IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0249528.html
   My bibliography  Save this article

Human microbiome privacy risks associated with summary statistics

Author

Listed:
  • Jae-Chang Cho

Abstract

Recognizing that microbial community composition within the human microbiome is associated with the physiological state of the host has sparked a large number of human microbiome association studies (HMAS). With the increasing size of publicly available HMAS data, the privacy risk is also increasing because HMAS metadata could contain sensitive private information. I demonstrate that a simple test statistic based on the taxonomic profiles of an individual’s microbiome along with summary statistics of HMAS data can reveal the membership of the individual’s microbiome in an HMAS sample. In particular, species-level taxonomic data obtained from small-scale HMAS can be highly vulnerable to privacy risk. Minimal guidelines for HMAS data privacy are suggested, and an assessment of HMAS privacy risk using the simulation method proposed is recommended at the time of study design.

Suggested Citation

  • Jae-Chang Cho, 2021. "Human microbiome privacy risks associated with summary statistics," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-11, April.
  • Handle: RePEc:plo:pone00:0249528
    DOI: 10.1371/journal.pone.0249528
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249528
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249528&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0249528?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. Peter J. Turnbaugh & Ruth E. Ley & Micah Hamady & Claire M. Fraser-Liggett & Rob Knight & Jeffrey I. Gordon, 2007. "The Human Microbiome Project," Nature, Nature, vol. 449(7164), pages 804-810, October.
    2. Rosemary Braun & William Rowe & Carl Schaefer & Jinghui Zhang & Kenneth Buetow, 2009. "Needles in the Haystack: Identifying Individuals Present in Pooled Genomic Data," PLOS Genetics, Public Library of Science, vol. 5(10), pages 1-8, October.
    3. Alexandre Almeida & Alex L. Mitchell & Miguel Boland & Samuel C. Forster & Gregory B. Gloor & Aleksandra Tarkowska & Trevor D. Lawley & Robert D. Finn, 2019. "A new genomic blueprint of the human gut microbiota," Nature, Nature, vol. 568(7753), pages 499-504, April.
    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. Shilan Li & Jianxin Shi & Paul Albert & Hong-Bin Fang, 2022. "Dependence Structure Analysis and Its Application in Human Microbiome," Mathematics, MDPI, vol. 11(1), pages 1-14, December.
    2. Daphna Rothschild & Erez Dekel & Jean Hausser & Anat Bren & Guy Aidelberg & Pablo Szekely & Uri Alon, 2014. "Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-9, May.
    3. Li Zhang & Karen R. Jonscher & Zuyuan Zhang & Yi Xiong & Ryan S. Mueller & Jacob E. Friedman & Chongle Pan, 2022. "Islet autoantibody seroconversion in type-1 diabetes is associated with metagenome-assembled genomes in infant gut microbiomes," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Pirjo Wacklin & Harri Mäkivuokko & Noora Alakulppi & Janne Nikkilä & Heli Tenkanen & Jarkko Räbinä & Jukka Partanen & Kari Aranko & Jaana Mättö, 2011. "Secretor Genotype (FUT2 gene) Is Strongly Associated with the Composition of Bifidobacteria in the Human Intestine," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-10, May.
    5. Yee Sang Wong & Nicholas John Osborne, 2022. "Biodiversity Effects on Human Mental Health via Microbiota Alterations," IJERPH, MDPI, vol. 19(19), pages 1-13, September.
    6. Weiyue Ji & Handuo Shi & Haoqian Zhang & Rui Sun & Jingyi Xi & Dingqiao Wen & Jingchen Feng & Yiwei Chen & Xiao Qin & Yanrong Ma & Wenhan Luo & Linna Deng & Hanchi Lin & Ruofan Yu & Qi Ouyang, 2013. "A Formalized Design Process for Bacterial Consortia That Perform Logic Computing," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    7. Disha Tandon & Mohammed Monzoorul Haque & Sharmila S Mande, 2016. "Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-16, April.
    8. Eric Z. Chen & Frederic D. Bushman & Hongzhe Li, 2017. "A Model-Based Approach for Species Abundance Quantification Based on Shotgun Metagenomic Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 13-27, June.
    9. Zhenqiu Liu & Dechang Chen & Li Sheng & Amy Y Liu, 2013. "Class Prediction and Feature Selection with Linear Optimization for Metagenomic Count Data," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-7, March.
    10. Charles K Fisher & Thierry Mora & Aleksandra M Walczak, 2017. "Variable habitat conditions drive species covariation in the human microbiota," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-18, April.
    11. Bahareh Mansoorian & Emilie Combet & Areej Alkhaldy & Ada L. Garcia & Christine Ann Edwards, 2019. "Impact of Fermentable Fibres on the Colonic Microbiota Metabolism of Dietary Polyphenols Rutin and Quercetin," IJERPH, MDPI, vol. 16(2), pages 1-12, January.
    12. Ran Li & Yongming Wang & Han Hu & Yan Tan & Yingfei Ma, 2022. "Metagenomic analysis reveals unexplored diversity of archaeal virome in the human gut," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    13. Ying-Li Zhou & Paraskevi Mara & Guo-Jie Cui & Virginia P. Edgcomb & Yong Wang, 2022. "Microbiomes in the Challenger Deep slope and bottom-axis sediments," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    14. Candice R. Gurbatri & Georgette A. Radford & Laura Vrbanac & Jongwon Im & Elaine M. Thomas & Courtney Coker & Samuel R. Taylor & YoungUk Jang & Ayelet Sivan & Kyu Rhee & Anas A. Saleh & Tiffany Chien , 2024. "Engineering tumor-colonizing E. coli Nissle 1917 for detection and treatment of colorectal neoplasia," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    15. Matthew D. Koslovsky, 2023. "A Bayesian zero‐inflated Dirichlet‐multinomial regression model for multivariate compositional count data," Biometrics, The International Biometric Society, vol. 79(4), pages 3239-3251, December.
    16. Jake M. Robinson & Jacob G. Mills & Martin F. Breed, 2018. "Walking Ecosystems in Microbiome-Inspired Green Infrastructure: An Ecological Perspective on Enhancing Personal and Planetary Health," Challenges, MDPI, vol. 9(2), pages 1-15, November.
    17. Patricio S La Rosa & J Paul Brooks & Elena Deych & Edward L Boone & David J Edwards & Qin Wang & Erica Sodergren & George Weinstock & William D Shannon, 2012. "Hypothesis Testing and Power Calculations for Taxonomic-Based Human Microbiome Data," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-13, December.
    18. Xinhui Wang & Marinus J C Eijkemans & Jacco Wallinga & Giske Biesbroek & Krzysztof Trzciński & Elisabeth A M Sanders & Debby Bogaert, 2012. "Multivariate Approach for Studying Interactions between Environmental Variables and Microbial Communities," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    19. Barbara Emmenegger & Julien Massoni & Christine M. Pestalozzi & Miriam Bortfeld-Miller & Benjamin A. Maier & Julia A. Vorholt, 2023. "Identifying microbiota community patterns important for plant protection using synthetic communities and machine learning," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    20. Margaret Coleman & Christopher Elkins & Bradford Gutting & Emmanuel Mongodin & Gloria Solano‐Aguilar & Isabel Walls, 2018. "Microbiota and Dose Response: Evolving Paradigm of Health Triangle," Risk Analysis, John Wiley & Sons, vol. 38(10), pages 2013-2028, October.

    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:pone00:0249528. 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.