The rapid integration of genomic technologies in clinical diagnostics has resulted in the detection of a multitude of missense variants whose clinical significance is often unknown. As a result, a plethora of computational tools have been developed to facilitate variant interpretation. However, choosing an appropriate software from such a broad range of tools can be challenging; therefore, systematic benchmarking with high-quality, independent datasets is critical. Using three independent benchmarking datasets compiled from the ClinVar database, we evaluated the performance of ten widely used prediction algorithms with missense variants from 21 clinically relevant genes, including BRCA1 and BRCA2. A fourth dataset consisting of 1053 missense variants was also used to investigate the impact of type 1 circularity on their performance. The performance of the prediction algorithms varied widely across datasets. Based on Matthews Correlation Coefficient and Area Under the Curve, SNPs&GO and PMut consistently displayed an overall above-average performance across the datasets. Most of the tools demonstrated greater sensitivity and negative predictive values at the expense of lower specificity and positive predictive values. We also demonstrated that type 1 circularity significantly impacts the performance of these tools and, if not accounted for, may confound the selection of the best performing algorithms.

Background: Gut microbiome composition may influence the risk of intracranial aneurysm rupture. Methods: This study analyzed the gut microbiota of 48 patients—24 with ruptured aneurysms (RA) and 24 with unruptured intracranial aneurysms (UIA)—using next-generation sequencing. Results: While alpha diversity was similar between groups, beta diversity revealed significant taxonomic differences (Bray–Curtis: p = 0.02; unweighted UniFrac: p = 0.0291). Both groups were dominated by the phyla Bacillota, Bacteroidota, and Proteobacteria, but genus- and family-level differences were observed. RA patients showed higher abundances of Anaerotruncus, Coprobacillus, Sellimonas, Hungatella, and Ruthenibacterium, whereas UIA patients exhibited greater levels of Faecalibacterium, Brotolimicola, Clostridiaceae, Roseburia, and Agathobaculum. Linear discriminant analysis identified one class, 10 genera, and 17 species that differed significantly between groups. Notably, Faecalibacterium prausnitzii and Agathobaculum butyriciproducens—bacteria known for their anti-inflammatory and neuroprotective properties—were enriched in UIA patients. Conclusions: These findings suggest that gut microbiota, particularly short-chain fatty acid–producing bacteria, may contribute to vascular protection and aneurysm pathophysiology. Microbiome-based therapeutic strategies could offer new avenues for the prevention of cerebrovascular disease.

Alterations to intestinal microbiota are assumed to occur in the pathogenesis of inflammatory bowel disease (IBD). This study aims to analyze the association of fecal microbiota composition, body composition, and lipid characteristics in patients with Crohn’s disease (CD). In our cross-sectional study, patients with CD were enrolled and blood and fecal samples were collected. Clinical and endoscopic disease activity and body composition were assessed and laboratory tests were made. Fecal bacterial composition was analyzed using the shotgun method. Microbiota alterations based on obesity, lipid parameters, and disease characteristics were analyzed. In this study, 27 patients with CD were analyzed, of which 37.0% were obese based on visceral fat area (VFA). Beta diversities were higher in non-obese patients (p < 0.001), but relative abundances did not differ. C. innocuum had a higher abundance at a high cholesterol level than Bacillota (p = 0.001, p = 0.0034). Adlercreutzia, B. longum, and Blautia alterations were correlated with triglyceride levels. Higher Clostridia (p = 0.009) and B. schinkii (p = 0.032) and lower Lactobacillus (p = 0.035) were connected to high VFA. Disease activity was coupled with dysbiotic elements. Microbiota alterations in obesity highlight the importance of gut microbiota in diseases with a similar inflammatory background and project therapeutic options.