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BackgroundHearing loss in older adults is associated with increased dementia risk. Underlying mechanisms that connect hearing loss with dementia remain largely unclear.MethodsWe studied the association of hearing loss and biomarkers for dementia risk in two age groups with normal cognition: 65 participants from the European Medical Information Framework (EMIF)-Alzheimer’s disease (AD) 90+ study (oldest-old; mean age 92.7 years, 56.9% female) and 60 participants from the EMIF-AD PreclinAD study (younger-old; mean age 74.4, 43.3% female). Hearing function was tested by the ‘digits-in-noise test’ and cognition by repeated neuropsychological evaluation. Regressions and generalised estimating equations were used to test the association of hearing function and PET-derived amyloid burden, and linear mixed models were used to test the association of hearing function and cognitive decline. In the oldest-old group, mediation analyses were performed to study whether cognitive decline is mediated through regional brain atrophy.ResultsIn oldest-old individuals, hearing function was not associated with amyloid pathology (p=0.7), whereas in the younger-old individuals hearing loss was associated with higher amyloid burden (p=0.0034). In oldest-old individuals, poorer hearing was associated with a steeper decline in memory, global cognition and language, and in the younger-old with steeper decline in language only. The hippocampus and nucleus accumbens mediated the effects of hearing loss on memory and global cognition in the oldest-old individuals.ConclusionsHearing loss was associated with amyloid binding in younger-old individuals only, and with cognitive decline in both age groups. These results suggest that mechanisms linking hearing loss with risk for dementia depends on age.

Executive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one ‘network of networks.’ We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.

Development of disease-modifying therapies against Alzheimer's disease (AD) requires biomarkers reflecting the diverse pathological pathways specific for AD. We measured 665 proteins in 797 cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment with abnormal amyloid (MCI(A beta+): n = 50), AD-dementia (n = 230), non-AD dementias (n = 322) and cognitively unimpaired controls (n = 195) using proximity ligation-based immunoassays. Here we identified >100 CSF proteins dysregulated in MCI(A beta+) or AD compared to controls or non-AD dementias. Proteins dysregulated in MCI(A beta+) were primarily related to protein catabolism, energy metabolism and oxidative stress, whereas those specifically dysregulated in AD dementia were related to cell remodeling, vascular function and immune system. Classification modeling unveiled biomarker panels discriminating clinical groups with high accuracies (area under the curve (AUC): 0.85-0.99), which were translated into custom multiplex assays and validated in external and independent cohorts (AUC: 0.8-0.99). Overall, this study provides novel pathophysiological leads delineating the multifactorial nature of AD and potential biomarker tools for diagnostic settings or clinical trials.This study identifies CSF proteins specifically dysregulated along the AD continuum that reflect the multifactorial nature of disease progression. Some of these CSF proteins were used to build biomarker panels with high diagnostic accuracies.

INTRODUCTION: At the Alzheimer's Association's APOE and Immunity virtual conference, held in October 2021, leading neuroscience experts shared recent research advances on and inspiring insights into the various roles that both the apolipoprotein E gene (APOE) and facets of immunity play in neurodegenerative diseases, including Alzheimer's disease and other dementias. METHODS: The meeting brought together more than 1200 registered attendees from 62 different countries, representing the realms of academia and industry. RESULTS: During the 4-day meeting, presenters illuminated aspects of the cross-talk between APOE and immunity, with a focus on the roles of microglia, triggering receptor expressed on myeloid cells 2 (TREM2), and components of inflammation (e.g., tumor necrosis factor α [TNFα]). DISCUSSION: This manuscript emphasizes the importance of diversity in current and future research and presents an integrated view of innate immune functions in Alzheimer's disease as well as related promising directions in drug development.

Alzheimer’s disease (AD) is heterogenous on the molecular level. Understanding this heterogeneity is critical for AD drug development. We aimed to define AD molecular subtypes by mass spectrometry proteomics in cerebrospinal fluid (CSF). Of the 3863 proteins detected in CSF, 1058 proteins had different levels in individuals with AD (n=419) compared with controls (n=187). Cluster analyses of AD individuals on these 1058 proteins revealed five subtypes: subtype 1 was characterized by neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier dysfunction. Distinct genetic profiles were associated with subtypes, e.g., subtype 1 was enriched withTREM2 R47H. Subtypes also differed in brain atrophy and clinical outcomes. For example, survival was shorter in subtype 3 compared to subtype 1 (5.6 versus 8.9 years). These novel insights into AD molecular heterogeneity highlight the need for personalized medicine.

Mild Cognitive Impairment (MCI) is a phase that can precede Alzheimer's Disease (AD). To better understand the molecular mechanisms underlying conversion from MCI to AD, we proposed a multiomics machine learning pipeline (four algorithms) to identify key pathways. Data consisted of metabolites (n=540) and proteins (n=3630) measured in blood plasma coupled with standard clinical tests (n=26). The cohort comprised 230 controls, 386 MCI participants and 184 AD-type dementia participants. Multiclass models showed that oleamide, MMSE and the priority language Z-score were the most relevant variables. Oleamide was increased in the MCI group and further increased in converters (both P

The amyloid cascade hypothesis has strongly impacted the Alzheimer's disease research agenda and clinical trial designs over the past decades, but precisely how amyloid-β pathology initiates the aggregation of neocortical tau remains unclear. We cannot exclude the possibility of a shared upstream process driving both amyloid-β and tau in an independent manner instead of there being a causal relationship between amyloid-β and tau. Here, we tested the premise that if a causal relationship exists, then exposure should be associated with outcome both at the individual level as well as within identical twin-pairs, who are strongly matched on genetic, demographic and shared environmental background. Specifically, we tested associations between longitudinal amyloid-β PET and cross-sectional tau PET, neurodegeneration and cognitive decline using genetically identical twin-pair difference models, which provide the unique opportunity of ruling out genetic and shared environmental effects as potential confounders in an association. We included 78 cognitively unimpaired identical twins with [18F]flutemetamol (amyloid-β)-PET, [18F]flortaucipir (tau)-PET, MRI (hippocampal volume) and cognitive data (composite memory). Associations between each modality were tested at the individual level using generalized estimating equation models, and within identical twin-pairs using within-pair difference models. Mediation analyses were performed to test for directionality in the associations as suggested by the amyloid cascade hypothesis. At the individual level, we observed moderate-to-strong associations between amyloid-β, tau, neurodegeneration and cognition. The within-pair difference models replicated results observed at the individual level with comparably strong effect sizes. Within-pair differences in amyloid-β were strongly associated with within-pair differences in tau (β = 0.68, P < 0.001), and moderately associated with within-pair differences in hippocampal volume (β = −0.37, P = 0.03) and memory functioning (β = −0.57, P < 0.001). Within-pair differences in tau were moderately associated with within-pair differences in hippocampal volume (β = −0.53, P < 0.001) and strongly associated with within-pair differences in memory functioning (β = −0.68, P < 0.001). Mediation analyses showed that of the total twin-difference effect of amyloid-β on memory functioning, the proportion mediated through pathways including tau and hippocampal volume was 69.9%, which was largely attributable to the pathway leading from amyloid-β to tau to memory functioning (proportion mediated, 51.6%). Our results indicate that associations between amyloid-β, tau, neurodegeneration and cognition are unbiased by (genetic) confounding. Furthermore, effects of amyloid-β on neurodegeneration and cognitive decline were fully mediated by tau. These novel findings in this unique sample of identical twins are compatible with the amyloid cascade hypothesis and thereby provide important new knowledge for clinical trial designs.

IntroductionThis study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. MethodsUsing the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). ResultsAT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DiscussionThis study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Cortical atrophy is an early feature of Alzheimers acute accent disease (AD). The biological processes associated with variability in cortical thickness remain largely unknown. We studied 220 cerebrospinal fluid (CSF) proteins to evaluate biological pathways associated with cortical thickness in 34 brain regions in 79 cognitively normal older individuals with normal (>192 ng/L, n = 47), and abnormal (

Introduction: Cerebrospinal fluid (CSF) biomarkers for specific cellular disease processes are lacking for tauopathies. In this translational study we aimed to identify CSF biomarkers reflecting early tau pathology-associated unfolded protein response (UPR) activation. Methods: We employed mass spectrometry proteomics and targeted immunoanalysis in a combination of biomarker discovery in primary mouse neurons in vitro and validation in patient CSF from two independent large multicentre cohorts (EMIF-AD MBD, n = 310; PRIDE, n = 771). Results: First, we identify members of the protein disulfide isomerase (PDI) family in the neuronal UPR-activated secretome and validate secretion upon tau aggregation in vitro. Next, we demonstrate that PDIA1 and PDIA3 levels correlate with total- and phosphorylated-tau levels in CSF. PDIA1 levels are increased in CSF from AD patients compared to controls and patients with tau-unrelated frontotemporal and Lewy body dementia (LBD). Highlights: Neuronal unfolded protein response (UPR) activation induces the secretion of protein disulfide isomerases (PDIs) in vitro. PDIA1 is secreted upon tau aggregation in neurons in vitro. PDIA1 and PDIA3 levels correlate with total and phosphorylated tau levels in CSF. PDIA1 levels are increased in CSF from Alzheimer's disease (AD) patients compared to controls. PDIA1 levels are not increased in CSF from tau-unrelated frontotemporal dementia (FTD) and Lewy body dementia (LBD) patients.

Background: Early amyloid deposition results in functional and structural brain alterations in predementia stages of Alzheimer's disease (AD). However, how early functional and structural brain changes are related to each other remains unclear. Investigating the simultaneous disruptions of functional-structural brain features within individuals in relation to amyloid deposition may increase our understanding of the neuropathological processes underlying AD. Method: We included 648 non-demented participants from the European Prevention for Alzheimer’s Dementia (EPAD) cohort vIMI baseline data release. The cut-off for cerebrospinal fluid (CSF) amyloid-β positivity (A+) was defined at

Background We previously identified four Alzheimer’s disease (AD) subgroups with increasingly higher cerebrospinal fluid (CSF) levels of tau phosphorylated at threonine 181 (p-tau). These subgroups included individuals across the cognitive spectrum, suggesting p-tau subgroups could reflect distinct biological changes in AD, rather than disease severity. Therefore, in the current study, we further investigated which potential processes may be related with p-tau subgroups, by comparing individuals on CSF markers for presynaptic structure [vesicle-associated membrane protein 2 (VAMP2)], postsynaptic structure [neurogranin (NRGN)], axonal damage [neurofilament light (NfL)], and amyloid production [beta-secretase 1 (BACE1) and amyloid-beta 1–40 (Aβ40)]. Methods We selected 348 amyloid-positive (A+) individuals (53 preclinical, 102 prodromal, 193 AD dementia) and 112 amyloid-negative (A−) cognitively normal (CN) individuals from the Amsterdam Dementia Cohort (ADC). Individuals were labeled according to their p-tau subgroup (subgroup 1: p-tau ≤ 56 pg/ml; subgroup 2: 57–96 pg/ml; subgroup 3: 97–159 pg/ml; subgroup 4: > 159 pg/ml). CSF protein levels were measured with ELISA (NRGN, BACE1, Aβ40, NfL) or single-molecule array (Simoa) (VAMP2). We tested whether protein levels differed between the p-tau subgroups within A+ individuals with linear models corrected for age and sex and whether disease stage influenced these relationships. Results Among A+ individuals, higher p-tau subgroups showed a higher percentage of AD dementia [subgroup 1: n = 41/94 (44%); subgroup 2: n = 81/147 (55%); subgroup 3: n = 59/89 (66%); subgroup 4: n = 7/11 (64%)]. Relative to controls, subgroup 1 showed reduced CSF levels of BACE1, Aβ40, and VAMP2 and higher levels of NfL. Subgroups 2 to 4 showed gradually increased CSF levels of all measured proteins, either across the first three (NfL and Aβ40) or across all subgroups (VAMP2, NRGN, BACE1). The associations did not depend on the clinical stage (interaction p-values ranging between 0.19 and 0.87). Conclusions The results suggest that biological heterogeneity in p-tau levels in AD is related to amyloid metabolism and synaptic integrity independent of clinical stage. Biomarkers reflecting amyloid metabolism and synaptic integrity may be useful outcome measures in clinical trials targeting tau pathology.

© 2022 the Alzheimer's Association.Background: Grey matter covariance networks become disrupted early in Alzheimer’s disease (AD), when amyloid starts aggregating, and before the onset of irreversible atrophy. However, the precise relationship of grey matter network breakdown and the AD pathophysiological process remains unclear. Here, we studied to what extent shared familial (genes and family environment) or environmental factors unique to a twin contribute to these relationships in a sample of older monozygotic twins with intact cognition. Method: From the EMIF-AD PreclinAD study we included monozygotic twins who had at least an MRI scan (n=197) and CSF available (n=124). We assessed the upper limit of genetic contribution to grey matter network measures (size, degree, connectivity density, clustering, path length, small-world measures) with within-twin pair correlations. Associations between CSF AD markers (Aβ42/40, t-tau, p-tau) and other markers related to AD pathophysiology (neurogranin, Aβ38, Aβ40, BACE1) with grey matter network disruptions were assessed with linear mixed models. Twin analyses (cross-twin cross-trait, twin difference analyses) were used to assess the contribution of shared familial and/or unique environmental factors to these associations. Result: Twenty individuals (16%) had abnormal CSF Aβ42/40 levels. Grey matter network measures were highly correlated within twin pairs (r=0.54-0.97; all p

Background: In preclinical Alzheimer’s disease (AD), amyloid accumulates in highly-functionally connected brain regions. This selective vulnerability is related to the high neuronal fluctuations, typical of these regions. Dynamic functional connectivity (FC) was introduced to investigate network organization over time, with high network variations indicating regional flexibility, hence promoting functional integration. The relation of early amyloid deposition with FC dynamics remains unclear. Eigenvector centrality (EC) evaluates a node's importance in functional networks, both for the whole functional MRI time series (“static” EC) or within sliding-windows (“dynamic” EC). We studied the association of cerebrospinal fluid (CSF) amyloid load with static and dynamic EC in non-demented individuals from the European Prevention of Alzheimer’s Dementia (EPAD) cohort. Methods: Data for 701 non-demented participants were available. CSF Aβ1-42 levels

Background: Brain amyloid-β (Aβ) is the pathological hallmark of Alzheimer's disease (AD). In logistic disease models, Aβ accumulation is a sigmoid function of time-since-disease-onset (TSDO) (figure 1). Previous positron emission tomography (PET)-based models vary accumulation onset(t50) and duration(r) globally; capacity(K) and baseline(NS) regionally (Whittington2018). We confirm existing approaches and propose a more powerful ICA-based approach to quantify disease severity and estimate TSDO. Method: We used 1071 18F-florbetapir standard uptake value ratio (SUVR) images from the ADNI-2 study (adni.loni.usc.edu/data-samples/data-types/pet). Images were mapped into MNI space. Averages were extracted using the Harvard-Oxford brain-atlas. Whole-brain tracer-specific sigmoid parameters (Jack2013) obtained from the literature were used to estimate TSDO. Of 16 models of regional Aβ accumulation (each of the 4 regional sigmoid parameters varied either regionally or globally), the optimal Bayesian information criterion was found with global t50 and r, and regional NS and K (figure 1) with global values r=6.16y and t50=4.10y. Linearised maps of NS and K were obtained by regressing the SUVR maps onto the global sigmoid. We also estimated these maps as independent components, using a 2-component ICA on the SUVR maps. Both outcomes were used to quantify Aβ accumulation from SUVR images as weighting factors of the accumulation map. We compared the weights from the logistic model and the ICA model in ADNI, using effect size measured with Hedges' g between cognitively normal (CN), subjective memory complaints (SMC), mild cognitive impairment (EMCI/MCI/LMCI) and AD groups. We compared 3 longitudinal visits (N=112) in the OASIS-3 study (see www.oasis-brains.org) with both methods, global SUVR and Centiloid (Klunk2015) using 11C-PiB PET SUVR images. Result: Maps of accumulation capacity from both models had spatial correlation of 0.86 (figure 2); baseline maps had spatial correlation of 0.95. Hedges' g between ADNI groups was 2.25 for K, and 2.42 for ICA (1.46 for global SUVR). In OASIS-3, Hedges' g between visits was 1.24 for K, 1.46 for ICA (global SUVR 0.15, Centiloid 0.4). Conclusion: We demonstrate that linear accumulation models can be used to quantify brain Aβ with PET; maps obtained by ICA yield larger effect sizes than the logistic method for differentiating groups and measuring changes between visits.

Background Cerebrospinal fluid (CSF) is an important biofluid for biomarkers of neurodegenerative diseases such as Alzheimer’s disease (AD). By employing tandem mass tag (TMT) proteomics, thousands of proteins can be quantified simultaneously in large cohorts, making it a powerful tool for biomarker discovery. However, TMT proteomics in CSF is associated with analytical challenges regarding sample preparation and data processing. In this study we address those challenges ranging from data normalization over sample preparation to sample analysis. Method Using liquid chromatography coupled to mass-spectrometry (LC–MS), we analyzed TMT multiplex samples consisting of either identical or individual CSF samples, evaluated quantification accuracy and tested the performance of different data normalization approaches. We examined MS2 and MS3 acquisition strategies regarding accuracy of quantification and performed a comparative evaluation of filter-assisted sample preparation (FASP) and an in-solution protocol. Finally, four normalization approaches (median, quantile, Total Peptide Amount, TAMPOR) were applied to the previously published European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) dataset. Results The correlation of measured TMT reporter ratios with spiked-in standard peptide amounts was significantly lower for TMT multiplexes composed of individual CSF samples compared with those composed of aliquots of a single CSF pool, demonstrating that the heterogeneous CSF sample composition influences TMT quantitation. Comparison of TMT reporter normalization methods showed that the correlation could be improved by applying median- and quantile-based normalization. The slope was improved by acquiring data in MS3 mode, albeit at the expense of a 29% decrease in the number of identified proteins. FASP and in-solution sample preparation of CSF samples showed a 73% overlap in identified proteins. Finally, using optimized data normalization, we present a list of 64 biomarker candidates (clinical AD vs. controls, p Conclusion We have evaluated several analytical aspects of TMT proteomics in CSF. The results of our study provide practical guidelines to improve the accuracy of quantification and aid in the design of sample preparation and analytical protocol. The AD biomarker list extracted from the EMIF-AD cohort can provide a valuable basis for future biomarker studies and help elucidate pathogenic mechanisms in AD.

The recently reportedTNIP1/GPX3locus from AD GWAS studies was investigated. Using proteomics and other functional omics data, we identified evidence for a functional mechanism linking variants in this locus to decreased CSF GPX3 levels as AD progresses, suggesting a new potential target for intervention.

© 2022 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.Objectives: Frontotemporal dementia (FTD) can present with changes in music appreciation. Research has suggested a relationship of altered music appreciation phenotypes with typical socio-emotional changes. We aimed to determine the prevalence and severity of music appreciation phenotypes in FTD and study the relationship with emotion recognition capacities in order to examine whether they could serve as a proxy for changes in socio-emotional functioning. Methods/Design: Based on reported musical changes in the literature, we developed an informant-based questionnaire to assess musical changes and a music test to assess music emotion recognition. Social cognition was assessed with the Ekman 60 faces test in a subgroup of patients (n = 23). Relationships between measures were assessed with linear regressions. Results: We included 47 patients (44.7% female, mean age 65.0 ± 8.4, 31 behavioral variant FTD (bvFTD), 10 semantic dementia (SD), and six progressive nonfluent aphasia (PNFA)). Thirty-six caregivers were included in the music emotion recognition test as controls. Altered music appreciation phenotypes were observed in 79% of the FTD patients. Musicophilia was present in a third of bvFTD patients, and only in up to 10% in language FTD variants. Changes in music appreciation were not associated with decreased music emotion recognition or visual emotion recognition. Compared to controls, bvFTD performed worse on the music emotion recognition task (p < 0.003), and no differences were found with SD (p = 0.06) and PNFA patients (p = 0.8). Conclusions: Music appreciation phenotypes are highly prevalent in FTD patients. Future studies should further investigate the potential diagnostic value of changes in music processing.

Objective The present work was undertaken to study the genetic contribution to the start of Alzheimer's disease (AD) with amyloid and tau biomarkers in cognitively intact older identical twins.Methods We studied in 96 monozygotic twin-pairs relationships between amyloid-beta (A beta) aggregation as measured by the A beta 1-42/1-40 ratio in cerebrospinal fluid (CSF; n = 126) and positron emission tomography (PET, n = 194), and CSF markers for A beta production (beta-secretase 1, A beta 1-40, and A beta 1-38) and CSF tau. Associations among markers were tested with generalized estimating equations including a random effect for twin status, adjusted for age, gender, and apolipoprotein E epsilon 4 genotype. We used twin analyses to determine relative contributions of genetic and/or environmental factors to AD pathophysiological processes.Results Twenty-seven individuals (14%) had an abnormal amyloid PET, and 14 twin-pairs (15%) showed discordant amyloid PET scans. Within twin-pairs, A beta production markers and total-tau (t-tau) levels strongly correlated (r range = 0.73-0.86, all p < 0.0001), and A beta aggregation markers and 181-phosphorylated-tau (p-tau) levels correlated moderately strongly (r range = 0.50-0.64, all p < 0.0001). Cross-twin cross-trait analysis showed that A beta 1-38 in one twin correlated with A beta 1-42/1-40 ratios, and t-tau and p-tau levels in their cotwins (r range = -0.28 to 0.58, all p < .007). Within-pair differences in A beta production markers related to differences in tau levels (r range = 0.49-0.61, all p < 0.0001). Twin discordance analyses suggest that A beta production and tau levels show coordinated increases in very early AD.Interpretation Our results suggest a substantial genetic/shared environmental background contributes to both A beta and tau increases, suggesting that modulation of environmental risk factors may aid in delaying the onset of AD pathophysiological processes. ANN NEUROL 2021

This scientific commentary refers to ‘Time course of phosphorylated-tau181 in blood across the Alzheimer’s disease spectrum’, by Moscoso et al. (doi:10.1093/brain/awaa399).

Cerebrospinal fluid (CSF) biomarkers play an important role in diagnosing Alzheimers disease (AD) which is characterized by amyloid-beta (A beta) amyloidosis. Here, we used two App knock-in mouse models, App(NL-F/NL-F) and App(NL-G-F/NL-G-F), exhibiting AD-like A beta pathology to analyze how the brain pathologies translate to CSF proteomes by label-free mass spectrometry (MS). This identified several extracellular matrix (ECM) proteins as significantly altered in App knock-in mice. Next, we compared mouse CSF proteomes with previously reported human CSF MS results acquired from patients across the AD spectrum. Intriguingly, the ECM protein decorin was similarly and significantly increased in both App(NL-F/NL-F) and App(NL-G-F/NL-G-F) mice, strikingly already at three months of age in the App(NL-F/NL-F) mice and preclinical AD subjects having abnormal CSF-A beta 42 but normal cognition. Notably, in this group of subjects, CSF-decorin levels positively correlated with CSF-A beta 42 levels indicating that the change in CSF-decorin is associated with early A beta amyloidosis. Importantly, receiver operating characteristic analysis revealed that CSF-decorin can predict a specific AD subtype having innate immune activation and potential choroid plexus dysfunction in the brain. Consistently, in App(NL-F/NL-F) mice, increased CSF-decorin correlated with both AP plaque load and with decorin levels in choroid plexus. In addition, a low concentration of human A beta 42 induces decorin secretion from mouse primary neurons. Interestingly, we finally identify decorin to activate neuronal autophagy through enhancing lysosomal function. Altogether, the increased CSF-decorin levels occurring at an early stage of A beta amyloidosis in the brain may reflect pathological changes in choroid plexus, present in a subtype of AD subjects. Funding Agencies|Karolinska Institute; Hallsten Research Foundation; Swedish Research Council; Swedish Brain foundation; Torsten Soderberg Foundation; Erling-Persson Family Foundation; China Scholarship Council; Swedish Research Council [2015-4870]; uropean Unions Horizon 2020 research and innovation program under the Marie Sk1odowska-Curie grant [676144]; Gun and Bertil Stohnes Foundation; Gamla Tjanarinnor grant; Margaretha af Ugglas Stiftelse; Alzheimerfonden [AF-930934]; Alzheimerfonden; Hjarnfonden; Swedish Brain Foundation [ALZ2022-0004, FO-2020-0207]; European Research Council [681712]; Swedish State Support for Clinical Research [ALFGBG-720931]; Alzheimer Drug Discovery Foundation (ADDF), USA [201809-2016862]; AD Strategic Fund; Alzheimers Association [ADSF-21-831376-C, ADSF-21-831381-C, ADSF-21-831377-C]; Olav Thon Foundation; Stiftelsen for Gamla Tjanarinnor, Hjarnfonden, Sweden [FO2019-0228]; European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [860197]; European Union Joint Program for Neurodegenerative Disorders [JPND2021-00694]; UK Dementia Research Institute at UCL

Providing an accurate prognosis for individual dementia patients remains a challenge since they greatly differ in rates of cognitive decline. In this study, we used machine learning techniques with the aim to identify cerebrospinal fluid (CSF) biomarkers that predict the rate of cognitive decline within dementia patients. First, longitudinal mini-mental state examination scores (MMSE) of 210 dementia patients were used to create fast and slow progression groups. Second, we trained random forest classifiers on CSF proteomic profiles and obtained a well-performing prediction model for the progression group (ROC–AUC = 0.82). As a third step, Shapley values and Gini feature importance measures were used to interpret the model performance and identify top biomarker candidates for predicting the rate of cognitive decline. Finally, we explored the potential for each of the 20 top candidates in internal sensitivity analyses. TNFRSF4 and TGF $$\upbeta $$ β -1 emerged as the top markers, being lower in fast-progressing patients compared to slow-progressing patients. Proteins of which a low concentration was associated with fast progression were enriched for cell signalling and immune response pathways. None of our top markers stood out as strong individual predictors of subsequent cognitive decline. This could be explained by small effect sizes per protein and biological heterogeneity among dementia patients. Taken together, this study presents a novel progression biomarker identification framework and protein leads for personalised prediction of cognitive decline in dementia.

Background: Alzheimer's disease (AD) is a neurodegenerative disorder with significant heterogeneity. Different AD phenotypes may be associated with specific brain network changes. Uncovering disease heterogeneity by using functional networks could provide insights into precise diagnoses. Methods: We investigated the subtypes of AD using nonnegative matrix factorization clustering on the previously identified 216 resting-state functional connectivities that differed between AD and normal control subjects. We conducted the analysis using a discovery dataset (n = 809) and a validated dataset (n = 291). Next, we grouped individuals with mild cognitive impairment according to the model obtained in the AD groups. Finally, the clinical measures and brain structural characteristics were compared among the subtypes to assess their relationship with differences in the functional network. Results: Individuals with AD were clustered into 4 subtypes reproducibly, which included those with 1) diffuse and mild functional connectivity disruption (subtype 1), 2) predominantly decreased connectivity in the default mode network accompanied by an increase in the prefrontal circuit (subtype 2), 3) predominantly decreased connectivity in the anterior cingulate cortex accompanied by an increase in prefrontal cortex connectivity (subtype 3), and 4) predominantly decreased connectivity in the basal ganglia accompanied by an increase in prefrontal cortex connectivity (subtype 4). In addition to these differences in functional connectivity, differences between the AD subtypes were found in cognition, structural measures, and cognitive decline patterns. Conclusions: These comprehensive results offer new insights that may advance precision medicine for AD and facilitate strategies for future clinical trials.

Individuals with prodromal Alzheimer’s disease show considerable variability in rates of cognitive decline, which hampers the ability to detect potential treatment effects in clinical trials. Prognostic markers to select those individuals who will decline rapidly within a trial time frame are needed. Brain network measures based on grey matter covariance patterns have been associated with future cognitive decline in Alzheimer’s disease. In this longitudinal cohort study, we investigated whether cut-offs for grey matter networks could be derived to detect fast disease progression at an individual level. We further tested whether detection was improved by adding other biomarkers known to be associated with future cognitive decline [i.e. CSF tau phosphorylated at threonine 181 (p-tau181) levels and hippocampal volume]. We selected individuals with mild cognitive impairment and abnormal CSF amyloid β1–42 levels from the Amsterdam Dementia Cohort and the Alzheimer’s Disease Neuroimaging Initiative, when they had available baseline structural MRI and clinical follow-up. The outcome was progression to dementia within 2 years. We determined prognostic cut-offs for grey matter network properties (gamma, lambda and small-world coefficient) using time-dependent receiver operating characteristic analysis in the Amsterdam Dementia Cohort. We tested the generalization of cut-offs in the Alzheimer’s Disease Neuroimaging Initiative, using logistic regression analysis and classification statistics. We further tested whether combining these with CSF p-tau181 and hippocampal volume improved the detection of fast decliners. We observed that within 2 years, 24.6% (Amsterdam Dementia Cohort, n = 244) and 34.0% (Alzheimer’s Disease Neuroimaging Initiative, n = 247) of prodromal Alzheimer’s disease patients progressed to dementia. Using the grey matter network cut-offs for progression, we could detect fast progressors with 65% accuracy in the Alzheimer’s Disease Neuroimaging Initiative. Combining grey matter network measures with CSF p-tau and hippocampal volume resulted in the best model fit for classification of rapid decliners, increasing detecting accuracy to 72%. These data suggest that single-subject grey matter connectivity networks indicative of a more random network organization can contribute to identifying prodromal Alzheimer’s disease individuals who will show rapid disease progression. Moreover, we found that combined with p-tau and hippocampal volume this resulted in the highest accuracy. This could facilitate clinical trials by increasing chances to detect effects on clinical outcome measures.

Cerebrospinal fluid (CSF) β-site amyloid precursor protein cleaving enzyme 1 (BACE1), neurogranin and the neurogranin/BACE1 ratio are proposed markers for Alzheimer’s disease. BACE1 is also a drug target. However, CSF levels may differ between early-stage amyloid plaque formation (A) and later stage downstream tau-tangle pathology (T) and neurodegeneration (N) and may be expressed as an A/T/N stage (e.g. A+/T−/N or A+/T+/N+). Whether BACE1 and neurogranin levels are persistent traits or change with disease progression is unknown. The aim of this study was to investigate whether CSF neurogranin and BACE1 concentrations differ between A/T/N stages, whether these change over time and correlate with memory decline. This may have implications for patient selection in future trials. We used CSF markers to determine A/T/N stage using amyloid beta42/40 ratio, p-tau181 and total-tau respectively in predementia Alzheimer’s disease cases (n = 176) [including cases that progressed to dementia (n = 10)] and controls (n = 74) from the Norwegian Dementia Disease Initiation cohort. We selected cases at the presumed early (A+/T−/N−, n = 86) and late stages (A+/T+/N+, n = 90) of the Alzheimer’s disease continuum and controlled with normal markers (A−/T−/N−, n = 74). A subset of subjects in all A/T/N groups underwent repeat CSF sampling at approximately 2-year intervals up to 6 years from baseline. Using linear mixed models, longitudinal measurements of CSF BACE1 and neurogranin levels in A+/T−/N− and A+/T+/N+ as compared to A−/T−/N− healthy controls were performed. Next, we measured changes in CSF BACE1 and neurogranin levels in cases that progressed from A−/T−/N− to A+/T−/N− (n = 12), from A+/T−/N− to A+/T or N+ (n = 12), remained stable A+/T−/N− (n = 26), remained stable A+/T+/N+ (n = 28) compared with controls remaining stable A−/T−/N− (n = 33). Lastly, associations between these markers and memory decline were assessed. Compared with A−/T−/N− healthy controls, neurogranin was unaltered in A+/T−/N− (n.s.) but higher in A+/T+/N+ (P < 0.0001). In contrast, BACE1 was lower in A+/T−/N− (P < 0.05) and higher in A+/T+/N+ (P < 0.0001). The neurogranin/BACE1 ratio was increased in both A+/T−/N− (P < 0.05) and A+/T+/N+ (P < 0.0001) groups as compared to A-/T-/N- healthy controls and was more strongly associated with memory decline (b = −0.29, P = 0.0006) than neurogranin (b = −0.20, P = 0.002) and BACE1 (b = −0.13, P = 0.046). Neurogranin and BACE1 level differences remained stable over time not only within A/T/N groups but also in patients progressing to more pathological A/T/N stages (e.g. progressing from A+/T−/N− to A + T or N+) and in cases progressing to dementia. Our results suggest that neurogranin and BACE1 levels may differentiate pathomechanistic Alzheimer’s disease subgroups, putatively with different options for treatment.

IntroductionThe contribution of genetic and environmental factors to the relation between cerebrospinal fluid (CSF) biomarkers and cognitive decline in preclinical Alzheimer's disease remains unclear. We studied this in initially cognitively normal monozygotic twins.MethodsWe included 122 cognitively normal monozygotic twins (51 pairs) with a follow-up of 4.3 ± 0.4 years. We first tested associations of baseline CSF Aβ1-42/1-40 ratio, total tau (t-tau), and 181-phosphorylated-tau (p-tau) status with subsequent cognitive decline using linear mixed models, and then performed twin specific analyses.ResultsBaseline abnormal amyloid-β and tau CSF markers predicted steeper decline on memory (p ≤ .003) and language (p ≤ 0.04). Amyloid-β and p-tau markers in one twin predicted decline in memory in the co-twin and tau markers in one twin predicted decline in language in the co-twin (r range -0.26,0.39; p’s ≤ .02).DiscussionThese results suggest that memory and language decline are early features of AD that are in part determined by the same genetic factors that influence amyloid-β and tau regulation.

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.

Introduction: Individuals in the Alzheimer's disease (AD) continuum with mild cognitive impairment (prodromal AD) are at increased risk to develop dementia. Still, underlying pathophysiological processes remain unclear. We studied whether cerebrospinal fluid (CSF) proteome changes are related to time to clinical progression in prodromal AD.Methods: We measured 671 CSF proteins in 49 prodromal AD individuals (67±7 years old, 22 [45%] female) from the Amsterdam Dementia Cohort. Associations of protein levels with time to dementia onset were tested with Cox regression models, followed by biological pathway enrichment analysis.Results: Eighteen (36%) individuals developed dementia during follow-up. In total, 128 (98%) proteins were associated with a 1.4- to 17-fold increased risk of progression to dementia (all P < .05). These proteins showed enrichment for immune system processes, signal transduction, neuronal death, and neurodevelopmental biology.Discussion: CSF proteome changes related to rate of progression to dementia can be detected in prodromal AD, providing more insight into processes involved in early AD pathophysiology.

A B S T R A C T Late-onset Alzheimer's disease (AD) has a significant genetic component, but the molecular mechanisms through which genetic risk factors contribute to AD pathogenesis are unclear. We screened for genetic sharing between AD and the blood levels of 615 metabolites to elucidate how the polygenic architecture of AD affects metabolomic profiles. We retrieved summary statistics from genome-wide association studies of AD and the metabolite blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 31 metabolites, all of which were lipids, we identified and replicated genetic sharing with AD. We also found a positive genetic concordance implying that genetic risk factors for AD are associated with higher blood levels for 16 of the 31 replicated metabolites. In the brain, lipids and their intermediate metabolites have essential structural and functional roles, such as forming and dynamically regulating synaptic membranes. Our results imply that genetic risk factors for AD affect lipid levels, which may be leveraged to develop novel treatment strategies for AD. (c) 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Background As Alzheimer’s disease (AD) pathology presents decades before dementia manifests, unbiased biomarker cut-points may more closely reflect presence of pathology than clinically defined cut-points. Currently, unbiased cerebrospinal fluid (CSF) tau cut-points are lacking. Methods We investigated CSF t-tau and p-tau cut-points across the clinical spectrum using Gaussian mixture modelling, in two independent cohorts (Amsterdam Dementia Cohort and ADNI). Results Individuals with normal cognition (NC) (total n = 1111), mild cognitive impairment (MCI) (total n = 1213) and Alzheimer’s disease dementia (AD) (total n = 1524) were included. In both cohorts, four CSF t- and p-tau distributions and three corresponding cut-points were identified. Increasingly high tau subgroups were characterized by steeper MMSE decline and higher progression risk to AD (cohort/platform-dependent HR, t-tau 1.9–21.3; p-tau 2.2–9.5). Limitations The number of subjects in some subgroups and subanalyses was small, especially in the highest tau subgroup and in tau PET analyses. Conclusions In two independent cohorts, t-tau and p-tau levels showed four subgroups. Increasingly high tau subgroups were associated with faster clinical decline, suggesting our approach may aid in more precise prognoses.