Biological subtypes of Alzheimer disease: A systematic review and meta-analysis

Latent Profile Analysis of Cognition in a Non-Demented Diverse Cohort: A Focus on Modifiable Cardiovascular and Lifestyle Factors

BACKGROUND

Cognitively-defined subgroups are well-documented within neurodegeneration.

OBJECTIVE

We examined such profiles in diverse non-demented older adults and considered how resulting subgroups relate to modifiable factors associated with neurodegeneration.

METHODS

121 non-demented (MMSE = 28.62) diverse (46%non-Latino Black, 40%non-Latino White, 15%Latino) community-dwelling adults (age = 67.7 years) completed cognitive, cardiovascular, physical activity, and diet evaluations. Latent profile analyses (LPA) employed six cognitive scores (letter fluency, letter-number sequencing, confrontational naming, 'animal' fluency, list-learning delayed recall, and recognition discriminability) to characterize cognitively-defined subgroups. Differences between resulting subgroups on cardiovascular (composite scores of overall health; specific health components including fasting blood levels) and lifestyle (sedentary behavior; moderate-to-vigorous physical activity; Mediterranean diet consumption) factors were examined using ANCOVAs adjusting for relevant confounders.

RESULTS

Based on sample means across cognitive scores, LPA resulted in the following cognitive subgroups: 1) high-average cognition, 55%non-Latino White and 64%female participants; 2) average cognition, 58%non-Latino Black and 68%male participants; 3) lower memory, 58%non-Latino Black participants; and 4) lower executive functioning, 70%Latinos. The high-average subgroup reported significantly higher Mediterranean diet consumption than the average subgroup (p = 0.001). The lower executive functioning group had higher fasting glucose and hemoglobin A1c than all other subgroups (p-values<0.001).

CONCLUSION

LPA revealed two average subgroups reflecting level differences in cognition previously reported between non-Latino White and Black adults, and two lower cognition subgroups in domains similar to those documented in neurodegeneration. These subgroups, and their differences, suggest the importance of considering social determinants of health in cognitive aging and modifiable risk.

Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data

Subtype and Stage Inference (SuStaIn) is an unsupervised learning algorithm that uniquely enables the identification of subgroups of individuals with distinct pseudo-temporal disease progression patterns from cross-sectional datasets. SuStaIn has been used to identify data-driven subgroups and perform patient stratification in neurodegenerative diseases and in lung diseases from continuous biomarker measurements predominantly obtained from imaging. However, the SuStaIn algorithm is not currently applicable to discrete ordinal data, such as visual ratings of images, neuropathological ratings, and clinical and neuropsychological test scores, restricting the applicability of SuStaIn to a narrower range of settings. Here we propose 'Ordinal SuStaIn', an ordinal version of the SuStaIn algorithm that uses a scored events model of disease progression to enable the application of SuStaIn to ordinal data. We demonstrate the validity of Ordinal SuStaIn by benchmarking the performance of the algorithm on simulated data. We further demonstrate that Ordinal SuStaIn out-performs the existing continuous version of SuStaIn (Z-score SuStaIn) on discrete scored data, providing much more accurate subtype progression patterns, better subtyping and staging of individuals, and accurate uncertainty estimates. We then apply Ordinal SuStaIn to six different sub-scales of the Clinical Dementia Rating scale (CDR) using data from the Alzheimer's disease Neuroimaging Initiative (ADNI) study to identify individuals with distinct patterns of functional decline. Using data from 819 ADNI1 participants we identified three distinct CDR subtype progression patterns, which were independently verified using data from 790 ADNI2 participants. Our results provide insight into patterns of decline in daily activities in Alzheimer's disease and a mechanism for stratifying individuals into groups with difficulties in different domains. Ordinal SuStaIn is broadly applicable across different types of ratings data, including visual ratings from imaging, neuropathological ratings and clinical or behavioural ratings data.

Effect of Age on Clinical Trial Outcome in Participants with Probable Alzheimer's Disease

Background:

Age may affect treatment outcome in trials of mild probable Alzheimer’s disease (AD).

Objective:

We examined age as a moderator of outcome in an exploratory study of deep brain stimulation targeting the fornix (DBS-f) region in participants with AD.

Methods:

Forty-two participants were implanted with DBS electrodes and randomized to double-blind DBS-f stimulation (“on”) or sham DBS-f (“off”) for 12 months.

Results:

The intervention was safe and well tolerated. However, the selected clinical measures did not differentiate between the “on” and “off” groups in the intent to treat (ITT) population. There was a significant age by time interaction with the Alzheimer’s Disease Assessment Scale; ADAS-cog-13 (p = 0.028). Six of the 12 enrolled participants < 65 years old (50%) markedly declined on the ADAS-cog-13 versus only 6.7%of the 30 participants≥65 years old regardless of treatment assignment (p = 0.005). While not significant, post-hoc analyses favored DBS-f “off” versus “on” over 12 months in the < 65 age group but favored DBS-f “on” versus “off” in the≥65 age group on all clinical metrics. On the integrated Alzheimer’s Disease rating scale (iADRS), the effect size contrasting DBS-f “on” versus “off” changed from +0.2 (favoring “off”) in the < 65 group to –0.52 (favoring “on”) in the≥65 age group.

Conclusion:

The findings highlight issues with subject selection in clinical trials for AD. Faster disease progression in younger AD participants with different AD sub-types may influence the results. Biomarker confirmation and genotyping to differentiate AD subtypes is important for future clinical trials.

Revisiting social MPE: an integration of molecular pathological epidemiology and social science in the new era of precision medicine

INTRODUCTION

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary area examining the relationships between various exposures and pathogenic signatures of diseases. In line with the accelerating advancements in MPE, social science and its health-related interdisciplinary areas have also developed rapidly. Accumulating evidence indicates the pathological role of social-demographic factors. We therefore initially proposed social MPE in 2015, which aims to elucidate etiological roles of social-demographic factors and address health inequalities globally. With the ubiquity of molecular diagnosis, there are ample opportunities for researchers to utilize and develop the social MPE framework.

AREAS COVERED

Molecular subtypes of breast cancer have been investigated rigorously for understanding its etiologies rooted from social factors. Emerging evidence indicates pathogenic heterogeneity of neurological disorders such as Alzheimer's disease. Presenting specific patterns of social-demographic factors across different molecular subtypes should be promising for advancing the screening, prevention, and treatment strategies of those heterogeneous diseases. This article rigorously reviewed literatures investigating differences of race/ethnicity and socioeconomic status across molecular subtypes of breast cancer and Alzheimer's disease to date.

EXPERT OPINION

With advancements of the multi-omics technologies, we foresee a blooming of social MPE studies, which can address health disparities, advance personalized molecular medicine, and enhance public health.

