Microarray profiling of skeletal muscle tissues from equally obese, non-diabetic insulin-sensitive and insulin-resistant Pima Indians

Yang, Xiaolin; Pratley, Richard E.; Tokraks, Stephen; Bogardus, Clifton; Permana, Paska A.

doi:10.1007/s00125-002-0905-7

Cited by 96 publications

(26 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dataset IR_Hs originally reports that the differentially expressed genes in insulin resistance of skeletal muscle cells are susceptible genes for T2D [34]. The datasets Preadipocyte_Hs and Adipocyte_Hs describes obesity induced inflammatory response in preadipocytes and adipocytes cells [35], [36].…”

Section: Methodsmentioning

confidence: 99%

Expression-Based Network Biology Identifies Alteration in Key Regulatory Pathways of Type 2 Diabetes and Associated Risk/Complications

et al. 2009

View full text Add to dashboard Cite

Type 2 diabetes mellitus (T2D) is a multifactorial and genetically heterogeneous disease which leads to impaired glucose homeostasis and insulin resistance. The advanced form of disease causes acute cardiovascular, renal, neurological and microvascular complications. Thus there is a constant need to discover new and efficient treatment against the disease by seeking to uncover various novel alternate signalling mechanisms that can lead to diabetes and its associated complications. The present study allows detection of molecular targets by unravelling their role in altered biological pathways during diabetes and its associated risk factors and complications. We have used an integrated functional networks concept by merging co-expression network and interaction network to detect the transcriptionally altered pathways and regulations involved in the disease. Our analysis reports four novel significant networks which could lead to the development of diabetes and other associated dysfunctions. (a) The first network illustrates the up regulation of TGFBRII facilitating oxidative stress and causing the expression of early transcription genes via MAPK pathway leading to cardiovascular and kidney related complications. (b) The second network demonstrates novel interactions between GAPDH and inflammatory and proliferation candidate genes i.e., SUMO4 and EGFR indicating a new link between obesity and diabetes. (c) The third network portrays unique interactions PTPN1 with EGFR and CAV1 which could lead to an impaired vascular function in diabetic nephropathy condition. (d) Lastly, from our fourth network we have inferred that the interaction of β-catenin with CDH5 and TGFBR1 through Smad molecules could contribute to endothelial dysfunction. A probability of emergence of kidney complication might be suggested in T2D condition. An experimental investigation on this aspect may further provide more decisive observation in drug target identification and better understanding of the pathophysiology of T2D and its complications.

show abstract

Section: Methodsmentioning

confidence: 99%

Expression-Based Network Biology Identifies Alteration in Key Regulatory Pathways of Type 2 Diabetes and Associated Risk/Complications

et al. 2009

View full text Add to dashboard Cite

show abstract

“…For example, microarray profiling of insulin-sensitive versus insulin-resistant tissues typically detects expression pattern changes in hundreds of genes [4-6]. Current electronic resources do not allow the list of differentially expressed genes to be automatically cross-checked against well described pathways.…”

Section: Rationalementioning

confidence: 99%

Reactome: a knowledge base of biologic pathways and processes

et al. 2007

View full text Add to dashboard Cite

show abstract

“…When corrected for the large multiple-testing penalty, essentially no genes emerged as differentially expressed between the experimental groups (139, 170). Mootha et al approached this problem with a dimension-reduction approach to the data analysis (98).…”

Section: Musclementioning

confidence: 99%

Physiological Insights Gained from Gene Expression Analysis in Obesity and Diabetes

Keller¹,

Attie

2010

Annu. Rev. Nutr.

View full text Add to dashboard Cite

Microarray technology permits the interrogation of nearly all expressed genes under a wide range of conditions. Patterns of gene expression in response to obesity and diabetes have yielded important insights into the pathogenesis of diabetes and its relationship to obesity. In muscle, microarray studies have motivated research into mitochondrial function. In adipose tissue, clues have pointed to the importance of inflammation in obesity. New adipocyte-derived hormones involved in insulin resistance have been found; a notable example is retinol binding protein 4. In liver, genes responsive to master regulators of lipid metabolism have been identified. In β-cells, genes involved in cell survival, cell proliferation, and insulin secretion have been identified. These studies have greatly expanded our understanding of mechanisms underlying the pathogenesis of obesity-induced diabetes. When combined with genetic information, microarray data can be used to construct causal network models linking gene expression with disease.

show abstract

Microarray profiling of skeletal muscle tissues from equally obese, non-diabetic insulin-sensitive and insulin-resistant Pima Indians

Cited by 96 publications

References 65 publications

Expression-Based Network Biology Identifies Alteration in Key Regulatory Pathways of Type 2 Diabetes and Associated Risk/Complications

Expression-Based Network Biology Identifies Alteration in Key Regulatory Pathways of Type 2 Diabetes and Associated Risk/Complications

Reactome: a knowledge base of biologic pathways and processes

Physiological Insights Gained from Gene Expression Analysis in Obesity and Diabetes

Contact Info

Product

Resources

About