Prodromal Alzheimer's Disease Research Articles

Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging.

Alzheimer's disease (AD) can be optimally managed from a healthcare point of view if detected at a prodromal stage. Amnestic mild cognitive impairment (MCI) is known as prodromal AD, has attracted extensive attention and research. To identify the differences in cognitive function and structural magnetic resonance imaging (MRI) features between men and women with MCI on the basis of A/T/N classification system ("A" means amyloid-β biomarker, "T" means tau biomarker, and "N" means neurodegeneration biomarker as determined by clinical imaging (e.g., positron emission tomography, magnetic resonance imaging (MRI)) or by the measurement of total tau protein (T-tau) in the cerebrospinal fluid (CSF)) and to further explore the correlation between them. 406 MCI subjects were selected from the Alzheimer's Disease Neuroimaging Initiative database and divided into male and female MCI groups. Differences in demographic characteristics, biomarkers, cognitive assessment performance, and regions of interest (ROIs) of structural MRI were compared between the two groups. The correlations between brain structural changes quantified by MRI and cognitive abilities were investigated through linear regression models. Compared with male MCI subjects, females had significantly higher T-tau concentration in CSF. There were significant differences in ROIs between the sex groups. In the male MCI group, the average cortical thicknesses of the right posterior cingulate, right anterior cingulate and right supramarginal gyrus were more closely correlated with cognitive function. In the female MCI group, the volume of the right rostral anterior cingulate, and the surface area and average cortical thickness of the right isthmus of the cingulate gyrus were more closely correlated with cognitive function. Based on A/T/N classification system, the structural MRI data analysis was closely correlated with the difference of cognitive function from patients with prodromal AD in a sex-dependent manner.

Alzheimer's Disease : Current Landscape and Future Directions

Introduction: Alzheimer's disease (AD) is the most prevalent form of dementia, constituting up to 72% of cases, and poses a significant financial burden on global healthcare. The aging population is expected to triple the cost of dementia to over $600 billion in the US alone by 2050. Dementia, a major cause of dependency and dysfunction, accounted for 11.4% of all reported deaths in Britain and Wales in 2022. Recent studies suggest a potential decline in dementia incidence, especially in males in Occident countries, possibly linked to better management of vascular risk. While 89% of dementia costs are attributed to high-income countries, middle and low-income nations face significant challenges in addressing the epidemiology of dementia. The prevalence of AD in developing nations is estimated at 3.4%, varying widely. Women exhibit a 1.17 times higher age-specific global prevalence compared to men, and their age-normalized death rate is also higher, suggesting factors beyond life expectancy contribute to their vulnerability. AD primarily affects individuals aged 75 or older, with 80% of cases in this age group. Acetylcholinesterase inhibitors are commonly used in all stages of dementia, though their efficacy in mild cognitive impairment and prodromal AD is uncertain. Distinguishing AD from depression symptoms can be challenging. The pathological features of AD involve neurofibrillary tangles (NFTs) and senile plaques, leading to neural and synaptic loss. Multiple mechanisms contribute to AD pathogenesis, including amyloid/tau toxicity and oxidative stress. Diagnosis : traditionally relies on clinical criteria, but biomarkers like CSF Aβ and tau proteins, as well as blood-based biomarkers, have shown promise in early detection. Noveltrearment: Promising treatment options include anti-amyloid monoclonal antibodies like aducanumab, lecanemab, and gantenerumab, with varying degrees of success in clinical trials. Donanemab, targeting a specific type of Aβ, has shown significant slowing of mental degradation in early-stage patients.

EEG biomarkers in Alzheimer’s and prodromal Alzheimer’s: a comprehensive analysis of spectral and connectivity features

