Phosphomannomutase deficiency (PMM2-CDG): Ataxia and cerebellar assessment

Background: Phosphomannomutase deficiency (PMM2-CDG) is the most frequent congenital disorder of glycosylation. The cerebellum is nearly always affected in PMM2-CDG patients, a cerebellar atrophy progression is observed, and cerebellar dysfunction is their main daily functional limitation. Different therapeutic agents are under development, and clinical evaluation of drug candidates will require a standardized score of cerebellar dysfunction. We aim to assess the validity of the International Cooperative Ataxia Rating Scale (ICARS) in children and adolescents with genetically confirmed PMM2-CDG deficiency. We compare ICARS results with the Nijmegen Pediatric CDG Rating Scale (NPCRS), neuroimaging, intelligence quotient (IQ) and molecular data. Methods: Our observational study included 13 PMM2-CDG patients and 21 control subjects. Ethical permissions and informed consents were obtained. Three independent child neurologists rated PMM2-CDG patients and control subjects using the ICARS. A single clinician administered the NPCRS. All patients underwent brain MRI, and the relative diameter of the midsagittal vermis was measured. Psychometric evaluations were available in six patients. The Mann-Whitney U test was used to compare ICARS between patients and controls. To evaluate inter-observer agreement in patients' ICARS ratings, intraclass correlation coefficients (ICC) were calculated. ICARS internal consistency was evaluated using Cronbach's alpha. Spearman's rank correlation coefficient test was used to correlate ICARS with NPCRS, midsagittal vermis relative diameter and IQ. Results: ICARS and ICARS subscores differed between patients and controls (p < 0.001). Interobserver agreement of ICARS was "almost perfect" (ICC = 0.99), with a "good" internal reliability (Cronbach's alpha = 0.72). ICARS was significantly correlated with the total NPCRS score (rs 0.90, p < 0.001). However, there was no agreement regarding categories of severity. Regarding neuroimaging, inverse correlations between ICARS and midsagittal vermis relative diameter (rs -0.85, p = 0.003) and IQ (rs -0.94, p = 0.005) were found. Patients bearing p.E93A, p.C241S or p.R162W mutations presented a milder phenotype. Conclusions: ICARS is a reliable instrument for assessment of PMM2-CDG patients, without significant inter-rater variability. Despite our limited sample size, the results show a good correlation between functional cerebellar assessment, IQ and neuroimagingFor the first a correlation between ICARS, neuroimaging and IQ in PMM2-CDG patients has been demonstratedThe work was supported by national grants PI14/00021, PI11/01096, PI11/01250, and PI10/00455 from the National Plan on I+D+I, cofinanced by ISC-III (Subdirección General de Evaluación y Fomento de la Investigación Sanitaria) and FEDER (Fondo Europeo de Desarrollo Regional) and IPT-2012- 0561-010000 from MINECO. Three research groups (U-746, U-737 and U703) from the Centre for Biomedical Research on Rare Diseases (CIBER-ER), Instituto de Salud Carlos III, Spain, have worked together for the present stud

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study

Background: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.11 página

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study

Background The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

Key Factors Associated With Pulmonary Sequelae in the Follow-Up of Critically Ill COVID-19 Patients

Introduction: Critical COVID-19 survivors have a high risk of respiratory sequelae. Therefore, we aimed to identify key factors associated with altered lung function and CT scan abnormalities at a follow-up visit in a cohort of critical COVID-19 survivors. Methods: Multicenter ambispective observational study in 52 Spanish intensive care units. Up to 1327 PCR-confirmed critical COVID-19 patients had sociodemographic, anthropometric, comorbidity and lifestyle characteristics collected at hospital admission; clinical and biological parameters throughout hospital stay; and, lung function and CT scan at a follow-up visit. Results: The median [p25–p75] time from discharge to follow-up was 3.57 [2.77–4.92] months. Median age was 60 [53–67] years, 27.8% women. The mean (SD) percentage of predicted diffusing lung capacity for carbon monoxide (DLCO) at follow-up was 72.02 (18.33)% predicted, with 66% of patients having DLCO < 80% and 24% having DLCO < 60%. CT scan showed persistent pulmonary infiltrates, fibrotic lesions, and emphysema in 33%, 25% and 6% of patients, respectively. Key variables associated with DLCO < 60% were chronic lung disease (CLD) (OR: 1.86 (1.18–2.92)), duration of invasive mechanical ventilation (IMV) (OR: 1.56 (1.37–1.77)), age (OR [per-1-SD] (95%CI): 1.39 (1.18–1.63)), urea (OR: 1.16 (0.97–1.39)) and estimated glomerular filtration rate at ICU admission (OR: 0.88 (0.73–1.06)). Bacterial pneumonia (1.62 (1.11–2.35)) and duration of ventilation (NIMV (1.23 (1.06–1.42), IMV (1.21 (1.01–1.45)) and prone positioning (1.17 (0.98–1.39)) were associated with fibrotic lesions. Conclusion: Age and CLD, reflecting patients’ baseline vulnerability, and markers of COVID-19 severity, such as duration of IMV and renal failure, were key factors associated with impaired DLCO and CT abnormalities

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Métodos y técnicas de monitoreo y predicción temprana en los escenarios de riesgos socionaturales

Esta obra concentra los métodos y las técnicas fundamentales para el seguimiento y monitoreo de las dinámicas de los escenarios de riesgos socionaturales (geológicos e hidrometeorológicos) y tiene como objetivo general orientar, apoyar y acompañar a los directivos y operativos de protección civil en aterrizar las acciones y políticas públicas enfocadas a la gestión del riesgo local de desastre