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Background In the last decade, non-invasive blood-based and neurophysiological biomarkers have shown great potential for the discrimination of several neurodegenerative disorders. However, in the clinical workup of patients with cognitive impairment, it will be highly unlikely that any biomarker will achieve the highest potential predictive accuracy on its own, owing to the multifactorial nature of Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD). Methods In this retrospective study, performed on 202 participants, we analysed plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau phosphorylated at amino acid 181 (p-Tau181) concentrations, as well as amyloid β42 to 40 ratio (Aβ1–42/1–40) ratio, using the ultrasensitive single-molecule array (Simoa) technique, and neurophysiological measures obtained by transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), long-interval intracortical inhibition (LICI), and short-latency afferent inhibition (SAI). We assessed the diagnostic accuracy of combinations of both plasma and neurophysiological biomarkers in the differential diagnosis between healthy ageing, AD, and FTLD. Results We observed significant differences in plasma NfL, GFAP, and p-Tau181 levels between the groups, but not for the Aβ1–42/Aβ1–40 ratio. For the evaluation of diagnostic accuracy, we adopted a two-step process which reflects the clinical judgement on clinical grounds. In the first step, the best single biomarker to classify “cases” vs “controls” was NfL (AUC 0.94, p p 181, GFAP, NfL, SICI, ICF, and SAI, resulting in an AUC of 0.99 (p 1–42/Aβ1–40 ratio, p-Tau181, SICI, ICF, and SAI, resulting in an AUC of 0.98 (p Conclusions The combined assessment of plasma and neurophysiological measures may greatly improve the differential diagnosis of AD and FTLD.

Blood-based biomarkers for amyloid beta and phosphorylated tau show good diagnostic accuracies and agreements with their corresponding CSF and neuroimaging biomarkers in the amyloid/tau/neurodegeneration [A/T/(N)] framework for Alzheimer’s disease. However, the blood-based neurodegeneration marker neurofilament light is not specific to Alzheimer’s disease while total-tau shows lack of correlation with CSF total-tau. Recent studies suggest that blood total-tau originates principally from peripheral, non-brain sources.We sought to address this challenge by generating an anti-tau antibody that selectively binds brain-derived tau and avoids the peripherally expressed ‘big tau’ isoform. We applied this antibody to develop an ultrasensitive blood-based assay for brain-derived tau, and validated it in five independent cohorts (n = 609) including a blood-to-autopsy cohort, CSF biomarker-classified cohorts and memory clinic cohorts.In paired samples, serum and CSF brain-derived tau were significantly correlated (rho = 0.85, P < 0.0001), while serum and CSF total-tau were not (rho = 0.23, P = 0.3364). Blood-based brain-derived tau showed equivalent diagnostic performance as CSF total-tau and CSF brain-derived tau to separate biomarker-positive Alzheimer’s disease participants from biomarker-negative controls. Furthermore, plasma brain-derived tau accurately distinguished autopsy-confirmed Alzheimer’s disease from other neurodegenerative diseases (area under the curve = 86.4%) while neurofilament light did not (area under the curve = 54.3%). These performances were independent of the presence of concomitant pathologies. Plasma brain-derived tau (rho = 0.52–0.67, P = 0.003), but not neurofilament light (rho = −0.14–0.17, P = 0.501), was associated with global and regional amyloid plaque and neurofibrillary tangle counts. These results were further verified in two memory clinic cohorts where serum brain-derived tau differentiated Alzheimer’s disease from a range of other neurodegenerative disorders, including frontotemporal lobar degeneration and atypical parkinsonian disorders (area under the curve up to 99.6%). Notably, plasma/serum brain-derived tau correlated with neurofilament light only in Alzheimer’s disease but not in the other neurodegenerative diseases. Across cohorts, plasma/serum brain-derived tau was associated with CSF and plasma AT(N) biomarkers and cognitive function.Brain-derived tau is a new blood-based biomarker that outperforms plasma total-tau and, unlike neurofilament light, shows specificity to Alzheimer’s disease-type neurodegeneration. Thus, brain-derived tau demonstrates potential to complete the AT(N) scheme in blood, and will be useful to evaluate Alzheimer’s disease-dependent neurodegenerative processes for clinical and research purposes.

