Patterns of atrophy in pathologically confirmed dementias: a voxelwise analysis

Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer's disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < -0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

In vivo PET classification of tau pathologies in patients with frontotemporal dementia

Frontotemporal dementia refers to a group of neurodegenerative disorders with diverse clinical and neuropathological features. In vivo neuropathological assessments of frontotemporal dementia at an individual level have hitherto not been successful. In this study, we aim to classify patients with frontotemporal dementia based on topologies of tau protein aggregates captured by PET with 18F-florzolotau (aka 18F-APN-1607 and 18F-PM-PBB3), which allows high-contrast imaging of diverse tau fibrils in Alzheimer's disease as well as in non-Alzheimer's disease tauopathies. Twenty-six patients with frontotemporal dementia, 15 with behavioural variant frontotemporal dementia and 11 with other frontotemporal dementia phenotypes, and 20 age- and sex-matched healthy controls were included in this study. They underwent PET imaging of amyloid and tau depositions with 11C-PiB and 18F-florzolotau, respectively. By combining visual and quantitative analyses of PET images, the patients with behavioural variant frontotemporal dementia were classified into the following subgroups: (i) predominant tau accumulations in frontotemporal and frontolimbic cortices resembling three-repeat tauopathies (n = 3), (ii) predominant tau accumulations in posterior cortical and subcortical structures indicative of four-repeat tauopathies (n = 4); (iii) amyloid and tau accumulations consistent with Alzheimer's disease (n = 4); and (iv) no overt amyloid and tau pathologies (n = 4). Despite these distinctions, clinical symptoms and localizations of brain atrophy did not significantly differ among the identified behavioural variant frontotemporal dementia subgroups. The patients with other frontotemporal dementia phenotypes were also classified into similar subgroups. The results suggest that PET with 18F-florzolotau potentially allows the classification of each individual with frontotemporal dementia on a neuropathological basis, which might not be possible by symptomatic and volumetric assessments.

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements

Background

Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data.

Objective

Train machine learning models to classify the presence or absence of autopsy-confirmed severe AD neuropathology using clinically available features.

Methods

AD neuropathological status are assessed at postmortem for participants from the National Alzheimer's Coordinating Center (NACC). Clinically available features are utilized, including demographics, Apolipoprotein E(APOE) genotype, and cortical thicknesses derived from ante-mortem MRI scans encompassing AD meta regions of interest (meta-ROI). Both logistic regression and random forest models are trained to identify linearly and nonlinearly separable features between participants with the presence (N = 91, age-at-MRI = 73.6±9.24, 38 women) or absence (N = 53, age-at-MRI = 68.93±19.69, 24 women) of severe AD neuropathology. The trained models are further validated in an external data set against in vivo amyloid biomarkers derived from PET imaging (amyloid-positive: N = 71, age-at-MRI = 74.17±6.37, 26 women; amyloid-negative: N = 73, age-at-MRI = 71.59±6.80, 41 women).

Results

Our models achieve a cross-validation accuracy of 84.03% in classifying the presence or absence of severe AD neuropathology, and an external-validation accuracy of 70.14% in classifying in vivo amyloid positivity status.

Conclusions

Our models show that clinically accessible features, including APOE genotype and cortical thinning encompassing AD meta-ROIs, are able to classify both postmortem confirmed AD neuropathological status and in vivo amyloid status with reasonable accuracies. These results suggest the potential utility of AD meta-ROIs in determining AD neuropathological status in living persons.

Cerebrospinal Fluid Proteomics Identifies Potential Biomarkers for Early-Onset Alzheimer's Disease

Background

Early-onset Alzheimer's disease (EOAD) exhibits a notable degree of heterogeneity as compared to late-onset Alzheimer's disease (LOAD). The proteins and pathways contributing to the pathophysiology of EOAD still need to be completed and elucidated.

Objective

Using correlation network analysis and machine learning to analyze cerebrospinal fluid (CSF) proteomics data to identify potential biomarkers and pathways associated with EOAD.

Methods

We employed mass spectrometry to conduct CSF proteomic analysis using the data-independent acquisition method in a Chinese cohort of 139 CSF samples, including 40 individuals with normal cognition (CN), 61 patients with EOAD, and 38 patients with LOAD. Correlation network analysis of differentially expressed proteins was performed to identify EOAD-associated pathways. Machine learning assisted in identifying crucial proteins differentiating EOAD. We validated the results in an Western cohort and examined the proteins expression by enzyme-linked immunosorbent assay (ELISA) in additional 9 EOAD, 9 LOAD, and 9 CN samples from our cohort.

Results

We quantified 2,168 CSF proteins. Following adjustment for age and sex, EOAD exhibited a significantly greater number of differentially expressed proteins than LOAD compared to CN. Additionally, our data indicates that EOAD may exhibit more pronounced synaptic dysfunction than LOAD. Three potential biomarkers for EOAD were identified: SH3BGRL3, LRP8, and LY6 H, of which SH3BGRL3 also accurately classified EOAD in the Western cohort. LY6 H reduction was confirmed via ELISA, which was consistent with our proteomic results.

Conclusions

This study provides a comprehensive profile of the CSF proteome in EOAD and identifies three potential EOAD biomarker proteins.

Neuroimaging determinants of cognitive impairment in the memory clinic: how important is the vascular burden?

While neurodegenerative and vascular neurocognitive disorder (NCD) often co-occur, the contribution of vascular lesions, especially stroke lesions identified on MRI, to global cognition in a real-life memory clinic population remains unclear. The main objective of this retrospective study was to determine NCD neuroimaging correlates: the GM atrophy pattern and vascular lesions (especially stroke lesion localization by voxel-based lesion-symptom mapping, VLSM) in a memory clinic. We included 336 patients with mild or major NCD who underwent cerebral MRI and a neuropsychological assessment. The GM atrophy pattern (obtained by voxel-based morphometry, VBM) and the stroke lesion localization (obtained by VLSM) associated with G5 z-score (a global cognitive score), were included as independent variables with other neuroimaging and clinical indices in a stepwise linear regression model. The mean age was 70.3 years and the mean MMSE score 21.3. On MRI, 75 patients had at least one stroke lesion. The G 5 z-score was associated with GM density in the pattern selected by the VBM analysis (R2 variation = 0.166, p < 0.001) and the presence of a stroke lesion in the region selected by the VSLM analysis (mainly in the right frontal region; R2 variation = 0.018, p = 0.008). The interaction between the two factors was insignificant (p = 0.374). In conclusion, in this first study combining VBM and VLSM analysis in a memory clinic, global cognition was associated with a specific GM atrophy pattern and the presence of a stroke lesion mainly in the right frontal region.

Predicting amyloid-PET status in a memory clinic: The role of the novel antero-posterior index and visual rating scales

INTRODUCTION

Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory clinic population. This study aims to assess the accuracy of a novel visual rating assessment, the antero-posterior index (API) scale, in predicting amyloid-PET status. Furthermore, the study seeks to determine the optimal cohort-based cutoffs for the medial temporal atrophy (MTA) and parietal atrophy (PA) scales and to integrate the main visual rating scores into a predictive model.

METHODS

We conducted a retrospective analysis of brain MRI and high-resolution TC scans from 153 patients with cognitive disorders who had undergone amyloid-PET assessments due to suspected AD pathology in a real-world memory clinic setting.

