| Literature DB >> 22414021 |
Antonella Mandas1, Claudia Abete, Paolo Francesco Putzu, Paolo la Colla, Sandra Dessì, Alessandra Pani.
Abstract
BACKGROUND: Cholesterol homeostasis dysfunction has been reported to have role in the pathogenesis of Alzheimer disease (AD). Therefore, changes in cholesterol metabolism in blood components may help to develop new potential AD biomarkers. In this study changes in cholesterol metabolism-related gene expression genes were evaluated in peripheral blood mononuclear cells (PBMCs) from AD subjects, their first degree relatives (FDR) and two groups of age matched controls (C1 > 80 years, C2 < 60 years). The expression of three genes related to APP processing was also determined.Entities:
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Year: 2012 PMID: 22414021 PMCID: PMC3323438 DOI: 10.1186/1476-511X-11-39
Source DB: PubMed Journal: Lipids Health Dis ISSN: 1476-511X Impact factor: 3.876
Figure 1ORO staining of cytoplasmic neutral lipids. Freshly isolated PBMCs were stained with ORO to demonstrate neutral lipids and counterstained with haematoxylin for nuclei. Cells were then examined by light microscopy and two different fields per sample were imaged. Red ORO intensity was measured in these two fields using NIH Image J software. Panel (a) shows representative images of ORO stained (on the left) and their corresponding ROI (on the right). Panel (b) shows quantization of red intensity expressed as the percentage of pixel intensity ± SD⁄ total area of each image. Analysis of variance (ANOVA) shows significant statistically differences among the four groups (P = 0.000).
Figure 2Representative blots of mRNA levels of cholesterol metabolism and APP processing-related genes. Total mRNA was extracted from PBMCs of the selected groups. mRNA levels of indicated genes were then determined by RT-PCR using appropriate primer sets. Specific bands were detected after addition of a chemiluminescent substrate.
Figure 3Densitometric analysis of mRNA levels of target genes normalized for the endogenous β-actin. mRNA levels were quantified by using NIH Image 1.63 program (Scion Image). Data values are represented as mean ± SD for each group. *Statistical analysis performed by using the one-way ANOVA test showed highly significant differences among the groups (P = 0.000 for all genes, with the exception of ACAT-1 for whom the significance was P = 0.006).
Pearson's correlation coefficient (age vs mRNA levels of selected genes)
| C1 + C2 (n.25) | AD + FDR-AD (n.25) | |
|---|---|---|
| Neprilysin | r = -0,2233 | |
| p = 0,283 | ||
| ABCA-1 | r = -0,3503 | r = 0,2457 |
| p = 0,086 | p = 0,236 | |
| ACAT-1 | r = -03421 | |
| p = 0,094 | ||
| APP | ||
| BACE-1 | r = -0,3629 | |
| p = 0,075 | ||
| Cav-1 | r = 0,0718 | |
| p = 0,733 | ||
| HMGCoA-R | ||
| LDL-R | ||
| nCEH | r = -0,0151 | |
| p = 0,943 | ||
| SREBP-2 | r = -0,2629 | |
| p = 0,204 | ||
Significant statistical differences were indicated in bold
Figure 4Schematic representation of the data collected from the mRNA quantifications. The schemes represent the expression level, cellular compartment and metabolic network position of genes linked to cholesterol homeostasis and to APP processing. The arrows (↑↓) denote the significant (P < 0.05) differences (increase or decrease, respectively) between the two indicated groups, obtained by applying a Bonferroni's multiple comparison test following ANOVA.