Defective extracellular matrix remodeling in brown adipose tissue is associated with fibro-inflammation and reduced diet-induced thermogenesis.

The relevance of extracellular matrix (ECM) remodeling is reported in white adipose tissue (AT) and obesity-related dysfunctions, but little is known about the importance of ECM remodeling in brown AT (BAT) function. Here, we show that a time course of high-fat diet (HFD) feeding progressively impairs diet-induced thermogenesis concomitantly with the development of fibro-inflammation in BAT. Higher markers of fibro-inflammation are associated with lower cold-induced BAT activity in humans. Similarly, when mice are housed at thermoneutrality, inactivated BAT features fibro-inflammation. We validate the pathophysiological relevance of BAT ECM remodeling in response to temperature challenges and HFD using a model of a primary defect in the collagen turnover mediated by partial ablation of the Pepd prolidase. Pepd-heterozygous mice display exacerbated dysfunction and BAT fibro-inflammation at thermoneutrality and in HFD. Our findings show the relevance of ECM remodeling in BAT activation and provide a mechanism for BAT dysfunction in obesity.

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.

Real-world evidence with a retrospective cohort of 15,968 Andalusian COVID-19 hospitalized patients suggests 21 new effective treatments and one drug that increases death risk.

Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19. Using data from a central registry of electronic health records (the Andalusian Population Health Database, BPS), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient survival was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality.

Assessing the impact of SARS-CoV-2 lineages and mutations on patient survival

After more than two years of COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations whose impact on COVID-19 severity and patient survival is uncertain. A total of 764 SARS-CoV-2 genomes sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30st April 2021, along with their clinical data, were used for survival analysis. A significant association of B.1.1.7, the alpha lineage, with patient mortality (Log Hazard ratio LHR=0.51, C.I.=[0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome rendered 27 of them significantly associated with higher mortality of patients. Most of these mutations were located in the S, ORF8 and N proteins. This study illustrates how a combination of genomic and clinical data provide solid evidence on the impact of viral lineage on patient survival.

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic [~]0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.

From partial to whole genome imputation of SARS-CoV-2 for epidemiological surveillance

Backgroundthe current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data. ResultsWe developed impuSARS, an application that includes Minimac, the most widely used strategy for genomic data imputation and, taking advantage of the enormous amount of SARS-CoV-2 whole genome sequences available, a reference panel containing 239,301 sequences was built. The impuSARS application was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing) showing great fidelity when reconstructing the original sequences. The impuSARS application is also able to impute whole genomes from commercial kits covering less than 20% of the genome or only from the Spike protein with a precision of 0.96. It also recovers the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (< 20%) Conclusionsimputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. impuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole genome sequencing.

Real world evidence of calcifediol use and mortality rate of COVID-19 hospitalized in a large cohort of 16,401 Andalusian patients

BackgroundCOVID-19 is a major worldwide health problem because of acute respiratory distress syndrome, and mortality. Several lines of evidence have suggested a relationship between the vitamin D endocrine system and severity of COVID-19. MethodsWe present a retrospective survival study that includes all Andalusian patients hospitalized between January and November 2020 because of COVID-19 infection. Based on a central registry of electronic health records (the Andalusian Population Health Database, BPS), prescription of vitamin D or its metabolites within 15-30 days before hospitalization were recorded. The effect of treatment with vitamin D metabolites for other indication previous to the hospitalization was studied with respect to patient survival by means of Kaplan-Meyer survival curves and Log Hazard Ratios, using a propensity score to compensate the disbalance of compared classes and the confounding factors. The availability of detailed patient data in the BPS allowed to obtain Real-World Evidence (RWE) of the effects of prior use of vitamin D or its metabolites on the mortality due to COVID-19 infection. FindingsA retrospective cohort of 16.401patients was extracted from the BPS, which includes all the patients hospitalized with COVID-19 diagnosis between January and November 2020 in Andalusia, one of the largest regions in Europe with the size of an average median country. A total of 358 patients were found with cholecalciferol, and 193 with calcifediol, prescriptions 15 days before hospitalization. For a period extended to 30 days before hospitalization, the numbers increase to 416 and 210 and, respectively. Kaplan-Meyer survival curves and hazard ratios support an association between consumption of these metabolites and patient survival. Such association was stronger in calcifediol (Log Hazard Ratio, LHR = -1.27{+/-}0.32) than in cholecalciferol (LHR= -0.56{+/-}0.15), when prescribed 15 days before hospitalization This effect decreases when a larger 30 days period is considered (calcifediol LHR= -1.01{+/-}0.27 and cholecalciferol LHR= -0.27{+/-}0.12), suggesting that the closer was the treatment to the hospitalization the stronger the association. ConclusionsA significant reduction in mortality in patients hospitalized with COVID-19 is associated with the prescription of vitamin D, especially calcifediol, within 15-30 days prior to hospitalization.

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.

Exploring sunflower responses to Sclerotinia head rot at early stages of infection using RNA-seq analysis.

Sclerotinia head rot (SHR), caused by the necrotrophic fungus Sclerotinia sclerotiorum, is one of the most devastating sunflower crop diseases. Despite its worldwide occurrence, the genetic determinants of plant resistance are still largely unknown. Here, we investigated the Sclerotinia-sunflower pathosystem by analysing temporal changes in gene expression in one susceptible and two tolerant inbred lines (IL) inoculated with the pathogen under field conditions. Differential expression analysis showed little overlapping among ILs, suggesting genotype-specific control of cell defense responses possibly related to differences in disease resistance strategies. Functional enrichment assessments yielded a similar pattern. However, all three ILs altered the expression of genes involved in the cellular redox state and cell wall remodeling, in agreement with current knowledge about the initiation of plant immune responses. Remarkably, the over-representation of long non-coding RNAs (lncRNA) was another common feature among ILs. Our findings highlight the diversity of transcriptional responses to SHR within sunflower breeding lines and provide evidence of lncRNAs playing a significant role at early stages of defense.

Mechanistic modeling of the SARS-CoV-2 disease map

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map in which the detailed activity of the human signaling circuits related to the viral infection and the different antiviral responses, including immune and inflammatory activities, can be inferred from gene expression experiments. Moreover, given to the mechanistic properties of the model, the effect of potential interventions, such as knock-downs, over-expression or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied in specific conditions. By providing a holistic, systems biology approach to the understanding of the complexities of the viral infection process, this tool will become an important asset in the search for efficient antiviral treatments. The tool is freely available at: http://hipathia.babelomics.org/covid19/