Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

Plasma biomarkers of amyloid, tau & neuroinflammation in Alzheimer's disease and corticobasal syndrome

Blood-based biomarkers (BBBMs) could significantly facilitate the diagnosis of Alzheimer's disease (AD) and non-AD dementia by providing less invasive alternatives to cerebrospinal fluid (CSF) and positron emission tomography (PET) imaging. This study investigated how well the BBBMs-amyloid-β (Aβ) 1-42/1-40 ratio, phosphorylated tau181 (pTau181), apolipoprotein E4 (ApoE4), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL)-reflect thorough clinical work-up validated by PET and CSF biomarkers in participants with AD (n = 27), Aβ-negative CBS (n = 26), and age-matched healthy controls (HC) (n = 17). Factor and correlation explored biomarker associations. Bayesian regression, backward selection regression, and ROC curve analysis were applied to identify optimal biomarker combinations and diagnostic cut-offs. In AD cases, pTau181 and ApoE4 levels were elevated, and the Aβ1-42/1-40 ratio was reduced. ROC analysis showed high accuracy for pTau181, ApoE4 and Aβ1-42/1-40 in discriminating AD from HC, with a combination significantly improving performance. However, limited fold change, and high variability reduced the diagnostic applicability of Aβ1-42/1-40 ratio. Elevated NfL levels were the most reliable biomarker for CBS-Aβ(-) cases. GFAP showed limited discriminatory power due to overlapping levels, suggesting that it may not serve as a disease-specific biomarker but may be indicative of general neurodegeneration. This study highlights the diagnostic utility of pTau181, ApoE4 and the Aβ1-42/1-40 ratio for AD and NfL in the CBS-Aβ(-) cases and emphasizes the added value of combined biomarker models for group differentiation. Prospective studies will help validate these findings and refine clinical thresholds.

A multiscale model to explain the spatiotemporal progression of amyloid beta and tau pathology in Alzheimer's disease

Amyloid-beta (Aβ) and tubulin-associated unit (tau) proteins are key biomarkers of Alzheimer's disease (AD), detectable by Positron Emission Tomography (PET) imaging and Cerebrospinal Fluid (CSF) assays. They reflect insoluble fibrils in the brain and soluble monomers in the cerebrospinal fluid, respectively. PET and CSF biomarkers have been utilized in diagnosing AD; however, their incomplete agreement significantly confounds the early detection. Additionally, the molecular mechanisms underlying the dynamics of AD biomarkers remain elusive and are yet to be quantitatively revealed. To answer these questions, we develop a multiscale mathematical model that characterizes various forms of AD biomarkers, including soluble molecules in cerebrospinal fluid, diffusive biomarkers across brain regions, and insoluble fibrils in the brain. Mathematical modeling of soluble and insoluble molecules enables the explanation of the asynchronous trajectory of AD biomarkers. Our model captures the spatiotemporal dynamics of Aβ and tau with neurodegeneration in AD. Simulation results demonstrate that the PET-CSF discordance is a typical stage in the natural history of protein aggregation, with CSF becoming abnormal before the onset of PET abnormality. Furthermore, correlation analysis reveals that neurodegeneration is more strongly associated with tau-PET than Aβ-PET. These findings suggest CSF Aβ is recognized as a biomarker at the early stage of AD, while tau-PET is more suitable for neurodegeneration assessment. The proposed multiscale model explains the underlying neurobiological factors contributing to neurodegeneration and offers a valuable tool for improving early detection and treatment strategies in clinical trials.

Cutting through the noise: A narrative review of Alzheimer's disease plasma biomarkers for routine clinical use

As novel, anti-amyloid therapies have become more widely available, access to timely and accurate diagnosis has become integral to ensuring optimal treatment of patients with early-stage Alzheimer's disease (AD). Plasma biomarkers are a promising tool for identifying AD pathology; however, several technical and clinical factors need to be considered prior to their implementation in routine clinical use. Given the rapid pace of advancements in the field and the wide array of available biomarkers and tests, this review aims to summarize these considerations, evaluate available platforms, and discuss the steps needed to bring plasma biomarker testing to the clinic. We focus on plasma phosphorylated(p)-tau, specifically plasma p-tau217, as a robust candidate across both primary and secondary care settings. Despite the high performance and robustness demonstrated in research, plasma p-tau217, like all plasma biomarkers, can be affected by analytical and pre-analytical variability as well as patient comorbidities, sex, ethnicity, and race. This review also discusses the advantages of the two-point cut-off approach to mitigating these factors, and the challenges raised by the resulting intermediate range measurements, where clinical guidance is still unclear. Further validation of plasma p-tau217 in heterogeneous, real-world cohorts will help to increase confidence in testing and support establishing a standardized approach. Plasma biomarkers are poised to become a more affordable and less invasive alternative to PET and CSF testing. However, understanding the factors that impact plasma biomarker measurement and interpretation is critical prior to their implementation in routine clinical use.

