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Issued by

National Institute of Allergy and Infectious Diseases (NIAID)

Purpose

This Request for Information (RFI) invites comments and suggestions regarding the application of state-of-the-art sampling and analysis techniques to identifying immunologic events underlying the onset, flare, remission, and progression of autoimmune diseases.

Background

NIAID has an interest in determining the immunologic events during the period preceding a diagnosis of autoimmune disease as well as the events that precede flare or progression of autoimmune disease. Better understanding of these events could enable faster and more accurate diagnosis of disease, earlier and more personalized therapeutic decisions, and opportunities to delay disease or prevent onset of disease. The ability to study the pre-clinical period in humans, however, is hampered by a number of unknowns, including the precise exposures that trigger autoimmune diseases, the timing of those exposures, and the relatively low incidence of spontaneous autoimmune disease in the human population as a whole.

The existence of longitudinal sample collections has enabled significant progress in understanding the serological events that presage the onset of some autoimmune diseases (1-3). However, the sample collections used for these studies are not generally available to researchers and their applicability to other autoimmune diseases and other facets of the immune response is limited. Recent studies have indicated that autoimmune disease patients can perform minimally invasive self-sampling that is sufficient to describe relevant immune pathways in active autoimmune disease (4). This raises the possibility that a self-sampling approach in an at-risk cohort might be a viable approach to elucidating immunologic events in the pre-clinical period.

Information Requested

NIAID seeks input from the scientific research community on two broad topics:

1. The utility, feasibility, and potential approaches to establishing a cohort of subjects at risk of developing autoimmune diseases and obtaining longitudinal samples from this cohort to identify immunologic events that drive disease onset in a productive, cost-effective, and minimally invasive manner; and
2. The feasibility of, potential approaches to, and impact of studies of autoimmune disease patient cohorts to define immunologic events that drive flares and remissions.

Related to these two broad topics, please include comments regarding any or all these points of interest:

• Autoimmune diseases which exhibit the greatest need for better definition of the preclinical phase, diseases which are likely to yield the greatest impact from this type of study, and advances in understanding that are most likely achievable in any given disease;
• Autoimmune diseases which exhibit the greatest need for better definition of the flare-remission cycle, diseases which are likely to yield the greatest impact from this type of study, and advances in understanding that are most likely achievable in any given disease;
• Immunologic events, phenotypes, or trends that are most likely to be informative in understanding the preclinical and immediate pre-flare period;
• Size, composition, and characteristics of at-risk cohorts that are necessary to achieve the goal of defining key immunologic events leading to emergence of clinical autoimmune disease or preceding flares;
• Approaches to recruitment, retention, sampling (e.g., self-sampling vs. centralized sampling vs. a combined approach) and monitoring of these cohorts for development or worsening of autoimmune disease;
• Nature and frequency of samples that could be collected without interaction with investigators (e.g., at-home self-sampling) and the corresponding quality of immunologic information that could be extracted from such samples;
• Challenges and limitations in assessing cellular immune responses from self-collected samples, priorities that should be assigned when studying these samples, and advances in sample procurement, shipping, processing, storage, and analysis that may be possible now or in the near future to aid studies of this nature;
• Frequency of sampling and of clinical monitoring appropriate for different autoimmune diseases, considering the rate at which at-risk subjects convert to frank disease and the time lag between sampling and diagnosis;
• Means for guiding participants to seek appropriate and timely care should symptoms of autoimmune disease develop during the study period; and
• Other topics relevant to efforts to elucidate the immunology of the preclinical phase and flare-remission cycles of autoimmune diseases.

How to Submit a Response

Responses to this RFI must be submitted electronically to: [email protected]

Responses must be received by March 15, 2021.

Responses to this RFI are voluntary. Do not include any proprietary, classified, confidential, trade secret, or sensitive information in your response. The responses will be reviewed by NIAID staff, and individual feedback will not be provided to any responder. 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 NIH 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 information and planning purposes only and shall not be construed as a solicitation, grant, or cooperative agreement, or as an obligation on the part of the Federal Government, the NIH, or individual NIH Institutes and Centers to provide support for any ideas identified in response to it. The Government will not pay for the preparation of any information submitted or for the Government’s use of such information. No basis for claims against the U.S. Government shall arise as a result of a response to this request for information or from the Government’s use of such information.

Citations

1. Sokolove J, Bromberg R, Deane KD, Lahey LJ, Derber LA, Chandra PE, Edison JD, Gilliland WR, Tibshirani RJ, Norris JM, Holers VM, Robinson WH. Autoantibody epitope spreading in the pre-clinical phase predicts progression to rheumatoid arthritis. PLoS One. 2012;7(5):e35296. doi: 10.1371/journal.pone.0035296. Epub 2012 May 25. Erratum in: PLoS One.doi: 10.1371/annotation/2e462817-ab93-4d78-95a4-1d8b9d172971. PMID: 22662108; PMCID: PMC3360701.

2. Munroe ME, Young KA, Kamen DL, Guthridge JM, Niewold TB, Costenbader KH, Weisman MH, Ishimori ML, Wallace DJ, Gilkeson GS, Karp DR, Harley JB, Norris JM, James JA. Discerning Risk of Disease Transition in Relatives of Systemic Lupus Erythematosus Patients Utilizing Soluble Mediators and Clinical Features. Arthritis Rheumatol. 2017 Mar;69(3):630-642. doi: 10.1002/art.40004. PMID: 27863174; PMCID: PMC5329053.

3. Ferrat LA, Vehik K, Sharp SA, Lernmark Å, Rewers MJ, She JX, Ziegler AG, Toppari J, Akolkar B, Krischer JP, Weedon MN, Oram RA, Hagopian WA; TEDDY Study Group; Committees. A combined risk score enhances prediction of type 1 diabetes among susceptible children. Nat Med. 2020 Aug;26(8):1247-1255. doi: 10.1038/s41591-020-0930-4. Epub 2020 Aug 7. PMID: 32770166; PMCID: PMC7556983.

4. Orange DE, Yao V, Sawicka K, Fak J, Frank MO, Parveen S, Blachere NE, Hale C, Zhang F, Raychaudhuri S, Troyanskaya OG, Darnell RB. RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares. N Engl J Med. 2020 Jul 16;383(3):218-228. doi: 10.1056/NEJMoa2004114. PMID: 32668112; PMCID: PMC7546156.

Inquiries

Please direct all inquiries to:

Thomas R. Esch, Ph.D.
National Institute of Allergy and Infectious Diseases (NIAID)
Telephone: 240-627-3565
Email: [email protected]