Leveraging Research Resources to Accelerate Innovation and Improve Rigor for Chronic and Comorbid Disease Research and Discovery

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Topic Description

Post Date: September 16, 2026

Expiration Date: September 16, 2028

As described in a recent NIH Nexus post on biorepositories, the National Institutes of Health (NIH) have made substantial investments in large-scale clinical consortia, longitudinal cohorts, and repositories that have generated rich, multidimensional datasets spanning clinical, imaging, multi-omics, environmental data, and patient-reported outcomes, as well as accompanying high-quality biospecimens.

These resources, including biospecimens and data, have been systematically generated and curated using highly standardized, quality-controlled protocols through coordinated efforts. As a result, they are expected to offer substantially greater statistical power and scientific rigor than smaller, independent studies.

 While primary analyses have yielded important findings, advancing our understanding of the etiology and pathogenesis of many chronic diseases, much of the scientific potential of these data and samples remains untapped. Moreover, the complex interplay of comorbid conditions, genetic susceptibility, environmental triggers, and immune dysregulation in many diseases presents challenges that may not be addressed by individual studies.

The availability of unique, high-quality, well-characterized data and biospecimens, complemented by recent advances in artificial intelligence and machine learning (AI/ML) and other cutting-edge tools and methods, presents a timely and unprecedented opportunity to:

  • Validate and replicate previously reported findings;
  • uncover novel disease mechanisms;
  • identify disease subtypes and druggable pathways;
  • improve risk prediction;
  • model disease progression and treatment response; and 
  • develop holistic approaches to health for people with multiple chronic conditions.

 

Purpose: 

This topic identifies specific existing repositories, datasets, and programs, produced by large-scale clinical consortia, longitudinal cohorts, and repositories, that the NIH encourages the scientific community to leverage for the generation of new insights into disease mechanisms, prevention, diagnosis, and treatment. These resources may be useful for: 

  • Clinical validation of hypotheses and algorithms for clinical decision-making;
  • Efforts that leverage these foundational resources by linking programs and harmonizing datasets to better characterize chronic conditions and uncover shared and distinct underlying mechanisms across diseases;
  • Advancing development of prognostic variables, biomarkers, therapeutics, and precision medicine;
  • Development and application of data science and AI/ML tools to predict disease progression and outcomes; 
  • Multimodal AI approaches that integrate diverse data types (e.g., ‘omic, imaging, clinical, environmental, and patient-reported data) to achieve a comprehensive understanding of patient health; and
  • Generation of synthetic clinical data and cohorts to support data sharing, method development, and benchmarking, while preserving patient privacy and mitigating risks associated with sensitive human data.
This topic is being issued as part of the Make America Healthy Again initiative, which is expanding NIH and agency research into specific areas.

It aligns with:

  • NIH MAHA Chronic Disease Initiative : The National Institutes of Health (NIH) will launch an Initiative on Chronic Disease to leverage and align existing NIH research projects, improve NIH coordination on chronic disease research, and generate actionable results for diseases arising in childhood and adulthood.
  • NIH MAHA Chronic Disease Initiative : The NIH will launch a new Whole-Person-Health approach to chronic disease prevention research and leverage collective expertise across the agency to catalyze transformative discovery science and intervention strategies that promote wellness, resilience, and optimal health, including metabolic health, at all stages of life.
  • Longitudinal Research for Chronic Disease Prevention : The NIH will leverage its extensive portfolio of longitudinal birth cohort data, including the Adolescent Brain Cognitive Development Study, Healthy Brain and Child Development Study, All of Us Research Program, and Environmental Influences on Child Health Outcomes Program to deepen our understanding of chronic disease at various stages of life by elucidating root causes, identifying modifiable risk factors, and uncovering effective prevention strategies. Examples of new research initiatives will include the importance of sleep and nutrition, health impacts of insulin resistance, potential health benefits of select high-quality supplements, and using fitness as a vital sign.
  • Artificial Intelligence : HHS, NIH, and the Office of Science and Technology Policy will develop an evidenced-based and AI-driven approach to harnessing the data and technology available to transform research and clinical trials on pediatric cancer. This can be a model for future research in other critical areas.

Participating ICOs

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

NIDDK prioritizes studies that accelerate scientific research in its mission areas that leverage existing samples and/or data from past and ongoing NIDDK studies. Resources of interest include but are not limited to:

  • The NIDDK Central Repository: from clinical trials and clinical research consortia
    • Multimodal data (clinical, imaging, genomic, metabolomic, survey, mHealth/wearables)
    • Biospecimens  
    • Example: Samples and data from the Type 1 Diabetes TrialNet and The Environmental Determinants of Diabetes in the Young (TEDDY) studies
  • The Kidney Precision Medicine Project (KPMP) Kidney Tissue Atlas
    • Whole slide images, segmentation masks, multi-omic data, and plasma and urine biomarkers 
  • NIH repositories that host genomic and multi-omic data from NIDDK studies include:  
    • database of Genotypes and Phenotypes (dbGaP)
    • Gene Expression Omnibus (GEO) 
    • Metabolomics Workbench
IC may dedicate funds available to support applications in this Topic area depending upon the availability of funds, the number of meritorious applications, and competing ICO priorities.
IC may give special consideration to support meritorious applications in this topic area.
ICO Scientific Contact:
Beena Akolkar, Ph.D., Division of Diabetes, Endocrinology, and Metabolism
[email protected]

Daniel Gossett, Ph.D., Division of Kidney, Urology, and Hematology
[email protected]

Ludmila Pawlikowska Ph.D., Division of Digestive Diseases and Nutrition
[email protected]

Rebecca Rodriguez, Ph.D., M.S., NIDDK Central Repository
[email protected]

Emily Leary, Ph.D., NIDDK Biostatistics Program
[email protected]

National Eye Institute (NEI)

NEI supports vision research, including work on chronic and comorbid diseases shaped by genetics, lifestyle, demographics, and environment. NEI encourages investigators to leverage existing resources to uncover mechanisms of eye disease onset, progression, and treatment response.

Example resources:

  • All of Us integrated health datasets 
  • ‘Omics data (Database of Genotypes and Phenotypes [dbGaP], Gene Expression Omnibus [GEO], Metabolomics Workbench)
  • Eye disease data sets (EyeGene, NEI Data Commons, Biomedical Research Informatics Computing System [BRICS], Jaeb Center for Health Research)
  • Comorbid disease data and specimens (NIDDK’s Epidemiology of Diabetes Interventions and Complications [EDIC] study)
  • Phenotypic/molecular databases for model organisms (Mouse Genome Informatics [MGI], Zebrafish Information Network [ZFIN], Flybase)
  • Tissue biobanks (Human Tissues and Organs for Research Resource [HTORR])
  • New York Stem Cell Foundation induced Pluripotent Stem Cell (iPSC) Repository 
ICO Scientific Contact:
Tiffany Cook, Ph.D.
[email protected]

National Institute on Aging (NIA)

NIA promotes research to understand the nature of aging and extend healthy, active years of life. NIA supports genetic, biological, clinical, behavioral, social, and economic research on aging and geroscience (chronic conditions, Alzheimer’s Disease and related dementias emphasized).

Appropriate resources include (but are not limited to): 

  • the AgingResearchBiobank ; 
  • rodent and nonhuman primate tissue banks; 
  • interventions testing programs; and 
  • population-representative, epidemiological, and deeply-phenotyped longitudinal studies.

Applications may:

  • Explore changes across the human lifespan affecting risk of age-related diseases/conditions and appropriate therapeutic targets/interventions.
  • Identify fundamental biological mechanisms through comparative analysis and biospecimens from model organism studies.
  • Use data integration methods to leverage existing resources and  generate insights into life course processes unavailable from individual datasets.
ICO Scientific Contact:
Rosaly Correa-de-Araujo, MD, MSc, PhD, Division of Geriatrics and Clinical Gerontology (for AgingResearchBiobank)
[email protected]

Tiziana Cogliati, PhD, Division of Aging Biology (NIA tissue banks, Intervention Testing Programs (ITPs), Caenorhaabditis ITP)
[email protected]

Damali Martin, PhD, Division of Neuroscience (NIA Genetics of Alzheimer’s Disease Data Storage Site, Precision Aging Network)
[email protected]

Minki Chatterji, PhD, Div of Behavioral Science Research (Health and Retirement Study, National Health and Aging Trends Study)
[email protected]

Amelia Karraker, PhD, Div of Behav Sci Res (Health and Retirement Study, Natnl Longitudinal Study of Adolescent to Adult Health)
[email protected]

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

NIAMS prioritizes studies that accelerate scientific research in its mission areas and that leverage existing resources from past and ongoing NIAMS studies. Examples include but are not limited to studies that:

  • Leverage existing datasets, repositories, and biobanks supported by NIAMS and other sources to maximize the scientific value of previously collected data and biospecimens, such as:
    • The Accelerating Medicines Partnership (AMP) portals
    • The Molecular Transducers of Physical Activity Consortium (MoTrPAC) Data Hub
    • Osteoarthritis Initiative data from the NIMH Data Archive
    • The Archiving and Sharing Skeletal Phenotyping Data Project
    • The Skin Condition Image Network (SCIN) Dataset
    • The All of Us Research Program
    • NIH genomic and multi-omic data repositories from NIAMS studies or relevant to NIAMS diseases
  • Foster cross-disease studies to identify shared biological pathways, comorbidities, and mechanisms
  • Advance biomarker, therapeutic target, and risk model development
ICO Scientific Contact:
Jana Eisenstein, M.S.
[email protected]

National Institute of Dental and Craniofacial Research (NIDCR)

NIDCR prioritizes investigator-initiated research that accelerates discovery in dental, oral, and craniofacial (DOC) health and disease. NIDCR supports studies that advance understanding of disease mechanisms, improve risk prediction and precision care, and identify shared biological pathways linking oral and craniofacial conditions with chronic diseases. NIDCR encourages projects that leverage mission-specific data and/or biospecimens from past or ongoing NIDCR studies. The NIDCR Data Driven Science (DDS) Hub highlights many resources including, but not limited to:

  • FaceBase, 
  • the National Dental Practice-Based Research Network (National Dental PBRN), 
  • the Human Oral Microbiome Database, 
  • the Human Salivary Proteome, and 
  • the Sjögren’s International Collaborative Clinical Alliance (SICCA). 

These resources provide multi-omic, imaging, clinical, genomic, microbial, proteomic, and biospecimen data to advance research on disease mechanisms, risk prediction, and precision care.

IC may give special consideration to support meritorious applications in this topic area.
ICO Scientific Contact:
NIDCR Division of Extramural Research
[email protected]

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