March 6, 2023
PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
National Heart, Lung, and Blood Institute (NHLBI)
This Notice of Special Interest is a reissue of NOT-HL-21-017.
Background and Purpose:
The symptom-based diagnosis and treatment of heart, lung, blood, and sleep (HLBS) diseases has vastly improved in recent years, yet an understanding of the molecular mechanisms underlying many of these diseases has remained elusive. Furthermore, in most cases the impact of genetic variation on severity of disease and treatment outcomes remains unknown. Therefore, the NHLBI has created the Trans-omics for Precision Medicine (TOPMed) program, which aims to utilize genomics data to characterize a variety of HLBS diseases. TOPMed is well on its way to collecting whole genome sequence (WGS) from over 194,270 well-phenotyped individuals and is currently generating multi-omics data (e.g., over 31,852 RNA sequences, over 44,342 DNA methylation profiles, and 26,124 metabolomics profiles) from many of these individuals to complement whole genome sequence information.
Having produced an unprecedented volume of high-throughput data, TOPMed now seeks to turn its attention to effectively leveraging this resource to uncover biological function and disease pathobiology through novel systems biology analyses and the power of artificial intelligence (AI) and Machine Learning (ML). Although lower costs and technological improvements in sequencing technology have vastly expanded our ability to generate large volumes of omics data, the ability to analyze such large datasets to extract biologically meaningful insights remains challenging. Systems level models incorporating trans-omics analyses will be an important step in uncovering the underlying biological networks and the gene-gene and gene-environment interactions influencing disease and treatment outcomes. Thus, advanced analyses that incorporate genotype and phenotype datasets from thousands to tens of thousands of individuals are essential to move TOPMed to the next phase of discovery.
Research Objectives:
The trans-omics resource currently being built by the TOPMed program presents a unique set of challenges and opportunities for genomic analysis. Whole genome sequence coupled with expression and other deep clinical and molecular phenotyping data from tens of thousands of individuals promises to hold important information about rare and common genetic variants influencing disease. Several phases of data generation have brought together a collection of cohorts and studies that span a wide variety of HLBS diseases, geographic locations, and ancestries. More information about participating studies can be found at TOPMed program web site.
As this data resource gains maturity, analyses that effectively synthesize very large volumes of information from across many different datatypes remain scarce. NHLBI seeks to fund analyses and development of tools that utilize existing TOPMed omics data to uncover the molecular mechanisms driving HLBS disease. Investigators are encouraged to utilize a systems approach incorporating computational modeling to bring together high throughput genotype and phenotype datasets. Analyses may incorporate new or existing data generated outside of TOPMed. However, this Notice seeks studies that will use existing TOPMed data as the major resource for analyses of HLBS diseases and measures. TOPMed has particular interest in questions about identifying associations between variants and disease phenotypes, and in analyses using existing functional data to reveal associations and/or make functional inferences. Investigators are encouraged to use the ancestry diversity of TOPMed for discovery and not merely for replication of findings in a single ancestry group.
Grants funded under this initiative will have access to data via dbGaP and BioData Catalyst, including phenotype and genotype data from joint variant-call of all TOPMed WGS samples by the TOPMed Informatics Research Center (IRC). The transcriptomics, methylation, and metabolomics data are also released in dbGaP. Further information about the dbGaP data access application process can be found here: https://www.ncbi.nlm.nih.gov/books/NBK482114/#DArequest.would_you_give_me_a_stepbystep. Applicants are also highly encouraged to use the NHLBI BioData Catalyst platform, which provides tools, applications, and workflows for finding, accessing, sharing, storing, and computing on large-scale datasets in a secure cloud-based ecosystem. For applicants who propose to use BioData Catalyst, the NHLBI will provide cloud credits to help applicants test cloud computing in BioData Catalyst platform.
This Notice seeks to garner analysis of TOPMed data and facilitate data analysis tool development. Suggested research examples include, but are not limited to:
- Investigation of pleiotropic gene effects and gene expression patterns across several cardiovascular risk factors
- Identification of biomarkers (metabolites, genetic variants, and DNA methylation) related to the severity of outcomes in sickle cell patients
- Research using AI/ML/modeling approaches to determine likely areas of the genome and/or variants related to biological function and HLBS diseases, such as the discovery of novel quantitative trait loci (e.g., expression, methylation, metabolomics, proteomics) or patterns in allele-specific expression that impact the risk of developing HLBS diseases
- Research using AI/ML/modeling approaches to predict the incidence, prevalence, and outcomes of HLBS diseases
- Research using AI/ML/modeling approaches to predict development of HLBS disorders relevant for women’s health across the life span (including pregnancy and postpartum period)
- Integration of genomic/omic data with deep longitudinal phenotypes to assess population-level penetrance estimates and clinical utility for genomic/omic variation that may impact HLBS disease risk; for example,
- Integration of large-scale omics data from multiple molecular levels and anatomical locations increases the power and accuracy of molecular classification of complex diseases, e.g., COPD
- Network analysis across genetic variation, expression profiling, and clinical data to reveal pathways associated with increased COPD risk
- Development of multi-omics approaches and tools to define clinical significance of clonal hematopoiesis in patients with SCD and other rare disorders to predict and prevent somatic mutations due to long-term complications of curative treatments in blood cells
- Spatial-temporal dynamic modeling approaches to integrate environment and geographic information into TOPMed for the study of gene-environment interactions
- Exploration of the molecular and cellular networks underlying the development of HLBS diseases by developing analytical tools or characterizing HLBS diseases at the molecular level through the integration of whole genome sequence with omics datasets
- Translation of deep phenotypic, genomic, and environmental data into knowledge about the determinants of health and disease risk in diverse human populations
- Data analysis that supports the development and improvement of omics technologies
Application and Submission Information
This notice applies to due dates on or after June 5, 2023 and subsequent receipt dates through May 7, 2026.
Submit applications for this initiative using the following funding opportunity announcements (FOAs) or any reissue of this announcement through the expiration date of this notice.
- PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:
- For funding consideration, applicants must include NOT-HL-23-067 in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.
Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative.
Inquiries
Please direct all inquiries related to this NOSI to the following Scientific/Research contacts:
James Luo, Ph.D.
Division of Cardiovascular Sciences
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0533
Email: luoja@nih.gov
Huiqing Li, Ph.D.
Division of Cardiovascular Sciences
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0448
Email: huiqing.li@nih.gov
Weiniu Gan, Ph.D.
Division of Lung Diseases
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0202
Email: ganw2@nih.gov
Pankaj Qasba, Ph.D.
Division of Blood Diseases and Resources
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0050
Email: qasbap@nhlbi.nih.gov
and Human Services (HHS)