Short leukocyte telomeres predict 25-year Alzheimer's disease incidence in non-APOE ε4-carriers

BACKGROUND

Leukocyte telomere length (LTL) has been shown to predict Alzheimer's disease (AD), albeit inconsistently. Failing to account for the competing risks between AD, other dementia types, and mortality, can be an explanation for the inconsistent findings in previous time-to-event analyses. Furthermore, previous studies indicate that the association between LTL and AD is non-linear and may differ depending on apolipoprotein E (APOE) ε4 allele carriage, the strongest genetic AD predictor.

METHODS

We analyzed whether baseline LTL in interaction with APOE ε4 predicts AD, by following 1306 initially non-demented subjects for 25 years. Gender- and age-residualized LTL (rLTL) was categorized into tertiles of short, medium, and long rLTLs. Two complementary time-to-event models that account for competing risks were used; the Fine-Gray model to estimate the association between the rLTL tertiles and the cumulative incidence of AD, and the cause-specific hazard model to assess whether the cause-specific risk of AD differed between the rLTL groups. Vascular dementia and death were considered competing risk events. Models were adjusted for baseline lifestyle-related risk factors, gender, age, and non-proportional hazards.

RESULTS

After follow-up, 149 were diagnosed with AD, 96 were diagnosed with vascular dementia, 465 died without dementia, and 596 remained healthy. Baseline rLTL and other covariates were assessed on average 8 years before AD onset (range 1-24). APOE ε4-carriers had significantly increased incidence of AD, as well as increased cause-specific AD risk. A significant rLTL-APOE interaction indicated that short rLTL at baseline was significantly associated with an increased incidence of AD among non-APOE ε4-carriers (subdistribution hazard ratio = 3.24, CI 1.404-7.462, P = 0.005), as well as borderline associated with increased cause-specific risk of AD (cause-specific hazard ratio = 1.67, CI 0.947-2.964, P = 0.07). Among APOE ε4-carriers, short or long rLTLs were not significantly associated with AD incidence, nor with the cause-specific risk of AD.

CONCLUSIONS

Our findings from two complementary competing risk time-to-event models indicate that short rLTL may be a valuable predictor of the AD incidence in non-APOE ε4-carriers, on average 8 years before AD onset. More generally, the findings highlight the importance of accounting for competing risks, as well as the APOE status of participants in AD biomarker research.

The existence of Aβ strains and their potential for driving phenotypic heterogeneity in Alzheimer's disease

Reminiscent of the human prion diseases, there is considerable clinical and pathological variability in Alzheimer's disease, the most common human neurodegenerative condition. As in prion disorders, protein misfolding and aggregation is a hallmark feature of Alzheimer's disease, where the initiating event is thought to be the self-assembly of Aβ peptide into aggregates that deposit in the central nervous system. Emerging evidence suggests that Aβ, similar to the prion protein, can polymerize into a conformationally diverse spectrum of aggregate strains both in vitro and within the brain. Moreover, certain types of Aβ aggregates exhibit key hallmarks of prion strains including divergent biochemical attributes and the ability to induce distinct pathological phenotypes when intracerebrally injected into mouse models. In this review, we discuss the evidence demonstrating that Aβ can assemble into distinct strains of aggregates and how such strains may be primary drivers of the phenotypic heterogeneity in Alzheimer's disease.

Subcortical and Cortical Regions of Amyloid-β Pathology Measured by 11C-PiB PET Are Differentially Associated with Cognitive Functions and Stages of Disease in Memory Clinic Patients

BACKGROUND

The effect of regional brain amyloid-β (Aβ) pathology on specific cognitive functions is incompletely known.

OBJECTIVE

The relationship between Aβ and cognitive functions was investigated in this cross-sectional multicenter study of memory clinic patients.

METHODS

The participants were patients diagnosed with Alzheimer's disease (AD, n = 83), mild cognitive impairment (MCI, n = 60), and healthy controls (HC, n = 32), who had been scanned by 11C-PiB PET in 13 brain regions of both hemispheres and who had been assessed by cognitive tests covering seven domains.

RESULTS

Hierarchic multiple regression analyses were performed on each cognitive test as dependent variable, controlling for demographic characteristics and APOE status (block 1) and PiB measures in 13 brain regions (block 2) as independent variables. The model was highly significant for each cognitive test and most strongly for tests of episodic memory (learning and retention) versus PiB in putamen, visuospatially demanding tests (processing and retention) versus the occipital lobe, semantic fluency versus the parietal lobe, attention versus posterior gyrus cinguli, and executive function versus nucleus accumbens. In addition, education had a positively and APOE status a negatively significant effect on cognitive tests.

CONCLUSION

Five subcortical and cortical regions with Aβ pathology are differentially associated with cognitive functions and stages of disease in memory clinic patients.

Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort

Data-driven disease progression models have provided important insight into the timeline of brain changes in AD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a population-based setting has not yet been investigated. In this study, we investigated if the disease timelines constructed in a case-controlled setting, with subjects stratified according to APOE status, are generalizable to a population-based cohort, and if progression along these disease timelines is predictive of AD. Seven volumetric biomarkers derived from structural MRI were considered. We estimated APOE-specific disease timelines of changes in these biomarkers using a recently proposed method called co-initialized discriminative event-based modeling (co-init DEBM). This method can also estimate a disease stage for new subjects by calculating their position along the disease timelines. The model was trained and cross-validated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and tested on the population-based Rotterdam Study (RS) cohort. We compared the diagnostic and prognostic value of the disease stage in the two cohorts. Furthermore, we investigated if the rate of change of disease stage in RS participants with longitudinal MRI data was predictive of AD. In ADNI, the estimated disease timeslines for ϵ4 non-carriers and carriers were found to be significantly different from one another (p<0.001). The estimate disease stage along the respective timelines distinguished AD subjects from controls with an AUC of 0.83 in both APOEϵ4 non-carriers and carriers. In the RS cohort, we obtained an AUC of 0.83 and 0.85 in ϵ4 non-carriers and carriers, respectively. Progression along the disease timelines as estimated by the rate of change of disease stage showed a significant difference (p<0.005) for subjects with pre-symptomatic AD as compared to the general aging population in RS. It distinguished pre-symptomatic AD subjects with an AUC of 0.81 in APOEϵ4 non-carriers and 0.88 in carriers, which was better than any individual volumetric biomarker, or its rate of change, could achieve. Our results suggest that co-init DEBM trained on case-controlled data is generalizable to a population-based cohort setting and that progression along the disease timelines is predictive of the development of AD in the general population. We expect that this approach can help to identify at-risk individuals from the general population for targeted clinical trials as well as to provide biomarker based objective assessment in such trials.

Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency" and decrease of the "clustering coefficient" in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes.

