The complexity of Alzheimer's disease: an evolving puzzle.

The history of Alzheimer's disease (AD) started in 1907, but we needed to wait until the end of the century to identify the components of pathological hallmarks and genetic subtypes and to formulate the first pathogenic hypothesis. Thanks to biomarkers and new technologies, the concept of AD then rapidly changed from a static view of an amnestic dementia of the presenium to a biological entity that could be clinically manifested as normal cognition or dementia of different types. What is clearly emerging from studies is that AD is heterogeneous in each aspect, such as amyloid composition, tau distribution, relation between amyloid and tau, clinical symptoms, and genetic background, and thus it is probably impossible to explain AD with a single pathological process. The scientific approach to AD suffers from chronological mismatches between clinical, pathological, and technological data, causing difficulty in conceiving diagnostic gold standards and in creating models for drug discovery and screening. A recent mathematical computer-based approach offers the opportunity to study AD in real life and to provide a new point of view and the final missing pieces of the AD puzzle.

NfL reliability across laboratories, stage-dependent diagnostic performance and matrix comparability in genetic FTD: a large GENFI study.

BACKGROUND: Blood neurofilament light chain (NfL) is increasingly considered as a key trial biomarker in genetic frontotemporal dementia (gFTD). We aimed to facilitate the use of NfL in gFTD multicentre trials by testing its (1) reliability across labs; (2) reliability to stratify gFTD disease stages; (3) comparability between blood matrices and (4) stability across recruiting sites. METHODS: Comparative analysis of blood NfL levels in a large gFTD cohort (GENFI) for (1)-(4), with n=344 samples (n=148 presymptomatic, n=11 converter, n=46 symptomatic subjects, with mutations in C9orf72, GRN or MAPT; and n=139 within-family controls), each measured in three different international labs by Simoa HD-1 analyzer. RESULTS: NfL revealed an excellent consistency (intraclass correlation coefficient (ICC) 0.964) and high reliability across the three labs (maximal bias (pg/mL) in Bland-Altman analysis: 1.12±1.20). High concordance of NfL across laboratories was moreover reflected by high areas under the curve for discriminating conversion stage against the (non-converting) presymptomatic stage across all three labs. Serum and plasma NfL were largely comparable (ICC 0.967). The robustness of NfL across 13 recruiting sites was demonstrated by a linear mixed effect model. CONCLUSIONS: Our results underline the suitability of blood NfL in gFTD multicentre trials, including cross-lab reliable stratification of the highly trial-relevant conversion stage, matrix comparability and cross-site robustness.

Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study.

BACKGROUND AND PURPOSE: We aimed to evaluate the accuracy of plasma neurofilament light chain (NfL) in predicting Alzheimer's disease (AD) and the progression of cognitive decline in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHODS: This longitudinal cohort study involved 140 patients (45 with SCD, 73 with MCI, and 22 with AD dementia [AD-D]) who underwent plasma NfL and AD biomarker assessments (cerebrospinal fluid, amyloid positron emission tomography [PET], and 18 F-fluorodeoxyglucose-PET) at baseline. The patients were rated according to the amyloid/tau/neurodegeneration (A/T/N) system and followed up for a mean time of 2.72 ± 0.95 years to detect progression from SCD to MCI and from MCI to AD. Forty-eight patients (19 SCD, 29 MCI) also underwent plasma NfL measurements 2 years after baseline. RESULTS: At baseline, plasma NfL detected patients with biomarker profiles consistent with AD (A+/T+/N+ or A+/T+/N-) with high accuracy (area under the curve [AUC] 0.82). We identified cut-off values of 19.45 pg/mL for SCD and 20.45 pg/mL for MCI. During follow-up, nine SCD patients progressed to MCI (progressive SCD [p-SCD]), and 14 MCI patients developed AD dementia (progressive MCI [p-MCI]). The previously identified cut-off values provided good accuracy in identifying p-SCD (80% [95% confidence interval 65.69: 94.31]). The rate of NfL change was higher in p-MCI (3.52 ± 4.06 pg/mL) compared to non-progressive SCD (0.81 ± 1.25 pg/mL) and non-progressive MCI (-0.13 ± 3.24 pg/mL) patients. A rate of change lower than 1.64 pg/mL per year accurately excluded progression from MCI to AD (AUC 0.954). CONCLUSION: Plasma NfL concentration and change over time may be a reliable, non-invasive tool to detect AD and the progression of cognitive decline at the earliest stages of the disease.

Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia.

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.

Neurodevelopmental effects of genetic frontotemporal dementia in young adult mutation carriers.

While frontotemporal dementia has been considered a neurodegenerative disease that starts in mid-life or later, it is now clearly established that cortical and subcortical volume loss is observed more than a decade prior to symptom onset and progresses with ageing. To test the hypothesis that genetic mutations causing frontotemporal dementia have neurodevelopmental consequences, we examined the youngest adults in the GENFI cohort of pre-symptomatic frontotemporal dementia mutation carriers who are between 19 and 30 years of age. Structural brain differences and improved performance on some cognitive tests were found for MAPT and GRN mutation carriers relative to familial non-carriers, while smaller volumes were observed in C9orf72 repeat expansion carriers at a mean age of 26 years. The detection of such early differences supports potential advantageous neurodevelopmental consequences of some frontotemporal dementia-causing genetic mutations. These results have implications for the design of therapeutic interventions for frontotemporal dementia. Future studies at younger ages are needed to identify specific early pathophysiologic or compensatory processes that occur during the neurodevelopmental period.

Parkinson-ALS with a novel MAPT variant.

The mutations on microtubule associated protein tau (MAPT) gene manifest clinically with behavioural frontotemporal dementia (FTD), parkinsonism, such as progressive supranuclear palsy and corticobasal degeneration, and rarely with amyotrophic lateral sclerosis (ALS). FTD-parkinsonism and FTD-ALS are clinical overlaps included in the spectrum of MAPT mutation's phenotypes. The mutations on MAPT gene cause the dysfunction of tau protein determining its accumulation in neurofibrillary tangles. Recent data describe frequently the co-occurrence of the aggregation of tau protein and α-synuclein in patients with parkinsonism and Parkinson disease (PD), suggesting an interaction of the two proteins in determining neurodegenerative process. The sporadic description of PD-ALS clinical complex, known as Brait-Fahn-Schwarz disease, supports the hypothesis of common neuropathological pathways between different disorders. Here we report the case of a 54-year-old Italian woman with idiopathic PD later complicated by ALS carrying a novel MAPT variant (Pro494Leu). The variant is characterized by an amino acid substitution and is classified as damaging for MAPT functions. The case supports the hypothesis of tau dysfunction as the basis of multiple neurodegenerative disorders.

Understanding the interplay between APO E polymorphism and cognition in the Italian oldest old: results from the "Mugello study".

INTRODUCTION: Recent data suggest that the deleterious effect on general health and cognition of ε4 allele of Apolipoprotein E (ApoE) observed in the elderly population, may attenuate in extreme aging. This study aimed to describe the ApoE genotype distribution and its relationship with cognition in a group of nonagenarians living in the Mugello area, Italy. MATERIAL AND METHODS: Cognition was evaluated using the Mini-Mental-State-Examination (MMSE). DNA was extracted from blood samples to determine ApoE genotyping. Participants were classified into three ApoE groups (ε2, ε3, ε4). Logistic and linear regression models were created, to assess the relationship between ApoE genotype group and dementia diagnosis and cognitive performance, respectively. RESULTS: 169 subjects were included. ApoE ε3 was the most prevalent genotype (76.3%). Dementia prevalence was 26.6% and it was not associated with the presence of ApoE ε4. Participants of ε4 group were significantly more likely to have lower cognitive performances than ε2 and ε3, independently of a dementia diagnosis. DISCUSSION: Results support that ApoE genotype no longer plays a role in the health condition of the oldest old, however, an interaction is detectable between ApoE polymorphism and cognitive performances at this extreme age.

