Publications by authors named "Fabrizio Tagliavini"

220 Publications

Stratifying the Presymptomatic Phase of Genetic Frontotemporal Dementia by Serum NfL and pNfH: A Longitudinal Multicentre Study.

Ann Neurol 2021 Nov 7. Epub 2021 Nov 7.

Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.

Objective: Although the presymptomatic stages of frontotemporal dementia (FTD) provide a unique chance to delay or even prevent neurodegeneration by early intervention, they remain poorly defined. Leveraging a large multicenter cohort of genetic FTD mutation carriers, we provide a biomarker-based stratification and biomarker cascade of the likely most treatment-relevant stage within the presymptomatic phase: the conversion stage.

Methods: We longitudinally assessed serum levels of neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH) in the Genetic FTD Initiative (GENFI) cohort (n = 444), using single-molecule array technique. Subjects comprised 91 symptomatic and 179 presymptomatic subjects with mutations in the FTD genes C9orf72, GRN, or MAPT, and 174 mutation-negative within-family controls.

Results: In a biomarker cascade, NfL increase preceded the hypothetical clinical onset by 15 years and concurred with brain atrophy onset, whereas pNfH increase started close to clinical onset. The conversion stage was marked by increased NfL, but still normal pNfH levels, while both were increased at the symptomatic stage. Intra-individual change rates were increased for NfL at the conversion stage and for pNfH at the symptomatic stage, highlighting their respective potential as stage-dependent dynamic biomarkers within the biomarker cascade. Increased NfL levels and NfL change rates allowed identification of presymptomatic subjects converting to symptomatic disease and capture of proximity-to-onset. We estimate stage-dependent sample sizes for trials aiming to decrease neurofilament levels or change rates.

Interpretation: Blood NfL and pNfH provide dynamic stage-dependent stratification and, potentially, treatment response biomarkers in presymptomatic FTD, allowing demarcation of the conversion stage. The proposed biomarker cascade might pave the way towards a biomarker-based precision medicine approach to genetic FTD. ANN NEUROL 2021.
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http://dx.doi.org/10.1002/ana.26265DOI Listing
November 2021

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

Brain 2021 Oct 11. Epub 2021 Oct 11.

Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, OX3 9DU Oxford, UK.

Several CSF and blood biomarkers for genetic frontotemporal dementia (FTD) have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH)), synapse dysfunction (neuronal pentraxin 2 (NPTX2)), astrogliosis (glial fibrillary acidic protein (GFAP)), 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 FTD, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic FTD using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. 275 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-initialised DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on prior 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 NfL, blood pNfH, blood GFAP, 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 (AUC) of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The AUC to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic FTD revealed that NPTX2 and NfL 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.
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http://dx.doi.org/10.1093/brain/awab382DOI Listing
October 2021

Dissemination in time and space in presymptomatic granulin mutation carriers: a GENFI spatial chronnectome study.

Neurobiol Aging 2021 Dec 8;108:155-167. Epub 2021 Sep 8.

Nueld Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK.

The presymptomatic brain changes of granulin (GRN) disease, preceding by years frontotemporal dementia, has not been fully characterized. New approaches focus on the spatial chronnectome can capture both spatial network configurations and their dynamic changes over time. To investigate the spatial dynamics in 141 presymptomatic GRN mutation carriers and 282 noncarriers from the Genetic Frontotemporal dementia research Initiative cohort. We considered time-varying patterns of the default mode network, the language network, and the salience network, each summarized into 4 distinct recurring spatial configurations. Dwell time (DT) (the time each individual spends in each spatial state of each network), fractional occupacy (FO) (the total percentage of time spent by each individual in a state of a specific network) and total transition number (the total number of transitions performed by each individual in a specifict state) were considered. Correlations between DT, FO, and transition number and estimated years from expected symptom onset (EYO) and clinical performances were assessed. Presymptomatic GRN mutation carriers spent significantly more time in those spatial states characterised by greater activation of the insula and the parietal cortices, as compared to noncarriers (p < 0.05, FDR-corrected). A significant correlation between DT and FO of these spatial states and EYO was found, the longer the time spent in the spatial states, the closer the EYO. DT and FO significantly correlated with performances at tests tapping processing speed, with worse scores associated with increased spatial states' DT. Our results demonstrated that presymptomatic GRN disease presents a complex dynamic reorganization of brain connectivity. Change in both the spatial and temporal aspects of brain network connectivity could provide a unique glimpse into brain function and potentially allowing a more sophisticated evaluation of the earliest disease changes and the understanding of possible mechanisms in GRN disease.
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http://dx.doi.org/10.1016/j.neurobiolaging.2021.09.001DOI Listing
December 2021

Spontaneous ARIA-like Events in Cerebral Amyloid Angiopathy-Related Inflammation: A Multicenter Prospective Longitudinal Cohort Study.

Neurology 2021 Nov 16;97(18):e1809-e1822. Epub 2021 Sep 16.

From the School of Medicine and Surgery (L.A., J.C.D., G.B., C.F., N.Z., F. Piazza), University of Milano-Bicocca, Monza; Neurology Unit (M.Z.), Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico Milano and University of Milan (A.A., E.S.), Italy; Kyoto University Graduate School of Medicine (A.S.), Japan; University of Padova (A.C.); University of Chieti (M. Caulo), Italy; University of Southampton (R.O.C.), UK; Department of Neurology (A.C.), Boston Medical Center, Boston University, MA; University of Campania "Luigi Vanvitelli" (M. Cirillo), Napoli; Università Campus Biomedico (V.D.L.), Rome; Azienda Socio Sanitaria Territoriale di Cremona (A.G.); Italian National Research Council (D.I.), University of Florence; Neuroscience Institute (D.I.), Pisa; S. Bortolo Hospital (M.M., F. Perini), Vicenza; Azienda USL Toscana sud est (R.M.), Grosseto, Italy; National Cerebral and Cardiovascular Center (M.I.), Osaka, Japan; University of São Paulo Medical School (R.N.), Brazil; S.S. Filippo and Nicola Hospital (B.O.), Avezzano; University of Brescia (A.P.); Neuroradiology Unit (R.P.), Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia; IRCCS Mondino Foundation and University of Pavia (G.P.); Ospedale Papa Giovanni XXIII (M.S.), Bergamo; Fondazione IRCCS "Carlo Besta" National Neurological Institute (F.T.), Milan, Italy; Azienda USL Toscana Centro (R.V.), Prato, Italy; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) (J.F.V.-C.), Valencia; Hospital Universitario 12 de Octubre (A.V.-G.), Madrid, Spain; St. Marianna University School of Medicine (Y.H.), Kawasaki, Japan; and CAA and AD Translational Research and Biomarkers Laboratory (F. Piazza), PhD Program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.

Background And Objectives: The goal of this work was to investigate the natural history and outcomes after treatment for spontaneous amyloid-related imaging abnormalities (ARIA)-like in cerebral amyloid angiopathy-related inflammation (CAA-ri).

Methods: This was a multicenter, hospital-based, longitudinal, prospective observational study of inpatients meeting CAA-ri diagnostic criteria recruited through the Inflammatory Cerebral Amyloid Angiopathy and Alzheimer's Disease βiomarkers International Network from January 2013 to March 2017. A protocol for systematic data collection at first-ever presentation and at subsequent in-person visits, including T1-weighted, gradient recalled echo-T2*, fluid-suppressed T2-weighted (fluid-attenuated inversion recovery), and T1 postgadolinium contrast-enhanced images acquired on 1.5T MRI, was used at the 3-, 6-, 12-, and 24-month follow-up. Centralized reads of MRIs were performed by investigators blinded to clinical, therapeutic, and time-point information. Main outcomes were survival, clinical and radiologic recovery, intracerebral hemorrhage (ICH), and recurrence of CAA-ri.

