grant

Network and Systems Biology Scientific Core 3

Organization CLEVELAND CLINIC LERNER COM-CWRULocation CLEVELAND, UNITED STATESPosted 1 Jul 2022Deadline 30 Jun 2027
NIHUS FederalResearch GrantFY2025AgeApoplexyArrhythmiaAssayAtrial FibrillationAuricular FibrillationBioassayBiological AssayBrain Vascular AccidentCardiac ArrhythmiaCell NucleusCerebral StrokeCerebrovascular ApoplexyCerebrovascular StrokeClinicalDataDetectionDiagnosisDiseaseDisorderDoctor of PhilosophyGWA studyGWASGene ExpressionGenesGeneticGenomicsGoalsHeart ArrhythmiasHuman ResourcesIncidenceInvestigatorsKineticsKnowledgeLeadManpowerMetabolicModelingMolecularNon-Polyadenylated RNANucleusObesityOutcomePb elementPh.D.PhDPopulationProcessProteinsProteomicsRNARNA Gene ProductsRNA ProcessingRNA SeqRNA sequencingRNAseqReproducibilityResearch InstituteResearch PersonnelResearchersRibonucleic AcidRiskSample SizeSamplingServicesSingle-Nucleus SequencingStrokeStudy modelsSystems BiologyTherapeuticVisualizationWorkadiposityagesatriumbrain attackcardiovascular riskcardiovascular risk factorcell typecerebral vascular accidentcerebrovascular accidentclinical applicabilityclinical applicationcorpulencedifferential expressiondifferentially expresseddrug discoveryexperienceflexibilityflexiblegenome wide associationgenome wide association scangenome wide association studygenomewide association scangenomewide association studyheavy metal Pbheavy metal leadmetabolism measurementmetabolomicsmetabonomicsmortalitynetwork modelspersonnelpower analysissNuc-Seqsingle nucleus RNA-sequencingsingle nucleus seqsingle-nucleus RNA-seqskillssnRNA sequencingsnRNA-seqstrokedstrokessuccesstherapeutically effectivetraittranscriptional differencestranscriptome sequencingtranscriptomic sequencingtranscriptomicswhole genome association analysiswhole genome association study
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Full Description

SC3 PROJECT SUMMARY
Atrial fibrillation (AF) is the most common arrhythmia and a major risk factor for cardiovascular mortality and

stroke. Incidence of AF is further increasing due to the rise in obesity and age of the population, factors closely

related to AF risk and progression. Despite significant advances in AF diagnosis and management, treatment

and clinical outcomes remain poor and more than a decade has passed since the last AF drug discovery. The

overall goal of this PPG application is to use genomic and transcriptomic findings to identify preventative and

therapeutic strategies for AF and develop them towards clinical application. Our central hypothesis is that

increasing our knowledge about molecular mechanisms involved in genetic, transcriptomic, metabolic and

structural changes in the atria will allow us to pinpoint possible targets for safer and more effective therapeutic

strategies. To help the projects advance towards these goals, the Network and Systems Biology Core (SC3)

will be responsible for the processing, analysis, integration and network modeling of all RNA sequencing data,

including bulk and single nuclei, proteomic, metabolomics, and functional assay data used and generated in

the four projects. All Projects have proposed extensive use of RNA sequencing studies, making SC3 integral

to their success. Functional assay data will be generated primarily in SC1 and SC2 under direction of the

Projects and then sent to SC3 for analysis and integration with RNASeq. SC3 will work closely with the project

leads and personnel to help interpret and visualize the results including those from traditional differential

analyses as well as from more advanced network and systems biology approaches. SC3 has a unique blend of

expertise and experience, combining personnel with RNA processing and modeling skills and those with a

network and systems biology focus, which together with a rigorous and reproducible pipeline implementation

will help enable the four projects in this PPG to fill knowledge gaps and make advances towards understanding

and treating atrial fibrillation. SC3 will provide two major groups of services to the PPG organized around the

type of data being analyzed. Aim 1 will focus on services for RNA sequencing data, including advanced

network and systems biology approaches, while Aim 2 will focus on services for functional assay data as well

as integrations with the RNA data.

Grant Number: 5P01HL158502-04
NIH Institute/Center: NIH

Principal Investigator: John Barnard

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