Unknown

Dataset Information

0

Genome-wide linkage analysis of multiple metabolic factors: evidence of genetic heterogeneity.


ABSTRACT: The metabolic syndrome is a highly complex disease and has become one of the major public-health challenges worldwide. We sought to identify genetic loci with potential influence on multiple metabolic factors in a white population in Beaver Dam, Wisconsin, and to explore the possibility of genetic heterogeneity by family history of diabetes (FHD). Three metabolic factors were generated using principal-component factor analysis, and they represented: (i) glycemia, (ii) blood pressure, and (iii) combined (BMI, high-density lipoprotein (HDL) cholesterol, and serum uric acid) factors. Multipoint model-free linkage analysis of these factors with 385 microsatellite markers was performed on 1,055 sib-pairs, using Haseman-Elston regression. Genome-wide suggestive evidence of linkage was found at 30 cM on chromosome 22q (empirical P (P(e)) = 0.0002) for the glycemia factor, at 188-191 cM on chromosome 1q (P(e) = 0.0007) for the blood pressure factor, and at 82 cM on chromosome 17q (P(e) = 0.0007) for the combined factor. Subset analyses of the families by FHD showed evidence of genetic heterogeneity, with divergent linkage signals in the subsets on at least four chromosomes. We found evidence of genetic heterogeneity by FHD for the three metabolic factors. The results also confirmed findings of previous studies that mapped components of the metabolic syndrome to a chromosome 1q region.

SUBMITTER: Cheng CY 

PROVIDER: S-EPMC2866100 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

altmetric image

Publications

Genome-wide linkage analysis of multiple metabolic factors: evidence of genetic heterogeneity.

Cheng Ching-Yu CY   Lee Kristine E KE   Duggal Priya P   Moore Emily L EL   Wilson Alexander F AF   Klein Ronald R   Bailey-Wilson Joan E JE   Klein Barbara E K BE  

Obesity (Silver Spring, Md.) 20090514 1


The metabolic syndrome is a highly complex disease and has become one of the major public-health challenges worldwide. We sought to identify genetic loci with potential influence on multiple metabolic factors in a white population in Beaver Dam, Wisconsin, and to explore the possibility of genetic heterogeneity by family history of diabetes (FHD). Three metabolic factors were generated using principal-component factor analysis, and they represented: (i) glycemia, (ii) blood pressure, and (iii) c  ...[more]

Similar Datasets

| S-EPMC2838753 | biostudies-other
| S-EPMC5511258 | biostudies-literature
| S-EPMC1735631 | biostudies-other
| S-EPMC3136385 | biostudies-other
| S-EPMC4875235 | biostudies-other
| S-EPMC2671990 | biostudies-literature
| S-EPMC3105232 | biostudies-literature
| S-EPMC1226029 | biostudies-literature
| S-EPMC5870548 | biostudies-literature
| S-EPMC3655878 | biostudies-literature