ID
45435
Descrizione
Principal Investigator: Nir Barzilai, MD, Albert Einstein College of Medicine, Bronx, NY, USA MeSH: Longevity https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000584 Aging is a complex, universal condition leading to the functional decline of all cells and organisms, and to major national and global public health problems. Although aging is the major risk factor for developing most adult-onset diseases, systematic investigations into the fundamental physiology, biology and genetics of aging are only just beginning. In the Longevity Genes Project at Albert Einstein College of Medicine, Dr. Nir Barzilai and his team conducted genetic research on more than 500 healthy elderly people between the ages of 95 and 112, and on their children. The identification of longevity genes by Einstein researchers could lead to new drug therapies that might help people live longer, healthier lives and avoid or significantly delay age-related diseases such as Alzheimer's disease, type 2 diabetes and cardiovascular disease.
collegamento
Keywords
versioni (1)
- 29/11/22 29/11/22 - Simon Heim
Titolare del copyright
Nir Barzilai, MD, Albert Einstein College of Medicine, Bronx, NY, USA
Caricato su
29 novembre 2022
DOI
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Licenza
Creative Commons BY 4.0
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dbGaP phs000584 The Longevity Genes Project
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent group information, and subject aliases.
- This pedigree data table contains family relationships in the format of family IDs, subject IDs, father IDs, mother IDs, sex of subjects, monozygotic twin IDs, and superfamily grouping for related individuals for which a complete pedigree could not be determined.
- 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 phenotypes data table includes subject's sex, age at recruitment, cholesterol, triglycerides, HDL, LDL, glucose levels, systolic and diastolic blood pressure measurements, BMI, height, and weight.
- This sample attributes table includes body site where sample was collected, analyte type, histological type, and tumor status.
Similar models
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent group information, and subject aliases.
- This pedigree data table contains family relationships in the format of family IDs, subject IDs, father IDs, mother IDs, sex of subjects, monozygotic twin IDs, and superfamily grouping for related individuals for which a complete pedigree could not be determined.
- 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 phenotypes data table includes subject's sex, age at recruitment, cholesterol, triglycerides, HDL, LDL, glucose levels, systolic and diastolic blood pressure measurements, BMI, height, and weight.
- This sample attributes table includes body site where sample was collected, analyte type, histological type, and tumor status.
C0680251 (UMLS CUI [1,2])
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C0032659 (UMLS CUI [1,3])
C0015177 (UMLS CUI [1,4])
C0020174 (UMLS CUI [1,5])
C0032356 (UMLS CUI [1,6])
C0035970 (UMLS CUI [1,7])
C0017480 (UMLS CUI [1,8])
C0035826 (UMLS CUI [1,9])
C0010872 (UMLS CUI [1,10])
C0001779 (UMLS CUI [1,11])
C3844810 (UMLS CUI [1,2])
C0032659 (UMLS CUI [1,3])
C0015177 (UMLS CUI [1,4])
C0020174 (UMLS CUI [1,5])
C0032356 (UMLS CUI [1,6])
C0035970 (UMLS CUI [1,7])
C0017480 (UMLS CUI [1,8])
C0035826 (UMLS CUI [1,9])
C0010872 (UMLS CUI [1,10])
C0001779 (UMLS CUI [1,11])