{Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at s \sqrt{s} = 13 TeV}

A search for direct production of low-mass dimuon resonances is performed using = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017–2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb−1. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1–2.6 GeV and 4.2–7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world’s best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε2 in the dark photon model above 10−6 are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θH) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tan β = 0.5

Biological insights from 108 schizophrenia-associated genetic loci

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 x 10(-15)), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 x 10(-6)). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 x 10(-11)) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 x 10(-5)). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination

Bempegaldesleukin Plus Nivolumab in First-Line Metastatic Melanoma.

PURPOSE: Therapies that produce deep and durable responses in patients with metastatic melanoma are needed. This phase II cohort from the international, single-arm PIVOT-02 study evaluated the CD122-preferential interleukin-2 pathway agonist bempegaldesleukin (BEMPEG) plus nivolumab (NIVO) in first-line metastatic melanoma. METHODS: A total of 41 previously untreated patients with stage III/IV melanoma received BEMPEG 0.006 mg/kg plus NIVO 360 mg once every 3 weeks for ≤ 2 years; 38 were efficacy-evaluable (≥ 1 postbaseline scan). Primary end points were safety and objective response rate (blinded independent central review); other end points included progression-free survival, overall survival (OS), and exploratory biomarkers. RESULTS: At 29.0 months\u27 median follow-up, the objective response rate was 52.6% (20 of 38 patients), and the complete response rate was 34.2% (13 of 38 patients). Median change in size of target lesions from baseline was -78.5% (response-evaluable population); 47.4% (18 of 38 patients) experienced complete clearance of target lesions. Median progression-free survival was 30.9 months (95% CI, 5.3 to not estimable). Median OS was not reached; the 24-month OS rate was 77.0% (95% CI, 60.4 to 87.3). Grade 3 and 4 treatment-related and immune-mediated adverse events occurred in 17.1% (7 of 41) and 4.9% (2 of 41) of patients, respectively. Increased polyfunctional responses in CD8+ and CD4+ T cells were seen in blood after treatment, driven by cytokines with effector functions. Early on-treatment blood biomarkers (CD8+ polyfunctional strength difference and eosinophils) correlated with treatment response. CONCLUSION: BEMPEG in combination with NIVO was tolerated, with relatively low rates of grade 3 and 4 treatment-related and immune-mediated adverse events. The combination had encouraging antitumor activity in first-line metastatic melanoma, including an extended median progression-free survival. Exploratory analyses associated noninvasive, on-treatment biomarkers with response, before radiologic evidence was observed

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi sublining fibroblasts, IL1B+ pro-inflammatory monocytes, ITGAX+TBX21+ autoimmune-associated B cells and PDCD1+ peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+ T cells characterized by GZMK+, GZMB+, and GNLY+ phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis

A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework

Background: There is considerable evidence that many complex traits have a partially shared genetic basis, termed pleiotropy. It is therefore useful to consider integrating genome-wide association study (GWAS) data across several traits, usually at the summary statistic level. A major practical challenge arises when these GWAS have overlapping subjects. This is particularly an issue when estimating pleiotropy using methods that condition the significance of one trait on the signficance of a second, such as the covariate-modulated false discovery rate (cmfdr). Results: We propose a method for correcting for sample overlap at the summary statistic level. We quantify the expected amount of spurious correlation between the summary statistics from two GWAS due to sample overlap, and use this estimated correlation in a simple linear correction that adjusts the joint distribution of test statistics from the two GWAS. The correction is appropriate for GWAS with case-control or quantitative outcomes. Our simulations and data example show that without correcting for sample overlap, the cmfdr is not properly controlled, leading to an excessive number of false discoveries and an excessive false discovery proportion. Our correction for sample overlap is effective in that it restores proper control of the false discovery rate, at very little loss in power. Conclusions: With our proposed correction, it is possible to integrate GWAS summary statistics with overlapping samples in a statistical framework that is dependent on the joint distribution of the two GWAS