The role of plasma neurofilament light chain and glial fibrillary acidic protein in subjective cognitive decline and mild cognitive impairment.

INTRODUCTION AND AIM: NfL and GFAP are promising blood-based biomarkers for Alzheimer's disease. However, few studies have explored plasma GFAP in the prodromal and preclinical stages of AD. In our cross-sectional study, our aim is to investigate the role of these biomarkers in the earliest stages of AD. MATERIALS AND METHODS: We enrolled 40 patients (11 SCD, 21 MCI, 8 AD dementia). All patients underwent neurological and neuropsychological examinations, analysis of CSF biomarkers (Aß42, Aß42/Aß40, p-tau, t-tau), Apolipoprotein E (APOE) genotype analysis and measurement of plasma GFAP and NfL concentrations. Patients were categorized according to the ATN system as follows: normal AD biomarkers (NB), carriers of non-Alzheimer's pathology (non-AD), prodromal AD, or AD with dementia (AD-D). RESULTS: GFAP was lower in NB compared to prodromal AD (p = 0.003, d = 1.463) and AD-D (p = 0.002, d = 1.695). NfL was lower in NB patients than in AD-D (p = 0.011, d = 1.474). NfL demonstrated fair accuracy (AUC = 0.718) in differentiating between NB and prodromal AD, with a cut-off value of 11.65 pg/mL. GFAP showed excellent accuracy in differentiating NB from prodromal AD (AUC = 0.901) with a cut-off level of 198.13 pg/mL. CONCLUSIONS: GFAP exhibited excellent accuracy in distinguishing patients with normal CSF biomarkers from those with prodromal AD. Our results support the use of this peripheral biomarker for detecting AD in patients with subjective and objective cognitive decline.

Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results.

INTRODUCTION: Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers. METHODS: We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment. RESULTS: Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset. DISCUSSION: Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset. HIGHLIGHTS: Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.

Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study.

BACKGROUND: Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. METHODS: In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. RESULTS: In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01). CONCLUSIONS: This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.

Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia.

Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.

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.

Neuropsychiatric symptoms in genetic frontotemporal dementia: developing a new module for Clinical Rating Scales.

BACKGROUND: Current clinical rating scales in frontotemporal dementia (FTD) often do not incorporate neuropsychiatric features and may therefore inadequately measure disease stage. METHODS: 832 participants from the Genetic FTD Initiative (GENFI) were recruited: 522 mutation carriers and 310 mutation-negative controls. The standardised GENFI clinical questionnaire assessed the frequency and severity of 14 neuropsychiatric symptoms: visual, auditory, and tactile hallucinations, delusions, depression, anxiety, irritability/lability, agitation/aggression, euphoria/elation, aberrant motor behaviour, hypersexuality, hyperreligiosity, impaired sleep, and altered sense of humour. A principal component analysis (PCA) was performed to identify key groupings of neuropsychiatric and behavioural items in order to create a new neuropsychiatric module that could be used as an addition to the Clinical Dementia Rating (CDR) plus National Alzheimer's Coordinating Center Behaviour and Language Domains (NACC FTLD) rating scale. RESULTS: Overall, 46.4% of mutation carriers had neuropsychiatric symptoms (51.6% C9orf72, 40.8% GRN, 46.6% MAPT) compared with 24.5% of controls. Anxiety and depression were the most common in all genetic groups but fluctuated longitudinally and loaded separately in the PCA. Hallucinations and delusions loaded together, with the remaining neuropsychiatric symptoms loading with the core behavioural features of FTD. These results suggest using a single 'psychosis' neuropsychiatric module consisting of hallucinations and delusions. Adding this to the CDR plus NACC FTLD, called the CDR plus NACC FTLD-N, leads to a number of participants being scored more severely, including those who were previously considered asymptomatic now being scored as prodromal. CONCLUSIONS: Neuropsychiatric symptoms occur in mutation carriers at all disease stages across all three genetic groups. However, only psychosis features provided additional staging benefit to the CDR plus NACC FTLD. Inclusion of these features brings us closer to optimising the rating scale for use in trials.

