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Previous studies have suggested a relationship between the number of CAG triplet repeats in the HTT gene and neurodegenerative diseases not related to Huntington's disease (HD). This study seeks to investigate whether the number of CAG repeats of HTT is associated with the risk of developing certain tauopathies and its influence as a modulator of the clinical and neuropathological phenotype. Additionally, it aims to evaluate the potential of polyglutamine staining as a neuropathological screening. We genotyped the HTT gene CAG repeat number and APOE‐ℰ isoforms in a cohort of patients with neuropathological diagnoses of tauopathies (n=588), including 34 corticobasal degeneration (CBD), 98 progressive supranuclear palsy (PSP) and 456 Alzheimer's disease (AD). Furthermore, we genotyped a control group of 1070 patients, of whom 44 were neuropathologic controls. We identified significant differences in the number of patients with pathological HTT expansions in the CBD group (2.7%) and PSP group (3.2%) compared to control subjects (0.2%). A significant increase in the size of the HTT CAG repeats was found in the AD compared to the control group, influenced by the presence of the Apoliprotein E (APOE)‐ℰ4 isoform. Post‐mortem assessments uncovered tauopathy pathology with positive polyglutamine aggregates, with a slight predominance in the neostriatum for PSP and CBD cases and somewhat greater limbic involvement in the AD case. Our results indicated a link between HTT CAG repeat expansion with other non‐HD pathology, suggesting they could share common neurodegenerative pathways. These findings support that genetic or histological screening for HTT repeat expansions should be considered in tauopathies. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Neuroinflammation is a major contributor to the progression of frontotemporal dementia (FTD). Galectin‐3 (Gal‐3), a microglial activation regulator, holds promise as a therapeutic target and potential biomarker. Our study aimed to investigate Gal‐3 levels in patients with FTD and assess its diagnostic potential. METHODS: We examined Gal‐3 levels in brain, serum, and cerebrospinal fluid (CSF) samples of patients with FTD and controls. Multiple linear regressions between Gal‐3 levels and other FTD markers were explored. RESULTS: Gal‐3 levels were increased significantly in patients with FTD, mainly across brain tissue and CSF, compared to controls. Remarkably, Gal‐3 levels were higher in cases with tau pathology than TAR‐DNA Binding Protein 43 (TDP‐43) pathology. Only MAPT mutation carriers displayed increased Gal‐3 levels in CSF samples, which correlated with total tau and 14‐3‐3. DISCUSSION: Our findings underscore the potential of Gal‐3 as a diagnostic marker for FTD, particularly in MAPT cases, and highlights the relation of Gal‐3 with neuronal injury markers. [ABSTRACT FROM AUTHOR]

Background: Blood‐based biomarkers have recently emerged as minimally‐invasive, accessible and relatively inexpensive diagnostic and prognostic tools for people with cognitive impairment. Before being routinely implemented in clinical practice, the diagnostic performance of distinct commercially available assays should be studied in real‐world cohorts. We aimed to study and compare the diagnostic accuracy of different plasma biomarkers measured using two different assay platforms in a memory clinic cohort. Method: Participants were selected from a prospective memory clinic cohort; all had Alzheimer's disease (AD) CSF biomarkers performed. Plasma p‐tau181, GFAP and NfL were measured using Simoa (Quanterix), while plasma p‐tau181, Aβ1‐40 and Aβ1‐42 were quantified using Lumipulse G (Fujirebio). Clinical diagnoses were made according to published criteria, blinded to plasma biomarkers. Aβ status (‐/+) was defined by CSF Aβ concentration using local cutoffs. Result: One hundred and ten participants were included (mean age [standard deviation] 66 [7.8] years, 56% women). Diagnostic categories included 10 cognitively unimpaired controls, 24 with suspected non‐neurodegenerative cause of cognitive impairment (SND), 53 AD, 9 Lewy body disease (LBD, 4 Aβ+) and 14 frontotemporal dementia (FTD, 1 Aβ+). Plasma p‐tau181Quanterix and Aβ1‐42/Aβ1‐40 had the highest diagnostic accuracy (Figure 1) to discriminate between SND and AD (AUC [CI] 0.94 [0.89‐0.99] and 0.94 [0.85‐1]), followed by GFAP (0.93 [0.87‐0.99]), p‐tau181Fujirebio (0.90 [0.82‐0.98]) and Aβ1‐42 (0.71 [0.58‐0.85]). Plasma NfL performed the best to differentiate FTD from SND and AD (AUC 0.95 [0.88‐1] and 0.85 [0.71‐0.99], respectively). For Aβ status discrimination (Figure 2), p‐tau181Quanterix had an AUC [CI] of 0.91 [0.85‐0.96], followed by p‐tau181Fujirebio (0.86 [0.79‐0.93]), Aβ1‐42/Aβ1‐40 (0.85 [0.76‐0.93]) and GFAP (0.84 [0.77‐0.92]) with no statistically significant differences in AUCs. Balanced (Youden index) cut‐offs were calculated to study diagnostic performance, resulting in sensitivities of 79‐83%, specificities of 74‐83% and accuracies of 76‐83%. No combination of plasma biomarkers resulted in a significantly increased discriminative accuracy for Aβ status. All plasma biomarkers were moderately correlated with p‐tau181Quanterix (ρ = 0.40‐0.75, Figure 3). Conclusion: In our cohort, p‐tau181Quanterix, p‐tau181Fujirebio, Aβ1‐42/Aβ1‐40 and GFAP had a high diagnostic performance to discriminate CSF‐defined Aβ status. Plasma NfL identified individuals with FTD. Further studies comparing different plasma biomarkers are needed before implementation in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Little is known about the influence of age at onset (AAO) on plasma biomarkers and their use as prognostic biomarkers in Alzheimer's disease (AD). Method: We selected patients with AD diagnosis with available neuropsychological testing (NPS) at time of diagnosis and two years later, and plasma biomarkers at baseline. NPS battery included Free and Cued Selective Reminding Test (FCSRT), Landscape test (visual memory), Boston Naming Test, Semantic Fluency, BDAE auditory comprehension, Constructional and Ideomotor Praxis, Visual Object and Space Perception (VOSP) Incomplete Letters and Number Location subtests, Trail Making Test (TMT) A and B, Phonemic Fluency, and Digit Span Forward and Backward. NPS scores were compared by AAO: early‐onset AD (EOAD; <65 years) vs. late onset AD (LOAD; >65y). We analyzed plasma biomarkers phosphorilated‐tau181 (p‐tau181), total tau (t‐tau), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP) and ubiquitin C‐terminal hydrolase L1 (UCHL‐1) using the Quanterix Simoa p‐tau181 Advantage V2 and Neurology 4‐Plex A assays. Group comparisons and linear regressions adjusted by years of education (YOE) were performed in Stata/IC 16.1. Result: Forty‐two participants were included, 23 LOAD and 19 EOAD. Plasma p‐tau181 and GFAP levels were higher in LOAD (Table 1). We did not find differences between LOAD and EOAD in NPS tests at baseline or +2 years (Table 2). Plasma ptau‐181 was associated with progression in MMSE globally, VOSP‐Incomplete letters globally and in EOAD. Plasma NfL were associated to Boston Naming test globally and in EOAD, Semantic fluency test globally, VOSP‐incomplete letters in EOAD, and Free and Total Learning of FCSRT in LOAD. Plasma GFAP was associated to MMSE globally and in EOAD, Free learning of FCSRT in LOAD and VOSP‐Incomplete letters and number location globally. Plasma UCHL‐1 was associated to Semantic fluency test in LOAD (Table 3). Praxis and attention and executive function tests loss were not associated to plasma biomarkers. Conclusion: Plasma p‐tau18, NfL, GFAP and UCHL‐1 were associated to pogression in memory, language and visual tests. They were predominantly associated to memory loss in LOAD and language and visual function loss in EOAD. Results need to be interpreted cautiously due to small sample size. [ABSTRACT FROM AUTHOR]

Background: Plasma Neurofilament light chain (pNfL) is a promising biomarker to discriminate Frontotemporal dementia (FTD) from other diagnoses such as Alzheimer's disease (AD) or psychiatric disorders. Currently, the diagnostic criteria for FTD syndromes are structured hierarchically into "Possible", "Probable" and "Definite" levels depending on the degree of confidence set by biomarkers. We aim to study the diagnostic and prognostic values of pNfL in the different confidence levels of FTD diagnosis. Method: Patients fulfilling criteria for FTD were classified as "Possible", "Probable" or "Definite" FTD based on the current diagnostic criteria. pNfL levels were determined with SiMoA, and then compared to Control and AD groups, as well as within the different levels of confidence in the FTD diagnosis. Result: 187 subjects were included: 37 controls, 79 AD and 71 FTD (11 Possible, 49 Probable and 11 Definite). The FTD group showed higher concentrations of pNfL than the Control (p < 0.001, AUC: 0.817) and the AD groups (p < 0.001, AUC: 0.677) (Figure 1A and 1B). Within the FTD group, pNfL levels differed across the different diagnostic confidence levels (Figure 1C). Subjects with Probable and Definite FTD showed higher levels of pNfL than subjects with Possible FTD (p < 0.001 and p < 0.01 respectively). By contrast, the Possible FTD group did not show differences in pNfL concentrations with the control group. In that sense, the diagnostic value of pNfL varied according to the different grades of diagnostic confidence (Figure 1D), with cases with probable or definite FTD exhibiting an excellent AUC to distinguish from controls (AUC 0.860 and 0.908 respectively), but with no discrimination between possible FTD and controls (AUC 0.583). pNfL presented an excellent performance in the differentiation of structural or functional impairment in the neuroimage (AUC 0.94, and AUC 0.86 respectively) (Figure 2). Finally, higher baseline pNfL levels were associated with worse clinical progression in FTD cases (Figure 3). Conclusion: pNfL were higher in FTD patients compared to controls or AD patients. However, we found significant variation across the different confidence levels of FTD diagnosis. Finally, pNfL predicted neuroimage alterations and a worse clinical progression in FTD patients. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of early‐onset neurodegenerative dementias (<65 years) can represent a challenge due to their lower frequency respect to late‐onset dementias and atypical forms of presentation. Cognitive impairment has emerged as a frequent complaint after COVID‐19 infection. Method: We retrospectively reviewed (2016‐2021) the demographic and clinical data of the new referrals at our early onset dementia clinic (Hospital Clínic Barcelona). We used Fisher's Exact test and ANOVA in Stata/IC 16.1 to analyze differences between patients visited in 2021, 2020 and the period 2016‐2019. Result: We evaluated 296 patients in 2021, 104 in 2020 and 98 patients/year in 2016‐2019. In 2021, patients had an age at onset (AAO) of 50.1 years, lower than 2020 (53.4) and the period 2016‐2019 (53.0) (p<0.05). The percentage of women in 2021 (69.6%) was higher than 2020 (57.7) and 2016‐2019 (56.0) (p<0.05). Diagnostic delay was lower in 2021 (2.1 years) than 2020 (3.3) and 2016‐2019 (3.0) (p<0.05). No differences were found in Minimental (MMSE) scores (Table 1). In the period 2016‐2021, the number of neurodegenerative diseases (ND) remained steady, the number of subjective cognitive decline (SCD) decreased and the number of non neurodegenerative causes (NNC) experienced a large increase (Table 1), representing 77.7% of visits in 2021. We did not find differences in the type of ND diagnosis in each period (Figure 1A). ND subgroups did not show differences in AAO, sex or MMSE. In 2021, NND presented lower AAO, higher percentage of women, lower diagnostic delay (Figure 1B) and higher MMSE scores than previous years. No differences were found in the SCD group. Cognitive impairment after Covid‐19 accounted for 16.7% of NND in 2020 (n = 8, AAO 50.6 (11.8), 62.5% female, MMSE 26.8(2.3)) and 66.6% of NND in 2021 (n = 153, AAO 49,0 (10.0), 80.1% female, MMSE 27.8 (2.6)). Conclusion: In 2021 we visited approximately three times more patients than in 2016‐2020, among which we observed an increase in NND, mainly patients with cognitive impairment after Covid‐19. On contrast, we found a similar number of ND diagnosis and reduction in SCD. [ABSTRACT FROM AUTHOR]

Background: The application of blood‐based biomarkers for the identification of Alzheimer's disease (AD) and the development of novel digital technologies as cognitive screening tests are critical to moving toward a reliable, more accessible early diagnosis. Our aim was to evaluate the diagnostic performance of a machine learning‐based cognitive assessment known as Altoida's digital neuro‐signature (DNS) in patients with non‐degenerative mild cognitive impairment (ndMCI) and MCI due to AD (prodromal AD) and its association with CSF and plasma biomarkers. Method: Altoida's MCI‐DNS is a 10‐minute cognitive test battery evaluating activities of daily living via motoric and augmented reality tasks. The test consists of placing and finding virtual objects in a real environment and its final score is obtained by weighting multi‐modal digital data features, such as hands' micro‐movements, speed, reaction times, or navigation trajectories. We included 81 participants, classified according to their clinical status and CSF AD biomarker profile as: cognitively unimpaired controls, CTR (n = 10; age = 68.5±5.9; MMSE = 29.4±1.1), ndMCI (n = 25; age = 67.6±7.2; MMSE = 26.9±1.9) and prodromal AD (n = 46; age = 70.8±4.9; MMSE = 24.3±3.3). We further investigated a subsample of participants classified according to their plasma pTau181 levels as measured by SiMoA [cutoff = 1.37 pg/mL (Sarto et al., 2022)]: pTau181 negative (n = 27; age = 68.5±5.9; MMSE = 26.9±2.7) or pTau181 positive (n = 30; age = 70.3±5.5; MMSE = 24.1±3.7). Result: Significant differences were found in MCI‐DNS scores between CTR group and ndMCI (F = 23.5; p<0.001) and prodromal AD (F = 114.4; p<0.001) groups. Also, ndMCI showed higher MCI‐DNS scores than the prodromal AD group (F = 4.53; p<0.05, Fig. 1). ROC curves showed an excellent diagnostic accuracy of the MCI‐DNS in the discrimination between CTR vs. ndMCI (AUC = 0.879) and CTR vs. prodromal AD (AUC = 0.975) (Fig. 1). Further analyses showed differences in MCI‐DNS scores between CSF Aβ42 negative and CSF Aβ42 positive (F = 18.9; p<0.001; Fig. 2), as well as between plasma pTau181 negative and plasma pTau181 positive (F = 6.16; p<0.01; Fig. 2). Finally, MCI DNS scores significantly correlated with CSF Aβ42, CSF Aβ42/pTau ratio, CSF neurofilament‐light chain (NfL) and plasma pTau181 concentrations (Fig. 3). Conclusion: Altoida's MCI‐DNS test allows excellent discrimination between CTR and patients with MCI. MCI‐DNS scores significantly correlate with CSF AD core biomarkers, biomarkers of neurodegeneration and blood‐based biomarkers (i.e., plasma pTau181). [ABSTRACT FROM AUTHOR]

Background: Neuropsychiatric symptoms, including sleep‐wake disturbances, are more common in Early‐onset Alzheimer's disease (EOAD) than in Late‐onset AD (LOAD)(Falgàs, EurJNeurol2022). The pattern of tau‐related degeneration of wake and sleep‐promoting neurons determine sleep‐wake profiles in neurodegenerative disorders (Oh, JAMANeurol2022). We hypothesize that distinct patterns of noradrenergic (locus coeruleus‐LC) and orexigenic (hypothalamus‐HT) degeneration contribute for the differential sleep‐wake patterns between EOAD and LOAD. Method: A group of 21 participants (7 EOAD, 18 LOAD) with a diagnosis of AD confirmed by cerebrospinal fluid biomarkers (CSF) were recruited from Hospital Clínic de Barcelona. Participants underwent sleep questionnaires (Pittsburg Sleep Quality Inventory‐PSQI and Epworth Sleepiness Scale‐ESS), 2‐week actigraphy (MotionWatch8, CamnTech) and 3T‐neuromelanin‐sensitive MRI to measure locus coeruleus (LC) and hypothalamus (HT) volumes. Sleep, napping, and circadian parameters were obtained (MotionWare). Result: The preliminary results showed no differences in sex (71vs.61% women) or disease stage (CDR 0.5: 85% vs.72%). The amnestic phenotype was prevalent (100 vs.78%). EOAD had longer daytime napping (93.2±74 vs. 58.2±28min, p<0.05), later fell asleep times (0:42am vs. 11:30pm, p<0.05) and higher central phase measure (4.4±0.5 vs. 3.5±1 h, p<0.05, midpoint between fell asleep and wake‐up) than LOAD. Daytime napping correlated with ESS (r = 0.53, p<0.01). Other parameters such as actual sleep time, sleep efficiency, sleep latency, or fragmentation index showed no differences. PSQI did not correlate to any measures. LC‐volumes were lower in EOAD than in LOAD (24.4±7mm3 vs. 33.3±6 p<0.01). In contrast, HT‐ trended towards higher volumes in EOAD (416.8±38 vs. 392.9±36, p = 0.09), being inversely correlated to the age at onset (r = ‐0.47, p<0.05). The central phase measure was inversely correlated to LC‐volumes (r = ‐0.47, p<0.05) but not to HT. Further analyses with increased sample size, CSF noradrenaline and orexin will be performed. Conclusion: Greater daytime sleepiness and circadian dysfunction could be main differing traits regarding sleep‐wake patterns between EOAD and LOAD. An opposite pattern of degeneration within wake‐promoting systems consisting of higher degeneration of the LC‐noradrenergic system and relative preservation of the HT‐orexigenic in EOAD in contrast to LOAD might underlie differing sleep‐wake phenotypes. Age‐related hypothalamic volume loss can be adding to AD driven loss resulting in higher volumes in EOAD. [ABSTRACT FROM AUTHOR]

Background: One of the clinical problems for biomarkers' clinical use is the ability to differentiate between Alzheimer's disease (AD), frontotemporal dementia (FTD), and healthy subjects (CTR). This clearly challenges diagnosis and prognosis. We implemented a ML algorithm that provides individual probabilistic diagnoses for these dementias based on magnetic resonance imaging (MRI) and we correlated the results with biochemical markers. Method: We studied 3T‐T1w MRI of 432 subjects. A subset of these participants had cerebrospinal fluid (CSF) and plasma biomarkers (Table 1). We obtained regional subcortical gray matter volumes and cortical thickness measures using Freesurfer. We implemented a calibrated classifier with a Support Vector Machine with only the MRI data. We tested paired‐wise classification and classification across the 3 groups. We obtained individual probabilities associated with group correspondence. We studied the correlation between these probabilities and CSF and plasma biomarkers. For this, we subdivided the groups into true‐group (subjects with classification according to clinical diagnosis) and false‐group (subjects which did not coincide with clinical diagnosis). Finally, we implemented a permutation test to find the importance of each region in the classification. Result: We obtained accuracies of 90.7 ± 6.7% in the CTR vs AD classification, 88.6 ± 4.5% for CTR vs FTD, 79.3 ± 8.8% for AD vs FTD, and 79.9 ± 5.1% when discriminating the 3 groups. We obtained a significant positive correlation for plasma p‐tau181 for the false‐AD in the comparison AD vs CTR (Figure 1). The correlation of the false‐CTR was significantly positive for the CSF and plasma NfL. Finally, in the AD vs FTD, the true‐FTD had a significant negative correlation with CSF NfL. The other biochemical biomarkers did not provide additional information. The most important regions for classification are shown in Figure 2. Conclusion: The ML algorithm gave high accuracies. Within wrongly classified AD patients, probabilities correlated positively with plasma p‐tau181, suggesting hidden pathological processes associated with subjects clinically classified as CTR. Finally, the group probability within well‐classified FTD patients in comparison with AD negatively correlated with CSF NfL. We suggest that this approach can be used as a tool to try to develop personalized diagnoses. [ABSTRACT FROM AUTHOR]

Background: In healthy ageing, there is evidence of sex differences in vulnerability of hippocampal subfields to volume loss. However, this has not been investigated in early‐onset Alzheimer's disease (<65 years; EOAD). Method: We included 106 subjects: 62 EOAD (A+T+N+, MMSE>15) and 44 healthy controls (HC; A‐T‐N‐) that underwent lumbar puncture for analysis of AD biomarkers, 3T‐MRI scan and neuropsychological assessment. Hippocampal subfield segmentation was performed using T1‐weighted images and Freesurfer 6.0. Volume was adjusted by intracranial volume. Adjusted linear models were used to analyze differences between EOAD and HC and differences between sexes. We calculated Cohen's d as a measure of the effect size of volume change by sex, restricted to volume differences between EOAD and HC. In EOAD, we used linear models adjusted by age and education to investigate the association of volume loss with 18 cognition z‐scores. Results were adjusted using Bonferroni correction for multiple comparisons. Result: There were no demographic differences across groups. APOEε4 carriers were higher in EOAD‐female/EOAD‐male than HC‐female. EOAD‐female showed higher T‐Tau and P‐Tau levels than EOAD‐male (all p<0.05; Table1). Comparing EOAD vs. HC, differences were found in volume of all subfields and hippocampus (p<0.05, Bonferroni corrected), except for bilateral parasubiculum and right cornu ammonis (CA) 2/3. No differences were found between EOAD‐female and EOAD‐male (p>0.05). When compared to HC of the same sex, EOAD‐female showed differences in the same regions as the whole sample, while EOAD‐male showed differences in bilateral hippocampal tail and left presubiculum and hippocampus (all p<0.05, Bonferroni corrected, Figure 1). We observed larger effect sizes than in women in these regions, except for left hippocampus (Figure 2). In EOAD, higher volume in left CA2/3 predicted higher memory z‐scores, including free and total learning and delayed total recall (p<0.05 Bonferroni corrected; Figure 3). No associations were found in EOAD‐female nor EOAD‐male. Conclusion: In EOAD, the pattern of volume loss in hippocampal subfields was similar between sexes. However, females showed more marked differences from HC, except for bilateral hippocampal tail and left presubiculum. Further studies are necessary to elucidate the existence of sex differences in EOAD and their implication for cognitive impairment. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T‐T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2‐year follow‐up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross‐sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross‐sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross‐sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross‐sectional and longitudinal data. [ABSTRACT FROM AUTHOR]

Background and purpose: How the APOE genotype can differentially affect cortical and subcortical memory structures in biomarker‐confirmed early‐onset (EOAD) and late‐onset (LOAD) Alzheimer's disease (AD) was assessed. Method: Eighty‐seven cerebrospinal fluid (CSF) biomarker‐confirmed AD patients were classified according to their APOE genotype and age at onset. 28 were EOAD APOE4 carriers (+EOAD), 21 EOAD APOE4 non‐carriers (–EOAD), 23 LOAD APOE4 carriers (+LOAD) and 15 LOAD APOE4 non‐carriers (–LOAD). Grey matter (GM) volume differences were analyzed using voxel‐based morphometry in Papez circuit regions. Multiple regression analyses were performed to determine the relation between GM volume loss and cognition. Results: Significantly more mammillary body atrophy in +EOAD compared to –EOAD is reported. The medial temporal and posterior cingulate cortex showed less GM in +LOAD compared to –LOAD. Medial temporal GM volume loss was also found in +EOAD compared to –LOAD. With an exception for +EOAD, medial temporal GM was strongly associated with episodic memory in the three groups, whilst posterior cingulate cortex GM volume was more related with visuospatial abilities. Visuospatial abilities and episodic memory were also associated with the anterior thalamic nucleus in –LOAD. Conclusions: Our results show that the APOE genotype has a significant effect on GM integrity as a function of age of disease onset. Specifically, whilst LOAD APOE4 genotype is mostly associated with increased medial temporal and parietal atrophy compared to –LOAD, for EOAD APOE4 might have a more specific effect on subcortical (mammillary body) structures. The findings suggest that APOE genotype needs to be taken into account when classifying patients by age at onset. [ABSTRACT FROM AUTHOR]

Background: Posterior cortical atrophy (PCA) is a clinically defined syndrome characterized by impairment in higher‐order visual processing. The underlying pathology in PCA is most commonly Alzheimer's disease (AD), but large‐scale biomarker and neuropathological studies are lacking. In this ongoing project we aim to describe demographic, clinical, biomarker and neuropathological correlates of PCA in a large‐scale international cohort. Method: We contacted 55 research centers conducting PCA research identified in a literature review (n=1353 papers) as well as additional sites recruited through the ISTAART Atypical AD Professional Interest Group (n=7 sites) requesting deidentified, single‐subject data from PCA patients (published and unpublished). Inclusion criteria were: 1. clinical diagnosis of PCA, 2. availability of AD biomarkers (PET or CSF) or 3. availability of autopsy diagnosis. Single‐subject demographic, clinical, fluid, neuroimaging and neuropathological data were collected. Result: As of January 2022, we have collected individual patient data from 390 participants evaluated at 14 sites in 10 countries (Table 1). In the preliminary sample, mean age at symptom onset was 63.1 ± 8.8 years, 62.3% of participants were female, and 78.3% presented with a "PCA‐pure" clinical syndrome by Crutch 2017 diagnostic criteria. APOE4 genotype was present in 45.6% (n=125). Preliminary results show that 82.9% (n=270) display predominant MRI atrophy and 91.9% (n=185) predominant FDG hypometabolism in posterior cortical regions. CSF amyloid markers were positive in 80.2% participants (n=187), while CSF phosphorylated tau markers were positive in 61.4% (n=184). Amyloid PET was positive in 85.2% (n=129) while tau PET was only available in 65 patients (positive in all, and all were amyloid positive). At autopsy (n=36, data from 4 centers), high AD neuropathologic changes were found in all but one patient, who had primary frontotemporal lobar degeneration with TDP‐43 type A pathology. Lewy bodies, argyrophilic grains and cerebral amyloid angiopathy were common co‐pathologies (Figure 1). Conclusion: In a large international cohort, PCA is strongly associated with positive AD biomarkers and neuropathology. Data collection is ongoing, and we further aim to identify clinical features associated with non‐AD underlying causes of PCA. [ABSTRACT FROM AUTHOR]

Objectives: Early‐ and late‐onset Alzheimer's disease (EOAD and LOAD) share the same neuropathological traits but show distinct cognitive features. We aimed to explore baseline and longitudinal outcomes of global and domain‐specific cognitive function in a well characterized cohort of patients with a biomarker‐based diagnosis. Methods: In this retrospective cohort study, 195 participants were included and classified according to their age, clinical status, and CSF AD biomarker profile: 89 EOAD, 37 LOAD, 46 young healthy controls (age ≤ 65 years), and 23 old healthy controls (>65 years). All subjects underwent clinical and neuropsychological assessment, neuroimaging, APOE genotyping and lumbar puncture. Results: We found distinct neuropsychological profiles between EOAD and LOAD at the time of diagnosis. Both groups showed similar performances on memory and language domains, but the EOAD patients displayed worsened deficits in visual perception, praxis, and executive tasks (p < 0.05). Longitudinally, cognitive decline in EOAD was more pronounced than LOAD in the global outcomes at the expense of these non‐amnestic domains. We found that years of education significantly influenced the decline in most of the neuropsychological tests. Besides, the APOE ε4 status showed a significant effect on the decline of memory‐related tasks within the EOAD cohort (p < 0.05). Interpretation: Age of onset is a main factor shaping the cognitive trajectories in AD patients, with younger age driving to a steeper decline of the non‐memory domains. Years of education are related to a transversal decline in all cognitive domains and APOE ε4 status to a specific decline in memory performance in EOAD. [ABSTRACT FROM AUTHOR]

Background and purpose: Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early‐onset AD (EOAD; <65 years) is scarce. Methods: We included 62 EOAD patients and 44 healthy controls (HCs) with core AD cerebrospinal fluid (CSF) biomarkers, neurofilament light chain levels, neuropsychological assessment, and 3‐T magnetic resonance imaging. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using FreeSurfer. Adjusted linear models were used to analyze sex‐differences and the relationship between atrophy and cognition. Results: Compared to same‐sex HCs, female EOAD subjects showed greater cognitive impairment and broader atrophy burden than male EOAD subjects. In a direct female‐EOAD versus male‐EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female EOAD than in male EOAD subjects. Greater atrophy was associated with worse cognition in female EOAD subjects. Conclusions: At diagnosis, there are sex differences in the pattern of cognitive impairment, atrophy burden, and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD. [ABSTRACT FROM AUTHOR]

Background: Currently used biomarkers for the differential diagnosis of cognitive impairment are expensive and/or relatively invasive, limiting their availability to the general population. Blood protein biomarkers have showed promising results for screening, differential diagnosis, and prognosis. We aimed to study the diagnostic performance of plasma p‐tau181 in a daily clinical practice, prospective memory clinic cohort. Method: All patients referred for a first clinical evaluation with suspected cognitive impairment between January 1st, 2020 and March 30th, 2021, were invited to participate in the study. Plasma p‐tau181 was measured using SIMOA technology (Quanterix). Clinical diagnoses were made following current diagnostic criteria and blinded to plasma p‐tau181 results. Result: A total of 232 participants were recruited (mean age 69y, mean MMSE 24), including 25 cognitively unimpaired (CU) controls (mean age 67y, MMSE 28). Clinical diagnoses were AD (82 subjects, 43 of them with prodromal AD [CDR = 0.5]), 83 non‐neurodegenerative cognitive impairment (non‐ND, 75 of them CDR = 0.5), 22 frontotemporal dementia (FTD) and 20 Lewy body disease (LBD). Plasma p‐tau181 levels were statistically higher in AD (mean 2.39 pg/mL) compared with CU (mean 1.09 pg/mL), non‐ND (mean 1.43 pg/mL), FTD (mean 1.69 pg/mL) and LBD (mean 1.64 pg/mL) with a relatively good diagnostic performance for the differential diagnosis between AD and CU, non‐ND, LBD and FTD (AUC of 0.89, 0.80, 0.73 and 0.71, respectively). 128 subjects (55% of the cohort) had specific AD biomarkers (CSF or PET) available. In this subgroup, p‐tau181 differentiated AD from CU and non‐ND (AUC 0.91 and 0.92, respectively) and prodromal AD from CDR = 0.5 non‐ND participants (2.32 vs 1.02 pg/mL, p<0.001, AUC 0.90). Plasma p‐tau181 discriminated between a positive and negative amyloid beta status (defined by CSF/PET) with an AUC of 0.87 and AD subjects from those with a clinical diagnosis of LBD and FTD who had a negative amyloid beta status (AUC of 0.94 and 0.86, respectively). Plasma p‐tau181 correlated with CSF p‐tau181 (rs = 0.48, p<0.001). Conclusion: In our cohort of everyday clinical practice, plasma p‐tau181 is an accurate biomarker for predicting the AD pathophysiological process and discriminating AD from other neurodegenerative and non‐neurodegenerative causes of cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: The behavioral variant of frontotemporal dementia (bvFTD) is characterized by progressive behavioral change along with social, cognitive, and functional deterioration. In contrast Alzheimer´s disease, patients with bvFTD show an anterior pattern of neurodegeneration with selective involvement of the frontotemporal cortex. Biological sex is an increasingly recognized factor driving clinical heterogeneity in Alzheimer's disease, but its role in bvFTD is unknown. Method: In this multicenter study, we aimed to characterize the impact of sex on clinical presentation, longitudinal decline, and cortical thickness in bvFTD. We included 216 patients with bvFTD and 235 controls with MRI. We compared the clinical characteristics and cortical thickness between men and women with bvFTD and controls. We further explored the existence of sex differences in cognitive reserve by following the residuals approach to operationalize reserve as having better cognition and fewer behavioral changes than predicted by cortical thickness (a proxy of pathology). To do this, we modeled the relationship between cognition or behavior with cortical thickness and used each individual's residual as a proxy of their reserve. Result: At diagnosis, women with bvFTD showed greater atrophy burden in frontotemporal regions compared to men despite very subtle differences in cognitive and functional impairment, progression, and survival. For a similar amount of atrophy, women demonstrated better‐than‐expected scores on executive function and less apathy, sleep, and appetite changes than men. Conclusion: Our findings suggest that women might have greater behavioral and executive reserve than men. Future studies should examine the specific mechanisms underlying the observed differences and consider biological sex for the design of research studies and clinical trials in bvFTD and other frontotemporal lobar degeneration syndromes. [ABSTRACT FROM AUTHOR]

Background: Despite previous studies establishing cognitive impairment as a major complaint in post‐acute COVID‐19 syndrome (PACS), a deeper understanding of the neuropsychological features and underlying causes is needed. We aimed to characterize the cognitive profile of patients affected with cognitive PACS and the influence of biological and psychological factors. Method: We performed a prospective single‐center study. We included participants with confirmed SARS‐CoV‐2 infection and long‐term symptoms ≥ 8 weeks after onset who were referred to our unit because of cognitive complaints. All participants completed a comprehensive neuropsychological battery (NPS) and questionnaires assessing depression (Beck Depression Inventory), anxiety (Beck Anxiety Inventory), apathy (Starkstein Apathy Scale) and fatigue (Multidimensional Fatigue Inventory) at baseline and +1, +3 and +6 months. We collected blood samples and cerebrospinal fluid (CSF) to obtain biochemical and immunological profiles. Group comparisons, correlations and Principal component analysis (PCA) were performed. Longitudinal analyses are ongoing. Result: Forty‐nine participants were included (79.6% female, mean age 50.1 (SD 7.9). At the time of assessment, they presented multiple symptoms other than cognitive complaints (88% fatigue, 61% headache, 63% dyspnea, and 10% fever). The NPS showed that executive functions were the most affected (up to 29% of the sample had at least one test altered), followed by memory (at least one test altered in 25%) (Figure 1). On the contrary, language and praxis were preserved. Participants presented with anxiety symptoms (minimal 8.7%, mild in 34.8%, moderate 26.1%, severe 30.4%), depressive symptoms (none 34.8%, mild 26.1%, borderline clinical depression 23.9%, moderate 8.7%, severe 6.5%), and clinically relevant apathy in 64.4%. The sample presented a mean score of total fatigue of 58 (min 48, max 68), (scores 20‐100). Fever and or moderate/severe anxiety were associated with lower scores in some memory and executive functions subtests (Figure 2). Most of the variability in the sample was explained by executive functions subtests (PCA, Figure 3). Patients presented increased levels of interleukins (IL) IL‐1b, IL‐17a and IL‐18 in CSF compared to controls. Conclusion: Cognitive PACS predominantly affected executive functions and memory. Fever and moderate/severe anxiety were associated with worse cognitive outcomes. Several inflammatory markers were altered in cognitive PACS. [ABSTRACT FROM AUTHOR]

Background: Post‐acute Covid‐19 syndrome (PACS) frequently refers to cognitive complaints. It is not yet clear whether there is an association between cognitive symptoms with brain changes or neuropsychiatric symptoms. Our aims are 1) to study cross‐sectional and longitudinal MRI brain measures in a cohort of PACS and 2) their association with cognitive performance and mood disturbances. Method: We performed a prospective single‐center study with 3T‐T1w MRI of 49 PACS patients at a cross‐sectional level. These participants had confirmed SARS‐CoV2 infection, ≥ 8 weeks after symptoms onset and cognitive complaints. All participants completed a comprehensive neuropsychological battery (NPS) and questionnaires assessing depression, anxiety, and subjective cognitive complaints (SCD). We obtained global MRI measures (e.g; gray and white matter volumes and mean cortical thickness) with FreeSurfer. We measured correlations of global MRI measures with SCD, memory and executive function outcomes, anxiety, and depression. All analyses were corrected for multiple comparisons. 44 PACS subjects had a 6‐month follow‐up MRI: in these, we performed longitudinal analyses with Generalized Linear Mixed‐Effects Models to study changes between visits in global MRI measures. Result: Demographics are shown in Table 1. We did not find any correlation between clinical outcomes (SCD, anxiety, depression) and MRI findings. Visual memory (Rey figure's recall) and cognitive interference inhibition and processing speed ((Stroop's color‐word condition) were positively correlated with global gray and white matter volume measures (Figure 1). We did not identify changes in global MRI measures at 6 months in PACS participants. Conclusion: In PACS, worse visual memory and executive function, but not other clinical outcomes, were associated with lower global structural MRI indexes. We did not observe global longitudinal changes in MRI. [ABSTRACT FROM AUTHOR]

Background: Lewy Body Dementia (LBD) is the second most common neurodegenerative dementia. To date, no validated biochemical marker is available to support clinical diagnosis. The development of the Real‐Time Quaking‐Induced Conversion (RT‐QuIC) assay for detecting alpha‐synuclein (aSyn) seeds in biological samples can be a sensitive biomarker specific for the diagnosis easily applicable in a clinical setting. We aimed to describe the diagnostic performance of RT‐QuIC aSyn assay in cerebrospinal fluid (CSF) to diagnose LBD in a clinical cohort with cognitive impairment. Method: A cohort of subjects with cognitive impairment (neurodegenerative and non‐neurodegenerative) with available CSF sample at the moment of first evaluation was selected by convenience sample in our database. Subjects had clinical follow‐ups ranging from 6 months to 12 years and current clinical diagnosis according to established consensus criteria. The diagnostic performance of RT‐QuIC aSyn for the diagnosis of LBD were evaluated. Result: The test was evaluated in 155 subjects (age 65 years (SD 11), MMSE 24 (SD 4.5), 56% male) with the following clinical diagnoses: LBD (n = 40), Alzheimer's disease (AD) (n = 73)(all with compatible CSF profile), frontotemporal dementia (FTD) (n = 7), non‐neurodegenerative mild cognitive impairment (MCI) (n = 21), other neurodegenerative diagnoses (n = 12) and healthy controls (n = 2). aSyn was detected in 33/40 (83%) LBD patients, 7/73 (10%) AD, 0/7 FTD patients, 0/21 MCI patients, 0/12 patients with other neurodegenerative diseases and 0/2 healthy controls. Only 3/7 (42%) LBD subjects with a negative RT‐QuIC asyn fulfilled criteria for LBD (established or prodromal) at the moment of first evaluation as compared with 23/33 (69%) of LBD with positive RTQuIC suggesting a more initial disease in the negative group at the moment of CSF sampling. The sensitivity and specificity of the assay were 83% and 94% respectively for the diagnosis of LBD, with a PPV of 83% and a NPV of 94%. Conclusion: Detection of αSyn seeds by RT‐QuIC has a good performance in identifying patients with LBD in a clinical cohort of cognitively impaired subjects. The test also identifies aSyn co‐pathology in a subgroup of subjects diagnosed with AD. [ABSTRACT FROM AUTHOR]