Results: The study enrolled 113 participants (10.6% definite, 71.7% probable, and 17.7% possible CAA-ri). Their mean age was 72.9 years; 43.4% were female; 37.1% were ε4 carriers; 36.3% had a history of Alzheimer disease; and 33.6% had a history of ICH. A history of ICH and the occurrence of new ICH at follow-up were more common in patients with cortical superficial siderosis at baseline (52.6% vs 14.3%, < 0.0001 and 19.3% vs 3.6%, < 0.009, respectively). After the first-ever presentation of CAA-ri, 70.3% (95% confidence interval [CI] 61.6%-78.5%) and 84.1% (95% CI 76.2%-90.6%) clinically recovered within 3 and 12 months, followed by radiologic recovery in 45.1% (95% CI 36.4%-54.8%) and 77.4% (95% CI 67.7%-85.9%), respectively. After clinicoradiologic resolution of the first-ever episode, 38.3% (95% CI 22.9%-59.2%) had at least 1 recurrence within the following 24 months. Recurrence was more likely if IV high-dose corticosteroid pulse therapy was suddenly stopped compared to slow oral tapering off (hazard ratio 4.68, 95% CI 1.57-13.93; = 0.006).

Discussion: These results from the largest longitudinal cohort registry of patients with CAA-ri support the transient and potentially relapsing inflammatory nature of the clinical-radiologic acute manifestations of the disease and the effectiveness of slow oral tapering off after IV corticosteroid pulse therapy in preventing recurrences. Our results highlight the importance of differential diagnosis for spontaneous ARIA-like events in β-amyloid-driven diseases, including treatment-related ARIA in patients with Alzheimer disease exposed to immunotherapy drugs.
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http://dx.doi.org/10.1212/WNL.0000000000012778DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8610623PMC
November 2021

COVID-19 Vaccination in Fragile Patients: Current Evidence and an Harmonized Transdisease Trial.

Front Immunol 2021;12:704110. Epub 2021 Aug 10.

Department of Biomedical Sciences, Humanitas University, Milan, Italy.

Patients diagnosed with malignancy, neurological and immunological disorders, , fragile patients, have been excluded from COVID-19 vaccine trials. However, this population may present immune response abnormalities, and relative reduced vaccine responsiveness. Here we review the limited current evidence on the immune responses to vaccination of patients with different underlying diseases. To address open questions we present the VAX4FRAIL study aimed at assessing immune responses to vaccination in a large transdisease cohort of patients with cancer, neurological and rheumatological diseases.
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http://dx.doi.org/10.3389/fimmu.2021.704110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8383886PMC
September 2021

Comparison of clinical rating scales in genetic frontotemporal dementia within the GENFI cohort.

J Neurol Neurosurg Psychiatry 2021 Aug 5. Epub 2021 Aug 5.

Department of Neurofarba, University of Florence, Firenze, Italy.

Background: Therapeutic trials are now underway in genetic forms of frontotemporal dementia (FTD) but clinical outcome measures are limited. The two most commonly used measures, the Clinical Dementia Rating (CDR)+National Alzheimer's Disease Coordinating Center (NACC) Frontotemporal Lobar Degeneration (FTLD) and the FTD Rating Scale (FRS), have yet to be compared in detail in the genetic forms of FTD.

Methods: The CDR+NACC FTLD and FRS were assessed cross-sectionally in 725 consecutively recruited participants from the Genetic FTD Initiative: 457 mutation carriers (77 microtubule-associated protein tau (, 187 , 193 ) and 268 family members without mutations (non-carrier control group). 231 mutation carriers (51 92 88 ) and 145 non-carriers had available longitudinal data at a follow-up time point.

Results: Cross-sectionally, the mean FRS score was lower in all genetic groups compared with controls: mutation carriers mean 83.4 (SD 27.0), mutation carriers 78.2 (28.8), mutation carriers 71.0 (34.0), controls 96.2 (7.7), p<0.001 for all comparisons, while the mean CDR+NACC FTLD Sum of Boxes was significantly higher in all genetic groups: mutation carriers mean 2.6 (5.2), mutation carriers 3.2 (5.6), mutation carriers 4.2 (6.2), controls 0.2 (0.6), p<0.001 for all comparisons. Mean FRS score decreased and CDR+NACC FTLD Sum of Boxes increased with increasing disease severity within each individual genetic group. FRS and CDR+NACC FTLD Sum of Boxes scores were strongly negatively correlated across all mutation carriers (r=-0.77, p<0.001) and within each genetic group (r=-0.67 to -0.81, p<0.001 in each group). Nonetheless, discrepancies in disease staging were seen between the scales, and with each scale and clinician-judged symptomatic status. Longitudinally, annualised change in both FRS and CDR+NACC FTLD Sum of Boxes scores initially increased with disease severity level before decreasing in those with the most severe disease: controls -0.1 (6.0) for FRS, -0.1 (0.4) for CDR+NACC FTLD Sum of Boxes, asymptomatic mutation carriers -0.5 (8.2), 0.2 (0.9), prodromal disease -2.3 (9.9), 0.6 (2.7), mild disease -10.2 (18.6), 3.0 (4.1), moderate disease -9.6 (16.6), 4.4 (4.0), severe disease -2.7 (8.3), 1.7 (3.3). Sample sizes were calculated for a trial of prodromal mutation carriers: over 180 participants per arm would be needed to detect a moderate sized effect (30%) for both outcome measures, with sample sizes lower for the FRS.

Conclusions: Both the FRS and CDR+NACC FTLD measure disease severity in genetic FTD mutation carriers throughout the timeline of their disease, although the FRS may be preferable as an outcome measure. However, neither address a number of key symptoms in the FTD spectrum, for example, motor and neuropsychiatric deficits, which future scales will need to incorporate.
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http://dx.doi.org/10.1136/jnnp-2021-326868DOI Listing
August 2021

Alzheimer's disease: the controversial approval of Aducanumab.

Neurol Sci 2021 Aug 29;42(8):3069-3070. Epub 2021 Jul 29.

Department Medicine, Surgery and Neurosciences, Medical School, University of Siena, Viale Bracci 2, 53100, Siena, Italy.

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http://dx.doi.org/10.1007/s10072-021-05497-4DOI Listing
August 2021

The Revised Self-Monitoring Scale detects early impairment of social cognition in genetic frontotemporal dementia within the GENFI cohort.

Alzheimers Res Ther 2021 07 12;13(1):127. Epub 2021 Jul 12.

Department of Neurology, Ludwig-Maximilians Universität München, Munich, Germany.

Background: Although social cognitive dysfunction is a major feature of frontotemporal dementia (FTD), it has been poorly studied in familial forms. A key goal of studies is to detect early cognitive impairment using validated measures in large patient cohorts.

Methods: We used the Revised Self-Monitoring Scale (RSMS) as a measure of socioemotional sensitivity in 730 participants from the genetic FTD initiative (GENFI) observational study: 269 mutation-negative healthy controls, 193 C9orf72 expansion carriers, 193 GRN mutation carriers and 75 MAPT mutation carriers. All participants underwent the standardised GENFI clinical assessment including the 'CDR® plus NACC FTLD' scale and RSMS. The RSMS total score and its two subscores, socioemotional expressiveness (EX score) and modification of self-presentation (SP score) were measured. Volumetric T1-weighted magnetic resonance imaging was available from 377 mutation carriers for voxel-based morphometry (VBM) analysis.