RESULTS

The API scale (cutoff ≥1) exhibited the highest accuracy (AUC = 0.721) among the visual rating scales. The combination of the cohort-based MTA and PA threshold with the API yielded favorable accuracy (AUC = 0.787). Analyzing a cohort of MCI/Mild dementia patients below 75 years of age, the API scale and the predictive model improved their accuracy (AUC = 0.741 and 0.813, respectively), achieving excellent results in the early-onset population (AUC = 0.857 and 0.949, respectively).

CONCLUSION

Our study emphasizes the significance of visual rating scales in predicting amyloid-PET positivity within a real-world memory clinic. Implementing the novel API scale, alongside our cohort-based MTA and PA thresholds, has the potential to substantially enhance diagnostic accuracy.

A promising tool to explore functional impairment in neurodegeneration: A systematic review of near-infrared spectroscopy in dementia

This systematic review aimed to evaluate previous studies which used near-infrared spectroscopy (NIRS) in dementia given its suitability as a diagnostic and investigative tool in this population. From 800 identified records which used NIRS in dementia and prodromal stages, 88 studies were evaluated which employed a range of tasks testing memory (29), word retrieval (24), motor (8) and visuo-spatial function (4), and which explored the resting state (32). Across these domains, dementia exhibited blunted haemodynamic responses, often localised to frontal regions of interest, and a lack of task-appropriate frontal lateralisation. Prodromal stages, such as mild cognitive impairment, revealed mixed results. Reduced cognitive performance accompanied by either diminished functional responses or hyperactivity was identified, the latter suggesting a compensatory response not present at the dementia stage. Despite clear evidence of alterations in brain oxygenation in dementia and prodromal stages, a consensus as to the nature of these changes is difficult to reach. This is likely partially due to the lack of standardisation in optical techniques and processing methods for the application of NIRS to dementia. Further studies are required exploring more naturalistic settings and a wider range of dementia subtypes.

Investigating the relationship between periodontitis and specific memory processes in the search for cognitive markers of Alzheimer's disease risk

The spontaneous retrieval deficit (SRD) hypothesis argues that individuals in the preclinical stages of Alzheimer's disease (AD) are particularly impaired in spontaneous retrieval, which manifests in reduced mind-wandering. Our main purpose was to provide novel evidence to support the SRD hypothesis by investigating, for the first time, the relationship between mind-wandering and periodontitis, the latter being the risk factor for AD. The second objective was to address the lack of deeper understanding of the relationship between oral health and specific cognitive abilities by investigating whether periodontitis would be primarily associated with memory. Sixty community-dwelling dementia-free older adults completed neuropsychological tests that focused on various cognitive abilities and a computerised task, during which mind-wandering was evaluated. Periodontal health was assessed subjectively, and through an oral examination by a qualified dentist that focused on visible periodontitis-related changes in gingival tissues and the number of periodontitis bacteria. In line with our predictions, objective and subjective symptoms of poorer periodontal health were associated with less mind-wandering, providing further support for the SRD hypothesis. Again in line with predictions, poorer periodontal health was associated with worse episodic memory, with no relationship between periodontitis and the measure targeting various cognitive abilities, from which memory was excluded.

Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitoring AD progression. However, atrophy patterns are complex and vary by patient. To address this issue, researchers have made efforts to develop more concise metrics that can summarize AD-specific atrophy. Many of these methods can be difficult to interpret clinically, hampering adoption. In this study, we introduce a novel index which we call an "AD-NeuroScore," that uses a modified Euclidean-inspired distance function to calculate differences between regional brain volumes associated with cognitive decline. The index is adjusted for intracranial volume (ICV), age, sex, and scanner model. We validated AD-NeuroScore using 929 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, with a mean age of 72.7 years (SD = 6.3; 55.1-91.5) and cognitively normal (CN), mild cognitive impairment (MCI), or AD diagnoses. Our validation results showed that AD-NeuroScore was significantly associated with diagnosis and disease severity scores (measured by MMSE, CDR-SB, and ADAS-11) at baseline. Furthermore, baseline AD-NeuroScore was associated with both changes in diagnosis and disease severity scores at all time points with available data. The performance of AD-NeuroScore was equivalent or superior to adjusted hippocampal volume (AHV), a widely used metric in AD research. Further, AD-NeuroScore typically performed as well as or sometimes better when compared to other existing sMRI-based metrics. In conclusion, we have introduced a new metric, AD-NeuroScore, which shows promising results in detecting AD, benchmarking disease severity, and predicting disease progression. AD-NeuroScore differentiates itself from other metrics by being clinically practical and interpretable.

Detection of subclinical epileptiform discharges in Alzheimer's disease using long-term outpatient EEG monitoring

BACKGROUND

In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC).

METHODS

In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months.

RESULTS

The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77-5.01, p < 0.001). Most patients with AD (91.7%) showed epileptiform discharges when combining all ear-EEG recordings.

CONCLUSIONS

Long-term ear-EEG monitoring detects epileptiform discharges in most patients with AD with a three-fold increased spike frequency compared to HC, which most likely originates from the temporal lobes. Since most patients showed epileptiform discharges with multiple recordings, elevated spike frequency should be considered a marker of hyperexcitability in AD.

Sex difference in evolution of cognitive decline: studies on mouse model and the Dominantly Inherited Alzheimer Network cohort

Women carry a higher burden of Alzheimer's disease (AD) compared to men, which is not accounted entirely by differences in lifespan. To identify the mechanisms underlying this effect, we investigated sex-specific differences in the progression of familial AD in humans and in APPswe/PS1ΔE9 mice. Activity dependent protein translation and associative learning and memory deficits were examined in APPswe/PS1ΔE9 mice and wild-type mice. As a human comparator group, progression of cognitive dysfunction was assessed in mutation carriers and non-carriers from DIAN (Dominantly Inherited Alzheimer Network) cohort. Female APPswe/PS1ΔE9 mice did not show recall deficits after contextual fear conditioning until 8 months of age. Further, activity dependent protein translation and Akt1-mTOR signaling at the synapse were impaired in male but not in female mice until 8 months of age. Ovariectomized APPswe/PS1ΔE9 mice displayed recall deficits at 4 months of age and these were sustained until 8 months of age. Moreover, activity dependent protein translation was also impaired in 4 months old ovariectomized APPswe/PS1ΔE9 mice compared with sham female APPswe/PS1ΔE9 mice. Progression of memory impairment differed between men and women in the DIAN cohort as analyzed using linear mixed effects model, wherein men showed steeper cognitive decline irrespective of the age of entry in the study, while women showed significantly greater performance and slower decline in immediate recall (LOGIMEM) and delayed recall (MEMUNITS) than men. However, when the performance of men and women in several cognitive tasks (such as Wechsler's logical memory) are compared with the estimated year from expected symptom onset (EYO) we found no significant differences between men and women. We conclude that in familial AD patients and mouse models, females are protected, and the onset of disease is delayed as long as estrogen levels are intact.

Tau-Neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum

Variability in the relationship of tau-based neurofibrillary tangles (T) and degree of neurodegeneration (N) in Alzheimer's Disease (AD) is likely attributable to the non-specific nature of N, which is also modulated by such factors as other co-pathologies, age-related changes, and developmental differences. We studied this variability by partitioning patients within the Alzheimer's continuum into data-driven groups based on their regional T-N dissociation, which reflects the residuals after the effect of tau pathology is "removed". We found six groups displaying distinct spatial T-N mismatch and thickness patterns despite similar tau burden. Their T-N patterns resembled the neurodegeneration patterns of non-AD groups partitioned on the basis of z-scores of cortical thickness alone and were similarly associated with surrogates of non-AD factors. In an additional sample of individuals with antemortem imaging and autopsy, T-N mismatch was associated with TDP-43 co-pathology. Finally, T-N mismatch training was then applied to a separate cohort to determine the ability to classify individual patients within these groups. These findings suggest that T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability to Alzheimer's disease.

