Structural and molecular cholinergic imaging markers of cognitive decline in Parkinson's disease.

Cognitive decline in Parkinson's disease is related to cholinergic system degeneration, which can be assessed in vivo using structural MRI markers of basal forebrain volume and PET measures of cortical cholinergic activity. In the present study we aimed to examine the interrelation between basal forebrain degeneration and PET-measured depletion of cortical acetylcholinesterase activity as well as their relative contribution to cognitive impairment in Parkinson's disease. This cross-sectional study included 143 Parkinson's disease participants without dementia and 52 healthy control participants who underwent structural MRI, PET scanning with 11C-methyl-4-piperidinyl propionate (PMP) as a measure of cortical acetylcholinesterase activity, and a detailed cognitive assessment. Based on the fifth percentile of the overall cortical PMP PET signal from the control group, people with Parkinson's disease were subdivided into a normo-cholinergic (n = 94) and a hypo-cholinergic group (n = 49). Volumes of functionally defined posterior and anterior basal forebrain subregions were extracted using an established automated MRI volumetry approach based on a stereotactic atlas of cholinergic basal forebrain nuclei. We used Bayesian t-tests to compare basal forebrain volumes between controls, and normo- and hypo-cholinergic Parkinson's participants after covarying out age, sex and years of education. Associations between the two cholinergic imaging measures were assessed across all people with Parkinson's disease using Bayesian correlations and their respective relations with performance in different cognitive domains were assessed with Bayesian ANCOVAs. As a specificity analysis, hippocampal volume was added to the analysis. We found evidence for a reduction of posterior basal forebrain volume in the hypo-cholinergic compared to both normo-cholinergic Parkinson's disease [Bayes factor against the null model (BF10) = 8.2] and control participants (BF10 = 6.0), while for the anterior basal forebrain the evidence was inconclusive (BF10 < 3). In continuous association analyses, posterior basal forebrain volume was significantly associated with cortical PMP PET signal in a temporo-posterior distribution. The combined models for the prediction of cognitive scores showed that both cholinergic markers (posterior basal forebrain volume and cortical PMP PET signal) were independently related to multi-domain cognitive deficits, and were more important predictors for all cognitive scores, including memory scores, than hippocampal volume. We conclude that degeneration of the posterior basal forebrain in Parkinson's disease is accompanied by functional cortical changes in acetylcholinesterase activity and that both PET and MRI cholinergic imaging markers are independently associated with multi-domain cognitive deficits in Parkinson's disease without dementia. Comparatively, hippocampal atrophy only seems to have minimal involvement in the development of early cognitive impairment in Parkinson's disease.

Cholinergic white matter pathways along the Alzheimer's disease continuum.

Previous studies have shown that the cholinergic nucleus basalis of Meynert and its white matter projections are affected in Alzheimer's disease dementia and mild cognitive impairment. However, it is still unknown whether these alterations can be found in individuals with subjective cognitive decline, and whether they are more pronounced than changes found in conventional brain volumetric measurements. To address these questions, we investigated microstructural alterations of two major cholinergic pathways in individuals along the Alzheimer's disease continuum using an in vivo model of the human cholinergic system based on neuroimaging. We included 402 participants (52 Alzheimer's disease, 66 mild cognitive impairment, 172 subjective cognitive decline and 112 healthy controls) from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study. We modelled the cholinergic white matter pathways with an enhanced diffusion neuroimaging pipeline that included probabilistic fibre-tracking methods and prior anatomical knowledge. The integrity of the cholinergic white matter pathways was compared between stages of the Alzheimer's disease continuum, in the whole cohort and in a CSF amyloid-beta stratified subsample. The discriminative power of the integrity of the pathways was compared to the conventional volumetric measures of hippocampus and nucleus basalis of Meynert, using a receiver operating characteristics analysis. A multivariate model was used to investigate the role of these pathways in relation to cognitive performance. We found that the integrity of the cholinergic white matter pathways was significantly reduced in all stages of the Alzheimer's disease continuum, including individuals with subjective cognitive decline. The differences involved posterior cholinergic white matter in the subjective cognitive decline stage and extended to anterior frontal white matter in mild cognitive impairment and Alzheimer's disease dementia stages. Both cholinergic pathways and conventional volumetric measures showed higher predictive power in the more advanced stages of the disease, i.e. mild cognitive impairment and Alzheimer's disease dementia. In contrast, the integrity of cholinergic pathways was more informative in distinguishing subjective cognitive decline from healthy controls, as compared with the volumetric measures. The multivariate model revealed a moderate contribution of the cholinergic white matter pathways but not of volumetric measures towards memory tests in the subjective cognitive decline and mild cognitive impairment stages. In conclusion, we demonstrated that cholinergic white matter pathways are altered already in subjective cognitive decline individuals, preceding the more widespread alterations found in mild cognitive impairment and Alzheimer's disease. The integrity of the cholinergic pathways identified the early stages of Alzheimer's disease better than conventional volumetric measures such as hippocampal volume or volume of cholinergic nucleus basalis of Meynert.

Morphological connectivity differences in Alzheimer's disease correlate with gene transcription and cell-type.

Alzheimer's disease (AD) is one of the most prevalent forms of dementia in older individuals. Convergent evidence suggests structural connectome abnormalities in specific brain regions are linked to AD progression. The biological basis underpinnings of these connectome changes, however, have remained elusive. We utilized an individual regional mean connectivity strength (RMCS) derived from a regional radiomics similarity network to capture altered morphological connectivity in 1654 participants (605 normal controls, 766 mild cognitive impairment [MCI], and 283 AD). Then, we also explored the biological basis behind these morphological changes through gene enrichment analysis and cell-specific analysis. We found that RMCS probes of the hippocampus and medial temporal lobe were significantly altered in AD and MCI, with these differences being spatially related to the expression of AD-risk genes. In addition, gene enrichment analysis revealed that the modulation of chemical synaptic transmission is the most relevant biological process associated with the altered RMCS in AD. Notably, neuronal cells were found to be the most pertinent cells in the altered RMCS. Our findings shed light on understanding the biological basis of structural connectome changes in AD, which may ultimately lead to more effective diagnostic and therapeutic strategies for this devastating disease.

Aberrant Claustrum Microstructure in Humans after Premature Birth.

Several observations suggest an impact of prematurity on the claustrum. First, the claustrum's development appears to depend on transient subplate neurons of intra-uterine brain development, which are affected by prematurity. Second, the claustrum is the most densely connected region of the mammalian forebrain relative to its volume; due to its effect on pre-oligodendrocytes, prematurity impacts white matter connections and thereby the development of sources and targets of such connections, potentially including the claustrum. Third, due to its high connection degree, the claustrum contributes to general cognitive functioning (e.g., selective attention and task switching/maintaining); general cognitive functioning, however, is at risk in prematurity. Thus, we hypothesized altered claustrum structure after premature birth, with these alterations being associated with impaired general cognitive performance in premature born persons. Using T1-weighted and diffusion-weighted magnetic resonance imaging in 70 very preterm/very low-birth-weight (VP/VLBW) born adults and 87 term-born adults, we found specifically increased mean diffusivity in the claustrum of VP/VLBW adults, associated both with low birth weight and at-trend with reduced IQ. This result demonstrates altered claustrum microstructure after premature birth. Data suggest aberrant claustrum development, which is potentially related with aberrant subplate neuron and forebrain connection development of prematurity.

[LATE: not every dementia is Alzheimer's disease-Discussion of a new disease entity based on a case example : Current status of limbic-predominant age-related TDP-43 encephalopathy (LATE)]. / LATE: Nicht jede Demenz ist Alzheimer ­ Diskussion einer neuen Krankheitsentität am Fallbeispiel : Zum aktuellen Stand der "limbic-predominant age-related TDP-43 encephalopathy" (LATE).

Limbic-predominant age-related TDP-43 (Transactivation response(TAR)-DNA-binding protein 43 kDa) encephalopathy (LATE) has recently been characterized as a distinct neuropathological entity within the spectrum of dementia. Neuropathological alterations in the sense of LATE were already previously described as a comorbidity to Alzheimer's disease (AD) and it has been diagnosed independently from AD pathology in autopsy studies since 2008. The framework of LATE would account for the pathogenetic impact of limbic TDP-43 proteinopathy as a driver of amnestic dementia, either together with comorbid typical AD changes or as a distinct feature. The LATE possibly explains divergent clinical observations and biomarker results in patients suffering from severe amnestic impairment without biomarker evidence of AD-related amyloid and tau alterations. Whether LATE represents a distinct neuropathological entity or is part of the spectrum of neurodegenerative diseases associated with TDP-43 is currently a matter of debate. Further studies on the role of TDP-43 in the development of amnestic dementia are urgently needed. Thus, the enrichment of an amnestic phenotype in amyloid-centered therapeutic drug studies bears the risk of higher rates of patients with TDP-43 comorbidity, which could hinder the proof of efficacy in such trials. This article presents the current state of the discussion on LATE and illustrates the concept and the clinical considerations with a case study.

The corticotopic organization of the human basal forebrain as revealed by regionally selective functional connectivity profiles.

The cholinergic basal forebrain (CBF), comprising different groups of cortically projecting cholinergic neurons, plays a crucial role in higher cognitive processes and has been implicated in diverse neuropsychiatric disorders. A distinct corticotopic organization of CBF projections has been revealed in animal studies, but little is known about their organization in the human brain. We explored regional differences in functional connectivity (FC) profiles within the human CBF by applying a clustering approach to resting-state functional magnetic resonance imaging (rs-fMRI) data of healthy adult individuals (N = 85; 19-85 years). We further examined effects of age on FC of the identified CBF clusters and assessed the reproducibility of cluster-specific FC profiles in independent data from healthy older individuals (N = 25; 65-89 years). Results showed that the human CBF is functionally organized into distinct anterior-medial and posterior-lateral subdivisions that largely follow anatomically defined boundaries of the medial septum/diagonal band and nucleus basalis Meynert. The anterior-medial CBF subdivision was characterized by connectivity with the hippocampus and interconnected nodes of an extended medial cortical memory network, whereas the posterior-lateral subdivision was specifically connected to anterior insula and dorsal anterior cingulate components of a salience/attention network. FC of both CBF subdivisions declined with increasing age, but the overall topography of subregion-specific FC profiles was reproduced in independent rs-fMRI data of healthy older individuals acquired in a typical clinical setting. Rs-fMRI-based assessments of subregion-specific CBF function may complement established volumetric approaches for the in vivo study of CBF involvement in neuropsychiatric disorders.

The European DTI Study on Dementia - A multicenter DTI and MRI study on Alzheimer's disease and Mild Cognitive Impairment.

The European DTI Study on Dementia (EDSD) is a multicenter framework created to study the diagnostic accuracy and inter-site variability of DTI-derived markers in patients with manifest and prodromal Alzheimer's disease (AD). The dynamically growing database presently includes 493 DTI, 512 T1-weighted MRI, and 300 FLAIR scans from patients with AD dementia, patients with Mild Cognitive Impairment (MCI) and matched Healthy Controls, acquired on 13 different scanner platforms. The imaging data is publicly available, along with the subjects' demographic and clinical characterization. Detailed neuropsychological information, cerebrospinal fluid information on biomarkers and clinical follow-up diagnoses are included for a subset of subjects. This paper describes the rationale and structure of the EDSD, summarizes the available data, and explains how to gain access to the database. The EDSD is a useful database for researchers seeking to investigate the contribution of DTI to dementia diagnostics.

Measuring Cortical Connectivity in Alzheimer's Disease as a Brain Neural Network Pathology: Toward Clinical Applications.

OBJECTIVES: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer's disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. METHODS: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). RESULTS: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior-posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. CONCLUSIONS: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD.

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM.

Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying white matter tracts. Machine learning algorithms are able to automatically detect the patterns of the disease in image data, and therefore, constitute a suitable basis for automated image diagnostic systems. The question of which magnetic resonance imaging (MRI) modalities are most useful in a clinical context is as yet unresolved. We examined multimodal MRI data acquired from 28 subjects with clinically probable AD and 25 healthy controls. Specifically, we used fiber tract integrity as measured by diffusion tensor imaging (DTI), GM volume derived from structural MRI, and the graph-theoretical measures 'local clustering coefficient' and 'shortest path length' derived from resting-state functional MRI (rs-fMRI) to evaluate the utility of the three imaging methods in automated multimodal image diagnostics, to assess their individual performance, and the level of concordance between them. We ran the support vector machine (SVM) algorithm and validated the results using leave-one-out cross-validation. For the single imaging modalities, we obtained an area under the curve (AUC) of 80% for rs-fMRI, 87% for DTI, and 86% for GM volume. When it came to the multimodal SVM, we obtained an AUC of 82% using all three modalities, and 89% using only DTI measures and GM volume. Combined multimodal imaging data did not significantly improve classification accuracy compared to the best single measures alone.

The ε4 genotype of apolipoprotein E and white matter integrity in Alzheimer's disease.

BACKGROUND: In this multicenter study, we investigated a possible association between the APOE ε4 allele and white matter (WM) integrity in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). METHODS: We analyzed fractional anisotropy (FA) and mean diffusivity (MD) as indices of WM integrity in 70 AD patients (35 APOE ε4 carriers, 35 noncarriers) and 56 healthy control (HC) subjects (28 APOE ε4 carriers, 28 noncarriers). APOE ε4 carriers and noncarriers were matched for age and gender within each diagnostic group. RESULTS: We found significant effects of diagnosis (Pcorrected < .05 [FWE]; i.e., smaller FA values and larger MD values in AD patients compared with HCs) and significant effects (P < .001) of APOE ε4 carrier status on MD in HCs but not in AD subjects. CONCLUSIONS: The results indicate that APOE ε4 has a moderate effect on WM integrity in HCs, but no effect on WM integrity in manifest AD.

Contrastive Self-supervised Learning for Neurodegenerative Disorder Classification.

Neurodegenerative diseases such as Alzheimer's disease (AD) or frontotemporal lobar degeneration (FTLD) involve specific loss of brain volume, detectable in vivo using T1-weighted MRI scans. Supervised machine learning approaches classifying neurodegenerative diseases require diagnostic-labels for each sample. However, it can be difficult to obtain expert labels for a large amount of data. Self-supervised learning (SSL) offers an alternative for training machine learning models without data-labels. We investigated if the SSL models can applied to distinguish between different neurodegenerative disorders in an interpretable manner. Our method comprises a feature extractor and a downstream classification head. A deep convolutional neural network trained in a contrastive self-supervised way serves as the feature extractor, learning latent representation, while the classifier head is a single-layer perceptron. We used N=2694 T1-weighted MRI scans from four data cohorts: two ADNI datasets, AIBL and FTLDNI, including cognitively normal controls (CN), cases with prodromal and clinical AD, as well as FTLD cases differentiated into its sub-types. Our results showed that the feature extractor trained in a self-supervised way provides generalizable and robust representations for the downstream classification. For AD vs. CN, our model achieves 82% balanced accuracy on the test subset and 80% on an independent holdout dataset. Similarly, the Behavioral variant of frontotemporal dementia (BV) vs. CN model attains an 88% balanced accuracy on the test subset. The average feature attribution heatmaps obtained by the Integrated Gradient method highlighted hallmark regions, i.e., temporal gray matter atrophy for AD, and insular atrophy for BV. In conclusion, our models perform comparably to state-of-the-art supervised deep learning approaches. This suggests that the SSL methodology can successfully make use of unannotated neuroimaging datasets as training data while remaining robust and interpretable.

Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease.

We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.

Longitudinal trajectories of cognitive reserve in hypometabolic subtypes of Alzheimer's disease.