Multi-Atlas MRI-Based Striatum Segmentation for 123I-FP-CIT SPECT (DAT-SPECT) Compared With the Bolt Method and SPECT-Atlas-Based Segmentation Method Toward the Accurate Diagnosis of Parkinson's Disease/Syndrome

Aims: This study aimed to analyze the performance of multi-atlas MRI-based parcellation for ¹²³I-FP-CIT SPECT (DAT-SPECT) in healthy volunteers. The proposed method was compared with the SPECT-atlas-based and Bolt methods. ¹⁸F-FE-PE2I-PET (DAT-PET) was used as a reference.

Methods: Thirty healthy subjects underwent DAT-SPECT, DAT-PET, and 3D-T1WI-MRI. We calculated the striatum uptake ratio (SUR/SBR), caudate uptake ratio (CUR), and putamen uptake ratio (PUR) for DAT-SPECT using the multi-atlas MRI-based method, SPECT-atlas-based method, and Bolt method. In the multi-atlas MRI-based method, the cerebellum, occipital cortex, and whole-brain were used as reference regions. The correlation of age with DAT-SPECT activity and the correlations of SUR/SBR, CUR, and PUR between DAT-SPECT and DAT-PET were calculated by each of the three methods.

Results: The correlation between age and SUR/SBR for DAT-SPECT based on the multi-atlas MRI-based method was comparable to that based on the SPECT-atlas-based method (r = −0.441 to −0.496 vs. −0.488). The highest correlation between DAT-SPECT and DAT-PET was observed using the multi-atlas MRI-based method with the occipital lobe defined as the reference region compared with the SPECT-atlas-based and Bolt methods (SUR, CUR, and PUR: 0.687, 0.723, and 0.676 vs. 0.698, 0.660, and 0.616 vs. 0.655).

Conclusion: Multi-atlas MRI-based parcellation with the occipital lobe defined as the reference region was at least comparable to the clinical methods.

Pathobiological Subtypes of Alzheimer Disease

Alzheimer disease (AD), the most common form of dementia, is a heterogenous disorder with various pathobiological subtypes. In addition to the 4 major subtypes based on the distribution of tau pathology and brain atrophy (typical, limbic predominant, hippocampal sparing, and minimal atrophy [MA]), several other clinical variants showing distinct regional patterns of tau burden have been identified: nonamnestic, corticobasal syndromal, primary progressive aphasia, posterior cortical atrophy, behavioral/dysexecutive, and mild dementia variants. Among the subtypes, differences were found in age at onset, sex distribution, cognitive status, disease duration, APOE genotype, and biomarker levels. The patterns of key network destructions parallel the tau and atrophy patterns of the AD subgroups essentially. Interruption of key networks, in particular the default-mode network that is responsible for cognitive decline, is consistent in hetero-genous AD groups. AD pathology is often associated with co-pathologies: cerebrovascular lesions, Lewy pathology, and TDP-43 proteinopathies. These mixed pathologies essentially influence the clinical picture of AD and may accel-erate disease progression. Unraveling the heterogeneity among the AD spectrum entities is important for opening a window to pathogenic mechanisms affecting the brain and enabling precision medicine approaches as a basis for developing preventive and ultimately successful disease-modifying therapies for AD.

Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β_1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.

Four distinct trajectories of tau deposition identified in Alzheimer's disease

Alzheimer's disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These 'subtypes' were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.

Quantitative Radiomic Features as New Biomarkers for Alzheimer's Disease: An Amyloid PET Study

Growing evidence indicates that amyloid-beta (Aβ) accumulation is one of the most common neurobiological biomarkers in Alzheimer's disease (AD). The primary aim of this study was to explore whether the radiomic features of Aβ positron emission tomography (PET) images are used as predictors and provide a neurobiological foundation for AD. The radiomics features of Aβ PET imaging of each brain region of the Brainnetome Atlas were computed for classification and prediction using a support vector machine model. The results showed that the area under the receiver operating characteristic curve (AUC) was 0.93 for distinguishing AD (N = 291) from normal control (NC; N = 334). Additionally, the AUC was 0.83 for the prediction of mild cognitive impairment (MCI) converting (N = 88) (vs. no conversion, N = 100) to AD. In the MCI and AD groups, the systemic analysis demonstrated that the classification outputs were significantly associated with clinical measures (apolipoprotein E genotype, polygenic risk scores, polygenic hazard scores, cerebrospinal fluid Aβ, and Tau, cognitive ability score, the conversion time for progressive MCI subjects and cognitive changes). These findings provide evidence that the radiomic features of Aβ PET images can serve as new biomarkers for clinical applications in AD/MCI, further providing evidence for predicting whether MCI subjects will convert to AD.

In vitro Characterization of the Regional Binding Distribution of Amyloid PET Tracer Florbetaben and the Glia Tracers Deprenyl and PK11195 in Autopsy Alzheimer's Brain Tissue

BACKGROUND

Emerging evidence indicates a central role of gliosis in Alzheimer's disease (AD) pathophysiology. However, the regional distribution and interaction of astrogliosis and microgliosis in association with amyloid-β (Aβ) still remain uncertain.

OBJECTIVE

Here we studied the pathological profiles in autopsy AD brain by using specific imaging tracers.

METHODS

Autopsy brain tissues of AD (n = 15, age 70.4±8.5 years) and control cases (n = 12, age 76.6±10.9) were examined with homogenate binding assays, autoradiography for Aβ plaques (3H-florbetaben/3H-PIB), astrogliosis (3H-L-deprenyl), and microgliosis (3H-PK11195/3H-FEMPA), as well as immunoassays.

RESULTS

In vitro saturation analysis revealed high-affinity binding sites of 3H-florbetaben, 3H-L-deprenyl, and 3H-PK11195/3H-FEMPA in the frontal cortex of AD cases. In vitro3H-florbetaben binding increased across cortical and subcortical regions of AD compared to control with the highest binding in the frontal and parietal cortices. The in vitro3H-L-deprenyl binding showed highest binding in the hippocampus (dentate gyrus) followed by cortical and subcortical regions of AD while the GFAP expression was upregulated only in the hippocampus compared to control. The in vitro3H-PK11195 binding was solely increased in the parietal cortex and the hippocampus of AD compared to control. The 3H-florbetaben binding positively correlated with the 3H-L-deprenyl binding in the hippocampus and parietal cortex of AD and controls. Similarly, a positive correlation was observed between 3H-florbetaben binding and GFAP expression in hippocampus of AD and control.

CONCLUSION

The use of multi-imaging tracers revealed different regional pattern of changes in autopsy AD brain with respect to amyloid plaque pathology versus astrogliosis and microgliosis.

A Review of Brain Atrophy Subtypes Definition and Analysis for Alzheimer’s Disease Heterogeneity Studies

Alzheimer’s disease (AD) is a heterogeneous disease with different subtypes. Studying AD subtypes from brain structure, neuropathology, and cognition are of great importance for AD heterogeneity research. Starting from the study of constructing AD subtypes based on the features of T1-weighted structural magnetic resonance imaging, this paper introduces the major connections between the subtype definition and analysis strategies, including brain region-based subtype definition, and their demographic, neuropathological, and neuropsychological characteristics. The advantages and existing problems are analyzed, and reasonable improvement schemes are prospected. Overall, this review offers a more comprehensive view in the field of atrophy subtype in AD, along with their advantages, challenges, and future prospects, and provide a basis for improving individualized AD diagnosis.

Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease

INTRODUCTION

We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).

METHODS

A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.

RESULTS

Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.

CONCLUSIONS

Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.

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.

Amyloid pathology arrangements in Alzheimer's disease brains modulate in vivo seeding capability

Amyloid-β (Aβ) misfolding is one of the hallmark pathological features of Alzheimer's disease (AD). AD can manifest with diverse symptomatology including variable rates of cognitive decline, duration of clinical disease, and other detrimental changes. Several reports suggest that conformational diversity in misfolded Aβ is a leading factor for clinical variability in AD, analogous to what it has been described for prion strains in prion diseases. Notably, prion strains generate diverse patterns of misfolded protein deposition in the brains of affected individuals. Here, we tested the in vivo prion-like transmission features of four AD brains displaying particular patterns of amyloidosis. AD brains induced different phenotypes in recipient mice, as evaluated by their specific seeding activity, as well as the total amount of Aβ deposited surrounding vascular structures and the reactivity of amyloid pathology to thioflavin S. Our results support the notion that AD-subtypes are encoded in disease-associated Aβ. Further research exploring whether AD include a spectrum of different clinical conditions or syndromes may pave the way to personalized diagnosis and treatments.

Decoding Causal Links Between Sleep Apnea and Alzheimer’s Disease

Obstructive sleep apnea (OSA) and Alzheimer’s disease (AD) are two common chronic diseases with a well-documented association. Whether the association is causal has been highlighted by recent evidence reporting a neurobiological link between these disorders. This narrative review discusses the brain regions and networks involved in OSA as potential vulnerable areas for the development of AD neuropathology with a particular focus on gender-related implications. Using a neuroimaging perspective supported by neuropathological investigations, we provide a new model of neurodegeneration common to OSA and AD, that we have called OSA-AD neurodegeneration in order to decode the causal links between these two chronic conditions.

The Effect of GBA Mutations and APOE Polymorphisms on Dementia with Lewy Bodies in Ashkenazi Jews

BACKGROUND

Glucocerebrosidase (GBA) gene mutations and APOE polymorphisms are common in dementia with Lewy bodies (DLB), however their clinical impact is only partially elucidated.

OBJECTIVE

To explore the clinical impact of mutations in the GBA gene and APOE polymorphisms separately and in combination, in a cohort of Ashkenazi Jewish (AJ) patients with DLB.

METHODS

One hundred consecutively recruited AJ patients with clinically diagnosed DLB underwent genotyping for GBA mutations and APOE polymorphisms, and performed cognitive and motor clinical assessments.

RESULTS

Thirty-two (32%) patients with DLB were carriers of GBA mutations and 33 (33%) carried an APOE ɛ4 allele. GBA mutation carriers had a younger age of onset (mean [SD] age, 67.2 years [8.9] versus 71.97 [5.91]; p = 0.03), poorer cognition as assessed by the Mini-Mental State Examination (21.41 [6.9] versus 23.97 [5.18]; p < 0.005), and more severe parkinsonism as assessed with the Unified Parkinson's Disease Rating Scale motor part III (34.41 [13.49] versus 28.38 [11.21]; p = 0.01) compared to non-carriers. There were statistically significant interactions between the two genetic factors, so that patients who carried both a mild GBA mutation and the APOE ɛ4 allele (n = 9) had more severe cognitive (p = 0.048) and motor dysfunction (p = 0.037).

CONCLUSION

We found a high frequency of both GBA mutations and the APOE ɛ4 allele among AJ patients with DLB, both of which have distinct effects on the clinical disease phenotype, separately and in combination.

Mutual structural effects of unmodified and pyroglutamylated amyloid β peptides during aggregation

Amyloid β (Aβ) peptide aggregates are linked to Alzheimer's disease (AD). Posttranslationally pyroglutamylated Aβ (pEAβ) occurs in AD brains in significant quantities and is hypertoxic, but the underlying structural and aggregation properties remain poorly understood. Here, the structure and aggregation of Aβ_1-40 and pEAβ_3-40 are analyzed separately and in equimolar combination. Circular dichroism data show that Aβ_1-40 , pEAβ_3-40 , and their combination assume α-helical structure in dry state and transition to unordered structure in aqueous buffer. Aβ_1-40 and the 1:1 combination gradually acquire β-sheet structure while pEAβ_3-40 adopts an α-helix/β-sheet conformation. Thioflavin-T fluorescence studies suggest that the two peptides mutually inhibit fibrillogenesis. Fourier transform infrared (FTIR) spectroscopy identifies the presence of β-turn and α-helical structures in addition to β-sheet structure in peptides in aqueous buffer. The kinetics of transitions from the initial α-helical structure to β-sheet structure were resolved by slow hydration of dry peptides by D₂ O vapor, coupled with isotope-edited FTIR. These data confirmed the mutual suppression of β-sheet formation by the two peptides. Remarkably, pEAβ_3-40 maintained a significant fraction of α-helical structure in the combined sample, implying a reduced β-sheet propensity of pEAβ_3-40 . Altogether, the data imply that the combination of unmodified and pyroglutamylated Aβ peptides resists fibrillogenesis and favors the prefibrillar state, which may underlie hypertoxicity of pEAβ.

Multiple Subtypes of Alzheimer's Disease Base on Brain Atrophy Pattern

Alzheimer’s disease (AD) is a disease of a heterogeneous nature, which can be disentangled by exploring the characteristics of each AD subtype in the brain structure, neuropathology, and cognition. In this study, a total of 192 AD and 228 cognitively normal (CN) subjects were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Based on the cortical thickness patterns, the mixture of experts method (MOE) was applied to the implicit model spectrum of transforms lined with each AD subtype, then their neuropsychological and neuropathological characteristics were analyzed. Furthermore, the piecewise linear classifiers composed of each AD subtype and CN were resolved, and each subtype was comprehensively explained. The following four distinct AD subtypes were discovered: bilateral parietal, frontal, and temporal atrophy AD subtype (occipital sparing AD subtype (OSAD), 29.2%), left temporal dominant atrophy AD subtype (LTAD, 22.4%), minimal atrophy AD subtype (MAD, 16.1%), and diffuse atrophy AD subtype (DAD, 32.3%). These four subtypes display their own characteristics in atrophy pattern, cognition, and neuropathology. Compared with the previous studies, our study found that some AD subjects showed obvious asymmetrical atrophy in left lateral temporal-parietal cortex, OSAD presented the worst cerebrospinal fluid levels, and MAD had the highest proportions of APOE ε4 and APOE ε2. The subtype characteristics were further revealed from the aspect of the model, making it easier for clinicians to understand. The results offer an effective support for individual diagnosis and prognosis.