The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at‐genetic‐risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal‐centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches. [ABSTRACT FROM AUTHOR]

Cognitive impairment and behavioral changes in amyotrophic lateral sclerosis (ALS) are now recognized as part of the disease. Whether it is solely related to the extent of TDP‐43 pathology is currently unclear. We aim to evaluate the influence of age, genetics, neuropathological features, and concomitant pathologies on cognitive impairment in ALS patients. We analyzed a postmortem series of 104 ALS patients and retrospectively reviewed clinical and neuropathological data. We assessed the burden and extent of concomitant pathologies, the role of APOE ε4 and mutations, and correlated these findings with cognitive status. We performed a logistic regression model to identify which pathologies are related to cognitive impairment. Cognitive decline was recorded in 38.5% of the subjects. Neuropathological features of frontotemporal lobar degeneration (FTLD) were found in 32.7%, explaining most, but not all, cases with cognitive impairment. Extent of TDP‐43 pathology and the presence of hippocampal sclerosis were associated with cognitive impairment. Mutation carriers presented a higher burden of TDP‐43 pathology and FTLD more frequently than sporadic cases. Most cases (89.4%) presented some degree of concomitant pathologies. The presence of concomitant pathologies was associated with older age at death. FTLD, but also Alzheimer's disease, were the predominant underlying pathologies explaining the cognitive impairment in ALS patients. In sum, FTLD explained the presence of cognitive decline in most but not all ALS cases, while other non‐FTLD related findings can influence the cognitive status, particularly in older age groups. [ABSTRACT FROM AUTHOR]

Background: The ongoing COVID‐19 pandemic and related care policies have affected dementia patients. The characteristics of early‐onset dementia (EOD, <65 years) patients in 2020 may provide insights on how to rearrange the provision of care. Method: We retrospectively reviewed, from 2016 to 2020, the demographic and clinical data of the new referrals at our EOD clinic (Hospital Clínic Barcelona). We used Fisher's Exact test and Mann–Whitney U test in R4.0.2 (http://www.R‐project.org/) to analyze differences between 2020 and the period 2016‐2019. Result: In 2020, we did not visit any new referral from 15th march to 31th may. We evaluated 104 patients in 2020 and 392 patients in 2016‐2019 (mean=98(SD=11.8) patients/year). No differences were found in age at onset (AAO), sex, diagnostic delay and MMSE score (Table1). Significant differences were found in the diagnoses obtained in each period (p<0.000005, Figure1A). In 2020, 19.2% of the patients were diagnosed with neurodegenerative diseases (ND), 48.1% with non‐neurodegenerative diseases (NND) and 32.7% with subjective cognitive decline (SCD). On contrast, in 2016‐2019, 26% of the patients were diagnosed with ND, 22.2% with NND and 51.8% with SCD. Compared to 2016‐2019, ND, but not SCD or NND, presented longer diagnostic delay in 2020 (p<0.0005, Figure1B). ND, NND and SCD did not show differences between periods in AAO, sex or MMSE. We did not find differences in the type of ND in each period (Figure1A). Compared to 2016‐2019, Frontotemporal Lobar Degeneration (FTLD) presented longer diagnostic delay in 2020 (p<0.005, Figure1B) while ND subgroups did not show differences in AAO, sex or MMSE. Cognitive disturbances in recovered COVID‐19 patients accounted for 16% of NND in 2020 [N=8, AAO 50.63(12), 63% female, MMSE 26.8(2.3)]. Conclusion: In 2020, albeit we were forced to stop our normal activity during 2.5 months, we visited a similar number of patients among which we observed an increase in NND, including cognitive disturbances in patients with recovered COVID‐19. On contrast, we found a reduction in SCD and, to a lesser extent, ND. ND showed a longer diagnostic delay in 2020 that mainly affected FTLD. Whether COVID‐19 pandemic entails a diagnostic delay in dementia patients must be confirmed in 2021. [ABSTRACT FROM AUTHOR]

Prior studies have described distinct patterns of brain gray matter and white matter alterations in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), as well as differences in their cerebrospinal fluid (CSF) biomarkers profiles. We aim to investigate the relationship between early‐onset AD (EOAD) and FTLD structural alterations and CSF biomarker levels. We included 138 subjects (64 EOAD, 26 FTLD, and 48 controls), all of them with a 3T MRI brain scan and CSF biomarkers available (the 42 amino acid‐long form of the amyloid‐beta protein [Aβ42], total‐tau protein [T‐tau], neurofilament light chain [NfL], neurogranin [Ng], and 14‐3‐3 levels). We used FreeSurfer and FSL to obtain cortical thickness (CTh) and fraction anisotropy (FA) maps. We studied group differences in CTh and FA and described the "AD signature" and "FTLD signature." We tested multiple regression models to find which CSF‐biomarkers better explained each disease neuroimaging signature. CTh and FA maps corresponding to the AD and FTLD signatures were in accordance with previous literature. Multiple regression analyses showed that the biomarkers that better explained CTh values within the AD signature were Aβ and 14‐3‐3; whereas NfL and 14‐3‐3 levels explained CTh values within the FTLD signature. Similarly, NfL levels explained FA values in the FTLD signature. Ng levels were not predictive in any of the models. Biochemical markers contribute differently to structural (CTh and FA) changes typical of AD and FTLD. [ABSTRACT FROM AUTHOR]

Introduction: Synaptic damage, axonal neurodegeneration, and neuroinflammation are common features in Alzheimer's disease (AD), frontotemporal dementia (FTD), and Creutzfeldt‐Jakob disease (CJD). Methods: Unicentric cohort of 353 participants included healthy control (HC) subjects, AD continuum stages, genetic AD and FTD, and FTD and CJD. We measured cerebrospinal fluid neurofilament light (NF‐L), neurogranin (Ng), 14‐3‐3, and YKL‐40 proteins. Results: Biomarkers showed differences in HC subjects versus AD, FTD, and CJD. Disease groups differed between them except AD versus FTD for YKL‐40. Only NF‐L differed between all stages within the AD continuum. AD and FTD symptomatic mutation carriers presented differences with respect to HC subjects. Applying the AT(N) system, 96% subjects were positive for neurodegeneration if 14‐3‐3 was used, 94% if NF‐L was used, 62% if Ng was used, and 53% if YKL‐40 was used. Discussion: Biomarkers of synapse and neurodegeneration differentiate HC subjects from neurodegenerative dementias and between AD, FTD, and CJD. NF‐L and 14‐3‐3 performed similar to total tau when AT(N) system was applied. [ABSTRACT FROM AUTHOR]

Objective: We aimed to investigate the relationship between cerebrospinal fluid levels (CSF) of amyloid precursor protein (APP)‐derived peptides related to the amyloidogenic pathway, cortical thickness, neuropsychological performance, and cortical gene expression profiles in frontotemporal lobar degeneration (FTLD)‐related syndromes, Alzheimer's disease (AD), and healthy controls. Methods: We included 214 participants with CSF available recruited at two centers: 93 with FTLD‐related syndromes, 57 patients with AD, and 64 healthy controls. CSF levels of amyloid β (Aβ)1‐42, Aβ1‐40, Aβ1‐38, and soluble β fragment of APP (sAPPβ) were centrally analyzed. We compared CSF levels of APP‐derived peptides between groups and, we studied the correlation between CSF biomarkers, cortical thickness, and domain‐specific cognitive composites in each group. Then, we explored the relationship between cortical thickness, CSF levels of APP‐derived peptides, and regional gene expression profile using a brain‐wide regional gene expression data in combination with gene set enrichment analysis. Results: The CSF levels of Aβ1‐40, Aβ1‐38, and sAPPβ were lower in the FTLD‐related syndromes group than in the AD and healthy controls group. CSF levels of all APP‐derived peptides showed a positive correlation with cortical thickness and the executive cognitive composite in the FTLD‐related syndromes group but not in the healthy control or AD groups. In the cortical regions where we observed a significant association between cortical thickness and CSF levels of APP‐derived peptides, we found a reduced expression of genes related to synaptic function. Interpretation: APP‐derived peptides in CSF may reflect FTLD‐related neurodegeneration. This observation has important implications as Aβ1‐42 levels are considered an indirect biomarker of cerebral amyloidosis. [ABSTRACT FROM AUTHOR]

Background: The semi‐essential amino acid L‐arginine is metabolically versatile with a number of bioactive metabolites that are involved in synaptic plasticity, learning and memory, cerebral blood flow and microtubule stabilization processes. Altered brain arginine metabolism is evident in patients with late‐onset Alzheimer's disease and has been implicated in the disease pathogenesis. However, the brain arginine metabolic profile is yet to be investigated in early‐onset Alzheimer's disease (EOAD) and frontotemporal dementia (FTD). Method: Using high performance liquid chromatography and liquid chromatography/mass spectrometry, we measured the concentrations of L‐arginine and its downstream metabolites L‐citrulline, L‐ornithine, agmatine, glutamate, glutamine, GABA, putrescine, spermidine and spermine in the hippocampus and frontal and temporal cortices from EOAD (n = 27‐28/region), FTD (n = 27‐31/region) and control (n = 9‐17/region) cases. Result: There were significantly reduced levels of L‐ornithine in all three brain regions in both groups of dementia cases compared to the controls. Furthermore, the putrescine levels were significantly reduced in all brain regions examined in the FTD cases, and in the temporal cortex and hippocampus of the EOAD cases. In the hippocampus, there were increased L‐arginine levels, but decreased agmatine levels, in both the EOAD and FTD cases relative to the controls. Conclusion: This study demonstrates for the first time that brain arginine metabolism is altered similarly in both EOAD and FTD cases, and therefore suggests that altered L‐arginine metabolism may be a common mechanism involved in the neurodegenerative processes in these two early‐onset dementias. Further research is required to investigate the mechanisms for these metabolite changes and to explore the therapeutic potential of targeting L‐arginine metabolism in EOAD and FTD. [ABSTRACT FROM AUTHOR]

