Neurological outcome following out of hospital cardiac arrest: Evaluation of performance of existing risk prediction models in a UK cohort.

Introduction: Out of hospital cardiac arrest (OHCA) is a common problem. Rates of survival are low and a proportion of survivors are left with an unfavourable neurological outcome. Four models have been developed to predict risk of unfavourable outcome at the time of critical care admission - the Cardiac Arrest Hospital Prognosis (CAHP), MIRACLE2, Out of Hospital Cardiac Arrest (OHCA), and Targeted Temperature Management (TTM) models. This evaluation evaluates the performance of these four models in a United Kingdom population and provides comparison to performance of the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score. Methods: A retrospective evaluation of the performance of the models was conducted over a 43-month period in 414 adult, non-pregnant patients presenting consecutively following non-traumatic OHCA to the five units in our regional critical care network. Scores were generated for each model for where patients had complete data (CAHP = 347, MIRACLE2 = 375, OHCA = 356, TTM = 385). Cerebral Performance Category (CPC) outcome was calculated for each patient at last documented follow up and an unfavourable outcome defined as CPC ⩾ 3. Performance for discrimination of unfavourable outcome was tested by generating receiver operating characteristic (ROC) curves for each model and comparing the area under the curve (AUC). Results: Best performance for discrimination of unfavourable outcome was demonstrated by the high risk group of the CAHP score with an AUC of 0.87 [95% CI 0.83-0.91], specificity of 97.1% [95% CI 93.8-100] and positive predictive value (PPV) of 96.3% [95% CI 92.2-100]. The high risk group of the MIRACLE2 model, which is significantly easier to calculate, had an AUC of 0.81 [95% CI 0.76-0.86], specificity of 92.3% [95% CI 87.2-97.4] and PPV of 95.2% [95% CI 91.9-98.4]. Conclusion: The CAHP, MIRACLE2, OHCA and TTM scores all perform comparably in a UK population to the original development and validation cohorts. All four scores outperform APACHE-II in a population of patients resuscitated from OHCA. CAHP and TTM perform best but are more complex to calculate than MIRACLE2, which displays inferior performance.

A transient protein folding response targets aggregation in the early phase of TDP-43-mediated neurodegeneration.

Understanding the mechanisms that drive TDP-43 pathology is integral to combating amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD) and other neurodegenerative diseases. Here we generated a longitudinal quantitative proteomic map of the cortex from the cytoplasmic TDP-43 rNLS8 mouse model of ALS and FTLD, and developed a complementary open-access webtool, TDP-map ( https://shiny.rcc.uq.edu.au/TDP-map/ ). We identified distinct protein subsets enriched for diverse biological pathways with temporal alterations in protein abundance, including increases in protein folding factors prior to disease onset. This included increased levels of DnaJ homolog subfamily B member 5, DNAJB5, which also co-localized with TDP-43 pathology in diseased human motor cortex. DNAJB5 over-expression decreased TDP-43 aggregation in cell and cortical neuron cultures, and knockout of Dnajb5 exacerbated motor impairments caused by AAV-mediated cytoplasmic TDP-43 expression in mice. Together, these findings reveal molecular mechanisms at distinct stages of ALS and FTLD progression and suggest that protein folding factors could be protective in neurodegenerative diseases.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Aggregation-prone TDP-43 sequesters and drives pathological transitions of free nuclear TDP-43.