Diagnose it yourself: will there be a home test kit for Alzheimer's disease?

Alzheimer's disease is the most common neurodegenerative process leading to dementia. To date, there is no curative approach; thus, establishing a diagnosis as early as possible is necessary to implement preventive measures. However, today's gold standard for diagnosing Alzheimer's disease is high in both cost and effort and is not readily available. This defines the need for low-effort and economic alternatives that give patients low-threshold access to testing systems at their general practitioners or even at home for an independent retrieval of a biologic specimen. This perspective gives an overview of established and novel approaches in the field and speculates on the future of test strategies eventually technically implementable at home.

PET Imaging of Tau Pathology and Amyloid-β, and MRI for Alzheimer's Disease Feature Fusion and Multimodal Classification

BACKGROUND

Machine learning is a promising tool for biomarker-based diagnosis of Alzheimer's disease (AD). Performing multimodal feature selection and studying the interaction between biological and clinical AD can help to improve the performance of the diagnosis models.

OBJECTIVE

This study aims to formulate a feature ranking metric based on the mutual information index to assess the relevance and redundancy of regional biomarkers and improve the AD classification accuracy.

METHODS

From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 722 participants with three modalities, including florbetapir-PET, flortaucipir-PET, and MRI, were studied. The multivariate mutual information metric was utilized to capture the redundancy and complementarity of the predictors and develop a feature ranking approach. This was followed by evaluating the capability of single-modal and multimodal biomarkers in predicting the cognitive stage.

RESULTS

Although amyloid-β deposition is an earlier event in the disease trajectory, tau PET with feature selection yielded a higher early-stage classification F1-score (65.4%) compared to amyloid-β PET (63.3%) and MRI (63.2%). The SVC multimodal scenario with feature selection improved the F1-score to 70.0% and 71.8% for the early and late-stage, respectively. When age and risk factors were included, the scores improved by 2 to 4%. The Amyloid-Tau-Neurodegeneration [AT(N)] framework helped to interpret the classification results for different biomarker categories.

CONCLUSION

The results underscore the utility of a novel feature selection approach to reduce the dimensionality of multimodal datasets and enhance model performance. The AT(N) biomarker framework can help to explore the misclassified cases by revealing the relationship between neuropathological biomarkers and cognition.

Anti-Neurodegenerative Benefits of Acetylcholinesterase Inhibitors in Alzheimer's Disease: Nexus of Cholinergic and Nerve Growth Factor Dysfunction

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is increasingly viewed as a complex multi-dimensional disease without effective treatments. Recent randomized, placebo-controlled studies have shown volume losses of ~0.7% and ~3.5% per year, respectively, in the basal cholinergic forebrain (CBF) and hippocampus in untreated suspected prodromal AD. One year of donepezil treatment reduced these annualized rates of atrophy to about half of untreated rates. Similar positive although variable results have also been found in volumetric measurements of the cortex and whole brain in patients with mild cognitive impairment as well as more advanced AD stages after treatments with all three currently available acetylcholinesterase (AChE) inhibitors (donepezil, rivastigmine, and galantamine). Here we review the anti-neurodegenerative benefits of AChE inhibitors and the expected parallel disease-accelerating impairments caused by anticholinergics, within a framework of the cholinergic hypothesis of AD and AD-associated loss of nerve growth factor (NGF). Consistent with the "loss of trophic factor hypothesis of AD," we propose that AChE inhibitors enhance acetylcholine-dependent release and uptake of NGF, thereby sustaining cholinergic neuronal viability and thus slowing AD-associated degeneration of the CBF, to ultimately delay dementia progression. We propose that improved cholinergic therapies for AD started early in asymptomatic persons, especially those with risk factors, will delay the onset, progression, or emergence of dementia. The currently available competitive and pseudo- irreversible AChE inhibitors are not CNS-selective and thus induce gastrointestinal toxicity that limits cortical AChE inhibition to ~30% (ranges from 19% to 41%) as measured by in vivo PET studies in patients undergoing therapy. These levels of inhibition are marginal relative to what is required for effective symptomatic treatment of dementia or slowing AD-associated neurodegeneration. In contrast, because of the inherently slow de novo synthesis of AChE in the CNS (about one-- tenth the rate of synthesis in peripheral tissues), irreversible AChE inhibitors produce significantly higher levels of inhibition in the CNS than in peripheral tissues. For example, methanesulfonyl fluoride, an irreversible inhibitor reduces CNS AChE activity by ~68% in patients undergoing therapy and ~80% in cortical biopsies of non-human primates. The full therapeutic benefits of AChE inhibitors, whether for symptomatic treatment of dementia or disease-slowing, thus would benefit by producing high levels of CNS inhibition. One way to obtain such higher levels of CNS AChE inhibition would be by using irreversible inhibitors.

Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes

BACKGROUND

Social cognition is critically compromised across neurodegenerative diseases, including the behavioral variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and Parkinson's disease (PD). However, no previous study has used social cognition and other cognitive tasks to predict diagnoses of these conditions, let alone reporting the brain correlates of prediction outcomes.

OBJECTIVE

We performed a diagnostic classification analysis using social cognition, cognitive screening (CS), and executive function (EF) measures, and explored which anatomical and functional networks were associated with main predictors.

METHODS

Multiple group discriminant function analyses (MDAs) and ROC analyses of social cognition (facial emotional recognition, theory of mind), CS, and EF were implemented in 223 participants (bvFTD, AD, PD, controls). Gray matter volume and functional connectivity correlates of top discriminant scores were investigated.

RESULTS

Although all patient groups revealed deficits in social cognition, CS, and EF, our classification approach provided robust discriminatory characterizations. Regarding controls, probabilistic social cognition outcomes provided the best characterization for bvFTD (together with CS) and PD, but not AD (for which CS alone was the best predictor). Within patient groups, the best MDA probabilities scores yielded high classification rates for bvFTD versus PD (98.3%, social cognition), AD versus PD (98.6%, social cognition + CS), and bvFTD versus AD (71.7%, social cognition + CS). Top MDA scores were associated with specific patterns of atrophy and functional networks across neurodegenerative conditions.

CONCLUSION

Standardized validated measures of social cognition, in combination with CS, can provide a dimensional classification with specific pathophysiological markers of neurodegeneration diagnoses.

Severity Distribution of Alzheimer's Disease Dementia and Mild Cognitive Impairment in the Framingham Heart Study

BACKGROUND

Studies providing Alzheimer's disease (AD) prevalence data have largely neglected to characterize the proportion of AD that is mild, moderate, or severe. Estimates of the severity distribution along the AD continuum, including the mild cognitive impairment (MCI) stage, are important to plan research and allocate future resources, particularly resources targeted at particular stages of disease.

OBJECTIVE

To characterize the distribution of severity of AD dementia and MCI among prevalent cases in the population-based Framingham Heart Study.

