Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure.

BACKGROUND: Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and validate a novel, machine-learning-derived model to predict cardiovascular mortality risk using office blood pressure (OBP) and ambulatory blood pressure (ABP). METHODS: The performance of the novel risk score was compared with existing risk scores, and the possibility of predicting ABP phenotypes utilizing clinical variables was assessed. Using data from 59 124 patients enrolled in the Spanish ABP Monitoring registry, machine-learning approaches (logistic regression, gradient-boosted decision trees, and deep neural networks) and stepwise forward feature selection were used. RESULTS: For the prediction of cardiovascular mortality, deep neural networks yielded the highest clinical performance. The novel mortality prediction models using OBP and ABP outperformed other risk scores. The area under the curve achieved by the novel approach, already when using OBP variables, was significantly higher when compared with the area under the curve of the Framingham risk score, Systemic Coronary Risk Estimation 2, and Atherosclerotic Cardiovascular Disease score. However, the prediction of cardiovascular mortality with ABP instead of OBP data significantly increased the area under the curve (0.870 versus 0.865; P=3.61×10-28), accuracy, and specificity, respectively. The prediction of ABP phenotypes (ie, white-coat, ambulatory, and masked hypertension) using clinical characteristics was limited. CONCLUSIONS: The receiver operating characteristic curves for cardiovascular mortality using ABP and OBP with deep neural network models outperformed all other risk metrics, indicating the potential for improving current risk scores by applying state-of-the-art machine learning approaches. The prediction of cardiovascular mortality using ABP data led to a significant increase in area under the curve and performance metrics.

SingmiR: a single-cell miRNA alignment and analysis tool.

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues.

Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

Cas9-mediated knockout of Ndrg2 enhances the regenerative potential of dendritic cells for wound healing.

Chronic wounds impose a significant healthcare burden to a broad patient population. Cell-based therapies, while having shown benefits for the treatment of chronic wounds, have not yet achieved widespread adoption into clinical practice. We developed a CRISPR/Cas9 approach to precisely edit murine dendritic cells to enhance their therapeutic potential for healing chronic wounds. Using single-cell RNA sequencing of tolerogenic dendritic cells, we identified N-myc downregulated gene 2 (Ndrg2), which marks a specific population of dendritic cell progenitors, as a promising target for CRISPR knockout. Ndrg2-knockout alters the transcriptomic profile of dendritic cells and preserves an immature cell state with a strong pro-angiogenic and regenerative capacity. We then incorporated our CRISPR-based cell engineering within a therapeutic hydrogel for in vivo cell delivery and developed an effective translational approach for dendritic cell-based immunotherapy that accelerated healing of full-thickness wounds in both non-diabetic and diabetic mouse models. These findings could open the door to future clinical trials using safe gene editing in dendritic cells for treating various types of chronic wounds.

Ageing-associated small RNA cargo of extracellular vesicles.

Previous work on murine models and humans demonstrated global as well as tissue-specific molecular ageing trajectories of RNAs. Extracellular vesicles (EVs) are membrane vesicles mediating the horizontal transfer of genetic information between different tissues. We sequenced small regulatory RNAs (sncRNAs) in two mouse plasma fractions at five time points across the lifespan from 2-18 months: (1) sncRNAs that are free-circulating (fc-RNA) and (2) sncRNAs bound outside or inside EVs (EV-RNA). Different sncRNA classes exhibit unique ageing patterns that vary between the fcRNA and EV-RNA fractions. While tRNAs showed the highest correlation with ageing in both fractions, rRNAs exhibited inverse correlation trajectories between the EV- and fc-fractions. For miRNAs, the EV-RNA fraction was exceptionally strongly associated with ageing, especially the miR-29 family in adipose tissues. Sequencing of sncRNAs and coding genes in fat tissue of an independent cohort of aged mice up to 27 months highlighted the pivotal role of miR-29a-3p and miR-29b-3p in ageing-related gene regulation that we validated in a third cohort by RT-qPCR.

miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations.

MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in regulating diverse biological processes. Extracting functional insights from a list of miRNAs is challenging, as each miRNA can potentially interact with hundreds of genes. To address this challenge, we developed miEAA, a flexible and comprehensive miRNA enrichment analysis tool based on direct and indirect miRNA annotation. The latest release of miEAA includes a data warehouse of 19 miRNA repositories, covering 10 different organisms and 139 399 functional categories. We have added information on the cellular context of miRNAs, isomiRs, and high-confidence miRNAs to improve the accuracy of the results. We have also improved the representation of aggregated results, including interactive Upset plots to aid users in understanding the interaction among enriched terms or categories. Finally, we demonstrate the functionality of miEAA in the context of ageing and highlight the importance of carefully considering the miRNA input list. MiEAA is free to use and publicly available at https://www.ccb.uni-saarland.de/mieaa/.

isomiRdb: microRNA expression at isoform resolution.