Aggregation of the RNA-binding protein, TDP-43, is the unifying hallmark of amyotrophic lateral sclerosis and frontotemporal dementia. TDP-43-related neurodegeneration involves multiple changes to normal physiological TDP-43, which undergoes nuclear depletion, cytoplasmic mislocalisation, post-translational modification, and aberrant liquid-liquid phase separation, preceding inclusion formation. Along with toxic cytoplasmic aggregation, concurrent depletion and dysfunction of normal nuclear TDP-43 in cells with TDP-43 pathology is likely a key potentiator of neurodegeneration, but is not well understood. To define processes driving TDP-43 dysfunction, we used CRISPR/Cas9-mediated fluorescent tagging to investigate how disease-associated stressors and pathological TDP-43 alter abundance, localisation, self-assembly, aggregation, solubility, and mobility dynamics of normal nuclear TDP-43 over time in live cells. Oxidative stress stimulated liquid-liquid phase separation of endogenous TDP-43 into droplet-like puncta, or spherical shell-like anisosomes. Further, nuclear RNA-binding-ablated or acetylation-mimicking TDP-43 readily sequestered and depleted free normal nuclear TDP-43 into dynamic anisosomes, in which recruited endogenous TDP-43 proteins remained soluble and highly mobile. Large, phosphorylated inclusions formed by nuclear or cytoplasmic aggregation-prone TDP-43 mutants also caused sequestration, but rendered endogenous TDP-43 immobile and insoluble, indicating pathological transition. These findings suggest that RNA-binding deficiency and post-translational modifications including acetylation exacerbate TDP-43 aggregation and dysfunction by driving sequestration, mislocalisation, and depletion of normal nuclear TDP-43 in neurodegenerative diseases.

Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study.

COVID-19 is clinically characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied clustering techniques to a large prospective cohort of hospitalised patients with COVID-19 to identify clinically meaningful sub-phenotypes. We obtained structured clinical data on 59,011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25,477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33,534 cases recruited to ISARIC-4C, and in 4,445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-phenotypes. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were also identified, alongside a sub-phenotype of patients reporting few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom sub-phenotypes were highly consistent in replication analysis within the ISARIC-4C study. Similar patterns were externally verified in patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four sub-phenotypes are usefully distinct from the core symptom group: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms.

Whole-genome sequencing reveals host factors underlying critical COVID-19.

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

TDP-43 pathology: From noxious assembly to therapeutic removal.

Our understanding of amyotrophic lateral sclerosis and frontotemporal dementia has advanced dramatically since the discovery of cytoplasmic TAR DNA-binding protein 43 (TDP-43) inclusions as the hallmark pathology of these neurodegenerative diseases. Recent studies have provided insights into the physiological function of TDP-43 as an essential DNA-/RNA-modulating protein, and the triggers and consequences of TDP-43 dysfunction and aggregation. The formation of TDP-43 pathology is a progressive process, involving the generation of multiple distinct protein species, each with varying biophysical properties and roles in neurodegeneration. Here, we explore how the pathogenic changes to TDP-43, including mislocalisation, misfolding, aberrant liquid-liquid phase separation, stress granule assembly, oligomerisation, and post-translational modification, drive disease-associated aggregation in TDP-43 proteinopathies. We highlight how pathological TDP-43 species are formed and contribute to cellular dysfunction and toxicity, via both loss-of-function and gain-of-function mechanisms. We also review the role of protein homeostasis mechanisms, namely the ubiquitin proteasome system, autophagy-lysosome pathway, heat-shock response, and chaperone-mediated autophagy, in combating TDP-43 aggregation and discuss how their dysfunction likely promotes disease pathogenesis and progression. Finally, we evaluate pre-clinical studies aimed at enhancing TDP-43 protein clearance via these mechanisms and provide insight on promising strategies for future therapeutic advances. Harnessing the mechanisms that protect against or ameliorate TDP-43 pathology presents promising opportunities for developing disease-modifying treatments for these neurodegenerative diseases.

