Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis.

BACKGROUND: Measurement of beta-amyloid (Aß) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination. METHODS: A systematic search of prospective and retrospective studies investigating the association of Aß and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature. RESULTS: A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aß42 or Aß42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aß exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]). CONCLUSIONS: Identifying Aß-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aß, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aß decreases with age. TRIAL REGISTRATION: The study was registered in PROSPERO (ID: CRD42021288100).

Relationship of Perivascular Space Markers With Incident Dementia in Cerebral Small Vessel Disease.

BACKGROUND: Recent studies, using diffusion tensor image analysis along the perivascular space (DTI-ALPS), suggest impaired perivascular space (PVS) function in cerebral small vessel disease, but they were cross-sectional, making inferences on causality difficult. We determined associations between impaired PVS, measured using DTI-ALPS and PVS volume, and cognition and incident dementia. METHODS: In patients with lacunar stroke and confluent white matter hyperintensities, without dementia at baseline, recruited prospectively in a single center, magnetic resonance imaging was performed annually for 3 years, and cognitive assessments, including global, memory, executive function, and processing speed, were performed annually for 5 years. We determined associations between DTI-ALPS and PVS volume with cerebral small vessel disease imaging markers (white matter hyperintensity volume, lacunes, and microbleeds) at baseline and with changes in imaging markers. We determined whether DTI-ALPS and PVS volume at baseline and change over 3 years predicted incident dementia. Analyses were controlled for conventional diffusion tensor image metrics using 2 markers (median mean diffusivity [MD] and peak width of skeletonized MD) and adjusted for age, sex, and vascular risk factors. RESULTS: A total of 120 patients, mean age 70.0 years and 65.0% male, were included. DTI-ALPS declined over 3 years, while no change in PVS volume was found. Neither DTI-ALPS nor PVS volume was associated with cerebral small vessel disease imaging marker progression. Baseline DTI-ALPS was associated with changes in global cognition (ß=0.142, P=0.032), executive function (ß=0.287, P=0.027), and long-term memory (ß=0.228, P=0.027). Higher DTI-ALPS at baseline predicted a lower risk of dementia (hazard ratio, 0.328 [0.183-0.588]; P<0.001), and this remained significant after including median MD as a covariate (hazard ratio, 0.290 [0.139-0.602]; P<0.001). Change in DTI-ALPS predicted dementia conversion (hazard ratio, 0.630 [0.428-0.964]; P=0.048), but when peak width of skeletonized MD and median MD were entered as covariates, the association was not significant. There was no association between baseline PVS volume, or PVS change over 3 years, and conversion to dementia. CONCLUSIONS: DTI-ALPS predicts future dementia risk in patients with lacunar strokes and confluent white matter hyperintensities. However, the weakening of the association between change in DTI-ALPS and incident dementia after controlling for peak width of skeletonized MD and median MD suggests part of the signal may represent conventional diffusion tensor image metrics. PVS volume is not a predictor of future dementia risk.

Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia.

Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF: accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.

The usefulness of the retina for identifying people with type 2 diabetes with prodromal stages of dementia.

Type 2 diabetes (T2D) is associated with cognitive impairment and dementia. The detection of cognitive impairment is important because this population is at higher risk of experiencing difficulties in the self-management of diabetes. Mild cognitive impairment (MCI) often remains undiagnosed due to lack of simple tools for screening at large scale. This represents an important gap in the patients' management because subjects with diabetes and MCI are at high risk of progressing to dementia. Due to its developmental origin as a brain-derived tissue, the retina has been proposed as a potential means of non-invasive and readily accessible exploration of brain pathology. Recent evidence showed that retinal imaging and/or functional tests are correlated with the cognitive function and brain changes in T2D. Simple retinal functional tests (i.e. retinal microperimetry) have proven to be useful as reliable tool for the cognitive evaluation and monitoring in patients with T2D>65 years. This review gives an overall update on the usefulness of retinal imaging in identifying patients with T2D at risk of developing dementia.

Brain artery diameters and risk of dementia and stroke.