METHODS

Participants (aged 50-94) with prevalent MCI or AD dementia clinical syndrome were cross-sectionally selected from three time-windows of the population-based Framingham Heart Study in 2004-2005 (n = 381), 2006-2007 (n = 422), and 2008-2009 (n = 389). Summary estimates of the severity distribution were achieved by pooling results across time-windows. Diagnosis and severity were assessed by consensus dementia review. MCI-progressive was determined if the participant had documented progression to AD dementia clinical syndrome using longitudinal data.

RESULTS

Among AD dementia participants, the pooled percentages were 50.4%for mild, 30.3%for moderate, and 19.3%for severe. Among all MCI and AD participants, the pooled percentages were 29.5%, 19.6%, 25.7%, and 45.2%for MCI-not-progressive, MCI-progressive, mild AD dementia, and the combined group of MCI-progressive and mild AD dementia, respectively. Distributions by age and sex were presented.

CONCLUSION

The finding that half of the people living with AD have mild disease underscores the need for research and interventions to slow decline or prevent progression of this burdensome disease.

Clinical relevance of brain atrophy subtypes categorization in memory clinics

INTRODUCTION

The clinical relevance of brain atrophy subtypes categorization in non-demented persons without a priori knowledge regarding their amyloid status or clinical presentation is unknown.

METHODS

A total of 2083 outpatients with either subjective cognitive complaint or mild cognitive impairment at study entry were followed during 4 years (MEMENTO cohort). Atrophy subtypes were defined using baseline magnetic resonance imaging (MRI) and previously described algorithms.

RESULTS

Typical/diffuse atrophy was associated with faster cognitive decline and the highest risk of developing dementia and Alzheimer's disease (AD) over time, both in the whole analytic sample and in amyloid-positive participants. Hippocampal-sparing and limbic-predominant atrophy were also associated with incident dementia, with faster cognitive decline in the limbic predominant atrophy group. Lewy body dementia was more frequent in the hippocampal-sparing and minimal/no atrophy groups.

DISCUSSION

Atrophy subtypes categorization predicted different subsequent patterns of cognitive decline and rates of conversion to distinct etiologies of dementia in persons attending memory clinics.

Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations

Alzheimer's disease (AD) is the most common form of dementia and is phenotypically heterogeneous. APOE is a triallelic gene which correlates with phenotypic heterogeneity in AD. In this work, we determined the effect of APOE alleles on the disease progression timeline of AD using a discriminative event-based model (DEBM). Since DEBM is a data-driven model, stratification into smaller disease subgroups would lead to more inaccurate models as compared to fitting the model on the entire dataset. Hence our secondary aim is to propose and evaluate novel approaches in which we split the different steps of DEBM into group-aspecific and group-specific parts, where the entire dataset is used to train the group-aspecific parts and only the data from a specific group is used to train the group-specific parts of the DEBM. We performed simulation experiments to benchmark the accuracy of the proposed approaches and to select the optimal approach. Subsequently, the chosen approach was applied to the baseline data of 417 cognitively normal, 235 mild cognitively impaired who convert to AD within 3 years, and 342 AD patients from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset to gain new insights into the effect of APOE carriership on the disease progression timeline of AD. In the ε4 carrier group, the model predicted with high confidence that CSF Amyloidβ₄₂ and the cognitive score of Alzheimer's Disease Assessment Scale (ADAS) are early biomarkers. Hippocampus was the earliest volumetric biomarker to become abnormal, closely followed by the CSF Phosphorylated Tau₁₈₁ (PTAU) biomarker. In the homozygous ε3 carrier group, the model predicted a similar ordering among CSF biomarkers. However, the volume of the fusiform gyrus was identified as one of the earliest volumetric biomarker. While the findings in the ε4 carrier and the homozygous ε3 carrier groups fit the current understanding of progression of AD, the finding in the ε2 carrier group did not. The model predicted, with relatively low confidence, CSF Neurogranin as one of the earliest biomarkers along with cognitive score of Mini-Mental State Examination (MMSE). Amyloid β₄₂ was found to become abnormal after PTAU. The presented models could aid understanding of the disease, and in selecting homogeneous group of presymptomatic subjects at-risk of developing symptoms for clinical trials.

A Review and a Framework of Variables for Defining and Characterizing Tinnitus Subphenotypes

Tinnitus patients can present with various characteristics, such as those related to the tinnitus perception, symptom severity, and pattern of comorbidities. It is speculated that this phenotypic heterogeneity is associated with differences in the underlying pathophysiology and personal reaction to the condition. However, there is as yet no established protocol for tinnitus profiling or subtyping, hindering progress in treatment development. This review summarizes data on variables that have been used in studies investigating phenotypic differences in subgroups of tinnitus, including variables used to both define and compare subgroups. A PubMed search led to the identification of 64 eligible articles. In most studies, variables for subgrouping were chosen by the researchers (hypothesis-driven approach). Other approaches included application of unsupervised machine-learning techniques for the definition of subgroups (data-driven), and subgroup definition based on the response to a tinnitus treatment (treatment response). A framework of 94 variable concepts was created to summarize variables used across all studies. Frequency statistics for the use of each variable concept are presented, demonstrating those most and least commonly assessed. This review highlights the high dimensionality of tinnitus heterogeneity. The framework of variables can contribute to the design of future studies, helping to decide on tinnitus assessment and subgrouping.

Behavioral, neuromorphological, and neurobiochemical effects induced by omega-3 fatty acids following basal forebrain cholinergic depletion in aged mice

Background

In recent years, mechanistic, epidemiologic, and interventional studies have indicated beneficial effects of omega-3 polyunsaturated fatty acids (n-3 PUFA) against brain aging and age-related cognitive decline, with the most consistent effects against Alzheimer’s disease (AD) confined especially in the early or prodromal stages of the pathology.

In the present study, we investigated the action of n-3 PUFA supplementation on behavioral performances and hippocampal neurogenesis, volume, and astrogliosis in aged mice subjected to a selective depletion of basal forebrain cholinergic neurons. Such a lesion represents a valuable model to mimic one of the most reliable hallmarks of early AD neuropathology.

Methods

Aged mice first underwent mu-p75-saporin immunotoxin intraventricular lesions to obtain a massive cholinergic depletion and then were orally supplemented with n-3 PUFA or olive oil (as isocaloric control) for 8 weeks. Four weeks after the beginning of the dietary supplementation, anxiety levels as well as mnesic, social, and depressive-like behaviors were evaluated. Subsequently, hippocampal morphological and biochemical analyses and n-3 PUFA brain quantification were carried out.

Results

The n-3 PUFA treatment regulated the anxiety alterations and reverted the novelty recognition memory impairment induced by the cholinergic depletion in aged mice. Moreover, n-3 PUFA preserved hippocampal volume, enhanced neurogenesis in the dentate gyrus, and reduced astrogliosis in the hippocampus. Brain levels of n-3 PUFA were positively related to mnesic abilities.