Results: The RSMS was decreased in symptomatic mutation carriers in all genetic groups but at a prodromal stage only in the C9orf72 (for the total score and both subscores) and GRN (for the modification of self-presentation subscore) groups. RSMS score correlated with disease severity in all groups. The VBM analysis implicated an overlapping network of regions including the orbitofrontal cortex, insula, temporal pole, medial temporal lobe and striatum.

Conclusions: The RSMS indexes socioemotional impairment at an early stage of genetic FTD and may be a suitable outcome measure in forthcoming trials.
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http://dx.doi.org/10.1186/s13195-021-00865-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276486PMC
July 2021

Characterizing the Clinical Features and Atrophy Patterns of -Related Frontotemporal Dementia With Disease Progression Modeling.

Neurology 2021 08 22;97(9):e941-e952. Epub 2021 Jun 22.

From the Department of Neuroimaging (A.L.Y., S.C.R.W.), Institute of Psychiatry, Psychology and Neuroscience, King's College London; Departments of Computer Science (A.L.Y., D.C.A.) and Medical Physics and Biomedical Engineering (D.M.C.), Centre for Medical Image Computing, University College London; Dementia Research Centre (M.B., L.L.R., R.S.C., G.P., E.T., D.M.C., C.V.G., L.J., J.D.R.), Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK; Department of Neurology (J.v.S., L.J., H.S.), Erasmus Medical Centre, Rotterdam, the Netherlands; Cognitive Disorders Unit (F.M.), Department of Neurology, Donostia University Hospital; Neuroscience Area (F.M.), Biodonostia Health Research Institute, San Sebastian, Gipuzkoa, Spain; Alzheimer's Disease and Other Cognitive Disorders Unit (R.S.-V.), Neurology Service, Hospital Clínic, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Spain; Neurology Unit (B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine (R.L.), Université Laval, Québec; Sunnybrook Health Sciences Centre, Sunnybrook Research Institute (M.M.), and Tanz Centre for Research in Neurodegenerative Diseases (M.C.T.), University of Toronto, Canada; Center for Alzheimer Research (C.G.), Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet; Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Solna, Sweden; Fondazione Ca'Granda (D.G.), IRCCS Ospedale Policlinico; University of Milan (D.G.), Centro Dino Ferrari, Italy; Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust (J.B.R.), University of Cambridge, UK; Department of Clinical Neurological Sciences (E.F.), University of Western Ontario, London, Canada; Department of Neurodegenerative Diseases (M.S.), Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen; Center for Neurodegenerative Diseases (DZNE) (M.S.), Tübingen, Germany; Laboratory for Cognitive Neurology, Department of Neurosciences (R.V.), and Leuven Brain Institute (R.V.), KU Leuven; Neurology Service (R.V.), University Hospitals Leuven, Belgium; Faculty of Medicine (A.d.M.), University of Lisbon, Portugal; Fondazione IRCCS Istituto Neurologico Carlo Besta (F.T.), Milan, Italy; University Hospital of Coimbra (HUC), Neurology Service (I.S.), and Center for Neuroscience and Cell Biology (I.S.), Faculty of Medicine, University of Coimbra, Portugal; Department of Psychiatry, McGill University Health Centre (S.D.), and McConnell Brain Imaging Centre, Montreal Neurological Institute (S.D.), McGill University, Montreal, Canada; Nuffield Department of Clinical Neurosciences (C.B.), Medical Sciences Division, University of Oxford; Division of Neuroscience and Experimental Psychology (A.G.), Wolfson Molecular Imaging Centre, University of Manchester, UK; Departments of Geriatric Medicine and Nuclear Medicine (A.G.), University of Duisburg-Essen; Department of Neurology (J.L., A.D.), Ludwig-Maximilians Universität München; German Center for Neurodegenerative Diseases (DZNE) (J.L.); Munich Cluster of Systems Neurology (SyNergy) (J.L.), Munich; Department of Neurology (M.O.), University of Ulm, Germany; Departments of Neuroscience, Psychology, Drug Research, and Child Health (S.S.), University of Florence; and IRCCS Don Gnocchi (S.S.), Florence, Italy.

Background And Objective: Mutations in the gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signature of mutations have grouped all different mutations together and shown an association with focal atrophy of the temporal lobe. The variability in atrophy patterns between each particular mutation is less well-characterized. We aimed to investigate whether there were distinct groups of mutation carriers based on their neuroanatomical signature.

Methods: We applied Subtype and Stage Inference (SuStaIn), an unsupervised machine learning technique that identifies groups of individuals with distinct progression patterns, to characterize patterns of regional atrophy in associated FTD within the Genetic FTD Initiative (GENFI) cohort study.

Results: Eighty-two mutation carriers were analyzed, the majority of whom had P301L, IVS10+16, or R406W mutations, along with 48 healthy noncarriers. SuStaIn identified 2 groups of mutation carriers with distinct atrophy patterns: a temporal subtype, in which atrophy was most prominent in the hippocampus, amygdala, temporal cortex, and insula; and a frontotemporal subtype, in which atrophy was more localized to the lateral temporal lobe and anterior insula, as well as the orbitofrontal and ventromedial prefrontal cortex and anterior cingulate. There was one-to-one mapping between IVS10+16 and R406W mutations and the temporal subtype and near one-to-one mapping between P301L mutations and the frontotemporal subtype. There were differences in clinical symptoms and neuropsychological test scores between subtypes: the temporal subtype was associated with amnestic symptoms, whereas the frontotemporal subtype was associated with executive dysfunction.

Conclusion: Our results demonstrate that different mutations give rise to distinct atrophy patterns and clinical phenotype, providing insights into the underlying disease biology and potential utility for patient stratification in therapeutic trials.
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http://dx.doi.org/10.1212/WNL.0000000000012410DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408507PMC
August 2021

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Nat Commun 2021 06 7;12(1):3417. Epub 2021 Jun 7.

Servei de Neurologia, Hospital Universitari i Politècnic La Fe, Valencia, Spain.

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.
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http://dx.doi.org/10.1038/s41467-021-22491-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184987PMC
June 2021

Impairment of episodic memory in genetic frontotemporal dementia: A GENFI study.

Alzheimers Dement (Amst) 2021 13;13(1):e12185. Epub 2021 May 13.

Douglas Mental Health University Institute Department of Psychiatry McGill University Montreal Canada.

Introduction: We aimed to assess episodic memory in genetic frontotemporal dementia (FTD) with the Free and Cued Selective Reminding Test (FCSRT).

Methods: The FCSRT was administered in 417 presymptomatic and symptomatic mutation carriers (181 chromosome 9 open reading frame 72 [], 163 progranulin [], and 73 microtubule-associated protein tau []) and 290 controls. Group differences and correlations with other neuropsychological tests were examined. We performed voxel-based morphometry to investigate the underlying neural substrates of the FCSRT.

Results: All symptomatic mutation carrier groups and presymptomatic mutation carriers performed significantly worse on all FCSRT scores compared to controls. In the presymptomatic group, deficits were found on all scores except for the delayed total recall task, while no deficits were found in presymptomatic mutation carriers. Performance on the FCSRT correlated with executive function, particularly in mutation carriers, but also with memory and naming tasks in the group. FCSRT performance also correlated with gray matter volumes of frontal, temporal, and subcortical regions in and , but mainly temporal areas in mutation carriers.

