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

The hippocampal sparing subtype of Alzheimer's disease assessed in neuropathology and in vivo tau positron emission tomography: a systematic review

Neuropathology and neuroimaging studies have identified several subtypes of Alzheimer's disease (AD): hippocampal sparing AD, typical AD, and limbic predominant AD. An unresolved question is whether hippocampal sparing AD cases can present with neurofibrillary tangles (NFT) in association cortices while completely sparing the hippocampus. To address that question, we conducted a systematic review and performed original analyses on tau positron emission tomography (PET) data. We searched EMBASE, PubMed, and Web of Science databases until October 2022. We also implemented several methods for AD subtyping on tau PET to identify hippocampal sparing AD cases. Our findings show that seven out of the eight reviewed neuropathologic studies included cases at Braak stages IV or higher and therefore, could not identify hippocampal sparing cases with NFT completely sparing the hippocampus. In contrast, tau PET did identify AD participants with tracer retention in the association cortex while completely sparing the hippocampus. We conclude that tau PET can identify hippocampal sparing AD cases with NFT completely sparing the hippocampus. Based on the accumulating data, we suggest two possible pathways of tau spread: (1) a canonical pathway with early involvement of transentorhinal cortex and subsequent involvement of limbic regions and association cortices, and (2) a less common pathway that affects association cortices with limbic involvement observed at end stages of the disease or not at all.

Early termination of pivotal trials in Alzheimer's disease-Preserving optimal value for participants and science

Participants in Alzheimer's disease late-phase clinical trials are frequently confronted with a situation of early termination. We discuss measures to protect the perceived value of study participation and to maximize the scientific value under such circumstances. A communication strategy should ensure that trial participants maintain a positive relationship with the research team and have their informational needs optimally met. Measures to maximize the scientific value may include data/sample sharing, strategies for personalized medicine, as well as scientific follow-up. Critical for the success of such a concept are networks of excellence, extending models of existing initiatives like Global Alzheimer's Platform Foundation Network (GAP-Net). These networks could fundamentally strengthen the role of clinical investigators if they decide on their involvement in trials based upon their estimation of the scientific value and benefit for the participants, actively contribute to scientific analyses, and mediate optimal communication among the relevant trial stakeholders.

Dementia Prevention in Clinical Practice

Over 55 million people globally are living with dementia and, by 2050, this number is projected to increase to 131 million. This poses immeasurable challenges for patients and their families and a significant threat to domestic and global economies. Given this public health crisis and disappointing results from disease-modifying trials, there has been a recent shift in focus toward primary and secondary prevention strategies. Approximately 40% of Alzheimer's disease (AD) cases, which is the most common form of dementia, may be prevented or at least delayed. Success of risk reduction studies through addressing modifiable risk factors, in addition to the failure of most drug trials, lends support for personalized multidomain interventions rather than a "one-size-fits-all" approach. Evolving evidence supports early intervention in at-risk patients using individualized interventions directed at modifiable risk factors. Comprehensive risk stratification can be informed by emerging principals of precision medicine, and include expanded clinical and family history, anthropometric measurements, blood biomarkers, neurocognitive evaluation, and genetic information. Risk stratification is key in differentiating subtypes of dementia and identifies targetable areas for intervention. This article reviews a clinical approach toward dementia risk stratification and evidence-based prevention strategies, with a primary focus on AD.

Imaging markers of cerebral amyloid angiopathy and hypertensive arteriopathy differentiate Alzheimer disease subtypes synergistically

Background

Both cerebral amyloid angiopathy (CAA) and hypertensive arteriopathy (HA) are related to cognitive impairment and dementia. This study aimed to clarify CAA- and HA-related small vessel disease (SVD) imaging marker associations with cognitive dysfunction and Alzheimer disease (AD) subtypes.

Methods

A sample of 137 subjects with clinically diagnosed late-onset AD identified from the dementia registry of a single center from January 2017 to October 2021 were enrolled. Semi-quantitative imaging changes (visual rating scale grading) suggestive of SVD were analyzed singularly and compositely, and their correlations with cognitive domains and AD subtypes were examined.

Results

Patients with typical and limbic-predominant AD subtypes had worse cognitive performance and higher dementia severity than minimal-atrophy subtype patients. Deep white matter hyperintensity (WMH) presence correlated inversely with short-term memory (STM) performance. The three composite SVD scores correlated with different cognitive domains and had distinct associations with AD subtypes. After adjusting for relevant demographic factors, multivariate logistic regression (using minimal-atrophy subtype as the reference condition) revealed the following: associations of the typical subtype with periventricular WMH [odds ratio (OR) 2.62; 95% confidence interval (CI), 1.23–5.57, p = 0.012], global SVD score (OR 1.67; 95%CI, 1.11–2.52, p = 0.009), and HA-SVD score (OR 1.93; 95%CI, 1.10–3.52, p = 0.034); associations of limbic-predominant subtype with HA-SVD score (OR 2.57; 95%CI, 1.23–5.37, p = 0.012) and most global and domain-specific cognitive scores; and an association of hippocampal-sparing subtype with HA-SVD score (OR 3.30; 95%CI, 1.58–6.85, p = 0.001).

Conclusion

Composite SVD imaging markers reflect overall CAA and/or HA severity and may have differential associations with cognitive domains and AD subtypes. Our finding supports the possibility that the clinical AD subtypes may reflect differing burdens of underlying CAA and HA microangiopathologies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01083-8.

Biomarkers Related to Synaptic Dysfunction to Discriminate Alzheimer's Disease from Other Neurological Disorders

Recently, the synaptic proteins neurogranin (Ng) and α-synuclein (α-Syn) have attracted scientific interest as potential biomarkers for synaptic dysfunction in neurodegenerative diseases. In this study, we measured the CSF Ng and α-Syn concentrations in patients affected by AD (n = 69), non-AD neurodegenerative disorders (n-AD = 50) and non-degenerative disorders (n-ND, n = 98). The concentrations of CSF Ng and α-Syn were significantly higher in AD than in n-AD and n-ND. Moreover, the Aβ42/Ng and Aβ42/α-Syn ratios showed statistically significant differences between groups and discriminated AD patients from n-AD patients, better than Ng or α-Syn alone. Regression analyses showed an association of higher Ng concentrations with MMSE < 24, pathological Aβ 42/40 ratios, pTau, tTau and the ApoEε4 genotype. Aβ 42/Ng was associated with MMSE < 24, an AD-related FDG-PET pattern, the ApoEε4 genotype, pathological Aβ 42 levels and Aβ 42/40 ratios, pTau, and tTau. Moreover, APO-Eε4 carriers showed higher Ng concentrations than non-carriers. Our results support the idea that the Aβ 42/Ng ratio is a reliable index of synaptic dysfunction/degeneration able to discriminate AD from other neurological conditions.

Sex differences in early-onset Alzheimer's disease

INTRODUCTION

Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (<65 years, EOAD) is scarce.

METHODS

We included 62 EOAD patients and 44 healthy controls (HC) with cerebrospinal fluid (CSF) AD's core biomarkers and neurofilament light chain levels, neuropsychological assessment, and 3T-MRI. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using Freesurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition.

RESULTS

Compared to same-sex HC, female-EOAD showed greater cognitive impairment and broader atrophy burden than male-EOAD. In a direct female-EOAD and male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female-EOAD than in male-EOAD. Greater atrophy was associated with worse cognition in female-EOAD.

CONCLUSIONS

At diagnosis, there are sex-differences in the pattern of cognitive impairment, atrophy burden and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.

