# Maintenance and Incidence of ME/CFS following Mono

> **NIH NIH R01** · DE PAUL UNIVERSITY · 2021 · $282,868

## Abstract

Abstract
Behavioral and pathophysiological underpinnings of the development of COVID-19 are poorly understood.
From 2014 through 2018, our research group collected psychological and biological data of 4,501 young
adults. We are currently funded to re-contact and interview these subjects regarding symptoms of ME/CFS.
This supplemental funding request would allow us to also collect data involving COVIDF-19 infection and
recovery vs nonrecovery from that infection as well. Using our baseline data, we will be able to compare the
biological and behavioral data of young adults prior to the epidemic and during the epidemic, we will be able to
compare those who became ill with COVID-19 and those who did not, to identify possible predisposing
characteristics and to determine those who fully recovered vs those who did not. We emphasize the urgent
nature of the request, as we will need to see these patients starting in June, July, and August. This cohort is
significant in our effort to identify risk factors predisposing patients to developing COVID-19, which may help
uncover underlying mechanisms of COVID-19. We believe our proposal addresses an urgent need for
research on “biological effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and
effects of COVID-19 on the nervous system”.

## Key facts

- **NIH application ID:** 10191581
- **Project number:** 3R01NS111105-02S1
- **Recipient organization:** DE PAUL UNIVERSITY
- **Principal Investigator:** Leonard A Jason
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $282,868
- **Award type:** 3
- **Project period:** 2020-01-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10191581

## Citation

> US National Institutes of Health, RePORTER application 10191581, Maintenance and Incidence of ME/CFS following Mono (3R01NS111105-02S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10191581. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*