INTRODUCTION: We tested the association of brain artery diameters with dementia and stroke risk in three distinct population-based studies using conventional T2-weighted brain magnetic resonance imaging (MRI) images. METHODS: We included 8420 adults > 40 years old from three longitudinal population-based studies with brain MRI scans. We estimated and meta-analyzed the hazard ratios (HRs) of the brain and carotids and basilar diameters associated with dementia and stroke. RESULT: Overall and carotid artery diameters > 95th percentile increased the risk for dementia by 1.74 (95% confidence interval [CI], 1.13-2.68) and 1.48 (95% CI, 1.12-1.96) fold, respectively. For stroke, meta-analyses yielded HRs of 1.59 (95% CI, 1.04-2.42) for overall arteries and 2.11 (95% CI, 1.45-3.08) for basilar artery diameters > 95th percentile. DISCUSSION: Individuals with dilated brain arteries are at higher risk for dementia and stroke, across distinct populations. Our findings underline the potential value of T2-weighted brain MRI-based brain diameter assessment in estimating the risk of dementia and stroke.

Infection, delirium, and risk of dementia in patients with and without white matter disease on previous brain imaging: a population-based study.

BACKGROUND: The increased risk of dementia after delirium and infection might be influenced by cerebral white matter disease (WMD). In patients with transient ischaemic attack (TIA) and minor stroke, we assessed associations between hospital admissions with delirium and 5-year dementia risk and between admissions with infection and dementia risk, stratified by WMD severity (moderate or severe vs absent or mild) on baseline brain imaging. METHODS: We included patients with TIA and minor stroke (National Institutes of Health Stroke Score <3) from the Oxford Vascular Study (OXVASC), a longitudinal population-based study of the incidence and outcomes of acute vascular events in a population of 94 567 individuals, with no age restrictions, attending eight general practices in Oxfordshire, UK. Hospitalisation data were obtained through linkage to the Oxford Cognitive Comorbidity, Frailty, and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR). Brain imaging was done using CT and MRI, and WMD was prospectively graded according to the age-related white matter changes (ARWMC) scale and categorised into absent, mild, moderate, or severe WMD. Delirium and infection were defined by ICD-10 coding supplemented by hand-searching of hospital records. Dementia was diagnosed using clinical or cognitive assessment, medical records, and death certificates. Associations between hospitalisation with delirium and hospitalisation with infection, and post-event dementia were assessed using time-varying Cox analysis with multivariable adjustment, and all models were stratified by WMD severity. FINDINGS: From April 1, 2002, to March 31, 2012, 1369 individuals were prospectively recruited into the study. Of 1369 patients (655 with TIA and 714 with minor stroke, mean age 72 [SD 13] years, 674 female and 695 male, and 364 with moderate or severe WMD), 209 (15%) developed dementia. Hospitalisation during follow-up occurred in 891 (65%) patients of whom 103 (12%) had at least one delirium episode and 236 (26%) had at least one infection episode. Hospitalisation without delirium or infection did not predict subsequent dementia (HR 1·01, 95% CI 0·86-1·20). In contrast, hospitalisation with delirium predicted subsequent dementia independently of infection in patients with and without WMD (2·64, 1·47-4·74; p=0·0013 vs 3·41, 1·91-6·09; p<0·0001) especially in those with unimpaired baseline cognition (cognitive test score above cutoff; 4·01, 2·23-7·19 vs 3·94, 1·95-7·93; both p≤0·0001). However, hospitalisation with infection only predicted dementia in those with moderate or severe WMD (1·75, 1·04-2·94 vs 0·68, 0·39-1·20; pdiff=0·023). INTERPRETATION: The increased risk of dementia after delirium is unrelated to the presence of WMD, whereas infection increases risk only in patients with WMD, suggesting differences in underlying mechanisms and in potential preventive strategies. FUNDING: National Institute for Health and Care Research and Wellcome Trust.

Long-Term Longitudinal Course of Cognitive and Motor Symptoms in Patients With Cerebral Small Vessel Disease.

BACKGROUND AND OBJECTIVES: Patients with cerebral small vessel disease (SVD) show a heterogenous clinical course. The aim of the current study was to investigate the longitudinal course of cognitive and motor function in patients who developed parkinsonism, dementia, both, or none. METHODS: Participants were from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study, a prospective cohort of patients with SVD. Parkinsonism and dementia were, respectively, diagnosed according to the UK Parkinson's Disease Society brain bank criteria and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria for major neurocognitive disorder. Linear and generalized linear mixed-effect analyses were used to study the longitudinal course of motor and cognitive tasks. RESULTS: After a median follow-up of 12.8 years (interquartile range 10.2-15.3), 132 of 501 (26.3%) participants developed parkinsonism, dementia, or both. Years before diagnosis of these disorders, participants showed distinct clinical trajectories from those who developed none: Participant who developed parkinsonism had an annual percentage of 22% (95% CI 18%-27%) increase in motor part of the Unified Parkinson's Disease Rating Scale score. This was significantly higher than the 16% (95% CI 14%-18%) of controls, mainly because of a steep increase in bradykinesia and posture and gait disturbances. When they developed dementia as well, the increase in Timed Up and Go Test time of 0.73 seconds per year (95% CI 0.58-0.87) was significantly higher than the 0.20 seconds per year increase (95% CI 0.16-0.23) of controls. All groups, including the participants who developed parkinsonism without dementia, showed a faster decline in executive function compared with controls: Annual decline in Z-score was -0.07 (95% CI -0.10 to -0.05), -0.09 (95% CI -0.11 to -0.08), and -0.11 (95% CI -0.14 to -0.08) for participants who developed, respectively, parkinsonism, dementia, and both parkinsonism and dementia. These declines were all significantly faster than the annual decline in Z-score of 0.07 (95% CI -0.10 to -0.05) of controls. DISCUSSION: A distinct pattern in deterioration of clinical markers is visible in patients with SVD, years before the diagnosis of parkinsonism and dementia. This knowledge aids early identification of patients with a high risk of developing these disorders.

Early prediction of dementia using fMRI data with a graph convolutional network approach.

Objective. Alzheimer's disease is a progressive neurodegenerative dementia that poses a significant global health threat. It is imperative and essential to detect patients in the mild cognitive impairment (MCI) stage or even earlier, enabling effective interventions to prevent further deterioration of dementia. This study focuses on the early prediction of dementia utilizing Magnetic Resonance Imaging (MRI) data, using the proposed Graph Convolutional Networks (GCNs).Approach. Specifically, we developed a functional connectivity (FC) based GCN framework for binary classifications using resting-state fMRI data. We explored different types and processing methods of FC and evaluated the performance on the OASIS-3 dataset. We developed the GCN model for two different purposes: (1) MCI diagnosis: classifying MCI from normal controls (NCs); and (2) dementia risk prediction: classifying NCs from subjects who have the potential for developing MCI but have not been clinically diagnosed as MCI.Main results. The results of the experiments revealed several important findings: First, the proposed GCN outperformed both the baseline GCN and Support Vector Machine (SVM). It achieved the best average accuracy of 80.3% (11.7% higher than the baseline GCN and 23.5% higher than SVM) and the highest accuracy of 91.2%. Secondly, the GCN framework with (absolute) individual FC performed slightly better than that with global FC generally. However, GCN using global graphs with appropriate connectivity can achieve equivalent or superior performance to individual graphs in some cases, which highlights the significance of suitable connectivity for achieving performance. Additionally, the results indicate that the self-network connectivity of specific brain network regions (such as default mode network, visual network, ventral attention network and somatomotor network) may play a more significant role in GCN classification.Significance. Overall, this study offers valuable insights into the application of GCNs in brain analysis and early diagnosis of dementia. This contributes significantly to the understanding of MCI and has substantial potential for clinical applications in early diagnosis and intervention for dementia and other neurodegenerative diseases. Our code for GCN implementation is available at:https://github.com/Shuning-Han/FC-based-GCN.

Common infections and neuroimaging markers of dementia in three UK cohort studies.

INTRODUCTION: We aimed to investigate associations between common infections and neuroimaging markers of dementia risk (brain volume, hippocampal volume, white matter lesions) across three population-based studies. METHODS: We tested associations between serology measures (pathogen serostatus, cumulative burden, continuous antibody responses) and outcomes using linear regression, including adjustments for total intracranial volume and scanner/clinic information (basic model), age, sex, ethnicity, education, socioeconomic position, alcohol, body mass index, and smoking (fully adjusted model). Interactions between serology measures and apolipoprotein E (APOE) genotype were tested. Findings were meta-analyzed across cohorts (Nmain  = 2632; NAPOE-interaction  = 1810). RESULTS: Seropositivity to John Cunningham virus associated with smaller brain volumes in basic models (ß = -3.89 mL [-5.81, -1.97], Padjusted  < 0.05); these were largely attenuated in fully adjusted models (ß = -1.59 mL [-3.55, 0.36], P = 0.11). No other relationships were robust to multiple testing corrections and sensitivity analyses, but several suggestive associations were observed. DISCUSSION: We did not find clear evidence for relationships between common infections and markers of dementia risk. Some suggestive findings warrant testing for replication.

