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Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR.
Pubmed ID: 24358131 RIS Download
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Software application that provides researchers with the tools necessary for various types of statistical genetic analysis of human family data. (entry from Genetic Analysis Software)
View all literature mentionsA longitudinal, epidemiologic study to identify the common risk factors or characteristics that contribute to cardiovascular disease by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms or suffered a heart attack or stroke. Since that time the FHS has studied three generations of participants resulting in biological specimens and data from nearly 15,000 participants. Since 1994, two groups from minority populations, including related individuals have been added to the FHS. FHS welcomes proposals from outside investigators for data and biospecimens. The researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have continued to return to the study every two years for a detailed medical history, physical examination, and laboratory tests, and in 1971, the Study enrolled a second generation - 5,124 of the original participants'''' adult children and their spouses - to participate in similar examinations. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study was enrolled. In April 2002 the Study entered a new phase, the enrollment of a third generation of participants, the grandchildren of the Original Cohort. In 2003, a second group of Omni participants was enrolled. Over the years, careful monitoring of the Framingham Study population has led to the identification of major CVD risk factors, as well as valuable information on the effects of these factors such as blood pressure, blood triglyceride and cholesterol levels, age, gender, and psychosocial issues. Risk factors for other physiological conditions such as dementia have been and continue to be investigated. In addition, the relationships between physical traits and genetic patterns are being studied. FHS clinical and research data is stored in the dbGaP and NHLBI Repository repositories and may be accessed by application. Please check the following repositories before applying for data through FHS. Investigators seeking data that is not available through dbGaP or BioLINCC or seeking biological specimens may submit a proposal through the FHS web-based research application. The FHS data repository may be accessed through this FHS website, under the For Researchers link, then Description of Data, in order to determine if and how the desired data is stored. Proposals may involve the use of existing data, the collection of new data, either directly from participants or from previously collected samples, images, or other materials (e.g., medical records). The FHS Repository also has biological specimens available for genetic and non-genetic research proposals. Specimens include urine, blood and blood products, as well as DNA.
View all literature mentionsSoftware application that carries out single-point and multipoint analyses of pedigree data, including IBD and kinship calculations, nonparametric and variance component linkage analyses, error detection and information content mapping. For multipoint analyses in dense maps, Merlin allows the user to impose constraints on the number of recombinants between consecutive markers. Merlin estimates haplotypes by finding the most likely path of gene flow or by sampling paths of gene flow at all markers jointly. It can also list all possible nonrecombinant haplotypes within short regions. Finally, Merlin provides swap-file support for handling very large numbers of markers as well as gene-dropping simulations for estimating empirical significance levels. (entry from Genetic Analysis Software)
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