Discussion: The FCSRT detects presymptomatic deficits in - and -associated FTD and provides important insight into the underlying cause of memory impairment in different forms of FTD.
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http://dx.doi.org/10.1002/dad2.12185DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116844PMC
May 2021

Neuro-telehealth for fragile patients in a tertiary referral neurological institute during the COVID-19 pandemic in Milan, Lombardy.

Neurol Sci 2021 Jul 30;42(7):2637-2644. Epub 2021 Apr 30.

Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.

Background: Lombardy was severely hit by the COVID-19 pandemic since February 2020 and the Health System underwent rapid reorganization. Outpatient clinics were stopped for non-urgent patients: it became a priority to manage hundreds of fragile neurological patients who suddenly had less reference points. In Italy, before the pandemic, Televisits were neither recognized nor priced.

Methods: At the Fondazione IRCCS Istituto Neurologico C. Besta, we reorganized outpatient clinics to deliver Neuro-telemedicine services, including Televisits and Teleneurorehabilitation, since March 2020. A dedicated Working Group prepared the procedure, tested the system, and designed satisfaction questionnaires for adults and children.

Results: After a pilot phase, we prepared a procedure for Telemedicine outpatient clinics which was approved by hospital directions. It included prescription, booking, consenting, privacy and data protection, secure connection with patients (Teams Microsoft 365), electronic report preparation and delivery, reporting, and accountability of the services. During the March-September 2020 period, we delivered 3167 Telemedicine services, including 1618 Televisits, to 1694 patients (972 adults, 722 children) with a wide range of chronic neurological disorders. We successfully administered different clinical assessment and scales. Satisfaction among patients and caregivers was very high.

Conclusions: During the dramatic emergency, we were able to take care of more than 1600 patients by organizing Neuro-telehealth in a few weeks, lessening the impact of the pandemic on fragile patients with chronic neurological disorders; this strategy is now stably embedded in our care pathways. In Italy, Telehealth is at present recognized and priced and is becoming a stable pillar of the health system.
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http://dx.doi.org/10.1007/s10072-021-05252-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086222PMC
July 2021

Differential early subcortical involvement in genetic FTD within the GENFI cohort.

Neuroimage Clin 2021 29;30:102646. Epub 2021 Mar 29.

Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich German Center for Neurodegenerative Diseases (DZNE), Munich Munich Cluster of Systems Neurology, Munich, Germany.

Background: Studies have previously shown evidence for presymptomatic cortical atrophy in genetic FTD. Whilst initial investigations have also identified early deep grey matter volume loss, little is known about the extent of subcortical involvement, particularly within subregions, and how this differs between genetic groups.

Methods: 480 mutation carriers from the Genetic FTD Initiative (GENFI) were included (198 GRN, 202 C9orf72, 80 MAPT), together with 298 non-carrier cognitively normal controls. Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans. Mutation carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score: asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more).

Results: In all three groups, subcortical involvement was seen at the CDR 0.5 stage prior to phenoconversion, whereas in the C9orf72 and MAPT mutation carriers there was also involvement at the CDR 0 stage. In the C9orf72 expansion carriers the earliest volume changes were in thalamic subnuclei (particularly pulvinar and lateral geniculate, 9-10%) cerebellum (lobules VIIa-Crus II and VIIIb, 2-3%), hippocampus (particularly presubiculum and CA1, 2-3%), amygdala (all subregions, 2-6%) and hypothalamus (superior tuberal region, 1%). In MAPT mutation carriers changes were seen at CDR 0 in the hippocampus (subiculum, presubiculum and tail, 3-4%) and amygdala (accessory basal and superficial nuclei, 2-4%). GRN mutation carriers showed subcortical differences at CDR 0.5 in the presubiculum of the hippocampus (8%).

Conclusions: C9orf72 expansion carriers show the earliest and most widespread changes including the thalamus, basal ganglia and medial temporal lobe. By investigating individual subregions, changes can also be seen at CDR 0 in MAPT mutation carriers within the limbic system. Our results suggest that subcortical brain volumes may be used as markers of neurodegeneration even prior to the onset of prodromal symptoms.
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http://dx.doi.org/10.1016/j.nicl.2021.102646DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099608PMC
July 2021

Machine Learning Driven Profiling of Cerebrospinal Fluid Core Biomarkers in Alzheimer's Disease and Other Neurological Disorders.

Front Neurosci 2021 31;15:647783. Epub 2021 Mar 31.

Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy.

Amyloid-beta (Aβ) 42/40 ratio, tau phosphorylated at threonine-181 (p-tau), and total-tau (t-tau) are considered core biomarkers for the diagnosis of Alzheimer's disease (AD). The use of fully automated biomarker assays has been shown to reduce the intra- and inter-laboratory variability, which is a critical factor when defining cut-off values. The calculation of cut-off values is often influenced by the composition of AD and control groups. Indeed, the clinically defined AD group may include patients affected by other forms of dementia, while the control group is often very heterogeneous due to the inclusion of subjects diagnosed with other neurological diseases (OND). In this context, unsupervised machine learning approaches may overcome these issues providing unbiased cut-off values and data-driven patient stratification according to the sole distribution of biomarkers. In this work, we took advantage of the reproducibility of automated determination of the CSF core AD biomarkers to compare two large cohorts of patients diagnosed with different neurological disorders and enrolled in two centers with established expertise in AD biomarkers. We applied an unsupervised Gaussian mixture model clustering algorithm and found that our large series of patients could be classified in six clusters according to their CSF biomarker profile, some presenting a typical AD-like profile and some a non-AD profile. By considering the frequencies of clinically defined OND and AD subjects in clusters, we subsequently computed cluster-based cut-off values for Aβ42/Aβ40, p-tau, and t-tau. This approach promises to be useful for large-scale biomarker studies aimed at providing efficient biochemical phenotyping of neurological diseases.
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http://dx.doi.org/10.3389/fnins.2021.647783DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044304PMC
March 2021

Plasma Neurofilament Light for Prediction of Disease Progression in Familial Frontotemporal Lobar Degeneration.

Neurology 2021 05 7;96(18):e2296-e2312. Epub 2021 Apr 7.

