ID
45922
Description
Principal Investigator: Scott T. Weiss, MD, MS, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA MeSH: Asthma,Immunoglobulin E, Basic Level of, in Serum,Body Mass Index,Body Weight,Body Height https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000988 *This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance.* Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). *The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches.* Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. *Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods.* We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.
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Versions (1)
- 2/8/24 2/8/24 - Simon Heim
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Scott T. Weiss, MD, MS, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
Uploaded on
February 8, 2024
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Creative Commons BY 4.0
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dbGaP phs000988 NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica
This subject phenotype table includes gender, race, age, asthma status, anthropometric measurements (n=3 variables; height, weight, and bmi), and smoking status (n=6 variables; ever, current, and former smoking status, number of cigarettes/day, average cigarettes and packs/year).
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent group information, and subject's sex.
- This pedigree data table contains family relationships in the format of family IDs, subject IDs, father IDs, mother IDs, sex of subjects, and monozygotic twin IDs.
- This subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype table includes gender, race, age, asthma status, anthropometric measurements (n=3 variables; height, weight, and bmi), and smoking status (n=6 variables; ever, current, and former smoking status, number of cigarettes/day, average cigarettes and packs/year).
- This sample attributes table includes body site where sample was collected, analyte type, tumor status, sequencing center, funding source, TOPMed phase, study name, and project.
Similar models
This subject phenotype table includes gender, race, age, asthma status, anthropometric measurements (n=3 variables; height, weight, and bmi), and smoking status (n=6 variables; ever, current, and former smoking status, number of cigarettes/day, average cigarettes and packs/year).
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent group information, and subject's sex.
- This pedigree data table contains family relationships in the format of family IDs, subject IDs, father IDs, mother IDs, sex of subjects, and monozygotic twin IDs.
- This subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype table includes gender, race, age, asthma status, anthropometric measurements (n=3 variables; height, weight, and bmi), and smoking status (n=6 variables; ever, current, and former smoking status, number of cigarettes/day, average cigarettes and packs/year).
- This sample attributes table includes body site where sample was collected, analyte type, tumor status, sequencing center, funding source, TOPMed phase, study name, and project.
C2348585 (UMLS CUI [1,2])
C1442880 (UMLS CUI [1,2])
C1882515 (UMLS CUI [1,3])
C1510992 (UMLS CUI [1,2])
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