Poor Oral Health Is Associated With Inflammation, Aortic Valve Calcification, and Brain Volume Among Forager-Farmers.

Poor oral health is associated with cardiovascular disease and dementia. Potential pathways include sepsis from oral bacteria, systemic inflammation, and nutritional deficiencies. However, in post-industrialized populations, links between oral health and chronic disease may be confounded because the lower socioeconomic exposome (poor diet, pollution, and low physical activity) often entails insufficient dental care. We assessed tooth loss, caries, and damaged teeth, in relation to cardiovascular and brain aging among the Tsimane, a subsistence population living a relatively traditional forager-horticulturalist lifestyle with poor dental health, but minimal cardiovascular disease and dementia. Dental health was assessed by a physician in 739 participants aged 40-92 years with cardiac and brain health measured by chest computed tomography (CT; n = 728) and brain CT (n = 605). A subset of 356 individuals aged 60+ were also assessed for dementia and mild cognitive impairment (n = 33 impaired). Tooth loss was highly prevalent, with 2.2 teeth lost per decade and a 2-fold greater loss in women. The number of teeth with exposed pulp was associated with higher inflammation, as measured by cytokine levels and white blood cell counts, and lower body mass index. Coronary artery calcium and thoracic aortic calcium were not associated with tooth loss or damaged teeth. However, aortic valve calcification and brain tissue loss were higher in those who had more teeth with exposed pulp. Overall, these results suggest that dental health is associated with indicators of chronic diseases in the absence of typical confounds, even in a population with low cardiovascular and dementia risk factors.

Association of the Sleep Regularity Index With Incident Dementia and Brain Volume.

BACKGROUND AND OBJECTIVES: Irregular sleep may increase the risk of cardiometabolic conditions, but its association with incident dementia is unclear. The aim of this study was to assess the association between sleep regularity, that is, the day-to-day consistency in sleep-wake patterns and the risk of incident dementia and related brain MRI endophenotypes. METHODS: We used Cox proportional hazard models to investigate the relationships between sleep regularity and incident dementia in 88,094 UK Biobank participants. The sleep regularity index (SRI) was calculated as the probability of being in the same state (asleep/awake) at any 2 time points 24 hours apart, averaged over 7 days of accelerometry. RESULTS: The mean age of the sample was 62 years (SD = 8), 56% were women, and the median SRI was 60 (SD = 10). There were 480 cases of incident dementia over a median 7.2 years of follow-up. Following adjustments for demographic, clinical, and genetic confounders (APOE ε4), there was a nonlinear association between the SRI and dementia hazard (p [global test of spline term] < 0.001) with hazard ratios (HRs) following a U-shape pattern. HRs, relative to the median SRI, were 1.53 (95% CI 1.24-1.89) for participants with SRI at the 5th percentile (SRI = 41) and 1.16 (95% CI 0.89-1.50) for those with SRI at the 95th percentile (SRI = 71). In a subset with brain MRI (n = 15,263), gray matter and hippocampal volume tended to be lowest at the extremes of the SRI. DISCUSSION: Sleep regularity displayed a U-shaped association with risk of incident dementia. Irregular sleep may represent a novel dementia risk factor.

Rethinking Dementia Risk Prediction: A Critical Evaluation of a Multimodal Machine Learning Predictive Model.

A recent study by Ding et al. explores the integration of artificial intelligence (AI) in predicting dementia risk over a 10-year period using a multimodal approach. While revealing the potential of machine learning models in identifying high-risk individuals through neuropsychological testing, MRI imaging, and clinical risk factors, the imperative of dynamic frailty assessment emerges for accurate late-life dementia prediction. The commentary highlights challenges associated with AI models, including dimensionality and data standardization, emphasizing the critical need for a dynamic, comprehensive approach to reflect the evolving nature of dementia and improve predictive accuracy.

Association of Plasma YKL-40 With MRI, CSF, and Cognitive Markers of Brain Health and Dementia.

