Limits...
Adipose tissue deficiency and chronic inflammation in diabetic Goto-Kakizaki rats.

Xue B, Sukumaran S, Nie J, Jusko WJ, Dubois DC, Almon RR - PLoS ONE (2011)

Bottom Line: Systemic inflammation was reflected by chronically elevated white blood cell counts.Furthermore, chronic inflammation in adipose tissue was evident from the differential expression of genes involved in inflammatory responses and activation of natural immunity, including two interferon regulated genes, Ifit and Iipg, as well as MHC class II genes.This study demonstrates an age specific failure to accumulate adipose tissue in the GK rat and the presence of chronic inflammation in adipose tissue from these animals.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York, United States of America.

ABSTRACT
Type 2 diabetes (T2DM) is a heterogeneous group of diseases that is progressive and involves multiple tissues. Goto-Kakizaki (GK) rats are a polygenic model with elevated blood glucose, peripheral insulin resistance, a non-obese phenotype, and exhibit many degenerative changes observed in human T2DM. As part of a systems analysis of disease progression in this animal model, this study characterized the contribution of adipose tissue to pathophysiology of the disease. We sacrificed subgroups of GK rats and appropriate controls at 4, 8, 12, 16 and 20 weeks of age and carried out a gene array analysis of white adipose tissue. We expanded our physiological analysis of the animals that accompanied our initial gene array study on the livers from these animals. The expanded analysis included adipose tissue weights, HbA1c, additional hormonal profiles, lipid profiles, differential blood cell counts, and food consumption. HbA1c progressively increased in the GK animals. Altered corticosterone, leptin, and adiponectin profiles were also documented in GK animals. Gene array analysis identified 412 genes that were differentially expressed in adipose tissue of GKs relative to controls. The GK animals exhibited an age-specific failure to accumulate body fat despite their relatively higher calorie consumption which was well supported by the altered expression of genes involved in adipogenesis and lipogenesis in the white adipose tissue of these animals, including Fasn, Acly, Kklf9, and Stat3. Systemic inflammation was reflected by chronically elevated white blood cell counts. Furthermore, chronic inflammation in adipose tissue was evident from the differential expression of genes involved in inflammatory responses and activation of natural immunity, including two interferon regulated genes, Ifit and Iipg, as well as MHC class II genes. This study demonstrates an age specific failure to accumulate adipose tissue in the GK rat and the presence of chronic inflammation in adipose tissue from these animals.

Show MeSH

Related in: MedlinePlus

Data mining flowchart.Filters are presented for elimination of non-differentially regulated genes. Step A begins with all probe sets (31,099) normalized to the 50th percentile of signals on that chip. Steps B and C employed a function of Affymetrix Microarray Suite 5.0 which scores signal intensities as present (P), absent (A), or marginal (M). Probe sets not Present on at least 5 of 25 GK chips were eliminated in B, and those not Present on at least 5 of 25 WKY chips were eliminated in C. Step D (probe sets not eliminated in B and C) represent probe sets (22,007) expressed in adipose tissue from either strain. Probe sets remaining in Step D are normalized in Step E by dividing the value of individual GK probe sets by the median value of that probe set from WKY chips. Normalized probe sets from Step E are filtered for differential expression (minimum 2-fold difference) in Steps F and G. Step H represents total probe sets (611) differentially expressed in at least 3 ages and used for further analysis.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3045458&req=5

pone-0017386-g001: Data mining flowchart.Filters are presented for elimination of non-differentially regulated genes. Step A begins with all probe sets (31,099) normalized to the 50th percentile of signals on that chip. Steps B and C employed a function of Affymetrix Microarray Suite 5.0 which scores signal intensities as present (P), absent (A), or marginal (M). Probe sets not Present on at least 5 of 25 GK chips were eliminated in B, and those not Present on at least 5 of 25 WKY chips were eliminated in C. Step D (probe sets not eliminated in B and C) represent probe sets (22,007) expressed in adipose tissue from either strain. Probe sets remaining in Step D are normalized in Step E by dividing the value of individual GK probe sets by the median value of that probe set from WKY chips. Normalized probe sets from Step E are filtered for differential expression (minimum 2-fold difference) in Steps F and G. Step H represents total probe sets (611) differentially expressed in at least 3 ages and used for further analysis.

Mentions: In order to objectively identify probe sets of interest, the entire dataset was filtered with criteria similar to the ones applied to previous gene array datasets [18], [19] and identical to the approach used with the liver array results [16]. This approach does not select for probe sets but rather eliminates those probe sets that do not meet certain criteria, leaving the remainder for further consideration. In this case, probe sets that were not expressed in WAT were first eliminated, leaving a remainder of 22,007. These remaining probe sets were then filtered to eliminate those that did not exhibit at least 2-fold differences in expression in at least three ages when comparing GK and WKY. This second filtering step kept a total 611 probe sets for further investigation, 278 higher in GK rats and 333 higher in WKY rats. Filtering steps are presented in Figure 1 and in our previous publication on the livers from these animals [16].


Adipose tissue deficiency and chronic inflammation in diabetic Goto-Kakizaki rats.

Xue B, Sukumaran S, Nie J, Jusko WJ, Dubois DC, Almon RR - PLoS ONE (2011)

Data mining flowchart.Filters are presented for elimination of non-differentially regulated genes. Step A begins with all probe sets (31,099) normalized to the 50th percentile of signals on that chip. Steps B and C employed a function of Affymetrix Microarray Suite 5.0 which scores signal intensities as present (P), absent (A), or marginal (M). Probe sets not Present on at least 5 of 25 GK chips were eliminated in B, and those not Present on at least 5 of 25 WKY chips were eliminated in C. Step D (probe sets not eliminated in B and C) represent probe sets (22,007) expressed in adipose tissue from either strain. Probe sets remaining in Step D are normalized in Step E by dividing the value of individual GK probe sets by the median value of that probe set from WKY chips. Normalized probe sets from Step E are filtered for differential expression (minimum 2-fold difference) in Steps F and G. Step H represents total probe sets (611) differentially expressed in at least 3 ages and used for further analysis.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3045458&req=5

pone-0017386-g001: Data mining flowchart.Filters are presented for elimination of non-differentially regulated genes. Step A begins with all probe sets (31,099) normalized to the 50th percentile of signals on that chip. Steps B and C employed a function of Affymetrix Microarray Suite 5.0 which scores signal intensities as present (P), absent (A), or marginal (M). Probe sets not Present on at least 5 of 25 GK chips were eliminated in B, and those not Present on at least 5 of 25 WKY chips were eliminated in C. Step D (probe sets not eliminated in B and C) represent probe sets (22,007) expressed in adipose tissue from either strain. Probe sets remaining in Step D are normalized in Step E by dividing the value of individual GK probe sets by the median value of that probe set from WKY chips. Normalized probe sets from Step E are filtered for differential expression (minimum 2-fold difference) in Steps F and G. Step H represents total probe sets (611) differentially expressed in at least 3 ages and used for further analysis.
Mentions: In order to objectively identify probe sets of interest, the entire dataset was filtered with criteria similar to the ones applied to previous gene array datasets [18], [19] and identical to the approach used with the liver array results [16]. This approach does not select for probe sets but rather eliminates those probe sets that do not meet certain criteria, leaving the remainder for further consideration. In this case, probe sets that were not expressed in WAT were first eliminated, leaving a remainder of 22,007. These remaining probe sets were then filtered to eliminate those that did not exhibit at least 2-fold differences in expression in at least three ages when comparing GK and WKY. This second filtering step kept a total 611 probe sets for further investigation, 278 higher in GK rats and 333 higher in WKY rats. Filtering steps are presented in Figure 1 and in our previous publication on the livers from these animals [16].

Bottom Line: Systemic inflammation was reflected by chronically elevated white blood cell counts.Furthermore, chronic inflammation in adipose tissue was evident from the differential expression of genes involved in inflammatory responses and activation of natural immunity, including two interferon regulated genes, Ifit and Iipg, as well as MHC class II genes.This study demonstrates an age specific failure to accumulate adipose tissue in the GK rat and the presence of chronic inflammation in adipose tissue from these animals.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York, United States of America.

ABSTRACT
Type 2 diabetes (T2DM) is a heterogeneous group of diseases that is progressive and involves multiple tissues. Goto-Kakizaki (GK) rats are a polygenic model with elevated blood glucose, peripheral insulin resistance, a non-obese phenotype, and exhibit many degenerative changes observed in human T2DM. As part of a systems analysis of disease progression in this animal model, this study characterized the contribution of adipose tissue to pathophysiology of the disease. We sacrificed subgroups of GK rats and appropriate controls at 4, 8, 12, 16 and 20 weeks of age and carried out a gene array analysis of white adipose tissue. We expanded our physiological analysis of the animals that accompanied our initial gene array study on the livers from these animals. The expanded analysis included adipose tissue weights, HbA1c, additional hormonal profiles, lipid profiles, differential blood cell counts, and food consumption. HbA1c progressively increased in the GK animals. Altered corticosterone, leptin, and adiponectin profiles were also documented in GK animals. Gene array analysis identified 412 genes that were differentially expressed in adipose tissue of GKs relative to controls. The GK animals exhibited an age-specific failure to accumulate body fat despite their relatively higher calorie consumption which was well supported by the altered expression of genes involved in adipogenesis and lipogenesis in the white adipose tissue of these animals, including Fasn, Acly, Kklf9, and Stat3. Systemic inflammation was reflected by chronically elevated white blood cell counts. Furthermore, chronic inflammation in adipose tissue was evident from the differential expression of genes involved in inflammatory responses and activation of natural immunity, including two interferon regulated genes, Ifit and Iipg, as well as MHC class II genes. This study demonstrates an age specific failure to accumulate adipose tissue in the GK rat and the presence of chronic inflammation in adipose tissue from these animals.

Show MeSH
Related in: MedlinePlus