BackgroundBiomarkers of Alzheimer’s disease (AD) and mild cognitive impairment (MCI, or prodromal AD) are highly significant for early diagnosis, clinical trials and treatment outcome evaluations. Electroencephalography (EEG), being noninvasive and easily accessible, has recently been the center of focus. However, a comprehensive understanding of EEG in dementia is still needed. A primary objective of this study is to investigate which of the many EEG characteristics could effectively differentiate between individuals with AD or prodromal AD and healthy individuals.MethodsWe collected resting state EEG data from individuals with AD, prodromal AD, and normal cognition. Two distinct preprocessing pipelines were employed to study the reliability of the extracted measures across different datasets. We extracted 41 different EEG features. We have also developed a stand-alone software application package, Feature Analyzer, as a comprehensive toolbox for EEG analysis. This tool allows users to extract 41 EEG features spanning various domains, including complexity measures, wavelet features, spectral power ratios, and entropy measures. We performed statistical tests to investigate the differences in AD or prodromal AD from age-matched cognitively normal individuals based on the extracted EEG features, power spectral density (PSD), and EEG functional connectivity.ResultsSpectral power ratio measures such as theta/alpha and theta/beta power ratios showed significant differences between cognitively normal and AD individuals. Theta power was higher in AD, suggesting a slowing of oscillations in AD; however, the functional connectivity of the theta band was decreased in AD individuals. In contrast, we observed increased gamma/alpha power ratio, gamma power, and gamma functional connectivity in prodromal AD. Entropy and complexity measures after correcting for multiple electrode comparisons did not show differences in AD or prodromal AD groups. We thus catalogued AD and prodromal AD-specific EEG features.ConclusionsOur findings reveal that the changes in power and connectivity in certain frequency bands of EEG differ in prodromal AD and AD. The spectral power, power ratios, and the functional connectivity of theta and gamma could be biomarkers for diagnosis of AD and prodromal AD, measure the treatment outcome, and possibly a target for brain stimulation.

Monoclonal anti-amyloid antibody treatment: the epidemiological profile of the target patients in Austria and the status of treatment-eligible patients registered at an outpatient memory clinic.

The development of monoclonal anti-amyloid antibodies, adisease-modifying treatment for Alzheimer's disease (AD), has raised the necessity to identify the epidemiological profile of the possible target patients who would benefit from such therapy. These are patients in the early stages of AD with biomarker-confirmed brain amyloid positivity. In this study, the epidemiological profile of possible target patients in Austria and Vienna was estimated. The number of patients in the stage of amyloid-beta (Aβ)-positive prodromal AD in Austria and Vienna are 193,500 and 34,700 patients, respectively. The expected patient demand for the upcoming therapy in Austria and Vienna are 61,200 and 11,100 patients, respectively.In the memory clinic of the Vienna General Hospital, the number of treatment-eligible patients for an upcoming anti-amyloid antibody was on average 52.8 patients per year, which is about 10% of the total number of patients visiting the memory clinic every year. Several challenges to provide therapy to the general population include expanding the MCI screening in primary care and increasing the capacity of the healthcare system for biomarker testing, infusion delivery, and ARIA management. The study primarily addresses the status quo of identifying patients on memory clinics through cognitive screening and biomarker testing.

Genistein, A Phytoestrogen, Delays the Transition to Dementia in Prodromal Alzheimer's Disease Patients.

Alzheimer's disease is recognized as a complex condition influenced by multiple factors, necessitating a similarly multifaceted approach to treatment. Ideally, interventions should prioritize averting the progression to dementia. Given the chronic nature of the disease, long-term management strategies are required. Within this framework, lifestyle modifications and dietary supplements emerge as appealing options due to their minimal toxicity, limited side effects, and cost-effectiveness. This study presents findings from a double-blind, placebo-controlled bicentric pilot clinical trial, demonstrating the significant cognitive preservation associated with genistein, a phytoestrogen found in soy and various other dietary sources, among individuals with prodromal Alzheimer's disease. Our prior investigation utilizing APP/PS1 mice elucidated the specific mechanisms through which genistein operates, including anti-amyloid-β, antioxidant, anti-inflammatory, and antiapoptotic effects. These findings underscore the potential of identifying bioactive compounds from dietary sources for the management of Alzheimer's disease.

Early CA2 Tau Inclusions Do Not Distinguish an Age-Related Tauopathy from Early Alzheimer's Disease.