Mining High-Level Imaging Genetic Associations via Clustering AD Candidate Variants with Similar Brain Association Patterns

Brain imaging genetics examines associations between imaging quantitative traits (QTs) and genetic factors such as single nucleotide polymorphisms (SNPs) to provide important insights into the pathogenesis of Alzheimer's disease (AD). The individual level SNP-QT signals are high dimensional and typically have small effect sizes, making them hard to be detected and replicated. To overcome this limitation, this work proposes a new approach that identifies high-level imaging genetic associations through applying multigraph clustering to the SNP-QT association maps. Given an SNP set and a brain QT set, the association between each SNP and each QT is evaluated using a linear regression model. Based on the resulting SNP-QT association map, five SNP-SNP similarity networks (or graphs) are created using five different scoring functions, respectively. Multigraph clustering is applied to these networks to identify SNP clusters with similar association patterns with all the brain QTs. After that, functional annotation is performed for each identified SNP cluster and its corresponding brain association pattern. We applied this pipeline to an AD imaging genetic study, which yielded promising results. For example, in an association study between 54 AD SNPs and 116 amyloid QTs, we identified two SNP clusters with one responsible for amyloid beta clearances and the other regulating amyloid beta formation. These high-level findings have the potential to provide valuable insights into relevant genetic pathways and brain circuits, which can help form new hypotheses for more detailed imaging and genetics studies in independent cohorts.

Subjective Impairments in Olfaction and Cognition Predict Dissociated Behavioral Outcomes

BACKGROUND

Self-rated subjective cognitive decline (SCD) and subjective olfactory impairment (SOI) are associated with objective cognitive decline and dementia. However, their relationship and co-occurrence is unknown. We aimed to (a) describe the occurrence of SOI, SCD and their overlap in the general population; (b) compare SOI and SCD in terms of longitudinal associations with corresponding objective olfactory and cognitive measures; and (c) describe how SOI and SCD may lead to distinct sensory and cognitive outcomes.

METHODS

Cognitively unimpaired individuals from the third wave of the Swedish population-based Betula study (n = 784, aged 35-90 years; 51% females) were split into self-rated SOI, SCD, overlapping SCD + SOI, and controls. Between-subject and within-subject repeated-measures MANCOVA were used to compare the groups regarding odor identification, cognition, age, sex, and education. Spearman correlation was used to assess the different patterns of association between olfaction and cognition across groups.

RESULTS

SOI was present in 21.1%, whereas SCD was present in 9.9% of participants. According to a chi-square analysis, the SCD + SOI overlap (2.7%) is on a level that could be expected if the phenomena were independent. Odor identification in SOI showed decline at the 10-year follow-up (n = 284) and was positively associated with cognition. The SOI and SCD groups showed distinct cognitive-olfactory profiles at follow-up.

CONCLUSIONS

SOI occur independently of SCD in the population, and these risk factors are associated with different cognitive and olfactory outcomes. The biological causes underlying SOI and SCD, as well as the risk for future cognitive impairment, need further investigation.

Effect of cognitive reserve on amnestic mild cognitive impairment due to Alzheimer’s disease defined by fluorodeoxyglucose-positron emission tomography

This study aimed to investigate the effect of cognitive reserve (CR) on the rate of cognitive decline and cerebral glucose metabolism in amnestic mild cognitive impairment (MCI) using the Study on Diagnosis of Early Alzheimer’s Disease-Japan (SEAD-J) dataset. The patients in SEAD-J underwent cognitive tests and fluorodeoxyglucose-positron emission tomography (FDG-PET). MCI to be studied was classified as amnestic MCI due to Alzheimer’s disease (AD) with neurodegeneration. A total of 57 patients were visually interpreted as having an AD pattern (P1 pattern, Silverman’s classification). The 57 individuals showing the P1 pattern were divided into a high-education group (years of school education ≥13, N = 18) and a low-education group (years of school education ≤12, N = 39). Voxel-based statistical parametric mapping revealed more severe hypometabolism in the high-education group than in the low-education group. Glucose metabolism in the hippocampus and temporoparietal area was inversely associated with the years of school education in the high- and low-education groups (N = 57). General linear mixed model analyses demonstrated that cognitive decline was more rapid in the high-education group during 3-year follow-up. These results suggest that the cerebral glucose metabolism is lower and cognitive function declines faster in patients with high CR of amnestic MCI due to AD defined by FDG-PET.

Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease

Understanding Alzheimer's disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aβ+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aβ- and 90 Aβ+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aβ-, 5 Aβ+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

p38α‐MAPK‐deficient myeloid cells ameliorate symptoms and pathology of APP ‐transgenic Alzheimer's disease mice

Alzheimer's disease (AD), the most common cause of dementia in the elderly, is pathologically characterized by extracellular deposition of amyloid‐β peptides (Aβ) and microglia‐dominated inflammatory activation in the brain. p38α‐MAPK is activated in both neurons and microglia. How p38α‐MAPK in microglia contributes to AD pathogenesis remains unclear. In this study, we conditionally knocked out p38α‐MAPK in all myeloid cells or specifically in microglia of APP‐transgenic mice, and examined animals for AD‐associated pathologies (i.e., cognitive deficits, Aβ pathology, and neuroinflammation) and individual microglia for their inflammatory activation and Aβ internalization at different disease stages (e.g., at 4 and 9 months of age). Our experiments showed that p38α‐MAPK‐deficient myeloid cells were more effective than p38α‐MAPK‐deficient microglia in reducing cerebral Aβ and neuronal impairment in APP‐transgenic mice. Deficiency of p38α‐MAPK in myeloid cells inhibited inflammatory activation of individual microglia at 4 months but enhanced it at 9 months. Inflammatory activation promoted microglial internalization of Aβ. Interestingly, p38α‐MAPK‐deficient myeloid cells reduced IL‐17a‐expressing CD4‐positive lymphocytes in 9 but not 4‐month‐old APP‐transgenic mice. By cross‐breeding APP‐transgenic mice with Il‐17a‐knockout mice, we observed that IL‐17a deficiency potentially activated microglia and reduced Aβ deposition in the brain as shown in 9‐month‐old myeloid p38α‐MAPK‐deficient AD mice. Thus, p38α‐MAPK deficiency in all myeloid cells, but not only in microglia, prevents AD progression. IL‐17a‐expressing lymphocytes may partially mediate the pathogenic role of p38α‐MAPK in peripheral myeloid cells. Our study supports p38α‐MAPK as a therapeutic target for AD patients.

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.

Metabolic Reprogramming of Microglia Enhances Proinflammatory Cytokine Release through EphA2/p38 MAPK Pathway in Alzheimer’s Disease

Background: The activation of microglia and neuroinflammation has been implicated in the pathogenesis of Alzheimer’s disease (AD), but the exact roles of microglia and the underlying mechanisms remain unclear. Objective: To clarify how the metabolic reprogramming of microglia induce by amyloid-β (Aβ)1-42 to affect the release of proinflammatory cytokines in AD. Methods: MTS assay was used to detect the viability of BV2 cells treated with different concentrations of Aβ1-42 for different periods of time. The expression levels of proinflammatory cytokines were determined by qRT-PCR and western blot assay in BV2 cells and hippocampus of mice. RNA sequencing was applied to evaluate the gene expression profiles in response to HK2 knockdown in BV2 cells treated with Aβ1-42. Results: Low concentrations of Aβ1-42 increased the viability of BV2 cells and promoted the release of proinflammatory cytokines, and this process is accompanied by increased glycolysis. Inhibition of glycolysis significantly downregulated the release of proinflammatory cytokines in BV2 cells and hippocampus of mice treated with Aβ1-42. The results of RNA sequencing revealed the expression of chemokine ligand 2 (Cxcl2) and ephrin receptor tyrosine kinase A2 (EphA2) were significantly downregulated when knocked down HK2 in BV2 cells. Subsequently, the expression of proinflammatory cytokines was downregulated in BV2 cell after knocking down EphA2. Conclusion: This study demonstrated that EphA2/p38 MAPK pathway is involved the release of proinflammatory cytokines in microglia induced by Aβ1-42 in AD, which is accompanied by metabolic reprogramming from oxidative phosphorylation (OXPHOS) to glycolysis.