From the University of California, San Francisco (J.C.R., P.W., A.M.S., Y.C., A.W., S.-Y.M.G., P.A.L., H.W.H., J.C.F., J.B.T., A.M.K., L.L.M., J.K., J.H.K., B.L.M., H.J.S., A.L.B.); UK Dementia Research Centre (C.H., D.M.C., R.S.C., M.B., M.F., C.V.G., G.P., L.R., I.S., E.T., J.D.R.), UCL Institute of Neurology, Queen Square, London; Quanterix Corp (E.V., L.S., A.J., D.H.), Lexington; Novartis Institutes for Biomedical Research Inc (L.Y., A. Khinikar, R.S.), Cambridge, MA; Novartis Pharma AG (A. Kieloch, M.-A.V.), Basel, Switzerland; Bluefield Project to Cure Frontotemporal Dementia (L.L.M., R.P.), San Francisco, CA; Mayo Clinic (K.K., D.S.K., B.F.B.), Rochester, MN; Mayo Clinic (N.G.-R., L.P., R.R.), Jacksonville, FL; University of Pennsylvania (D.J.I., M.G.), Philadelphia; University of California, Los Angeles (E.M.R., G.C., M.F.M., Y.B.); Harvard University/Massachusetts General Hospital (B.D.C.), Boston, MA; Washington University (N.G.), St. Louis, MO; Columbia University (E.D.H.), New York, NY; University of British Columbia (I.R.M., G.-Y.R.H.), Vancouver, Canada; Case Western Reserve University (B.S.A.), Cleveland, OH; University of Washington (K.D.-R.), Seattle; Laboratory of Neuroimaging (A.W.T.), University of Southern California, Los Angeles; Northwestern University (S.W.), Chicago, IL; University of North Carolina (D.I.K.), Chapel Hill; Texas Health Presbyterian Hospital Dallas (D.K.); University of California, San Diego (I.L.); Johns Hopkins Hospital (C.U.O., A.P.), Baltimore, MD; University of Alabama at Birmingham (E.D.R.); University of Toronto (M.C.T., M.M.), Ontario, Canada; Indiana University School of Medicine (T.F.), Indianapolis; Biogen Inc (W.C., J.C., D.L.G.), Cambridge, MA; Erasmus Medical Centre (J.C.v.S.), Rotterdam, the Netherlands; University of Brescia (B.B.), Italy; University of Barcelona (R.S.-V.); Donostia University Hospital (F.M.), San Sebastian, Gipuzkoa, Spain; Clinique Interdisciplinaire de Mémoire (R.L.), Département des Sciences Neurologiques, CHU de Québec; Faculté de Médecine (R.L.), Université Laval, Quebec, Canada; Center for Alzheimer Research (C.G.), Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet; Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Solna, Sweden; University of Tübingen (M.S.); Center for Neurodegenerative Diseases (DZNE) (M.S.), Tübingen, Germany; Fondazione IRCCS Ospedale Policlinico (D.G.); University of Milan (D.G.), Centro Dino Ferrari, Italy; Department of Clinical Neurosciences and Cambridge University Hospital (J.B.R.), University of Cambridge, UK; University of Western Ontario (E.F.), London, Canada; KU Leuven (R.V.), Belgium; Neurology Service (R.V.), University Hospitals Leuven, Belgium; University of Lisbon (A.d.M.), Portugal; Fondazione IRCCS Istituto Neurologico Carlo Besta (F.T.), Milan, Italy; University of Coimbra (I.S.), Portugal; McGill University (S.D.), Montreal, Québec, Canada; University of Oxford (C.R.B.); Wolfson Molecular Imaging Centre (A.G.), University of Manchester, UK; University of Duisburg-Essen (A.G.), Duisberg; Ludwig-Maximilians-Universität München (J.L., A.D.); German Center for Neurodegenerative Diseases (J.L.), Munich Cluster for Systems Neurology (SyNergy); University of Ulm (M.O.), Germany; and Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence, and IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.

Objective: We tested the hypothesis that plasma neurofilament light chain (NfL) identifies asymptomatic carriers of familial frontotemporal lobar degeneration (FTLD)-causing mutations at risk of disease progression.

Methods: Baseline plasma NfL concentrations were measured with single-molecule array in original (n = 277) and validation (n = 297) cohorts. , , and mutation carriers and noncarriers from the same families were classified by disease severity (asymptomatic, prodromal, and full phenotype) using the CDR Dementia Staging Instrument plus behavior and language domains from the National Alzheimer's Disease Coordinating Center FTLD module (CDR+NACC-FTLD). Linear mixed-effect models related NfL to clinical variables.

Results: In both cohorts, baseline NfL was higher in asymptomatic mutation carriers who showed phenoconversion or disease progression compared to nonprogressors (original: 11.4 ± 7 pg/mL vs 6.7 ± 5 pg/mL, = 0.002; validation: 14.1 ± 12 pg/mL vs 8.7 ± 6 pg/mL, = 0.035). Plasma NfL discriminated symptomatic from asymptomatic mutation carriers or those with prodromal disease (original cutoff: 13.6 pg/mL, 87.5% sensitivity, 82.7% specificity; validation cutoff: 19.8 pg/mL, 87.4% sensitivity, 84.3% specificity). Higher baseline NfL correlated with worse longitudinal CDR+NACC-FTLD sum of boxes scores, neuropsychological function, and atrophy, regardless of genotype or disease severity, including asymptomatic mutation carriers.

Conclusions: Plasma NfL identifies asymptomatic carriers of FTLD-causing mutations at short-term risk of disease progression and is a potential tool to select participants for prevention clinical trials.

Trial Registration Information: ClinicalTrials.gov Identifier: NCT02372773 and NCT02365922.

Classification Of Evidence: This study provides Class I evidence that in carriers of FTLD-causing mutations, elevation of plasma NfL predicts short-term risk of clinical progression.
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http://dx.doi.org/10.1212/WNL.0000000000011848DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166434PMC
May 2021

Microglial Heterogeneity and Its Potential Role in Driving Phenotypic Diversity of Alzheimer's Disease.

Int J Mol Sci 2021 Mar 9;22(5). Epub 2021 Mar 9.

Neurology 5 and Neuropathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy.

Alzheimer's disease (AD) is increasingly recognized as a highly heterogeneous disorder occurring under distinct clinical and neuropathological phenotypes. Despite the molecular determinants of such variability not being well defined yet, microglial cells may play a key role in this process by releasing distinct pro- and/or anti-inflammatory cytokines, potentially affecting the expression of the disease. We carried out a neuropathological and biochemical analysis on a series of AD brain samples, gathering evidence about the heterogeneous involvement of microglia in AD. The neuropathological studies showed differences concerning morphology, density and distribution of microglial cells among AD brains. Biochemical investigations showed increased brain levels of IL-4, IL-6, IL-13, CCL17, MMP-7 and CXCL13 in AD in comparison with control subjects. The molecular profiling achieved by measuring the brain levels of 25 inflammatory factors known to be involved in neuroinflammation allowed a stratification of the AD patients in three distinct "neuroinflammatory clusters". These findings strengthen the relevance of neuroinflammation in AD pathogenesis suggesting, in particular, that the differential involvement of neuroinflammatory molecules released by microglial cells during the development of the disease may contribute to modulate the characteristics and the severity of the neuropathological changes, driving-at least in part-the AD phenotypic diversity.
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http://dx.doi.org/10.3390/ijms22052780DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967159PMC
March 2021

MRI data-driven algorithm for the diagnosis of behavioural variant frontotemporal dementia.

J Neurol Neurosurg Psychiatry 2021 Mar 15. Epub 2021 Mar 15.

McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.

Introduction: Structural brain imaging is paramount for the diagnosis of behavioural variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis.

Methods: A total of 515 subjects from two different bvFTD cohorts (training and independent validation cohorts) were used to perform voxel-wise morphometric analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from deformation-based morphometry differences in isolation and together with semantic fluency. Tenfold cross validation was used to assess the performance of the classifier within the training cohort. A second held-out cohort of genetically confirmed bvFTD cases was used for additional validation.

Results: Average 10-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In the separate validation cohort of definite bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added semantic fluency scores.

Conclusion: Our results show that structural MRI and semantic fluency can accurately predict bvFTD at the individual subject level within a completely independent validation cohort coming from a different and independent database.
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http://dx.doi.org/10.1136/jnnp-2020-324106DOI Listing
March 2021

Disease-related cortical thinning in presymptomatic granulin mutation carriers.

Neuroimage Clin 2021 29;29:102540. Epub 2020 Dec 29.

