Establishing a new baseline for monitoring the status of EU Spatial Data Infrastructure: Experiences and conclusions from INSPIRE 2019 monitoring and reporting

The INSPIRE Directive, which aims to establish a pan-European Spatial Data Infrastructure for the purposes of EU environmental policies, requires Member States to monitor and report on the implementation status on an annual basis. The way the INSPIRE monitoring and reporting process was performed in 2019 was driven by Commission Implementing Decision (EU) 2019/1372, which introduced the automated calculation of 19 new indicators through the direct use of the INSPIRE Geoportal and the INSPIRE Reference Validator to process the metadata harvested from Member States discovery services. These indicators are grouped into 5 categories: availability of spatial data and services, conformity of metadata, conformity of spatial data sets, accessibility of spatial data sets through view and download services, and conformity of network services. Most indicators are calculated as a percentage, thus providing a direct measure of performance and allowing also country-by-country comparisons. For each indicator, this report provides a detailed description of the calculation method, the values achieved for all Member States and some summary statistics to capture the overall performance trends. The results show that the status of INSPIRE implementation is very heterogeneous across the EU, with some countries performing well and some others still lagging behind. However, after 13 years from the entry into force of the Directive, there is no single country which has yet achieved full implementation according to the roadmap. The accessibility of data sets through view or download services is on average only about 30%, while the conformity of metadata, data sets and network services varies between 30% and 45% on average. In addition to providing an objective snapshot of the current status of INSPIRE implementation, the results of 2019 monitoring and reporting represent a reliable baseline to monitor the evolution of the EU Spatial Data Infrastructure and its contribution to the European Green Deal data space in the years to come.JRC.B.6-Digital Econom

The effect of LRRK2 loss-of-function variants in humans

Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson’s disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns5–8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9, 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work10, confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.</p

Author Correction: The effect of LRRK2 loss-of-function variants in humans

A Correction to this paper has been published: https://doi.org/10.1038/s41591-020-01185-6

The effect of LRRK2 loss-of-function variants in humans

Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson’s disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns5–8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9, 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work10, confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery

Non-AIDS defining cancers in the D:A:D Study - time trends and predictors of survival : A cohort study

Background: Non-AIDS defining cancers (NADC) are an important cause of morbidity and mortality in HIV-positive individuals. Using data from a large international cohort of HIV-positive individuals, we described the incidence of NADC from 2004-2010, and described subsequent mortality and predictors of these.Methods: Individuals were followed from 1st January 2004/enrolment in study, until the earliest of a new NADC, 1st February 2010, death or six months after the patient's last visit. Incidence rates were estimated for each year of follow-up, overall and stratified by gender, age and mode of HIV acquisition. Cumulative risk of mortality following NADC diagnosis was summarised using Kaplan-Meier methods, with follow-up for these analyses from the date of NADC diagnosis until the patient's death, 1st February 2010 or 6 months after the patient's last visit. Factors associated with mortality following NADC diagnosis were identified using multivariable Cox proportional hazards regression.Results: Over 176,775 person-years (PY), 880 (2.1%) patients developed a new NADC (incidence: 4.98/1000PY [95% confidence interval 4.65, 5.31]). Over a third of these patients (327, 37.2%) had died by 1st February 2010. Time trends for lung cancer, anal cancer and Hodgkin's lymphoma were broadly consistent. Kaplan-Meier cumulative mortality estimates at 1, 3 and 5 years after NADC diagnosis were 28.2% [95% CI 25.1-31.2], 42.0% [38.2-45.8] and 47.3% [42.4-52.2], respectively. Significant predictors of poorer survival after diagnosis of NADC were lung cancer (compared to other cancer types), male gender, non-white ethnicity, and smoking status. Later year of diagnosis and higher CD4 count at NADC diagnosis were associated with improved survival. The incidence of NADC remained stable over the period 2004-2010 in this large observational cohort.Conclusions: The prognosis after diagnosis of NADC, in particular lung cancer and disseminated cancer, is poor but has improved somewhat over time. Modifiable risk factors, such as smoking and low CD4 counts, were associated with mortality following a diagnosis of NADC. © 2013 Worm et al.; licensee BioMed Central Ltd

Structural robustness of RC frames under blast events

This paper presents a numerical procedure for the robustness quantification of RC frames under blast-induced damage scenarios. The procedure is supported by a non-linear numerical analysis, by quantifying the structural response at the global level (i.e., response of the structural system/frame to the blast-induced damage) and by obtaining the so-called “robustness curves”, representing the residual strength of the structure under increasing damage levels. The procedure is then applied to a 2D RC frame structure. The sensitivity of the robustness curves with respect to a set of analysis parameters is discusse