TIGER : The gene expression regulatory variation landscape of human pancreatic islets

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.Peer reviewe

Single nucleotide polymorphisms in DNA repair genes as risk factors associated to prostate cancer progression

Background Besides serum levels of PSA, there is a lack of prostate cancer specific biomarkers. It is need to develop new biological markers associated with the tumor behavior which would be valuable to better individualize treatment. The aim of this study was to elucidate the relationship between single nucleotide polymorphisms (SNPs) in genes involved in DNA repair and prostate cancer progression.Methods A total of 494 prostate cancer patients from a Spanish multicenter study were genotyped for 10 SNPs in XRCC1, ERCC2, ERCC1, LIG4, ATM and TP53 genes. The SNP genotyping was made in a Biotrove OpenArray® NT Cycler. Clinical tumor stage, diagnostic PSA serum levels, and Gleason score at diagnosis were obtained for all participants. Genotypic and allelic frequencies were determined using the web-based environment SNPator.Results SNPs rs11615 (ERCC1) and rs17503908 (ATM) appeared as risk factors for prostate cancer aggressiveness. Patients wild homozygous for these SNPs (AA and TT, respectively) were at higher risk for developing cT2b – cT4 (OR = 2.21 (confidence interval (CI) 95% 1.47 – 3.31), p < 0.001) and Gleason scores ≥ 7 (OR = 2.22 (CI 95% 1.38 – 3.57), p < 0.001), respectively. Moreover, those patients wild homozygous for both SNPs had the greatest risk of presenting D’Amico high-risk tumors (OR = 2.57 (CI 95% 1.28 – 5.16)).Conclusions Genetic variants at DNA repair genes are associated with prostate cancer progression, and would be taken into account when assessing the malignancy of prostate cancer.This work was subsidized by a grant from the Instituto de Salud Carlos III (Ministerio de Economía y Competitividad from Spain), ID: PI12/01867. Almudena Valenciano has a grant from the Instituto Canario de Investigación del Cáncer (ICIC)

Anaesthetic Impairment of Immune Function Is Mediated via GABAA Receptors

GABA(A) receptors are members of the Cys-loop family of neurotransmitter receptors, proteins which are responsible for fast synaptic transmission, and are the site of action of wide range of drugs. Recent work has shown that Cys-loop receptors are present on immune cells, but their physiological roles and the effects of drugs that modify their function in the innate immune system are currently unclear. We are interested in how and why anaesthetics increase infections in intensive care patients; a serious problem as more than 50% of patients with severe sepsis will die. As many anaesthetics act via GABA(A) receptors, the aim of this study was to determine if these receptors are present on immune cells, and could play a role in immunocompromising patients.We demonstrate, using RT-PCR, that monocytes express GABA(A) receptors constructed of α1, α4, β2, γ1 and/or δ subunits. Whole cell patch clamp electrophysiological studies show that GABA can activate these receptors, resulting in the opening of a chloride-selective channel; activation is inhibited by the GABA(A) receptor antagonists bicuculline and picrotoxin, but not enhanced by the positive modulator diazepam. The anaesthetic drugs propofol and thiopental, which can act via GABA(A) receptors, impaired monocyte function in classic immunological chemotaxis and phagocytosis assays, an effect reversed by bicuculline and picrotoxin.Our results show that functional GABA(A) receptors are present on monocytes with properties similar to CNS GABA(A) receptors. The functional data provide a possible explanation as to why chronic propofol and thiopental administration can increase the risk of infection in critically ill patients: their action on GABA(A) receptors inhibits normal monocyte behaviour. The data also suggest a potential solution: monocyte GABA(A) receptors are insensitive to diazepam, thus the use of benzodiazepines as an alternative anesthetising agent may be advantageous where infection is a life threatening problem

Genetic Cross-Interaction between APOE and PRNP in Sporadic Alzheimer's and Creutzfeldt-Jakob Diseases