A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients' samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.

Ischemic Stroke-A Scientometric Analysis.

Background: Stroke is the second leading cause of death world-wide. A comprehensive scientometric study regarding ischemic stroke research has not been performed yet. This study aims at investigating the global research output on ischemic stroke research. Methods: All 21,115 articles regarding ischemic stroke were retrieved from the Web-of-Science-Core-Collection and analyzed regarding regional differences, the authors' sex, subtopics of stroke, as well as international research collaborations. Results: A total of 132 different countries participated, with the USA contributing most publications with 4,614 (21.9%), followed by China with 3,872 (18.3%), and Germany with 1,120 (5.3%). Analyzing the scientific quality of different countries by H-index, the USA ranked first with an H-index of 202, followed by Germany (H-index 135) and the United Kingdom (UK;H-index 129). The most frequently used topic was "Clinical Neurology" with 9,028 publications. Among all first authors attributed to their sex, 32.3% of all first authors were female and 67.7% were male (4,335 vs. 9,097). The proportion of female last authors was comparatively lower at 22.4% (3,083 publications) compared with 77.6% male authors (10,658 publications). There was a broad network of international collaborations. Conclusions: Research in ischemic stroke has substantially increased over time. Scientists from the USA have the highest number of publications, followed by China and Germany. Measured by the H-index, the USA held the highest publication quality, followed by Germany and the UK. The scientific landscape was male-dominated with 67.7% of all first authors being male. Worldwide international collaborations play a major role in ischemic stroke research.

Disrupting mechanotransduction decreases fibrosis and contracture in split-thickness skin grafting.

Burns and other traumatic injuries represent a substantial biomedical burden. The current standard of care for deep injuries is autologous split-thickness skin grafting (STSG), which frequently results in contractures, abnormal pigmentation, and loss of biomechanical function. Currently, there are no effective therapies that can prevent fibrosis and contracture after STSG. Here, we have developed a clinically relevant porcine model of STSG and comprehensively characterized porcine cell populations involved in healing with single-cell resolution. We identified an up-regulation of proinflammatory and mechanotransduction signaling pathways in standard STSGs. Blocking mechanotransduction with a small-molecule focal adhesion kinase (FAK) inhibitor promoted healing, reduced contracture, mitigated scar formation, restored collagen architecture, and ultimately improved graft biomechanical properties. Acute mechanotransduction blockade up-regulated myeloid CXCL10-mediated anti-inflammation with decreased CXCL14-mediated myeloid and fibroblast recruitment. At later time points, mechanical signaling shifted fibroblasts toward profibrotic differentiation fates, and disruption of mechanotransduction modulated mesenchymal fibroblast differentiation states to block those responses, instead driving fibroblasts toward proregenerative, adipogenic states similar to unwounded skin. We then confirmed these two diverging fibroblast transcriptional trajectories in human skin, human scar, and a three-dimensional organotypic model of human skin. Together, pharmacological blockade of mechanotransduction markedly improved large animal healing after STSG by promoting both early, anti-inflammatory and late, regenerative transcriptional programs, resulting in healed tissue similar to unwounded skin. FAK inhibition could therefore supplement the current standard of care for traumatic and burn injuries.

BusyBee Web: towards comprehensive and differential composition-based metagenomic binning.

Despite recent methodology and reference database improvements for taxonomic profiling tools, metagenomic assembly and genomic binning remain important pillars of metagenomic analysis workflows. In case reference information is lacking, genomic binning is considered to be a state-of-the-art method in mixed culture metagenomic data analysis. In this light, our previously published tool BusyBee Web implements a composition-based binning method efficient enough to function as a rapid online utility. Handling assembled contigs and long nanopore generated reads alike, the webserver provides a wide range of supplementary annotations and visualizations. Half a decade after the initial publication, we revisited existing functionality, added comprehensive visualizations, and increased the number of data analysis customization options for further experimentation. The webserver now allows for visualization-supported differential analysis of samples, which is computationally expensive and typically only performed in coverage-based binning methods. Further, users may now optionally check their uploaded samples for plasmid sequences using PLSDB as a reference database. Lastly, a new application programming interface with a supporting python package was implemented, to allow power users fully automated access to the resource and integration into existing workflows. The webserver is freely available under: https://www.ccb.uni-saarland.de/busybee.

Molecular hallmarks of heterochronic parabiosis at single-cell resolution.

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

Sex Differences in Cardiovascular Research: A Scientometric Analysis.