Depressive Symptoms and Amyloid Pathology

Importance

Depressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology.

Objective

To examine the association between depressive symptoms and amyloid pathology and its dependency on age, sex, education, and APOE genotype in older individuals without dementia.

Design, Setting, and Participants

Cross-sectional analyses were performed using data from the Amyloid Biomarker Study data pooling initiative. Data from 49 research, population-based, and memory clinic studies were pooled and harmonized. The Amyloid Biomarker Study has been collecting data since 2012 and data collection is ongoing. At the time of analysis, 95 centers were included in the Amyloid Biomarker Study. The study included 9746 individuals with normal cognition (NC) and 3023 participants with mild cognitive impairment (MCI) aged between 34 and 100 years for whom data on amyloid biomarkers, presence of depressive symptoms, and age were available. Data were analyzed from December 2022 to February 2024.

Main Outcomes and Measures

Amyloid-β1-42 levels in cerebrospinal fluid or amyloid positron emission tomography scans were used to determine presence or absence of amyloid pathology. Presence of depressive symptoms was determined on the basis of validated depression rating scale scores, evidence of a current clinical diagnosis of depression, or self-reported depressive symptoms.

Results

In individuals with NC (mean [SD] age, 68.6 [8.9] years; 5664 [58.2%] female; 3002 [34.0%] APOE ε4 carriers; 937 [9.6%] had depressive symptoms; 2648 [27.2%] had amyloid pathology), the presence of depressive symptoms was not associated with amyloid pathology (odds ratio [OR], 1.13; 95% CI, 0.90-1.40; P = .29). In individuals with MCI (mean [SD] age, 70.2 [8.7] years; 1481 [49.0%] female; 1046 [44.8%] APOE ε4 carriers; 824 [27.3%] had depressive symptoms; 1668 [55.8%] had amyloid pathology), the presence of depressive symptoms was associated with a lower likelihood of amyloid pathology (OR, 0.73; 95% CI 0.61-0.89; P = .001). When considering subgroup effects, in individuals with NC, the presence of depressive symptoms was associated with a higher frequency of amyloid pathology in APOE ε4 noncarriers (mean difference, 5.0%; 95% CI 1.0-9.0; P = .02) but not in APOE ε4 carriers. This was not the case in individuals with MCI.

Conclusions and Relevance

Depressive symptoms were not consistently associated with a higher frequency of amyloid pathology in participants with NC and were associated with a lower likelihood of amyloid pathology in participants with MCI. These findings were not influenced by age, sex, or education level. Mechanisms other than amyloid accumulation may commonly underlie depressive symptoms in late life.

The impact of kidney function on Alzheimer's disease blood biomarkers: implications for predicting amyloid-β positivity

BACKGROUND

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer's disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity.

METHODS

We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [18F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m2, based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models.

RESULTS

Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values.

CONCLUSIONS

We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

Plasma Biomarkers in the Distinction of Alzheimer's Disease and Frontotemporal Dementia

Plasma biomarkers are promising tools for the screening and diagnosis of dementia in clinical settings. We analyzed plasma levels of Alzheimer's core biomarkers, neurofilament light chain (NfL) and glial fibrillary acid protein (GFAP), through single-molecule Array in 108 patients with Alzheimer's (AD, cerebrospinal fluid with an amyloid+ tau+ neurodegeneration+ profile), 73 patients with frontotemporal dementia (FTD, 24 with genetic diagnosis), and 54 controls. The best area under the curve (AUC) was used to assess the discriminative power. Patients with AD had lower Aß42/40 ratios and NfL levels, along with higher levels of p-tau181 and GFAP, compared with FTD patients. Single biomarkers discriminated well between dementia patients and controls: the Aß42/40 ratio (AUC:0.86) or GFAP (AUC:0.83) was found for AD, and the NfL (AUC:0.84) was found for FTD patients. However, a combination of two (NfL with p-tau181, or the GFAP/NfL ratio, AUCs ~0.87) or three biomarkers (NfL, P-tau181, and Aß42/40 ratio, AUC: 0.90) was required to distinguish between AD and FTD. Biomarker profiles were similar across different FTD phenotypes, except for carriers of PGRN mutations, who had higher levels of NfL than C9orf72 expansion carriers. In our series, NfL alone provided the best distinction between FTD and controls, while a combination of two or three biomarkers was required to obtain good discrimination between AD and FTD.