Neuropathologic studies of brains from autopsy series show tau inclusions (pretangles, neuropils threads, neurofibrillary tangles) are detectable more than a decade before amyloid-β (Aβ) deposition in Alzheimer's disease (AD) and develop in a characteristic manner that forms the basis for AD staging. An alternative position views pathological tau without Aβ deposition as a 'primary age-related tauopathy' (PART) rather than prodromal AD. Recently, an early focus of tau inclusions in the Ammon's horn second sector (CA2) with relative sparing of CA1 that occurs before tau inclusions develop in the entorhinal cortex (EC) was proposed as an additional feature of PART. To test the 'definite PART' hypothesis. We used AT8-immunohistochemistry in 100μm sections to examine the EC, transentorhinal cortex (TRE), and Ammon's horn in 325 brains with tau inclusions lacking Aβ deposits (average age at death 66.7 years for females, 66.4 years for males). 100% of cases displayed tau inclusions in the TRE. In 89% of cases, the CA1 tau rating was greater than or equal to that in CA2. In 25%, CA2 was devoid of tau inclusions. Only 4% displayed a higher tau score in CA2 than in the TRE, EC, and CA1. The perforant path also displayed early tau changes. APOE genotyping was available for 199/325 individuals. Of these, 44% had an ɛ4 allele that placed them at greater risk for developing later NFT stages and, therefore, clinical AD. Our new findings call into question the PART hypothesis and are consistent with the idea that our cases represent prodromal AD.

Illana Gozes: From the pivotal discovery of activity-dependent neuroprotective protein (ADNP) through its investigational drug davunetide: brain molecular medicine providing hope for autism, schizophrenia, and Alzheimer's disease

Professor Illana Gozes, Ph.D., is a faculty member at Tel Aviv University. Formerly holding the Lily and Avraham Gildor Chair for the Investigation of Growth Factors, she now directs the Dr. Diana and Zelma Elton Laboratory for Molecular Neuroendocrinology. A world-renowned neurochemist, Professor Gozes currently serves as the President of the European Society for Neurochemistry and Vice President of Drug Development at ExoNavis Therapeutics Ltd. Her groundbreaking research began in the late 1970s and early 1980s when she discovered multiple tubulin forms within a single neuron. She demonstrated that these forms evolve with brain development, play a crucial role in synapse formation, and can be identified using monoclonal tubulin antibodies. At the forefront of molecular neuroscience in the 1980s, Professor Gozes became the first to clone the gene encoding vasoactive intestinal peptide (VIP), a key regulatory neuropeptide in the brain. Her research revealed increased VIP expression during synapse formation. In her quest to identify proteins activated by VIP and facilitate neuro-glial interaction, the Gozes laboratory discovered and cloned a novel protein: activity-dependent neuroprotective protein (ADNP). Subsequent research established ADNP's essential role in brain formation and function. Through a series of highly cited articles, Professor Gozes demonstrated that ADNP regulates thousands of essential genes during brain development in a sex-dependent manner and associates with an intricate array of vital proteins. She uncovered ADNP's key role in autophagy and schizophrenia, revealed a fundamental shared mechanism in autism involving critical binding of ADNP with SHANK3 and actin, and showed ADNP's regulation of microtubule dynamics and Tau interaction, which protects against tauopathy. Furthermore, she discovered somatic mutations in ADNP and related genes in Alzheimer's disease, paralleling tauopathy. Her pioneering work on ADNP-deficient mouse models predicted the ADNP syndrome, an autistic/intellectual disability syndrome driven by de novo mutations in ADNP and presenting with tauopathy. Professor Gozes took a reductionist approach to discover an active site in ADNP, leading to the development of the investigational drug davunetide (NAP). This compound has shown promise in protecting against ADNP deficiency/mutations in animal models and in clinical trials. It has been tested in women suffering from progressive supranuclear palsy (PSP), a pure tauopathy, and in individuals with prodromal Alzheimer's disease, demonstrating effects in a sex-dependent manner. Further promise was shown in schizophrenia patients, suggesting improvement in real-world problem solving and task performance. We are honored that Professor Gozes has agreed to share her life's journey with our readers in this Genomic Press Interview.