Conclusions

The demonstration that n-3 PUFA are able to counteract behavioral deficits and hippocampal neurodegeneration in cholinergically depleted aged mice promotes their use as a low-cost, safe nutraceutical tool to improve life quality at old age, even in the presence of first stages of AD.

Alzheimer's disease: from basic science to precision medicine approach

Alzheimer’s disease (AD) is the most common form of dementia in the elderly. Together with cerebral amyloid accumulation, several factors contribute to AD pathology including vascular alterations, systemic inflammation, genetic/epigenetic status and mitochondrial dysfunction. Much is now being devoted to neuroinflammation. However, anti-inflammatory drugs as numerous other therapies, mainly targeted on β-amyloid, have failed to show efficacious effects in AD. Timing, proper selection of patients, and the need for a multitarget approach appear to be the main weak points of current therapeutic efforts. The efficacy of a treatment could be better evaluate if efficient biomarkers are available. We propose here the application of precision medicine principles in AD to simultaneously verify the efficacy of a treatment and the reliability of specific biomarkers according to individually tailored biomarker-guided targeted therapies. People at risk of developing AD or in the very early phase of the disease should be stratified according to: (1) neuropsychological tests; (2) apolipoprotein E (ApoE) genotyping; (3) biochemical analysis of plasma and cerebrospinal fluid (CSF); (4) MRI and positron emission tomography and (5) assessment of their inflammatory profile by an integration of various genetic and biochemical parameters in plasma, CSF and an analysis of microbiota composition. The selected population should be treated with antiamyloidogenic and anti-inflammatory drugs in randomised, longitudinal, placebo-controlled studies using ad hoc profiles (eg, vascular profile, mitochondrial profile, etc…) If these criteria are adopted widely and the results shared, it may be possible to rapidly develop innovative and personalised drug treatment protocols with more realistic chances of being efficacious.

Comparison of subtyping methods for neuroimaging studies in Alzheimer's disease: a call for harmonization

Biological subtypes in Alzheimer's disease, originally identified on neuropathological data, have been translated to in vivo biomarkers such as structural magnetic resonance imaging and positron emission tomography, to disentangle the heterogeneity within Alzheimer's disease. Although there is methodological variability across studies, comparable characteristics of subtypes are reported at the group level. In this study, we investigated whether group-level similarities translate to individual-level agreement across subtyping methods, in a head-to-head context. We compared five previously published subtyping methods. Firstly, we validated the subtyping methods in 89 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 70 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging. Secondly, we extended and applied the subtyping methods to 53 amyloid-beta positive prodromal Alzheimer's disease and 30 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 200 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging and tau positron emission tomography. Subtyping methods were implemented as outlined in each original study. Group-level and individual-level comparisons across methods were performed. Each individual subtyping method was replicated, and the proof-of-concept was established. At the group level, all methods captured subtypes with similar patterns of demographic and clinical characteristics, and with similar cortical thinning and tau positron emission tomography uptake patterns. However, at the individual level, large disagreements were found in subtype assignments. Although characteristics of subtypes are comparable at the group level, there is a large disagreement at the individual level across subtyping methods. Therefore, there is an urgent need for consensus and harmonization across subtyping methods. We call for the establishment of an open benchmarking framework to overcome this problem.

TNF receptors are associated with tau pathology and conversion to Alzheimer's dementia in subjects with mild cognitive impairment

BACKGROUND

Tumor necrosis factor-a (TNF-α) signaling pathway plays a significant role in Alzheimer's disease (AD). This study aimed to explore the relationship between TNF-α related inflammatory proteins and pathological markers of AD, and examine their possibility as a predictor of the conversion of mild cognitive impairment (MCI) to AD.

METHODS

This study included both cross-sectional and longitudinal designs. The levels of TNF-α related inflammatory proteins, Aβ_1-42, total-tau(t-tau), phosphorylated tau (p-tau) from cerebrospinal fluid (CSF) were analyzed in healthy controls (HC, n = 90), MCI (n = 116), and AD participants (n = 75) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Kaplan-Meier analyses were used to evaluate the predictive value of the examined putative AD markers after follow-up visits.

RESULTS

In the cross-sectional cohort, we observed higher CSF levels of TNF-α related inflammatory proteins in the MCI and AD patients with positive tau pathology. TNF receptors (TNFR) were more closely associated with t-tau and p-tau than Aβ_1-42, in HC, MCI and AD subjects. In the longitudinal cohort with a mean follow-up of 30.2 months, MCI patients with high levels of CSF TNFR1 (p = 0.001) and low levels of TNFR2 (p < 0.001) were more likely to develop into AD.

CONCLUSION

TNFR-signaling might be involved in the early pathogenesis of AD and TNF receptors may serve as potential predictive biomarkers for MCI.

Neuropathological assessment of the Alzheimer spectrum

Alzheimer disease (AD), the most common form of dementia globally, classically defined a clinicopathological entity, is a heterogenous disorder with various pathobiological subtypes, currently referred to as Alzheimer continuum. Its morphological hallmarks are extracellular parenchymal β-amyloid (amyloid plaques) and intraneuronal (tau aggregates forming neurofibrillary tangles) lesions accompanied by synaptic loss and vascular amyloid deposits, that are essential for the pathological diagnosis of AD. In addition to "classical" AD, several subtypes with characteristic regional patterns of tau pathology have been described that show distinct clinical features, differences in age, sex distribution, biomarker levels, and patterns of key network destructions responsible for cognitive decline. AD is a mixed proteinopathy (amyloid and tau), frequently associated with other age-related co-pathologies, such as cerebrovascular lesions, Lewy and TDP-43 pathologies, hippocampal sclerosis, or argyrophilic grain disease. These and other co-pathologies essentially influence the clinical picture of AD and may accelerate disease progression. The purpose of this review is to provide a critical overview of AD pathology, its defining pathological substrates, and the heterogeneity among the Alzheimer spectrum entities that may provide a broader diagnostic coverage of this devastating disorder as a basis for implementing precision medicine approaches and for ultimate development of successful disease-modifying drugs for AD.

Synaptosome as a tool in Alzheimer's disease research

Synapse dysfunction is an integral feature of Alzheimer's disease (AD) pathophysiology. In fact, prodromal manifestation of structural and functional deficits in synapses much prior to appearance of overt pathological hallmarks of the disease indicates that AD might be considered as a degenerative disorder of the synapses. Several research instruments and techniques have allowed us to study synaptic function and plasticity and their alterations in pathological conditions, such as AD. One such tool is the biochemically isolated preparations of detached and resealed synaptic terminals, the "synaptosomes". Because of the preservation of many of the physiological processes such as metabolic and enzymatic activities, synaptosomes have proved to be an indispensable ex vivo model system to study synapse physiology both when isolated from fresh or cryopreserved tissues, and from animal or human post-mortem tissues. This model system has been tremendously successful in the case of post-mortem tissues because of their accessibility relative to acute brain slices or cultures. The current review details the use of synaptosomes in AD research and its potential as a valuable tool in furthering our understanding of the pathogenesis and in devising and testing of therapeutic strategies for the disease.

