Monocytes release cystatin F dimer to associate with Aß and aggravate amyloid pathology and cognitive deficits in Alzheimer's disease.

BACKGROUND: Understanding the molecular mechanisms of Alzheimer's disease (AD) has important clinical implications for guiding therapy. Impaired amyloid beta (Aß) clearance is critical in the pathogenesis of sporadic AD, and blood monocytes play an important role in Aß clearance in the periphery. However, the mechanism underlying the defective phagocytosis of Aß by monocytes in AD remains unclear. METHODS: Initially, we collected whole blood samples from sporadic AD patients and isolated the monocytes for RNA sequencing analysis. By establishing APP/PS1 transgenic model mice with monocyte-specific cystatin F overexpression, we assessed the influence of monocyte-derived cystatin F on AD development. We further used a nondenaturing gel to identify the structure of the secreted cystatin F in plasma. Flow cytometry, enzyme-linked immunosorbent assays and laser scanning confocal microscopy were used to analyse the internalization of Aß by monocytes. Pull down assays, bimolecular fluorescence complementation assays and total internal reflection fluorescence microscopy were used to determine the interactions and potential interactional amino acids between the cystatin F protein and Aß. Finally, the cystatin F protein was purified and injected via the tail vein into 5XFAD mice to assess AD pathology. RESULTS: Our results demonstrated that the expression of the cystatin F protein was specifically increased in the monocytes of AD patients. Monocyte-derived cystatin F increased Aß deposition and exacerbated cognitive deficits in APP/PS1 mice. Furthermore, secreted cystatin F in the plasma of AD patients has a dimeric structure that is closely related to clinical signs of AD. Moreover, we noted that the cystatin F dimer blocks the phagocytosis of Aß by monocytes. Mechanistically, the cystatin F dimer physically interacts with Aß to inhibit its recognition and internalization by monocytes through certain amino acid interactions between the cystatin F dimer and Aß. We found that high levels of the cystatin F dimer protein in blood contributed to amyloid pathology and cognitive deficits as a risk factor in 5XFAD mice. CONCLUSIONS: Our findings highlight that the cystatin F dimer plays a crucial role in regulating Aß metabolism via its peripheral clearance pathway, providing us with a potential biomarker for diagnosis and potential target for therapeutic intervention.

Prenatal treatment with preimplantation factor improves early postnatal neurogenesis and cognitive impairments in a mouse model of Down syndrome.

Down syndrome (DS) is a genetic disease characterized by a supernumerary chromosome 21. Intellectual deficiency (ID) is one of the most prominent features of DS. Central nervous system defects lead to learning disabilities, motor and language delays, and memory impairments. At present, a prenatal treatment for the ID in DS is lacking. Subcutaneous administration of synthetic preimplantation factor (sPIF, a peptide with a range of biological functions) in a model of severe brain damage has shown neuroprotective and anti-inflammatory properties by directly targeting neurons and microglia. Here, we evaluated the effect of PIF administration during gestation and until weaning on Dp(16)1Yey mice (a mouse model of DS). Possible effects at the juvenile stage were assessed using behavioral tests and molecular and histological analyses of the brain. To test the influence of perinatal sPIF treatment at the adult stage, hippocampus-dependent memory was evaluated on postnatal day 90. Dp(16)1Yey pups showed significant behavioral impairment, with impaired neurogenesis, microglial cell activation and a low microglial cell count, and the deregulated expression of genes linked to neuroinflammation and cell cycle regulation. Treatment with sPIF restored early postnatal hippocampal neurogenesis, with beneficial effects on astrocytes, microglia, inflammation, and cell cycle markers. Moreover, treatment with sPIF restored the level of DYRK1A, a protein that is involved in cognitive impairments in DS. In line with the beneficial effects on neurogenesis, perinatal treatment with sPIF was associated with an improvement in working memory in adult Dp(16)1Yey mice. Perinatal treatment with sPIF might be an option for mitigating cognitive impairments in people with DS.

Cognitive impairment and hippocampal neuronal damage in ß-thalassaemia mice.

