Dynamic multilayer functional connectivity detects preclinical and clinical Alzheimer's disease.

Increasing evidence suggests that patients with Alzheimer's disease present alterations in functional connectivity but previous results have not always been consistent. One of the reasons that may account for this inconsistency is the lack of consideration of temporal dynamics. To address this limitation, here we studied the dynamic modular organization on resting-state functional magnetic resonance imaging across different stages of Alzheimer's disease using a novel multilayer brain network approach. Participants from preclinical and clinical Alzheimer's disease stages were included. Temporal multilayer networks were used to assess time-varying modular organization. Logistic regression models were employed for disease stage discrimination, and partial least squares analyses examined associations between dynamic measures with cognition and pathology. Temporal multilayer functional measures distinguished all groups, particularly preclinical stages, overcoming the discriminatory power of risk factors such as age, sex, and APOE ϵ4 carriership. Dynamic multilayer functional measures exhibited strong associations with cognition as well as amyloid and tau pathology. Dynamic multilayer functional connectivity shows promise as a functional imaging biomarker for both early- and late-stage Alzheimer's disease diagnosis.

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging.

BACKGROUND: Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. METHODS: A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. RESULTS: Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). CONCLUSION: The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

Social Health and Cognitive Change in Old Age: Role of Brain Reserve.

OBJECTIVE: Individual aspects of social health (SH; eg, network, engagement, support) have been linked to cognitive health. However, their combined effect and the role of the structural properties of the brain (brain reserve [BR]) remain unclear. We investigated the interplay of SH and BR on cognitive change in older adults. METHODS: Within the Swedish National Study on Aging and Care-Kungsholmen, 368 dementia-free adults aged ≥60 years with baseline brain magnetic resonance imaging were followed over 12 years to assess cognitive change. A measure of global cognition was computed at each of the 5 waves of assessment by averaging domain-specific Z scores for episodic memory, perceptual speed, semantic memory, and letter and category fluency. An SH composite score was computed at baseline by combining leisure activities and social network. BR was proxied by total brain tissue volume (TBTV). Linear mixed models (adjusted for sociodemographic, vascular, and genetic factors) were used to estimate cognitive trajectories in relation to SH and TBTV. Interaction analysis and stratification were used to examine the interplay between SH and TBTV. RESULTS: Moderate-good SH (n = 245; vs poor, ß-slope = 0.01, 95% confidence interval [CI] = 0.002-0.02, p = 0.018) and moderate-to-large TBTV (n = 245; vs small, ß-slope = 0.03, 95% CI = 0.02-0.04, p < 0.001) were separately associated with slower cognitive decline. In stratified analysis, moderate-good SH was associated with higher cognitive levels (but not change) only in participants with moderate-to-large TBTV (ß-intercept = 0.21, 95% CI = 0.06-0.37, p < 0.01; interaction SH * TBTV, p < 0.05). INTERPRETATION: Our findings highlight the interplay between SH and BR that likely unfolds throughout the entire life course to shape old-age cognitive outcomes. ANN NEUROL 2023;93:844-855.

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.

Effects of current alcohol use on brain volume among older adults in the Gothenburg H70 Birth Cohort study 2014-16.

Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014-16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0-50 g/week, used as reference group, 51-100 g/week, 101-150 g/week, 151-200 g/week, 201-250 g/week, 251-300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week.

Long-term effects of cholinesterase inhibitors and memantine on cognitive decline, cardiovascular events, and mortality in dementia with Lewy bodies: An up to 10-year follow-up study.