Mutations in the MAPT gene cause frontotemporal dementia with tau deposits. We report the novel p.P397S MAPT variant in eight subjects from five apparently nonrelated families suffering from frontotemporal dementia with autosomal dominant pattern of inheritance. In silico analysis reported conflicting evidence of pathogenicity. The segregation analysis support that this variant is likely pathogenic. The mean age at onset (61.4 years) and mean disease duration (13.9 years) of these subjects and their affected relatives were significantly higher compared with our series of p.P301L MAPT mutation carriers. These findings suggest that p.P397S variant could be a new MAPT mutation associated with a less aggressive phenotype than other MAPT mutations. [ABSTRACT FROM AUTHOR]

Background: Early‐onset Alzheimer's disease (EOAD, onset before 65 years), is the most common early‐onset neurodegenerative dementia. However, it still represents a diagnostic challenge especially when compared with late‐onset Alzheimer's disease (LOAD). Our aim was to describe and compare the neuropsychological presentation at diagnosis and its progression in patients with EOAD and LOAD. Methods: One‐hundred ninety‐five participants were included and classified accordingly to their CSF AD biomarker profile and clinical status: 46 young controls (Y‐CTR) aged below 65 years (age=57.4±4.7; MMSE=28.7±1.6), 23 old controls (O‐CTR) aged 65 or above (age=69.7±3.7; MMSE=28.0±1.4), 89 EOAD (age=59.8±4.2; MMSE=22.6±3.9) and 37 LOAD (age=74.5±4.8; MMSE=24.3±3.1). All subjects underwent clinical and neuropsychological assessment, APOE genotyping and lumbar puncture at baseline. Clinical and neuropsychological follow‐up was performed annually over 2 years. Results: No differences were found in terms of gender or years of education among the study groups. APOE4 was more frequent in EOAD and LOAD groups than controls (p<0.01). As expected, the control groups presented higher CSF Aβ42 and lower CSF tau and p‐tau levels than AD groups (Table 1). Baseline neuropsychological assessment (Figure 1) revealed differences between EOAD and LOAD in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function and working memory (p<0.05). When comparing controls and AD groups, EOAD performed significantly worse than Y‐CTR in all cognitive domains while LOAD showed differences with O‐CTR in memory, language and executive function but obtained a similar performance in ideomotor and constructional praxis, visuospatial function, attention and working memory. Longitudinally (Figure 2), no differences between EOAD and LOAD were observed on memory or language domains but EOAD showed higher decline in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function, attention (p<0.05) and working memory (p<0.05). Conclusions: Early‐ and late‐onset AD present distinct neuropsychological profiles at diagnosis with EOAD displaying higher difficulties in non‐memory domains and a more aggressive course. The present data may help on enhancing EOAD diagnosis and therefore on ensuring an earlier intervention in this population. [ABSTRACT FROM AUTHOR]

Background: Structural neuroimaging longitudinal studies in Alzheimer's disease (AD) have consistently defined a "cortical signature" of gray matter loss. Apparently, early‐onset AD (EOAD) has a greater density of amyloid, a more generalized atrophy and a more aggressive evolution than late‐onset AD (LOAD). We hypothesize EOAD would show pronounced longitudinal cortical atrophy, especially in associative areas like precuneus and in addition to temporal lobe loss. Methods: We investigate longitudinal 3T‐MRI structural data from the Alzheimer's disease Neuroimaging Initiative (ADNI) 2 cohort. We included patients aged ≤65 years with a baseline mild cognitive impairment (MCI) diagnosis. According to AD biomarkers at baseline, patients were divided into MCI due to AD with high likelihood (MCI‐AD) and MCI unlikely due to AD (MCI‐nonAD). We downloaded the summary of longitudinal measures for volume and cortical thickness. We used linear mixed effects in SPSS25 with data at baseline and month 24 to compare atrophy progression between groups. We focused on "AD's cortical signature", including entorhinal, inferior temporal, middle temporal, inferior parietal, fusiform areas, and also precuneus and posterior cingulate. In addition, we studied volume of hippocampus (HpV) and total subcortical supratentorial (SSupratV). We tested for group by time interactions and significance level was set at p<0.05, FDR corrected. Results: We included 22 MCI‐AD and 26 MCI‐nonAD patients. MMSE mean score was lower in MCI‐AD [Table1]. MCI‐AD had significant lower baseline Cth in precuneus, middle temporal and entorhinal and lower HpV. At group by time interactions, MCI‐AD showed significant greater CTh atrophy in middle temporal, enthorhinal and posterior cingulate, and higher volume decrease in HpV and SSupratV than MCI‐nonAD [Figure1]. Notably, the rest of areas studied were not significantly different at baseline or at group by time effects. Conclusion: Compared to MCI‐nonAD, MCI‐AD showed greater decline in only some of the areas previously defined as the cortical AD signature and in hippocampal volume and global subcortical volume. The study could be biased by the small sample size, by the age being close to LOAD and by no stratification by clinical symptoms. Further analyses are needed to understand AD atrophy progression pattern in relation to age at onset. [ABSTRACT FROM AUTHOR]

Background: Early‐onset Alzheimer's Disease presentations (EOAD, under 65) frequently present with atypical phenotypes and a more aggressive disease course with a higher burden of neuropsychiatric symptoms than late‐onset AD (LOAD). Current treatments for sleep and behavioral disturbances are still non‐specific, causing side effects (e.g., sedation, falls). Identifying the underlying changes driving behavioral differences between EOAD and LOAD is crucial to developing tailored treatment avenues. The noradrenergic locus coeruleus (LC), one of the first sites of tau deposition in AD, has been implicated in sleep‐wake patterns and mood regulation. We aim to test the hypothesis that the LC is more affected in EOAD than LOAD by comparing LC volume (neuromelanin‐sensitive MRI) and sleep‐behavioral symptoms in biomarker‐confirmed EOAD and LOAD cohorts. Method: Fifty‐four subjects with AD biomarker‐based diagnosis (20 EOAD, 34 LOAD) were recruited at the Hospital Clínic de Barcelona. All participants and informants completed the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and Neuropsychiatric Inventory (NPI) questionnaires to assess the severity of sleep‐wake alterations and neuropsychiatric symptoms. In addition, they underwent a 3T turbospin‐echo MRI to measure LC volume. We compared mean values of LC volume, ESS, PSQI, and NPI between EOAD and LOAD. Furthermore, linear regression models controlling by cognitive status (MMSE) were performed. Result: EOAD and LOAD had similar cognition (MMSE 21.3±5 vs. 22.6±4, respectively), functional status (CDR 0.92±0.1 vs. 0.68±0.1), and prevalence of amnestic phenotype (57 vs. 70%). EOAD compared to LOAD, trended towards higher scores for ESS (7.4±1 vs. 5.1±1, respectively), PSQI (7.3±2 vs. 5.6±1), NPI (21.6±8 vs. 14.6±8), and caregiver distress (9.4±3 vs. 4.7±3). LC volume was lower in EOAD according to preliminary MRI data [n=18, 9 EOAD (21.8±3 mm3), 9 LOAD (29.5±3 mm3)]. Linear regression models showed that MMSE did not influence the EOAD/LOAD effect on LC volume (coef. 7.7, p=0.032). Conclusion: The current preliminary study suggests that LC degeneration is greater in EOAD than LOAD. This difference may explain the EOAD‐associated worse sleep‐wake dysfunction and neuropsychiatric symptoms. Deep phenotyping/comparison of EOAD and LOAD can inform tailored treatment strategies for these behavioral symptoms. [ABSTRACT FROM AUTHOR]

We report clinico‐pathological features of a 65‐year‐old woman and a 56‐year‐old man with a 5‐year clinical history who had clinical and neuropathological characteristics of upper and lower motor neuron disease consistent with amyotrophic lateral sclerosis, and a frontotemporal atrophy pattern in case 2 without TDP‐43 pathology. Instead, spongiform change and pathological prion protein deposits were observed in several brain regions. No prion protein gene mutations were found. Western blot analysis showed a five‐band profile compatible with variably protease‐sensitive prionopathy. We conclude that this disease can display prolonged disease duration and clinico‐pathological features within the ALS/FTLD spectrum. [ABSTRACT FROM AUTHOR]

Introduction We aimed to investigate if cerebral amyloid angiopathy (CAA) is more frequent in genetically determined than in sporadic early-onset forms of Alzheimer's disease (AD) (early-onset AD [EOAD]). Methods Neuroimaging features of CAA, apolipoprotein ( APOE ), and cerebrospinal fluid amyloid β (Aβ) 40 levels were studied in subjects with Down syndrome (DS, n = 117), autosomal-dominant AD (ADAD, n = 29), sporadic EOAD ( n = 42), and healthy controls ( n = 68). Results CAA was present in 31%, 38%, and 12% of cognitively impaired DS, symptomatic ADAD, and sporadic EOAD subjects and in 13% and 4% of cognitively unimpaired DS individuals and healthy controls, respectively. APOE ε4 genotype was borderline significantly associated with CAA in sporadic EOAD ( P = .06) but not with DS or ADAD. There were no differences in Aβ040 levels between groups or between subjects with and without CAA. Discussion CAA is more frequently found in genetically determined AD than in sporadic EOAD. Cerebrospinal fluid Aβ40 levels are not a useful biomarker for CAA in AD. [ABSTRACT FROM AUTHOR]

