Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease

Author:

Ward Rebecca A1ORCID,Aghaeepour Nima234,Bhattacharyya Roby P15,Clish Clary B5ORCID,Gaudillière Brice23ORCID,Hacohen Nir56,Mansour Michael K17,Mudd Philip A8ORCID,Pasupneti Shravani910ORCID,Presti Rachel M1112ORCID,Rhee Eugene P13,Sen Pritha15714,Spec Andrej11ORCID,Tam Jenny M715ORCID,Villani Alexandra-Chloé5714ORCID,Woolley Ann E16,Hsu Joe L910,Vyas Jatin M17ORCID

Affiliation:

1. Division of Infectious Disease, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA

2. Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA

3. Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA

4. Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, California, USA

5. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

6. Cancer for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

7. Harvard Medical School, Boston, Massachusetts, USA

8. Department of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri, USA

9. Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA

10. Veterans Affairs Palo Alto Health Care System, Medical Service, Palo Alto, California, USA

11. Division of Infectious Diseases, Department of lnternal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA

12. Center for Vaccines and Immunity to Microbial Pathogens, Washington University School of Medicine, St. Louis, Missouri, USA

13. The Nephrology Division and Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA

14. Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA

15. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA

16. Division of Infectious Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

Abstract

Abstract The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in “omics” technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Oncology

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