Comparing Medial Temporal Atrophy Between Early-Onset Semantic Dementia and Early-Onset Alzheimer's Disease Using Voxel-Based Morphometry: A Multicenter MRI Study

BACKGROUND

Early-onset Semantic dementia (EOSD) and early-onset Alzheimer's disease (EOAD) are often difficult to clinically differentiate in the early stages of the diseases because of the overlaps of clinical symptoms such as language symptoms. We compared the degree of atrophy in medial temporal structures between the two types of dementia using the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD).

METHODS

The participants included 29 (age: 61.7±4.5 years) and 39 (age: 60.2±4.9 years) patients with EOSD and EOAD, respectively. The degree of atrophy in medial temporal structures was quantified using the VSRAD for magnetic resonance imaging data. Receiver operating characteristic (ROC) analysis was performed to distinguish patients with EOSD and EOAD using the mean Z score (Z-score) in bilateral medial temporal structures and the absolute value (laterality score) of the laterality of Z-score (| right-left |) for indicating the degree of asymmetrical atrophy in medial temporal structures.

RESULTS

The EOSD group had significantly higher Z and laterality scores than the EOAD group (Zscores: mean ± standard deviation: 3.74±1.05 vs. 1.56±0.81, respectively; P<0.001; laterality score: mean ± standard deviation: 2.35±1.23 vs. 0.68±0.51, respectively; P<0.001). In ROC analysis, the sensitivity and specificity to differentiate EOSD from EOAD by a Z-score of 2.29 were 97% and 85%, respectively and by the laterality score of 1.05 were 93% and 85%, respectively.

CONCLUSION

EOSD leads to more severe and asymmetrical atrophy in medial temporal structures than EOAD. The VSRAD may be useful to distinguish between these dementias that have several clinically similar symptoms.

Disentangling tau and brain atrophy cluster heterogeneity across the Alzheimer's disease continuum

Introduction

Neuroimaging heterogeneity in dementia has been examined using single modalities. We evaluated the associations of magnetic resonance imaging (MRI) atrophy and flortaucipir positron emission tomography (PET) clusters across the Alzheimer's disease (AD) spectrum.

Methods

We included 496 Alzheimer's Disease Neuroimaging Initiative participants with brain MRI, flortaucipir PET scan, and amyloid beta biomarker measures obtained. We applied a novel robust collaborative clustering (RCC) approach on the MRI and flortaucipir PET scans. We derived indices for AD-like (SPARE-AD index) and brain age (SPARE-BA) atrophy.

Results

We identified four tau (I-IV) and three atrophy clusters. Tau clusters were associated with the apolipoprotein E genotype. Atrophy clusters were associated with white matter hyperintensity volumes. Only the hippocampal sparing atrophy cluster showed a specific association with brain aging imaging index. Tau clusters presented stronger clinical associations than atrophy clusters. Tau and atrophy clusters were partially associated.

Conclusions

Each neuroimaging modality captured different aspects of brain aging, genetics, vascular changes, and neurodegeneration leading to individual multimodal phenotyping.

Aberrant topological organization and age-related differences in the human connectome in subjective cognitive decline by using regional morphology from magnetic resonance imaging

Subjective cognitive decline (SCD) is characterized by self-experienced deficits in cognitive capacity with normal performance in objective cognitive tests. Previous structural covariance studies showed specific insights into understanding the structural alterations of the brain in neurodegenerative diseases. Moreover, in subjects with neurodegenerative diseases, accelerated brain degeneration with aging was shown. However, the age-related variations in coordinated topological patterns of morphological networks in individuals with SCD remain poorly understood. In this study, 77 individual morphological networks were constructed, including 42 normal controls (NCs) and 35 SCD individuals, from structural magnetic resonance imaging (sMRI). A stepwise linear regression model and partial correlation analysis were constructed to evaluate the differences in age-related alterations of the network properties in individuals with SCD compared with NCs. Compared with NC, the properties of integration and segregation in individuals with SCD were lower, and the aberrant metrics were negatively correlated with age in SCD. The rich-club connections persevered, but the paralimbic system connections were disrupted in individuals with SCD compared with NCs. In addition, age-related differences in nodal global efficiency are distributed mainly in prefrontal cortex regions. In conclusion, the age-related disruption of topological organizations in individuals with SCD may indicate that the degeneration of brain efficiency with aging was accelerated in individuals with SCD.

Long-term use of pharmacological treatment in Alzheimer's disease: a retrospective cohort study in real-world clinical practice

PURPOSE

To assess the impact of long-term use of different drugs commonly prescribed in Alzheimer's disease (AD) on its clinical course and to identify clinical and therapeutic factors associated with a delay in AD progression.

METHODS

We retrospectively enrolled 50 patients visited at the Neurology Unit, Careggi University Hospital (Florence), followed for at least 24 months. AD diagnosis was made according to clinical diagnostic criteria for probable/possible AD dementia, always supported at least by one biomarker. Clinical features, MMSE scores evaluated at diagnosis and every 6 months, and AD drugs used for at least 6 months, were recorded. Cox regression analysis was performed to estimate the hazard ratio (HR) for AD progression, assuming as the "final event," the progression to a more severe disease stage, defined as the achievement of an MMSE score less than 10.

RESULTS

At baseline, the median MMSE score was 22. During follow-up (median of 41 months), 56% of patients progressed to a more severe disease stage. The use of memantine, either alone (HR 0.24; 95% CI 0.09-0.60) or combined with acetylcholinesterase inhibitors (HR 0.35; 95% CI 0.14-0.88) and a higher MMSE score at baseline (HR 0.82; 95% CI 0.70-0.96) were associated with a significantly lower risk of AD progression.

CONCLUSION

Nowadays, effective disease-modifying therapy for AD is missing. Nevertheless, when the diagnosis is established, our results support the advantage of long-term use of available pharmacological treatments, especially in combination, in delaying AD progression to its more severe disease stage.

Cancer History Is Associated with Slower Speed of Cognitive Decline in Patients with Amnestic Cognitive Impairment

Background: Several epidemiological studies report a negative association between Cancer and Alzheimer’s disease (AD). Objective: To characterize the trajectories of memory loss in individuals with early amnestic cognitive impairment with and without history of previous cancer. Methods: Cognitive deterioration was assessed using the Montreal Cognitive Assessment (MoCA) or MoCA-Memory Index Score (MoCA-MIS) biannually in subjects with early amnestic cognitive impairment followed-up retrospectively from 2007 to 2021. History of Cancer was obtained from clinical records. Simple linear regressions of MoCA-MIS scores were calculated for each subject and analyzed with K-means cluster analysis to identify subgroups with different cognitive decline trajectories. χ 2 and t tests were used for descriptive categorical and continuous variables and mixed multiple linear regressions to determine cognitive decline covariates. Results: Analysis of the trajectory of cognitive decline in 141 subjects with early amnestic cognitive impairment identified two subgroups: Fast (n = 60) and Slow (n = 81) progressors. At baseline Fast progressors had better MoCA-MIS (p <  0.001) and functionality (CDR p = 0.02, AD8 p = 0.05), took less anti-dementia medications (p = 0.005), and had higher depression rates (p = 0.02). Interestingly, Fast progressors slowed their speed of memory decline (from 1.6 to 1.1 MoCA-MIS points/year) and global cognitive decline (from 2.0 to 1.4 total MoCA points/year) when Cancer history was present. Conclusion: Two trajectories of amnestic cognitive decline were identified, possibly derived from different neurophysiopathologies or clinical stages. This study suggests that a history of previous Cancer slows down amnestic cognitive decline, specifically in a subgroup of subjects with depression at baseline and accelerated deterioration at follow-up.