Objective: To determine the usefulness of dopamine transporter (DAT) imaging to identify idiopathic rapid eye movement sleep behavior disorder (IRBD) patients at risk for short-term development of clinically defined synucleinopathy.Methods: Eighty-seven patients with polysomnography-confirmed IRBD underwent 123 I-FP-CIT DAT-SPECT. Results were compared to 20 matched controls without RBD who underwent DAT-SPECT. In patients, FP-CIT uptake was considered abnormal when values were two standard deviations below controls' mean uptake. After DAT-SPECT, patients were followed up during 5.7 ± 2.2 (range, 2.6-9.9) years.Results: Baseline DAT deficit was found in 51 (58.6%) patients. During follow-up, 25 (28.7%) subjects developed clinically defined synucleinopathy (Parkinson's disease in 11, dementia with Lewy bodies in 13, and multiple system atrophy in 1) with mean latency of 3.2 ± 1.9 years from imaging. Kaplan-Meier survival analysis showed increased risk of incident synucleinopathy in patients with abnormal DAT-SPECT than with normal DAT-SPECT (20% vs 6% at 3 years, 33% vs 18% at 5 years; log rank test, p = 0.006). Receiver operating characteristics curve revealed that reduction of FP-CIT uptake in putamen greater than 25% discriminated patients with DAT deficit who developed synucleinopathy from patients with DAT deficit that remained disease free after 3 years of follow-up. At 5-year follow-up, DAT-SPECT had 75% sensitivity, 51% specificity, 44% positive predictive value, 80% negative predictive value, and likelihood ratio 1.54 to predict synucleinopathy.Interpretation: DAT-SPECT identifies IRBD patients at short-term risk for synucleinopathy. Decreased FP-CIT putamen uptake greater than 25% predicts synucleinopathy after 3 years' follow-up. These observations may be useful to select candidates for disease modification trials in IRBD. Ann Neurol 2017;82:419-428. [ABSTRACT FROM AUTHOR]

Introduction TREM2 is involved in the regulation of inflammatory response and phagocytosis. A soluble fragment (sTREM2) is often found abnormally increased in cerebrospinal fluid (CSF) in Alzheimer's disease (AD). Methods One hundred fourteen participants (45 control, 19 preclinical, 27 mild cognitive impairment [MCI], and 23 AD) underwent CSF sTREM2 determination and magnetic resonance imaging (MRI). We studied the association between CSF sTREM2, gray matter volume, and water motion diffusivity and anisotropy across groups. Results In MCI patients, a positive correlation between CSF sTREM2 and gray matter volume was found in the bilateral inferior and middle temporal cortices, precuneus, the supramarginal, and angular gyri, after controlling by age, sex, and p-tau. A negative correlation with mean diffusivity was detected in overlapping regions, among others. Discussion In early AD, augmented CSF sTREM2 levels correspond with cerebral MRI features typical of brain swelling, supporting a role for TREM2 in the regulation of the neuroinflammatory response to early neurodegeneration. [ABSTRACT FROM AUTHOR]

In sporadic Creutzfeldt-Jakob disease (sCJD), high signal intensity in fluid attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) sequences in striatum and/or cortical regions of the brain are present in about 83% of cases, reflecting tissue damage, such as spongiform change and abnormal prion protein deposits. Novel diffusion sequences of MRI might improve the detection of CJD characteristic changes in the subset of patients in whom these alterations are absent or less evident. We report a neuropathologically confirmed case of the rare MM2 T + C subtype of sCJD, with mixed clinical and neuropathological features of MM2 thalamic and MM2 cortical subtypes, in whom the use of diffusion tensor imaging helped to identify cortical hyperintensities that could be easily overlooked with conventional DWI. [ABSTRACT FROM AUTHOR]

Aims The aims of this study were to assess the sensitivity of the International Behavioural Variant FTD Criteria Consortium ( FTDC) revised criteria of behavioural variant frontotemporal dementia ( bvFTD) in a pathological cohort and to determine their predictive values in a clinical context suggestive of bvFTD. In addition, the study aimed to assess the influence of the age at onset and underlying pathology in the clinicopathological correlations. Methods Retrospective, blinded review of the clinical and neuropathological data from the Neurological Tissue Bank of the Biobank Hospital Clinic- IDIBAPS, Barcelona ( Spain) was conducted, assessing the fulfilment of the diagnostic criteria on a case-by-case basis. Two separate nonexclusive cohorts were selected: Cohort 1 ( n = 58) subjects with pathological diagnosis of frontotemporal lobar degeneration ( FTLD) and Cohort 2 ( n = 66) subjects with the premortem diagnosis of bvFTD. Results The FTDC criteria reached a sensitivity of 93% for possible and 80% for probable bvFTD. Early-onset cases displayed significantly more disinhibition, loss of empathy and compulsive behaviour with respect to late-onset bvFTD, leading to a slightly higher sensitivity of the diagnostic criteria (97% vs. 91%). There were no differences in the diagnostic performance between tau-positive and tau-negative cases. In subjects clinically diagnosed as bvFTD, a 'possible bvFTD' diagnosis reached a positive predictive value for FTLD pathology of 90%, irrespective of underlying proteinopathy. False-positive clinical diagnoses were mainly Alzheimer's disease. These cases were significantly older, had less family history of dementia and had a predominantly apathetic clinical picture. Conclusions The revised bvFTD criteria present good sensitivity and positive predictive value in both early- and late-onset cases and regardless of the underlying FTLD pathology. [ABSTRACT FROM AUTHOR]

Background: The amyloid deposition (A) in the 2018 ATN classification of Alzheimer disease can be assessed by CSF Aβ 1‐42 or amyloid PET. Although the agreement between them is high, it is not exact. Method: We selected patients from the Alzheimer's disease and other cognitive disorders Unit at Hospital Clínic of Barcelona with available amyloid PET and lumbar puncture, with a maximum difference of time of one and a half year between them. We used F18 Florbetapir (n=27), F18 Florbetaben (n=7), F18 Flutemetamol (n=16) or 11C‐PIB (n=2) as tracers for amyloid PET. CSF Aβ 1‐42, total tau (tTau) and phosphorylated tau (pTau) were measured using INNOTEST® Fujirebio until June 2019 and using LUMIPULSE® Fujirebio after June 2019. We analyzed the agreement between amyloid PET and CSF biomarkers. Result: We included 52 patients. They had been diagnosed of Alzheimer disease (n=32), frontotemporal dementia (n=11), Lewy body disease (n=2) and psychiatric disorders (n=7) (Table 1). There was a perfect agreement between CSF biomarkers and amyloid PET when CSF biomarkers were all normal or all altered (Figure 1): All patients with CSF A+T+N+ (n=19) had a positive amyloid PET and all patients with CSF A‐T‐N‐ (n=7) had a negative amyloid PET. Agreement decreased with other CSF results. Only 11/19 patients with CSF A+T‐N‐ had a positive amyloid PET. 31/32 (97%) patients with positive amyloid PET had low Aβ 1‐42 levels (A+) but only 11/20 (55%) patients with negative amyloid PET had normal Aβ 1‐42 levels (A‐). Conclusion: CSF biomarkers and amyloid PET showed a perfect agreement when CSF biomarkers were all normal or all altered. For other CSF ATN results, agreement with amyloid PET was much lower. [ABSTRACT FROM AUTHOR]

Background: Changes in functional connectivity (FC) networks have been extensively reported in late onset Alzheimer's Disease (AD), being the default mode network (DMN) the key system to be affected. However, it remains unclear if FC in early‐onset AD (EOAD) would show a similar pattern than late onset AD. Method: We studied 48 EOAD patients (mean age=57.40±5.53 years) and 31 healthy controls (CTR, mean age=58.22±3.94 years) who underwent resting state functional magnetic resonance imaging (rs‐fMRI) in a 3T MRI scanner. We used group independent component analysis to identify the main resting state networks (RSNs). We studied group‐differences in the spatial extent of these networks, in the amplitude of their temporal oscillations and in the temporal correlation between pairs of networks, using FSLNETS. We also evaluated the discrimination capability of FC patterns by using a support vector machine (SVM) classifier. Result: We identified 17 RSNs that were further classified into DMN, visual, motor, executive, salience and cerebellum systems. The network spatial maps' vertex‐wise analysis shows regional increases of some executive networks in EOAD (p<0.05, FWE corrected), suggesting increased aberrant local connectivity surrounding the main RSN nodes. In the temporal domain, we find decreases in amplitude in the posterior DMN and the salience network (p<0.05, corrected), and increases in the anterior DMN and the cerebellum networks. With the study of correlations between networks we describe a pattern of altered inter‐network connectivity that involves both increases and decreases of connectivity. Importantly, the entire pattern of network correlations discriminated AD from CTR subjects with an accuracy of 83.5%. Conclusion: Our results suggest that EOAD is characterized by a complex pattern of FC alterations involving alterations in the amplitude of the main RSNs and in the way that they interconnect. Increase in connectivity in short‐range connections surrounding the main nodes might be a consequence of the decreases of larger connections between nodes. Alterations in the salience network differ from the late onset AD literature. Overall, the entire FC pattern gives a good classification rate suggesting that it might be a good biomarker for EOAD. [ABSTRACT FROM AUTHOR]