The HOPE4MCI study: AGB101 treatment slows progression of entorhinal cortex atrophy in APOE ε4 non‐carriers with mild cognitive impairment due to Alzheimer's disease

AbstractIntroductionHippocampal hyperactivity is a hallmark of prodromal Alzheimer's disease (AD) that predicts progression in patients with amnestic mild cognitive impairment (aMCI). AGB101 is an extended‐release formulation of levetiracetam in the dose range previously demonstrated to normalize hippocampal activity and improve cognitive performance in aMCI. The HOPE4MCI study was a 78‐week trial to assess the progression of MCI due to AD. As reported in Mohs et al., the decline in the Clinical Dementia Rating Sum of Boxes score (CDR‐SB) was reduced by 40% in apolipoprotein E (APOE) ε4 non‐carriers over the 78‐week duration of the study with a negligible effect in carriers. Here we report an exploratory analysis of the effects of AGB101 on neuroimaging and biomarker measures in the 44 APOE ε4 non‐carriers who completed the 78‐week protocol.MethodsStructural magnetic resonance imaging scans obtained at baseline and after 78 weeks were analyzed using the Automated Segmentation of Hippocampal Subfields software providing volume measures of key structures of the medial temporal lobe relevant to AD progression. Blood samples collected at 78 weeks in the study were analyzed for plasma biomarkers.ResultsTreatment with AGB101 significantly reduced atrophy of the left entorhinal cortex (ERC) compared to placebo. This reduction in atrophy was correlated with less decline in the CDR‐SB score over 78 weeks and with lower neurofilament light chain (NfL), a marker of neurodegeneration.DiscussionThe HOPE4MCI study showed that APOE ε4 non‐carriers treated with AGB101 demonstrated a substantially more favorable treatment effect compared to carriers. Here we report that treatment with AGB101 in non‐carriers of APOE ε4 significantly reduced atrophy of the left ERC over 78 weeks. That reduction in atrophy was closely coupled with the change in CDR‐SB and with plasma NfL indicative of neurodegeneration in the brain. These exploratory analyses are consistent with a reduction in neurodegeneration in APOE ε4 non‐carriers treated with AGB101 before a clinical diagnosis of dementia.Highlights AGB101 slows entorhinal cortex (ERC) atrophy in apolipoprotein E (APOE) ε4 non‐carriers with mild cognitive impairment (MCI) due to Alzheimer's disease (AD). Slowing ERC atrophy by AGB101 is associated with less Clinical Dementia Rating Sum of Boxes decline. Slowing ERC atrophy by AGB101 is associated with lower neurofilament light chain. AGB101 treatment reduces neurodegeneration in APOE ε4 non‐carriers with MCI due to AD.

Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains.

The paramagnetic iron, diamagnetic amyloid beta (Aβ) plaques and their interaction are crucial in Alzheimer's disease (AD) pathogenesis, complicating non-invasive magnetic resonance imaging for prodromal AD detection. We used a state-of-the-art sub-voxel quantitative susceptibility mapping method to simultaneously measure Aβ and iron levels in post mortem human brains, validated by histology. Further transcriptomic analysis using Allen Human Brain Atlas elucidated the underlying biological processes. Regional increased paramagnetic and diamagnetic susceptibility were observed in medial prefrontal, medial parietal, and para-hippocampal cortices associated with iron deposition (R=0.836, p=0.003) and Aβ accumulation (R=0.853, p=0.002) in AD brains. Higher levels of gene expression relating to cell cycle, post-translational protein modifications, and cellular response to stress were observed. These findings provide quantitative insights into the variable vulnerability of cortical regions to higher levels of Aβ aggregation, iron overload, and subsequent neurodegeneration, indicating changes preceding clinical symptoms. The vulnerability of distinct brain regions to amyloid beta (Aβ) and iron accumulation varies. Histological validation was performed on stained sections of ex-vivo human brains. Regional variations in susceptibility were linked to gene expression profiles. Iron and Aβ levels in ex-vivo brains were simultaneously quantified.

Prodromal Alzheimer's Disease: Global Cognition, Cue Efficiency, and Cerebrospinal Fluid Neurofilament Light Values Predict Short-Term Conversion to Dementia.