Hippocampal Atrophy Subtypes of Alzheimer's Disease Using Automatic MRI in a Memory Clinic Cohort: Clinical Implications

INTRODUCTION

One pathological hallmark of Alzheimer's disease (AD) is atrophy of medial temporal brain regions that can be visualized on magnetic resonance imaging (MRI), but not all patients will have atrophy. The aim was to use MRI to categorize patients according to their hippocampal atrophy status and to present prevalence of the subtypes, difference in clinical symptomatology and progression, and factors associated with hippocampal subtypes.

METHODS

We included 215 patients with AD who had been assessed with the clinically available MRI software NeuroQuant (NQ; CorTechs labs/University of California, San Diego, CA, USA). NQ measures the hippocampus volume and calculates a normative percentile. Atrophy was regarded to be present if the percentile was ≤5. Demographics, cognitive measurements, AD phenotypes, apolipoprotein E status, and results from cerebrospinal fluid and amyloid positron emission tomography analyses were included as explanatory variables of the hippocampal subtypes.

RESULTS

Of all, 60% had no hippocampal atrophy. These patients were younger and less cognitively impaired concerning global measures, memory function, and abstraction but impaired concerning executive, visuospatial, and semantic fluency, and more of them had nonamnestic AD, compared to those with hippocampal atrophy. No difference in progression rate was observed between the two groups. In mild cognitive impairment patients, amyloid pathology was associated with the no hippocampal atrophy group.

CONCLUSION

The results have clinical implications. Clinicians should be aware of the large proportion of AD patients presenting without atrophy of the hippocampus as measured with this clinical MRI method in the diagnostic set up and that nonamnestic phenotypes are more common in this group as compared to those with atrophy. Furthermore, the findings are relevant in clinical trials.

Comparison and aggregation of event sequences across ten cohorts to describe the consensus biomarker evolution in Alzheimer's disease

BACKGROUND

Previous models of Alzheimer's disease (AD) progression were primarily hypothetical or based on data originating from single cohort studies. However, cohort datasets are subject to specific inclusion and exclusion criteria that influence the signals observed in their collected data. Furthermore, each study measures only a subset of AD-relevant variables. To gain a comprehensive understanding of AD progression, the heterogeneity and robustness of estimated progression patterns must be understood, and complementary information contained in cohort datasets be leveraged.

METHODS

We compared ten event-based models that we fit to ten independent AD cohort datasets. Additionally, we designed and applied a novel rank aggregation algorithm that combines partially overlapping, individual event sequences into a meta-sequence containing the complementary information from each cohort.

RESULTS

We observed overall consistency across the ten event-based model sequences (average pairwise Kendall's tau correlation coefficient of 0.69 ± 0.28), despite variance in the positioning of mainly imaging variables. The changes described in the aggregated meta-sequence are broadly consistent with the current understanding of AD progression, starting with cerebrospinal fluid amyloid beta, followed by tauopathy, memory impairment, FDG-PET, and ultimately brain deterioration and impairment of visual memory.

CONCLUSION

Overall, the event-based models demonstrated similar and robust disease cascades across independent AD cohorts. Aggregation of data-driven results can combine complementary strengths and information of patient-level datasets. Accordingly, the derived meta-sequence draws a more complete picture of AD pathology compared to models relying on single cohorts.

Divergent Cortical Tau Positron Emission Tomography Patterns Among Patients With Preclinical Alzheimer Disease

Importance

Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease.

Objective

To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+).

Design, Setting, and Participants

This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022.

Main Outcomes and Measures

Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical+) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined.

Results

The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL+). Individuals in the A+T cortical+ group were younger than those in the A+T MTL+ group (t61.867 = -2.597; P = .03). Across the A+T cortical+ and A+T MTL+ groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical+ and A+T MTL+ groups, whereas executive functioning scores were lower for the A+T cortical+ group than for the A+T MTL+ group. The prevalence of the A+T cortical+ group and tau patterns within the A+T cortical+ group were consistent in ADNI, HABS, and Wisconsin.

Conclusions and Relevance

This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.

Characterization of Alzheimer’s Disease Subtypes Based on Magnetic Resonance Imaging and Perfusion Single-Photon Emission Computed Tomography

Background: Alzheimer’s disease (AD) is a biologically heterogenous disease. Previous studies have reported the existence of various AD subtypes, and the various clinical features of the subtypes. However, inconsistent results have been obtained. Objective: To clarify the clinical characteristics of the various AD subtypes, by classifying probable AD into subtypes based on magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) findings. Methods: A total of 245 patients with probable AD were classified into the typical AD (TAD) subtype, limbic-predominant (LP) subtype, hippocampal-sparing (HS) subtype, and minimal-change (MC) subtype, based on the presence of medial temporal lobe atrophy on MRI and posterior cerebral hypoperfusion on SPECT. Demographics, including age, sex, body mass index, disease duration, education years, comorbidities, frailty, leisure activity, and neuropsychological findings were compared between the AD subtypes. Results: he frequency of TAD, LP, HS, and MC subtypes was 49%, 20%, 18%, and 13%, respectively. Patients with the LP subtype were older and characterized by fewer major comorbidities, higher frailty, and slower progression of disease. Patients with the HS subtype were younger and characterized by shorter disease duration, lower frailty, and preserved memory, but had prominent constructional dysfunction. Patients of the MC subtype were characterized by shorter disease duration, lower education level, less leisure activity, less impaired memory and orientation, and slower progression. Conclusion: Patients with different AD subtypes differed in their demographic and clinical features. The characterization of patients’ AD subtypes may provide effective support for the diagnosis, treatment, and care of AD patients.

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer's disease

Alzheimer's disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer's Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.

Exploratory imaging outcomes of a phase 1b/2a clinical trial of allopregnanolone as a regenerative therapeutic for Alzheimer's disease: Structural effects and functional connectivity outcomes

Introduction

Allopregnanolone (ALLO), an endogenous neurosteroid, promoted neurogenesis and oligogenesis and restored cognitive function in animal models of Alzheimer's disease (AD). Based on these discovery research findings, we conducted a randomized-controlled phase 1b/2a multiple ascending dose trial of ALLO in persons with early AD (NCT02221622) to assess safety, tolerability, and pharmacokinetics. Exploratory imaging outcomes to determine whether ALLO impacted hippocampal structure, white matter integrity, and functional connectivity are reported.

Methods

Twenty-four individuals participated in the trial (n = 6 placebo; n = 18 ALLO) and underwent brain magnetic resonance imaging (MRI) before and after 12 weeks of treatment. Hippocampal atrophy rate was determined from volumetric MRI, computed as rate of change, and qualitatively assessed between ALLO and placebo sex, apolipoprotein E (APOE) ε4 allele, and ALLO dose subgroups. White matter microstructural integrity was compared between placebo and ALLO using fractional and quantitative anisotropy (QA). Changes in local, inter-regional, and network-level functional connectivity were also compared between groups using resting-state functional MRI.

Results

Rate of decline in hippocampal volume was slowed, and in some cases reversed, in the ALLO group compared to placebo. Gain of hippocampal volume was evident in APOE ε4 carriers (range: 0.6% to 7.8% increased hippocampal volume). Multiple measures of white matter integrity indicated evidence of preserved or improved integrity. ALLO significantly increased fractional anisotropy (FA) in 690 of 690 and QA in 1416 of 1888 fiber tracts, located primarily in the corpus callosum, bilateral thalamic radiations, and bilateral corticospinal tracts. Consistent with structural changes, ALLO strengthened local, inter-regional, and network level functional connectivity in AD-vulnerable regions, including the precuneus and posterior cingulate, and network connections between the default mode network and limbic system.

Discussion

Indicators of regeneration from previous preclinical studies and these exploratory MRI-based outcomes from this phase 1b/2a clinical cohort support advancement to a phase 2 proof-of-concept efficacy clinical trial of ALLO as a regenerative therapeutic for mild AD (REGEN-BRAIN study; NCT04838301).