Background: Several previous studies have analyzed the genetic expression in late‐onset Alzheimer's disease (AD). In this study, we aim to analyze the differential gene expression between sporadic early‐onset AD (sEOAD) and autosomal dominant AD due to the presence of PSEN1 mutations (PSEN1) in two type of samples, brain tissue and lymphoblastoid cell lines (LCL). Method: Frozen prefrontal cortex (5 CTRL, 4 sEOAD and 4 PSEN1) was obtained from the Neurological Tissue Bank and LCL (5 CTRL, 5 sEOAD and 5 PSEN1) from the Alzheimer's Disease Unit, both from the Hospital Clinic of Barcelona, IDIBAPS. Gene expression was measured with microarray Clariom D (Affymetrix). Differentially expressed genes (DEG) were obtained selecting the 35% most variable genes (n = 8473) by adjusting a linear model with empirical Bayes moderation of the variance. Significance threshold was set at p.value < 0.05 and fold change in absolute value >0.5. The analysis of biological significance was based on gene set enrichment analysis on Reactome Pathway Knowledge database. Result: 781/355 (brain/LCL) genes were differentially expressed in the sEOAD vs CTRL comparison, 503/275 in the PSEN1 vs CTRL, and 244/115 in the PSEN1 vs EOAD. No DEG were found with a significance threshold of an adjusted p.value <0.05. Any of the DEG survived after multiple comparisons correction. The top 10 enriched pathways for each comparison, using the most significative p.value and a normalized enrichment score (NES) absolute value >1.8, were considered. Pathways involved in synapsis were found in 2 comparisons: sEOAD vs CTRL (brain) and PSEN1 vs CTRL (LCL). Pathways related to metabolism (mainly Krebs cycle) were identified in all comparisons between patients and controls in both tissues. Signal transduction pathways were found in all comparisons. Immune system was observed in all comparisons between PSEN1 and sEOAD, as well as sEOAD vs CTRL in brain. Conclusion: Genes involved in the immune system and signal transduction pathways were differentially expressed in sporadic and autosomal dominant AD caused by PSEN1 mutations. The number of DEG was higher in brain tissue than in LCL comparisons. Validation of these findings by quantitative‐PCR would be necessary to discard false positive results. [ABSTRACT FROM AUTHOR]

Background: ABCA7 gene (ATP‐binding cassette transporter A7) loss‐of‐function mutations are related to increased risk of suffering Alzheimer's disease (AD). On the other hand, mutations in GRN (Progranulin) gene are causative of frontotemporal dementia (FTD). Methods: The proband was a patient diagnosed from semantic variant of primary progressive aphasia. Age at onset was at 50 years‐old, presenting progressive cognitive decline with an important language loss. The MRI showed a left temporal atrophy. AD CSF biomarkers were normal and no familial history of dementia was reported. Next generation sequencing was performed with Illumina NextSeq500. Single nucleotide variants were detected using GATK and copy number variants using ExomeDepth algorithm. Sanger sequencing was performed for GRN variant confirmation and MLPA technique for ABCA7 deletion validation. C9orf72 repeat expansion was studied with a repeat primed PCR and fragment analysis. Biological samples from his mother and a brother were obtained. Commercial ELISA kit was used to measure serum PGRN levels (Adipogen). Results: Patient showed an ABCA7 partial deletion (exons 17‐47) plus 4 contiguous genes, of a total of 105 kb in size (hg19 chr19:g.1048865_1154298). Deletion was confirmed in the proband and discarded in the proband's mother and brother by MLPA. Patient and his mother (asymptomatic at 81 yo) were also carriers of a reported GRN variant, p.(Asp33Glu; rs63750742). Progranulin serum levels were normal in the patient and his family members. C9orf72 screening was negative. Conclusions: The patient harbored two genetic alterations in genes related to dementia risk, although it is unlikely that any of them alone could be responsible of the FTD phenotype. ABCA7 deletion should be de novo or father inherited. ABCA7 protein truncating variant at exon 14 (p.Arg578fs), which has a similar protein consequence, is relatively frequent in control population, although has showed a 1.8‐fold enrichment in AD patients. Moreover, GRN variant does not seem to be pathogenic or low penetrance because proband's mother is unaffected and serum progranulin levels are normal. In conclusion, these variants per se are likely not sufficient to cause the disease, but rather risk variants of intermediate to high penetrance along with other factors. [ABSTRACT FROM AUTHOR]

Background: Early onset Alzheimer disease (EOAD) (age at onset < 65 years) represents an important cause of early‐onset dementia. EOAD has some clinical, pathologic and neuroimaging differences compared to the late onset form of the disease that makes this subset of patients more difficult to diagnose and manage. Our objectives are to describe the clinical‐pathological correlation of a cohort of pathology‐confirmed EOAD, and to compare the findings with our antecedent EOAD cohort. Method: Clinical and neuropathological data of subjects from the Neurological Tissue Bank‐Hospital Clínic/IDIBAPS (Barcelona, Spain, 2010‐2017) with postmortem confirmation of AD and age of onset before 60 years were collected retrospectively and analyzed. Patients with PSEN1, PSEN2 and APP mutations or insufficient clinical data were excluded. The findings were compared with those of our previously reported EOAD cohort (n = 40, 1994‐2009). Result: A total of 36 new patients (44% women) were included. The mean age at onset was 55 years (SD ± 3.5), the mean of diagnostic delay was 2.8 years (SD ± 1.8) and the mean duration of disease was 10.4 years (SD ± 4.2). An onset with typical/episodic memory impairment was observed in 83% of the subjects. There was a lack of clinico‐pathological correlation on initial and final clinical diagnosis in 11% and 8%, respectively. Initial misdiagnoses were frontotemporal dementia (n = 1) and non‐neurodegenerative causes (n = 3), while final misdiagnoses were dementia with Lewy bodies (n = 1), frontotemporal dementia (n = 1) and progressive supranuclear palsy (n = 1). Three patients underwent AD biomarker analysis (3 CSF, 1 amyloid PET), and were consistent with AD profile. The former cohort had less typical/amnestic presentations (χ2 = 4.1, p = 0.04), a trend towards higher percentage of misdiagnoses (23% on initial diagnosis and 20% on final diagnosis, p non‐significant) and a similar diagnostic delay (3.1 years). Neuropathology showed, in addition to AD‐pathology, cerebral amyloid angiopathy in 94% and Lewy‐body copathology in half of patients; these data was similar to the previous cohort. Conclusion: There is a trend towards diagnostic improvement in EOAD, that might be explained by improved diagnostic criteria, increasing experience on EOAD, a higher number of typical presentations and the beginning of use of biomarkers, although diagnostic delay and neuropathological findings remain similar. [ABSTRACT FROM AUTHOR]

Objective We describe the neuroimaging characteristics of prodromal AD (PrdAD) patients diagnosed using the new research criteria in a clinical setting. In order to further characterize these patients, we also study the relationship between neuropsychology, CSF biomarkers and magnetic resonance imaging (MRI) findings. Methods/Patients 76 participants-24 controls (CTR), 20 amnesic patients, and 32 Alzheimer's disease (AD) patients-were included in the study. PrdAD was defined on the basis of an objective episodic memory deficit and an AD CSF profile. Structural MRI was performed in all participants. Results After FWE correction, voxel-based morphometry (VBM) analysis of PrdAD patients versus CTR showed significant clusters of decreased gray matter (GM) volume in the left hemisphere regions including the parahippocampal gyrus, uncus, precuneus, and middle frontal gyrus. We did not find differences in brain atrophy between PrdAD and mild AD patients. Some significant associations were found between CSF levels and episodic and semantic fluency tests in the PrdAD group. Correlations in the PrdAD group revealed that patients with higher scores on delayed free recall had significantly greater GM volume in the left superior temporal gyrus ( t = 6.64, p < 0.0001). Conclusions PrdAD patients presented mainly medial temporal GM atrophy, which was related with significant episodic memory impairment. The cognitive deficit observed in PrdAD patients was also associated with CSF biomarker levels. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Diagnostic accuracy for the early detection of mild cognitive impairment (MCI) is critical both in the clinical and research settings. Our aim was to evaluate the diagnostic performance of the ALTOIDA‐iADL test in subjects with non‐degenerative MCI and prodromal (pAD) and mild (mAD) Alzheimer's disease. Methods: ALTOIDA‐iADL is a 10‐minute administrable cognitive test, which assesses activities of daily living in the form of an augmented virtual reality game. The task consists of placing and finding virtual objects in a real environment and provides a final score (the NeuroMotor Index; NMI). The NMI is obtained by weighting multi‐modal information such as hands' micromovements, walking bouts and speed, reaction time and navigation trajectory (among others), and represents the overall outcome of the individual task performance. Fifty‐one participants were included and classified according to cerebrospinal fluid (CSF) AD biomarkers: MCI (n = 22; age: 68.2; MMSE: 26.5), pAD (n = 15; age: 69.4; MMSE: 24.0) and mAD (n = 14; age: 70.6; MMSE: 20.7). Results: The NMI allowed differentiating between subjects with absence (Aβ‐) and presence (Aβ+) of abnormalities in the amyloid biomarker (p < 0.01). Also, differences were found between the MCI group and the pAD (p < 0.01) and mAD (p < 0.01) groups (Fig. 1). ROC curves showed good diagnostic accuracy of the NMI in the discrimination between the Aβ‐ and Aβ+ (AUC = 0.777; p < 0.01), MCI and pAD (AUC = 0.781; p < 0.01) and MCI and mAD (AUC = 0.772; p < 0.01). The NMI did not discriminate between the pAD and mAD (AUC = 0.557; p = 0.61) groups (Fig. 2). The NMI correlated with CSF NfL levels (r = ‐.456; p < 0.05) and the MMSE score (r =.432; p < 0.01), showing an association with the degree of cognitive impairment. Conclusions: ALTOIDA‐iADL is useful in the differential diagnosis between patients with non‐degenerative MCI and prodromal and mild Alzheimer's disease. Its performance is related to the degree of impairment in cognitive screening tests and with biomarkers of axonal damage/neurodegeneration. [ABSTRACT FROM AUTHOR]