Predicting which patients with prodromal AD (pAD) will imminently convert to dementia may be paramount in a memory clinical setting, especially with potential disease-modifying therapies on the horizon. To explore a practical tool for this prediction, combining cognitive tests and cerebrospinal fluid (CSF) biomarkers. We designed a longitudinal prospective, observational, and multicenter study, enrolling patients with pAD. Inclusion criteria comprised memory complaints, Mini-Mental State Examination (MMSE) score of≥22, memory impairment as indicated by the Free and Cued Selective Reminding Test with Immediate Recall (FCSRT + IR) and/or TMA-93, Clinical Dementia Rating-Global Score (CDR-GS) of 0.5, and positive CSF Aβ42/Aβ40 ratio (<0.095, Euroimmun). The primary outcome was the conversion to dementia (CDR-GS≥1) within the first year of follow-up, referred to as "short-term conversion". A multiple regression logistic model was adopted to design the "Predict Short-Term Conversion" (PSTC) score. Between 2020 and 2022, 83 patients were recruited. The median age was 74, with 49.4% being women. Twenty-five (30.1%) patients were classified as short-term converters. The PSTC score incorporated baseline scores on MMSE ( ≤24 = 3, >24 = 0) and FCSRT + IR Total Recall ( ≤14 = 4, >14 = 0), and CSF neurofilament light chains (NfLs) concentrations (β=0.001299). The PSTC score demonstrated an area under the curve of 0.78 (95% CI: 0.67-0.90, p < 0.001), with a cutoff value of 5.14 presenting 76% sensitivity and 80% specificity. The PSTC score, comprising two relatively brief cognitive test scores and NfLs CSF concentrations, could be useful for predicting short-term converters among patients diagnosed with pAD.

Behavioral Alterations of Spatial Cognition and Role of the Apolipoprotein E-ε4 in Patients with MCI Due to Alzheimer's Disease: Results from the BDSC-MCI Project.

Background: Beyond memory deterioration, spatial disorientation may occur along the continuum of normal aging-dementia of Alzheimer's type. The present study aims at detecting behavioral disorders of spatial cognition in prodromal Alzheimer's disease (AD) and verifying the association between Apolipoprotein E-ε4 (ApoE-ε4) genotype and gait patterns during a real-world naturalistic task. Methods: A sample of 58 elderly participants, of which 20 patients with mild cognitive impairment with CFS biomarker evidence of AD, 23 individuals with subjective cognitive decline (SCD), and 15 healthy controls (HCs), was tested by a modified version of the Detour Navigation Test (DNT-mv). Generalized linear models were run to explore the association between group belonging and wrong turns (WTs)/moments of hesitation (MsH) as behavioral disorientation scores of the DNT-mv as well as the effect of ApoE-ε4 genotype on time and walking speed registered by a smartphone app providing GPS tracking of body movement around urban environments. Results: Patients with MCI due to AD reported more WTs than individuals with SCD and HCs. Further, the ApoE-ε4 genotype determined a lower capacity in spatial information processing, influencing gait during naturalistic spatial navigation tasks. Conclusions: Behavior alterations of spatial cognition can be detected ecologically in prodromal AD. The use of technological solutions supporting gait analysis may help in corroborating the experimental observation.

Path Integration Detects Prodromal Alzheimer's Disease and Predicts Cognitive Decline.

The entorhinal cortex is the very earliest involvement of Alzheimer's disease (AD). Grid cells in the medial entorhinal cortex form part of the spatial navigation system. We aimed to determine whether path integration performance can be used to detect patients with mild cognitive impairment (MCI) at high risk of developing AD, and whether it can predict cognitive decline. Path integration performance was assessed in 71 patients with early MCI (EMCI) and late MCI (LMCI) using a recently developed 3D virtual reality navigation task. Patients with LMCI were further divided into those displaying characteristic brain imaging features of AD, including medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single-photon emission tomography (LMCI+), and those not displaying such features (LMCI-). Path integration performance was significantly lower in patients with LMCI+than in those with EMCI and LMCI-. A significantly lower performance was observed in patients who showed progression of MCI during 12 months, than in those with stable MCI. Path integration performance distinguished patients with progressive MCI from those with stable MCI, with a high classification accuracy (a sensitivity of 0.88 and a specificity of 0.70). Our results suggest that the 3D virtual reality navigation task detects prodromal AD patients and predicts cognitive decline after 12 months. Our navigation task, which is simple, short (12-15 minutes), noninvasive, and inexpensive, may be a screening tool for therapeutic choice of disease-modifiers in individuals with prodromal AD.