Dementia Research Centre, Department of Neurodegenerative Disease, Queen Square UCL Institute of Neurology, London, UK.

Mutations in the granulin gene (GRN) cause familial frontotemporal dementia. Understanding the structural brain changes in presymptomatic GRN carriers would enforce the use of neuroimaging biomarkers for early diagnosis and monitoring. We studied 100 presymptomatic GRN mutation carriers and 94 noncarriers from the Genetic Frontotemporal dementia initiative (GENFI), with MRI structural images. We analyzed 3T MRI structural images using the FreeSurfer pipeline to calculate the whole brain cortical thickness (CTh) for each subject. We also perform a vertex-wise general linear model to assess differences between groups in the relationship between CTh and diverse covariables as gender, age, the estimated years to onset and education. We also explored differences according to TMEM106B genotype, a possible disease modifier. Whole brain CTh did not differ between carriers and noncarriers. Both groups showed age-related cortical thinning. The group-by-age interaction analysis showed that this age-related cortical thinning was significantly greater in GRN carriers in the left superior frontal cortex. TMEM106B did not significantly influence the age-related cortical thinning. Our results validate and expand previous findings suggesting an increased CTh loss associated with age and estimated proximity to symptoms onset in GRN carriers, even before the disease onset.
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http://dx.doi.org/10.1016/j.nicl.2020.102540DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804836PMC
June 2021

Progression of Behavioral Disturbances and Neuropsychiatric Symptoms in Patients With Genetic Frontotemporal Dementia.

JAMA Netw Open 2021 01 4;4(1):e2030194. Epub 2021 Jan 4.

Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Importance: Behavioral disturbances are core features of frontotemporal dementia (FTD); however, symptom progression across the course of disease is not well characterized in genetic FTD.

Objective: To investigate behavioral symptom frequency and severity and their evolution and progression in different forms of genetic FTD.

Design, Setting, And Participants: This longitudinal cohort study, the international Genetic FTD Initiative (GENFI), was conducted from January 30, 2012, to May 31, 2019, at 23 multicenter specialist tertiary FTD research clinics in the United Kingdom, the Netherlands, Belgium, France, Spain, Portugal, Italy, Germany, Sweden, Finland, and Canada. Participants included a consecutive sample of 232 symptomatic FTD gene variation carriers comprising 115 with variations in C9orf72, 78 in GRN, and 39 in MAPT. A total of 101 carriers had at least 1 follow-up evaluation (for a total of 400 assessments). Gene variations were included only if considered pathogenetic.

Main Outcomes And Measures: Behavioral and neuropsychiatric symptoms were assessed across disease duration and evaluated from symptom onset. Hierarchical generalized linear mixed models were used to model behavioral and neuropsychiatric measures as a function of disease duration and variation.

Results: Of 232 patients with FTD, 115 (49.6%) had a C9orf72 expansion (median [interquartile range (IQR)] age at evaluation, 64.3 [57.5-69.7] years; 72 men [62.6%]; 115 White patients [100%]), 78 (33.6%) had a GRN variant (median [IQR] age, 63.4 [58.3-68.8] years; 40 women [51.3%]; 77 White patients [98.7%]), and 39 (16.8%) had a MAPT variant (median [IQR] age, 56.3 [49.9-62.4] years; 25 men [64.1%]; 37 White patients [94.9%]). All core behavioral symptoms, including disinhibition, apathy, loss of empathy, perseverative behavior, and hyperorality, were highly expressed in all gene variant carriers (>50% patients), with apathy being one of the most common and severe symptoms throughout the disease course (51.7%-100% of patients). Patients with MAPT variants showed the highest frequency and severity of most behavioral symptoms, particularly disinhibition (79.3%-100% of patients) and compulsive behavior (64.3%-100% of patients), compared with C9orf72 carriers (51.7%-95.8% of patients with disinhibition and 34.5%-75.0% with compulsive behavior) and GRN carriers (38.2%-100% with disinhibition and 20.6%-100% with compulsive behavior). Alongside behavioral symptoms, neuropsychiatric symptoms were very frequently reported in patients with genetic FTD: anxiety and depression were most common in GRN carriers (23.8%-100% of patients) and MAPT carriers (26.1%-77.8% of patients); hallucinations, particularly auditory and visual, were most common in C9orf72 carriers (10.3%-54.5% of patients). Most behavioral and neuropsychiatric symptoms increased in the early-intermediate phases and plateaued in the late stages of disease, except for depression, which steadily declined in C9orf72 carriers, and depression and anxiety, which surged only in the late stages in GRN carriers.

Conclusions And Relevance: This cohort study suggests that behavioral and neuropsychiatric disturbances differ between the common FTD gene variants and have different trajectories throughout the course of disease. These findings have crucial implications for counseling patients and caregivers and for the design of disease-modifying treatment trials in genetic FTD.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.30194DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788468PMC
January 2021

Apathy in presymptomatic genetic frontotemporal dementia predicts cognitive decline and is driven by structural brain changes.

Alzheimers Dement 2021 06 14;17(6):969-983. Epub 2020 Dec 14.

Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.

Introduction: Apathy adversely affects prognosis and survival of patients with frontotemporal dementia (FTD). We test whether apathy develops in presymptomatic genetic FTD, and is associated with cognitive decline and brain atrophy.

Methods: Presymptomatic carriers of MAPT, GRN or C9orf72 mutations (N = 304), and relatives without mutations (N = 296) underwent clinical assessments and MRI at baseline, and annually for 2 years. Longitudinal changes in apathy, cognition, gray matter volumes, and their relationships were analyzed with latent growth curve modeling.

Results: Apathy severity increased over time in presymptomatic carriers, but not in non-carriers. In presymptomatic carriers, baseline apathy predicted cognitive decline over two years, but not vice versa. Apathy progression was associated with baseline low gray matter volume in frontal and cingulate regions.

Discussion: Apathy is an early marker of FTD-related changes and predicts a subsequent subclinical deterioration of cognition before dementia onset. Apathy may be a modifiable factor in those at risk of FTD.
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http://dx.doi.org/10.1002/alz.12252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247340PMC
June 2021

Pathogenic Huntingtin Repeat Expansions in Patients with Frontotemporal Dementia and Amyotrophic Lateral Sclerosis.

Neuron 2021 02 26;109(3):448-460.e4. Epub 2020 Nov 26.

Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25125, Italy; MAC Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25125, Italy.

We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40-64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington's disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered.
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http://dx.doi.org/10.1016/j.neuron.2020.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864894PMC
February 2021

Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility.

Brain Struct Funct 2021 Jan 24;226(1):137-150. Epub 2020 Nov 24.

Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy.

Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.
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http://dx.doi.org/10.1007/s00429-020-02172-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817563PMC
January 2021

Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort.

Cortex 2020 12 26;133:384-398. Epub 2020 Sep 26.

Department of Neurology, Ludwig-Maximilians-University, Munich, Germany.

A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the disease.
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http://dx.doi.org/10.1016/j.cortex.2020.08.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754789PMC
December 2020

Brain functional network integrity sustains cognitive function despite atrophy in presymptomatic genetic frontotemporal dementia.

Alzheimers Dement 2021 03 20;17(3):500-514. Epub 2020 Nov 20.

Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Introduction: The presymptomatic phase of neurodegenerative disease can last many years, with sustained cognitive function despite progressive atrophy. We investigate this phenomenon in familial frontotemporal dementia (FTD).

