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Diffuse invasion of the surrounding brain parenchyma is a major obstacle in the treatment of gliomas with various therapeutics, including anti-angiogenic agents. Here we identify the epi-/genetic and microenvironmental downregulation of ephrinB2 as a crucial step that promotes tumour invasion by abrogation of repulsive signals. We demonstrate that ephrinB2 is downregulated in human gliomas as a consequence of promoter hypermethylation and gene deletion. Consistently, genetic deletion of ephrinB2 in a murine high-grade glioma model increases invasion. Importantly, ephrinB2 gene silencing is complemented by a hypoxia-induced transcriptional repression. Mechanistically, hypoxia-inducible factor (HIF)-1α induces the EMT repressor ZEB2, which directly downregulates ephrinB2 through promoter binding to enhance tumour invasiveness. This mechanism is activated following anti-angiogenic treatment of gliomas and is efficiently blocked by disrupting ZEB2 activity. Taken together, our results identify ZEB2 as an attractive therapeutic target to inhibit tumour invasion and counteract tumour resistance mechanisms induced by anti-angiogenic treatment strategies.
Objectives: To investigate the prevalence of depressive symptoms in rheumatoid arthritis (RA) patients using two previously validated questionnaires in a large patient sample, and to evaluate depressive symptoms in the context of clinical characteristics (e.g. remission of disease) and patient-reported impact of disease.
Methods: In this cross-sectional study, the previously validated Patient Health Questionnaire (PHQ-9) and Beck-Depression Inventory II (BDI-II) were used to assess the extent of depressive symptoms in RA patients. Demographic background, RA disease activity score (DAS28), RA impact of disease (RAID) score, comorbidities, anti-rheumatic therapy and antidepressive treatment, were recorded. Cut-off values for depressive symptomatology were PHQ-9 ≥5 or BDI-II ≥14 for mild depressive symptoms or worse and PHQ-9 ≥ 10 or BDI-II ≥ 20 for moderate depressive symptoms or worse. Prevalence of depressive symptomatology was derived by frequency analysis while factors independently associated with depressive symptomatology were investigated by using multiple logistic regression analyses. Ethics committee approval was obtained, and all patients provided written informed consent before participation.
Results: In 1004 RA-patients (75.1% female, mean±SD age: 61.0±12.9 years, mean disease duration: 12.2±9.9 years, DAS28 (ESR): 2.5±1.2), the prevalence of depressive symptoms was 55.4% (mild or worse) and 22.8% (moderate or worse). Characteristics independently associated with depressive symptomatology were: age <60 years (OR = 1.78), RAID score >2 (OR = 10.54) and presence of chronic pain (OR = 3.25). Of patients classified as having depressive symptoms, only 11.7% were receiving anti-depressive therapy.
Conclusions: Mild and moderate depressive symptoms were common in RA patients according to validated tools. In routine clinical practice, screening for depression with corresponding follow-up procedures is as relevant as incorporating these results with patient-reported outcomes (e.g. symptom state), because the mere assessment of clinical disease activity does not sufficiently reflect the prevalence of depressive symptoms.
Clinical trial registration number: This study is registered in the Deutsches Register Klinischer Studien (DRKS00003231) and ClinicalTrials.gov (NCT02485483).
Protein turnover and quality control by the proteasome is of paramount importance for cell homeostasis. Dysfunction of the proteasome is associated with aging processes and human diseases such as neurodegeneration, cardiomyopathy, and cancer. The regulation, i.e. activation and inhibition of this fundamentally important protein degradation system, is still widely unexplored. We demonstrate here that the evolutionarily highly conserved type II triple-A ATPase VCP and the proteasome inhibitor PSMF1/PI31 interact directly, and antagonistically regulate proteasomal activity. Our data provide novel insights into the regulation of proteasomal activity.
Objective: Combination antiretroviral therapy (cART) has markedly increased survival and quality of life in people living with HIV. With the advent of new treatment options, including single-tablet regimens, durability and efficacy of first-line cART regimens are evolving.
Methods: We analyzed data from the prospective multicenter German Clinical Surveillance of HIV Disease (ClinSurv) cohort of the Robert-Koch Institute. Kaplan–Meier and Cox proportional hazards models were run to examine the factors associated with treatment modification. Recovery after treatment initiation was analyzed comparing pre-cART viral load and CD4+ T-cell counts with follow-up data.
Results: We included 8788 patients who initiated cART between 2005 and 2017. The sample population was predominantly male (n = 7040; 80.1%), of whom 4470 (63.5%) were reporting sex with men as the transmission risk factor. Overall, 4210 (47.9%) patients modified their first-line cART after a median time of 63 months (IQR 59–66). Regimens containing integrase strand transfer inhibitors (INSTI) were associated with significantly lower rates of treatment modification (adjusted hazard ratio 0.44; 95% CI 0.39–0.50) compared to protease inhibitor (PI)-based regimens. We found a decreased durability of first-line cART significantly associated with being female, a low CD4+ T-cell count, cART initiation in the later period (2011–2017), being on a multi-tablet regimen (MTR).
Conclusions: Drug class and MTRs are significantly associated with treatment modification. INSTI-based regimens showed to be superior compared to PI-based regimens in terms of durability.
EphrinB2 and GRIP1 stabilize mushroom spines during denervation-induced homeostatic plasticity
(2021)
Highlights
• Denervation induces mushroom spine loss and AMPAR redistribution to the surface
• GRIP1 and ephrinB2 mediate homeostatic mechanisms after lesion
• Stimulation with the ephrinB2 receptor EphB4 promotes a surface shift of AMPARs
• AMPARs surface shift restores impaired spine recovery after lesion in GRIP1 mutants
Summary
Despite decades of work, much remains elusive about molecular events at the interplay between physiological and structural changes underlying neuronal plasticity. Here, we combined repetitive live imaging and expansion microscopy in organotypic brain slice cultures to quantitatively characterize the dynamic changes of the intracellular versus surface pools of GluA2-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) across the different dendritic spine types and the shaft during hippocampal homeostatic plasticity. Mechanistically, we identify ephrinB2 and glutamate receptor interacting protein (GRIP) 1 as mediating AMPAR relocation to the mushroom spine surface following lesion-induced denervation. Moreover, stimulation with the ephrinB2 specific receptor EphB4 not only prevents the lesion-induced disappearance of mushroom spines but is also sufficient to shift AMPARs to the surface and rescue spine recovery in a GRIP1 dominant-negative background. Thus, our results unravel a crucial role for ephrinB2 during homeostatic plasticity and identify a potential pharmacological target to improve dendritic spine plasticity upon injury.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.