Monomeric Amyloid Peptide-induced Toxicity in Human Oligodendrocyte Cell Line and Mouse Brain Primary Mixed-glial Cell Cultures: Evidence for a Neuroprotective Effect of Neurosteroid 3α-O-allyl-allopregnanolone.

Amyloid-peptide (Aβ) monomeric forms (ABM) occurring in presymptomatic Alzheimer's disease (AD) brain are thought to be devoid of neurotoxicity while the transition/aggregation of ABM into oligomers is determinant for Aβ-induced toxicity since Aβ is predominantly monomeric up to 3µM and aggregates over this concentration. However, recent imaging and/or histopathological investigations revealed alterations of myelin in prodromal AD brain in absence of aggregated Aβ oligomers, suggesting that ABM may induce toxicity in myelin-producing cells in early AD-stages. To check this hypothesis, here we studied ABM effects on the viability of the Human oligodendrocyte cell line (HOG), a reliable oligodendrocyte model producing myelin proteins. Furthermore, to mimic closely interactions between oligodendrocytes and other glial cells regulating myelination, we investigated also ABM effects on mouse brain primary mixed-glial cell cultures. Various methods were combined to show that ABM concentrations (600nM-1µM), extremely lower than 3µM, significantly decreased HOG cell and mouse brain primary mixed-glial cell survival. Interestingly, flow-cytometry studies using specific cell-type markers demonstrated that oligodendrocytes represent the most vulnerable glial cell population affected by ABM toxicity. Our work also shows that the neurosteroid 3α-O-allyl-allopregnanolone BR351 (250 and 500nM) efficiently prevented ABM-induced HOG and brain primary glial cell toxicity. Bicuculline (50-100nM), the GABA-A-receptor antagonist, was unable to block/reduce BR351 effect against ABM-induced HOG and primary glial cell toxicity, suggesting that BR351-evoked neuroprotection of these cells may not depend on GABA-A-receptor allosterically modulated by neurosteroids. Altogether, our results suggest that further exploration of BR351 therapeutic potential may offer interesting perspectives to develop effective neuroprotective strategies.

Neurometabolic topography and associations with cognition in Alzheimer's disease: A whole-brain high-resolution 3D MRSI study.

Altered neurometabolism, detectable via proton magnetic resonance spectroscopic imaging (1H-MRSI), is spatially heterogeneous and underpins cognitive impairments in Alzheimer's disease (AD). However, the spatial relationships between neurometabolic topography and cognitive impairment in AD remain unexplored due to technical limitations. We used a novel whole-brain high-resolution 1H-MRSI technique, with simultaneously acquired 18F-florbetapir positron emission tomography (PET) imaging, to investigate the relationship between neurometabolic topography and cognitive functions in 117 participants, including 22 prodromal AD, 51 AD dementia, and 44 controls. Prodromal AD and AD dementia patients exhibited spatially distinct reductions in N-acetylaspartate, and increases in myo-inositol. Reduced N-acetylaspartate and increased myo-inositol were associated with worse global cognitive performance, and N-acetylaspartate correlated with five specific cognitive scores. Neurometabolic topography provides biological insights into diverse cognitive dysfunctions. Whole-brain high-resolution 1H-MRSI revealed spatially distinct neurometabolic topographies associated with cognitive decline in AD, suggesting potential for noninvasive brain metabolic imaging to track AD progression. Whole-brain high-resolution 1H-MRSI unveils neurometabolic topography in AD. Spatially distinct reductions in NAA, and increases in mI, are demonstrated. NAA and mI topography correlates with global cognitive performance. NAA topography correlates with specific cognitive performance.

Amyloid profile is associated with sleep quality in preclinical but not in prodromal Alzheimer’s disease older adults