INTRODUCTION: We aimed to assess the impact of cholinesterase inhibitors (ChEIs) and memantine on cognition, major adverse cardiovascular events (MACE) and mortality in dementia with Lewy bodies (DLB). METHODS: A total of 1,095 incident DLB patients from the Swedish Registry on cognitive/dementia disorders were included. Using an inverse probability of treatment weighting, the effect of initiating ChEI or memantine within 90 days of DLB diagnosis and nonuse was evaluated on cognitive trajectories and risks of MACE and death. RESULTS: The use of ChEIs significantly slowed cognitive decline at follow-ups (Mini-Mental State Examination [MMSE] -0.39 points/y; 95% confidence interval [CI], -0.96 to 0.18) compared to memantine (-2.49 points/y; -4.02 to -0.97) and nonuse (-2.50 points/y; -4.28 to -0.73). Treatment groups did not differ in MACE events. ChEI use was associated with lower risk of death in the first year after DLB diagnosis (adjusted hazard ratio [HR] 0.66, 95% CI 0.46, 0.94). DISCUSSION: Our findings illuminate the potential benefits of ChEI treatment in DLB patients. HIGHLIGHTS: Cholinesterase inhibitors slow cognitive decline over a 5-year follow-up period when compared to both memantine treatment and nonuse in patients with dementia with Lewy bodies. Cholinesterase Inhibitors reduce risk of mortality within the initial year, but this effect is not sustained after 1 year in patients with dementia with Lewy bodies.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS: We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS: CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION: These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS: Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Sex differences in brain atrophy in dementia with Lewy bodies.

INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European-DLB consortium and the Mayo Clinic. Sex differences and sex-by-age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex-by-age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. HIGHLIGHTS: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.

Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration.

Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2  ∈ [.924, .940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.

Lifelong olfactory deprivation-dependent cortical reorganization restricted to orbitofrontal cortex.

Prolonged sensory deprivation has repeatedly been linked to cortical reorganization. We recently demonstrated that individuals with congenital anosmia (CA, complete olfactory deprivation since birth) have seemingly normal morphology in piriform (olfactory) cortex despite profound morphological deviations in the orbitofrontal cortex (OFC), a finding contradictory to both the known effects of blindness on visual cortex and to the sparse literature on brain morphology in anosmia. To establish whether these unexpected findings reflect the true brain morphology in CA, we first performed a direct replication of our previous study to determine if lack of results was due to a deviant control group, a confound in cross sectional studies. Individuals with CA (n = 30) were compared to age and sex matched controls (n = 30) using voxel- and surface-based morphometry. The replication results were near identical to the original study: bilateral clusters of group differences in the OFC, including CA atrophy around the olfactory sulci and volume increases in the medial orbital gyri. Importantly, no group differences in piriform cortex were detected. Subsequently, to assess any subtle patterns of group differences not detectable by our mass-univariate analysis, we explored the data from a multivariate perspective. Combining the newly collected data with data from the replicated study (CA = 49, control = 49), we performed support vector machine classification based on gray matter volume. In line with the mass-univariate analyses, the multivariate analysis could accurately differentiate between the groups in bilateral OFC, whereas the classification accuracy in piriform cortex was at chance level. Our results suggest that despite lifelong olfactory deprivation, piriform (olfactory) cortex is morphologically unaltered and the morphological deviations in CA are confined to the OFC.

(Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies.

Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Associations between dietary patterns and dementia-related neuroimaging markers.

BACKGROUND: The exploration of associations between dietary patterns and dementia-related neuroimaging markers can provide insights on food combinations that may impact brain integrity. METHODS: Data were derived from the Swedish Gothenburg H70 Birth Cohort Study (n = 610). Three dietary patterns were obtained using principal component analysis. Magnetic resonance imaging markers included cortical thickness, an Alzheimer's disease (AD) signature score, small vessel disease, and white matter microstructural integrity. Adjusted linear/ordinal regression analyses were performed. RESULTS: A high-protein and alcohol dietary pattern was negatively associated with cortical thickness in the whole brain (Beta: -0.011; 95% confidence interval [CI]: -0.018 to -0.003), and with an Alzheimer's disease cortical thickness signature score (Beta: -0.013; 95% CI: -0.024 to -0.001). A positive association was found between a Mediterranean-like dietary pattern and white matter microstructural integrity (Beta: 0.078; 95% CI: 0.002-0.154). No associations were found with a Western-like dietary pattern. DISCUSSION: Dietary patterns may impact brain integrity through neurodegenerative and vascular pathways. HIGHLIGHTS: Certain dietary patterns were associated with dementia-related neuroimaging markers. A Mediterranean dietary pattern was positively associated with white matter microstructure. A high-protein and alcohol pattern was negatively associated with cortical thickness.

White matter abnormalities mediate the association between masticatory dysfunction and cognition among older adults.

