Biology subjects

Grosskreutz, J.

Publications and source records attributed to Grosskreutz, J..

3 recordsLinked to original sources

bioRxiv2025

The Good, the Bad, and the Ugly: Segmentation-Based Quality Control of Structural Magnetic Resonance Images

The processing and analysis of magnetic resonance images is highly dependent on the quality of the input data, and systematic differences in quality can consequently lead to loss of sensitivity or biased results. However, varying image properties due to different scanners and acquisition protocols, as well as subject-specific image interferences, such as motion artifacts, can be incorporated in the analysis. A reliable assessment of image quality is therefore essential to identify critical outliers that may bias results. Here we present a quality assessment for structural (T1-weighted) images using tissue classification. We introduce multiple useful image quality measures, standardize them into quality scales and combine them into an integrated structural image quality rating to facilitate the interpretation and fast identification of outliers with (motion) artifacts. The reliability and robustness of the measures are evaluated using synthetic and real datasets. Our study results demonstrate that the proposed measures are robust to simulated segmentation problems and variables of interest such as cortical atrophy, age, sex, brain size and severe disease-related changes, and might facilitate the separation of motion artifacts based on within-protocol deviations. The quality control framework presents a simple but powerful tool for the use in research and clinical settings.

neuroscience↗

bioRxiv2024

Small molecule inhibitors of hnRNPA2B1-RNA interactions reveal a predictable sorting of RNA subsets into extracellular vesicles

Extracellular vesicles (EVs) are cell-secreted membranous particles contributing to intercellular communication. Coding and non-coding RNAs are widely detected EV cargo, and RNA-binding proteins (RBPs), such as hnRNPA2B1, have been circumstantially implicated in sorting vesicular RNAs. However, the contribution of competitive RBP-RNA interactions responsible for RNA-sorting outcomes still needs to be deciphered, especially for EV-RNA interference and predictability. We conducted a reverse proteomic analysis that prioritized heterogeneous nuclear ribonucleoproteins recognizing purine-rich RNA sequences representing a subset of previously identified EXO motifs. A screening campaign using a full-length human hnRNPA2B1 protein and artificial purine-rich RNA brought to small molecule inhibitors orthogonally validated through biochemical and cell-based approaches. Selected drugs effectively interfered with a post-transcriptional layer impacting secreted EV- RNAs, reducing the vesicular pro-inflammatory miR-221 while counteracting the hnRNPA2B1- or TDP43Q331K-dependent paracrine activation of NF-{kappa}B in EV-recipient cells. This study demonstrates the possibility of predicting the EV-RNA quality for developing innovative strategies targeting discrete paracrine functions. SummaryExtracellular vesicles (EVs) are cell-released, heterogeneous lipid particles conceived as vehicles for intercellular communication. RNA is a widely detected cargo, and the comprehension of EV-sorting mechanisms represents a step forward in predicting EV quality and associated paracrine effects. While it is known that specific RNA-binding proteins (RBPs) play a role in EV-RNA sorting, the quantitative contribution of competing RBP-RNA interactions and the predictability of RNA-sorting outcomes are poorly understood. Here, we show that a core of hnRNPs compete for the binding to the heterogeneous EV-RNA in vitro. Given prioritized interactions with purine-rich RNA motifs, we set up a pharmacological screen platform to find inhibitors of protein-RNA interactions. Our results suggest that selected small molecules can interfere with EV-RNA quality, altering the distribution of specific miRNA cargoes and associating with a discriminant NF-kB activation in EV-recipient cells. This work highlights the role of RBP-RNA interactions in influencing the EV-RNA quality and paracrine functions.

molecular biology↗

bioRxiv2019

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative syndrome of the human motor neuron system, for which no effective treatment exists. Variability in the rate of disease progression limits the efficacy of ALS clinical trials, suggesting that developing of better biomarkers for prognosis will facilitate therapeutic progress. Here, we applied unbiased next-generation sequencing to investigate the potential of plasma cell-free microRNAs as biomarkers of ALS prognosis, in 252 patients with detailed clinical-phenotyping. First, we identified miRNAs, whose plasma levels remain stable over the course of disease in a longitudinal cohort of 22 patients. Next, we demonstrated that high levels of miR-181, a miRNA enriched in neurons of the brain and spinal cord, predicts a >2 fold risk of death in discovery cohort (126 patients) and an independent replication cohort (additional 122 patients). miR-181 performance is comparable with the established neurofilament light chain (NfL) biomarker and when combined together, miR-181+NfL establish a novel RNA-protein biomarker pair with superior prediction capacity of ALS prognosis. Therefore, plasma miR-181 predicts ALS disease course, and a novel miRNA-protein biomarker approach, based on miR-181+NfL, boosts precision of patient stratification and may greatly enhance the power of clinical trials. One Sentence Summaryplasma miR-181 levels indicate high mortality risk in ALS patients.

neuroscience↗