BackgroundFew studies have assessed whether neuropathological markers of AD in the preclinical and prodromal stages are associated with polysomnographic changes and obstructive sleep apnea (OSA). MethodsThis was a cross-sectional, case-control study of older adults (≥60 years) without relevant clinical and psychiatric comorbidities selected randomly from a cohort of individuals without dementia in a tertiary university hospital in São Paulo, Brazil. They underwent neuropsychological evaluation for clinical diagnosis and were allocated into two samples: cognitively unimpaired (CU) and mild cognitive impairment (MCI). Also, they underwent PET-PiB to determine the amyloid profile and all-night in-lab polysomnography. For each sample, we compared polysomnographic parameters according to the amyloid profile (A+ vs A-). ResultsWe allocated 67 participants (mean age 73 years, SD 10,1), 70 % females, 14 ± 5 years of education, into two samples: CU (n = 28, 42.4 %) and MCI (n = 39, 57.6 %). In the CU sample, the group A+ (n = 9) showed worse sleep parameters than A- (n = 19) (lower total sleep time (p = 0.007), and sleep efficiency (p = 0.005); higher sleep onset latency (p = 0.025), wake time after sleep onset (p = 0.011), and arousal index (AI) (p = 0.007)), and changes in sleep structure: higher %N1 (p = 0.005), and lower %REM (p = 0.006). In the MCI sample, MCI A-had higher AI (p = 0.013), respiratory disturbance index (p = 0.025, controlled for age), and higher rates of severe OSA than A+. DiscussionThe amyloid profile was associated with polysomnographic markers of worse sleep quality in individuals with preclinical AD but not with prodromal AD, probably due to the higher frequencies of severe OSA.

Synaptic protein CSF levels relate to memory scores in individuals without dementia.

We investigated how cerebrospinal fluid levels of synaptic proteins associate with memory function in normal cognition (CN) and mild cognitive impairment (MCI), and investigated the effect of amyloid positivity on these associations. We included 242 CN (105(43%) abnormal amyloid), and 278 MCI individuals (183(66%) abnormal amyloid) from EMIF-AD MBD and ADNI. For 181 (EMIF-AD MBD) and 36 (ADNI) proteins with a synaptic annotation in SynGO, associations with word learning recall were analysed with linear models. Subsets of synaptic proteins showed lower levels with worse recall in preclinical AD (EMIF-AD MBD: 7, ADNI: 5 proteins, none overlapping), prodromal AD (EMIF-AD MBD only, 27 proteins) and non-AD MCI (EMIF-AD MBD: 1, ADNI: 7 proteins). The majority of these associations were specific to these groups. Synaptic disturbance-related memory impairment occurred very early in AD, indicating it may be relevant to develop therapies targeting the synapse early in the disease.

Disentangling brain atrophy heterogeneity in Alzheimer's disease: A deep self-supervised approach with interpretable latent space

Alzheimer's disease (AD) is heterogeneous, but existing methods for capturing this heterogeneity through dimensionality reduction and unsupervised clustering have limitations when it comes to extracting intricate atrophy patterns. In this study, we propose a deep learning based self-supervised framework that characterizes complex atrophy features using latent space representation. It integrates feature engineering, classification, and clustering to synergistically disentangle heterogeneity in Alzheimer's disease. Through this representation learning, we trained a clustered latent space with distinct atrophy patterns and clinical characteristics in AD, and replicated the findings in prodromal Alzheimer's disease. Moreover, we discovered that these clusters are not solely attributed to subtypes but also reflect disease progression in the latent space, representing the core dimensions of heterogeneity, namely progression and subtypes. Furthermore, longitudinal latent space analysis revealed two distinct disease progression pathways: medial temporal and parietotemporal pathways. The proposed approach enables effective latent representations that can be integrated with individual-level cognitive profiles, thereby facilitating a comprehensive understanding of AD heterogeneity.

Contrastive Self-supervised Learning for Neurodegenerative Disorder Classification.

Neurodegenerative diseases such as Alzheimer's disease (AD) or frontotemporal lobar degeneration (FTLD) involve specific loss of brain volume, detectable in vivo using T1-weighted MRI scans. Supervised machine learning approaches classifying neurodegenerative diseases require diagnostic-labels for each sample. However, it can be difficult to obtain expert labels for a large amount of data. Self-supervised learning (SSL) offers an alternative for training machine learning models without data-labels. We investigated if the SSL models can applied to distinguish between different neurodegenerative disorders in an interpretable manner. Our method comprises a feature extractor and a downstream classification head. A deep convolutional neural network trained in a contrastive self-supervised way serves as the feature extractor, learning latent representation, while the classifier head is a single-layer perceptron. We used N=2694 T1-weighted MRI scans from four data cohorts: two ADNI datasets, AIBL and FTLDNI, including cognitively normal controls (CN), cases with prodromal and clinical AD, as well as FTLD cases differentiated into its sub-types. Our results showed that the feature extractor trained in a self-supervised way provides generalizable and robust representations for the downstream classification. For AD vs. CN, our model achieves 82% balanced accuracy on the test subset and 80% on an independent holdout dataset. Similarly, the Behavioral variant of frontotemporal dementia (BV) vs. CN model attains an 88% balanced accuracy on the test subset. The average feature attribution heatmaps obtained by the Integrated Gradient method highlighted hallmark regions, i.e., temporal gray matter atrophy for AD, and insular atrophy for BV. In conclusion, our models perform comparably to state-of-the-art supervised deep learning approaches. This suggests that the SSL methodology can successfully make use of unannotated neuroimaging datasets as training data while remaining robust and interpretable.

