Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?

In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA in vitro studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon–intron boundaries of BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, ATM, BRIP1, CDH1, PALB2, PTEN, RAD51D, STK11, and TP53, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites.We provide recommendations for combining algorithms to conduct in silico splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by in vitro RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors

Risk categories in COVID-19 based on degrees of inflammation: data on more than 17,000 patients from the Spanish SEMI-COVID-19 registry

Background: the inflammation or cytokine storm that accompanies COVID-19 marks the prognosis. This study aimed to identify three risk categories based on inflammatory parameters on admission. Methods: retrospective cohort study of patients diagnosed with COVID-19, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish SEMI-COVID-19 Registry. The three categories of low, intermediate, and high risk were determined by taking into consideration the terciles of the total lymphocyte count and the values of C-reactive protein, lactate dehydrogenase, ferritin, and D-dimer taken at the time of admission. Results: a total of 17,122 patients were included in the study. The high-risk group was older (57.9 vs. 64.2 vs. 70.4 years; p < 0.001) and predominantly male (37.5% vs. 46.9% vs. 60.1%; p < 0.001). They had a higher degree of dependence in daily tasks prior to admission (moderate-severe dependency in 10.8% vs. 14.1% vs. 17%; p < 0.001), arterial hypertension (36.9% vs. 45.2% vs. 52.8%; p < 0.001), dyslipidemia (28.4% vs. 37% vs. 40.6%; p < 0.001), diabetes mellitus (11.9% vs. 17.1% vs. 20.5%; p < 0.001), ischemic heart disease (3.7% vs. 6.5% vs. 8.4%; p < 0.001), heart failure (3.4% vs. 5.2% vs. 7.6%; p < 0.001), liver disease (1.1% vs. 3% vs. 3.9%; p = 0.002), chronic renal failure (2.3% vs. 3.6% vs. 6.7%; p < 0.001), cancer (6.5% vs. 7.2% vs. 11.1%; p < 0.001), and chronic obstructive pulmonary disease (5.7% vs. 5.4% vs. 7.1%; p < 0.001). They presented more frequently with fever, dyspnea, and vomiting. These patients more frequently required high flow nasal cannula (3.1% vs. 4.4% vs. 9.7%; p < 0.001), non-invasive mechanical ventilation (0.9% vs. 3% vs. 6.3%; p < 0.001), invasive mechanical ventilation (0.6% vs. 2.7% vs. 8.7%; p < 0.001), and ICU admission (0.9% vs. 3.6% vs. 10.6%; p < 0.001), and had a higher percentage of in-hospital mortality (2.3% vs. 6.2% vs. 23.9%; p < 0.001). The three risk categories proved to be an independent risk factor in multivariate analyses. Conclusion: the present study identifies three risk categories for the requirement of high flow nasal cannula, mechanical ventilation, ICU admission, and in-hospital mortality based on lymphopenia and inflammatory parameters

Computational tools for splicing defect prediction in breast/ovarian cancer genes: how efficient are they at predicting RNA alterations?

In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA in vitro studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon-intron boundaries of BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, ATM, BRIP1, CDH1, PALB2, PTEN, RAD51D, STK11, and TP53, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites. We provide recommendations for combining algorithms to conduct in silico splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by in vitro RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors

H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells

In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type-independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Computational tools for splicing defect prediction in breast/ovarian cancer genes: how efficient are they at predicting RNA alterations?

In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA in vitro studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon-intron boundaries of BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, ATM, BRIP1, CDH1, PALB2, PTEN, RAD51D, STK11, and TP53, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites. We provide recommendations for combining algorithms to conduct in silico splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by in vitro RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors

Sharing Plant Uses with Animals: Plants Used for Feeding and Curing Humans and Animals in the Spanish Inventory of Traditional Knowledge Related to Biodiversity

Trabajo presentado en la 57th Annual Meeting of the Society for Economic Botany (Cultural resilience and resource extraction: preserving plants & people of degraded ecosystems), celebrada en Pine Mountain (USA) del 5 al 9 de junio de 2016.Spain has a very rich and dynamic traditional ecological knowledge system that has suffered severe erosion over the last decades. This knowledge has been deeply influenced by a rich and diverse historical heritage that includes many centuries old documents from ancient cultures, some over 2000 years old. Spanish acute useful flora comprises around 3,000 species, most of them autochthonous. A team of more than 70 scientists from more than 30 universities and other research centres are developing the Spanish Inventory of Traditional Knowledge. The inventory includes a database with information from over180 papers. The review of such papers showed that more than 2,300 plant species are used in human and animal food and medicine: 1,681 in human medicine, 1,295 in animal food, 953 in human food and 709 in veterinary medicine. Nearly 14% of the species (313) are shared in the four categories and a very important amount of species are used both for humans and animals: 35% of the species (800) are employed in animal food and medicine, 31% (710) in human food and medicine, 28% (650) in human and veterinary medicine and 27% (624) in animal and human food. This high percentage of overlap between human and animal uses may indicate that the observation of animal behaviour , specially feeding and selfmedication behaviours, might have given clues to humans on how to use food and medicinal plants[Lo1]. It also reinforces the idea that food and medicine represent a continuum not only for humans, but also for animals.Peer reviewe

Sustainability of traditional ecological knowledge: importance, distribution, endemicity and conservation of Spanish medicinal plants

Trabajo presentado en la 58th Annual Meeting of the Society for Economic Botany (Living in a global world: local knowledge ans sustainability), celebrada en Braganza (Portugal) del 4 al 9 de junio de 2017.-- IECTB authors: L Aceituno, R Acosta, A Alvarez, E Barroso, J Blanco, MA Bonet, L Calvet, E Carrio, R Cavero, U DAmbrosio , L Delgado, J Fajardo, I Fernandez-Ordonez, J Garcia, T Garnatje, JA Gonzalez, R Gonzalez-Tejero, A Gras, E Hernandez-Bermejo, E Laguna, JA Latorre, C. Lopez, MJ Macia, E Marcos, V Martinez, G Menendez, M Molina, R Morales, LM Munoz, C Obon, R Ontillera, M Parada, A Perdomo, I Perez, MP Puchades, V Reyes-Garcia, M Rigat, S Rios, D Rivera, R Rodriguez, O Rodriguez, R Roldan, L San Joaquin, FJ Tardio, JR Vallejo, J Valles, H Velasco and A Verde.More than 17,000 of the plant species of the world have been used as medicines. The Mediterranean basin, and specifically Spain, has a great floristic and ethnobotanical richness, comprising its useful flora around 3,000 plant species. This paper studies medicinal plants traditionally used in Spain in order to analyze the sustainability of their exploitation. Given that sustainability is related to the amount of the resource and its gathering pressure, its availability and cultural importance were analysed based on: the number of papers cited from a selection of over 180 papers, the number of 10x10 km UTM grid cells in which the plants were represented, the number of phytosociological inventories in which the presence of the plant has been registered, and searched on their current conservation status in European, national and regional legislations. The total number of wild or naturalized medicinal species in Spain reaches 1,393, 15% of them being endemic. A positive correlation was found among cultural importance and abundance (ρ=0.48) and among cultural importance and distribution (ρ=0.502), showing that abundant widely distributed species are those more commonly used. Most of the medicinal plants (72%) do not appear on the consulted regulations and do not have any legal protection or known threat and only 11 species are registered in any of the annexes of the European Habitats directive. While this study confirms that people tend to select as medicinal abundant and widely distributed species, many other criteria are used for selecting them.Peer reviewe