Using Integrative Networks to Explore Heterogeneous Phenotypes in COPD
Using Integrative Networks to Explore Heterogeneous Phenotypes in COPD
批准号:
9164450
负责人:
Kimberly Renee Glass
金额:
$18.9万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-08-01 至 2021-05-31
关键词:
AmericanAreaAutomobile DrivingAwardBenchmarkingBiologicalBiological ProcessBiologyBloodCancer CenterCellsChIP-seqCharacteristicsChestChronic Obstructive Airway DiseaseClinicalClinical DataComplexComputer ArchitecturesDataData AnalysesData ScienceData SetDatabasesDiseaseEducational workshopEnvironmentEpigenetic ProcessFacultyFundingGene Expression RegulationGenesGeneticGenomeGenomic approachGenomicsGenotype-Tissue Expression ProjectGlassGoalsGrantHeterogeneityHistocompatibility TestingHospitalsImageIndividualInformation NetworksInstitutesInstitutionKnowledgeLinkLungLung diseasesMassachusettsMeasuresMediatingMedicalMedicineMentorsMethodsMicroRNAsModelingNaturePathogenesisPathway AnalysisPathway interactionsPatientsPhenotypePhysicsPlayPopulationPopulation HeterogeneityProcessPropertyProteomePublic Health SchoolsQualifyingRegulator GenesResearchResearch PersonnelResearch TrainingResourcesRoleSamplingScienceSocietiesSourceStatistical ModelsStructureStructure of parenchyma of lungSystemTechnologyTissuesTrainingTraining ProgramsTranslationsUniversitiesWashingtonWomanWorkWritingabstractingcareercatalystclinical applicationcomputer sciencecomputing resourcesdata integrationdisease heterogeneitydisease phenotypeeffective therapyepigenomeexperiencegenomic datainnovationinsightmedical schoolsmeetingsmembermetabolomemethod developmentnetwork modelsnew technologyphenotypic dataprecision medicinereconstructionrespiratoryskillsstatisticssymposiumtargeted treatmenttooltranscriptometranslational medicinetreatment responsetreatment strategy
中文摘要
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英文摘要
Project Summary/Abstract
Rapidly evolving genomic technologies are providing unprecedented amounts of data with the potential to
yield new insights into the processes driving lung disease, including Chronic Obstructive Pulmonary Disease
(COPD). These data have already allowed us to develop a more unified understanding of how multiple
biological mechanisms work together to influence COPD. We now appreciate that in most cases a single gene
or pathway does not fully characterize the disease or alterations in disease-state. Rather, disease-related
changes often involve simultaneous alterations to the genome, epigenome, transcriptome, metabolome, and
proteome of the cell and can be represented by complex networks whose structures are altered as the disease
develops. Importantly, many of these changes are associated with complex shifts in the regulatory networks
from the normal to a diseased state. Modeling these changes can inform us about the processes that drive
COPD and suggest potential targeted therapies.
In this proposal we develop and expand methods for integrating emerging multi-omic data to reconstruct
comprehensive regulatory networks in COPD. We then develop approaches for analyzing these networks and
for effectively linking regulatory alterations with disease mechanisms within different observed COPD
phenotypes. We begin by developing quantitative approaches for inferring, analyzing, decomposing and
comparing networks. These methods will allow us to discover new features about the nature of lung disease, to
understand the complex regulatory processes at work across patients, and ultimately have the power suggest
ways to more effectively treat COPD.
Executing on this plan will require a unique set of skills that span biology, network science, computer
science, translational medicine and lung disease. Dr. Glass’ background is in physics, complex systems and
genomic data analysis. Although her previous experiences have prepared her well for the proposed research,
she recognizes that there are new challenges that need to be overcome when applying networks and
genomics approaches to study COPD. Therefore, Dr. Glass has selected a mentored research environment
and crafted a training program that will allow her to obtain the interdisciplinary skills necessary to accomplish
the goals of this project.
In support of her proposed research, Dr. Glass will make use of the many high-quality computational
resources available to her through the Channing Division of Network Medicine (CDNM) at Brigham and
Women’s Hospital (BWH), the Dana-Farber/Harvard Cancer Center, Harvard Medical School, and the Harvard
School of Public Health and well as additional resources directly provided by her mentors and advisory board
members. Along these lines, Dr. Glass has assembled a diverse and well-qualified mentoring team to oversee
and advise her research efforts. Her primary mentor, Dr. Quackenbush, and advisory board member Dr. Yuan
both have extensive and complementary experience in analyzing and interpreting many types of genomic data.
Advisory board member Dr. Kepner has deep knowledge of scalable computer architecture and will support Dr.
Glass by providing computational resources such as access to the MIT SuperCloud. After constructing
regulatory networks in COPD, interpreting them in the context of relevant biological questions will be essential.
Advisory board member Dr. Onnela is an expert in developing methods for network quantification and will play
an important role in helping Dr. Glass to create objective measures of network structural differences. Finally,
co-mentor Dr. Silverman is a leading expert in COPD and network medicine, and will provide important
guidance to Dr. Glass as she determines how to relate network measures to patient data, including relevant
clinical features of COPD.
Dr. Glass will supplement her hands-on training with formal coursework and specific mentored exploration
focused in three main areas: 1) Lung disease, translational medicine and clinical applications, with training
through courses offered through the Harvard Catalyst and Harvard School of Public Health, attending the
annual American Thoracic Society meeting, and working closely with Dr. Silverman and the Respiratory
Medicine faculty at the CDNM/BWH; 2) Biomedical data analysis and computation, with training from taking
online classes offered by the University of Washington and Massachusetts Institute of Technology, attending
local workshops and working closely with Drs. Quackenbush, Yuan and Kepner; and 3) Statistics and network
analysis methods development, with training from taking courses offered by the Harvard School of Public
Health, attending national conferences, and working closely with Drs. Quackenbush and Onnela. Finally, Dr.
Glass will actively participate in and receive training on the grant writing process throughout the award period,
so as to be well-prepared to apply for independent funding at the conclusion of the project.
Dr. Glass’s career goal is to become an independent investigator studying non-neoplastic lung disease at
an academic institution. Through the proposed research and training plan, she will be able to hone the
computational abilities she has already developed and collect a variety of additional skills that will be essential
to becoming an independent investigator capable of leveraging biomedical data to perform computational
research and network analysis that has translational applications in COPD and lung disease.
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会议论文
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