Dataset Information

Expression analyses of the genes harbored by the type 2 diabetes and pediatric BMI associated locus on 10q23.

ABSTRACT:

Background

There is evidence that one of the key type 2 diabetes (T2D) loci identified by GWAS exerts its influence early on in life through its impact on pediatric BMI. This locus on 10q23 harbors three genes, encoding hematopoietically expressed homeobox (HHEX), insulin-degrading enzyme (IDE) and kinesin family member 11 (KIF11), respectively.

Methods

We analyzed the impact of adipogeneis on the mRNA and protein expression levels of these genes in the human adipocyte Simpson-Golabi-Behmel syndrome (SGBS) cell line in order to investigate which could be the culprit gene(s) in this region of linkage disequilibrium.

Results

Following activation of differentiation with a PPAR? ligand, we observed ~20% decrease in IDE, ~40% decrease in HHEX and in excess of 80% decrease in KIF11 mRNA levels when comparing the adipocyte and pre-adipocyte states. We also observed decreases in KIF11 and IDE protein levels, but conversely we observed a dramatic increase in HHEX protein levels. Subsequent time course experiments revealed some marked changes in expression as early as three hours after activation of differentiation.

Conclusion

Our data suggest that the expression of all three genes at this locus are impacted during SGBS adipogenesis and provides insights in to the possible mechanisms of how the genes at this 10q23 locus could influence both adipocyte differentiation and susceptibility to T2D through insulin resistance.

SUBMITTER: Zhao J

PROVIDER: S-EPMC3514277 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Publications

Expression analyses of the genes harbored by the type 2 diabetes and pediatric BMI associated locus on 10q23.

Zhao Jianhua J Deliard Sandra S Aziz Ali Rahim AR Grant Struan F A SF

BMC medical genetics 20120924

<h4>Background</h4>There is evidence that one of the key type 2 diabetes (T2D) loci identified by GWAS exerts its influence early on in life through its impact on pediatric BMI. This locus on 10q23 harbors three genes, encoding hematopoietically expressed homeobox (HHEX), insulin-degrading enzyme (IDE) and kinesin family member 11 (KIF11), respectively.<h4>Methods</h4>We analyzed the impact of adipogeneis on the mRNA and protein expression levels of these genes in the human adipocyte Simpson-Gol ...[more]

PMID: 22998375

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Project description:BackgroundCoronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.MethodA data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.ResultsWe identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).ConclusionThe SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Dataset Information

Expression analyses of the genes harbored by the type 2 diabetes and pediatric BMI associated locus on 10q23.

Background

Methods

Results

Conclusion

Publications

Expression analyses of the genes harbored by the type 2 diabetes and pediatric BMI associated locus on 10q23.

Similar Datasets

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