Crossing Borders Between Frontotemporal Dementia and Psychiatric Disorders: An Updated Overview

Frontotemporal dementia (FTD) includes a group of neurocognitive syndromes, clinically characterized by altered behaviors, impairment of language proficiency, and altered executive functioning. FTD is one of the most frequently observed forms of dementia in the elderly population and the most common in presenile age. As for other subtypes of dementia, FTD incidence is constantly on the rise due to the steadily increasing age of the population, and its recognition is now becoming a determinant for clinicians. FTD and psychiatric disorders can overlap in terms of clinical presentations by sharing a common genetic predisposition and neuropathological mechanism in some cases. Nonetheless, this association is often unclear and underestimated. Since its first reports, research into FTD has constantly grown, with the identification of recent findings related to its neuropathology, genetic, clinical, and therapeutic issues. Literature is thriving on this topic, with numerous research articles published in recent years. In the present review, we aimed to provide an updated description of the clinical manifestations that link and potentially confound the diagnosis of FTD and psychiatric disorders in order to improve their differential diagnosis and early detection. In particular, we systematically reviewed the literature, considering articles specifically focused on the behavioral variant FTD, published after 2015 on the PubMed database

CSF β-amyloid predicts prognosis in patients with multiple sclerosis

Background: The importance of predicting disease progression in multiple sclerosis (MS) has increasingly been recognized, and hence reliable biomarkers are needed. Objectives: To investigate the prognostic role of cerebrospinal fluid (CSF) amyloid beta 1\u201342 (A\u3b2) levels by the determination of a cut-off value to classify patients in slow and fast progressors. To evaluate possible association with white matter (WM) and grey matter (GM) damage at early disease stages. Methods: Sixty patients were recruited and followed up for 3\u20135 years. Patients underwent clinical assessment, brain magnetic resonance imaging (MRI; at baseline and after 1 year), and CSF analysis to determine A\u3b2 levels. T1-weighted volumes were calculated. T2-weighted scans were used to quantify WM lesion loads. Results: Lower CSF A\u3b2 levels were observed in patients with a worse follow-up Expanded Disability Status Scale (EDSS; r = 120.65, p < 0.001). The multiple regression analysis confirmed CSF A\u3b2 concentration as a predictor of patients\u2019 EDSS increase (r = 120.59, p < 0.0001). Generating a receiver operating characteristic curve, a cut-off value of 813 pg/mL was determined as the threshold able to identify patients with worse prognosis (95% confidence interval (CI): 0.690\u20130.933, p = 0.0001). No differences in CSF tau and neurofilament light chain (NfL) levels were observed (p > 0.05). Conclusion: Low CSF A\u3b2 levels may represent a predictive biomarker of disease progression in MS

Age at symptom onset and death and disease duration in genetic frontotemporal dementia : an international retrospective cohort study

Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49\ub75 years (SD 10\ub70; onset) and 58\ub75 years (11\ub73; death) in the MAPT group, 58\ub72 years (9\ub78; onset) and 65\ub73 years (10\ub79; death) in the C9orf72 group, and 61\ub73 years (8\ub78; onset) and 68\ub78 years (9\ub77; death) in the GRN group. Mean disease duration was 6\ub74 years (SD 4\ub79) in the C9orf72 group, 7\ub71 years (3\ub79) in the GRN group, and 9\ub73 years (6\ub74) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0\ub745 between individual and parental age at onset, r=0\ub763 between individual and mean family age at onset, r=0\ub758 between individual and parental age at death, and r=0\ub769 between individual and mean family age at death) than in either the C9orf72 group (r=0\ub732 individual and parental age at onset, r=0\ub736 individual and mean family age at onset, r=0\ub738 individual and parental age at death, and r=0\ub740 individual and mean family age at death) or the GRN group (r=0\ub722 individual and parental age at onset, r=0\ub718 individual and mean family age at onset, r=0\ub722 individual and parental age at death, and r=0\ub732 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35\u201362, for age at onset; 61%, 47\u201373, for age at death), and even more by family membership (66%, 56\u201375, for age at onset; 74%, 65\u201382, for age at death). In the GRN group, only 2% (0\u201310) of the variability of age at onset and 9% (3\u201321) of that of age of death was explained by the specific mutation, whereas 14% (9\u201322) of the variability of age at onset and 20% (12\u201330) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11\u201326) of the variability of age at onset and 19% (12\u201329) of that of age at death. Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society

Searches for lepton-flavour-violating decays of the Higgs boson in s=13\sqrt{s}=13 TeV pp\mathit{pp} collisions with the ATLAS detector

This Letter presents direct searches for lepton flavour violation in Higgs boson decays, H → eτ and H → μτ , performed with the ATLAS detector at the LHC. The searches are based on a data sample of proton–proton collisions at a centre-of-mass energy √s = 13 TeV, corresponding to an integrated luminosity of 36.1 fb−1. No significant excess is observed above the expected background from Standard Model processes. The observed (median expected) 95% confidence-level upper limits on the leptonflavour-violating branching ratios are 0.47% (0.34+0.13−0.10%) and 0.28% (0.37+0.14−0.10%) for H → eτ and H → μτ , respectively.publishedVersio

Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb⁻¹ of pp collisions at \sqrts = 13 TeV with the ATLAS experiment

A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5). © 2019 The Author(s

Measurement of prompt photon production in sNN√=8.16 TeV p+Pb collisions with ATLAS

The inclusive production rates of isolated, prompt photons in p+Pb collisions at sNN√=8.16 TeV are studied with the ATLAS detector at the Large Hadron Collider using a dataset with an integrated luminosity of 165 nb−1 recorded in 2016. The cross-section and nuclear modification factor RpPb are measured as a function of photon transverse energy from 20 GeV to 550 GeV and in three nucleon-nucleon centre-of-mass pseudorapidity regions, (-2.83,-2.02), (-1.84,0.91), and (1.09,1.90). The cross-section and RpPb values are compared with the results of a next-to-leading-order perturbative QCD calculation, with and without nuclear parton distribution function modifications, and with expectations based on a model of the energy loss of partons prior to the hard scattering. The data disfavour a large amount of energy loss and provide new constraints on the parton densities in nuclei.We acknowledge the support of ANPCyT, Argentina; YerPhI, Ar-menia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azer-baijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Is-rael; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portu-gal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Fed-eration; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallen-berg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, in-dividual groups and members have received support from BCKDF, Canarie, CRC and Compute Canada, Canada; COST, ERC, ERDF, Hori-zon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro-grammes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine