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Harnessing human microbiomes for disease prediction

  • University of Cambridge
  • Baker Heart and Diabetes Institute
  • Department of Clinical Pathology
  • University of Melbourne
  • St. Vincent's Institute for Medical Research
  • School of Biosciences
  • Monash University
  • Department of Medical Science
  • Uppsala University
  • La Trobe University
  • Department of Cardiometabolic Health
  • Department of Cardiovascular Research

Research output: Contribution to journalReview articlepeer-review

12   Link opens in a new tab Citations (SciVal)

Abstract

The human microbiome has been increasingly recognized as having potential use for disease prediction. Predicting the risk, progression, and severity of diseases holds promise to transform clinical practice, empower patient decisions, and reduce the burden of various common diseases, as has been demonstrated for cardiovascular disease or breast cancer. Combining multiple modifiable and non-modifiable risk factors, including high-dimensional genomic data, has been traditionally favored, but few studies have incorporated the human microbiome into models for predicting the prospective risk of disease. Here, we review research into the use of the human microbiome for disease prediction with a particular focus on prospective studies as well as the modulation and engineering of the microbiome as a therapeutic strategy.

Original languageEnglish
Pages (from-to)707-719
Number of pages13
JournalTrends in Microbiology
Volume32
Issue number7
Early online date20 Jan 2024
DOIs
Publication statusPublished - 31 Jul 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • disease prediction
  • gut microbiota
  • machine learning
  • metagenomics
  • microbiome

ASJC Scopus subject areas

  • Microbiology
  • Microbiology (medical)
  • Virology
  • Infectious Diseases

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