The Frequency of Intermediate Alleles in Patients with Cerebellar Phenotypes.

Cerebellar syndromes are clinically and etiologically heterogeneous and can be classified as hereditary, neurodegenerative non-hereditary, or acquired. Few data are available on the frequency of each form in the clinical setting. Growing interest is emerging regarding the genetic forms caused by triplet repeat expansions. Alleles with repeat expansion lower than the pathological threshold, termed intermediate alleles (IAs), have been found to be associated with disease manifestation. In order to assess the relevance of IAs as a cause of cerebellar syndromes, we enrolled 66 unrelated Italian ataxic patients and described the distribution of the different etiology of their syndromes and the frequency of IAs. Each patient underwent complete clinical, hematological, and neurophysiological assessments, neuroimaging evaluations, and genetic tests for autosomal dominant cerebellar ataxia (SCA) and fragile X-associated tremor/ataxia syndrome (FXTAS). We identified the following diagnostic categories: 28% sporadic adult-onset ataxia, 18% cerebellar variant of multiple system atrophy, 9% acquired forms, 9% genetic forms with full-range expansion, and 12% cases with intermediate-range expansion. The IAs were six in the FMR1 gene, two in the gene responsible for SCA8, and one in the ATXN2 gene. The clinical phenotype of patients carrying the IAs resembles, in most of the cases, the one associated with full-range expansion. Our study provides an exhaustive description of the causes of cerebellar ataxia, estimating for the first time the frequency of IAs in SCAs- and FXTAS-associated genes. The high percentage of cases with IAs supports further screening among patients with cerebellar syndromes.

Effect of BDNF Val66Met polymorphism on hippocampal subfields in multiple sclerosis patients.

Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism was shown to strongly affect BDNF function, but its role in modulating gray matter damage in multiple sclerosis (MS) patients is still not clear. Given BDNF relevance on the hippocampus, we aimed to explore BDNF Val66Met polymorphism effect on hippocampal subfield volumes and its role in cognitive functioning in MS patients. Using a 3T scanner, we obtained dual-echo and 3DT1-weighted sequences from 50 MS patients and 15 healthy controls (HC) consecutively enrolled. MS patients also underwent genotype analysis of BDNF, neurological and neuropsychological evaluation. Hippocampal subfields were segmented by using Freesurfer. The BDNF Val66Met polymorphism was found in 22 MS patients (44%). Compared to HC, MS patients had lower volume in: bilateral hippocampus-amygdala transition area (HATA); cornus ammonis (CA)1, granule cell layer of dentate gyrus (GCL-DG), CA4 and CA3 of the left hippocampal head; molecular layer (ML) of the left hippocampal body; presubiculum of right hippocampal body and right fimbria. Compared to BDNF Val66Val, Val66Met MS patients had higher volume in bilateral hippocampal tail; CA1, ML, CA3, CA4, and GCL-DG of left hippocampal head; CA1, ML, and CA3 of the left hippocampal body; left HATA and presubiculum of the right hippocampal head. In MS patients, higher lesion burden was associated with lower volume of presubiculum of right hippocampal body; lower volume of left hippocampal tail was associated with worse visuospatial memory performance; lower volume of left hippocampal head with worse performance in semantic fluency. Our findings suggest the BNDF Val66Met polymorphism may have a protective role in MS patients against both hippocampal atrophy and cognitive impairment. BDNF genotype might be a potential biomarker for predicting cognitive prognosis, and an interesting target to study for neuroprotective strategies.

PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With machine learning: the PREVIEW study protocol.