Diverse limbic comorbidities cause limbic and temporal atrophy in lewy body disease

BACKGROUND

In contrast to Alzheimer's disease (AD)-related pathology, the influence of comorbid limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) or argyrophilic grains (AG) on structural imaging in Lewy body disease (LBD) has seldom been evaluated.

OBJECTIVE

This study aimed to investigate whether non-AD limbic comorbidities, including LATE-NC and AG, cause cortical atrophy in LBD.

METHODS

Seventeen patients with pathologically confirmed LBD with lower Braak neurofibrillary tangle stage (<IV) and 10 healthy controls (HC) were included. Based on the presence of comorbid LATE-NC or AG, LBD patients were subdivided into nine patients with these proteinopathies (mixed LBD [mLBD]) and eight without (pure LBD [pLBD]). In addition to clinical feature evaluation, gray matter atrophy on voxel-based morphometry was compared between the two LBD and HC groups.

RESULTS

The mean age at antemortem magnetic resonance imaging of the mLBD patients was higher than that of the pLBD patients (84.3 ± 3.9 vs. 76.5 ± 10.5; p = .046). Irrespective of the presence or absence of comorbid LATE-NC or AG, all patients were clinically diagnosed with probable dementia with Lewy bodies or Parkinson's disease with dementia, respectively. Compared to the pLBD group, the mLBD group showed more conspicuous cortical atrophy of the bilateral hippocampus, amygdala, and temporal pole.

CONCLUSIONS

Non-AD limbic comorbidities, including LATE-NC and AG, are associated with limbic and temporal atrophy in older patients with LBD. Therefore, the possibility of non-AD limbic comorbidities should be considered in the diagnosis of elderly patients with dementia with clinical symptoms of LBD and medial temporal atrophy.

Associations between cerebrospinal fluid markers and cognition in ageing and dementia: A systematic review

A biomarker associated with cognition in neurodegenerative dementias would aid in the early detection of disease progression, complement clinical staging and act as a surrogate endpoint in clinical trials. The current systematic review evaluates the association between cerebrospinal fluid protein markers of synapse loss and neuronal injury and cognition. We performed a systematic search which revealed 67 studies reporting an association between cerebrospinal fluid markers of interest and neuropsychological performance. Despite the substantial heterogeneity between studies, we found some evidence for an association between neurofilament-light and worse cognition in Alzheimer's diseases, frontotemporal dementia and typical cognitive ageing. Moreover, there was an association between cerebrospinal fluid neurogranin and cognition in those with an Alzheimer's-like cerebrospinal fluid biomarker profile. Some evidence was found for cerebrospinal fluid neuronal pentraxin-2 as a correlate of cognition across dementia syndromes. Due to the substantial heterogeneity of the field, no firm conclusions can be drawn from this review. Future research should focus on improving standardization and reporting as well as establishing the importance of novel markers such as neuronal pentraxin-2 and whether such markers can predict longitudinal cognitive decline.

Longitudinal Patterns of Cortical Atrophy on MRI in Patients With Alzheimer Disease With and Without Lewy Body Pathology

BACKGROUND AND OBJECTIVES

Although Alzheimer disease (AD) and dementia with Lewy bodies (DLBs) represent 2 different pathologies, they have clinical overlap, and there is a significant degree of co-occurrence of their neuropathologic findings. Many studies have examined imaging characteristics in clinically diagnosed patients; however, there is a relative lack of longitudinal studies that have studied patients with pathologic confirmation. We examined whether there were differences in longitudinal patterns of cortical atrophy between patients with both AD and DLB (AD/DLB) vs those with AD alone.

METHODS

We collected and analyzed clinical and neuroimaging data from the AD Neuroimaging Initiative (ADNI) database for patients who underwent autopsy. The rates of change in various neuropsychological assessments were not significantly different between patients with AD/DLB and AD, and each group had neuropsychological outcomes consistent with disease progression. For our neuroimaging analysis, we used a linear mixed-effects model to examine whether there were longitudinal differences in cortical rates of atrophy between patients with AD/DLB and AD.

RESULTS

Autopsies and serial neuroimaging were available on 48 patients (24 AD and 24 AD/DLB). Patients with AD alone had significantly higher atrophy rates in the left cuneus, lateral occipital, and parahippocampal regions over time when compared with patients with concomitant DLB, after covarying for interval from imaging to autopsy, sex, and total estimated intracranial volume. Site ID was included as a random effect to account for site differences. For these regions, the rate of decline over time in the AD/DLB group was less steep by a difference of 0.1887, 0.395, and 0.0989, respectively (p = 0.022, 0.006, and 0.006). The lattermost left cuneus volume measurement and Braak Lewy score had a Pearson product-moment correlation of 0.37, p = 0.009, while the lattermost left parahippocampal volume measurement and Braak neurofibrillary tangle score had a Pearson product-moment correlation of -0.327, p = 0.02.

DISCUSSION

Patients with AD had more significant atrophy in the left cuneus, lateral occipital, and parahippocampal regions when compared with patients with AD/DLB. These regions are known to distinguish DLB and AD pathology cross-sectionally but here are shown to distinguish longitudinal disease progression.

Widespread cell stress and mitochondrial dysfunction occur in patients with early Alzheimer's disease

Cell stress and impaired oxidative phosphorylation are central to mechanisms of synaptic loss and neurodegeneration in the cellular pathology of Alzheimer's disease (AD). In this study, we quantified the in vivo expression of the endoplasmic reticulum stress marker, sigma 1 receptor (S1R), using [¹¹C]SA4503 positron emission tomography (PET), the mitochondrial complex I (MC1) with [¹⁸F]BCPP-EF, and the presynaptic vesicular protein SV2A with [¹¹C]UCB-J in 12 patients with early AD and in 16 cognitively normal controls. We integrated these molecular measures with assessments of regional brain volumes and cerebral blood flow (CBF) measured with magnetic resonance imaging arterial spin labeling. Eight patients with AD were followed longitudinally to estimate the rate of change of the physiological and structural pathology markers with disease progression. The patients showed widespread increases in S1R (≤ 27%) and regional reduction in MC1 (≥ -28%) and SV2A (≥ -25%) radioligand binding, brain volume (≥ -23%), and CBF (≥ -26%). [¹⁸F]BCPP-EF PET MC1 binding (≥ -12%) and brain volumes (≥ -5%) showed progressive reductions over 12 to 18 months, suggesting that they both could be used as pharmacodynamic indicators in early-stage therapeutics trials. Associations of reduced MC1 and SV2A and increased S1R radioligand binding with reduced cognitive performance in AD, although exploratory, suggested a loss of metabolic functional reserve with disease. Our study thus provides in vivo evidence for widespread, clinically relevant cellular stress and bioenergetic abnormalities in early AD.

Quantitative susceptibility mapping demonstrates different patterns of iron overload in subtypes of early-onset Alzheimer's disease

OBJECTIVES

We aimed to define brain iron distribution patterns in subtypes of early-onset Alzheimer's disease (EOAD) by the use of quantitative susceptibility mapping (QSM).