Application of predictive models in boosting power of Alzheimer's disease clinical trials: A post hoc analysis of phase 3 solanezumab trials

Background

The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and would also respond to the therapeutic intervention.

Objective

To investigate if predictive models can be an effective tool for identifying and excluding people unlikely to show cognitive decline as an enrichment strategy in AD trials.

Method

We used data from the placebo arms of two phase 3, double-blind trials, EXPEDITION and EXPEDITION2. Patients had 18 months of follow-up. Based on the longitudinal data from the placebo arm, we classified participants into two groups: one showed cognitive decline (any negative slope) and the other showed no cognitive decline (slope is zero or positive) on the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-cog). We used baseline data for EXPEDITION to train regression-based classifiers and machine learning classifiers to estimate probability of cognitive decline. Models were applied to EXPEDITION2 data to assess predicted performance in an independent sample. Features used in predictive models included baseline demographics, apolipoprotein E ε4 genotype, neuropsychological scores, functional scores, and volumetric magnetic resonance imaging.

Result

In EXPEDITION, 46.3% of placebo-treated patients showed no cognitive decline and the proportion was similar in EXPEDITION2 (45.6%). Models had high sensitivity and modest specificity in both the training (EXPEDITION) and replication samples (EXPEDITION2) for detecting the stable group. Positive predictive value of models was higher than the base prevalence of cognitive decline, and negative predictive value of models were higher than the base rate of participants who had stable cognition.

Conclusion

Excluding persons with AD unlikely to decline from the active and placebo arms of clinical trials using predictive models may boost the power of AD trials through selective inclusion of participants expected to decline.

Association of Alzheimer's Disease with COVID-19 Susceptibility and Severe Complications: A Nationwide Cohort Study

BACKGROUND

Identification of patients at high susceptibility and high risk of developing serious complications related to coronavirus disease 2019 (COVID-19) infection is clinically important in the face of the COVID-19 pandemic.

OBJECTIVE

To investigate whether patients with Alzheimer's disease (AD) are more susceptible to COVID-19 infection and whether they have a higher risk of developing serious complications.

METHODS

We retrospectively reviewed the Korean nationwide population-based COVID-19 dataset for participants who underwent real-time reverse transcription polymerase chain reaction assays for COVID-19 between January 1 and June 4, 2020. A 1 : 3 ratio propensity score matching and binary logistic regression analysis were performed to investigate the association between AD and the susceptibility or severe complications (i.e., mechanical ventilation, intensive care unit admission, or death) of COVID-19.

RESULTS

Among 195,643 study participants, 5,725 participants had AD and 7,334 participants were diagnosed with COVID-19. The prevalence of participants testing positive for COVID-19 did not differ according to the presence of AD (p = 0.234). Meanwhile, AD was associated with an increased risk of severe COVID-19 complications (OR 2.25 [95% CI 1.54-3.28]). Secondary outcome analyses showed that AD patients had an increased risk for mortality (OR 3.09 [95% CI 2.00-4.78]) but were less likely to receive mechanical ventilation (OR 0.42 [95% CI 0.20-0.87]).

CONCLUSION

AD was not associated with increased susceptibility to COVID-19 infection, but was associated with severe COVID-19 complications, especially with mortality. Early diagnosis and active intervention are necessary for patients with AD suspected COVID-19 infection.

A systematic analysis of diagnostic performance for Alzheimer's disease using structural MRI

Background

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders in the elderly. Although numerous structural magnetic resonance imaging (sMRI) studies have reported diagnostic models that could distinguish AD from normal controls (NCs) with 80-95% accuracy, limited efforts have been made regarding the clinically practical computer-aided diagnosis (CAD) system for AD.

Objective

To explore the potential factors that hinder the clinical translation of the AD-related diagnostic models based on sMRI.

Methods

To systematically review the diagnostic models for AD based on sMRI, we identified relevant studies published in the past 15 years on PubMed, Web of Science, Scopus, and Ovid. To evaluate the heterogeneity and publication bias among those studies, we performed subgroup analysis, meta-regression, Begg's test, and Egger's test.

Results

According to our screening criterion, 101 studies were included. Our results demonstrated that high diagnostic accuracy for distinguishing AD from NC was obtained in recently published studies, accompanied by significant heterogeneity. Meta-analysis showed that many factors contributed to the heterogeneity of high diagnostic accuracy of AD using sMRI, which included but was not limited to the following aspects: (i) different datasets; (ii) different machine learning models, e.g. traditional machine learning or deep learning model; (iii) different cross-validation methods, e.g. k-fold cross-validation leads to higher accuracies than leave-one-out cross-validation, but both overestimate the accuracy when compared to validation in independent samples; (iv) different sample sizes; and (v) the publication times. We speculate that these complicated variables might be the adverse factor for developing a clinically applicable system for the early diagnosis of AD.

Conclusions

Our findings proved that previous studies reported promising results for classifying AD from NC with different models using sMRI. However, considering the many factors hindering clinical radiology practice, there would still be a long way to go to improve.

Discrepancy between cognitive test and brain imaging results in Alzheimer's disease associated with diabetes

BACKGROUND/OBJECTIVE

Although a large number of studies have been performed on the association between Alzheimer's disease (AD) and type 2 diabetes mellitus (DM), the underlying pathophysiology of AD associated with DM has not been fully elucidated to date. We compared cognitive functions and brain imaging findings between AD patients with and without DM to characterize the association between cognition and imaging findings in AD patients with DM.

METHODS

Cognitive functions and brain imaging findings, including medial temporal lobe atrophy analyzed by magnetic resonance imaging, and hypoperfusion in the parietal, posterior cingulate, and frontal regions analyzed by single-photon emission computed tomography were compared between 126 AD patients without DM ([AD-DM]) and 51 AD patients with DM ([AD+DM]). Factors associated with cognitive-imaging associations, including education, occupation, leisure activity, comorbidity, frailty, and other demographics, were analyzed.

RESULTS

The [AD+DM] group showed significantly more severe cognitive dysfunction than the [AD- DM] group, despite a similar degree of brain imaging abnormalities. Among the factors associated with cognitive-imaging associations, the level of leisure activity was significantly lower in the [AD+DM] group than in the [AD-DM] group, but no significant differences in other factors were observed between the 2 groups.

CONCLUSION

The cognitive-imaging discrepancy observed in AD patients with DM may be associated with their low cognitive reserve, possibly caused by their low amount of leisure activities. Our findings suggest that lifestyle interventions, including physical, cognitive, and social activities, may reduce cognitive decline in AD patients with DM.

Hemispheric Asymmetry and Atypical Lobar Progression of Alzheimer-Type Tauopathy

The spread of neurofibrillary tau pathology in Alzheimer disease (AD) mostly follows a stereotypical pattern of topographical progression but atypical patterns associated with interhemispheric asymmetry have been described. Because histopathological studies that used bilateral sampling are limited, this study aimed to assess interhemispheric tau pathology differences and the presence of topographically atypical cortical spreading patterns. Immunohistochemical staining for detection of tau pathology was performed in 23 regions of interest in 57 autopsy cases comparing bilateral cortical regions and hemispheres. Frequent mild (82% of cases) and occasional moderate (32%) interhemispheric density discrepancies were observed, whereas marked discrepancies were uncommon (7%) and restricted to occipital regions. Left and right hemispheric tau pathology dominance was observed with similar frequencies, except in Braak Stage VI that favored a left dominance. Interhemispheric Braak stage differences were observed in 16% of cases and were more frequent in advanced (IV-VI) versus early (I-III) stages. One atypical lobar topographical pattern in which occipital tau pathology density exceeded frontal lobe scores was identified in 4 cases favoring a left dominant asymmetry. We speculate that asymmetry and atypical topographical progression patterns may be associated with atypical AD clinical presentations and progression characteristics, which should be tested by comprehensive clinicopathological correlations.

