Pulse pressure amplification and its determinants

<div><p><i>Background</i>. Pulse pressure (PP) amplification expressed as the peripheral-to-central PP ratio has gained importance in the assessment of cardiovascular phenotypes and cardiovascular risk. The aim of the present study was to assess the relationship between PP amplification, large vessel parameters and peripheral blood pressure (BP) to gain insights into the amplification phenomenon. <i>Methods</i>. Peripheral BP, central BP and carotid-femoral pulse wave velocity (cfPWV) were assessed using the OMRON M6, SphygmoCor and Complior devices, respectively, in 741 adults attending the hypertension outpatient clinic. Analysis of covariance, partial correlations and multiple linear regression models were performed to assess the relationship between PP amplification, peripheral BP and cfPWV. <i>Results</i>. PP amplification was inversely related to BP group. Women showed lower PP amplification than men (1.24 ± 0.18 and 1.35 ± 0.18, respectively, <i>p</i> < 0.001). Age, female gender and mean arterial pressure were inversely associated with PP amplification (<i>p</i> < 0.001), whereas heart rate and body mass index showed positive associations (<i>p</i> < 0.001 and <i>p</i> = 0.049, respectively). cfPWV was a predictor of PP amplification in men but not in women (<i>p</i> = 0.006 and <i>p</i> = 0.424, respectively). <i>Conclusions</i>. PP amplification is related to BP: the higher the BP, the lower the PP amplification. Gender, age and body composition have a significant impact on PP amplification.</p></div

Comparison of fold-change expression of microRNAs between urinary fractions from patients with systemic lupus erythematosus.

<p>The level of the four miRNAs species miR-335*, miR-302d, miR-200c and miR-146a was quantitatively assayed and compared between urine fractions, cell-free urine (CFU), exosome-depleted supernatant (Sn) and exosomes (Exo), in systemic lupus erythematosus with individual TaqMan miRNA Assays. Spiked-in cel-miR-39 was used as the normalization control for all samples. The graphs represents relative miRNA fold change by the 2^-ΔΔCt method. Data represents the mean ± SEM. *p<0.05; **p<0.01.</p

Baseline clinical data of the study subjects.

<p>The data are expressed as the mean ± SD, unless noted otherwise. C3: complement 3, C4: complement 4; GFR: glomerular filtration rate; LN: lupus nephritis; SLE: systemic lupus erythematosus; SLEDAI: SLE activity index.</p><p>*p<0.05 compared to controls</p><p>**p<0.01 compared to controls</p><p>†p<0.05 compared to Active Lupus Nephritis</p><p>^‡p<0.01 compared to Active Lupus Nephritis</p><p>Baseline clinical data of the study subjects.</p

Characterization of urinary exosomes isolated by ultracentrifugation.

<p>(A) Transmission electron microscopy (TEM) micrographs of exosome isolations stained by uranyl acetate. Bar represents 200 μm. (B), size distribution (mean ± SD) of urinary exosomes. A total of 10 micrographs for two samples were analysed. (C), Western immunoblotting of exosomes isolated from urine using exosomal markers such as Tsg101 and CD9, and non-exosomal markers such as calnexin (endoplasmic reticulum), nucleoporin p62 (nucleus) and GM-130 (Golgi apparatus) in the individual urine fractions: whole urine (WU), exosome-depleted supernatant from the 160,000 g spin (Sn), cell-free urine (CFU) and exosome pellet (Exo). Whole-cell lysates from HuH7 cells were loaded as a positive control sample.</p

Urinary miRNA quantification and comparison among urine components in systemic lupus erythematosus groups.

<p>The level of the miRNAs was compared in the different urine fractions, cell-free urine (CFU), exosome-depleted supernatant (Sn) and exosomes (Exo), in controls (A), active lupus nephritis (B), inactive lupus nephritis (C) and systemic lupus erythematosus with the absence of lupus nephritis (D). Spiked-in cel-miR-39 was used as the normalization control for all samples. Left data graphs are expressed as absolute differences (Ct) and the right graphs as relative miRNA fold change by the 2^-ΔΔCt method. Data represents the mean ± SEM. *p<0.05; **p<0.01.</p

Representative Bioanalyzer profiles of urine fractions using the Agilent RNA Pico Chip.

<p>(A), the small RNAs were dominant in the exosomal RNAs. (B), Bioanalyzer electropherograms from the various urine components, cell-free urine (CFU), exosome-depleted supernatant (Sn) and exosomes (Exo). (C), Total RNA cell pellets from urine, as determined also by an RNA Pico Chip. Large RNA species (18S and 28S) were slightly detected in cell pellets, suggesting degradation of cellular RNA.</p

Comparison of miRNAs between control and pathological groups in each individual fractions of urine.

<p>The level of the four miRNAs species miR-335*, miR-302d, miR-200c and miR-146a were compared among controls, active lupus nephritis (active LN), inactive lupus nephritis (inactive LN) and systemic lupus erythematosus in the absence of lupus nephritis (absence LN) in each urinary individual component: (A), exosomes (Exo); (B), cell-free urine (CFU); (C), exosome-depleted supernatant (Sn). Left data graphs are expressed as absolute differences (Ct) and right graphs as relative miRNA fold change (2^-ΔΔCt). Spiked-in cel-miR-39 was used as normalization control for all samples. Each data represents mean ± SEM. *p<0.05; **p<0.01, ***p<0.001 compared to controls.</p

Relative microRNAs expression in urinary fractions from patients with systemic lupus erythematosus respect to controls.

<p>Level of the four miRNAs species miR-335*, miR-302d, miR-200c and miR-146a among controls and systemic lupus erythematosus patients in each urinary individual component: (A), exosomes (Exo); (B), cell-free urine (CFU); (C), exosome-depleted supernatant (Sn). The graphs represents relative miRNA fold change by the 2^-ΔΔCt method. Data represents the mean ± SEM. *p<0.05; **p<0.01, ***p<0.001.</p

Supplemental Material - Towards a personalized health care using a divisive hierarchical clustering approach for comorbidity and the prediction of conditioned group risks

Supplemental Material for Towards a personalized health care using a divisive hierarchical clustering approach for comorbidity and the prediction of conditioned group risks by J Ramón Navarro-Cerdán, Manuel Sánchez-Gomis, Patricia Pons, Santiago Gálvez-Settier, Francisco Valverde, Ana Ferrer-Albero, Inmaculada Saurí, Antonio Fernández and Josep Redon in Health Informatics Journal</p

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors

<div><p>Background</p><p>To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population.</p><p>Methods and Findings</p><p>One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by ¹H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of <i>Group 3</i> and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of <i>Group 3</i> and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.</p><p>Conclusions</p><p>The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.</p></div