METHODS

EOAD patients prospectively underwent MRI on a 3-T scanner and concomitant clinical and neuropsychological evaluation, between 2016 and 2019. An age-matched control group was constituted of cognitively healthy participants at risk of developing AD. Volumetry of the hippocampus and cerebral cortex was performed on 3DT1 images. EOAD subtypes were defined according to the hippocampal to cortical volume ratio (HV:CTV). Limbic-predominant atrophy (LP_MRI) is referred to HV:CTV ratios below the 25^th percentile, hippocampal-sparing (HpSp_MRI) above the 75^th percentile, and typical-AD between the 25^th and 75^th percentile. Brain iron was estimated using QSM. QSM analyses were made voxel-wise and in 7 regions of interest within deep gray nuclei and limbic structures. Iron distribution in EOAD subtypes and controls was compared using an ANOVA.

RESULTS

Sixty-eight EOAD patients and 43 controls were evaluated. QSM values were significantly higher in deep gray nuclei (p < 0.001) and limbic structures (p = 0.04) of EOAD patients compared to controls. Among EOAD subtypes, HpSp_MRI had the highest QSM values in deep gray nuclei (p < 0.001) whereas the highest QSM values in limbic structures were observed in LP_MRI (p = 0.005). QSM in deep gray nuclei had an AUC = 0.92 in discriminating HpSp_MRI and controls.

CONCLUSIONS

In early-onset Alzheimer's disease patients, we observed significant variations of iron distribution reflecting the pattern of brain atrophy. Iron overload in deep gray nuclei could help to identify patients with atypical presentation of Alzheimer's disease.

KEY POINTS

• In early-onset AD patients, QSM indicated a significant brain iron overload in comparison with age-matched controls. • Iron load in limbic structures was higher in participants with limbic-predominant subtype. • Iron load in deep nuclei was more important in participants with hippocampal-sparing subtype.

Deficits in spontaneous and stimulus-dependent retrieval as an early sign of abnormal aging

Research on early cognitive markers of Alzheimer's disease is primarily focused on episodic memory tests that involve deliberate retrieval. Our purpose was to provide clear evidence to support a novel Spontaneous Retrieval Deficit hypothesis, which predicts that people at pre-clinical stages of dementia, including those with amnestic Mild Cognitive Impairment (aMCI), are particularly impaired on tasks based on spontaneous retrieval. We compared 27 aMCI individuals and 27 healthy controls on mind-wandering while performing a task during which there were exposed to either highly meaningful or unmeaningful pictures. The substantial reduction in mind-wandering among individuals with aMCI was found with exposure to highly meaningful stimuli, but not to unmeaningful pictures, and it was most pronounced for past-oriented thoughts, i.e., involuntary autobiographical memories. Those findings provide strong support for this novel hypothesis, and show that it is the spontaneous, but bottom-up and cue-driven processes, for which meaningful environmental stimuli are crucial, that are very promising early markers of the disease.

Fractal dimension of the brain in neurodegenerative disease and dementia: A systematic review

Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.

Brain Glucose Hypometabolism and Iron Accumulation in Different Brain Regions in Alzheimer's and Parkinson's Diseases

The aim of this study was to examine the relationship between the presence of glucose hypometabolism (GHM) and brain iron accumulation (BIA), two potential pathological mechanisms in neurodegenerative disease, in different regions of the brain in people with late-onset Alzheimer's disease (AD) or Parkinson's disease (PD). Studies that conducted fluorodeoxyglucose positron emission tomography (FDG-PET) to map GHM or quantitative susceptibility mapping-magnetic resonance imaging (QSM-MRI) to map BIA in the brains of patients with AD or PD were reviewed. Regions of the brain where GHM or BIA were reported in each disease were compared. In AD, both GHM and BIA were reported in the hippocampus, temporal, and parietal lobes. GHM alone was reported in the cingulate gyrus, precuneus and occipital lobe. BIA alone was reported in the caudate nucleus, putamen and globus pallidus. In PD, both GHM and BIA were reported in thalamus, globus pallidus, putamen, hippocampus, and temporal and frontal lobes. GHM alone was reported in cingulate gyrus, caudate nucleus, cerebellum, and parietal and occipital lobes. BIA alone was reported in the substantia nigra and red nucleus. GHM and BIA are observed independent of one another in various brain regions in both AD and PD. This suggests that GHM is not always necessary or sufficient to cause BIA and vice versa. Hypothesis-driven FDG-PET and QSM-MRI imaging studies, where both are conducted on individuals with AD or PD, are needed to confirm or disprove the observations presented here about the potential relationship or lack thereof between GHM and BIA in AD and PD.

Identification of multimodal brain imaging association via a parameter decomposition based sparse multi-view canonical correlation analysis method

BACKGROUND

With the development of noninvasive imaging technology, collecting different imaging measurements of the same brain has become more and more easy. These multimodal imaging data carry complementary information of the same brain, with both specific and shared information being intertwined. Within these multimodal data, it is essential to discriminate the specific information from the shared information since it is of benefit to comprehensively characterize brain diseases. While most existing methods are unqualified, in this paper, we propose a parameter decomposition based sparse multi-view canonical correlation analysis (PDSMCCA) method. PDSMCCA could identify both modality-shared and -specific information of multimodal data, leading to an in-depth understanding of complex pathology of brain disease.

RESULTS

Compared with the SMCCA method, our method obtains higher correlation coefficients and better canonical weights on both synthetic data and real neuroimaging data. This indicates that, coupled with modality-shared and -specific feature selection, PDSMCCA improves the multi-view association identification and shows meaningful feature selection capability with desirable interpretation.

CONCLUSIONS

The novel PDSMCCA confirms that the parameter decomposition is a suitable strategy to identify both modality-shared and -specific imaging features. The multimodal association and the diverse information of multimodal imaging data enable us to better understand the brain disease such as Alzheimer's disease.

Multiple-region grey matter atrophy as a predictor for the development of dementia in a community: the Hisayama Study

OBJECTIVE

To assess the association of regional grey matter atrophy with dementia risk in a general older Japanese population.

METHODS

We followed 1158 dementia-free Japanese residents aged ≥65 years for 5.0 years. Regional grey matter volume (GMV) at baseline was estimated by applying voxel-based morphometry methods. The GMV-to-total brain volume ratio (GMV/TBV) was calculated, and its association with dementia risk was estimated using Cox proportional hazard models. We assessed whether the predictive ability of a model based on known dementia risk factors could be improved by adding the total number of regions with grey matter atrophy among dementia-related brain regions, where the cut-off value for grey matter atrophy in each region was determined by receiver operating characteristic curves.

RESULTS

During the follow-up, 113 participants developed all-cause dementia, including 83 with Alzheimer's disease (AD). Lower GMV/TBV of the medial temporal lobe, insula, hippocampus and amygdala were significantly/marginally associated with higher risk of all-cause dementia and AD (all p for trend ≤0.08). The risks of all-cause dementia and AD increased significantly with increasing total number of brain regions exhibiting grey matter atrophy (both p for trend <0.01). Adding the total number of regions with grey matter atrophy into a model consisting of known risk factors significantly improved the predictive ability for AD (Harrell's c-statistics: 0.765-0.802; p=0.02).

CONCLUSIONS

Our findings suggest that the total number of regions with grey matter atrophy among the medial temporal lobe, insula, hippocampus and amygdala is a significant predictor for developing dementia, especially AD, in the general older population.

Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data

BACKGROUND

Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer's disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features.

METHODS

We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions.

RESULTS

We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-β and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores.

CONCLUSIONS

This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials.