Concordance of Alzheimer’s Disease Subtypes Produced from Different Representative Morphological Measures: A Comparative Study

Background: Gray matter (GM) density and cortical thickness (CT) obtained from structural magnetic resonance imaging are representative GM morphological measures that have been commonly used in Alzheimer’s disease (AD) subtype research. However, how the two measures affect the definition of AD subtypes remains unclear. Methods: A total of 180 AD patients from the ADNI database were used to identify AD subgroups. The subtypes were identified via a data-driven strategy based on the density features and CT features, respectively. Then, the similarity between the two features in AD subtype definition was analyzed. Results: Four distinct subtypes were discovered by both density and CT features: diffuse atrophy AD, minimal atrophy AD (MAD), left temporal dominant atrophy AD (LTAD), and occipital sparing AD. The matched subtypes exhibited relatively high similarity in atrophy patterns and neuropsychological and neuropathological characteristics. They differed only in MAD and LTAD regarding the carrying of apolipoprotein E ε2. Conclusions: The results verified that different representative morphological GM measurement methods could produce similar AD subtypes. Meanwhile, the influences of apolipoprotein E genotype, asymmetric disease progression, and their interactions should be considered and included in the AD subtype definition. This study provides a valuable reference for selecting features in future studies of AD subtypes.

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.

Unraveling the Gordian knot: genetics and the troubled road to effective therapeutics for Alzheimer's disease

In the late 20th century, identification of the major protein components of amyloid plaques and neurofibrillary tangles provided a window into the molecular pathology of Alzheimer's disease, ushering in an era of optimism that targeted therapeutics would soon follow. The amyloid-cascade hypothesis took hold very early, supported by discoveries that dominant mutations in APP, PSEN1, and PSEN2 cause the very rare, early-onset, familial forms of the disease. However, in the past decade, a stunning series of failed Phase-3 clinical trials, testing anti-amyloid antibodies or processing-enzyme inhibitors, prompts the question, What went wrong? The FDA's recent controversial approval of aducanumab, despite widespread concerns about efficacy and safety, only amplifies the question. The assumption that common, late-onset Alzheimer's is a milder form of familial disease was not adequately questioned. The differential timing of discoveries, including blood-brain-barrier-penetrant tracers for imaging of plaques and tangles, made it easy to focus on amyloid. Furthermore, the neuropathology community initially implemented Alzheimer's diagnostic criteria based on plaques only. The discovery that MAPT mutations cause frontotemporal dementia with tauopathy made it even easier to overlook the tangles in Alzheimer's. Many important findings were simply ignored. The accepted mouse models did not predict the human clinical trials data. Given this lack of pharmacological validity, input from geneticists in collaboration with neuroscientists is needed to establish criteria for valid models of Alzheimer's disease. More generally, scientists using genetic model organisms as whole-animal bioassays can contribute to building the pathogenesis network map of Alzheimer's disease.

Entorhinal Subfield Vulnerability to Neurofibrillary Tangles in Aging and the Preclinical Stage of Alzheimer's Disease

BACKGROUND

Neurofibrillary tangle (NFT) accumulation in the entorhinal cortex (EC) precedes the transformation from cognitive controls to mild cognitive impairment and Alzheimer's disease (AD). While tauopathy has been described in the EC before, the order and degree to which the individual subfields within the EC are engulfed by NFTs in aging and the preclinical AD stage is unknown.

OBJECTIVE

We aimed to investigate substructures within the EC to map the populations of cortical neurons most vulnerable to tau pathology in aging and the preclinical AD stage.

METHODS

We characterized phosphorylated tau (CP13) in 10 cases at eight well-defined anterior-posterior levels and assessed NFT density within the eight entorhinal subfields (described by Insausti and colleagues) at the preclinical stages of AD. We validated with immunohistochemistry and labeled the NFT density ratings on ex vivo MRIs. We measured subfield cortical thickness and reconstructed the labels as three-dimensional isosurfaces, resulting in anatomically comprehensive, histopathologically validated tau "heat maps."

RESULTS

We found the lateral EC subfields ELc, ECL, and ECs (lateral portion) to have the highest tau density in semi-quantitative scores and quantitative measurements. We observed significant stepwise higher tau from anterior to posterior levels (p < 0.001). We report an age-dependent anatomically-specific vulnerability, with all cases showing posterior tau pathology, yet older individuals displaying an additional anterior tau burden. Finally, cortical thickness of each subfield negatively correlated with respective tau scores (p < 0.05).

CONCLUSION

Our findings indicate that posterior-lateral subfields within the EC are the most vulnerable to early NFTs and atrophy in aging and preclinical AD.

Transcriptomic Changes Highly Similar to Alzheimer's Disease Are Observed in a Subpopulation of Individuals During Normal Brain Aging

Aging is a major risk factor for late-onset Alzheimer’s disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic datasets from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45–70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic datasets from another cohort of older individuals (>70 years), we found that samples from cognitively normal older individuals clustered with the “healthy aging” subgroup while AD samples mainly clustered with the “AD similar” subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the “normal brain aging” to identify the very early molecular events that may lead to LOAD development.

Preserved Consciousness in Alzheimer's Disease and Other Dementias: Caregiver Awareness and Communication Strategies

Alzheimer's disease is an insidious onset neurodegenerative syndrome without effective treatment or cure. It is rapidly becoming a global health crisis that is overwhelming healthcare, society, and individuals. The clinical nature of neurocognitive decline creates significant challenges in bidirectional communication between caregivers and persons with Alzheimer's disease (AD) that can negatively impact quality-of-life. This paper sought to understand how and to what extent would awareness training about the levels of consciousness in AD influence the quality-of-life interactions in the caregiver-patient dyad. A literature review of multiple databases was conducted utilizing a transdisciplinary approach. The sum of findings indicates a positive relationship between enhanced caregiver awareness and training, positive interactions, and improved QOL measures among patients and caregivers. A multidirectional relationship was found among healthcare policies, training and education resources, caregivers, and persons with AD. Specifically, the current lack of policy and inadequate training and educational resources has various detrimental effects on patients and caregivers, while improvements in training and education of caregivers yields positive outcomes in communication and QOL. Furthermore, evidence of preserved consciousness in persons with AD was demonstrated from multiple disciplines, including neurobiological, psychological, and biopsychosocial models. The literature further revealed several methods to access the preserved consciousness in persons with AD and related dementias, including sensory, emotional, and cognitive stimulations. The evidence from the literature suggests a reframed approach to our understanding and treatment of persons with AD is not only warranted, but crucial to address the needs of those affected by AD.

pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm

Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modelling situations within a single, consistent architecture.

Clinicopathological heterogeneity of Alzheimer's disease with pure Alzheimer's disease pathology: Cases associated with dementia with Lewy bodies, very early-onset dementia, and primary progressive aphasia

We report four cases depicting the heterogeneity of Alzheimer's disease (AD) associated with pure AD pathology. Case 1 was a 77-year-old man with a false positive diagnosis of dementia with Lewy bodies with reduced dopamine transporter uptake activity of the striatum but no Lewy body pathology. There were tau deposits in the large neurons in the putamen, which may be related to the development of parkinsonism. Case 2 was an AD patient in his early 30s who presented with a psychotic episode and a cognitive decline, and later developed myoclonus and seizures. He demonstrated considerable amyloid-beta deposits in the cerebral cortex, including cotton wool plaques, basal ganglia, and cerebellum. Tau deposits were also abundant in the cerebral neocortex, hippocampus, basal ganglia, and brain stem. Case 3 was a 60-year-old woman who exhibited typical symptoms characteristic of the logopenic variant of primary progressive aphasia (lvPPA). Case 4 was a 68-year-old man who exhibited the semantic variant of primary progressive aphasia (svPPA) plus repetition impairment, a rare case associated with AD pathology. In addition to tau pathology, astrocytic pathology was prominent in the white matter and cortical layers of the left temporoparietal cortices. While the main AD lesion in case 4 was evaluated by tau accumulation and astrogliosis in the left temporal lobe, that in case 3 in was evaluated by the same points in the left parietal lobe. Within the spectrum of lvPPA, case 4 may be regarded as a temporal variant of lvPPA presenting svPPA. The pathology of PPA associated with AD may have broader clinical manifestations than that in previously described cases. Case 4 also showed pathological features characteristic of cerebral amyloid angiopathy throughout the cerebral cortex. The distribution of tau and astrocytic pathologies in the cerebral cortex, basal ganglia, brain stem, and cerebellum may explain the various symptoms of atypical pure AD patients.