Methods: We studied 121 presymptomatic FTD mutation carriers and 134 family members without mutations, using multivariate data-driven approach to link cognitive performance with both structural and functional magnetic resonance imaging. Atrophy and brain network connectivity were compared between groups, in relation to the time from expected symptom onset.

Results: There were group differences in brain structure and function, in the absence of differences in cognitive performance. Specifically, we identified behaviorally relevant structural and functional network differences. Structure-function relationships were similar in both groups, but coupling between functional connectivity and cognition was stronger for carriers than for non-carriers, and increased with proximity to the expected onset of disease.

Discussion: Our findings suggest that the maintenance of functional network connectivity enables carriers to maintain cognitive performance.
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http://dx.doi.org/10.1002/alz.12209DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611220PMC
March 2021

Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia.

Brain Commun 2020 Jul 19;2(2). Epub 2020 Aug 19.

Instituto di Recovero e Cura a Carattere Scientifico Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Frontotemporal dementia is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of frontotemporal dementia, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work we combined gene expression data for 16,772 genes from the Allen Institute for Brain Science atlas with brain maps of gray matter atrophy in symptomatic and mutation carriers obtained from the Genetic Frontotemporal dementia Initiative study. No significant association was seen between and expression and the atrophy patterns in the respective genetic groups. After adjusting for spatial autocorrelation, between 1,000 and 5,000 genes showed a negative or positive association with the atrophy pattern within each individual genetic group, with the most significantly associated genes being and (negative association in and respectively) and , and (positive association in and respectively). An overrepresentation analysis identified a negative association with genes involved in mitochondrial function, and a positive association with genes involved in vascular and glial cell function in each of the genetic groups. A set of 423 and 700 genes showed significant positive and negative association, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in frontotemporal dementia than previously assumed, and in the case of the positively-associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood-brain barrier respectively.
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http://dx.doi.org/10.1093/braincomms/fcaa122DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7667525PMC
July 2020

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease.

Brain Sci 2020 Nov 3;10(11). Epub 2020 Nov 3.

Fondazione IRCCS Istituto Neurologico Carlo Besta, Division of Neurology 5 and Neuropathology, 20133 Milan, Italy.

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.
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http://dx.doi.org/10.3390/brainsci10110815DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692713PMC
November 2020

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts.

Front Neurol 2020 23;11:1021. Epub 2020 Sep 23.

Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify-CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, = 432), Mild Cognitive Impairment (MCI, = 456), and AD ( = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from "slight" to "significant" in 80% of the cases. GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.
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http://dx.doi.org/10.3389/fneur.2020.01021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538836PMC
September 2020

, age at onset, and ancestry help discriminate behavioral from language variants in FTLD cohorts.

Neurology 2020 12 17;95(24):e3288-e3302. Epub 2020 Sep 17.

From the Institute of Neurology (B.C., D.A.K., J.H., P.A.L., R.F.), School of Pharmacy (C.M.), and UCL Movement Disorders Centre (J.H.), University College London; School of Pharmacy (C.M., P.A.L.), University of Reading, Whiteknights; Neurogenetics Laboratory (M.B.-Q., C.W., J.M.P.), National Hospital for Neurology and Neurosurgery, London, UK; Aptima Clinic (Miquel Aguilar), Terrassa; Memory Disorders Unit, Department of Neurology (I.A., M.D.-F., P.P.), University Hospital Mutua de Terrassa, Barcelona; Hospital Universitario Central de Asturias (V.A., M.M.-G.), Oviedo, Spain; NORMENT (O.A.), Institute of Clinical Medicine, University of Oslo, Norway; Regional Neurogenetic Centre (Maria Anfossi, Livia Bernardi, A.C.B., M.E.C., Chiara Cupidi, F.F., Maura Gallo, R.M., N.S.), ASPCZ, Lamezia Terme; Department of Neuroscience, Psychology, Drug Research and Child Health (S.B., B.N., I.P., S.S.), University of Florence; Molecular Markers Laboratory (Luisa Benussi, Giuliano Binetti, R.G.), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Sheffield Institute for Translational Neuroscience (SITraN), Department of Neuroscience (D.B.), University of Sheffield, UK; Research Center and Memory Clinic (M.B., I.H., S.M.-G., Agustín Ruiz), Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya (UIC), Barcelona, Spain; Centre for Neurodegenerative Disorders (B.B., A.P.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Department of Clinical Neurosciences (Lucy Bowns, T.E.C., J.B.R.), Cambridge University, UK; Department of Neurology (Geir Bråthen, S.B.S.), University Hospital of Trondheim, Norway; Dept NVS, Division of Neurogeriatrics (H.-H.C., C.G., B.K., L.Ö.), Karolinska Institutet, Bioclinicum Solna, Sweden; Department of Neurology (J.C., O.D.-I., I.I.-G., A.L.), IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Spain; Anne Rowling Regenerative Neurology Clinic (S.C., G.J.T.H., S.P.) and Centre for Clinical Brain Sciences (S.P.), University of Edinburgh, UK; NeuroGenomics and Informatics, Department of Psychiatry (Carlos Cruchaga), Washington University, St. Louis, MO; Cognitive Impairment Center (M.E.D.B., Maurizio Gallucci) and Immunohematology and Transfusional Medicine Service (E.D., A.V.), Local Health Authority n.2 Marca Trevigiana, Treviso, Italy; Department of Psychiatry and Psychotherapy (J.D.-S., C.R.), School of Medicine, Technical University of Munich, Germany; Department of Neurology (D.F., M.G.K.) and Clinical Institute of Medical Genetics (A.M., B.P.), University Medical Center Ljubljana, Slovenia; Dino Ferrari Center (D.G., Elio Scarpini, M.S.), University of Milan, Italy; Cognitive Neuroscience Lab, Think and Speak Lab (J.H.G.), Shirley Ryan Ability Lab, Chicago, IL; Department of Pathology and Laboratory Medicine (Murray Grossman, EunRan Suh, J.Q.T., V.M.V.D.), Center for Neurodegenerative Diseases, Perelman School of Medicine at the University of Pennsylvania, Philadelphia; UCL Dementia Research Institute (J.H.), London; Reta Lila Weston Institute (J.H.), UCL Queen Square Institute of Neurology, UK; Institute for Advanced Study (J.H.), The Hong Kong University of Science and Technology, China; Royal Edinburgh Hospital (G.J.T.H.), UK; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (E.D.H.), Columbia University, New York, NY; Department of Neurology, Memory and Aging Center (A.K., B.M., J.Y.), University of California, San Francisco; UCL Genomics (M.K., G.K.M., Y.P.), UCL Great Ormond Street Institute of Child Health, London, UK; Geriatric Center Frullone ASL Napoli 1 Centro (G.M.), Napoli, Italy; Department of Neurology (M.O.M., J.v.R., J.C.V.S.), Erasmus Medical Center, Rotterdam, the Netherlands; Rona Holdings (P.M.), Silicon Valley, CA; Newcastle Brain Tissue Resource, Institute of Neuroscience (C.M.M.), Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK; Department of Neurology (C.N.), Skåne University Hospital, Malmö, Sweden; Fondazione Policlinico Universitario A. Gemelli IRCCS (V.N.), Rome, Italy; Division of Neuroscience & Experimental Psychology (S.P.-B., A.M.T.R., S.R., J.C.T.), University of Manchester, UK; Amsterdam University Medical Center (Y.A.L.P.), VU University Medical Center, the Netherlands; Cardiovascular Research Unit (A.A.P.), IRCCS Multimedica, Milan; Neurology I, Department of Neuroscience (I.R., Elisa Rubino), University of Torino; NeurOMICS laboratory (G.M., Antonella Rendina, E.V.), Institute of Biochemistry and Cell Biology (IBBC), CNR Napoli, Italy; Manchester Centre for Clinical Neurosciences (A.M.T.R., J.S., J.C.T.), Salford Royal NHS Trust, Manchester, UK; Tanz Centre for Research in Neurodegenerative Diseases (Ekaterina Rogaeva), University of Toronto, Canada; Department of Biotechnology (B.R.), Jožef Stefan Institute, Ljubljana, Slovenia; Division of Neurology V and Neuropathology (G.R., F.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy; Alzheimer's Disease and Other Cognitive Disorders Unit (R.S.-V.), Hospital Clínic of Barcelona, Spain; Clinical Memory Research Unit, Department of Clinical Sciences Malmö (C.N., A.F.S.), and Division of Clinical Sciences Helsingborg, Department of Clinical Sciences Lund (M.L.W.), Lund University, Sweden; Neurodegenerative Brain Diseases Group (J.V.d.Z., C.V.B.), Center for Molecular Neurology, VIB, Antwerp, Belgium; Medical Research Council Centre for Neuropsychiatric Genetics and Genomics (V.E.-P.), Division of Psychological Medicine and Clinical Neurosciences and Dementia Research Institute, Cardiff University, UK; Instituto de Investigación Sanitaria del Principado de Asturias (V.A.), Oviedo, Asturias; Fundació per la Recerca Biomèdica i Social Mútua Terrassa (I.A., M.D.-F., P.P.), Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED) (M.B., J.C., O.D.-I., I.H., I.I.-G., A.L., S.M.-G., Agustín Ruiz), Instituto de Salud Carlos III, Madrid, Spain; MRC Cognition and Brain Sciences Unit (Lucy Bowns, T.E.C., J.B.R.), Cambridge University, UK; Department of Neuromedicine and Movement Science (Geir Bråthen, S.B.S.), Norwegian University of Science and Technology, Trondheim, Norway; Unit for Hereditary Dementias (H.-H.C., C.G., B.K., L.Ö.), Theme Aging, Karolinska University Hospital, Solna, Sweden; Medical Faculty (D.F., M.G.K.), University of Ljubljana, Slovenia; Fondazione IRCCS Ca'Granda (D.G., Elio Scarpini, M.S.), Ospedale Policlinico, Milan, Italy; Penn Center for Frontotemporal Degeneration (Murray Grossman), Philadelphia, PA; Universidad de Oviedo (M.M.-G.), Asturias, Spain; IRCCS Fondazione Don Carlo Gnocchi (B.N., S.S.), Florence; Istituto di Medicina Genomica (V.N.), Università Cattolica del sacro Cuore, Rome, Italy; Amsterdam Neuroscience (Y.A.L.P.), the Netherlands; Department of Medicine and Surgery (A.A.P.), University of Salerno, Baronissi (SA), Italy; Faculty of Chemistry and Chemical Technology (B.R.), University of Ljubljana, Slovenia; Institud d'Investigacions Biomèdiques August Pi i Sunyer (R.S.-V.), Barcelona, Spain; Department of Biomedical Sciences (J.V.d.Z., C.V.B.), University of Antwerp, Belgium; and Department of Comparative Biomedical Sciences (P.A.L.), The Royal Veterinary College, London, UK.

