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Recently, we have shown that SARS-CoV-2 Omicron virus isolates are less effective at inhibiting the host cell interferon response than Delta viruses. Here, we present further evidence that reduced interferon-antagonising activity explains at least in part why Omicron variant infections are inherently less severe than infections with other SARS-CoV-2 variants. Most importantly, we here also show that Omicron variant viruses display enhanced sensitivity to interferon treatment, which makes interferons promising therapy candidates for Omicron patients, in particular in combination with other antiviral agents.
The SARS-CoV-2 Omicron variant is currently causing a large number of infections in many countries. A number of antiviral agents are approved or in clinical testing for the treatment of COVID-19. Despite the high number of mutations in the Omicron variant, we here show that Omicron isolates display similar sensitivity to eight of the most important anti-SARS-CoV-2 drugs and drug candidates (including remdesivir, molnupiravir, and PF-07321332, the active compound in paxlovid), which is of timely relevance for the treatment of the increasing number of Omicron patients. Most importantly, we also found that the Omicron variant displays a reduced capability of antagonising the host cell interferon response. This provides a potential mechanistic explanation for the clinically observed reduced pathogenicity of Omicron variant viruses compared to Delta variant viruses.
Graph data is an omnipresent way to represent information in machine learning. Especially, in neuroscience research, data from Diffusion-Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI) is commonly represented as graphs. Exploiting the graph structure of these modalities using graph-specific machine learning applications is currently hampered by the lack of easy-to-use software. PHOTONAI Graph aims to close the gap between domain experts of machine learning, graph experts and neuroscientists. Leveraging the rapid machine learning model development features of the Python machine learning API PHOTONAI, PHOTONAI Graph enables the design, optimization, and evaluation of reliable graph machine learning models for practitioners. As such, it provides easy access to custom graph machine learning pipelines including, hyperparameter optimization and algorithm evaluation ensuring reproducibility and valid performance estimates. Integrating established algorithms such as graph neural networks, graph embeddings and graph kernels, it allows researchers without significant coding experience to build and optimize complex graph machine learning models within a few lines of code. We showcase the versatility of this toolbox by building pipelines for both resting–state fMRI and DTI data in the hope that it will increase the adoption of graph-specific machine learning algorithms in neuroscience research.
The new variant of concern (VOC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Omicron (B.1.1.529), is genetically very different from other VOCs. We compared Omicron with the preceding VOC Delta (B.1.617.2) and the wildtype strain (B.1) with respect to their interactions with the antiviral type I interferon (IFN-alpha/beta) response in infected cells. Our data indicate that Omicron has gained an elevated capability to suppress IFN-beta induction upon infection and to better withstand the antiviral state imposed by exogenously added IFN-alpha.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
Endothelial tip cells are essential for VEGF-induced angiogenesis, but underlying mechanisms are elusive. Endothelial-specific deletion of EVL, a member of the mammalian Ena/VASP protein family, reduced the expression of the tip cell marker protein endothelial cell specific molecule-1 (Esm1) and compromised the radial sprouting of the vascular plexus in the postnatal mouse retina. The latter effects could at least partly be attributed to reduced VEGF receptor 2 (VEGFR2) internalization and signaling but the underlying mechanisms(s) are not fully understood. In the present study, we revealed that the expression of the long non-coding RNA H19 was significantly reduced in endothelial cells from postnatal EVL-/- mice and in siRNA-transfected human endothelial cells under hypoxic conditions. H19 was recently shown to promote VEGF expression and bioavailability via Esm1 and hypoxia inducible factor 1α (HIF-1α). Similar to EVL-/- mice, the radial outgrowth of the vascular plexus was significantly delayed in the postnatal retina of H19-/- mice. In summary, our data suggests that loss of EVL not only impairs VEGFR2 internalition and downstream signaling, but also impairs VEGF expression and bioavailability in the hypoxic retina via downregulation of lncRNA H19.
At present, there are no quantitative, objective methods for diagnosing the Parkinson disease. Existing methods of quantitative analysis by myograms suffer by inaccuracy and patient strain; electronic tablet analysis is limited to the visible drawing, not including the writing forces and hand movements. In our paper we show how handwriting analysis can be obtained by a new electronic pen and new features of the recorded signals. This gives good results for diagnostics. Keywords: Parkinson diagnosis, electronic pen, automatic handwriting analysis
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
Background: Microvolt T-wave alternans (MTWA) testing in many studies has proven to be a highly accurate predictor of ventricular tachyarrhythmic events (VTEs) in patients with risk factors for sudden cardiac death (SCD) but without a prior history of sustained VTEs (primary prevention patients). In some recent studies involving primary prevention patients with prophylactically implanted cardioverter-defibrillators (ICDs), MTWA has not performed as well.
Objective: This study examined the hypothesis that MTWA is an accurate predictor of VTEs in primary prevention patients without implanted ICDs, but not of appropriate ICD therapy in such patients with implanted ICDs.
Methods: This study identified prospective clinical trials evaluating MTWA measured using the spectral analytic method in primary prevention populations and analyzed studies in which: (1) few patients had implanted ICDs and as a result none or a small fraction (≤15%) of the reported end point VTEs were appropriate ICD therapies (low ICD group), or (2) many of the patients had implanted ICDs and the majority of the reported end point VTEs were appropriate ICD therapies (high ICD group).
Results: In the low ICD group comprising 3,682 patients, the hazard ratio associated with a nonnegative versus negative MTWA test was 13.6 (95% confidence interval [CI] 8.5 to 30.4) and the annual event rate among the MTWA-negative patients was 0.3% (95% CI: 0.1% to 0.5%). In contrast, in the high ICD group comprising 2,234 patients, the hazard ratio was only 1.6 (95% CI: 1.2 to 2.1) and the annual event rate among the MTWA-negative patients was elevated to 5.4% (95% CI: 4.1% to 6.7%). In support of these findings, we analyzed published data from the Multicenter Automatic Defibrillator Trial II (MADIT II) and Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) trials and determined that in those trials only 32% of patients who received appropriate ICD therapy averted an SCD.
Conclusion: This study found that MTWA testing using the spectral analytic method provides an accurate means of predicting VTEs in primary prevention patients without implanted ICDs; in particular, the event rate is very low among such patients with a negative MTWA test. In prospective trials of ICD therapy, the number of patients receiving appropriate ICD therapy greatly exceeds the number of patients who avert SCD as a result of ICD therapy. In trials involving patients with implanted ICDs, these excess appropriate ICD therapies seem to distribute randomly between MTWA-negative and MTWA-nonnegative patients, obscuring the predictive accuracy of MTWA for SCD. Appropriate ICD therapy is an unreliable surrogate end point for SCD.
Motivation DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding.
Results We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy.
Availability An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/FAME.