The possibility to generalize our understandings on treatments and assessments to both familial frontotemporal dementia (f-FTD) and sporadic FTD (s-FTD) is a fundamental perspective for the near future, considering the constant advancement in potential disease-modifying therapies that target particular genetic forms of FTD. We aimed to investigate differences in clinical features, cerebrospinal fluid (CSF), and blood-based biomarkers between f-FTD and s-FTD.In this longitudinal cohort study, we evaluated a consecutive sample of symptomatic FTD patients, classified as f-FTD and s-FTD according to Goldman scores (GS). All patients underwent clinical, behavioral, and neuropsychiatric symptom assessment, CSF biomarkers and serum neurofilament light (NfL) analysis, and brain atrophy evaluation with magnetic resonance imaging.Of 570 patients with FTD, 123 were classified as f-FTD, and 447 as s-FTD. In the f-FTD group, 95 had a pathogenic FTD mutation while 28 were classified as GS = 1 or 2; of the s-FTD group, 133 were classified as GS = 3 and 314 with GS = 4. f-FTD and s-FTD cases showed comparable demographic features, except for younger age at disease onset, age at diagnosis, and higher years of education in the f-FTD group (allf-FTD and s-FTD are very similar clinical entities, but with different biological mechanisms, and different rates of progression. The parallel characterization of both f-FTD and s-FTD will improve our understanding of the disease, and aid in designing future clinical trials for both genetic and sporadic forms of FTD.Do clinical features and biomarkers differ between patients with familial frontotemporal dementia (f-FTD) and sporadic FTD (s-FTD)?In this cohort study of 570 patients with FTD, f-FTD and s-FTD share similar demographic features, but with younger age at disease onset and diagnosis in the f-FTD group.f-FTD showed higher serum neurofilament light concentrations, greater brain damage, and shorter survival, compared to s-FTD.f-FTD and s-FTD are very similar clinical entities, but with different cognitive reserve mechanisms and different rates of progression.

Purpose: We aim to report the quality of accuracy studies investigating the utility of [18F]fluorodeoxyglucose (FDG)-PET in supporting the diagnosis of prodromal Alzheimer’s Disease (AD), frontotemporal lobar degeneration (FTLD) and prodromal dementia with Lewy bodies (DLB) in mild cognitive impairment (MCI) subjects, and the corresponding recommendations made by a panel of experts. Methods: Seven panellist, four from the European Association of Nuclear Medicine, and three from the European Academy of Neurology, produced recommendations taking into consideration the incremental value of FDG-PET, as added on clinical-neuropsychological examination, to ascertain the aetiology of MCI (AD, FTLD or DLB). A literature search using harmonized population, intervention, comparison, and outcome (PICO) strings was performed, and an evidence assessment consistent with the European Federation of Neurological Societies guidance was provided. The consensual recommendation was achieved based on Delphi rounds. Results: Fifty-four papers reported the comparison of interest. The selected papers allowed the identification of FDG patterns that characterized MCI due to AD, FTLD and DLB. While clinical outcome studies supporting the diagnosis of MCI due to AD showed varying accuracies (ranging from 58 to 100%) and varying areas under the receiver-operator characteristic curves (0.66 to 0.97), no respective data were identified for MCI due to FTLD or for MCI due to DLB. However, the high negative predictive value of FDG-PET and the existence of different disease-specific patterns of hypometabolism support the consensus recommendations for the clinical use of this imaging technique in MCI subjects. Conclusions: FDG-PET has clinical utility on a fair level of evidence in detecting MCI due to AD. Although promising also in detecting MCI due to FTLD and MCI due to DLB, more research is needed to ultimately judge the clinical utility of FDG-PET in these entities.