Riluzole does not ameliorate disease caused by cytoplasmic TDP-43 in a mouse model of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease commonly treated with riluzole, a small molecule that may act via modulation of glutamatergic neurotransmission. However, riluzole only modestly extends lifespan for people living with ALS, and its precise mechanisms of action remain unclear. Most ALS cases are characterised by accumulation of cytoplasmic TAR DNA binding protein of 43 kDa (TDP-43), and understanding the effects of riluzole in models that closely recapitulate TDP-43 pathology may provide insights for development of improved therapeutics. We therefore investigated the effects of riluzole in female transgenic mice that inducibly express nuclear localisation sequence (NLS)-deficient human TDP-43 in neurons (NEFH-tTA/tetO-hTDP-43ΔNLS, 'rNLS8', mice). Riluzole treatment from the first day of hTDP-43ΔNLS expression did not alter disease onset, weight loss or performance on multiple motor behavioural tasks. Riluzole treatment also did not alter TDP-43 protein levels, solubility or phosphorylation. Although we identified a significant decrease in GluA2 and GluA3 proteins in the cortex of rNLS8 mice, riluzole did not ameliorate this disease-associated molecular phenotype. Likewise, riluzole did not alter the disease-associated atrophy of hindlimb muscle in rNLS8 mice. Finally, riluzole treatment beginning after disease onset in rNLS8 mice similarly had no effect on progression of late-stage disease or animal survival. Together, we demonstrate specific glutamatergic receptor alterations and muscle fibre-type changes reminiscent of ALS in female rNLS8 mice, but riluzole had no effect on these or any other disease phenotypes. Future targeting of pathways related to accumulation of TDP-43 pathology may be needed to develop better treatments for ALS.

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice.

Phenotypic Assays for Characterizing Compound Effects on Induced Pluripotent Stem Cell-Derived Cardiac Spheroids.

Development of more complex, biologically relevant, and predictive cell-based assays for compound screening is a major challenge in drug discovery. The focus of this study was to establish high-throughput compatible three-dimensional (3D) cardiotoxicity assays using human induced pluripotent stem cell-derived cardiomyocytes. Using both high-content imaging and fast kinetic fluorescence imaging, the impact of various compounds on the beating rates and patterns of cardiac spheroids was monitored by changes in intracellular Ca2+ levels with calcium-sensitive dyes. Advanced image analysis methods were implemented to provide multiparametric characterization of the Ca2+ oscillation patterns. In addition, we used confocal imaging and 3D analysis methods to characterize compound effects on the morphology of 3D spheroids. This phenotypic assay allows for the characterization of parameters such as beating frequency, amplitude, peak width, rise and decay times, as well as cell viability and morphological characteristics. A set of 22 compounds, including a number of known cardioactive and cardiotoxic drugs, was assayed at different time points, and the calculated EC50 values for compound effects were compared between 3D and two-dimensional (2D) model systems. A significant concordance in the phenotypes was observed for compound effects between the two models, but essential differences in the concentration responses and time dependencies of the compound-induced effects were observed. Together, these results indicate that 3D cardiac spheroids constitute a functionally distinct biological model system from traditional flat 2D cultures. In conclusion, we have demonstrated that phenotypic assays using 3D model systems are enabled for screening and suitable for cardiotoxicity assessment in vitro.

The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.

Discovering known and unanticipated protein modifications using MS/MS database searching.

We present an MS/MS database search algorithm with the following novel features: (1) a novel protein database structure containing extensive preindexing and (2) zone modification searching, which enables the rapid discovery of protein modifications of known (i.e., user-specified) and unanticipated delta masses. All of these features are implemented in Interrogator, the search engine that runs behind the Pro ID, Pro ICAT, and Pro QUANT software products. Speed benchmarks demonstrate that our modification-tolerant database search algorithm is 100-fold faster than traditional database search algorithms when used for comprehensive searches for a broad variety of modification species. The ability to rapidly search for a large variety of known as well as unanticipated modifications allows a significantly greater percentage of MS/MS scans to be identified. We demonstrate this with an example in which, out of a total of 473 identified MS/MS scans, 315 of these scans correspond to unmodified peptides, while 158 scans correspond to a wide variety of modified peptides. In addition, we provide specific examples where the ability to search for unanticipated modifications allows the scientist to discover: unexpected modifications that have biological significance; amino acid mutations; salt-adducted peptides in a sample that has nominally been desalted; peptides arising from nontryptic cleavage in a sample that has nominally been digested using trypsin; other unintended consequences of sample handling procedures.