The ratio of plasma pTau217 to Aβ42 outperforms individual measurements in detecting brain amyloidosis

IMPORTANCE

Early detection of brain amyloidosis (Aβ+) is pivotal for diagnosing Alzheimer's disease (AD) and optimizing patient management, especially in light of emerging treatments. While plasma biomarkers are promising, their combined diagnostic value through specific ratios remains underexplored.

OBJECTIVE

To evaluate the diagnostic accuracy of plasma pTau isoform (pTau181 and pTau217) to Aβ42 ratios in detecting Aβ+ status.

DESIGN SETTING AND PARTICIPANTS

This study included 423 participants from the multicenter prospective ALZAN cohort, recruited for cognitive complaints. Aβ+ status was determined using cerebrospinal fluid (CSF) biomarkers. Validation of the key findings was performed in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, where Aβ+ status was determined using PET imaging.

EXPOSURES

Plasma biomarkers (pTau181, pTau217, Aβ40, Aβ42) were measured using immunoassays and mass spectrometry, with specific ratios calculated. In the ALZAN cohort, the impact of confounding factors such as age, renal function, ApoE4 status, body mass index, and the delay between blood collection and processing was also evaluated to assess their influence on biomarker concentrations and diagnostic performance.

MAIN OUTCOMES AND MEASURES

The primary outcome was the diagnostic performance of plasma biomarkers and their ratios for detecting Aβ+ status. Secondary outcomes included the proportion of patients classified as low, intermediate, or high risk for Aβ+ using a two-cutoff approach.

RESULTS

The pTau181/Aβ42 ratio matched the diagnostic performance of pTau217 with AUC of 0.911 (0.880-0.936). The pTau217/Aβ42 ratio demonstrated the highest diagnostic accuracy in the ALZAN cohort, with an AUC of 0.927 (0.898-0.950), outperforming individual biomarkers. Both ratios effectively mitigated confounding factors, such as variations in renal function, and were particularly excellent in identifying Aβ+ status in individuals with early cognitive decline. Validation in the ADNI cohort confirmed these findings, with consistent performance across different measurement methods. The two-cutoff workflow using pTau217/Aβ42 reduced the intermediate-risk zone from 16% to 8%, enhancing stratification for clinical decision-making.

CONCLUSIONS AND RELEVANCE

The pTau217/Aβ42 ratio offers superior diagnostic accuracy for detecting Aβ+ compared to individual biomarkers and reduces diagnostic uncertainty. These findings highlight the clinical utility of plasma biomarker ratios for early AD detection, paving the way for broader implementation in clinical and research settings.

Updated Appropriate Use Criteria for Amyloid and Tau PET: A Report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup

The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. Methods: The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities. Results: For amyloid PET, 7 scenarios were rated as appropriate, 2 as uncertain, and 8 as rarely appropriate. For tau PET, 5 scenarios were rated as appropriate, 6 as uncertain, and 6 as rarely appropriate. Conclusion: AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.

18F-Florzolotau PET Imaging Unveils Tau Pathology in Dementia with Lewy Bodies

BACKGROUND

Dementia with Lewy bodies (DLB) commonly exhibits a complex neuropathology, sharing characteristics with Alzheimer's disease (AD), including tau aggregates. However, studies using the 18F-AV-1451 tau tracer have shown inconsistent findings regarding both the extent and topographical distribution of tau pathology in DLB.

OBJECTIVES

Our aim was to elucidate the topographical patterns of tau deposition in DLB and to investigate the in vivo pathological distinction between DLB and AD in virtue of the 18F-Florzolotau positron emission tomography (PET) imaging.

METHODS

This cross-sectional study enrolled patients with DLB (n = 24), AD (n = 43), and cognitively healthy controls (n = 18). Clinical assessments and 18F-Florzolotau PET imaging were performed. 18F-Florzolotau binding was quantitatively assessed on PET images using standardized uptake value ratios and voxel-wise analysis.

RESULTS

18F-Florzolotau PET imaging revealed widespread tau deposition across various cortical regions in DLB, uncovering heterogeneous topographical patterns. Among patients, 54.17% showed patterns similar to AD, whereas 16.67% exhibited distinct patterns. Compared to AD, DLB exhibited a unique in vivo neuropathological profile, characterized by a lower tau protein burden, heterogeneous topographical distributions, and a specific role of the medial temporal lobe in tau pathology.

