No interactions between previously associated 2-hour glucose gene variants and physical activity or BMI on 2-hour glucose levels.

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Background: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).Method: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.Results: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0. 902 for patients with ER-positive tumours (p = 2.3 x 10(-6)) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.Conclusion: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Measurement of the dependence of transverse energy production at large pseudorapidity on the hard-scattering kinematics of proton-proton collisions at √s=2.76 TeV with ATLAS

The relationship between jet production in the central region and the underlying-event activity in a pseudorapidity-separated region is studied in 4.0 pb-1 of s=2.76 TeV pp collision data recorded with the ATLAS detector at the LHC. The underlying event is characterised through measurements of the average value of the sum of the transverse energy at large pseudorapidity downstream of one of the protons, which are reported here as a function of hard-scattering kinematic variables. The hard scattering is characterised by the average transverse momentum and pseudorapidity of the two highest transverse momentum jets in the event. The dijet kinematics are used to estimate, on an event-by-event basis, the scaled longitudinal momenta of the hard-scattered partons in the target and projectile beam-protons moving toward and away from the region measuring transverse energy, respectively. Transverse energy production at large pseudorapidity is observed to decrease with a linear dependence on the longitudinal momentum fraction in the target proton and to depend only weakly on that in the projectile proton. The results are compared to the predictions of various Monte Carlo event generators, which qualitatively reproduce the trends observed in data but generally underpredict the overall level of transverse energy at forward pseudorapidity

Search for high-mass diphoton resonances in pp collisions at √s = 8 TeV with the ATLAS detector

This article describes a search for high-mass resonances decaying to a pair of photons using a sample of 20.3  fb−¹ of pp collisions at √s = 8 TeV recorded with the ATLAS detector at the Large Hadron Collider. The data are found to be in agreement with the Standard Model prediction, and limits are reported in the framework of the Randall-Sundrum model. This theory leads to the prediction of graviton states, the lightest of which could be observed at the Large Hadron Collider. A lower limit of 2.66 (1.41) TeV at 95% confidence level is set on the mass of the lightest graviton for couplings of k/M̄Pl=0.1(0.01)

Elevated CSF and plasma complement proteins in genetic frontotemporal dementia: results from the GENFI study

© The Author(s) 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background: Neuroinflammation is emerging as an important pathological process in frontotemporal dementia (FTD), but biomarkers are lacking. We aimed to determine the value of complement proteins, which are key components of innate immunity, as biomarkers in cerebrospinal fluid (CSF) and plasma of presymptomatic and symptomatic genetic FTD mutation carriers. Methods: We measured the complement proteins C1q and C3b in CSF by ELISAs in 224 presymptomatic and symptomatic GRN, C9orf72 or MAPT mutation carriers and non-carriers participating in the Genetic Frontotemporal Dementia Initiative (GENFI), a multicentre cohort study. Next, we used multiplex immunoassays to measure a panel of 14 complement proteins in plasma of 431 GENFI participants. We correlated complement protein levels with corresponding clinical and neuroimaging data, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Results: CSF C1q and C3b, as well as plasma C2 and C3, were elevated in symptomatic mutation carriers compared to presymptomatic carriers and non-carriers. In genetic subgroup analyses, these differences remained statistically significant for C9orf72 mutation carriers. In presymptomatic carriers, several complement proteins correlated negatively with grey matter volume of FTD-related regions and positively with NfL and GFAP. In symptomatic carriers, correlations were additionally observed with disease duration and with Mini Mental State Examination and Clinical Dementia Rating scale® plus NACC Frontotemporal lobar degeneration sum of boxes scores. Conclusions: Elevated levels of CSF C1q and C3b, as well as plasma C2 and C3, demonstrate the presence of complement activation in the symptomatic stage of genetic FTD. Intriguingly, correlations with several disease measures in presymptomatic carriers suggest that complement protein levels might increase before symptom onset. Although the overlap between groups precludes their use as diagnostic markers, further research is needed to determine their potential to monitor dysregulation of the complement system in FTD.This study was supported in the Netherlands by Memorabel grants from Deltaplan Dementie (ZonMw and Alzheimer Nederland; grant numbers 733050813, 733050103, 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte foundation (grant number 1402 1300), and the European Joint Programme—Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1) and the JPND GENFI-PROX grant (2019-02248); JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); ASE supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK; IJS is supported by the Alzheimer’s Association; JBR is supported by the Wellcome Trust (103838); in Spain by the Fundació Marató de TV3 (20143810 to RSV); in Germany by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and by grant 779357 “Solve-RD” from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Schörling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tjänarinnor, Karolinska Institutet Doctoral Funding, and StratNeuro. HZ is a Wallenberg Scholar.info:eu-repo/semantics/publishedVersio

Measurements of the charge asymmetry in top-quark pair production in the dilepton final state at s √ =8 TeV with the ATLAS detector

Measurements of the top-antitop quark pair production charge asymmetry in the dilepton channel, characterized by two high-pT leptons (electrons or muons), are presented using data corresponding to an integrated luminosity of 20.3  fb−1 from pp collisions at a center-of-mass energy s√=8  TeV collected with the ATLAS detector at the Large Hadron Collider at CERN. Inclusive and differential measurements as a function of the invariant mass, transverse momentum, and longitudinal boost of the tt¯ system are performed both in the full phase space and in a fiducial phase space closely matching the detector acceptance. Two observables are studied: AℓℓC based on the selected leptons and Att¯C based on the reconstructed tt¯ final state. The inclusive asymmetries are measured in the full phase space to be AℓℓC=0.008±0.006 and Att¯C=0.021±0.016, which are in agreement with the Standard Model predictions of AℓℓC=0.0064±0.0003 and Att¯C=0.0111±0.0004

A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions.This study was supported in the Netherlands by two Memorabel grants from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and Alzheimer Nederland; grant numbers 733050813,733050103 and 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte foundation (grant number 1402 1300), the European Joint Programme—Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); V.V. and S.K. have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 666992 (EuroPOND). E.B. was supported by the Hartstichting (PPP Allowance, 2018B011); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1); J.D.R. is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); I.J.S. is supported by the Alzheimer’s Association; J.B.R. is supported by the Wellcome Trust (103838); in Spain by the Fundació Marató de TV3 (20143810 to R.S.V.); in Germany by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and by grant 779357 ‘Solve-RD’ from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Schörling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tjänarinnor, Karolinska Institutet Doctoral Funding and StratNeuro. H.Z. is a Wallenberg Scholar.info:eu-repo/semantics/publishedVersio