ß-Thalassaemia is one of the most common genetic diseases worldwide. During the past few decades, life expectancy of patients has increased significantly owing to advance in medical treatments. Cognitive impairment, once has been neglected, has gradually become more documented. Cognitive impairment in ß-thalassaemia patients is associated with natural history of the disease and socioeconomic factors. Herein, to determined effect of ß-thalassaemia intrinsic factors, 22-month-old ß-thalassaemia mouse was used as a model to assess cognitive impairment and to investigate any aberrant brain pathology in ß-thalassaemia. Open field test showed that ß-thalassaemia mice had decreased motor function. However, no difference of neuronal degeneration in primary motor cortex, layer 2/3 area was found. Interestingly, impaired learning and memory function accessed by a Morris water maze test was observed and correlated with a reduced number of living pyramidal neurons in hippocampus at the CA3 region in ß-thalassaemia mice. Cognitive impairment in ß-thalassaemia mice was significantly correlated with several intrinsic ß-thalassaemic factors including iron overload, anaemia, damaged red blood cells (RBCs), phosphatidylserine (PS)-exposed RBC large extracellular vesicles (EVs) and PS-exposed medium EVs. This highlights the importance of blood transfusion and iron chelation in ß-thalassaemia patients. In addition, to improve patients' quality of life, assessment of cognitive functions should become part of routine follow-up.

Predicting Alzheimer's progression in MCI: a DTI-based white matter network model.

OBJECTIVE: This study aimed to identify features of white matter network attributes based on diffusion tensor imaging (DTI) that might lead to progression from mild cognitive impairment (MCI) and construct a comprehensive model based on these features for predicting the population at high risk of progression to Alzheimer's disease (AD) in MCI patients. METHODS: This study enrolled 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among them, 36 progressed to AD after four years of follow-up. A brain network was constructed for each patient based on white matter fiber tracts, and network attribute features were extracted. White matter network features were downscaled, and white matter markers were constructed using an integrated downscaling approach, followed by forming an integrated model with clinical features and performance evaluation. RESULTS: APOE4 and ADAS scores were used as independent predictors and combined with white matter network markers to construct a comprehensive model. The diagnostic efficacy of the comprehensive model was 0.924 and 0.919, sensitivity was 0.864 and 0.900, and specificity was 0.871 and 0.815 in the training and test groups, respectively. The Delong test showed significant differences (P < 0.05) in the diagnostic efficacy of the combined model and APOE4 and ADAS scores, while there was no significant difference (P > 0.05) between the combined model and white matter network biomarkers. CONCLUSIONS: A comprehensive model constructed based on white matter network markers can identify MCI patients at high risk of progression to AD and provide an adjunct biomarker helpful in early AD detection.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

OBJECTIVE: This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). METHODS: Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. RESULTS: A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. CONCLUSION: The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Interaction of high-fat diet and brain trauma alters adipose tissue macrophages and brain microglia associated with exacerbated cognitive dysfunction.

Obesity increases the morbidity and mortality of traumatic brain injury (TBI). Detailed analyses of transcriptomic changes in the brain and adipose tissue were performed to elucidate the interactive effects between high-fat diet-induced obesity (DIO) and TBI. Adult male mice were fed a high-fat diet (HFD) for 12 weeks prior to experimental TBI and continuing after injury. High-throughput transcriptomic analysis using Nanostring panels of the total visceral adipose tissue (VAT) and cellular components in the brain, followed by unsupervised clustering, principal component analysis, and IPA pathway analysis were used to determine shifts in gene expression patterns and molecular pathway activity. Cellular populations in the cortex and hippocampus, as well as in VAT, during the chronic phase after combined TBI-HFD showed amplification of central and peripheral microglia/macrophage responses, including superadditive changes in selected gene expression signatures and pathways. Furthermore, combined TBI and HFD caused additive dysfunction in Y-Maze, Novel Object Recognition (NOR), and Morris water maze (MWM) cognitive function tests. These novel data suggest that HFD-induced obesity and TBI can independently prime and support the development of altered states in brain microglia and VAT, including the disease-associated microglia/macrophage (DAM) phenotype observed in neurodegenerative disorders. The interaction between HFD and TBI promotes a shift toward chronic reactive microglia/macrophage transcriptomic signatures and associated pro-inflammatory disease-altered states that may, in part, underlie the exacerbation of cognitive deficits. Thus, targeting of HFD-induced reactive cellular phenotypes, including in peripheral adipose tissue immune cell populations, may serve to reduce microglial maladaptive states after TBI, attenuating post-traumatic neurodegeneration and neurological dysfunction.

Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition: Insights from a Long-Term Follow-up.

BACKGROUND AND PURPOSE: There is a paucity of data on long-term neuroimaging findings from individuals who have developed the post-coronavirus 2019 (COVID-19) condition. Only 2 studies have investigated the correlations between cognitive assessment results and structural MR imaging in this population. This study aimed to elucidate the long-term cognitive outcomes of participants with the post-COVID-19 condition and to correlate these cognitive findings with structural MR imaging data in the post-COVID-19 condition. MATERIALS AND METHODS: A cohort of 53 participants with the post-COVID-19 condition underwent 3T brain MR imaging with T1 and FLAIR sequences obtained a median of 1.8 years after Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection. A comprehensive neuropsychological battery was used to assess several cognitive domains in the same individuals. Correlations between cognitive domains and whole-brain voxel-based morphometry were performed. Different ROIs from FreeSurfer were used to perform the same correlations with other neuroimaging features. RESULTS: According to the Frascati criteria, more than one-half of the participants had deficits in the attentional (55%, n = 29) and executive (59%, n = 31) domains, while 40% (n = 21) had impairment in the memory domain. Only 1 participant (1.89%) showed problems in the visuospatial and visuoconstructive domains. We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain. CONCLUSIONS: Our findings suggest that cognitive impairment in individuals with the post-COVID-19 condition is associated with long-term alterations in the structure of the brain. These macrostructural changes may provide insight into the nature of cognitive symptoms.

Structural white matter properties and cognitive resilience to tau pathology.

INTRODUCTION: We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS: We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-ß/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS: Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION: White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS: Aß and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study.

BACKGROUND: In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. METHODS: In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. FINDINGS: We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. INTERPRETATION: Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. FUNDING: None.

Frontal Cortex Lipid Alterations During the Onset of Alzheimer's Disease.

Background: Although sporadic Alzheimer's disease (AD) is a neurodegenerative disorder of unknown etiology, familial AD is associated with specific gene mutations. A commonality between these forms of AD is that both display multiple pathogenic events including cholinergic and lipid dysregulation. Objective: We aimed to identify the relevant lipids and the activity of their related receptors in the frontal cortex and correlating them with cognition during the progression of AD. Methods: MALDI-mass spectrometry imaging (MSI) and functional autoradiography was used to evaluate the distribution of phospholipids/sphingolipids and the activity of cannabinoid 1 (CB1), sphingosine 1-phosphate 1 (S1P1), and muscarinic M2/M4 receptors in the frontal cortex (FC) of people that come to autopsy with premortem clinical diagnosis of AD, mild cognitive impairment (MCI), and no cognitive impairment (NCI). Results: MALDI-MSI revealed an increase in myelin-related lipids, such as diacylglycerol (DG) 36:1, DG 38:5, and phosphatidic acid (PA) 40:6 in the white matter (WM) in MCI compared to NCI, and a downregulation of WM phosphatidylinositol (PI) 38:4 and PI 38:5 levels in AD compared to NCI. Elevated levels of phosphatidylcholine (PC) 32:1, PC 34:0, and sphingomyelin 38:1 were observed in discrete lipid accumulations in the FC supragranular layers during disease progression. Muscarinic M2/M4 receptor activation in layers V-VI decreased in AD compared to MCI. CB1 receptor activity was upregulated in layers V-VI, while S1P1 was downregulated within WM in AD relative to NCI. Conclusions: FC WM lipidomic alterations are associated with myelin dyshomeostasis in prodromal AD, suggesting WM lipid maintenance as a potential therapeutic target for dementia.

Amyloid-ß prediction machine learning model using source-based morphometry across neurocognitive disorders.

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aß) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aß-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aß-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.

White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition.

BACKGROUND: White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS: In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS: Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION: Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.

Neuroanatomical Correlates of Cognitive Dysfunction in 22q11.2 Deletion Syndrome.

22q11.2 Deletion Syndrome (22q11.2DS), the most common chromosomal microdeletion, presents as a heterogeneous phenotype characterized by an array of anatomical, behavioral, and cognitive abnormalities. Individuals with 22q11.2DS exhibit extensive cognitive deficits, both in overall intellectual capacity and focal challenges in executive functioning, attentional control, perceptual abilities, motor skills, verbal processing, as well as socioemotional operations. Heterogeneity is an intrinsic factor of the deletion's clinical manifestation in these cognitive domains. Structural imaging has identified significant changes in volume, thickness, and surface area. These alterations are closely linked and display region-specific variations with an overall increase in abnormalities following a rostral-caudal gradient. Despite the extensive literature developing around the neurocognitive and neuroanatomical profiles associated with 22q11.2DS, comparatively little research has addressed specific structure-function relationships between aberrant morphological features and deficient cognitive processes. The current review attempts to categorize these limited findings alongside comparisons to populations with phenotypic and structural similarities in order to answer to what degree structural findings can explain the characteristic neurocognitive deficits seen in individuals with 22q11.2DS. In integrating findings from structural neuroimaging and cognitive assessments, this review seeks to characterize structural changes associated with the broad neurocognitive challenges faced by individuals with 22q11.2DS.

Is white matter hyperintensity burden associated with cognitive and motor impairment in patients with parkinson's disease? A systematic review and meta-analysis.

White matter damage quantified as white matter hyperintensities (WMH) may aggravate cognitive and motor impairments, but whether and how WMH burden impacts these problems in Parkinson's disease (PD) is not fully understood. This study aimed to examine the association between WMH and cognitive and motor performance in PD through a systematic review and meta-analysis. We compared the WMH burden across the cognitive spectrum (cognitively normal, mild cognitive impairment, dementia) in PD including controls. Motor signs were compared in PD with low/negative and high/positive WMH burden. We compared baseline WMH burden of PD who did and did not convert to MCI or dementia. MEDLINE and EMBASE databases were used to conduct the literature search resulting in 50 studies included for data extraction. Increased WMH burden was found in individuals with PD compared with individuals without PD (i.e. control) and across the cognitive spectrum in PD (i.e. PD, PD-MCI, PDD). Individuals with PD with high/positive WMH burden had worse global cognition, executive function, and attention. Similarly, PD with high/positive WMH presented worse motor signs compared with individuals presenting low/negative WMH burden. Only three longitudinal studies were retrieved from our search and they showed that PD who converted to MCI or dementia, did not have significantly higher WMH burden at baseline, although no data was provided on WMH burden changes during the follow up. We conclude, based on cross-sectional studies, that WMH burden appears to increase with PD worse cognitive and motor status in PD.

Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer's Disease.

Background: Being able to differentiate mild cognitive impairment (MCI) patients who would eventually convert (MCIc) to Alzheimer's disease (AD) from those who would not (MCInc) is a key challenge for prognosis. Objective: This study aimed to investigate the ability of sulcal morphometry to predict MCI progression to AD, dedicating special attention to an accurate identification of sulci. Methods: Twenty-five AD patients, thirty-seven MCI and twenty-five healthy controls (HC) underwent a brain-MR protocol (1.5T scanner) including a high-resolution T1-weighted sequence. MCI patients underwent a neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 2.3 years. At follow-up, 12 MCI were classified as MCInc and 25 as MCIc. Sulcal morphometry was investigated using the BrainVISA framework. Consistency of sulci across subjects was ensured by visual inspection and manual correction of the automatic labelling in each subject. Sulcal surface, depth, length, and width were retrieved from 106 sulci. Features were compared across groups and their classification accuracy in predicting MCI conversion was tested. Potential relationships between sulcal features and cognitive scores were explored using Spearman's correlation. Results: The width of sulci in the temporo-occipital region strongly differentiated between each pair of groups. Comparing MCIc and MCInc, the width of several sulci in the bilateral temporo-occipital and left frontal areas was significantly altered. Higher width of frontal sulci was associated with worse performances in short-term verbal memory and phonemic fluency. Conclusions: Sulcal morphometry emerged as a strong tool for differentiating HC, MCI, and AD, demonstrating its potential prognostic value for the MCI population.

Impaired Glymphatic Flow on Diffusion Tensor MRI as a Marker of Neurodegeneration in Alzheimer's Disease: Correlation with Gray Matter Volume Loss and Cognitive Decline Independent of Cerebral Amyloid Deposition.

Background: Impaired glymphatic flow on the Alzheimer's disease (AD) spectrum may be evaluated using diffusion tensor image analysis along the perivascular space (DTI-ALPS). Objective: We aimed to validate impaired glymphatic flow and explore its association with gray matter volume, cognitive status, and cerebral amyloid deposition on the AD spectrum. Methods: 80 participants (mean age, 76.9±8.5 years; 57 women) with AD (n = 65) and cognitively normal (CN) (n = 15) who underwent 3T brain MRI including DTI and/or amyloid PET were included. After adjusting for age, sex, apolipoprotein E status, and burden of white matter hyperintensities, the ALPS-index was compared according to the AD spectrum. The association between the ALPS-index and gray matter volume, cognitive status, and quantitative amyloid from PET was assessed. Results: The ALPS-index in the AD was significantly lower (mean, 1.476; 95% CI, 1.395-1.556) than in the CN (1.784;1.615-1.952; p = 0.026). Volumes of the entorhinal cortex, hippocampus, temporal pole, and primary motor cortex showed significant associations with the ALPS-index (all, p < 0.05). There was a positive correlation between the ALPS-index and MMSE score (partial r = 0.435; p < 0.001), but there was no significant correlation between the ALPS-index and amyloid SUVRs (all, p > 0.05). Conclusions: Decreased glymphatic flow measured by DTI-ALPS in AD may serve as a marker of neurodegeneration correlating with structural atrophy and cognitive decline.

Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study.

BACKGROUND: Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early detection of MCI. On the other hand, magnetic resonance imaging (MRI) biomarkers have demonstrated their efficacy in quantifying observable structural brain changes that can aid in early MCI detection. Nevertheless, the relationship between VR-derived and MRI biomarkers remains an open question. In this context, we explored the integration of VR-derived and MRI biomarkers to enhance early MCI detection through a multimodal learning approach. OBJECTIVE: We aimed to evaluate and compare the efficacy of VR-derived and MRI biomarkers in the classification of MCI while also examining the strengths and weaknesses of each approach. Furthermore, we focused on improving early MCI detection by leveraging multimodal learning to integrate VR-derived and MRI biomarkers. METHODS: The study encompassed a total of 54 participants, comprising 22 (41%) healthy controls and 32 (59%) patients with MCI. Participants completed a virtual kiosk test to collect 4 VR-derived biomarkers (hand movement speed, scanpath length, time to completion, and the number of errors), and T1-weighted MRI scans were performed to collect 22 MRI biomarkers from both hemispheres. Analyses of covariance were used to compare these biomarkers between healthy controls and patients with MCI, with age considered as a covariate. Subsequently, the biomarkers that exhibited significant differences between the 2 groups were used to train and validate a multimodal learning model aimed at early screening for patients with MCI among healthy controls. RESULTS: The support vector machine (SVM) using only VR-derived biomarkers achieved a sensitivity of 87.5% and specificity of 90%, whereas the MRI biomarkers showed a sensitivity of 90.9% and specificity of 71.4%. Moreover, a correlation analysis revealed a significant association between MRI-observed brain atrophy and impaired performance in instrumental activities of daily living in the VR environment. Notably, the integration of both VR-derived and MRI biomarkers into a multimodal SVM model yielded superior results compared to unimodal SVM models, achieving higher accuracy (94.4%), sensitivity (100%), specificity (90.9%), precision (87.5%), and F1-score (93.3%). CONCLUSIONS: The results indicate that VR-derived biomarkers, characterized by their high specificity, can be valuable as a robust, early screening tool for MCI in a broader older adult population. On the other hand, MRI biomarkers, known for their high sensitivity, excel at confirming the presence of MCI. Moreover, the multimodal learning approach introduced in our study provides valuable insights into the improvement of early MCI detection by integrating a diverse set of biomarkers.