Alzheimer's disease (AD) and Creutzfeldt-Jakob disease (CJD) represent two distinct clinical entities belonging to a wider group, generically named as conformational disorders that share common pathophysiologic mechanisms. It is well-established that the APOE ε4 allele and homozygosity at polymorphic codon 129 in the PRNP gene are the major genetic risk factors for AD and human prion diseases, respectively. However, the roles of PRNP in AD, and APOE in CJD are controversial. In this work, we investigated for the first time, APOE and PRNP genotypes simultaneously in 474 AD and 175 sporadic CJD (sCJD) patients compared to a common control population of 335 subjects. Differences in genotype distribution between patients and control subjects were studied by logistic regression analysis using age and gender as covariates. The effect size of risk association and synergy factors were calculated using the logistic odds ratio estimates. Our data confirmed that the presence of APOE ε4 allele is associated with a higher risk of developing AD, while homozygosity at PRNP gene constitutes a risk for sCJD. Opposite, we found no association for PRNP with AD, nor for APOE with sCJD. Interestingly, when AD and sCJD patients were stratified according to their respective main risk genes (APOE for AD, and PRNP for sCJD), we found statistically significant associations for the other gene in those strata at higher previous risk. Synergy factor analysis showed a synergistic age-dependent interaction between APOE and PRNP in both AD (SF = 3.59, p = 0.027), and sCJD (SF = 7.26, p = 0.005). We propose that this statistical epistasis can partially explain divergent data from different association studies. Moreover, these results suggest that the genetic interaction between APOE and PRNP may have a biological correlate that is indicative of shared neurodegenerative pathways involved in AD and sCJD

Measurement of VH, H → b b ¯ production as a function of the vector-boson transverse momentum in 13 TeV pp collisions with the ATLAS detector

Cross-sections of associated production of a Higgs boson decaying into bottom-quark pairs and an electroweak gauge boson, W or Z, decaying into leptons are measured as a function of the gauge boson transverse momentum. The measurements are performed in kinematic fiducial volumes defined in the `simplified template cross-section' framework. The results are obtained using 79.8 fb-1 of proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13 TeV. All measurements are found to be in agreement with the Standard Model predictions, and limits are set on the parameters of an effective Lagrangian sensitive to modifications of the Higgs boson couplings to the electroweak gauge bosons

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at \sqrt{s}=13 TeV

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 \hbox {fb}^{-1} of pp collision data at \sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z\rightarrow \mu \mu and J/\psi \rightarrow \mu \mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |\eta |<2.7

Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger

The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the newMultichip Modules along with the improvements to the signal processing achieved.ANPCyTYerPhI, ArmeniaAustralian Research CouncilBMWFW, AustriaAustrian Science Fund (FWF)Azerbaijan National Academy of Sciences (ANAS)SSTC, BelarusNational Council for Scientific and Technological Development (CNPq)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Natural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationNational Natural Science Foundation of China (NSFC)Departamento Administrativo de Ciencia, Tecnología e Innovación ColcienciasMinistry of Education, Youth & Sports - Czech Republic Czech Republic GovernmentCzech Republic GovernmentDNRF, DenmarkDanish Natural Science Research CouncilCentre National de la Recherche Scientifique (CNRS)CEA-DRF/IRFU, FranceFederal Ministry of Education & Research (BMBF)Max Planck SocietyGreek Ministry of Development-GSRTRGC and Hong Kong SAR, ChinaIsrael Science FoundationBenoziyo Center, IsraelIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of ScienceCNRST, MoroccoRCN, NorwayPortuguese Foundation for Science and TechnologyMNE/IFA, RomaniaMES of RussiaMESTD, SerbiaMSSR, SlovakiaSlovenian Research Agency - SloveniaMIZS, SloveniaSpanish GovernmentSRC, SwedenWallenberg Foundation, SwedenSNSF Geneva, SwitzerlandMinistry of Science and Technology, TaiwanMinistry of Energy & Natural Resources - TurkeyScience & Technology Facilities Council (STFC)United States Department of Energy (DOE)National Science Foundation (NSF)BCKDF, CanadaCANARIE, CanadaCRC, CanadaEuropean Research Council (ERC)European Union (EU)French National Research Agency (ANR)German Research Foundation (DFG)Alexander von Humboldt FoundationGreek NSRF, GreeceBSF-NSF, IsraelGerman-Israeli Foundation for Scientific Research and DevelopmentLa Caixa Banking Foundation, SpainCERCA Programme Generalitat de Catalunya, SpainPROMETEO, SpainGenT Programmes Generalitat Valenciana, SpainGoran Gustafssons Stiftelse, SwedenRoyal Society of LondonLeverhulme TrustNRC, CanadaCERNANID, ChileChinese Academy of SciencesMinistry of Science and Technology, ChinaSRNSFG, GeorgiaHGF, GermanyNetherlands Organization for Scientific Research (NWO) Netherlands GovernmentMinistry of Science and Higher Education, PolandNCN, PolandNRCKI, Russia FederationJINRDST/NRF, South AfricaSERI, Geneva, SwitzerlandCantons of Bern and Geneva, SwitzerlandCompute Canada, CanadaHorizon 2020Marie Sklodowska-Curie ActionsEuropean Cooperation in Science and Technology (COST)EU-ESF, Greec