Hypothalamic Functional Connectivity and Apathy in People with Alzheimer's Disease and Cognitively Normal Healthy Controls

BACKGROUND

Earlier studies have described the neural markers of apathy in Alzheimer's disease (AD) and mild cognitive impairment (MCI), but few focused on the motivation circuits. Here, we targeted hypothalamus, a hub of the motivation circuit.

OBJECTIVE

To examine hypothalamic resting state functional connectivity (rsFC) in relation to apathy.

METHODS

We performed whole-brain regression of hypothalamic rsFC against Apathy Evaluation Scale (AES) total score and behavioral, cognitive, and emotional subscores in 29 patients with AD/MCI and 28 healthy controls (HC), controlling for age, sex, education, cognitive status, and depression. We evaluated the results at a corrected threshold and employed path analyses to assess possible interaction between hypothalamic rsFCs, apathy and depression/memory. Finally, we re-examined the findings in a subsample of amyloid-β-verified AD.

RESULTS

AES total score correlated negatively with hypothalamic precuneus (PCu)/posterior cingulate cortex (PCC) and positively with left middle temporal gyrus (MTG) and supramarginal gyrus rsFCs. Behavioral subscore correlated negatively with hypothalamic PCu/PCC and positively with middle frontal gyrus rsFC. Cognitive subscore correlated positively with hypothalamic MTG rsFC. Emotional subscore correlated negatively with hypothalamic calcarine cortex rsFC. In path analyses, hypothalamic-PCu/PCC rsFC negatively modulated apathy and, in turn, depression. The model where hypothalamic MTG rsFC and memory independently modulated apathy also showed a good fit. The findings of diminished hypothalamic-PCu/PCC rsFC in relation to apathy and, in turn, depression were confirmed in amyloid-verified AD.

CONCLUSION

The findings together support a role of altered hypothalamic connectivity in relation to apathy and depression, and modulation of apathy by memory dysfunction.

Inter- and Intra-Scanner Variability of Automated Brain Volumetry on Three Magnetic Resonance Imaging Systems in Alzheimer's Disease and Controls

Magnetic Resonance Imaging (MRI) has become part of the clinical routine for diagnosing neurodegenerative disorders. Since acquisitions are performed at multiple centers using multiple imaging systems, detailed analysis of brain volumetry differences between MRI systems and scan-rescan acquisitions can provide valuable information to correct for different MRI scanner effects in multi-center longitudinal studies. To this end, five healthy controls and five patients belonging to various stages of the AD continuum underwent brain MRI acquisitions on three different MRI systems (Philips Achieva dStream 1.5T, Philips Ingenia 3T, and GE Discovery MR750w 3T) with harmonized scan parameters. Each participant underwent two subsequent MRI scans per imaging system, repeated on three different MRI systems within 2 h. Brain volumes computed by icobrain dm (v5.0) were analyzed using absolute and percentual volume differences, Dice similarity (DSC) and intraclass correlation coefficients, and coefficients of variation (CV). Harmonized scans obtained with different scanners of the same manufacturer had a measurement error closer to the intra-scanner performance. The gap between intra- and inter-scanner comparisons grew when comparing scans from different manufacturers. This was observed at image level (image contrast, similarity, and geometry) and translated into a higher variability of automated brain volumetry. Mixed effects modeling revealed a significant effect of scanner type on some brain volumes, and of the scanner combination on DSC. The study concluded a good intra- and inter-scanner reproducibility, as illustrated by an average intra-scanner (inter-scanner) CV below 2% (5%) and an excellent overlap of brain structure segmentation (mean DSC > 0.88).

Baseline MRI atrophy predicts 2-year cognitive outcomes in early-onset Alzheimer's disease

BACKGROUND

MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD, < 65 years) patients with a biomarker-based diagnosis.

METHODS

Forty eight EOAD (MMSE ≥ 15; A + T + N +) and forty two age-matched healthy controls (HC; A - T - N -) from a prospective cohort underwent full neuropsychological assessment, 3T-MRI scan and lumbar puncture at baseline. Participants repeated the cognitive assessment annually. We used linear mixed models to investigate whether baseline cortical thickness (CTh) or subcortical volume predicts two-year cognitive outcomes in the EOAD group.

RESULTS

In EOAD, hemispheric CTh and ventricular volume at baseline were associated with global cognition, language and attentional/executive functioning 2 years later (p < 0.0028). Regional CTh was related to most cognitive outcomes (p < 0.0028), except verbal/visual memory subtests. Amygdalar volume was associated with letter fluency test (p < 0.0028). Hippocampal volume did not show significant associations.

CONCLUSION

Baseline hemispheric/regional CTh, ventricular and amygdalar volume, but not the hippocampus, predict two-year cognitive outcomes in EOAD.

Diet enriched in omega-3 fatty acids alleviates olfactory system deficits in APOE4 transgenic mice

Olfactory dysfunction is observed in several neurological disorders including Mild Cognitive Impairment (MCI) and Alzheimer disease (AD). These deficits occur early and correlate with global cognitive performance, depression and degeneration of olfactory regions in the brain. Despite extensive human studies, there has been little characterization of the olfactory system in models of AD. In order to determine if olfactory structural and/or molecular phenotypes are observed in a model expressing a genetic risk factor for AD, we assessed the olfactory bulb (OB) in APOE4 transgenic mice. A significant decrease in OB weight was observed at 12 months of age in APOE4 mice concurrent with inflammation and decreased NeuN expression. In order to determine if a diet rich in omega-3s may alleviate the olfactory system phenotypes observed, we assessed WT and APOE4 mice on a docosahexaenoic acid (DHA) diet. APOE4 mice on a DHA diet did not present with atrophy of the OB, and the alterations in NeuN and IBA-1 expression were alleviated. Furthermore, alterations in caspase mRNA and protein expression in the APOE4 OB were not observed with a DHA diet. Similar to the human AD condition, OB atrophy is an early phenotype in the APOE4 mice and concurrent with inflammation. These data support a link between the structural olfactory brain region atrophy and the olfactory dysfunction observed in AD and suggest that inflammation and cell death pathways may contribute to the olfactory deficits observed. Furthermore, the results suggest that diets enriched in DHA may provide benefit to APOE4 allele carriers.

Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer's disease

There is evidence of longitudinal atrophy in posterior brain areas in early-onset Alzheimer's disease (EOAD; aged < 65 years), but no studies have been conducted in an EOAD cohort with fluid biomarkers characterization. We used 3T-MRI and Freesurfer 6.0 to investigate cortical and subcortical gray matter loss at two years in 12 EOAD patients (A + T + N + ) compared to 19 controls (A-T-N-) from the Hospital Clínic Barcelona cohort. We explored group differences in atrophy patterns and we correlated atrophy and baseline CSF-biomarkers levels in EOAD. We replicated the correlation analyses in 14 EOAD (A + T + N + ) and 55 late-onset AD (LOAD; aged ≥ 75 years; A + T + N + ) participants from the Alzheimer's disease Neuroimaging Initiative. We found that EOAD longitudinal atrophy spread with a posterior-to-anterior gradient and beyond hippocampus/amygdala. In EOAD, higher initial CSF NfL levels correlated with higher ventricular volumes at baseline. On the other hand, higher initial CSF Aβ42 levels (within pathological range) predicted higher rates of cortical loss in EOAD. In EOAD and LOAD subjects, higher CSF t-tau values at baseline predicted higher rates of subcortical atrophy. CSF p-tau did not show any significant correlation. In conclusion, posterior cortices, hippocampus and amygdala capture EOAD atrophy from early stages. CSF Aβ42 might predict cortical thinning and t-tau/NfL subcortical atrophy.

