The vast amounts of data generated through NIH-funded biomedical research together with exponential advances in computing technology and power provide a unique moment of opportunity to use data science, AI/ML, and computational biology to cultivate knowledge and improve treatments. NIAMS also recognizes the critical importance of data sharing, stewardship, and quality assurance efforts in moving biomedicine forward as the institute implements the NIH Data Management and Sharing Policy.
NIAMS is committed to advancing its mission by supporting the generation, identification, storage, and sharing of individual high-value datasets and leveraging ongoing initiatives to better integrate clinical and observational data into biomedical data science. Analysis of these data to inform methods of improving patient outcomes is paramount, and efforts to develop, validate, and explore the use of AI/ML in the context of preclinical research, clinical research, and clinical practice to increase efficiency and accelerate advances that benefit patients are also encouraged. Furthermore, investigators should consider incorporating innovative use of computational biology methods in basic biology research and integrating these methods into mechanistic clinical trials to inform the use of patient-specific therapeutics for people who have arthritis or who have musculoskeletal or skin diseases across their lifespan.
NIAMS strongly supports responsible stewardship of data and technology. The institute holds its researchers to the highest standard to ensure that AI/ML approaches are used appropriately for NIAMS-funded studies and that data remain secure. Research should be guided by TRUST (transparency, responsibility, user focus, sustainability, and technology), and the data generated should adhere to FAIR principles (findability, accessibility, interoperability, and reusability), as well as data diversity, statistical, privacy, reporting, and open access standards. NIAMS also is interested in forming partnerships to develop, sustain, and strengthen an inclusive, interdisciplinary data science workforce for NIAMS-focused research. This can include promoting innovative collaborations between biomedical data science and other fields of study, such as mathematics, statistics, computer science, engineering, physics, and biology, to facilitate data-driven discoveries.
Examples under this topic include the following.
Strategy 3.1: Using Existing Resources and Technologies
- Forming partnerships to leverage datasets produced by studies on conditions within the purview of other NIH components, such as aging, cardiovascular disease, or diabetes, for the study of diseases of interest to NIAMS.
- Fostering collaborations among researchers so that they can leverage datasets from different sites to increase a study’s sample size, thereby improving their ability to address crucial research questions related to NIAMS-specific diseases.
- Mining large datasets, including clinical genetic test data and genomic data, to identify patients with undiagnosed rare diseases or treatable common diseases of interest to NIAMS to improve access to care.
- Using data science approaches to explore the bidirectional interactions between systemic factors and the musculoskeletal system and skin in health and disease.
- Integrating computational biology methods into clinical trials to inform the use of patient-specific therapeutics for diseases covered by the NIAMS mission across the lifespan.
Strategy 3.2: Improving Resources and Technologies
- Integrating and cross-annotating various omics datasets developed by the research community for human bone, joint, muscle, and skin tissues.
- Improving the collection and use of patient-reported electronic health records in studies of diseases of interest to NIAMS and their treatments via innovative approaches such as natural language processing.
- Integrating multidimensional human data, from molecular and cellular to population levels, so they can be integrated into studies to reduce the burden of diseases within NIAMS’ mission areas.
- Exploring the use of AI/ML tools to improve the conduct of clinical trials and patient care.
Strategy 3.3: Creating Resources and Technologies
- Developing and validating Common Data Elements in diverse populations and conditions related to the NIAMS mission to address biological and behavioral mechanisms that are driving outcomes.
- Developing and validating clinical support tools that integrate polygenic risk scores with demographic and clinical data to predict the development and progression of diseases covered by the NIAMS mission.
- Developing and validating deep learning-based imaging technologies for accelerated image reconstruction and tissue segmentation for early diagnosis of NIAMS-relevant diseases.
The Arthritis and Autoimmune and Related Diseases Knowledge (ARK) Portal
The Accelerating Medicines Partnership® (AMP®) program generates robust molecular, cellular, and clinical datasets as well as analytical tools, technologies, and protocols. To house the data generated from the AMP RA/SLE program, as well as a broad and diverse portfolio of datasets related to arthritis, autoimmune, skin, and related diseases, NIAMS created the ARK Portal. Directed by NIAMS and developed and maintained by Sage Bionetworks, this searchable knowledge portal is designed to facilitate public data interrogation and foster research. The ARK Portal is a public access repository that accumulates, organizes, and links core datasets generated by a network of research teams working collaboratively to deepen the understanding of arthritis and autoimmune and related diseases. Access to the datasets on the portal is free to the public and will stimulate further research in these disease areas.
Extramural Researchers Develop Integrated Databases and Artificial Intelligence-Based Resources for Skin Multi-omics and Cell Signaling
NIAMS-funded researchers have developed an interactive, searchable Hair Gene Expression Library database (hair-gel.net) that offers sequencing information on the stem cells and niche cells that interact to build hair follicles. The investigators developed this resource by using next-generation RNA-sequencing to compare transcriptomes in embryonic skin cells and uncovered hundreds of genes that are active as skin develops, including those that guide the formation of hair follicles. The research community can query any gene of interest to see if it is present and specifically expressed in any one of the distinct cell types that compose embryonic skin.
Inspired by this innovative approach to data sharing, another team of NIAMS-supported researchers generated SkinRegeneration.org. This searchable web resource allows others to query and investigate large databases of single‐cell RNA sequencing information on scarring and regenerative tissues. Investigators populate the database with information from their work to transform fibroblasts in adult skin into cells with the same regenerative potential as their embryonic skin counterparts without the altered development and homeostasis that significantly impact human aging and wound healing.
Further, a multidisciplinary, multi-institutional team of NIAMS grantees constructed a database of interactions among various signaling ligands, receptors, and their cofactors to develop CellChat (www.cellchat.org), a novel tool to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing data. The readily available tool may help other researchers speed the discovery of new patterns and principles of intercellular communications and aide in the development of extensive atlases of cell-cell communication in diverse tissues and disease conditions.
Other Research Priorities
Mechanisms in Human Health and Disease
Research detailing basic biological functioning has led to effective approaches to health maintenance and to disease prevention, diagnosis, and treatment. Additional comprehensive research into molecular and cellular mechanisms is needed to further develop the knowledge base necessary for more targeted interventions.
Regenerative Medicine
Regenerative medicine as a field focuses on new approaches for treating injuries and diseases using stem cells and other technologies, such as engineered biomaterials and gene editing. Researchers work to repair or replace damaged or aged cells, tissues, or organs and aim to restore tissue or organ structure and function using tissue engineering and biologics.
Behaviors and Environmental Exposures
Determining how behaviors and environmental exposures affect the onset, severity, and responses to treatment of diseases within the NIAMS mission is crucial for improving the lives of all Americans.
Interventions
NIAMS will emphasize studies with notable potential to advance clinical management and the development of guidelines related to diseases within the NIAMS mission that are not likely to be funded by industry.
Health Disparities
NIAMS is dedicated to supporting research that will ultimately reduce or eliminate the disparity gaps in diseases and conditions within its mission, including development of approaches to enable access to health care that can contribute to every person’s ability to live long, healthy lives. Many of these diseases and conditions exhibit sex, racial, ethnic, and other disparities.