Important pharmacogenetic information for drugs prescribed during the SARS-CoV-2 infection (COVID-19)

In December 2019, the severe acute respiratory syndrome virus-2 pandemic began, causing the coronavirus disease 2019. A vast variety of drugs is being used off-label as potential therapies. Many of the repurposed drugs have clinical pharmacogenetic guidelines available with therapeutic recommendations when prescribed as indicated on the drug label. The aim of this review is to provide a comprehensive summary of pharmacogenetic biomarkers available for these drugs, which may help to prescribe them more safelyM.N.-G. is co-financed by the European Social Fund and the Youth European Initiative; grant number PEJ-2018-TL/BMD-1108

Analysis of rare variants in the C3 gene in patients with age-related macular degeneration

Age-related macular degeneration (AMD) is a progressive retinal disorder affecting over 33 million people worldwide. Genome-wide association studies (GWASs) for AMD identified common variants at 19 loci accounting for 15-65% of the heritability and it has been hypothesized that the missing heritability may be attributed to rare variants with large effect sizes. Common variants in the complement component 3 (C3) gene have been associated with AMD and recently a rare C3 variant (Lys155Gln) was identified which exerts a large effect on AMD susceptibility independent of the common variants. To explore whether additional rare variants in the C3 gene are associated with AMD, we sequenced all coding exons in 84 unrelated AMD cases. Subsequently, we genotyped all identified variants in 1474 AMD cases and 2258 controls. Additionally, because of the known genetic overlap between AMD and atypical hemolytic uremic syndrome (aHUS), we genotyped two recurrent aHUS-associated C3 mutations in the entire cohort. Overall, we identified three rare variants (Lys65Gln (P = 0.04), Arg735Trp (OR = 17.4, 95% CI = 2.2-136; P = 0.0003), and Ser1619Arg (OR = 5.2, 95% CI = 1.0-25; P = 0.05) at the C3 locus that are associated with AMD in our EUGENDA cohort. However, the Arg735Trp and Ser1619Arg variants were not found to be associated with AMD in the Rotterdam Study. The Lys65Gln variant was only identified in patients from Nijmegen, the Netherlands, and thus may represent a region-specific AMD risk variant

PYTHIA 6.4 Physics and Manual

The PYTHIA program can be used to generate high-energy-physics `events', i.e. sets of outgoing particles produced in the interactions between two incoming particles. The objective is to provide as accurate as possible a representation of event properties in a wide range of reactions, within and beyond the Standard Model, with emphasis on those where strong interactions play a role, directly or indirectly, and therefore multihadronic final states are produced. The physics is then not understood well enough to give an exact description; instead the program has to be based on a combination of analytical results and various QCD-based models. This physics input is summarized here, for areas such as hard subprocesses, initial- and final-state parton showers, underlying events and beam remnants, fragmentation and decays, and much more. Furthermore, extensive information is provided on all program elements: subroutines and functions, switches and parameters, and particle and process data. This should allow the user to tailor the generation task to the topics of interest.Comment: 576 pages, no figures, uses JHEP3.cls. The code and further information may be found on the PYTHIA web page: http://www.thep.lu.se/~torbjorn/Pythia.html Changes in version 2: Mistakenly deleted section heading for "Physics Processes" reinserted, affecting section numbering. Minor updates to take into account referee comments and new colour reconnection option

Identification of new susceptibility loci for osteoarthritis (arcOGEN):a genome-wide association study

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Osteoarthritis is the most common form of arthritis worldwide and is a major cause of pain and disability in elderly people. The health economic burden of osteoarthritis is increasing commensurate with obesity prevalence and longevity. Osteoarthritis has a strong genetic component but the success of previous genetic studies has been restricted due to insufficient sample sizes and phenotype heterogeneity. We undertook a large genome-wide association study (GWAS) in 7410 unrelated and retrospectively and prospectively selected patients with severe osteoarthritis in the arcOGEN study, 80% of whom had undergone total joint replacement, and 11,009 unrelated controls from the UK. We replicated the most promising signals in an independent set of up to 7473 cases and 42,938 controls, from studies in Iceland, Estonia, the Netherlands, and the UK. All patients and controls were of European descent. We identified five genome-wide significant loci (binomial test p≤5·0×10(-8)) for association with osteoarthritis and three loci just below this threshold. The strongest association was on chromosome 3 with rs6976 (odds ratio 1·12 [95% CI 1·08-1·16]; p=7·24×10(-11)), which is in perfect linkage disequilibrium with rs11177. This SNP encodes a missense polymorphism within the nucleostemin-encoding gene GNL3. Levels of nucleostemin were raised in chondrocytes from patients with osteoarthritis in functional studies. Other significant loci were on chromosome 9 close to ASTN2, chromosome 6 between FILIP1 and SENP6, chromosome 12 close to KLHDC5 and PTHLH, and in another region of chromosome 12 close to CHST11. One of the signals close to genome-wide significance was within the FTO gene, which is involved in regulation of bodyweight-a strong risk factor for osteoarthritis. All risk variants were common in frequency and exerted small effects. Our findings provide insight into the genetics of arthritis and identify new pathways that might be amenable to future therapeutic intervention.Arthritis Research UK 1803

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Volume I. Introduction to DUNE

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE\u27s physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype