Key Dates

Related Announcements

NOT-HL-23-067 - Notice of Special Interest (NOSI): Integrative Omics Analysis of NHLBI TOPMed Data (Parent R01 Clinical Trial Not Allowed)

NOT-HL-23-086 - NHLBI TOPMed Announces Fellowship Program to Promote Diversity, Equity, and Inclusion in the Genomic Data Science Research Workforce.

Reissue of NOT-HL-21-007 - Notice of Special Interest (NOSI): Integrative Omics Analysis of NHLBI TOPMed Data (Parent R01 Clinical Trial Not Allowed) - Rescinded

PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

Issued by

National Heart, Lung, and Blood Institute (NHLBI)

Purpose

This Notice of Special Interest is a reissue of NOT-HL-21-007.

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 181,000 well-phenotyped individuals and is currently generating multi-omics data (e.g. over 17,700 RNA sequences, over 26,170 DNA methylation, 7,425 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 from them 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 required 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 tool development 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 analysis 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, 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 will soon be released as well. 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 the NHLBI BioData Catalyst platform, cloud computing costs should be proposed in the applicants budget justification. The NHLBI will provide limited supplemental cloud credits (please see the link here for details) to supplement cloud computing costs budgeted in applications.

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
• 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
• Network analysis across genetic variation, expression profiling, and clinical data to reveal pathways associated with increased COPD risk
• Spatial-temporal dynamic modeling approaches to integrate environment and geographic information into TOPMed for the study of gene-environment interactions
• Explore the molecular and cellular networks underlying the development of HLBS diseases by developing analytical tools or characterizing HLBS diseases at the molecular level by integrating whole genome sequence with omics datasets
• Translation of deep phenotypic and genomic 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 October 5, 2021 and subsequent receipt dates through May 8, 2023.

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-21-017 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

James Luo, Ph.D.
Division of Cardiovascular Sciences
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0533
Email: [email protected]

Huiqing Li, Ph.D.
Division of Cardiovascular Sciences
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0448
Email: [email protected]

Weiniu Gan, Ph.D.
Division of Lung Diseases
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0202
Email: [email protected]

Pankaj Qasba, Ph.D.
Division of Blood Diseases and Resources
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0050
Email: [email protected]