BACKGROUND: Masticatory parameters, such as reduced number of teeth and posterior contacts, have been shown to be associated with reduced cognitive status. The underlying mechanisms that affect these associations, are however, not well understood. OBJECTIVES: The study aims to investigate the association between masticatory dysfunction and cognition and explore the mediating effect of brain structure. METHODS: In this cross-sectional study, 45 older adults with subjective masticatory dysfunction (mean age 72.3 ± 4.0 years) were included. Mini-Mental State Examination score <25, brain trauma, neurological disease, neurodegenerative disorders, depression or poor Swedish language skills were criteria for exclusion. Cognitive functions (executive function and episodic memory) and masticatory dysfunction defined by functional occluding status (FOS; the number of occluding units and number of remaining teeth) were analysed with partial correlation models. Structural magnetic resonance imaging was performed on 28 feasible participants. Multiple regression analyses were performed to evaluate the predictive value of brain structure and white matter hypointensities (WM-hypo) on cognitive functions. A mediation analysis was applied to assess significant predictor/s of the association between FOS and cognition. RESULTS: Both episodic memory and executive functions were positively correlated with FOS. WM-hypo predicted cognitive status (executive function, p ≤ .01). WM-hypo mediated 66.6% (p = 0.06) of the association between FOS and executive functions. CONCLUSION: Associations between FOS and cognitive functions are reported, where FOS, a potential modifiable risk factor, was related to both episodic memory and executive functions. The mediating effect of WM-hypo on the association between FOS and executive functions highlights the impact of the vascularisation of the brain on the link between mastication and cognition. The present study provides increased knowledge that bridges the gap between masticatory dysfunction and cognition.

Cortical Networks Underpinning Compensation of Verbal Fluency in Normal Aging.

Elucidating compensatory mechanisms underpinning phonemic fluency (PF) may help to minimize its decline due to normal aging or neurodegenerative diseases. We investigated cortical brain networks potentially underpinning compensation of age-related differences in PF. Using graph theory, we constructed networks from measures of thickness for PF, semantic, and executive-visuospatial cortical networks. A total of 267 cognitively healthy individuals were divided into younger age (YA, 38-58 years) and older age (OA, 59-79 years) groups with low performance (LP) and high performance (HP) in PF: YA-LP, YA-HP, OA-LP, OA-HP. We found that the same pattern of reduced efficiency and increased transitivity was associated with both HP (compensation) and OA (aberrant network organization) in the PF and semantic cortical networks. When compared with the OA-LP group, the higher PF performance in the OA-HP group was associated with more segregated PF and semantic cortical networks, greater participation of frontal nodes, and stronger correlations within the PF cortical network. We conclude that more segregated cortical networks with strong involvement of frontal nodes seemed to allow older adults to maintain their high PF performance. Nodal analyses and measures of strength were helpful to disentangle compensation from the aberrant network organization associated with OA.

Normal Olfactory Functional Connectivity Despite Lifelong Absence of Olfactory Experiences.

Congenital blindness is associated with atypical morphology and functional connectivity within and from visual cortical regions; changes that are hypothesized to originate from a lifelong absence of visual input and could be regarded as a general (re) organization principle of sensory cortices. Challenging this is the fact that individuals with congenital anosmia (lifelong olfactory sensory loss) display little to no morphological changes in the primary olfactory cortex. To determine whether olfactory input from birth is essential to establish and maintain normal functional connectivity in olfactory processing regions, akin to the visual system, we assessed differences in functional connectivity within the olfactory cortex between individuals with congenital anosmia (n = 33) and matched controls (n = 33). Specifically, we assessed differences in connectivity between core olfactory processing regions as well as differences in regional homogeneity and homotopic connectivity within the primary olfactory cortex. In contrast to congenital blindness, none of the analyses indicated atypical connectivity in individuals with congenital anosmia. In fact, post-hoc Bayesian analysis provided support for an absence of group differences. These results suggest that a lifelong absence of olfactory experience has a limited impact on the functional connectivity in the olfactory cortex, a finding that indicates a clear difference between sensory modalities in how sensory cortical regions develop.

The protective gene dose effect of the APOE ε2 allele on gray matter volume in cognitively unimpaired individuals.

INTRODUCTION: Harboring two copies of the apolipoprotein E (APOE) ε2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described. METHODS: Multicenter brain magnetic resonance images (MRIs) from cognitively unimpaired ε2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of ε2 genotypic groups were compared to each other and to the reference group (APOE ε3/ε3). RESULTS: Carrying at least one ε2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE ε2 homozygotes, but not APOE ε2 heterozygotes, showed larger GM volumes in areas related to successful aging. DISCUSSION: In addition to the known resistance against amyloid-ß deposition, the larger GM volumes in key brain regions may confer APOE ε2 homozygotes additional protection against AD-related cognitive decline.

Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe.

INTRODUCTION: Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS: To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS: With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION: This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond.

Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT.

Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more widely available than MR scans, their application is currently limited to the visual assessment of brain integrity and the exclusion of co-pathologies. CT has rarely been used for tissue classification because the contrast between grey matter and white matter was considered insufficient. In this study, we propose an automatic method for segmenting grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and intracranial volume (ICV) from head CT images. A U-Net deep learning model was trained and validated on CT images with MRI-derived segmentation labels. We used data from 744 participants of the Gothenburg H70 Birth Cohort Studies for whom CT and T1-weighted MR images had been acquired on the same day. Our proposed model predicted brain tissue classes accurately from unseen CT images (Dice coefficients of 0.79, 0.82, 0.75, 0.93 and 0.98 for GM, WM, CSF, brain volume and ICV, respectively). To contextualize these results, we generated benchmarks based on established MR-based methods and intentional image degradation. Our findings demonstrate that CT-derived segmentations can be used to delineate and quantify brain tissues, opening new possibilities for the use of CT in clinical practice and research.

Demographic and Clinical Characteristics of Individuals with Mild Cognitive Impairment Related to Grade of Alcohol Consumption.

INTRODUCTION: While alcohol overconsumption is regarded as a risk factor for Alzheimer's disease, the specific relationship between alcohol consumption and cognitive impairment remains unclear and poorly understood. Our primary objective is to investigate whether alcohol consumption is associated with lower cognitive performance at an early phase of the development of cognitive impairment (mild cognitive impairment [MCI] stage) and second to present the clinical and demographic characteristics depending on the grade of alcohol consumption. METHODS: This is a cross-sectional observational study, including 251 subjects with the diagnosis MCI, having caregiving contact with Memory Clinic, Karolinska University Hospital, under year 2015. We compared subgroups with different levels of alcohol consumption, concerning social parameters, cognitive, radiological, laboratory profile as well as comorbidities and burden of drugs. RESULTS: Mini-mental State Examination score was not associated with alcohol consumption. Light to moderate drinkers were significantly higher educated. There were significantly more subjects using antianxiety medications among heavy drinkers in comparison with light to moderate drinkers. Finally, never/rare drinkers had significantly lower levels of erythrocyte mean corpuscular volume in their blood tests. DISCUSSION/CONCLUSION: Alcohol consumption was not correlated with a more pronounced cognitive deficit or a distinct clinical severity at an early stage of cognitive impairment apart from higher usage of antianxiety medications. We are planning to follow up all individuals to ascertain if heavy drinkers have a different outcome compared with the other groups.

The diagnostic and prognostic capabilities of plasma biomarkers in Alzheimer's disease.

INTRODUCTION: This study investigated the diagnostic and disease-monitoring potential of plasma biomarkers in mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and cognitively unimpaired (CU) individuals. METHODS: Plasma was analyzed using Simoa assays from 99 CU, 107 MCI, and 103 AD dementia participants. RESULTS: Phosphorylated-tau181 (P-tau181), neurofilament light, amyloid-ß (Aß42/40), Total-tau and Glial fibrillary acidic protein were altered in AD dementia but P-tau181 significantly outperformed all biomarkers in differentiating AD dementia from CU (area under the curve [AUC] = 0.91). P-tau181 was increased in MCI converters compared to non-converters. Higher P-tau181 was associated with steeper cognitive decline and gray matter loss in temporal regions. Longitudinal change of P-tau181 was strongly associated with gray matter loss in the full sample and with Aß measures in CU individuals. DISCUSSION: P-tau181 detected AD at MCI and dementia stages and was strongly associated with cognitive decline and gray matter loss. These findings highlight the potential value of plasma P-tau181 as a non-invasive and cost-effective diagnostic and prognostic biomarker in AD.