Nutrition guidance within a multimodal intervention improves diet quality in prodromal Alzheimer’s disease: Multimodal Preventive Trial for Alzheimer’s Disease (MIND-ADmini)

BackgroundMultimodal lifestyle interventions can benefit overall health, including cognition, in populations at-risk for dementia. However, little is known about the effect of lifestyle interventions in patients with prodromal Alzheimer’s disease (AD). Even less is known about dietary intake and adherence to dietary recommendations within this population making it difficult to design tailored interventions for them.MethodA 6-month MIND-ADmini pilot randomized controlled trial (RCT) was conducted among 93 participants with prodromal AD in Sweden, Finland, Germany, and France. Three arms were included in the RCT: 1) multimodal lifestyle intervention (nutritional guidance, exercise, cognitive training, vascular/metabolic risk management, and social stimulation); 2) multimodal lifestyle intervention + medical food product; and 3) regular health advice (control group). Adherence to dietary advice was assessed with a brief food intake questionnaire by using the Healthy Diet Index (HDI) and Mediterranean Diet Adherence Screener (MEDAS). The intake of macro- and micronutrients were analyzed on a subsample using 3-day food records.ResultsThe dietary quality in the intervention groups, pooled together, improved compared to that of the control group at the end of the study, as measured with by HDI (p = 0.026) and MEDAS (p = 0.008). The lifestyle-only group improved significantly more in MEDAS (p = 0.046) and almost significantly in HDI (p = 0.052) compared to the control group, while the lifestyle + medical food group improved in both HDI (p = 0.042) and MEDAS (p = 0.007) during the study. There were no changes in macro- or micronutrient intake for the intervention groups at follow-up; however, the intakes in the control group declined in several vitamins and minerals when adjusted for energy intake.ConclusionThese results suggest that dietary intervention as part of multimodal lifestyle interventions is feasible and results in improved dietary quality in a population with prodromal AD. Nutrient intakes remained unchanged in the intervention groups while the control group showed a decreasing nutrient density.Trial registrationClinicalTrials.gov NCT03249688, 2017–07-08.

Snoring and risk of dementia: a prospective cohort and Mendelian randomization study.

The association between snoring, a very common condition that increases with age, and dementia risk is controversial. We aimed to investigate the observational and causal relationship between snoring and dementia, and to elucidate the role of body mass index (BMI). Using data from 451,250 participants who were dementia-free at baseline, we examined the association between self-reported snoring and incident dementia using Cox proportional-hazards models. Causal relationship between snoring and Alzheimer's disease (AD) was examined using bidirectional two-sample Mendelian randomization (MR) analysis. During a median follow-up of 13.6 years, 8,325 individuals developed dementia. Snoring was associated with a lower risk of all-cause dementia (hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.89 to 0.98) and AD (HR 0.91; 95% CI 0.84 to 0.97). The association was slightly attenuated after adjusting for BMI, and was stronger in older individuals, APOE ε4 allele carriers, and during shorter follow-up periods. MR analyses suggested no causal effect of snoring on AD, however, genetic liability to AD was associated with a lower risk of snoring. Multivariable MR indicated that the effect of AD on snoring was primarily driven by BMI. The phenotypic association between snoring and lower dementia risk likely stems from reverse causation, with genetic predisposition to AD associated with reduced snoring. This may be driven by weight loss in prodromal AD. Increased attention should be paid to reduced snoring and weight loss in older adults as potential early indicators of dementia risk.