BACKGROUND: As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest stages of the disease. Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances on neuropsychological evaluation. Many studies demonstrated a higher prevalence of Alzheimer's pathology in patients diagnosed with SCD as compared to the general population. Consequently, SCD was suggested as an early symptomatic phase of AD. We will describe the study protocol of a prospective cohort study (PREVIEW) that aim to identify features derived from easily accessible, cost-effective and non-invasive assessment to accurately detect SCD patients who will progress to AD dementia. METHODS: We will include patients who self-referred to our memory clinic and are diagnosed with SCD. Participants will undergo: clinical, neurologic and neuropsychological examination, estimation of cognitive reserve and depression, evaluation of personality traits, APOE and BDNF genotyping, electroencephalography and event-related potential recording, lumbar puncture for measurement of Aß42, t-tau, and p-tau concentration and Aß42/Aß40 ratio. Recruited patients will have follow-up neuropsychological examinations every two years. Collected data will be used to train a machine learning algorithm to define the risk of being carriers of AD and progress to dementia in patients with SCD. DISCUSSION: This is the first study to investigate the application of machine learning to predict AD in patients with SCD. Since all the features we will consider can be derived from non-invasive and easily accessible assessments, our expected results may provide evidence for defining cost-effective and globally scalable tools to estimate the risk of AD and address the needs of patients with memory complaints. In the era of DMTs, this will have crucial implications for the early identification of patients suitable for treatment in the initial stages of AD. TRIAL REGISTRATION NUMBER (TRN): NCT05569083.

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

Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions.

Exploring depression in Alzheimer's disease: an Italian Delphi Consensus on phenomenology, diagnosis, and management.

BACKGROUND: In Alzheimer's disease (AD), the progressive cognitive impairment is often combined with a variety of neuropsychiatric symptoms, firstly depression. Nevertheless, its diagnosis and management is difficult, since specific diagnostic criteria and guidelines for treatment are still lacking. The aim of this Delphi study is to reach a shared point of view among different Italian specialists on depression in AD. METHODS: An online Delphi survey with 30 questions regarding epidemiology, diagnosis, clinical features, and treatment of depression in AD was administered anonymously to a panel of 53 expert clinicians. RESULTS: Consensus was achieved in most cases (86%). In the 80% of statements, a positive consensus was reached, while in 6% a negative consensus was achieved. No consensus was obtained in 14%. Among the most relevant findings, the link between depression and AD is believed to be strong and concerns etiopathogenesis and phenomenology. Further, depression in AD seems to have specific features compared to major depressive disorder (MDD). Regarding diagnosis, the DSM 5 diagnostic criteria for MDD seems to be not able to detect the specific aspects of depression in AD. Concerning treatment, antidepressant drugs are generally considered the main option for depression in dementia, according to previous guidelines. In order to limit side effects, multimodal and SSRI antidepressant are preferred by clinicians. In particular, the procognitive effect of vortioxetine seems to be appealing for the treatment of depression in AD. CONCLUSIONS: This study highlights some crucial aspects of depression in AD, but more investigations and specific recommendations are needed.

Exploring depression in Parkinson's disease: an Italian Delphi Consensus on phenomenology, diagnosis, and management.

BACKGROUND: Depression is a prodromic and a frequent non-motor symptom of Parkinson's disease, associated to reduced quality of life and poor outcomes. The diagnosis of depression in parkinsonian patients represents a challenge due to the overlapping of symptoms typical of the two conditions. METHODS: A Delphi panel survey was performed to reach a consensus amongst different Italian specialists on four main topics: the neuropathological correlates of depression, main clinical aspects, diagnosis, and management of depression in Parkinson's disease. RESULTS AND CONCLUSION: Experts have recognized that depression is an established risk factor of PD and that its anatomic substrate is related to the neuropathological abnormalities typical of the disease. Multimodal and SSRI antidepressant have been confirmed as a valid therapeutic option in the treatment of depression in PD. Tolerability, safety profile, and potential efficacy on broad spectrum of symptoms of depression including cognitive symptoms and anhedonia should be considered when selecting an antidepressant and the choice should be tailored on the patients' characteristics.

Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia.

INTRODUCTION: We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD). METHODS: For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression. RESULTS: We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants. DISCUSSION: Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion. HIGHLIGHTS: We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.