Electroencephalographic Rhythms in Alzheimer's Disease

Physiological brain aging is characterized by synapses loss and neurodegeneration that slowly lead to an age-related decline of cognition. Neural/synaptic redundancy and plastic remodelling of brain networking, also due to mental and physical training, promotes maintenance of brain activity in healthy elderly subjects for everyday life and good social behaviour and intellectual capabilities. However, age is the major risk factor for most common neurodegenerative disorders that impact on cognition, like Alzheimer's disease (AD). Brain electromagnetic activity is a feature of neuronal network function in various brain regions. Modern neurophysiological techniques, such as electroencephalography (EEG) and event-related potentials (ERPs), are useful tools in the investigation of brain cognitive function in normal and pathological aging with an excellent time resolution. These techniques can index normal and abnormal brain aging analysis of corticocortical connectivity and neuronal synchronization of rhythmic oscillations at various frequencies. The present review suggests that discrimination between physiological and pathological brain aging clearly emerges at the group level, with suggested applications also at the level of single individual. The possibility of combining the use of EEG together with biological/neuropsychological markers and structural/functional imaging is promising for a low-cost, non-invasive, and widely available assessment of groups of individuals at-risk

Resting State Cortical Electroencephalographic Rhythms in Alzheimer`s Disease

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[P‐092]: Neuroprotective effects of hormone replacement therapy in healthy postmenopausal women: A VBM study

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Presenilin 1 Protein Directly Interacts with Bcl-2

Presenilin proteins are involved in familial Alzheimer's disease, a neurodegenerative disorder characterized by massive death of neurons. We describe a direct interaction between presenilin 1 (PS1) and Bcl-2, a key factor in the regulation of apoptosis, by yeast two-hybrid interaction system, by co-immunoprecipitation, and by cross-linking experiments. Our data show that PS1 and Bcl-2 assemble into a macromolecular complex, and that they are released from this complex in response to an apoptotic stimulus induced by staurosporine. The results support the idea of cross-talk between these two proteins during apoptosis

Rare mutations in SQSTM1 modify susceptibility to frontotemporal lobar degeneration

Mutations in the gene coding for Sequestosome 1 (SQSTM1) have been genetically associated with amyotrophic lateral sclerosis (ALS) and Paget disease of bone. In the present study, we analyzed the SQSTM1 coding sequence for mutations in an extended cohort of 1,808 patients with frontotemporal lobar degeneration (FTLD), ascertained within the European Early-Onset Dementia consortium. As control dataset, we sequenced 1,625 European control individuals and analyzed whole-exome sequence data of 2,274 German individuals (total n = 3,899). Association of rare SQSTM1 mutations was calculated in a meta-analysis of 4,332 FTLD and 10,240 control alleles. We identified 25 coding variants in FTLD patients of which 10 have not been described. Fifteen mutations were absent in the control individuals (carrier frequency < 0.00026) whilst the others were rare in both patients and control individuals. When pooling all variants with a minor allele frequency < 0.01, an overall frequency of 3.2 % was calculated in patients. Rare variant association analysis between patients and controls showed no difference over the whole protein, but suggested that rare mutations clustering in the UBA domain of SQSTM1 may influence disease susceptibility by doubling the risk for FTLD (RR = 2.18 [95 % CI 1.24-3.85]; corrected p value = 0.042). Detailed histopathology demonstrated that mutations in SQSTM1 associate with widespread neuronal and glial phospho-TDP-43 pathology. With this study, we provide further evidence for a putative role of rare mutations in SQSTM1 in the genetic etiology of FTLD and showed that, comparable to other FTLD/ALS genes, SQSTM1 mutations are associated with TDP-43 pathology

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

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 2022;91:33–47

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI

Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high-dimensional large-scale population datasets to obtain individual scores of disease stage. We used cross-sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting-state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI-obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre-dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data-driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics

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

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.K.A.T. is supported by the British Academy Postdoctoral Fellowship (PF160048) and the Guarantors of Brain (101149). J.B.R. is supported by theWellcome Trust (103838), the Medical Research Council (SUAG/051 G101400), and the Cambridge NIHR Biomedical Research Centre. R. S.-V. is supported by the Instituto de Salud Carlos III and the JPND network PreFrontAls (01ED1512/AC14/0013) and the Fundació Marató de TV3 (20143810). M.M and E.F are supported by the UK Medical Research Council, the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, and also a Canadian Institutes of Health Research operating grant (MOP 327387) and funding from the Weston Brain Institute. J.D.R., D.C., and K.M.M. are supported by the NIHR Queen Square Dementia Biomedical Research Unit, the NIHR UCL/H Biomedical Research Centre, and the LeonardWolfson Experimental Neurology Centre (LWENC) Clinical Research Facility. J.D.R. is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH), the MRC UK GENFI grant (MR/ M023664/1), and The Bluefield Project. F.T. is supported by the Italian Ministry of Health (Grant NET-2011-02346784). L.C.J. and J.V.S. are supported by the Association for Frontotemporal Dementias Research Grant 2009, ZonMwMemorabel project number 733050103 and 733050813, and the Bluefield project. R.G. is supported by Italian Ministry of Health, Ricerca Corrente. J.L. was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145; SyNergy - ID 390857198). The Swedish contributors C.G., L.O., and C.A. were supported by grants from JPND Prefrontals Swedish Research Council (VR) 529-2014-7504, JPND GENFI-PROX Swedish Research Council (VR) 2019-02248, Swedish Research Council (VR) 2015- 02926, Swedish Research Council (VR) 2018-02754, Swedish FTD Initiative- Schorling Foundation, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Karolinska InstitutetDoctoral Funding, and StratNeuro, Swedish Demensfonden, during the conduct of the study