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Abstract Background Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process. Methods Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis. Results Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified. Conclusions We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

BackgroundProgressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).MethodIn this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.ResultsOur analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73 × 10-3) in PSP.ConclusionsThrough WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

Background: Despite disease‐specific symptoms, differentiation between Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) remains challenging, especially in early, prodromal stages. This is fueled by overlapping pathology in both diseases (Slaets et al., 2013). Monoamine neurotransmitters are significantly altered between DLB and AD and are capable of distinguishing DLB from AD, when added to the panel of cerebrospinal fluid (CSF) dementia biomarkers (Aβ1‐40, Aβ1‐42, T‐tau, P‐tau) and as standalone biomarkers (Janssens et al., 2018). Additionally, cognitive and behavioral differences linked to monoaminergic changes between DLB, AD patients and non‐demented control individuals, have been previously described (Engelborghs et al., 2006, Vermeiren et al., 2015).This study aimed to further explore these dissimilarities for improving discrimination between prodromal and advanced DLB and AD stages. Method: Monoamine neurotransmitter levels were measured in CSF and plasma of 160 prodromal AD (proAD), prodromal DLB (proDLB), AD and DLB patients and 40 non‐demented individuals, using ultra‐high‐performance liquid chromatography. CSF biomarker levels were determined through ELISA. A battery of cognitive and behavioral tests was performed. Monoaminergic, biomarker, cognitive and demographic data were integrated in stepwise regression models to discriminate between (prodromal) DLB and AD. Result: Significant serotonergic differences in CSF between DLB and AD, as well as noradrenergic, dopaminergic and serotonergic differences in plasma between DLB and AD and with non‐demented individuals were noted. CSF dementia biomarkers levels differed significantly between proAD, proDLB, DLB and AD stages and with non‐demented individuals. There were no CSF, plasma monoamines or CSF biomarker changes between proDLB versus DLB, and proAD versus AD stages. Cognitive functioning differed significantly between prodromal and advanced DLB and AD stages and with non‐demented individuals. Stepwise regression identified that models including plasma and CSF serotonergic components, as well as cognitive tests were the most accurate at discriminating between proDLB versus DLB, proAD versus AD, proDLB versus proAD and DLB versus AD, with area under the curve (AUC), sensitivity and specificity values > 0.9. Conclusion: These findings support differentially affected monoaminergic, pathological biomarker levels and cognitive abilities between (prodromal) AD and DLB, and with non‐demented individuals. In addition, this study provides robust models for discrimination between (prodromal) DLB and AD. [ABSTRACT FROM AUTHOR]

Background: ABCA7, an important risk gene for AD, encodes a transporter implicated in lipid transport and phagocytosis, and its disruptions have been linked to AD pathogenesis. However, the impact of these mutations on AD risk is complex due to their interaction with a multifaceted transcriptional architecture and cell type‐specificexpression patterns. This study aims to analyze the intricate patterns of ABCA7 expression across diverse cell types, considering various ABCA7 genotypes in relation to AD patients and non‐carrier controls, while also exploring the effects of ABCA7 mutations on transcriptome‐wide gene expression. Method: To address this complexity, we performed droplet‐based single‐nuclei RNA sequencing on BA10 brain samples (ABCA7 mutation carriers [n = 9], non‐carrier AD patients [n = 6], and non‐carrier control [n = 8]) using 10x Chromium library preparation followed by sequencing on a NovaSeq6000 platform. Cell type annotation was performed using scSorter. Differential gene expression was analyzed using limma‐voom, and pathway analyses were performed using fgsea in R across cell types and studied groups. Result: We obtained over 400,000 nuclei across 23 samples. Excitatory neurons had the highest proportion of cells expressing ABCA7. However, the highest average expression of ABCA7 was noted in microglia. We detected numerous differentially expressed genes between carrier and non‐carrier AD patients (pval_FDR_adj < 0.05 & abs(logFC) >1). Pathway analysis revealed a notable decrease in the expression of translation‐related genes in microglia, including those associated with nonsense‐mediated mRNA decay, in individuals carrying the mutation. Conclusion: In conclusion, our study unveils distinctive patterns of ABCA7 expression and enriched pathways across major brain cell types, suggesting different roles of ABCA7 in different cell types. [ABSTRACT FROM AUTHOR]