Background We sought to investigate sex-specific differences in authorship of cardiovascular research over the past decade. Methods and Results All 387 463 cardiovascular publications between 2010 and 2019 were retrieved from Web of Science. Articles increased from 19 960 to 29 604 articles per year (P>0.001). The number of articles written by female first authors increased by 76.3% (6434-11 343 articles) and by 35.0% for male first authors (13 526-18 261) (P<0.001). The first author was more likely to be a female author in articles with female last authors. The median impact factor (IF) for articles by female first authors was lower (2.46 [interquartile range, 7 1.11-4.03] versus 2.51 [interquartile range, 1.17-4.10]; P<0.001). Female authorship articles reached the highest IF in North America (average IF, 3.7), with the lowest in Africa (average IF, 1.8). Conclusions Publications in cardiovascular research have increased over the past decade, particularly by female authors. Female researchers are cited less often compared with their male peers. The IF remains lower for articles by female researchers.

miRNATissueAtlas2: an update to the human miRNA tissue atlas.

Small non-coding RNAs (sncRNAs) are pervasive regulators of physiological and pathological processes. We previously developed the human miRNA Tissue Atlas, detailing the expression of miRNAs across organs in the human body. Here, we present an updated resource containing sequencing data of 188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from the same bodies minimizes intra-individual variability and facilitates the making of a precise high-resolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and organ system-specificity of piwi-interacting RNAs (piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of our resource, we describe the identification of highly specific ncRNAs in different organs. The update also contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between Homo sapiens and Mus musculus. The updated resource of 87 252 non-coding RNAs from nine non-coding RNA classes for all organs and organ systems is available online without any restrictions (https://www.ccb.uni-saarland.de/tissueatlas2).

Deep learning-based detection of eosinophilic esophagitis.

BACKGROUND: For eosinophilic esophagitis (EoE), a substantial diagnostic delay is still a clinically relevant phenomenon. Deep learning-based algorithms have demonstrated potential in medical image analysis. Here we establish a convolutional neuronal network (CNN)-based approach that can distinguish the appearance of EoE from normal findings and candida esophagitis. METHODS: We trained and tested a CNN using 484 real-world endoscopic images from 134 subjects consisting of three classes (normal, EoE, and candidiasis). Images were split into two completely independent datasets. The proposed approach was evaluated against three trainee endoscopists using the test set. Model-explainability was enhanced by deep Taylor decomposition. RESULTS: Global accuracy (0.915 [95 % confidence interval (CI) 0.880-0.940]), sensitivity (0.871 [95 %CI 0.819-0.910]), and specificity (0.936 [95 %CI 0.910-0.955]) were significantly higher than for the endoscopists on the test set. Global area under the receiver operating characteristic curve was 0.966 [95 %CI 0.954-0.975]. Results were highly reproducible. Explainability analysis found that the algorithm identified the characteristic signs also used by endoscopists. CONCLUSIONS: Complex endoscopic classification tasks including more than two classes can be solved by CNN-based algorithms. Therefore, our algorithm may assist clinicians in making the diagnosis of EoE.

PLSDB: advancing a comprehensive database of bacterial plasmids.

Plasmids are known to contain genes encoding for virulence factors and antibiotic resistance mechanisms. Their relevance in metagenomic data processing is steadily growing. However, with the increasing popularity and scale of metagenomics experiments, the number of reported plasmids is rapidly growing as well, amassing a considerable number of false positives due to undetected misassembles. Here, our previously published database PLSDB provides a reliable resource for researchers to quickly compare their sequences against selected and annotated previous findings. Within two years, the size of this resource has more than doubled from the initial 13,789 to now 34,513 entries over the course of eight regular data updates. For this update, we aggregated community feedback for major changes to the database featuring new analysis functionality as well as performance, quality, and accessibility improvements. New filtering steps, annotations, and preprocessing of existing records improve the quality of the provided data. Additionally, new features implemented in the web-server ease user interaction and allow for a deeper understanding of custom uploaded sequences, by visualizing similarity information. Lastly, an application programming interface was implemented along with a python library, to allow remote database queries in automated workflows. The latest release of PLSDB is freely accessible under https://www.ccb.uni-saarland.de/plsdb.

A CYPome-wide study reveals new potential players in the pathogenesis of Parkinson's disease.