Previous studies have demonstrated resilience to AD-related neuropathology in a form of cognitive reserve (CR). In this study we investigated a relationship between CR and hypometabolic subtypes of AD, specifically the typical and the limbic-predominant subtypes. We analyzed data from 59 Aß-positive cognitively normal (CN), 221 prodromal Alzheimer's disease (AD) and 174 AD dementia participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) from ADNI and ADNIGO/2 phases. For replication, we analyzed data from 5 Aß-positive CN, 89 prodromal AD and 43 AD dementia participants from ADNI3. CR was estimated as standardized residuals in a model predicting cognition from temporoparietal grey matter volumes and covariates. Higher CR estimates predicted slower cognitive decline. Typical and limbic-predominant hypometabolic subtypes demonstrated similar baseline CR, but the results suggested a faster decline of CR in the typical subtype. These findings support the relationship between subtypes and CR, specifically longitudinal trajectories of CR. Results also underline the importance of longitudinal analyses in research on CR.

The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint.

Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer's disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer's disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline.

INTRODUCTION: We investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum. METHODS: We studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid. RESULTS: We found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline. DISCUSSION: Latent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.

Coupling of the spatial distributions between sMRI and PET reveals the progression of Alzheimer's disease.

Amyloid-beta (Aß) deposition and altered brain structure are the most relevant neuroimaging biomarkers for Alzheimer's disease (AD). However, their spatial inconsistency was always confusing and misleading. Furthermore, the relationship between this spatial inconsistency and AD progression is unclear. The current study introduced a regional radiomics similarity network (R2SN) to map structural MRI and Aß positron emission tomography (PET) images to study their cross-modal interregional coupling. A total of 790 participants (248 normal controls, 390 mild cognitive impaired patients, and 152 AD patients) with their structural MRI and PET images were studied. The results showed that global and regional R2SN coupling significantly decreased according to the severity of cognitive decline, from mild cognitive impairment to AD dementia. The global coupling patterns are discriminative between different APOE ε4, Aß, and Tau subgroups. R2SN coupling was probed for relationships with neuropsychiatric measures and peripheral biomarkers. Kaplan-Meier analysis showed that lower global coupling scores could reveal worse clinical progression of dementia. The R2SN coupling scores derived from the coupling between Aß and atrophy over individual brain regions could reflect the specific pathway of AD progression, which would be a reliable biomarker for AD.

A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study.

Background: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems. Methods: Cross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD. Findings: IBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10-16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aß (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10-14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10-15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = -0.70, p < 1 × 10-16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aß (beta = -0.26, p = 4.40 × 10-9) and CSF Tau (beta = 0.12, p = 1.02 × 10-5). Interpretation: Our findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials. Funding: Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, Beijing Natural Science Funds, the Fundamental Research Funds for the CentralUniversity, and the Startup Funds for Talents at Beijing Normal University.

Long-term environmental enrichment is associated with better fornix microstructure in older adults.

Background: Sustained environmental enrichment (EE) through a variety of leisure activities may decrease the risk of developing Alzheimer's disease. This cross-sectional cohort study investigated the association between long-term EE in young adulthood through middle life and microstructure of fiber tracts associated with the memory system in older adults. Methods: N = 201 cognitively unimpaired participants (≥ 60 years of age) from the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) baseline cohort were included. Two groups of participants with higher (n = 104) or lower (n = 97) long-term EE were identified, using the self-reported frequency of diverse physical, intellectual, and social leisure activities between the ages 13 to 65. White matter (WM) microstructure was measured by fractional anisotropy (FA) and mean diffusivity (MD) in the fornix, uncinate fasciculus, and parahippocampal cingulum using diffusion tensor imaging. Long-term EE groups (lower/higher) were compared with adjustment for potential confounders, such as education, crystallized intelligence, and socio-economic status. Results: Reported participation in higher long-term EE was associated with greater fornix microstructure, as indicated by higher FA (standardized ß = 0.117, p = 0.033) and lower MD (ß = -0.147, p = 0.015). Greater fornix microstructure was indirectly associated (FA: unstandardized B = 0.619, p = 0.038; MD: B = -0.035, p = 0.026) with better memory function through higher long-term EE. No significant effects were found for the other WM tracts. Conclusion: Our findings suggest that sustained participation in a greater variety of leisure activities relates to preserved WM microstructure in the memory system in older adults. This could be facilitated by the multimodal stimulation associated with the engagement in a physically, intellectually, and socially enriched lifestyle. Longitudinal studies will be needed to support this assumption.

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy: A Bayesian Approach.

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.