Linked Life Data

16451665

Source:http://linkedlifedata.com/resource/pubmed/id/16451665

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-1-19
pubmed:abstractText
Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1471-2156
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S53
pubmed:dateRevised
2010-9-20
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.
pubmed:affiliation
Center for Human Genetics, Duke University Medical Center, Durham, NC 27710, USA. yiju.li@duke.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural