13 research outputs found

    A time-resolved proteomic and prognostic map of COVID-19.

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    COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

    A time-resolved proteomic and prognostic map of COVID-19

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    COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

    Clinical and virological characteristics of hospitalised COVID-19 patients in a German tertiary care centre during the first wave of the SARS-CoV-2 pandemic: a prospective observational study

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    Purpose: Adequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories. The purpose of this work was to identify risk factors associated with need for invasive mechanical ventilation (IMV), to analyse viral kinetics in patients with and without IMV and to provide a comprehensive description of clinical course. Methods: A cohort of 168 hospitalised adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care centre was analysed. Results: Forty-four per cent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95% CI 1.10-1.37, p < 0.01) and history of hypertension (aOR 5.55, 95% CI 2.00-16.82, p < 0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p < 0.01). Median duration of hospitalisation was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV patients. Conclusions: Our results indicate a short duration of symptoms before admission as a risk factor for severe disease that merits further investigation and different viral load kinetics in severely affected patients. Median duration of hospitalisation of IMV patients was longer than described for acute respiratory distress syndrome unrelated to COVID-19

    cohort screening of 67 non-related families

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    Brachydaktylie Typ E (BDE) beschreibt eine Fehlbildung der Extremitäten, die durch das Fehlen oder die Verkürzung von Mittelphalangen charakterisiert wird. Die genetischen Ursachen der Erkrankung sind mehrheitlich ungeklärt. ZNF521 ist ein relevanter Transkriptionsfaktor während der Knochenentwicklung und direkter Effektor von PTHLH, das als bekanntes Krankheitsgen für die Entstehung der BDE beschrieben ist. Um die Rolle von ZNF521 an der Krankheitsentstehung der BDE zu klären, wurde das Gen in 67 nicht verwandten Familien mit BDE auf Mutationen via Sanger Sequenzierung untersucht. Zusätzlich wurde in 11 Familien mit gleicher Klinik das nicht-kodierende Genom und insbesondere der regulatorische Archipel vor dem HOXD Cluster via Array CGH analysiert, da Mutationen in HOXD ebenfalls zur Ausprägung einer BDE führen. Die Validierung erfolgte via qPCR. In einer Familie wurde eine bislang unbekannte Punktmutation in ZNF521 gefunden, die durch Prädiktionsprogramme mit einer hohen Wahrscheinlichkeit als pathogen eingestuft wird. Um sie als Pathologie zu beweisen, sollten weitere Fälle beschrieben und ein Beweis mit einem Mausmodell erbracht werden. Im regulatorischen Archipel des HOXD Clusters wurde in einer Familie eine bislang nicht beschriebene Deletion von vier nicht-kodierenden regulatorischen Islands gefunden. Diese Deletion zeigte sich im Laufe weiterer Forschung durch Untersuchungen an einem Mausmodell als ursächliche Mutation für die BDE. Dementsprechend sollten weitere ungeklärte Brachydaktylie Fälle auf Mutationen in diesem Bereich untersucht werden. Die Erkenntnis über die Rolle des regulatorischen Archipels bei der Entwicklung von Extremitäten im Menschen liefert Informationen für das Verständnis der Physiologie und Pathologie der Knochenentwicklung und könnte möglicherweise für die Entwicklung von Therapien hilfreich sein.Brachydactyly type E (BDE) is a limb malformation characterized by missing or shortening of middle phalanges. Its genetic causes remain mostly unknown. ZNF521 is an important transcription factor for bone development and direct effector of PTHLH, mutations of which are already known to cause BDE. In order to investigate the role of mutations in ZNF521 in disease development, 67 unrelated families with BDE were screened via Sanger sequencing. In addition, 11 families of the same cohort were screened via Array CGH for mutations in the noncoding regions of the genome. Special emphasis was laid on the regulatory archipelago of the HOXD cluster, as mutations in this area are already known to cause BDE. The results were validated via qPCR. Sanger sequencing showed a so far unknown missense mutation in ZNF521 which various prediction software programs classified as probably disease causing. A further case should be found to increase the probability of pathogenicity, whereas the final proof could be furnished by a mouse model. Furthermore, a so far unknown deletion involving four regulatory islands of the HOXD Cluster was found in one family. Further research brought up a mouse model proving this deletion to be disease causing. Therefore, more cases of BDE of unknown origin should be checked for mutations in the regulatory domain of the HOXD Cluster. The awareness about its impact on limb development in human organisms increases the comprehension of physiology and pathology of bone development and could be helpful for future therapy progress

    Noncoding copy-number variations are associated with congenital limb malformation

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    PurposeCopy-number variants (CNVs) are generally interpreted by linking the effects of gene dosage with phenotypes. The clinical interpretation of noncoding CNVs remains challenging. We investigated the percentage of disease-associated CNVs in patients with congenital limb malformations that affect noncoding cis-regulatory sequences versus genes sensitive to gene dosage effects.MethodsWe applied high-resolution copy-number analysis to 340 unrelated individuals with isolated limb malformation. To investigate novel candidate CNVs, we re-engineered human CNVs in mice using clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing.ResultsOf the individuals studied, 10% harbored CNVs segregating with the phenotype in the affected families. We identified 31 CNVs previously associated with congenital limb malformations and four novel candidate CNVs. Most of the disease-associated CNVs (57%) affected the noncoding cis-regulatory genome, while only 43% included a known disease gene and were likely to result from gene dosage effects. In transgenic mice harboring four novel candidate CNVs, we observed altered gene expression in all cases, indicating that the CNVs had a regulatory effect either by changing the enhancer dosage or altering the topological associating domain architecture of the genome.ConclusionOur findings suggest that CNVs affecting noncoding regulatory elements are a major cause of congenital limb malformations

    Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.

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    Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19

    A proteomic survival predictor for COVID-19 patients in intensive care.

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    Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care
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