CONCLUSIONS

18F-Florzolotau PET imaging elucidated tau pathology patterns in DLB, providing valuable insights for future in vivo pathological differentiation and potential disease-modifying therapies. © 2024 International Parkinson and Movement Disorder Society.

Updated appropriate use criteria for amyloid and tau PET: A report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup

INTRODUCTION

The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET.

METHODS

The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities.

RESULTS

For amyloid PET, seven scenarios were rated as appropriate, two as uncertain, and eight as rarely appropriate. For tau PET, five scenarios were rated as appropriate, six as uncertain, and six as rarely appropriate.

DISCUSSION

AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.

HIGHLIGHTS

A multidisciplinary workgroup convened by the Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging updated the appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. The goal of these updated AUC is to assist clinicians in identifying clinical scenarios in which amyloid or tau PET may be useful for guiding the diagnosis and management of patients who have, or are at risk for, cognitive decline These updated AUC are intended for dementia specialists who spend a significant proportion of their clinical effort caring for patients with cognitive complaints, as well as serve as a general reference for a broader audience interested in implementation of amyloid and tau PET in clinical practice.

A whole-brain functional connectivity model of Alzheimer's disease pathology

INTRODUCTION

Alzheimer's disease (AD) is characterized by the presence of two proteinopathies, amyloid and tau, which have a cascading effect on the functional and structural organization of the brain.

METHODS

In this study, we used a supervised machine learning technique to build a model of functional connections that predicts cerebrospinal fluid (CSF) p-tau/Aβ42 (the PATH-fc model). Resting-state functional magnetic resonance imaging (fMRI) data from 289 older adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were utilized for this model.

RESULTS

We successfully derived the PATH-fc model to predict the ratio of p-tau/Aβ42 as well as cognitive functioning in older adults across the spectrum of healthy and pathological aging. However, the in-sample fit magnitude was low, indicating a need for further model development.

DISCUSSION

Our pathology-based model of functional connectivity included representation from multiple canonical networks of the brain with intra-network connectivity associated with low pathology and inter-network connectivity associated with higher levels of pathology.

HIGHLIGHTS

Whole-brain functional connectivity model (PATH-fc) is linked to AD pathophysiology. The PATH-fc model predicts performance in multiple domains of cognitive functioning. The PATH-fc model is a distributed model including representation from all canonical networks.

The CSF p-tau/β-amyloid 42 ratio correlates with brain structure and fibrillary β-amyloid deposition in cognitively unimpaired individuals at the earliest stages of pre-clinical Alzheimer's disease

CSF concentrations of β-amyloid 42 (Aβ42) and phosphorylated tau (p-tau) are well-established biomarkers of Alzheimer's disease and have been studied in relation to several neuropathological features both in patients and in cognitively unimpaired individuals. The CSF p-tau/Aβ42 ratio, a biomarker combining information from both pathophysiological processes, has emerged as a promising tool for monitoring disease progression, even at pre-clinical stages. Here, we studied the association between the CSF p-tau/Aβ42 ratio with downstream markers of pre-clinical Alzheimer's disease progression including brain structure, glucose metabolism, fibrillary Aβ deposition and cognitive performance in 234 cognitively unimpaired individuals, who underwent cognitive testing, a lumbar puncture, MRI, 18F-fluorodeoxyglucose and 18F-flutemetamol PET scanning. We evaluated both main effects and interactions with Alzheimer's disease risk factors, such as older age, female sex and the apoliporoptein E (APOE)-ɛ4 allele, in a priori defined regions of interest and further examined the associations on the whole-brain using voxel-wise regressions. In addition, as the association between CSF Alzheimer's disease biomarkers and brain structure and function may be non-linear, we tested the interaction between the CSF p-tau/Aβ42 ratio and stages of pre-clinical Alzheimer's disease defined using the amyloid (A) and tau (T) classification. We found significantly positive associations between CSF p-tau/Aβ42 and both cortical Aβ deposition and regional grey matter volume while no effect was observed for brain metabolism. A significant interaction with age indicated that, for the same level of CSF p-tau/Aβ42, older individuals displayed both increased Aβ deposition and lower grey matter volume, in widespread cortical areas. In addition, we found that women compared with men had a greater Aβ fibrillary accumulation in midline cortical areas and inferior temporal regions, for the same level of the CSF biomarker. The impact of CSF p-tau/Aβ42 on grey matter volume was modulated by AT stages, with A+T+ individuals displaying significantly less positive associations in areas of early atrophy in the Alzheimer's continuum. Finally, we found that sex and APOE-ɛ4 modulated the association between the CSF biomarker and episodic memory as well as abstract reasoning, respectively. Our data indicate that the CSF p-tau/Aβ42 ratio is strongly associated with multiple downstream neuropathological events in cognitively unimpaired individuals and may thus serve as a potent biomarker to investigate the earliest changes in pre-clinical Alzheimer's disease. Given that its impact on both Aβ deposition and grey matter volume is modulated by specific risk factors, our results highlight the need to take into account such predisposing variables in both clinical practice and prevention trials.

