SJS/TEN 2019: From Science to Translation

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) are potentially life-threatening, immune-mediated adverse reactions characterized by widespread erythema, epidermal necrosis, and detachment of skin and mucosa. Efforts to grow and develop functional international collaborations and a multidisciplinary interactive network focusing on SJS/TEN as an uncommon but high burden disease will be necessary to improve efforts in prevention, early diagnosis and improved acute and long-term management. SJS/TEN 2019: From Science to Translation was a 1.5-day scientific program held April 26-27, 2019, in Vancouver, Canada. The meeting successfully engaged clinicians, researchers, and patients and conducted many productive discussions on research and patient care needs

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Overall survival after concurrent cisplatin-radiotherapy compared with radiotherapy alone in locoregionally advanced nasopharyngeal carcinoma

This phase III randomized study compared concurrent cisplatin-radiotherapy (CRT) versus radiotherapy (RT) alone in patients with locoregionally advanced nasopharyngeal carcinoma. A total of 350 patients were randomly assigned to receive external RT alone or concurrently with cisplatin at a dosage of 40 mg/m 2 weekly. The primary endpoint was overall survival, and the median follow-up was 5.5 years. The 5-year overall survival was 58.6% (95% confidence interval [CI] = 50.9% to 66.2%) for the RT arm and 70.3% (95% CI = 63.4% to 77.3%) for the CRT arm. In Cox regression analysis adjusted for T stage, age, and overall stage, the difference in overall survival was statistically significantly in favor of concurrent CRT (P = .049, hazard ratio [HR] = 0.71 [95% CI = 0.5 to 1.0]). Subgroup analysis demonstrated that there was no difference between overall survival in the arms for T1 /T2 stage (P = .74, HR = 0.93 [95% CI = 0.59 to 1.4] ), whereas there was a difference between the arms for T3/T4 stage (P = .013, HR = 0.51 [95% CI = 0.3 to 0.88]), favoring the CRT arm. The regimen of weekly concurrent CRT is a promising standard treatment strategy for locoregionally advanced nasopharyngeal carcinoma patients. © Oxford University Press 2005, all rights reserved.Link_to_subscribed_fulltex

Genetics of rheumatoid arthritis conributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery

Transverse momentum spectra of charged particles in proton–proton collisions at √s=900 GeV with ALICE at the LHC

The inclusive charged particle transverse momentum distribution is measured in proton–proton collisions at s=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|η|<0.8) over the transverse momentum range 0.15<pT<10 GeV/c. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for |η|<0.8 is 〈pT〉INEL=0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉NSD=0.489±0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger 〈pT〉 than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET