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REVIEW article

Front. Syst. Biol.
Sec. Translational Systems Biology and In Silico Trials
Volume 4 - 2024 | doi: 10.3389/fsysb.2024.1422384
This article is part of the Research Topic Insights in Translational Systems Biology and In Silico Trials: 2023 View all 4 articles

A multi-omics strategy to understand PASC through the RECOVER cohorts: a Paradigm for a Systems Biology Approach to the Study of Chronic Conditions

Provisionally accepted
Jun Sun Jun Sun 1Masanori Aikawa Masanori Aikawa 2Hassan Ashktorab Hassan Ashktorab 3Noam D Beckmann Noam D Beckmann 4Mike L Enger Mike L Enger 5Joaquin M Espinosa Joaquin M Espinosa 6Xiaowu Gai Xiaowu Gai 7Benjamin D Horne Benjamin D Horne 8Paul S Keim Paul S Keim 9Jessica Lasky-Su Jessica Lasky-Su 2Rebecca Letts Rebecca Letts 10,5Cheryl L Maier Cheryl L Maier 11Meisha Mandal Meisha Mandal 5Lauren Nichols Lauren Nichols 10,5Nadia R Roan Nadia R Roan 12Mark W Russell Mark W Russell 13Jacqueline Rutter Jacqueline Rutter 10,5George R Saade George R Saade 14Kumar Sharma Kumar Sharma 15Stephanie Shiau Stephanie Shiau 16Stephen N Thibodeau Stephen N Thibodeau 17Samuel Yang Samuel Yang 8Lucio Miele Lucio Miele 18*
  • 1 University of Illinois Chicago, Chicago, Illinois, United States
  • 2 Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
  • 3 Howard University, Washington, D.C., United States
  • 4 Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • 5 RTI International, Durham, North Carolina, United States
  • 6 University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
  • 7 University of Southern California, Los Angeles, California, United States
  • 8 Stanford University, Stanford, California, United States
  • 9 Northern Arizona University, Flagstaff, Arizona, United States
  • 10 RECOVER patient representative, Durham, United States
  • 11 Emory University, Atlanta, Georgia, United States
  • 12 School of Medicine, University of California San Francisco, San Francisco, California, United States
  • 13 University of Michigan, Ann Arbor, Michigan, United States
  • 14 Eastern Virginia Medical School, Norfolk, Virginia, United States
  • 15 The University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States
  • 16 Rutgers University, Newark, Newark, New Jersey, United States
  • 17 Mayo Clinic, Rochester, Minnesota, United States
  • 18 Department of Genetics, LSU Health Sciences Center New Orleans, Louisiana State University, New Orleans, Louisiana, United States

The final, formatted version of the article will be published soon.

    Post-Acute Sequelae of SARS-CoV-2 infection (PASC or "Long COVID"), includes numerous chronic conditions associated with widespread morbidity and rising healthcare costs. PASC has highly variable clinical presentations, and likely includes multiple molecular subtypes, but it remains poorly understood from a molecular and mechanistic standpoint. This hampers the development of rationally targeted therapeutic strategies. The NIH-sponsored "Researching COVID to Enhance Recovery" (RECOVER) initiative includes several retrospective/prospective observational cohort studies enrolling adult, pregnant adult and pediatric patients respectively. RECOVER formed an "OMICS" multidisciplinary task force, including clinicians, pathologists, laboratory scientists and data scientists, charged with developing recommendations to apply cutting-edge system biology technologies to achieve the goals of RECOVER. The task force met biweekly over 14 months, to evaluate published evidence, examine the possible contribution of each "omics" technique to the study of PASC and develop study design recommendations. The OMICS task force recommended an integrated, longitudinal, simultaneous systems biology study of participant biospecimens on the entire RECOVER cohorts through centralized laboratories, as opposed to multiple smaller studies using one or few analytical techniques. The resulting multi-dimensional molecular dataset should be correlated with the deep clinical phenotyping performed through RECOVER, as well as with information on demographics, comorbidities, social determinants of health, the exposome and lifestyle factors that may contribute to the clinical presentations of PASC. This approach will minimize lab-to-lab technical variability, maximize sample size for class discovery, and enable the incorporation of as many relevant variables as possible into statistical models. Many of our recommendations have already been considered by the NIH through the peer-review process, resulting in the creation of a systems biology panel that is currently designing the studies we proposed. This system biology strategy, coupled with modern data science approaches, will

    Keywords: COVID - 19, PASC, Recover, Systems Biology, Multi-omics (Min.5-Max. 8

    Received: 23 Apr 2024; Accepted: 14 Oct 2024.

    Copyright: © 2024 Sun, Aikawa, Ashktorab, Beckmann, Enger, Espinosa, Gai, Horne, Keim, Lasky-Su, Letts, Maier, Mandal, Nichols, Roan, Russell, Rutter, Saade, Sharma, Shiau, Thibodeau, Yang and Miele. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Lucio Miele, Department of Genetics, LSU Health Sciences Center New Orleans, Louisiana State University, New Orleans, 70112, Louisiana, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.