Differences Changes in Cerebellar Functional Connectivity Between Mild Cognitive Impairment and Alzheimer's Disease: A Seed-Based Approach

Background: Recent studies have discovered that functional connections are impaired among patients with Alzheimer's disease (AD), even at the preclinical stage. The cerebellum has been implicated as playing a role in cognitive processes. However, functional connectivity (FC) among cognitive sub-regions of the cerebellum in patients with AD and mild cognitive impairment (MCI) remains to be further elucidated. Objective: Our study aims to investigate the FC changes of the cerebellum among patients with AD and MCI, compared to healthy controls (HC). Additionally, we explored the role of cerebellum FC changes in the cognitive performance of all subjects. Materials: Resting-state functional magnetic resonance imaging (rs-fMRI) data from three different groups (28 AD patients, 26 MCI patients, and 30 HC) was collected. We defined cerebellar crus II and lobule IX as seed regions to assess the intragroup differences of cortico-cerebellar connectivity. Bias correlational analysis was performed to investigate the relationship between changes in FC and neuropsychological performance. Results: Compared to HC, AD patients had decreased FC within the caudate, limbic lobe, medial frontal gyrus (MFG), middle temporal gyrus, superior frontal gyrus, parietal lobe/precuneus, inferior temporal gyrus, and posterior cingulate gyrus. Interestingly, MCI patients demonstrated increased FC within inferior parietal lobe, and MFG, while they had decreased FC in the thalamus, inferior frontal gyrus, and superior frontal gyrus. Further analysis indicated that FC changes between the left crus II and the right thalamus, as well as between left lobule IX and the right parietal lobe, were both associated with cognitive decline in AD. Disrupted FC between left crus II and right thalamus, as well as between left lobule IX and right parietal lobe, was associated with attention deficit among subjects with MCI. Conclusion: These findings indicate that cortico-cerebellar FC in MCI and AD patients was significantly disrupted with different distributions, particularly in the default mode networks (DMN) and fronto-parietal networks (FPN) region. Increased activity within the fronto-parietal areas of MCI patients indicated a possible compensatory role for the cerebellum in cognitive impairment. Therefore, alterations in the cortico-cerebellar FC represent a novel approach for early diagnosis and a potential therapeutic target for early intervention.

Simple Quantitative Indices for the Differentiation of Advanced-Stage Alzheimer's Disease and Other Limbic Tauopathies

BACKGROUND

The differentiation of Alzheimer's disease (AD) from age-related limbic tauopathies (LT), including argyrophilic grain disease (AGD) and senile dementia of the neurofibrillary tangle type (SD-NFT), is often challenging because specific clinical diagnostic criteria have not yet been established. Despite the utility of specific biomarkers evaluating amyloid and tau to detect the AD-related pathophysiological changes, the expense and associated invasiveness preclude their use as first-line diagnostic tools for all demented patients. Therefore, less invasive and costly biomarkers would be valuable in routine clinical practice for the differentiation of AD and LT.

OBJECTIVE

The purpose of this study is to develop a simple reproducible method on magnetic resonance imaging (MRI) that could be adopted in daily clinical practice for the differentiation of AD and other forms of LT.

METHODS

Our newly proposed three quantitative indices and well-known medial temporal atrophy (MTA) score were evaluated using MRI of pathologically-proven advanced-stage 21 AD, 10 AGD, and 2 SD-NFT patients.

RESULTS

Contrary to MTA score, hippocampal angle (HPA), inferior horn area (IHA), and ratio between HPA and IHA (i.e., IHPA index) demonstrated higher diagnostic performance and reproducibility, especially to differentiate advanced-stage AD patients with Braak neurofibrillary tangle stage V/VI from LT patients (the area under the receiver-operating-characteristic curve of 0.83, 089, and 0.91; intraclass correlation coefficients of 0.930, 0.998, and 0.995, respectively).

CONCLUSION

Quantitative indices reflecting hippocampal deformation with ventricular enlargement are useful to differentiate advanced-stage AD from LT. This simple and convenient method could be useful in daily clinical practice.

Imaging Genetics Study Based on a Temporal Group Sparse Regression and Additive Model for Biomarker Detection of Alzheimer's Disease

Imaging genetics is an effective tool used to detect potential biomarkers of Alzheimer's disease (AD) in imaging and genetic data. Most existing imaging genetics methods analyze the association between brain imaging quantitative traits (QTs) and genetic data [e.g., single nucleotide polymorphism (SNP)] by using a linear model, ignoring correlations between a set of QTs and SNP groups, and disregarding the varied associations between longitudinal imaging QTs and SNPs. To solve these problems, we propose a novel temporal group sparsity regression and additive model (T-GSRAM) to identify associations between longitudinal imaging QTs and SNPs for detection of potential AD biomarkers. We first construct a nonparametric regression model to analyze the nonlinear association between QTs and SNPs, which can accurately model the complex influence of SNPs on QTs. We then use longitudinal QTs to identify the trajectory of imaging genetic patterns over time. Moreover, the SNP information of group and individual levels are incorporated into the proposed method to boost the power of biomarker detection. Finally, we propose an efficient algorithm to solve the whole T-GSRAM model. We evaluated our method using simulation data and real data obtained from AD neuroimaging initiative. Experimental results show that our proposed method outperforms several state-of-the-art methods in terms of the receiver operating characteristic curves and area under the curve. Moreover, the detection of AD-related genes and QTs has been confirmed in previous studies, thereby further verifying the effectiveness of our approach and helping understand the genetic basis over time during disease progression.

Neuroimaging in Frontotemporal Dementia: Heterogeneity and Relationships with Underlying Neuropathology

Frontotemporal dementia encompasses a group of clinical syndromes defined pathologically by degeneration of the frontal and temporal lobes. Historically, these syndromes have been challenging to diagnose, with an average of about three years between the time of symptom onset and the initial evaluation and diagnosis. Research in the field of neuroimaging has revealed numerous biomarkers of the various frontotemporal dementia syndromes, which has provided clinicians with a method of narrowing the differential diagnosis and improving diagnostic accuracy. As such, neuroimaging is considered a core investigative tool in the evaluation of neurodegenerative disorders. Furthermore, patterns of neurodegeneration correlate with the underlying neuropathological substrates of the frontotemporal dementia syndromes, which can aid clinicians in determining the underlying etiology and improve prognostication. This review explores the advancements in neuroimaging and discusses the phenotypic and pathologic features of behavioral variant frontotemporal dementia, semantic variant primary progressive aphasia, and nonfluent variant primary progressive aphasia, as seen on structural magnetic resonance imaging and positron emission tomography.

Hearing loss and dementia: radiologic and biomolecular basis of their shared characteristics. A systematic review

Dementia and hearing loss share radiologic and biologic findings that might explain their coexistence, especially in the elderly population. Brain atrophy has been observed in both conditions, as well as the presence of areas of gliosis. The brain atrophy is usually focal; it is located in the temporal lobe in patients with hearing loss, while it involves different part of brain in patients with dementia. Radiological studies have shown white matter hyperintensities (WMHs) in both conditions. WMHs have been correlated with the inability to correctly understand words in elderly persons with normal auditory thresholds and, the identification of these lesion in brain magnetic resonance imaging studies has been linked with an increased risk of developing cognitive loss. In addition to WMHs, some anatomopathological studies identified the presence of brain gliosis in the elderly's brain. The cause-effect link between hearing loss and dementia is still unknown, despite they might share some common findings. The aim of this systematic review is to analyze radiologic and biomolecular findings that these two conditions might share, identify a common pathological basis, and discuss the effects of hearing aids on prevention and treatment of cognitive decline in elderly patients with hearing loss.