BACKGROUND AND OBJECTIVES: Higher YKL-40 levels in the CSF are a known biomarker of brain inflammation. We explored the utility of plasma YKL-40 as a biomarker for accelerated brain aging and dementia risk. METHODS: We performed cross-sectional and prospective analyses of 4 community-based cohorts in the United States or Europe: the Age, Gene/Environment Susceptibility-Reykjavik Study, Atherosclerosis Risk in the Communities study, Coronary Artery Risk Development in Young Adults study, and Framingham Heart Study (FHS). YKL-40 was measured from stored plasma by a single laboratory using Mesoscale Discovery with levels log transformed and standardized within each cohort. Outcomes included MRI total brain volume, hippocampal volume, and white matter hyperintensity volume (WMHV) as a percentage of intracranial volume, a general cognitive composite derived from neuropsychological testing (SD units [SDU]), and the risk of incident dementia. We sought to replicate associations with dementia in the clinic-based ACE csf cohort, which also had YKL-40 measured from the CSF. RESULTS: Meta-analyses of MRI outcomes included 6,558 dementia-free participants, and for analysis of cognition, 6,670. The blood draw preceded MRI/cognitive assessment by up to 10.6 years across cohorts. The mean ages ranged from 50 to 76 years, with 39%-48% male individuals. In random-effects meta-analysis of study estimates, each SDU increase in log-transformed YKL-40 levels was associated with smaller total brain volume (ß = -0.33; 95% CI -0.45 to -0.22; p < 0.0001) and poorer cognition (ß = -0.04; 95% CI -0.07 to -0.02; p < 0.01), following adjustments for demographic variables. YKL-40 levels did not associate with hippocampal volume or WMHV. In the FHS, each SDU increase in log YKL-40 levels was associated with a 64% increase in incident dementia risk over a median of 5.8 years of follow-up, following adjustments for demographic variables (hazard ratio 1.64; 95% CI 1.25-2.16; p < 0.001). In the ACE csf cohort, plasma and CSF YKL-40 were correlated (r = 0.31), and both were associated with conversion from mild cognitive impairment to dementia, independent of amyloid, tau, and neurodegeneration status. DISCUSSION: Higher plasma YKL-40 levels were associated with lower brain volume, poorer cognition, and incident dementia. Plasma YKL-40 may be useful for studying the association of inflammation and its treatment on dementia risk.

Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis.

METHODS: 18F-FDG brain PET and clinical score were collected in 85 patients with dementia and 125 healthy controls (HC). Patients were assigned to various form of dementia on the basis of clinical evaluation, follow-up and voxels comparison with HC using a two-sample Student's t -test, to determine the regions of brain involved. Radiomic analysis was performed on the whole brain after normalization to an optimized template. After feature selection using the minimum redundancy maximum relevance method and Pearson's correlation coefficients, a Neural Network model was tested to find the accuracy to classify HC and demented patients. Twenty subjects not included in the training were used to test the models. The results were compared with those obtained by conventional CNN model. RESULTS: Four radiomic features were selected. The validation and test accuracies were 100% for both models, but the probability scores were higher with radiomics, in particular for HC group ( P  = 0.0004). CONCLUSION: Radiomic features extracted from standardized PET whole brain images seem to be more accurate than CNN to distinguish patients with and without dementia.

Cortical gray to white matter signal intensity ratio as a sign of neurodegeneration and cognition independent of ß-amyloid in dementia.

Cortical gray to white matter signal intensity ratio (GWR) measured from T1-weighted magnetic resonance (MR) images was associated with neurodegeneration and dementia. We characterized topological patterns of GWR during AD pathogenesis and investigated its association with cognitive decline. The study included a cross-sectional dataset and a longitudinal dataset. The cross-sectional dataset included 60 cognitively healthy controls, 61 mild cognitive impairment (MCI), and 63 patients with dementia. The longitudinal dataset included 26 participants who progressed from cognitively normal to dementia and 26 controls that remained cognitively normal. GWR was compared across the cross-sectional groups, adjusted for amyloid PET. The correlation between GWR and cognition performance was also evaluated. The longitudinal dataset was used to investigate GWR alteration during the AD pathogenesis. Dementia with ß-amyloid deposition group exhibited the largest area of increased GWR, followed by MCI with ß-amyloid deposition, MCI without ß-amyloid deposition, and controls. The spatial pattern of GWR-increased regions was not influenced by ß-amyloid deposits. Correlation between regional GWR alteration and cognitive decline was only detected among individuals with ß-amyloid deposition. GWR showed positive correlation with tau PET in the left supramarginal, lateral occipital gyrus, and right middle frontal cortex. The longitudinal study showed that GWR increased around the fusiform, inferior/superior temporal lobe, and entorhinal cortex in MCI and progressed to larger cortical regions after progression to AD. The spatial pattern of GWR-increased regions was independent of ß-amyloid deposits but overlapped with tauopathy. The GWR can serve as a promising biomarker of neurodegeneration in AD.

