mRNA PGC-1α levels in blood samples reliably correlates with its myocardial expression: study in patients undergoing cardiac surgery

et al.[Objective]: Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is a transcriptional coactivator that has been proposed to play a protective role in mouse models of cardiac ischemia and heart failure, suggesting that PGC-1α could be relevant as a prognostic marker. Our previous studies showed that the estimation of peripheral mRNA PGC-1α expression was feasible and that its induction correlated with the extent of myocardial necrosis and left ventricular remodeling in patients with myocardial infarction. In this study, we sought to determine if the myocardial and peripheral expressions of PGC-1α are well correlated and to analyze the variability of PGC-1α expression depending on the prevalence of some metabolic disorders. [Methods]: This was a cohort of 35 consecutive stable heart failure patients with severe aortic stenosis who underwent an elective aortic valve replacement surgery. mRNA PGC-1α expression was simultaneously determined from myocardial biopsy specimens and blood samples obtained during surgery by quantitative PCR, and a correlation between samples was made using the Kappa index. Patients were divided into two groups according to the detection of baseline expression levels of PGC-1α in blood samples, and comparisons between both groups were made by chi-square test or unpaired Student’s t-test as appropriate. [Results]: Based on myocardial biopsies, we found that mRNA PGC-1α expression in blood samples showed a statistically significant correlation with myocardial expression (Kappa index 0.66, p<0.001). The presence of higher systemic PGC-1α expression was associated with a greater expression of some target genes such as silent information regulator 2 homolog-1 (x-fold expression in blood samples: 4.43±5.22 vs. 1.09±0.14, p=0.044) and better antioxidant status in these patients (concentration of Trolox: 0.40±0.05 vs. 0.34±0.65, p=0.006). [Conclusions]: Most patients with higher peripheral expression also had increased myocardial expression, so we conclude that the non-invasive estimation of mRNA PGC-1α expression from blood samples provides a good approach of the constitutive status of the mitochondrial protection system regulated by PGC-1α and that this could be used as prognostic indicator in cardiovascular disease.Grant from Sociedad Valenciana de Cardiología, 2013 to Óscar Fabregat-Andrés.Peer Reviewe

Hierarchical clustering of miRNA expression.

<p>miRNA profiles of 36 paired tissue specimens from 19 colorectal cancer (orange box) and 17 pancreatic cancer (green box) patients were clustered. The 36 paired specimens are in rows (coloured bars) and the 866 miRNAs are in columns. <b>T</b>, tumor tissue; <b>N</b>, adjacent normal tissue.</p

Differentially regulated miRs in CRC and in PC vs. matched respective normal tissues.

<p>Differentially regulated miRs in CRC and in PC vs. matched respective normal tissues.</p

Multidimensional scaling plot.

<p>Proximity matrices from random forest analysis, where <i>x-</i> and <i>y-</i> axes are the multidimensional scaling coordinates. Subjects with similar miRNA expressions are represented by points close one to the other, whereas subjects with dissimilar miRNA expressions are represented by separated points. Red = tumor tissue, Black = adjacent normal tissue.</p

MicroRNAs selected by t-test in PC.

<p>Thirty-four miRs deregulated in tumoral compared to matched normal tissue and selected by p<0.01. Thirty overexpressed miRNAs in cancer are indicated by positive fold-change; four down-regulated miRNAs are indicated by negative fold-change.</p>§<p>: Tumour vs Normal tissue.</p

CRC and PC network.

<p>Green points depict the nodes corresponding to 24 miRNAs of CRC network and 23 miRNAs of PC network. The edges characterize the significant correlations, whose thickness reflects Spearman Correlation Coefficients (blue and green edges are used for positive and negative correlations respectively). In CRC network, as shown in panel <b>A</b>, m<i>iR-195, miR-28-3p, miR-1280, miR-18a</i> and <i>miR-1246</i> exhibit the highest <i>weighted</i> degree rank. No correlation is found for <i>miR-106a</i>. <i>MiR-1246</i> has also the highest <i>betweenness</i> rank. In PC network, as shown in panel <b>B</b>, <i>miR-103, miR-23a</i> and <i>miR-15b</i> have the highest <i>degrees</i> and are all linked to <i>miR-199a-3p</i> as well as to each other forming a four nodes <i>clique</i>. In addition, the removal of these nodes causes the deepest drop of the average clustering coefficient rank. <i>MiR-384</i> exhibits the highest betweenness centrality measure.</p

Merged results.

<p>For both tissues a significant overlap among detected miRNAs was found by merging t-test and RF results. A group of 24 miRNAs, whose expression was significantly altered in colorectal tumors, were obtained intersecting the list of first 42 miRNAs with best p-values, from t-test analysis, with those at highest MDA, from RF analysis. In the same fashion, 23 miRNAs with altered expression were selected in pancreatic tumors. * p<0.001; § RF>4.3; **p<0.05; # RF>0.94.</p

Variable Importance table.

<p>Mean Decrease in Accuracy (MDA) as a measure of miRNA importance in classifying tumor tissues from normal ones estimated by random forest analysis. The first 42 most important miRNAs in colorectal cancer (panel <b>A</b>) and 50 miRNAs in pancreatic cancer (panel <b>B</b>) are shown.</p

MicroRNAs selected by t-test in CRC.

<p>Forty-two miRs deregulated in tumoral compared to matched normal tissue and selected by p<0.001. Twenty-five overexpressed miRs in cancer are indicated by positive fold-change; seventeen down-regulated miRs are indicated by negative fold-change.</p>§<p>: Tumour vs Normal tissue.</p

Additional file 4: Table S4. of Association between polymorphisms of TAS2R16 and susceptibility to colorectal cancer

Description of data Association between colon/rectalcancer risk and SNPs in the TAS2R16 region considering only Italy. (DOCX 17 kb