--- title: "Framingham Heart Study (FHS)" id: "1019" type: "cohort" slug: "framingham-heart-study-fhs" published_at: "2020-02-19T15:07:07+00:00" modified_at: "2024-09-18T16:35:53+00:00" url: "https://dss.niagads.org/cohorts/framingham-heart-study-fhs/" markdown_url: "https://dss.niagads.org/cohorts/framingham-heart-study-fhs.md" excerpt: "The Framingham Heart Study, under the direction of the National Heart, Lung and Blood Institute (NHLBI), formerly known as the National Heart Institute, has been committed to identifying the common factors or characteristics that contribute to cardiovascular disease (CVD) since..." taxonomy_cohort_categories: - "ADSP" taxonomy_cohort_countries: - "United States of America" --- Website: [https://www.framinghamheartstudy.org/](https://www.framinghamheartstudy.org/) ## Description The Framingham Heart Study, under the direction of the National Heart, Lung and Blood Institute (NHLBI), formerly known as the National Heart Institute, has been committed to identifying the common factors or characteristics that contribute to cardiovascular disease (CVD) since its beginning in 1948. FHS has followed CVD development over a long period of time in three generations of participants. The Study began in 1948 by recruiting an Original Cohort of 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke. Since that time the Study has added an Offspring Cohort in 1971, the Omni Cohort in 1994, a Third Generation Cohort in 2002, a New Offspring Spouse Cohort in 2003, and a Second Generation Omni Cohort in 2003. Data collected over the course of FHS have included those derived from physical examinations, lifestyle interviews, detailed medical histories, and laboratory testing. DNA has been collected from blood samples for the Original, Offspring, and Third Generation Cohorts. Available phenotype information includes quantitative measures of the major CVD risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. ## Related Datasets - [NG00067 – ADSP Umbrella](https://dss.niagads.org/datasets/ng00067/) This dataset includes sequencing data and harmonized phenotypes from cohorts sequenced by the Alzheimer’s Disease Sequencing Project and other AD and Related Dementia’s studies. Samples are processed using a common… [Learn more](https://dss.niagads.org/datasets/ng00067/) - [NG00116 – Resolving Mutations in Challenging Genomic Regions to Test Association with Disease Phenotypes](https://dss.niagads.org/datasets/ng00116/) Many regions of the human genome present challenges that prohibit scientists from discovering potential disease-causing mutations. We developed methods to characterize mutations in these regions to rescue mutations that are… [Learn more](https://dss.niagads.org/datasets/ng00116/) - [NG00176-CNVs from ADSP WES data using CANOES software](https://dss.niagads.org/datasets/ng00176/) This dataset contains Copy Number Variation (CNV) calling from the Whole Exome Sequencing (WES) from multiple distinct Alzheimer Disease (AD) sequencing projects: both discovery and replication ADSP family dataset, ADSP… [Learn more](https://dss.niagads.org/datasets/ng00176/) ## Related Studies - [sa000001 - Alzheimer’s Disease Sequencing Project (ADSP)](https://dss.niagads.org/studies/sa000001/) Background An initiative in response to the National Alzheimer’s Project Act (NAPA) has been working towards new biological insights and cures for Alzheimer’s Disease (AD) since its introduction by NIH… [Learn more](https://dss.niagads.org/studies/sa000001/) - [sa000081 - Extremely Rare CNVs and Alzheimer’s Disease Risk: Analysis of ADSP WES Data](https://dss.niagads.org/studies/sa000081/) The purpose of this study is to find new Alzheimer related variants and genes, by combining exome data from healthy controls and Alzheimer patients from different studies. CNV calling was… [Learn more](https://dss.niagads.org/studies/sa000081/) - [sa000042 - Resolving mutations in challenging genomic regions to test association with disease phenotypes](https://dss.niagads.org/studies/sa000042/) Many regions of the human genome present challenges that prohibit scientists from discovering potential disease causing mutations. We developed methods to characterize mutations in these regions to rescue mutations that… [Learn more](https://dss.niagads.org/studies/sa000042/) ## Related Sample Sets - [snd10000 - ADSP Discovery](https://dss.niagads.org/sample-sets/snd10000/) The initial phase of the ADSP research plan is called the Discovery Phase. Samples were selected from well-characterized study cohorts of individuals with or without an AD diagnosis and the… [Learn more](https://dss.niagads.org/sample-sets/snd10000/) - [snd10074 - Camouflaged Variants](https://dss.niagads.org/sample-sets/snd10074/) Provided here are variant calls in VCF format for 14,526 samples derived from the ADSP whole-exome and whole-genome sequencing dataset (available via DSS: NG00067). [Learn more](https://dss.niagads.org/sample-sets/snd10074/) - [snd10139 - CNV Calling from ADSP Whole-Exome Sequencing (WES) Data](https://dss.niagads.org/sample-sets/snd10139/) This dataset comprises CNV calls from Whole Exome Sequencing (WES) across multiple distinct Alzheimer’s Disease (AD) sequencing projects, including the discovery and replication ADSP family datasets, the ADSP case-control dataset,… [Learn more](https://dss.niagads.org/sample-sets/snd10139/) ```