White matter variability, cognition, and disorders: a systematic review

Inter-individual differences can inform treatment procedures and—if accounted for—have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional, and connectional anatomy. Brain connections are essential to facilitate functional organization and, when severed, cause impairments or complete loss of function. Hence, the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate cognitive functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not correlated with one, but multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract–function correlations might still be a promising tool in identifying biomarkers for precision medicine. They can characterize variations in brain anatomy, differences in functional organization, and predicts resilience and recovery in patients.

Longitudinal Analysis of Brain-Predicted Age in Amnestic and Non-amnestic Sporadic Early-Onset Alzheimer's Disease

Objective: Predicted age difference (PAD) is a score computed by subtracting chronological age from "brain" age, which is estimated using neuroimaging data. The goal of this study was to evaluate the PAD as a marker of phenotypic heterogeneity and severity among early-onset Alzheimer's disease (EOAD) patients. Methods: We first used 3D T1-weighted (3D-T1) magnetic resonance images (MRI) of 3,227 healthy subjects aged between 18 and 85 years to train, optimize, and evaluate the brain age model. A total of 123 participants who met the criteria for early-onset (<65 years) sporadic form of probable Alzheimer's disease (AD) and presented with two distinctive clinical presentations [an amnestic form (n = 74) and a non-amnestic form (n = 49)] were included at baseline and followed-up for a maximum period of 4 years. All the participants underwent a work-up at baseline and every year during the follow-up period, which included clinical examination, neuropsychological testing and genotyping, and structural MRI. In addition, cerebrospinal fluid biomarker assay was recorded at baseline. PAD score was calculated by applying brain age model to 3D-T1 images of the EOAD patients and healthy controls, who were matched based on age and sex. At baseline, between-group differences for neuropsychological and PAD scores were assessed using linear models. Regarding longitudinal analysis of neuropsychological and PAD scores, differences between amnestic and non-amnestic participants were analyzed using linear mixed-effects modeling. Results: PAD score was significantly higher for non-amnestic patients (2.35 ± 0.91) when compared to amnestic patients (2.09 ± 0.74) and controls (0.00 ± 1). Moreover, PAD score was linearly correlated with the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating Sum of Boxes (CDR-SB), for both amnestic and non-amnestic sporadic forms. Longitudinal analyses showed that the gradual development of the disease in patients was accompanied by a significant increase in PAD score over time, for both amnestic and non-amnestic patients. Conclusion: PAD score was able to separate amnestic and non-amnestic sporadic forms. Regardless of the clinical presentation, as PAD score was a way of quantifying an early brain age acceleration, it was an appropriate method to detect the development of AD and follow the evolution of the disease as a marker of severity as MMSE and CDR-SB.

Mechanisms Involved in Microglial-Interceded Alzheimer's Disease and Nanocarrier-Based Treatment Approaches

Alzheimer's disease (AD) is a common neurodegenerative disorder accountable for dementia and cognitive dysfunction. The etiology of AD is complex and multifactorial in origin. The formation and deposition of amyloid-beta (Aβ), hyperphosphorylated tau protein, neuroinflammation, persistent oxidative stress, and alteration in signaling pathways have been extensively explored among the various etiological hallmarks. However, more recently, the immunogenic regulation of AD has been identified, and macroglial activation is considered a limiting factor in its etiological cascade. Macroglial activation causes neuroinflammation via modulation of the NLRP3/NF-kB/p38 MAPKs pathway and is also involved in tau pathology via modulation of the GSK-3β/p38 MAPK pathways. Additionally, microglial activation contributes to the discrete release of neurotransmitters and an altered neuronal synaptic plasticity. Therefore, activated microglial cells appear to be an emerging target for managing and treating AD. This review article discussed the pathology of microglial activation in AD and the role of various nanocarrier-based anti-Alzeihmenr's therapeutic approaches that can either reverse or inhibit this activation. Thus, as a targeted drug delivery system, nanocarrier approaches could emerge as a novel means to overcome existing AD therapy limitations.

Decreased Global EEG Synchronization in Amyloid Positive Mild Cognitive Impairment and Alzheimer's Disease Patients-Relationship to APOE ε4

The apolipoprotein E (APOE) ε4 allele is a risk factor for Alzheimer's disease (AD) that has been linked to changes in brain structure and function as well as to different biological subtypes of the disease. The present study aimed to investigate the association of APOE ε4 genotypes with brain functional impairment, as assessed by quantitative EEG (qEEG) in patients on the AD continuum. The study population included 101 amyloid positive patients diagnosed with mild cognitive impairment (MCI) (n = 50) and AD (n = 51) that underwent resting-state EEG recording and CSF Aβ42 analysis. In total, 31 patients were APOE ε4 non-carriers, 42 were carriers of one, and 28 were carriers of two APOE ε4 alleles. Quantitative EEG analysis included computation of the global field power (GFP) and global field synchronization (GFS) in conventional frequency bands. Amyloid positive patients who were carriers of APOE ε4 allele(s) had significantly higher GFP beta and significantly lower GFS in theta and beta bands compared to APOE ε4 non-carriers. Increased global EEG power in beta band in APOE ε4 carriers may represent a brain functional compensatory mechanism that offsets global EEG slowing in AD patients. Our findings suggest that decreased EEG measures of global synchronization in theta and beta bands reflect brain functional deficits related to the APOE ε4 genotype in patients that are on a biomarker-verified AD continuum.

Machine learning of brain structural biomarkers for Alzheimer's disease (AD) diagnosis, prediction of disease progression, and amyloid beta deposition in the Japanese population

INTRODUCTION

We developed machine learning (ML) designed to analyze structural brain magnetic resonance imaging (MRI), and trained it on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. In this study, we verified its utility in the Japanese population.

METHODS

A total of 535 participants were enrolled from the Japanese ADNI database, including 148 AD, 152 normal, and 235 mild cognitive impairment (MCI). Probability of AD was expressed as AD likelihood scores (ADLS).

RESULTS

The accuracy of AD diagnosis was 88.0% to 91.2%. The accuracy of predicting the disease progression in non-dementia participants over a 3-year observation was 76.0% to 79.3%. More than 90% of the participants with low ADLS did not progress to AD within 3 years. In the amyloid positron emission tomography (PET)-positive MCI, the hazard ratio of progression was 2.39 with low ADLS, and 5.77 with high ADLS. When high ADLS was defined as N+ and Pittsburgh compound B (PiB) PET positivity was defined as A+, the time to disease progression for 50% of MCI participants was 23.7 months in A+N+, whereas it was 52.3 months in A+N-.

CONCLUSION

These results support the feasibility of our ML for the diagnosis of AD and prediction of the disease progression.

Meta-analysis of cerebrospinal fluid neuron-specific enolase levels in Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy

Background

This study examined the usefulness of cerebrospinal fluid (CSF) neuron-specific enolase (NSE) levels as a candidate biomarker of neurodegeneration in Alzheimer’s disease (AD), Parkinson’s disease (PD), PD with dementia (PDD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA).

