol. 5(9), pages 1-13, September.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Diego A Forero & Sandra Lopez-Leon & Yeimy González-Giraldo & Pantelis G Bagos, 2019. "Ten simple rules for carrying out and writing meta-analyses," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-7, May.
    2. Cherif Ben Hamda & Raphael Sangeda & Liberata Mwita & Ayton Meintjes & Siana Nkya & Sumir Panji & Nicola Mulder & Lamia Guizani-Tabbane & Alia Benkahla & Julie Makani & Kais Ghedira & H3ABioNet Consor, 2018. "A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-21, July.
    3. Ram Bhupal Reddy & Anupama Rajan Bhat & Bonney Lee James & Sindhu Valiyaveedan Govindan & Rohit Mathew & Ravindra DR & Naveen Hedne & Jeyaram Illiayaraja & Vikram Kekatpure & Samanta S Khora & Wesley , 2016. "Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
    4. İlkay Unay-Gailhard & Mark A. Brennen, 2022. "How digital communications contribute to shaping the career paths of youth: a review study focused on farming as a career option," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1491-1508, December.
    5. Mahin Ghafari & Vali Baigi & Zahra Cheraghi & Amin Doosti-Irani, 2016. "The Prevalence of Asymptomatic Bacteriuria in Iranian Pregnant Women: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-10, June.
    6. Elizabeth T Cafiero-Fonseca & Andrew Stawasz & Sydney T Johnson & Reiko Sato & David E Bloom, 2017. "The full benefits of adult pneumococcal vaccination: A systematic review," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-23, October.
    7. Santos Urbina & Sofía Villatoro & Jesús Salinas, 2021. "Self-Regulated Learning and Technology-Enhanced Learning Environments in Higher Education: A Scoping Review," Sustainability, MDPI, vol. 13(13), pages 1-12, June.
    8. Oded Berger-Tal & Alison L Greggor & Biljana Macura & Carrie Ann Adams & Arden Blumenthal & Amos Bouskila & Ulrika Candolin & Carolina Doran & Esteban Fernández-Juricic & Kiyoko M Gotanda & Catherine , 2019. "Systematic reviews and maps as tools for applying behavioral ecology to management and policy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 30(1), pages 1-8.
    9. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
    10. Maryono, Maryono & Killoes, Aditya Marendra & Adhikari, Rajendra & Abdul Aziz, Ammar, 2024. "Agriculture development through multi-stakeholder partnerships in developing countries: A systematic literature review," Agricultural Systems, Elsevier, vol. 213(C).
    11. Alene Sze Jing Yong & Yi Heng Lim & Mark Wing Loong Cheong & Ednin Hamzah & Siew Li Teoh, 2022. "Willingness-to-pay for cancer treatment and outcome: a systematic review," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1037-1057, August.
    12. Xue-Ying Xu & Hong Kong & Rui-Xiang Song & Yu-Han Zhai & Xiao-Fei Wu & Wen-Si Ai & Hong-Bo Liu, 2014. "The Effectiveness of Noninvasive Biomarkers to Predict Hepatitis B-Related Significant Fibrosis and Cirrhosis: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-16, June.
    13. Vicente Miñana-Signes & Manuel Monfort-Pañego & Javier Valiente, 2021. "Teaching Back Health in the School Setting: A Systematic Review of Randomized Controlled Trials," IJERPH, MDPI, vol. 18(3), pages 1-18, January.
    14. Agnieszka A. Tubis & Katarzyna Grzybowska, 2022. "In Search of Industry 4.0 and Logistics 4.0 in Small-Medium Enterprises—A State of the Art Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    15. Obsa Urgessa Ayana & Jima Degaga, 2022. "Effects of rural electrification on household welfare: a meta-regression analysis," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 69(2), pages 209-261, June.
    16. Caloffi, Annalisa & Colovic, Ana & Rizzoli, Valentina & Rossi, Federica, 2023. "Innovation intermediaries' types and functions: A computational analysis of the literature," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    17. García-Poole, Chloe & Byrne, Sonia & Rodrigo, María José, 2019. "How do communities intervene with adolescents at psychosocial risk? A systematic review of positive development programs," Children and Youth Services Review, Elsevier, vol. 99(C), pages 194-209.
    18. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    19. Qing Ye & Bao-Xin Qian & Wei-Li Yin & Feng-Mei Wang & Tao Han, 2016. "Association between the HFE C282Y, H63D Polymorphisms and the Risks of Non-Alcoholic Fatty Liver Disease, Liver Cirrhosis and Hepatocellular Carcinoma: An Updated Systematic Review and Meta-Analysis o," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    20. Bishal Mohindru & David Turner & Tracey Sach & Diana Bilton & Siobhan Carr & Olga Archangelidi & Arjun Bhadhuri & Jennifer A. Whitty, 2020. "Health State Utility Data in Cystic Fibrosis: A Systematic Review," PharmacoEconomics - Open, Springer, vol. 4(1), pages 13-25, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0147475. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.