Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2005-3-28
pubmed:abstractText
Type 2 diabetes is a complex disease involving both genetic and environmental components. Abnormalities in insulin secretion and insulin action usually precede the development of type 2 diabetes and can serve as good quantitative measures for genetic mapping. We therefore undertook an autosomal genomic search to locate the quantitative trait locus (QTL) linked to these traits in 1,365 nondiabetic Chinese subjects from 411 nuclear families. Residuals of these log-transformed quantitative traits were analyzed in multipoint linkage analysis using a variance-components approach. The most significant QTL for fasting insulin, which coincides with the QTL for homeostasis model assessment of insulin resistance, was located at 37 cM on chromosome 20, with a maximum empirical logarithm of odds (LOD) score of 3.01 (empirical P = 0.00006) when adjusted for age, sex, BMI, antihypertensive medications, recruitment centers, and environmental factors. In the same region, a QTL for fasting glucose was identified at 51 cM, with an empirical LOD score of 2.03 (empirical P = 0.0012). There were other loci with maximum empirical LOD scores >or=1.29 located on chromosomes 1q, 2p, 5q, 7p, 9q, 10p, 14q, 18q, and 19q for different diabetes-related traits. These loci may harbor genes that regulate glucose homeostasis either independently or via interactions of the genes within these regions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0012-1797
pubmed:author
pubmed:issnType
Print
pubmed:volume
54
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1200-6
pubmed:dateRevised
2011-11-17
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
An autosomal genome-wide scan for loci linked to pre-diabetic phenotypes in nondiabetic Chinese subjects from the Stanford Asia-Pacific Program of Hypertension and Insulin Resistance Family Study.
pubmed:affiliation
Division of BiostatisticsBioinformatics, National Health Research Institutes, Taipei, Taiwan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't