Key Dates

Related Announcements

None

Issued by

National Heart, Lung, and Blood Institute (NHLBI)

Purpose

On behalf of the National Heart, Lung, and Blood Institute (NHLBI) and NIH, Office of the Director, this Notice is a time-sensitive Request for Information (RFI) inviting comments and suggestions on a proposal for a trans-NIH research initiative. This new initiative aims to support the development of novel research approaches, tools, technologies, and informative biomarkers or biosignatures, and/or social and behavioral factors that enable the identification of patients or patient populations susceptible to developing post-acute-sequelae of SARS-CoV-2 infection (PASC). Toward this end, the NIH is seeking input on approaches, tools, technologies, and/or biomarkers with potential to:

• Predict susceptibility of individuals to long-term sequelae of Coronavirus Disease 2019 (COVID-19).
• Predict longitudinal disease trajectory beyond acute exposure and/or infection.
• Identify patients or populations susceptible to long-term sequelae of COVID-19 that can receive early and appropriate clinical interventions to prevent PASC and hasten or optimize recovery from PASC.
• Identify patients or populations susceptible to severe COVID-19 as early as possible (e.g. at the time of initial diagnosis of COVID-19 or first SARS-CoV-2 positive test) to allow for early and appropriate clinical interventions to prevent acute and chronic severe COVID and to hasten or optimize recovery from COVID, and with potential application to identify patients or populations susceptible to developing PASC at early onset of COVID-19.
• Identify potential risk factors for developing severe COVID-19 that may be used to develop a PASC risk prediction model and predict patient susceptibility for developing PASC.
• Identify representative data on such risk factors and susceptibilities across the life span, social determinants, diverse patient populations, health status, and/or other contributing factors that ultimately predispose to PASC.

The information obtained will help advance the detection, prevention and treatment of PASC in numerous ways, including enhancing our scientific and clinical understanding of mechanisms of disease, risk factors, and susceptibility (genetic and acquired) to long-term sequelae of SARS-CoV-2 exposure and infection.

Background

While the long-term effects of COVID-19 have yet to be fully realized, new evidence is emerging that provides some indication of the sequelae of COVID-19. However, a clear understanding of who will experience these lingering symptoms, why they develop (e.g., their pathogenesis and mechanism of action), and course of onset and evolution to enable early detection is not yet available. Additionally, the spectrum of COVID-19 disease severity ranges from asymptomatic individuals to those hospitalized with life-threatening illness. It remains unclear whether the mechanisms driving the development of long-term sequelae from the initial acute infection differ according to disease severity. 

To address this knowledge gap and inform future avenues of scientific inquiry, NIH intends to support development of approaches, tools, technologies, informative biomarkers or biosignatures, and/or social and behavioral factors that can be used to identify people with susceptibility to, or risk factors, for PASC. NIH will use the information submitted in response to this RFI at their discretion.

Scope and Intended Use of Potential Technologies and Approaches that can Identify Individuals Susceptible to Developing PASC:

Identification of potential biomarker/biosignature candidates for detection and monitoring by unique testing approaches could rely on promising data from ongoing natural history studies.These approaches could include novel testing or other strategies and technologies (e.g., prognostic biomarkers and/or biosignatures) used alone or in combination (e.g.,suite of biomarkers, artificial intelligence [AI] and machine learning (ML)-based algorithms, digital biomarkers) to rapidly diagnose, characterize, accurately risk-stratify,and predict longitudinal disease severity throughout exposure and/or infection and throughout the course of illness. These approaches, strategies, tools, and technologies may lead to accurate and reliable devices and/or algorithms to facilitate treatment decisions for COVID-19 and could build on existing efforts to prevent, mitigate, or treat the following:

• Moderate to severe or life-threatening symptoms or conditions (e.g., decreased O₂ saturation) in acute disease due to index infection.
• Post-Acute Sequelae of SARS-CoV-2 Infection (PASC)–cases of symptoms or conditions that linger for weeks or months after an initial infection or that newly emerge after COVID-19. The CDC has developed a list of serious complications that have been reported for PASC and include:

• Cardiovascular: myocardial inflammation, ventricular dysfunction 
• Respiratory: pulmonary function abnormalities 
• Renal: acute kidney injury 
• Neurological: olfactory and gustatory dysfunction, sleep dysregulation, altered cognition, memory impairment, autonomic dysregulation
• Psychiatric: depression, anxiety, changes in mood 
• Dermatologic: rash, alopecia
• General: fatigue

Research on long-term consequences of COVID-19 is growing, including work to study the underlying pathology, consequences, and sequelae, as well as to develop rehabilitation strategies for patients. However, significant gaps in knowledge still exist.

