Literature DB >> 16096997

Identification and study of Utah pseudo-isolate populations-prospects for gene identification.

L A Cannon-Albright1, J M Farnham, A Thomas, N J Camp.   

Abstract

Isolate populations of varied types have proven powerful for gene identification for rare Mendelian disorders, and continue to show such promise for more complex phenotypes. Existing isolate populations are limited in the phenotypes available for study, and new population isolates are unlikely to arise. We utilize genealogical data available for the state of Utah, dating back to its European founders, to retrospectively define and examine pseudo-isolate subpopulations. These pseudo-isolate populations are defined by selection of a set of "founders" from the genealogical data, and then limitation of "immigration" by censoring of matings and offspring that do not match the isolate population design. A wide variety of pseudo isolate and other study designs are possible by varying the number and type of founders and the extent of immigration allowed. We present several different example Birth-Country pseudo-isolate populations defined within the Utah Population Database (UPDB). We utilize linked cancer phenotype data available for the Utah population to show the utility of this pseudo-isolate approach for identification of more genetically homogeneous prostate cancer pedigrees for predisposition gene identification. In conclusion, we present a unique approach to retrospective "creation" of isolate populations using existing genealogical data. We use the UPDB to exhibit the utility of this approach for the highly heterogeneous Utah population, and suggest the approach is feasible for any population for which high quality genealogy and phenotype data are available. (c) 2005 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2005        PMID: 16096997     DOI: 10.1002/ajmg.a.30893

Source DB:  PubMed          Journal:  Am J Med Genet A        ISSN: 1552-4825            Impact factor:   2.802


  6 in total

1.  The use of genealogy databases for risk assessment in genetic health service: a systematic review.

Authors:  Vigdis Stefansdottir; Oskar Th Johannsson; Heather Skirton; Laufey Tryggvadottir; Hrafn Tulinius; Jon J Jonsson
Journal:  J Community Genet       Date:  2012-07-18

2.  Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery.

Authors:  L M Taft; R S Evans; C R Shyu; M J Egger; N Chawla; J A Mitchell; S N Thornton; B Bray; M Varner
Journal:  J Biomed Inform       Date:  2008-09-14       Impact factor: 6.317

3.  Population-based family history-specific risks for colorectal cancer: a constellation approach.

Authors:  David P Taylor; Randall W Burt; Marc S Williams; Peter J Haug; Lisa A Cannon-Albright
Journal:  Gastroenterology       Date:  2009-12-21       Impact factor: 22.682

4.  Evidence of an Inherited Predisposition for Spinal Cord Tumors.

Authors:  William Ryan Spiker; Darrel S Brodke; Vadim Goz; Brandon Lawrence; Craig C Teerlink; Lisa A Cannon-Albright
Journal:  Global Spine J       Date:  2017-08-17

5.  A Rare Variant in ERF (rs144812092) Predisposes to Prostate and Bladder Cancers in an Extended Pedigree.

Authors:  Lisa Anne Cannon-Albright; Craig Carl Teerlink; Jeff Stevens; Franklin W Huang; Csilla Sipeky; Johanna Schleutker; Rolando Hernandez; Julio Facelli; Neeraj Agarwal; Donald L Trump
Journal:  Cancers (Basel)       Date:  2021-05-15       Impact factor: 6.639

6.  Familial aggregation of Parkinson disease in Utah: A population-based analysis using death certificates.

Authors:  Rodolfo Savica; Lisa A Cannon-Albright; Stefan Pulst
Journal:  Neurol Genet       Date:  2016-03-22
  6 in total

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