Genetic and environmental factors lead to the manifestation of Parkinson's disease (PD) but related mechanisms are only rudimentarily understood. Cytochromes P450 (P450s) are involved in the biotransformation of toxic compounds and in many physiological processes and thus predestinated to be involved in PD. However, so far only SNPs (single nucleotide polymorphisms) in CYP2D6 and CYP2E1 have been associated with the susceptibility of PD. Our aim was to evaluate the role of all 57 human P450s and their redox partners for the etiology and pathophysiology of PD and to identify novel potential players which may lead to the identification of new biomarkers and to a causative treatment of PD. The PPMI (Parkinson's Progression Markers Initiative) database was used to extract the gene sequences of all 57 P450s and their three redox partners to analyze the association of SNPs with the occurrence of PD. Applying statistical analyses of the data, corresponding odds ratios (OR) and confidence intervals (CI) were calculated. We identified SNPs significantly over-represented in patients with a genetic predisposition for PD (GPD patients) or in idiopathic PD (IPD patients) compared to HC (healthy controls). Xenobiotic-metabolizing P450s show a significant accumulation of SNPs in PD patients compared with HC supporting the role of toxic compounds in the pathogenesis of PD. Moreover, SNPs with high OR values (>5) in P450s catalyzing the degradation of cholesterol (CYP46A1, CY7B1, CYP39A1) indicate a prominent role of cholesterol metabolism in the brain for PD risk. Finally, P450s participating in the metabolism of eicosanoids show a strong over-representation of SNPs in PD patients underlining the effect of inflammation on the pathogenesis of PD. Also, the redox partners of P450 show SNPs with OR > 5 in PD patients. Taken together, we demonstrate that SNPs in 26 out of 57 P450s are at least 5-fold over-represented in PD patients suggesting these P450s as new potential players in the pathogenesis of PD. For the first time exceptionally high OR values (up to 12.9) were found. This will lead to deeper insight into the origin and development of PD and may be applied to develop novel strategies for a causative treatment of this disease.

Xenogeneic skin transplantation promotes angiogenesis and tissue regeneration through activated Trem2+ macrophages.

Skin allo- and xenotransplantation are the standard treatment for major burns when donor sites for autografts are not available. The relationship between the immune response to foreign grafts and their impact on wound healing has not been fully elucidated. Here, we investigated changes in collagen architecture after xenogeneic implantation of human biologic scaffolds. We show that collagen deposition in response to the implantation of human split-thickness skin grafts (hSTSGs) containing live cells recapitulates normal skin architecture, whereas human acellular dermal matrix (ADM) grafts led to a fibrotic collagen deposition. We show that macrophage differentiation in response to hSTSG implantation is driven toward regenerative Trem2+ subpopulations and found that hydrogel delivery of these cells significantly accelerated wound closure. Our study identifies the preclinical therapeutic potential of Trem2+ macrophages to mitigate fibrosis and promote wound healing, providing a novel effective strategy to develop advanced cell therapies for complex wounds.

CD4+ T cells contribute to neurodegeneration in Lewy body dementia.

Recent studies indicate that the adaptive immune system plays a role in Lewy body dementia (LBD). However, the mechanism regulating T cell brain homing in LBD is unknown. Here, we observed T cells adjacent to Lewy bodies and dopaminergic neurons in postmortem LBD brains. Single-cell RNA sequencing of cerebrospinal fluid (CSF) identified up-regulated expression of C-X-C motif chemokine receptor 4 (CXCR4) in CD4+ T cells in LBD. CSF protein levels of the CXCR4 ligand, C-X-C motif chemokine ligand 12 (CXCL12), were associated with neuroaxonal damage in LBD. Furthermore, we observed clonal expansion and up-regulated interleukin 17A expression by CD4+ T cells stimulated with a phosphorylated α-synuclein epitope. Thus, CXCR4-CXCL12 signaling may represent a mechanistic target for inhibiting pathological interleukin-17­producing T cell trafficking in LBD.

Disrupting biological sensors of force promotes tissue regeneration in large organisms.

Tissue repair and healing remain among the most complicated processes that occur during postnatal life. Humans and other large organisms heal by forming fibrotic scar tissue with diminished function, while smaller organisms respond with scarless tissue regeneration and functional restoration. Well-established scaling principles reveal that organism size exponentially correlates with peak tissue forces during movement, and evolutionary responses have compensated by strengthening organ-level mechanical properties. How these adaptations may affect tissue injury has not been previously examined in large animals and humans. Here, we show that blocking mechanotransduction signaling through the focal adhesion kinase pathway in large animals significantly accelerates wound healing and enhances regeneration of skin with secondary structures such as hair follicles. In human cells, we demonstrate that mechanical forces shift fibroblasts toward pro-fibrotic phenotypes driven by ERK-YAP activation, leading to myofibroblast differentiation and excessive collagen production. Disruption of mechanical signaling specifically abrogates these responses and instead promotes regenerative fibroblast clusters characterized by AKT-EGR1.