Complex reinnervation pattern after unilateral renal denervation in rats.

Renal denervation (DNX) is a treatment for resistant arterial hypertension. Efferent sympathetic nerves regrow, but reinnervation by renal afferent nerves has only recently been shown in the renal pelvis of rats after unilateral DNX. We examined intrarenal perivascular afferent and sympathetic efferent nerves after unilateral surgical DNX. Tyrosine hydroxylase (TH), CGRP, and smooth muscle actin were identified in kidney sections from 12 Sprague-Dawley rats, to distinguish afferents, efferents, and vasculature. DNX kidneys and nondenervated kidneys were examined 1, 4, and 12 wk after DNX. Tissue levels of CGRP and norepinephrine (NE) were measured with ELISA and mass spectrometry, respectively. DNX decreased TH and CGRP labeling by 90% and 95%, respectively (P < 0.05) within 1 wk. After 12 wk TH and CGRP labeling returned to baseline with a shift toward afferent innervation (P < 0.05). Nondenervated kidneys showed a doubling of both labels within 12 wk (P < 0.05). CGRP content decreased by 72% [3.2 ± 0.3 vs. 0.9 ± 0.2 ng/gkidney; P < 0.05] and NA by 78% [1.1 ± 0.1 vs. 0.2 ± 0.1 pmol/mgkidney; P < 0.05] 1 wk after DNX. After 12 wk, CGRP, but not NE, content in DNX kidneys was fully recovered, with no changes in the nondenervated kidneys. The use of phenol in the DNX procedure did not influence this result. We found morphological reinnervation and transmitter recovery of afferents within 12 wk after DNX. Despite morphological evidence of sympathetic regrowth, NE content did not fully recover. These results suggest a long-term net surplus of afferent influence on the DNX kidney may be contributing to the blood pressure lowering effect of DNX.

Joint multi-omics discriminant analysis with consistent representation learning using PANDA.

Integrative multi-omics analysis provides deeper insight and enables better and more realistic modeling of the underlying biology and causes of diseases than does single omics analysis. Although several integrative multi-omics analysis methods have been proposed and demonstrated promising results in integrating distinct omics datasets, inconsistent distribution of the different omics data, which is caused by technology variations, poses a challenge for paired integrative multi-omics methods. In addition, the existing discriminant analysis-based integrative methods do not effectively exploit correlation and consistent discriminant structures, necessitating a compromise between correlation and discrimination in using these methods. Herein we present PAN-omics Discriminant Analysis (PANDA), a joint discriminant analysis method that seeks omics-specific discriminant common spaces by jointly learning consistent discriminant latent representations for each omics. PANDA jointly maximizes between-class and minimizes within-class omics variations in a common space and simultaneously models the relationships among omics at the consistency representation and cross-omics correlation levels, overcoming the need for compromise between discrimination and correlation as with the existing integrative multi-omics methods. Because of the consistency representation learning incorporated into the objective function of PANDA, this method seeks a common discriminant space to minimize the differences in distributions among omics, can lead to a more robust latent representations than other methods, and is against the inconsistency of the different omics. We compared PANDA to 10 other state-of-the-art multi-omics data integration methods using both simulated and real-world multi-omics datasets and found that PANDA consistently outperformed them while providing meaningful discriminant latent representations. PANDA is implemented using both R and MATLAB, with codes available at https://github.com/WuLabMDA/PANDA.

Shared Nearest Neighbors Approach and Interactive Browser for Network Analysis of a Comprehensive Non-Small-Cell Lung Cancer Data Set.

PURPOSE: Advances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining. METHODS: We present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project. RESULTS: Benchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype. CONCLUSION: The network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.

Disproportional decrease in office blood pressure compared with 24-hour ambulatory blood pressure with antihypertensive treatment: dependency on pretreatment blood pressure levels.

The long-term relationship between 24-hour ambulatory blood pressure (ABP) and office BP in patients on therapy is not well documented. From a registry we included all patients in whom antihypertensive therapy needed to be uptitrated. Drug treatment included the direct renin inhibitor aliskiren or an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker or drugs not blocking the renin-angiotensin system, alone or on top of an existing drug regimen. In all patients, office BP and 24-hour ABP were obtained at baseline and after 1 year with validated devices. In the study population of 2722 patients, there was a good correlation between the change in office BP and 24-hour ABP (systolic: r=0.39; P<0.001; diastolic: r=0.34; P<0.001). However, the numeric decrease in office BP did not correspond to the decrease in ABP in a 1:1 fashion, for example, a decrease of 10, 20, and 30 mm Hg corresponded to a decrease of ≈7.2, 10.5, and 13.9 mm Hg in systolic ABP, respectively. The disproportionally greater decrease in systolic office BP compared with ABP was dependent on the level of the pretreatment BP, which was consistently higher for office BP than ABP. The white coat effect (difference between office BP and ABP) was on average 10/5 mm Hg lower 1 year after intensifying treatment and the magnitude of that was also dependent on pretreatment BP. There was a disproportionally greater decrease in systolic office BP than in ABP, which for both office BP and ABP seemed to depend on the pretreatment BP level.