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease.

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aß-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aß-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

The time course of motor and cognitive decline in older adults and their associations with brain pathologies: a multicohort study.

BACKGROUND: Many studies have reported that impaired gait precedes cognitive impairment in older people. We aimed to characterise the time course of cognitive and motor decline in older individuals and the association of these declines with the pathologies of Alzheimer's disease and related dementias. METHODS: This multicohort study used data from three community-based cohort studies (Religious Orders Study, Rush Memory and Aging Project, and Minority Aging Research Study, all in the USA). The inclusion criteria for all three cohorts were no clinical dementia at the time of enrolment and consent to annual clinical assessments. Eligible participants consented to post-mortem brain donation and had post-mortem pathological assessments and three or more repeated annual measures of cognition and motor functions. Clinical and post-mortem data were analysed using functional mixed-effects models. Global cognition was based on 19 neuropsychological tests, a hand strength score was based on grip and pinch strength, and a gait score was based on the number of steps and time to walk 8 feet and turn 360°. Brain pathologies of Alzheimer's disease and related dementias were assessed at autopsy. FINDINGS: From 1994 to 2022, there were 1570 eligible cohort participants aged 65 years or older, 1303 of whom had cognitive and motor measurements and were included in the analysis. Mean age at death was 90·3 years (SD 6·3), 905 (69%) participants were female, and 398 (31%) were male. Median follow-up time was 9 years (IQR 5-11). On average, cognition was stable from 25 to 15 years before death, when cognition began to decline. By contrast, gait function and hand strength declined during the entire study. The combinations of pathologies of Alzheimer's disease and related dementias associated with cognitive and motor decline and their onsets of associations varied; only tau tangles, Parkinson's disease pathology, and macroinfarcts were associated with decline of all three phenotypes. Tau tangles were significantly associated with cognitive decline, gait function decline, and hand function decline (p<0·0001 for each); however, the association with cognitive decline persisted for more than 11 years before death, but the association with hand strength only began 3·57 years before death and the association with gait began 3·49 years before death. By contrast, the association of macroinfarcts with declining gait function began 9·25 years before death (p<0·0001) compared with 6·65 years before death (p=0·0005) for cognitive decline and 2·66 years before death (p=0·024) for decline in hand strength. INTERPRETATION: Our findings suggest that average motor decline in older adults precedes cognitive decline. Macroinfarcts but not tau tangles are associated with declining gait function that precedes cognitive decline. This suggests the need for further studies to test if gait impairment is a clinical proxy for preclinical vascular cognitive impairment. FUNDING: National Institutes of Health.

Degeneration in Nucleus basalis of Meynert signals earliest stage of Alzheimer's disease progression.

Nucleus Basalis of Meynert (NbM), a crucial source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), has shown sensitivity to neurofibrillary degeneration in the early stages of Alzheimer's Disease. Using deformation-based morphometry (DBM) on up-sampled MRI scans from 1447 Alzheimer's Disease Neuroimaging Initiative participants, we aimed to quantify NbM degeneration along the disease trajectory. Results from cross-sectional analysis revealed significant differences of NbM volume between cognitively normal and early mild cognitive impairment cohorts, confirming recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. Longitudinal linear mixed-effect models were then used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results indicated the earliest deviations in NbM volumes from the cognitively healthy trajectory, challenging the prevailing idea that Alzheimer's originates in the EC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.