Effects of intrarenal afferent stimulation by bradykinin on renal sympathetic nerve activity: tonic inhibition contributing to renal function - Eva Hutter; Tilmann Ditting; Martin Hindermann; Karl F. Hilgers; Roland E. Schmieder; Christian Morath; Mario Schiffer; Kerstin Amann; Roland Veelken; Kristina Rodionova (Pflügers Archiv - European Journal of Physiology, 2025)
Bradykinin (BK) may increase renal sodium excretion by decreasing tubular ENaC activity. Afferent renal nerve activity (ARNA) putatively controls renal sympathetic nerve activity (RSNA) involved in renal sodium handling. We recently found tonic sympatho-inhibition due to intrarenal ARNA stimulation by the TRPV1 agonist capsaicin (CAP). Since BK is known to augment TRPV1 effects, we hypothesized that intrarenally applied BK also tonically inhibits RSNA. Four groups of rats (n = 8; BK, CAP, HOE + BK, NaCl-control) were equipped with arterial and venous catheters for blood pressure (BP) and heart rate (HR) recordings and drug application; bipolar electrodes for RSNA and ARNA recordings, renal arterial catheter for intrarenal administration (IRA) of bradykinin (BK: 10 −5 M, 20 µl and 10 –4 M; 2.5, 5, 10 µl), capsaicin (CAP 3.3, 6.6, 10 and 33*10 −7 M, 10 µl). The B2-receptor antagonist HOE-140 (10 –4 M, 40 µl) was administered intravenously (IV) just before IRA BK (HOE + BK), finally the NK 1 -receptor blocker RP67580 (10 −2 M, 15 µl; IV) was applied in all groups at the end of the experiment. IRA BK and CAP momentarily increased ARNA. IRA CAP, IRA BK, and IRA HOE + BK, decreased RSNA from 4.2 ± 0.8 to 1.3 ± 0.2 µV*sec (BK, P < 0.01), 3.6 ± 0.5 to 0.9 ± 0.2 µV*sec (CAP, P < 0.01) and 3.2 ± 0.3 to 0.8 ± 0.1 µV*sec (HOE-BK, P < 0.01). Suppressed RSNA (BK, CAP, HOE + BK) was unmasked by IV RP67580: 1.6 ± 0.5 to 8.6 ± 2.9 µV*sec (BK, P < 0.01); 1.0 ± 0.2 to 6.1 ± 1.5 µV*sec (CAP, P < 0.01); 0.8 ± 0.2 to 4.5 ± 0.8 µV*sec (HOE-BK, P < 0.05). IRA BK was associated with momentary increases of RSNA, abolished by HOE-140. Intrarenal stimulation of renal afferent nerves by BK induced tonic renal sympathodepression likely augmenting sodium and water excretion.

SCAview: an Intuitive Visual Approach to the Integrative Analysis of Clinical Data in Spinocerebellar Ataxias - Mischa Uebachs; Philipp Wegner; Sebastian Schaaf; Simon Kugai; Heike Jacobi; Sheng-Han Kuo; Tetsuo Ashizawa; Juliane Fluck; Sophie Tezenas du Montcel; Peter Bauer; Paola Giunti; Arron Cook; et al. (The Cerebellum, 2023)
With SCAview, we present a prompt and comprehensive tool that enables scientists to browse large datasets of the most common spinocerebellar ataxias intuitively and without technical effort. Basic concept is a visualization of data, with a graphical handling and filtering to select and define subgroups and their comparison. Several plot types to visualize all data points resulting from the selected attributes are provided. The underlying synthetic cohort is based on clinical data from five different European and US longitudinal multicenter cohorts in spinocerebellar ataxia type 1, 2, 3, and 6 (SCA1, 2, 3, and 6) comprising > 1400 patients with overall > 5500 visits. First, we developed a common data model to integrate the clinical, demographic, and characterizing data of each source cohort. Second, the available datasets from each cohort were mapped onto the data model. Third, we created a synthetic cohort based on the cleaned dataset. With SCAview, we demonstrate the feasibility of mapping cohort data from different sources onto a common data model. The resulting browser-based visualization tool with a thoroughly graphical handling of the data offers researchers the unique possibility to visualize relationships and distributions of clinical data, to define subgroups and to further investigate them without any technical effort. Access to SCAview can be requested via the Ataxia Global Initiative and is free of charge.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Diffusion Kurtosis Imaging Detects Microstructural Alterations in Brain of α-Synuclein Overexpressing Transgenic Mouse Model of Parkinson’s Disease: A Pilot Study - Amit Khairnar; Peter Latta; Eva Drazanova; Jana Ruda-Kucerova; Nikoletta Szabó; Anas Arab; Birgit Hutter-Paier; Daniel Havas; Manfred Windisch; Alexandra Sulcova; Zenon Starcuk; Irena Rektorova (Neurotoxicity Research, 2015)