R01DK140795
Project Grant
Overview
Grant Description
High-resolution, virome-wide infection analysis in type 1 diabetes birth cohorts - project abstract/summary
Type 1 diabetes (T1D) affects >20 million people globally, causing life-long dependency on exogenous insulin and reduced life expectancy.
Although the disease has a strong genetic basis, a substantial fraction of risk is not explained by genetic factors alone, and neither is the marked increase in T1D incidence over recent decades.
The identification of environmental determinants of T1D is important because it can reveal underlying mechanisms of pathogenesis and highlight intervention strategies that may be developed and/or deployed for high-risk subjects.
While infection by particular viruses has long been postulated as a risk factor for T1D, prior studies in this area have been limited in their power and/or breadth, with many investigating relatively small cross-sectional cohorts.
Large, prospective, longitudinal studies – including TEDDY (in the US / Europe) and ENDIA (in Australia) – offer opportunities to overcome these limitations, however existing viral analyses of these cohorts have so far been limited in their resolution (focused on infections defined symptomatically) and/or sensitivity (relying on the direct detection of viruses at the time/site of infection).
In this project, we will overcome these limitations by using an innovative technology (“PEPSEQ”) to perform a first-in-class, longitudinal, virome-wide serology-based analysis of the TEDDY and ENDIA cohorts.
PEPSEQ uses programmable, highly-multiplexed libraries of DNA-barcoded peptides to enable virome-wide serology at epitope-level resolution.
We recently showed that PEPSEQ can be combined with longitudinal sampling and an innovative analysis algorithm (PSEA) to enable the detection of temporally-resolved, virome-wide infection events at subspecies resolution.
Building directly on this work, we will use PEPSEQ+PSEA to study ~14,000 longitudinal plasma samples from TEDDY+ENDIA case/control subjects and comprehensively catalog the timing and identity of viral infection events.
We will begin by extending our existing PEPSEQ human virome library (which is already capable of subspecies resolution) to enable highly-controlled comparisons across ~600-700 virus subtypes (Aim 1).
Next, we will test whether and when these viruses are associated with autoimmunity in cases vs. matched controls, using selected longitudinal samples from (i) the first year of life, (ii) the year preceding the onset of T1D/IA, and (iii) mothers during pregnancy.
Overall, our approach combines the power of longitudinal sampling (to establish a temporal link with autoimmunity), the sensitivity of serology (to detect infections across all body sites) and the breadth and resolution of PEPSEQ (using 10,000s of peptides to address the virome comprehensively and at subspecies resolution).
Together, these innovations have the potential to reveal viral associations with autoimmunity that could not have been detected with previous, less powered approaches.
Moreover, by generating the largest known longitudinal dataset of virome-wide, subtype-resolved infection events in two highly-characterized birth cohorts, this project will enable future studies focused on the natural history and consequences of viral infections during ontogeny.
Type 1 diabetes (T1D) affects >20 million people globally, causing life-long dependency on exogenous insulin and reduced life expectancy.
Although the disease has a strong genetic basis, a substantial fraction of risk is not explained by genetic factors alone, and neither is the marked increase in T1D incidence over recent decades.
The identification of environmental determinants of T1D is important because it can reveal underlying mechanisms of pathogenesis and highlight intervention strategies that may be developed and/or deployed for high-risk subjects.
While infection by particular viruses has long been postulated as a risk factor for T1D, prior studies in this area have been limited in their power and/or breadth, with many investigating relatively small cross-sectional cohorts.
Large, prospective, longitudinal studies – including TEDDY (in the US / Europe) and ENDIA (in Australia) – offer opportunities to overcome these limitations, however existing viral analyses of these cohorts have so far been limited in their resolution (focused on infections defined symptomatically) and/or sensitivity (relying on the direct detection of viruses at the time/site of infection).
In this project, we will overcome these limitations by using an innovative technology (“PEPSEQ”) to perform a first-in-class, longitudinal, virome-wide serology-based analysis of the TEDDY and ENDIA cohorts.
PEPSEQ uses programmable, highly-multiplexed libraries of DNA-barcoded peptides to enable virome-wide serology at epitope-level resolution.
We recently showed that PEPSEQ can be combined with longitudinal sampling and an innovative analysis algorithm (PSEA) to enable the detection of temporally-resolved, virome-wide infection events at subspecies resolution.
Building directly on this work, we will use PEPSEQ+PSEA to study ~14,000 longitudinal plasma samples from TEDDY+ENDIA case/control subjects and comprehensively catalog the timing and identity of viral infection events.
We will begin by extending our existing PEPSEQ human virome library (which is already capable of subspecies resolution) to enable highly-controlled comparisons across ~600-700 virus subtypes (Aim 1).
Next, we will test whether and when these viruses are associated with autoimmunity in cases vs. matched controls, using selected longitudinal samples from (i) the first year of life, (ii) the year preceding the onset of T1D/IA, and (iii) mothers during pregnancy.
Overall, our approach combines the power of longitudinal sampling (to establish a temporal link with autoimmunity), the sensitivity of serology (to detect infections across all body sites) and the breadth and resolution of PEPSEQ (using 10,000s of peptides to address the virome comprehensively and at subspecies resolution).
Together, these innovations have the potential to reveal viral associations with autoimmunity that could not have been detected with previous, less powered approaches.
Moreover, by generating the largest known longitudinal dataset of virome-wide, subtype-resolved infection events in two highly-characterized birth cohorts, this project will enable future studies focused on the natural history and consequences of viral infections during ontogeny.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Phoenix,
Arizona
850042274
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 172% from $1,281,272 to $3,488,730.
Translational Genomics Research Institute was awarded
Virome-Wide Infection Analysis for Type 1 Diabetes Birth Cohorts
Project Grant R01DK140795
worth $3,488,730
from the National Institute of Diabetes and Digestive and Kidney Diseases in June 2024 with work to be completed primarily in Phoenix Arizona United States.
The grant
has a duration of 3 years and
was awarded through assistance program 93.847 Diabetes, Digestive, and Kidney Diseases Extramural Research.
The Project Grant was awarded through grant opportunity Collaborative Research Using Biosamples from Type 1 Diabetes Clinical Studies (R01 - Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 6/22/26
Period of Performance
6/1/24
Start Date
5/31/27
End Date
Funding Split
$3.5M
Federal Obligation
$0.0
Non-Federal Obligation
$3.5M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01DK140795
Additional Detail
Award ID FAIN
R01DK140795
SAI Number
R01DK140795-3703279235
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75NK00 NIH National Institute of Diabetes and Digestive and Kidney Diseases
Funding Office
75NK00 NIH National Institute of Diabetes and Digestive and Kidney Diseases
Awardee UEI
J19ZXYATJLT3
Awardee CAGE
3EKD9
Performance District
AZ-03
Senators
Kyrsten Sinema
Mark Kelly
Mark Kelly
Modified: 6/22/26