Volumetric MRI demonstrates atrophy of the olfactory cortex in AD

OBJECTIVE

Alzheimer disease (AD) is a chronic neurodegenerative disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction and deficits in attention, planning, language, and overall cognitive function. Olfactory dysfunction is a common symptom of AD and evidence supports that it is an early marker. Furthermore, olfactory bulb and entorhinal cortex atrophy are well described in AD. However, in AD, no studies have assessed the olfactory cortex as a whole and if sex effects are observed.

METHODS

Magnetic Resonance Imaging was used to scan 39 participants with an average age of 72 years and included men and women. AAL Single-Subject Atlas (implemented in PNEURO tool - PMOD 3.8) was used to determine the volume of the olfactory cortex and the hippocampus. Olfactory cortex volume was lower in both men and women AD cases compared with controls. This decrease was more apparent in the left olfactory cortex and was influenced by age. As expected, hippocampal volume was also significantly reduced in AD. However, this was only observed in the male cohort. A significant correlation was observed between levels of education and hippocampal volume in controls that were not detected in the AD participants. Asymmetry was observed in the olfactory cortex volume when comparing left and right volumes in both the control and AD participants, which was not observed in the hippocampus.

RESULTS

These data highlight the importance of the role of olfactory cortical atrophy in the pathogenesis of AD and the interplay between the olfactory deficits and degeneration of olfactory regions in the brain.

Subtle executive deficits are associated with higher brain amyloid burden and lower cortical volume in subjective cognitive decline: the FACEHBI cohort

To determine whether lower performance on executive function tests in subjective cognitive decline (SCD) individuals are associated with higher levels of brain amyloid beta (Aβ) deposition and regional volumetric reduction in areas of interest for Alzheimer’s disease (AD). 195 individuals with SCD from the FACEHBI study were assessed with a neuropsychological battery that included the following nine executive function tests: Trail Making Test A and B (TMTA, TMTB), the Rule Shift Cards subtest of BADS, the Automatic Inhibition subtest of the Syndrom Kurz Test (AI-SKT), Digit Span Backwards and Similarities from WAIS-III, and the letter, semantic, and verb fluency tests. All subjects underwent an 18F-Florbetaben positron emission tomography (FBB-PET) scan to measure global standard uptake value ratio (SUVR), and a magnetic resonance imaging (MRI). A multiple regression analysis, adjusted for age, was carried out to explore the association between global SUVR and performance on executive tests. Then, on those tests significantly associated with amyloid burden, a voxel-based morphometry (VBM) analysis was carried out to explore their correlates with grey matter volume. Multiple regression analysis revealed a statistically significant association between Aβ deposition and performance on one of the executive tests (the AI-SKT). Moreover, VBM analysis showed worse AI-SKT scores were related to lower volume in bilateral hippocampus and left inferior frontal regions. In conclusion, in SCD individuals, worse automatic inhibition ability has been found related to higher cerebral Aβ deposition and lower volume in the hippocampus and frontal regions. Thus, our results may contribute to the early detection of AD in individuals with SCD.

Prognostic value of complementary biomarkers of neurodegeneration in a mixed memory clinic cohort

Background

Biomarkers of neurodegeneration, e.g. MRI brain atrophy and [¹⁸F]FDG-PET hypometabolism, are often evaluated in patients suspected of neurodegenerative disease.

Objective

Our primary objective was to investigate prognostic properties of atrophy and hypometabolism.

Methods

From March 2015-June 2016, 149 patients referred to a university hospital memory clinic were included. The primary outcome was progression/stable disease course as assessed by a clinician at 12 months follow-up. Intracohort defined z-scores of baseline MRI automatic quantified volume and [¹⁸F]FDG-PET standardized uptake value ratios were calculated for all unilaterally defined brain lobes and dichotomized as pronounced atrophy (+A)/ pronounced hypometabolism (+H) at z-score <0. A logistic regression model with progression status as the outcome was carried out with number of lobes with the patterns +A/-H, -A/+H, +A/+H respectively as predictors. The model was mutually adjusted along with adjustment for age and sex. A sensitivity analysis with a z-score dichotomization at −0.1 and −0.5 and dichotomization regarding number of lobes affected at one and three lobes was done.

Results

Median follow-up time was 420 days [IQR: 387-461 days] and 50 patients progressed. Patients with two or more lobes affected by the pattern +A/+H compared to patients with 0–1 lobes affected had a statistically significant increased risk of progression (odds ratio, 95 % confidence interval: 4.33, 1.90–9.86) in a multivariable model. The model was partially robust to the applied sensitivity analysis.

Conclusion

Combined atrophy and hypometabolism as assessed by MRI and [¹⁸F]FDG-PET in patients under suspicion of neurodegenerative disease predicts progression over 1 year.

Neuropathologic features associated with basal forebrain atrophy in Alzheimer disease

OBJECTIVE

To study the neuropathologic correlates of cholinergic basal forebrain (BF) atrophy as determined using antemortem MRI in the Alzheimer disease (AD) spectrum.

METHODS

We determined associations between BF volume from antemortem MRI brain scans and postmortem assessment of neuropathologic features, including neuritic plaques, neurofibrillary tangles (NFTs), Lewy body (LB) pathology, and TDP-43, in 64 cases of the Alzheimer's Disease Neuroimaging Initiative cohort. For comparison, we assessed neuropathologic features associated with hippocampal and parahippocampal gyrus atrophy. In addition to region of interest-based analysis, we determined the association of neuropathologic features with whole brain gray matter volume using regionally unbiased voxel-based volumetry.

RESULTS

BF atrophy was associated with Thal amyloid phases (95% confidence interval [CI] -0.49 to -0.01, p = 0.049) and presence of LB pathology (95% CI -0.54 to -0.06, p = 0.015), as well as with the degree of LB pathology within the nucleus basalis Meynert (95% CI -0.54 to -0.07, p = 0.025). These effects were no longer significant after false discovery rate (FDR) correction. Hippocampal atrophy was significantly associated with the presence of TDP-43 pathology (95% CI -0.61 to -0.17, p = 0.003; surviving FDR correction), in addition to dentate gyrus NFT load (95% CI -0.49 to -0.01, p = 0.044; uncorrected). Voxel-based analysis confirmed spatially restricted effects of Thal phases and presence of LB pathology on BF volume.

CONCLUSIONS

These findings indicate that neuropathologic correlates of regional atrophy differ substantially between different brain regions that are typically involved in AD-related neurodegeneration, including different susceptibilities to common comorbid pathologies.

CDH6 and HAGH protein levels in plasma associate with Alzheimer's disease in APOE ε4 carriers

Many Alzheimer’s disease (AD) genes including Apolipoprotein E (APOE) are found to be expressed in blood-derived macrophages and thus may alter blood protein levels. We measured 91 neuro-proteins in plasma from 316 participants of the Rotterdam Study (incident AD = 161) using Proximity Extension Ligation assay. We studied the association of plasma proteins with AD in the overall sample and stratified by APOE. Findings from the Rotterdam study were replicated in 186 AD patients of the BioFINDER study. We further evaluated the correlation of these protein biomarkers with total tau (t-tau), phosphorylated tau (p-tau) and amyloid-beta (Aβ) 42 levels in cerebrospinal fluid (CSF) in the Amsterdam Dementia Cohort (N = 441). Finally, we conducted a genome-wide association study (GWAS) to identify the genetic variants determining the blood levels of AD-associated proteins. Plasma levels of the proteins, CDH6 (β = 0.638, P = 3.33 × 10⁻⁴) and HAGH (β = 0.481, P = 7.20 × 10⁻⁴), were significantly elevated in APOE ε4 carrier AD patients. The findings in the Rotterdam Study were replicated in the BioFINDER study for both CDH6 (β = 1.365, P = 3.97 × 10⁻³) and HAGH proteins (β = 0.506, P = 9.31 × 10⁻⁷) when comparing cases and controls in APOE ε4 carriers. In the CSF, CDH6 levels were positively correlated with t-tau and p-tau in the total sample as well as in APOE ε4 stratum (P < 1 × 10⁻³). The HAGH protein was not detected in CSF. GWAS of plasma CDH6 protein levels showed significant association with a cis-regulatory locus (rs111283466, P = 1.92 × 10⁻⁹). CDH6 protein is implicated in cell adhesion and synaptogenesis while HAGH protein is related to the oxidative stress pathway. Our findings suggest that these pathways may be altered during presymptomatic AD and that CDH6 and HAGH may be new blood-based biomarkers.

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology at the earliest stage of some neurodegenerative disorders, but do not have the scalability needed for population screening. Therefore, a blood-based marker for such pathophysiology would have greater utility in a primary care setting and in eligibility screening for clinical trials. Rapid advances in ultra-sensitive assays have enabled the levels of pathological proteins to be measured in blood samples, but research has been predominantly focused on Alzheimer disease (AD). Nonetheless, proteins that were identified as potential blood-based biomarkers for AD, for example, amyloid-β, tau, phosphorylated tau and neurofilament light chain, are likely to be relevant to other neurodegenerative disorders that involve similar pathological processes and could also be useful for the differential diagnosis of clinical symptoms. This Review outlines the neuropathological, clinical, molecular imaging and cerebrospinal fluid features of the most common neurodegenerative disorders outside the AD continuum and gives an overview of the current status of blood-based biomarkers for these disorders.

The Neural Correlates of Impaired Self-Monitoring Among Individuals With Neurodegenerative Dementias

Self-monitoring is a crucial component of human empathy and necessary for the formation and repair of social relations. Several studies have brought to light possible neuronal substrates associated with self-monitoring, but the information that they have provided is inconclusive. The authors, therefore, studied a large group of patients with dementia to assess what brain structures are necessary for the self-monitoring function.Methods: Seventy-seven patients with dementia of various types were screened using voxel-based morphometry to assess possible volume reduction in the brain structures of patients with self-monitoring problems, and the decrease of socioemotional expressiveness and modification of self-presentation was estimated using the Revised Self-Monitoring Scale. Regression analysis was employed to investigate the correlation between gray matter loss and deficient self-monitoring.Results: The socioemotional expressiveness scores were associated with decreased gray matter volume in the right olfactory cortex, inferior frontal gyrus, superior temporal pole, parahippocampal gyrus, insula, and medial temporal gyrus bilaterally. Self-presentation scores were associated with bilateral gray matter volume reduction in the olfactory cortex, insula, rectus gyrus and inferior frontal gyrus, right superior temporal pole, and parahippocampal gyrus, as well as the left medial temporal gyrus and anterior superior frontal gyrus.Conclusions: These results suggest that patients with dementia present decreased ability of self-monitoring, probably due to impaired insula and orbitofrontal cortex and their disconnection from structures of the salience network.

Deficits in Spontaneous Cognition as an Early Marker of Alzheimer's Disease

In the absence of a pharmacological cure, finding the most sensitive early cognitive markers of Alzheimer's disease (AD) is becoming increasingly important. In this article we review evidence showing that brain mechanisms of spontaneous, but stimulus-dependent, cognition overlap with key hubs of the default mode network (DMN) that become compromised by amyloid pathology years before the clinical symptoms of AD. This leads to the formulation of a novel hypothesis which predicts that spontaneous, but stimulus-dependent, conscious retrieval processes, that are generally intact in healthy aging, will be particularly compromised in people at the earliest stages of AD. Initial evidence for this hypothesis is presented across diverse experimental paradigms (e.g., prospective memory, mind-wandering), and new avenues for research in this area are outlined.

Topography of cortical thinning in the Lewy body diseases

Objective

Regional cortical thinning in dementia with Lewy bodies (DLB) and Parkinson disease dementia (PDD) may underlie some aspect of their clinical impairments; cortical atrophy likely reflects extensive Lewy body pathology with alpha-synuclein deposits, as well as associated Alzheimer's disease co-pathologies, when present. Here we investigated the topographic distribution of cortical thinning in these Lewy body diseases compared to cognitively normal PD and healthy non-PD control subjects, explored the association of regional thinning with clinical features and evaluated the impact of amyloid deposition.

Methods

Twenty-one participants with dementia with Lewy bodies (DLB), 16 with Parkinson disease (PD) - associated cognitive impairment (PD-MCI and PDD), and 24 cognitively normal participants with PD underwent MRI, PiB PET, and clinical evaluation. Cortical thickness across the brain and in regions of interest (ROIs) was compared across diagnostic groups and across subgroups stratified by amyloid status, and was related to clinical and cognitive measures.

Results

DLB and PD-impaired groups shared a similar distribution of cortical thinning that included regions characteristic of AD, as well as the fusiform, precentral, and paracentral gyri. Elevated PiB retention in DLB and PD-impaired but not in PD-normal participants was associated with more extensive and severe cortical thinning, in an overlapping topography that selectively affected the medial temporal lobe in DLB participants. In DLB, greater thinning in AD signature and fusiform regions was associated with greater cognitive impairment.

Conclusions

The pattern of cortical thinning is similar in DLB and PD-associated cognitive impairment, overlapping with and extending beyond AD signature regions to involve fusiform, precentral, and paracentral regions. Cortical thinning in AD signature and fusiform regions in these diseases reflects cognitive impairment and is markedly accentuated by amyloid co-pathology. Further work will be required to determine whether the distinct topography of cortical thinning in DLB and PD-associated cognitive impairment might have value as a diagnostic and/ or outcome biomarker in clinical trials.

The association between hippocampal subfield volumes in mild cognitive impairment and conversion to Alzheimer's disease

The hippocampal complex, strongly implicated in Alzheimer's disease (AD), is a region with functionally and structurally distinct subfields. Hippocampal subfield volumes may represent a more sensitive indicators of AD development than total hippocampal volume. We aimed to identify which subfield is the most predictive measure for an AD diagnosis and which is the most specific indicator of the conversion from mild cognitive impairment (MCI) to AD. We analyzed longitudinal structural neuroimaging data of 1350 individuals, 350 healthy controls (HC), 650 MCI and 350 AD, using FreeSurfer v6.0. The linear regression models corrected for total hippocampal volume revealed that subicular fields are the most predictive measures of AD diagnosis. Hippocampal fissure volume was significantly associated with conversion from MCI to AD. Our findings suggest that subicular hippocampal fields are most predictive of AD diagnosis, which has clinical implications for early detection. Specifically, subicular and hippocampal fissure volume measures may be used to select MCI participants who are most likely to convert in AD in clinical trials.