Neuroinflammation is linked to dementia risk in Parkinson's disease.

The development of dementia is a devastating aspect of Parkinson's disease (PD), affecting nearly half of patients within 10 years post-diagnosis. For effective therapies to prevent and slow progression to PD dementia (PDD), the key mechanisms that determine why some people with PD develop early dementia, while others remain cognitively unaffected, need to be understood. Neuroinflammation and tau protein accumulation have been demonstrated in post-mortem PD brains, and in many other neurodegenerative disorders leading to dementia. However, whether these processes mediate dementia risk early on in the PD disease course is not established. To this end, we used PET neuroimaging with 11C-PK11195 to index neuroinflammation and 18F-AV-1451 for misfolded tau in early PD patients, stratified according to dementia risk in our 'Neuroinflammation and Tau Accumulation in Parkinson's Disease Dementia' (NET-PDD) study. The NET-PDD study longitudinally assesses newly-diagnosed PD patients in two subgroups at low and high dementia risk (stratified based on pentagon copying, semantic fluency, MAPT genotype), with comparison to age- and sex-matched controls. Non-displaceable binding potential (BPND) in 43 brain regions (Hammers' parcellation) was compared between groups (pairwise t-tests), and associations between BPND of the tracers tested (linear-mixed-effect models). We hypothesized that people with higher dementia risk have greater inflammation and/or tau accumulation in advance of significant cognitive decline. We found significantly elevated neuroinflammation (11C-PK11195 BPND) in multiple subcortical and restricted cortical regions in the high dementia risk group compared with controls, while in the low-risk group this was limited to two cortical areas. The high dementia risk group also showed significantly greater neuroinflammation than the low-risk group concentrated on subcortical and basal ganglia regions. Neuroinflammation in most of these regions was associated with worse cognitive performance (Addenbrooke's Cognitive Examination-III score). Overall neuroinflammation burden also correlated with serum levels of pro-inflammatory cytokines. In contrast, increases in 18F-AV-1451 (tau) BPND in PD versus controls were restricted to subcortical regions where off-target binding is typically seen, with no relationship to cognition found. Whole-brain 18F-AV-1451 burden correlated with serum phosphorylated tau181 levels. Although there was minimal regional tau accumulation in PD, regional neuroinflammation and tau burden correlated in PD participants, with the strongest association in the high dementia risk group, suggesting possible co-localization of these pathologies. In conclusion, our findings suggest that significant regional neuroinflammation in early PD might underpin higher risk for PDD development, indicating neuroinflammation as a putative early modifiable aetiopathological disease factor to prevent or slow dementia development using immunomodulatory strategies.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk.

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS: We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Association between structural brain MRI abnormalities and epilepsy in older adults.

OBJECTIVE: To determine the association between brain MRI abnormalities and incident epilepsy in older adults. METHODS: Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status. RESULTS: Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3). INTERPRETATION: This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.

Magnetic resonance image-based brain age as a discriminator of dementia conversion in patients with amyloid-negative amnestic mild cognitive impairment.

Patients with amyloid-negative amnestic mild cognitive impairment (MCI) have a conversion rate of approximately 10% to dementia within 2 years. We aimed to investigate whether brain age is an important factor in predicting conversion to dementia in patients with amyloid-negative amnestic MCI. We conducted a retrospective cohort study of patients with amyloid-negative amnestic MCI. All participants underwent detailed neuropsychological evaluation, brain magnetic resonance imaging (MRI), and [18F]-florbetaben positron emission tomography. Brain age was determined by the volumetric assessment of 12 distinct brain regions using an automatic segmentation software. During the follow-up period, 38% of the patients converted from amnestic MCI to dementia. Further, 73% of patients had a brain age greater than their actual chronological age. When defining 'survival' as the non-conversion of MCI to dementia, these groups differed significantly in survival probability (p = 0.036). The low-educated female group with a brain age greater than their actual age had the lowest survival rate among all groups. Our findings suggest that the MRI-based brain age used in this study can contribute to predicting conversion to dementia in patients with amyloid-negative amnestic MCI.