Objective: We sought to characterize expansions in relation to genetic ancestry and age at onset (AAO) and to use these measures to discriminate the behavioral from the language variant syndrome in a large pan-European cohort of frontotemporal lobar degeneration (FTLD) cases.

Methods: We evaluated expansions frequency in the entire cohort (n = 1,396; behavioral variant frontotemporal dementia [bvFTD] [n = 800], primary progressive aphasia [PPA] [n = 495], and FTLD-motor neuron disease [MND] [n = 101]). We then focused on the bvFTD and PPA cases and tested for association between expansion status, syndromes, genetic ancestry, and AAO applying statistical tests comprising Fisher exact tests, analysis of variance with Tukey post hoc tests, and logistic and nonlinear mixed-effects model regressions.

Results: We found pathogenic expansions in 4% of all cases (56/1,396). Expansion carriers differently distributed across syndromes: 12/101 FTLD-MND (11.9%), 40/800 bvFTD (5%), and 4/495 PPA (0.8%). While addressing population substructure through principal components analysis (PCA), we defined 2 patients groups with Central/Northern (n = 873) and Southern European (n = 523) ancestry. The proportion of expansion carriers was significantly higher in bvFTD compared to PPA (5% vs 0.8% [ = 2.17 × 10; odds ratio (OR) 6.4; confidence interval (CI) 2.31-24.99]), as well as in individuals with Central/Northern European compared to Southern European ancestry (4.4% vs 1.8% [ = 1.1 × 10; OR 2.5; CI 1.17-5.99]). Pathogenic expansions and Central/Northern European ancestry independently and inversely correlated with AAO. Our prediction model (based on expansions status, genetic ancestry, and AAO) predicted a diagnosis of bvFTD with 64% accuracy.

Conclusions: Our results indicate correlation between pathogenic expansions, AAO, PCA-based Central/Northern European ancestry, and a diagnosis of bvFTD, implying complex genetic risk architectures differently underpinning the behavioral and language variant syndromes.
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http://dx.doi.org/10.1212/WNL.0000000000010914DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836664PMC
December 2020

Early symptoms in symptomatic and preclinical genetic frontotemporal lobar degeneration.

J Neurol Neurosurg Psychiatry 2020 09 7;91(9):975-984. Epub 2020 Aug 7.

Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.

Objectives: The clinical heterogeneity of frontotemporal dementia (FTD) complicates identification of biomarkers for clinical trials that may be sensitive during the prediagnostic stage. It is not known whether cognitive or behavioural changes during the preclinical period are predictive of genetic status or conversion to clinical FTD. The first objective was to evaluate the most frequent initial symptoms in patients with genetic FTD. The second objective was to evaluate whether preclinical mutation carriers demonstrate unique FTD-related symptoms relative to familial mutation non-carriers.

Methods: The current study used data from the Genetic Frontotemporal Dementia Initiative multicentre cohort study collected between 2012 and 2018. Participants included symptomatic carriers (n=185) of a pathogenic mutation in chromosome 9 open reading frame 72 (), progranulin () or microtubule-associated protein tau () and their first-degree biological family members (n=588). Symptom endorsement was documented using informant and clinician-rated scales.

Results: The most frequently endorsed initial symptoms among symptomatic patients were apathy (23%), disinhibition (18%), memory impairments (12%), decreased fluency (8%) and impaired articulation (5%). Predominant first symptoms were usually discordant between family members. Relative to biologically related non-carriers, preclinical carriers endorsed worse mood and sleep symptoms, and carriers endorsed marginally greater abnormal behaviours. Preclinical carriers endorsed less mood symptoms compared with non-carriers, and worse everyday skills.

Conclusion: Preclinical mutation carriers exhibited neuropsychiatric symptoms compared with non-carriers that may be considered as future clinical trial outcomes. Given the heterogeneity in symptoms, the detection of clinical transition to symptomatic FTD may be best captured by composite indices integrating the most common initial symptoms for each genetic group.
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http://dx.doi.org/10.1136/jnnp-2020-322987DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611534PMC
September 2020
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