Methods

We performed a systematic search of PubMed, the Cochrane Library, Scopus, and Google Scholar to find studies that measured CSF NSE levels in AD, PD, DLB, and/or MSA. For each disease, we pooled all available data and performed a meta-analysis, and meta-regression analyses of age and sex were conducted if the main analysis found a significant association.

Results

Twenty studies were included (13 for AD, 8 for PD/PDD/DLB, and 4 for MSA). Significantly elevated CSF NSE levels were detected in AD (Hedges’ g = 0.822, 95% confidence interval [95% CI] 0.332 to 1.311, p = 0.0010), but the data exhibited high heterogeneity (I² = 88.43%, p < 0.001). The meta-regression analysis of AD showed that age (p < 0.001), but not sex, had a significant effect on CSF NSE levels. A meta-analysis of the pooled data for PD/PDD/DLB did not show any significant changes in the CSF NSE level, but a sub-group analysis of PDD/DLB revealed significantly elevated CSF NSE levels (Hedges’ g = 0.507, 95% CI 0.020 to 0.993, p = 0.0412). No significant changes in CSF NSE levels were detected in MSA.

Conclusions

The CSF NSE level may be a useful biomarker of neurodegeneration in AD and PDD/DLB. Age was found to affect the CSF NSE levels of AD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00907-3.

Longitudinal cognitive performance of Alzheimer's disease neuropathological subtypes

INTRODUCTION

Alzheimer's disease (AD) neuropathological subtypes (limbic predominant [lpAD], hippocampal sparing [HpSpAD], and typical [tAD]), defined by relative neurofibrillary tangle (NFT) burden in limbic and cortical regions, have not been studied in prospectively characterized epidemiological cohorts with robust cognitive assessments.

METHODS

Two hundred ninety-two participants with neuropathologically confirmed AD from the Religious Orders Study and Memory and Aging Project were categorized by neuropathological subtype based on previously specified diagnostic criteria using quantitative regional NFT counts. Rates of cognitive decline were compared across subtypes using linear mixed-effects models that included subtype, time, and a subtype-time interaction as predictors and four cognitive domain factor scores (memory, executive function, language, visuospatial) and a global score as outcomes. To assess if memory was relatively preserved in HpSpAD, non-memory factor scores were included as covariates in the mixed-effects model with memory as the outcome.

RESULTS

There were 57 (20%) with lpAD, 22 (8%) with HpSpAD and 213 (73%) with tAD. LpAD died significantly later than the participants with tAD (2.4 years, P = .01) and with HpSpAD (3.8 years, P = .03). Compared to tAD, HpSpAD, but not lpAD, performed significantly worse in all cognitive domains at the time of initial impairment and declined significantly faster in memory, language, and globally. HpSpAD did not have relatively preserved memory performance at any time point.

CONCLUSION

The relative frequencies of AD neuropathological subtypes in an epidemiological sample were consistent with a previous report in a convenience sample. People with HpSpAD decline rapidly, but may not have a memory-sparing clinical syndrome. Cohort-specific differences in regional tau burden and comorbid neuropathology may explain the lack of clinicopathological correlation.

Cortical structure and the risk for Alzheimer's disease: a bidirectional Mendelian randomization study

Progressive loss of neurons in a specific brain area is one of the manifestations of Alzheimer's disease (AD). Much effort has been devoted to investigating brain atrophy and AD. However, the causal relationship between cortical structure and AD is not clear. We conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationship between cortical structure (surface area and thickness of the whole cortex and 34 cortical regions) and AD risk. Genetic variants used as instruments came from a large genome-wide association meta-analysis of cortical structure (33,992 participants of European ancestry) and AD (AD and AD-by-proxy, 71,880 cases, 383,378 controls). We found suggestive associations of the decreased surface area of the temporal pole (OR (95% CI): 0.95 (0.9, 0.997), p = 0.04), and decreased thickness of cuneus (OR (95% CI): 0.93 (0.89, 0.98), p = 0.006) with higher AD risk. We also found a suggestive association of vulnerability to AD with the decreased surface area of precentral (β (SE): -43.4 (21.3), p = 0.042) and isthmus cingulate (β (SE): -18.5 (7.3), p = 0.011). However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and AD met the threshold. We show suggestive evidence of an association of the atrophy of the temporal pole and cuneus with higher AD risk. In the other direction, there was a suggestive causal relationship between vulnerability to AD and the decreased surface area of the precentral and isthmus cingulate. Our findings shed light on the associations of cortical structure with the occurrence of AD.

Plasma Neurofilament Light and Future Declines in Cognition and Function in Alzheimer's Disease in the FIT-AD Trial

Background:

Utilities of blood-based biomarkers in Alzheimer’s disease (AD) clinical trials remain unknown.

Objective:

To evaluate the ability of plasma neurofilament light chain (NfL) to predict future declines in cognition and activities of daily living (ADL) outcomes in 26 older adults with mild-to-moderate AD dementia from the FIT-AD Trial.

Methods:

Plasma NfL was measured at baseline and 3 and 6 months. Cognition and ADL were assessed using the AD Assessment Scale-Cognition (ADAS-Cog) and AD Uniform Dataset Instruments and Disability Assessment for Dementia (DAD), respectively, at baseline, 3, 6, 9, and 12 months. Linear mixed effects models were used to examine the associations between baseline or change in plasma NfL and changes in outcomes.

Results:

Higher baseline plasma NfL was associated with greater rate of decline in ADAS-Cog from baseline to 6 months (standardized estimate of 0.00462, p = 0.02853) and in ADL from baseline to 12 months (standardized estimate of –0.00284, p = 0.03338). Greater increase in plasma NfL in short term from baseline to 3 months was associated with greater rate of decline in memory and ADL from 3 to 6 months (standardized estimate of –0.04638 [0.003], p = 0.01635; standardized estimate of –0.03818, p = 0.0435) and greater rate of decline in ADL from 3 to 12 month (standardized estimate of –0.01492, p = 0.01082).

Conclusion:

This study demonstrated that plasma NfL might have the potential to predict cognitive and function decline up to 12 months. However, future studies with bigger sample sizes need to confirm the findings.

The human connectome in Alzheimer disease - relationship to biomarkers and genetics

The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.

Heterogeneity and Factorial Structure in Alzheimer's Disease: A Cognitive Perspective

BACKGROUND

Alzheimer's disease (AD) patients show heterogeneous cognitive profiles which suggest the existence of cognitive subgroups. A deeper comprehension of this heterogeneity could contribute to move toward a precision medicine perspective.

OBJECTIVE

In this study, we aimed 1) to investigate AD cognitive heterogeneity as a product of the combination of within- (factors) and between-patients (sub-phenotypes) components, and 2) to promote its assessment in clinical practice by defining a small set of critical tests for this purpose.

METHODS

We performed factor mixture analysis (FMA) on neurocognitive assessment results of N = 230 patients with a clinical diagnosis of AD. This technique allowed to investigate the structure of cognitive heterogeneity in this sample and to characterize the core features of cognitive sub-phenotypes. Subsequently, we performed a tests selection based on logistic regression to highlight the best tests to detect AD patients in our sample. Finally, the accuracy of the same tests in the discrimination of sub-phenotypes was evaluated.

RESULTS

FMA revealed a structure characterized by five latent factors and four groups, which were identifiable by means of a few cognitive tests and were mainly characterized by memory deficits with visuospatial difficulties ("Visuospatial AD"), typical AD cognitive pattern ("Typical AD"), less impaired memory ("Mild AD"), and language/praxis deficits with relatively spared memory ("Nonamnestic AD").

CONCLUSION

The structure of cognitive heterogeneity in our sample of AD patients, as studied by FMA, could be summarized by four sub-phenotypes with distinct cognitive characteristics easily identifiable in clinical practice. Clinical implications under the precision medicine framework are discussed.