Background: Rare TREM2 variants are major risk factors for Alzheimer's disease (AD), but TREM2 variants may also confer a higher risk for other neurodegenerative diseases and a lower probability for cognitively healthy aging. We studied the TREM2 burden associated with different types of dementia and cognitively healthy centenarians (CHCs). Method: We included participants of the 100‐Plus Study, Amsterdam Dementia Cohort, Longitudinal Aging Study Amsterdam and various Dutch memory clinics. TREM2 variants (R47H, R62H, Q33X, R62C, T96K) were genotyped with a high density array or imputed using standard methods (TOPMED reference panel). To avoid family bias and ethnic differences, related individuals and those of non‐European ancestry were excluded. Frequencies of individual variants and the burden of TREM2 variants were compared in AD dementia, dementia with Lewy Bodies (DLB), frontotemporal dementia (FTD), cognitively normal controls and CHCs (correcting for 5 principal components). Result: We identified 242 carriers of TREM2 mutations and 6,683 controls without a TREM2 mutation with a mean age of 69 years (SD ±14 years), 50% female (Table 1). TREM2 variants were significantly associated with AD dementia (OR 1.4, 95%CI 1.1‐1.8, p = 0.01) (Table 2). R47H conferred the highest risk for AD (OR 2.8, 95%CI 1.4‐5.6, p = 0.004), compared to 1.3‐fold increased risk of R62H (95%CI 0.9‐1.7, p = 0.11). The carrier frequency was not increased in DLB (OR 1.4, 95%CI 0.7‐2.6, p = 0.34) and was not increased in FTD compared to controls (OR 0.59, 95%CI 0.3‐1.3, p = 0.18). Of interest, the allele frequency of TREM2 variants in centenarians is half of the expected frequency (OR = 0.46, 95%CI 0.1‐1.1, p = 0.10), and only concerns R62H. Conclusion: We replicate the association of TREM2 with increased risk of AD. In contrast to previous reports no association was observed with DLB or FTD. Cognitively healthy centenarians show a negative trend for TREM2 allele frequency suggesting that carrying a TREM2 variant decreases chances of survival to extreme age. [ABSTRACT FROM AUTHOR]

Background: MAPT p.R406W is an autosomal dominantly inherited missense mutation associated with FTLD with an amnestic, AD‐like phenotype. Our group first described a carrier pedigree (labeled ADG) in 2003, with 47 relatives. We aim to delineate phenotypic and genetic characteristics of MAPT p.R406W carriers through 19‐year follow‐up, and to provide first data on mutation frequency in FTD and AD. Method: We extended the ADG pedigree, obtained data over 19 years on symptoms, biomarkers and neuropathology. Furthermore, we screened FTD (n=647) and AD (n=1100) patient cohorts for new carriers. Result: The ADG family now counts 38 mutation carriers. 7 unrelated carriers were identified in AD and FTD cohorts. Inclusion of additional relatives procured 56 mutation carriers (39 affected). p.R406W mutation frequencies were 0.62% (FTD) and 0.27% (AD). All probands shared genetic kinship, suggesting a common ancestor. Average onset age and disease duration were 60.9 and 12.4 years (ranges 54‐69, 5‐25). Remarkably, two distinct phenotypes (clinical AD(n=10) or bvFTD(n=9)) emerged. bvFTD patients had significantly worse prognosis. Disinhibition/aggression were highly common (100% of bvFTD, 40% of AD patients). CSF amyloid‐β1‐42 was decreased in all 5 patients with CSF data, 2/5 with concomitant tau elevation. Neuropathology was FTLD‐tau, notably showing only 3R‐tau‐isoforms. Conclusion: We are first to report MAPT p.R406W mutation frequencies, unexpectedly high in FTD ànd AD. Contrary to previous reports, we observed a unique phenotypic shift in Belgian p.R406W carriers, with prominent behavioral symptoms, as well as memory decline. Surprisingly, CSF biomarkers showed decreased amyloid‐β1‐42, and neuropathology was FTLD‐tau with isolated 3R‐tau, highly unusual findings for this tauopathy. [ABSTRACT FROM AUTHOR]