Information Requested

In coordination with NIH research activities on post-acute sequelae of SARS-CoV-2infection (PASC), NIH seeks input from the biomedical research community, small businesses, and other interested organizations and stakeholders on novel prognostic strategies and technologies which could be developed and employed to identify and validate prognostic biomarkers and/or biosignatures that can be used to:

• Predict susceptibility of individuals to long-term consequences of COVID-19.
• Predict susceptibility of individuals to severe COVID-19 disease.
• Predict longitudinal disease trajectory throughout exposure and/or infection and throughout the course of illness.
• Develop point-of-care (POC) diagnostic devices for PASC to quickly identify susceptible populations that can receive early and appropriate clinical interventions.

NIH seeks comments on any or all the following topics (where applicable, please include pertinent references and/or names of key experts):

Potential Biomarkers and Risk Factors

This RFI refers to prognostic biosignatures which are used to identify the likelihood of a clinical event, disease recurrence or progression. Predictive biomarkers and biosignatures used to identify individuals likely to respond to a treatment, and diagnostic biomarkers and biosignatures used to confirm the presence of a disease, are not the subject of this RFI.

• Pathophysiologic pathways of PASC.
• Pathophysiologic pathways of severe COVID-19.
• Biomarkers that have the potential to help determine the onset and course of PASC.
• Biomarkers that have the potential to help determine onset and course of severe COVID-19.
• Risk factors that have the potential to help determine onset and course of PASC.
• Risk factors that have the potential to help determine onset and course of severe COVID-19.

Potential Available Data and Resources

• In addition to the RECOVER Cohorts, N3C, etc., please provide information about ongoing studies aimed at understanding the pathophysiology of PASC (or severe COVID-19 that could be applied to PASC) and key opinion leaders in this space.
• Data resources (basic science or clinical) and data-driven approaches being used to support the identification and measurements of informative biomarkers/biosignatures and risk factors for PASC (or severe COVID-19 that could be applied to PASC).
• Infrastructure and resources for AI/ML application and research using electronic health record (EHR) and other types of data (e.g., genomics, imaging, social determinants of health) to address health disparities and advance health equity of underrepresented groups.

Potential Technologies and Approaches

• Promising prognostic technologies or approaches that can identify the likelihood of developing PASC.
• Important considerations for preclinical development, including experimental verification and validation, of technologies and approaches intended to assist in the prediction of susceptibility for developing PASC and/or severity of COVID-19.
• Potential limitations in the development and clinical validation of relevant prognostic technologies.
• Biosamples that are important now and likely in the future to support preclinical development and clinical validation of prognostic technologies intended to identify the likelihood of developing PASC and/or severe COVID-19.
• Development and use of digital health technologies and digital biomarkers (e.g., wearable sensors and their underlying algorithms) that can identify the likelihood of developing PASC and/or severe COVID-19.
• Use of AI/ML for health disparities and inequities research to predict susceptibility to developing PASC and/or severe COVID-19 in diverse population.

How to Submit a Response

All responses to this RFI must be submitted electronically by August 27, 2021 to the following webpage: https://rfi.grants.nih.gov/?s=60e47d0b110b0000f70030d2.
 

Responses to this RFI are voluntary and may be submitted anonymously. Please do not include any personally identifiable or other information that you do not wish to make public. Proprietary, classified, confidential, or sensitive information should not be included in responses. The Government will use the information submitted in response to this RFI at its discretion. The Government reserves the right to use any submitted information on public websites, in reports, in summaries of the state of the science, in any possible resultant solicitation(s), grant(s), or cooperative agreement(s), or in the development of future funding opportunity announcements. This RFI is for informational and planning purposes only and is not a solicitation for applications or an obligation on the part of the Government to provide support for any ideas identified in response to it. Please note that the Government will not pay for the preparation of any information submitted or for use of that information.

We look forward to your input and hope that you will share this RFI document with your colleagues.

Inquiries

Please direct all inquiries to:

Orlando Lopez, PhD
National Institute of Dental and Craniofacial Research (NIDCR)
Telephone: (301) 402-4243
Email: orlando.lopez@nih.gov

Ivonne H. Schulman, MD
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Telephone: (301) 385-5744
Email: ivonne.schulman@nih.gov