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows for study confounding effects, 5) provides cluster visualization, 6) measures clustering uncertainty. We used amyloid-β positive AD and negative healthy subjects, three longitudinal structural magnetic resonance imaging scans (cortical thickness and subcortical volume) over two years. We found three distinct longitudinal AD brain atrophy patterns: one typical diffuse pattern (n=34, 47.2%), and two atypical patterns: minimal atrophy (n=23 31.9%) and hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.

Dysautonomia in Alzheimer's Disease

Alzheimer's disease is the most common neurodegenerative disorder, and its prevalence increases with age. Although there is a large amount of scientific literature focusing on Alzheimer's disease cardinal cognitive features, autonomic nervous system dysfunction remains understudied despite being common in the elderly. In this article, we reviewed the evidence for autonomic nervous system involvement in Alzheimer's disease. We identified four major potential causes for dysautonomia in Alzheimer's disease, out of which two are well-studied (comorbidities and medication) and two are rather hypothetical (Alzheimer's pathology and brain co-pathology). Although there appears to be some evidence linking Alzheimer's disease pathology to autonomic nervous system dysfunction, there is an important gap between two types of studies; histopathologic studies do not address dysautonomia manifestations, whereas clinical studies do not employ histopathologic diagnostic confirmation. Moreover, brain co-pathology is emerging as an important confounding factor. Therefore, we consider the correlation between dysautonomia and Alzheimer's disease to be an open question that needs further study. Nevertheless, given its impact on morbidity and mortality, we emphasize the importance of assessing autonomic dysfunction in patients with Alzheimer clinical syndrome.

The combined effect of amyloid-β and tau biomarkers on brain atrophy in dementia with Lewy bodies

BACKGROUND

Alzheimer's disease (AD)-related pathology is frequently found in patients with dementia with Lewy bodies (DLB). However, it is unknown how amyloid-β and tau-related pathologies influence neurodegeneration in DLB. Understanding the mechanisms underlying brain atrophy in DLB can improve our knowledge about disease progression, differential diagnosis, drug development and testing of anti-amyloid and anti-tau therapies in DLB.

OBJECTIVES

We aimed at investigating the combined effect of CSF amyloid-β42, phosphorylated tau and total tau on regional brain atrophy in DLB in the European DLB (E-DLB) cohort.

METHODS

86 probable DLB patients from the E-DLB cohort with CSF and MRI data were included. Random forest was used to analyze the association of CSF biomarkers (predictors) with visual rating scales for medial temporal lobe atrophy (MTA), posterior atrophy (PA) and global cortical atrophy scale-frontal subscale (GCA-F) (outcomes), including age, sex, education and disease duration as extra predictors.

RESULTS

DLB patients with abnormal MTA scores had abnormal CSF Aβ42, shorter disease duration and older age. DLB patients with abnormal PA scores had abnormal levels of CSF Aβ42 and p-tau, older age, lower education and shorter disease duration. Abnormal GCA-F scores were associated with lower education, male sex, and older age, but not with any AD-related CSF biomarker.

CONCLUSIONS

This study shows preliminary data on the potential combined effect of amyloid-β and tau-related pathologies on the integrity of posterior brain cortices in DLB patients, whereas only amyloid-β seems to be related to MTA. Future availability of α-synuclein biomarkers will help us to understand the effect of α-synuclein and AD-related pathologies on brain integrity in DLB.

The cholinergic system in subtypes of Alzheimer's disease: an in vivo longitudinal MRI study

BACKGROUND

The heterogeneity within Alzheimer's disease (AD) seriously challenges the development of disease-modifying treatments. We investigated volume of the basal forebrain, hippocampus, and precuneus in atrophy subtypes of AD and explored the relevance of subtype stratification in a small clinical trial on encapsulated cell biodelivery (ECB) of nerve growth factor (NGF) to the basal forebrain.

METHODS

Structural MRI data was collected for 90 amyloid-positive patients and 69 amyloid-negative healthy controls at baseline, 6-, 12-, and 24-month follow-up. The effect of the NGF treatment was investigated in 10 biopsy-verified AD patients with structural MRI data at baseline and at 6- or 12-month follow-up. Patients were classified as typical, limbic-predominant, hippocampal-sparing, or minimal atrophy AD, using a validated visual assessment method. Volumetric analyses were performed using a region-of-interest approach.

RESULTS

All AD subtypes showed reduced basal forebrain volume as compared with the healthy controls. The limbic-predominant subtype showed the fastest basal forebrain atrophy rate, whereas the minimal atrophy subtype did not show any significant volume decline over time. Atrophy rates of the hippocampus and precuneus also differed across subtypes. Our preliminary data from the small NGF cohort suggest that the NGF treatment seemed to slow the rate of atrophy in the precuneus and hippocampus in some hippocampal-sparing AD patients and in one typical AD patient.

CONCLUSIONS

The cholinergic system is differentially affected in distinct atrophy subtypes of AD. Larger studies in the future should confirm that this differential involvement of the cholinergic system may contribute to subtype-specific response to cholinergic treatment. Our preliminary findings suggest that future clinical trials should target specific subtypes of AD, or at least report treatment effects stratified by subtype.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01163825. Registered 14 July 2010.

Neuropathology of the Alzheimer's continuum: an update

Alzheimer's disease (AD), the most common form of dementia worldwide, is a mixed proteinopathy (amyloid and tau). Originally defined as a clinicopathological entity, it is a heterogenous, multifactorial disorder, currently referred to as the Alzheimer's continuum. Its cardinal pathological features are extracellular β-amyloid (amyloid plaques) and intraneuronal tau aggregates forming neurofibrillary tangles, which are accompanied by vascular amyloid deposits (cerebral amyloid angiopathy), synapse and neuronal loss, as well as neuroinflammation and reactive astrogliosis. In addition to "typical" AD, various subtypes with characteristic regional patterns of tau pathology have been described that show distinct clinical features, biomarker levels, and patterns of key network destructions responsible for cognitive decline. AD is frequently associated with other age-related changes including Lewy and TDP-43 pathologies, hippocampal sclerosis, argyrophilic grain disease, cerebrovascular lesions, and others. These additional pathologies influence the clinical picture of AD, may accelerate disease progression, and can cause a number of challenges in our understanding of the disease including the threshold of each individual pathology to cause dementia and the possibility of underlying common etiologies. This article provides an up-to-date overview of AD neuropathology, its heterogeneity, and additional pathologies in order to explain the difficulties in the diagnosis and the failure of clinical trials in AD patients.