Background: ABCA7 is a major risk gene for Alzheimer's disease (AD) and rare premature termination codon (PTC) and missense mutations are enriched in AD patients. In preliminary studies we obtained that ABCA7 PTC and missense mutation carriers present with a classic AD phenotype, but severe levels of cerebral amyloid angiopathy (CAA) were also found (table 1, figures 1‐2). We aim to delineate the clinicopathological phenotype of rare ABCA7 mutation carriers in Belgian CAA patients. Methods: Genetic screening of ABCA7 in a Belgian CAA cohort (n = 83), with genotype‐phenotype comparison of the ABCA7 carriers using demographics and clinicopathology data. Results: In 21.4% (18/84) of CAA patients a rare ABCA7 mutation was identified. Seven patients carried a PTC mutation, 10 a rare missense variant, and in one CAA patient we found a deletion. The mean onset age was 66.4±12.8 (range 47‐84) years, while the mean age at death was 68.0±10.3 (range 48‐92) years. In 87.5% (7/8) of patients a positive family history of disease was mentioned. Cognitive decline was present in 52.9% (9/17). Nine patients were diagnosed as probable CAA, and four as possible CAA. In six patients postmortem examination showed moderate‐to‐severe levels of CAA in all but one patient (83.3%, 5/6) and AD neuropathological hallmarks (100%, 6/6). Extensive levels of CAA were present in both the meningeal and capillary blood vessels, and moderate to high levels of CAA in the parenchymal blood vessels (Figure 3). Conclusions: Our data suggests that rare ABCA7 mutations are frequently present in CAA patients. Carriers show signs of severe levels of CAA, as well as AD neuropathological hallmarks. The findings of this study have important implications for future research and clinical practice. [ABSTRACT FROM AUTHOR]

Background: The framework globally used to classify Alzheimer's Disease stages for research purposes includes three core biomarkers: A) Aβ burden; T) tau pathology; and N) neuronal injury. A lack of consensus exists in linking cognitive and behavioral tests used in everyday clinical practice to biological stages of dementia as defined by the ATN classification. The aim of the current study is to identify the clinical variables that best classify individuals into biologically defined cognitive profiles. Method: A total of 751 subjects, from the Alzheimer's Disease Neuroimaging Initiative cohort, were categorized into seven ATN groups: 112 cognitively unimpaired with ATN‐; 46 cognitively unimpaired with ATN or AT+; 65 cognitively unimpaired with T, N or TN+; 128 amnestic Mild Cognitive Impairment (aMCI) with ATN‐; 223 aMCI with ATN or AT+; 94 aMCI with T, N or TN+ and 83 dementia with ATN or AT+. The groups for which the features exhibited differences during data exploration were classified employing 28 cognitive, behavioral, and demographic features using a supervised machine learning algorithm, specifically, a random forest classifier in combination with a synthetic oversampling technique. Result: We found that the selected features were not able to distinguish between all seven groups and in particular between the three cognitively unimpaired groups. Therefore, classification was only performed for the three ATN‐defined aMCI groups achieving 58% overall accuracy. The Logical Delayed Recall was the most relevant feature (explaining 17% of the variance), followed by the Alzheimer's Disease Assessment Scale‐Cognitive Subscale 13 (16%), Everyday Cognition Informant (8%), and Alzheimer's Disease Assessment Scale 4 (8%). Marital status, Everyday Cognition Patient and sex were not relevant (0%). Conclusion: Cognitive and behavioral tests were not able to accurately distinguish cognitively unimpaired individuals with different biological profiles. Although accuracy could be improved, our first results showed that a test of delayed memory, one of general cognition, and one on activities of daily living are relevant variables for distinguishing between patients with aMCI and different biological profiles. During diagnosis, treatment monitoring, or in research contexts, these variables might be informative in differentiating the three ATN‐defined aMCI profiles, especially when biomarkers are not available. [ABSTRACT FROM AUTHOR]

Background: Cognitive and daily functioning are conceptually critical in distinguishing Mild Cognitive Impairments (MCI) from dementia (Petersen, 2004), but findings on the association between the two have not always been consistent (e.g., Putcha & Tremont, 2016; Teng et al., 2010). We aimed to investigate whether cognitive functions could predict daily functioning among older adults. Method: A total of 182 participants were included in this study, aged between 51 and 92 years. Cognitive functioning was measured using various neuropsychological tests which target different domains (e.g., trail‐making test, WAIS digit span, verbal fluency), while daily functioning was measured using the Functional Activity Questionnaire (FAQ) and the Instrumental Activities of Daily Living (IADL). The Geriatric Depression Scale (DGS) was used to assess depression as a possible moderator. The association between cognitive domains and daily functioning was examined using Partial Least Squares Structural Equation Modelling in R with the "seminr" package. Result: A model with three cognitive predictors and no moderator provided the best fit to the data. However, the model only explained 16.7% of the total variance. Furthermore, only memory was significantly linked to daily functioning (b = ‐0.367, 95% CI [‐0.53 ‐0.18]), while language and attention/executive functions were not. Memory, language, and daily functioning showed good construct validity (all AVE > 0.5 and HTMT < 0.9), but "attention/executive function" construct suffered from poor convergent validity (AVE = 0.43) with only two out of its seven indicators demonstrating loading larger than 0.708. Also unexpectedly, depression was not found to be a significant predictor or a moderator. Conclusion: Our preliminary results suggest that cognitive function explains a small portion of the daily functioning variance and memory was found to be the best cognitive predictor. Indeed, in addition to executive function, memory has been rather consistently mentioned as crucial in the maintenance of daily functioning (Pérès et al., 2008; Royall et al., 2007). The lack of evidence for the role of executive function in this study might be due to the poor convergence of the "attention/executive function" construct in our model, suggesting that it may represent different cognitive functions and should be investigated further. [ABSTRACT FROM AUTHOR]

Background: Vascular dysregulations and changes in functional brain network integrity play a fundamental role in the pathogenesis of dementia. While often identified in individuals with dementia, the role of small vessel disease (SVD) in the development of dementia is not completely understood yet. Previously, structural and functional brain connectivity was shown to be different between individuals with and without cerebral SVD, but a comprehensive measure of SVD has not been used consistently. We aim to analyze functional brain activation differences in mild cognitive impairment (MCI) individuals with defined SVD burden. Method: Functional brain activation differences were analyzed in MCI individuals with absent or low (n = 34) or high (n = 34) SVD burden using data from the Parelsnoer Institute, a multicenter study involving eight Dutch medical centers. SVD burden was characterized using an ordinal scale ranging from 0 to 4 (Klarenbeek et al., 2013) considering the following markers: lacunes; microbleeds; perivascular spaces in the basal ganglia; white matter hyperintensities based on the Fazekas score. Two groups were identified: the absent or low SVD burden group with a score of 0 or 1 and the high SVD group with a score between 2 and 4. Activation differences were calculated using resting state fMRI data acquired using 3Tesla scanners and analyzed with group‐independent component analysis using the CONN toolbox. Result: Activation of two clusters in the high SVD burden group was lower than in the absent or low SVD group: the cerebellum (p‐FDR >. 001, F = 1.49) and the brainstem (p‐FDR >. 001, F = 2.79). The cerebellar cluster (4541 voxels, +20 ‐74 ‐38) consisted of the left cerebellum crus II, right cerebellum crus II, and left cerebellum lobule VIII. The brainstem cluster (218 voxels, +22 ‐28 +20) involved the right thalamus and the right caudate nucleus. Conclusion: Brain activation differences between groups of individuals with MCI and absent or low or high SVD burden were found in the cerebellum and brainstem. These brain areas are mainly responsible for motor, attentional and executive functions, domains which were found in previous studies to be mostly associated with SVD markers. [ABSTRACT FROM AUTHOR]

Background: Mild Cognitive Impairment (MCI) is a prodromal stage of Alzheimer's disease and other dementias (Langa & Levine, 2014). It has been suggested that a late event‐related potential (ERP) called the late positive potential (LPP) is related to cognitive functioning including sustained attention and reaction time in people with MCI (Waninger et al., 2018). The LPP in the occipital area was also suggested to be a biomarker of MCI (Liu et al., 2022). However, it remains unclear whether LPP in the occipital area is related to cognitive functioning. Method: We collected EEG of 50 people with MCI (mean age 72.44±7.96; education: 5.52±1.07) by using a 20‐channel EEG recording system while participants performed the simple vigilance task (SVT). Their reaction time (ms) was taken as a measure of sustained attention. Vienna Reaction Time Task (VRTT) (Schuhfried GmbH, Moedling, Austria) was used to measure processing speed and inhibition while separating motor action (measured as a motor time) and cognitive processing (measured as a reaction time). Mini‐Mental State Examination (MMSE) was used to measure the severity of cognitive impairment (mean score: 26.20±2.44). Correlation analysis was used to analyze the liner relationship between the average LPP amplitude in the occipital areas (Oz, O1, and O2; time window: 400 to 800 ms after stimulus presentation), reaction time on the three versions of the VRTT, and reaction time on the SVT. Result: We found significant correlations between reaction time on the SVT and motor time on VRTT (S1: p = 0.015; S2: p = 0.075; S3: p = 0.021;), but we found no significant correlations between reaction time on the SVT and VRTT (ps > 0.193), no significant correlations between LPP amplitude in the occipital areas and reaction time on any of the tasks (SVT: p > 0.056, VRTT: ps > 0.288) or between LPP amplitude and motor time on any version of the VRTT (ps > 0.500). Conclusion: Our preliminary results indicate that LPP amplitude measured over the occipital area was not significantly associated with sustained attention or inhibition. [ABSTRACT FROM AUTHOR]

Background: People with DS are at high risk to develop Alzheimer's disease dementia (AD) (Lott & Head, 2001). Predicting and monitoring decline and onset of dementia is a diagnostic challenge and of essence in daily care and support for people with DS. Behavioral and Psychological Symptoms of Dementia (BPSD) are an easily accessible tool for the prediction of dementia onset in the DS population. The BPSD‐DS II scale was developed and validated by our team to identify behavioral changes linked to AD between the last six months and pre‐existing behavior in an individual with DS (Dekker et al., 2021). This project is based on a cohort of DS individuals without AD (n = 94), with AD (n = 43), or with questionable AD (qAD) (n = 54) aged >35 years. At inclusion, the BPSD‐DS II was applied to assess AD‐linked behavioral changes, and biofluid sampling was performed as well. Changes in cerebrospinal fluid (CSF) levels of monoaminergic neurotransmitters and metabolites have been associated with BPSD in AD (Dekker et al., 2015). However, CSF sampling procedures remain difficult in DS, illustrating the need for blood biomarkers. BPSD‐DS II results will be correlated with the serum levels of monoaminergic and classical AD biomarkers. Three years post‐inclusion, a follow‐up study was conducted to assess the evolution of possible AD dementia within this group and to determine the predictive values of the BPSD‐DS II scale and the different analytes. Method: We will use reversed‐phase ultra‐high performance liquid chromatography with electrochemical detection to determine the levels of (nor)epinephrine, dopamine, serotonin and their metabolic products in serum. We will use the Simoaâ platform on the serum of clients with DS without or with (q)AD to detect the levels of Ab40, Ab42, total tau, phosphorylated tau, Glial Fibrillary Acidic Protein and Neurofilament Light chain. Result: We expect a correlation between the results of the BPSD‐DS II and the levels of the monoamines and classical biomarkers in patients with DS without or with (q)AD. Conclusion: The diagnosis predicted by the results of the BPSD‐DS II correlates with the levels of monoamines and classical biomarkers in individuals with DS without or with (q)AD. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease and vascular brain injury are the most common causes of dementia, and are present jointly in 40% of individuals at time of death. Yet, the interaction between Alzheimer's and vascular pathology on cognition is largely undetermined. We studied the interaction between arteriosclerosis and plasma biomarkers of Alzheimer's disease on cognition in a general population without dementia. Method: On stored plasma samples, obtained between 2002‐2005, we measured plasma levels of amyloid‐β40 and amyloid‐β42 by Simoa assay in 2252 participants of the population‐based Rotterdam Study (mean age: 68.9 years, 52% women). Arteriosclerosis was assessed using arterial calcification volumes that were quantified (semi‐)automatically on unenhanced computed tomography (CT). We captured the systemic burden of calcification, using a principal component analysis of calcification volumes in 4 different arterial vessel beds (intracranial and extracranial carotid arteries, coronary arteries and aortic arch). Cognitive assessment included the verbal fluency test, the letter‐digit substitution task, a 15‐word learning test, the Stroop test, and Purdue pegboard task. Global cognition (g‐factor) was calculated using a principal component analysis of these tests. We then determined the interaction between plasma amyloid‐β and calcification on cognitive performance, using multivariable linear regression models. Result: Plasma levels of amyloid‐β and systemic arteriosclerosis were both associated with poorer cognitive performance. After mutual adjustment in multivariable models only calcification remained significantly associated (beta [95%CI] for g‐factor per 1‐SD increase in amyloid‐β40: ‐0.02 [‐0.07; 0.03]; amyloid‐β42: 0.03 [‐0.01; 0.08]; and calcification burden: ‐0.06 [‐0.09; ‐0.04]). The association between amyloid‐β and cognition was stronger in individuals with higher burden of calcification (Figure 1), particularly for amyloid‐β40 (interaction amyloid‐β40×calcification: p = 0.04; amyloid‐β42×calcification: p = 0.001). Results were broadly similar across cognitive tests. The observed interaction between amyloid‐β40 and calcification volume was most profound for calcification burden in the intracranial carotid artery and aortic arch. Conclusion: Arteriosclerosis and amyloid‐β display synergistic effects on cognition in the general population. This interaction was more profound for amyloid‐β40 than for amyloid‐β42, suggesting our observations may relate particularly to amyloid angiopathy. [ABSTRACT FROM AUTHOR]

Background: We previously engineered mice to accumulate elevated levels of age‐related, antigen‐specific memory CD8 T cells as in humans. These mice spontaneously develop all major hallmarks of AD with aging. Analogous T cells reactive to an epitope on Amyloid Precursor Protein (APP) were found in aging humans, accumulated in AD brain, and decreased in AD blood. Here, we examine whether their levels are associated with established AD biomarkers in CSF. Method: Antigen‐specific CD8 T cells in blood were quantified by flow cytometric analysis after staining with anti‐CD8, anti‐KLRG1 and APP peptide‐HLA‐A2 multimers in normal aging, MCI with or without AD biomarkers, and confirmed late‐onset AD patient cohorts (n = 50). Aβ1‐42, total Tau, and pTau181 were quantified in CSF, and cognitive performance assessed by MMSE. Result: Percentage of APP‐specific memory CD8 T cells was significantly decreased with dementia (0.68 + 0.29% for MMSE <25; 1.63 + 0.32% for MMSE >24), reaching minimal levels in AD blood, which precluded meaningful correlations in AD patients. Nevertheless, increasing levels of APP‐specific memory CD8 T cells in blood from all subjects combined corresponded with increased CSF Aβ1‐42 (r = 0.373, P < 0.0004) and decreased total Tau but not pTau181 or MMSE (r = ‐0.234, P < 0.0292; r = ‐0.208, P < 0.0531; and r = ‐0.009, P < 0.9410, respectively). Decreases in the larger parental (KLRG1+) memory CD8 T cell population also correlated with decreased CSF Aβ1‐42 in AD patients alone (r = 0.511, P = 0.003 for % KLRG1+ of CD8 T cells; r = 0.682, P < 0.00009 for % KLRG1+CD8+ cells; n = 31). Conclusion: Our results reveal that age‐related memory CD8 T cells in blood decrease with dementia, and in proportion to decreased CSF Aβ1‐42 and total Tau in all patients, while their parental KLRG1+ population is directly proportional to Aβ1‐42 in AD patients only. This validates our previous findings that loss of APP‐specific memory CD8 T cells from blood accurately tracks the AD continuum, and support the notion that antigen‐specific memory CD8 T cells are associated with the earliest detectable pathologic changes in AD. [ABSTRACT FROM AUTHOR]

Background: Memory problems that are characteristic of amnestic mild cognitive impairment (aMCI) are often accompanied by difficulties in attention and executive functions (EF). Studies have consistently reported atrophy of the hippocampus and its association with memory decline in aMCI. However, it is less clear whether differences in grey matter volume (GMV) also contribute to difficulties in attention and EF. To that end, we investigated whether GMV is related to performance on a series of cognitive tests in people with aMCI. Method: GMV of 29 people with aMCI (mean age = 73.8 ± 7.6 Y, 5 F) was measured with voxel‐based morphometry and regressed against measures of task‐switching (Trail Making B‐A), inhibition (Stroop interference score), working memory (Symbol Digit Modalities), and attention (Vienna Reaction Time S1, S2, S3). Analyses were controlled for age and total intracranial volume. Because of the small sample, we used a lenient significance threshold of p < 0.001 (uncorrected) and cluster size (k) >= 20. Result: Better task performance was related to higher GMV in widespread cortical regions. Task‐switching was mainly related to GMV in the bilateral insula (k = 924, 456, Z = 4.87, 3.79) and prefrontal areas (k = 846, Z = 4.35). Inhibition was related to volume in left posterior areas (k = 302, 300, Z = 3.93, 3.62), and working memory to volume in left temporal, parietal, and frontal cortices (k = 21‐88, Z = 3.28‐3.67). Attention to visual stimuli was associated with GMV of cerebellar (k = 20‐281, Z = 3.36‐3.59) and parieto‐occipital regions (k = 20‐76, Z = 3.28‐4.17), and attention to auditory stimuli mainly with prefrontal regions (k = 113, 49, Z = 3.96, 3.53). Interestingly, slower reactions to complex stimuli were related to higher GMV in occipital gyri (k = 28, Z = 3.56). Conclusion: Our results suggest that EF and attention in people with aMCI are related to integrity of regions beyond those normally implicated in memory decline (e.g. the hippocampus). As investigation into aMCI is crucial for preventing disease progression, our findings should be further investigated by studies with a control group of healthy older adults. [ABSTRACT FROM AUTHOR]