Publicaciones: agosto 2023

Defective hippocampal neurogenesis underlies cognitive impairment by carotid stenosis-induced cerebral hypoperfusion in mice

Fraga E, Medina V, Cuartero MI et al. Front Cell Neurosci. 2023 Aug 11;17:1219847. doi: 10.3389/fncel.2023.1219847. eCollection 2023. PMID: 37636586

https://pubmed.ncbi.nlm.nih.gov/37636586/

Abstract: Chronic cerebral hypoperfusion due to carotid artery stenosis is a major cause of vascular cognitive impairment and dementia (VCID). Bilateral carotid artery stenosis (BCAS) in rodents is a well-established model of VCID where most studies have focused on white matter pathology and subsequent cognitive deficit. Therefore, our aim was to study the implication of adult hippocampal neurogenesis in hypoperfusion-induced VCID in mice, and its relationship with cognitive hippocampal deficits. Mice were subjected to BCAS; 1 and 3 months later, hippocampal memory and neurogenesis/cell death were assessed, respectively, by the novel object location (NOL) and spontaneous alternation performance (SAP) tests and by immunohistology. Hypoperfusion was assessed by arterial spin labeling-magnetic resonance imaging (ASL-MRI). Hypoperfused mice displayed spatial memory deficits with decreased NOL recognition index. Along with the cognitive deficit, a reduced number of newborn neurons and their aberrant morphology indicated a remarkable impairment of the hippocampal neurogenesis. Both increased cell death in the subgranular zone (SGZ) and reduced neuroblast proliferation rate may account for newborn neurons number reduction. Our data demonstrate quantitative and qualitative impairment of adult hippocampal neurogenesis disturbances associated with cerebral hypoperfusion-cognitive deficits in mice. These findings pave the way for novel diagnostic and therapeutic targets for VCID. 

Funding: This work was supported by grants from Spanish Ministry of Science and Innovation (MCIN) PID2019-106581RB-I00 (MM), from Leducq Foundation for Cardiovascular ResearchbTNE-19CVD01 (MM) and TNE-21CVD04 (MM and IL), and from Instituto de Salud Carlos III (ISCIII) and co-financed by the European Development Regional Fund “A Way to Achieve Europe” PI20/00535 and RICORS-ICTUS RD21/0006/0001 (IL). CNIC was supported by ISCIII, MCIN, and ProCNIC Foundation, and is a Severo Ochoa Center of Excellence
(CEX2020-001041-S). The microscopy experiments were performed in Unidad de Microscopía e Imagen Dinámica, CNIC, ICTS-ReDib, co-funded by MCIN/AEI/10.13039/501100011033 and FEDER “Una manera de hacer Europa” (#ICTS-2018- 04-CNIC-16). Part of the research work included in this publication has been carried out in the ReDIB ICTS infrastructure BioImaC, MCIN.

Genetic Architecture of Ischaemic Strokes after COVID-19 Shows Similarities with Large Vessel Strokes

Llucià-Carol L, Muiño E, Cullell N et al. Int J Mol Sci. 2023 Aug 30;24(17):13452. doi: 10.3390/ijms241713452. PMID: 37686257

https://pubmed.ncbi.nlm.nih.gov/37686257/

Abstract: We aimed to analyse whether patients with ischaemic stroke (IS) occurring within eight days after the onset of COVID-19 (IS-COV) are associated with a specific aetiology of IS. We used SUPERGNOVA to identify genome regions that correlate between the IS-COV cohort (73 IS-COV cases vs. 701 population controls) and different aetiological subtypes. Polygenic risk scores (PRSs) for each subtype were generated and tested in the IS-COV cohort using PRSice-2 and PLINK to find genetic associations. Both analyses used the IS-COV cohort and GWAS from MEGASTROKE (67,162 stroke patients vs. 454,450 population controls), GIGASTROKE (110,182 vs. 1,503,898), and the NINDS Stroke Genetics Network (16,851 vs. 32,473). Three genomic regions were associated (p-value < 0.05) with large artery atherosclerosis (LAA) and cardioembolic stroke (CES). We found four loci targeting the genes PITX2 (rs10033464, IS-COV beta = 0.04, p-value = 2.3 × 10−2 , se = 0.02), previously associated with CES, HS6ST1 (rs4662630, IS-COV beta = −0.04, p-value = 1.3 × 10−3, se = 0.01), TMEM132E (rs12941838 IS-COV beta = 0.05, p-value = 3.6 × 10−4 , se = 0.01), and RFFL (rs797989 IS-COV beta = 0.03, p-value = 1.0 × 10−2 , se = 0.01). A statistically significant PRS was observed for LAA. Our results suggest that IS-COV cases are genetically similar to LAA and CES subtypes. Larger cohorts are needed to assess if the genetic factors in IS-COV cases are shared with the general population or specific to viral infection.

Funding: This work was supported by the Spanish National Research Council (CSIC) via COVID19 Funds (Ref.CSIC202020E086), the European Commission—NextGenerationEU (Regulation EU 2020/2094), through CSIC’s Global Health Platform, the Instituto de Salud Carlos III through the iBioStroke project (AC19/00106 Eranet-Neuron, European research grants), the RICORS RD21/0006/0006, FEDER, NextGeneration EU, the PREVICTUS project (PMP21/00165), and the COPYCTUS project (PI21/01088). IIB SANT PAU is funded by the Catalan Government (CERCA Program/ Generalitat de Catalunya). M.L. is funded by a PFIS Contract (Contratos Predoctorales de Formación en Investigación en Salud FI19/00309) from Instituto de Salud Carlos III (ISCIII). C.G.-F. is supported by a Sara Borrel contract (CD20/00043) from Instituto Carlos III and Fondo Europeo de Desarrollo Regional (ISCIII-FEDER). The BelCovid cohort is funded by The Belgian National Funds for Scientific Research and Fondation Léon Fredericq. 

Paper-Based Analytical Devices for Accurate Assessment of Transferrin Saturation in Diagnosed Clinical Samples from Ischemic Stroke Patients

Silvia Dortez, Nùria DeGregorio-Rocasolano, Mónica Millán, Teresa Gasull, Agustín G Crevillen, Alberto Escarpa. Anal Chem. 2023 Aug 22;95(33): 12391-12397. DOI: 10.1021/acs.analchem.3c01982. PMID: 37486019

https://pubmed.ncbi.nlm.nih.gov/37486019/

Abstract: For the first time, a paper-based analytical device (PAD) was developed for the assessment of transferrin saturation (TSAT), which is defined as the ratio between iron bound to transferrin (Tf) and the total iron-binding capacity (TIBC) of Tf. Both parameters were simultaneously measured on the same PAD using ferrozine as a chromophore and a smartphone as the color reader. To this end, Tf was first isolated from serum using anti-Tf immunomagnetic beads to ensure that only the Tf-bound iron was measured, improving the selectivity and accuracy of TSAT assessment. To demonstrate the practical utility of the device, it was validated by analyzing a certified reference material, showing excellent accuracy (Er < 4%) and good precision (RSD ≤ 6%). Finally, 18 diagnosed serum samples from ischemic stroke patients were analyzed by this approach, and the results were compared with those obtained by urea-PAGE, showing not only an excellent correlation (r = 0.93, p < 0.05) but that the PAD approach has become statistically identical to the free-interference urea-PAGE. In comparison with the slow, tedious, and non-miniaturized-PAGE, this PAD approach exhibited attractive characteristics such as low cost, disposability, and connectivity, showing great potential for future point-of-care testing, especially in developing countries and/or remote areas, where access to medical or clinical facilities is limited.

Funding: This work has been financially supported by the TRANSNANOAVANSENS program from the Community of Madrid (P2018/NMT-4349) (A.E.), by the grant PID2020 118154GB-I00 funded by MCIN/AEI/ 10.13039/ 501100011033 (A.E.), by the RICORS RD21/0006/0024 and 2021SGR00925 (T.G.), and by the Spanish Ministry of Economy and Competitiveness (CTQ2017-86441-C2-1-R, FPI fellowship (S. D.)).

 

Perfusion-weighted software written in Python for DSC-MRI analysis

Fernández-Rodicio S, Ferro-Costas G, Sampedro-Viana A et al. Front Neuroinform. 2023 Aug 1;17:1202156. doi: 10.3389/fninf.2023.1202156. eCollection 2023. PMID: 37593674 Free

https://pubmed.ncbi.nlm.nih.gov/37593674/

Abstract:

Introduction: Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in dierent rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes.
Methods: The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood–brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature.
Results: A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland– Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF.

Conclusion: An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the dierent animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented

Funding: This research was funded by the Spanish Ministry of Science and Innovation (SAF2017-84267-R), PDC2021-121455-I00, Xunta de Galicia (Axencia Galega de Innovación: IN607A2022- 03), Instituto de Salud Carlos III (ISCIII) (PI17/01103, ISCIII/PI21/01256/Co-financed by the European Union), Spanish Research Network on Cerebrovascular Diseases RETICSINVICTUS PLUS (RD16/0019/0001), and RICORS-ICTUS (Cerebrovascular diseases) D21/0006/0003. MB-B is a PFIS Researcher (FI22/00200) of Instituto de Salud Carlos III. MP-M is a Sara Borrell Researcher (CD19/00033) of Instituto de Salud Carlos III. RI-R (CP22/00061) from the Miguel Servet Program of Instituto de Salud Carlos III and Co-financed by the EU. Sponsors did not participate in the study design, collection, analysis, or interpretation of the data, or in writing the report