Strong diagnostic performance of plasma ptau217 for CSF biomarker-defined young-onset Alzheimer disease in a diagnostically heterogeneous clinical cohort

OBJECTIVE

We investigated diagnostic utility of phosphorylated tau 217 and 181 (ptau217, ptau181), glial fibrillary acidic protein (GFAP), amyloid beta 42 and 40 (Aβ42, Aβ40), and neurofilament light (NfL) to distinguish biomarker-defined Alzheimer disease (AD) from non-AD conditions, in a heterogenous clinical cohort of younger people.

METHODS

Plasma biomarkers were analysed using ultrasensitive technology, and compared in patients with CSF Alzheimer disease profiles (A+T+) to other CSF profiles (Other).

RESULTS

Seventy-nine patients were included, median age 60.8 years: 16 A+T+, 63 Other. Ptau217, ptau181, GFAP were significantly elevated in A+T+ compared to Other (3.67 vs 1.12 pg/mL, 3.87 vs 1.79 pg/mL, 189 vs 80 pg/mL, respectively). ptau217 distinguished AD from Other with 90% accuracy (88% specificity, 100% sensitivity). ptau217 also demonstrated strong diagnostic performance for clinically diagnosed AD.

CONCLUSIONS

Plasma ptau217 has strong diagnostic performance in distinguishing CSF biomarker-defined AD in a clinically relevant, younger cohort of people with symptoms, adding further weight for a simple diagnostic blood test for AD as a cause of a patient's symptoms.

Assessing polyomic risk to predict Alzheimer's disease using a machine learning model

INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia in the elderly. Given that AD neuropathology begins decades before symptoms, there is a dire need for effective screening tools for early detection of AD to facilitate early intervention.

METHODS

Here, we used tree-based and deep learning methods to train polyomic prediction models for AD affection status and age at onset, employing genomic, proteomic, metabolomic, and drug use data from UK Biobank. We used SHAP to determine the feature's importance.

RESULTS

Our best-performing polyomic model achieved an area under the receiver operating characteristics curve (AUROC) of 0.87. We identified GFAP and CXCL17 proteins to be the strongest predictors of AD, besides apolipoprotein E (APOE) alleles. Increasing the number of cases by including "AD-by-proxy" cases did not improve AD prediction.

DISCUSSION

Among the four modalities, genomics, and proteomics were the most informative modality based on AUROC (area under the receiver operating characteristic curve). Our data suggest that two blood-based biomarkers (glial fibrillary acidic protein [GFAP] and CXCL17) may be effective for early presymptomatic prediction of AD.

HIGHLIGHTS

We developed a polyomic model to predict AD and age-at-onset using omics and medication use data from EHR. We identified GFAP and CXCL17 proteins to be the strongest predictors of AD, besides APOE alleles. "AD-by-proxy" cases, if used in training, do not improve AD prediction. Proteomics was the most informative modality overall for affection status and AAO prediction.

Distinct Cognitive Trajectories According to Amyloid Positivity in Non-Alzheimer Disease Dementias

BACKGROUND

The clinical effects of β-amyloid positivity (Aβ+) on copathologies in various dementias remain relatively underexamined. Thus, the present study was conducted to investigate the prevalence and clinical effects of Aβ+ in subcortical vascular cognitive impairment (SVCI) and frontotemporal dementia (FTD).

PATIENTS AND METHODS

We enrolled SVCI (n = 583), FTD (n = 152), and cognitively unimpaired (CU) participants (n = 1,249) who underwent Aβ PET scans. The odds of having Aβ+ were subsequently compared among the diagnostic groups (CU, SVCI, and FTD) according to age and apolipoprotein E genotype. Additionally, a linear mixed-effects model was used to investigate the effects of Aβ+ on cognitive trajectories in SVCI and FTD.

RESULTS

Compared with CU, the SVCI group had a higher prevalence of Aβ+ in the 75 to 90 years age group (adjusted odds ratio, 1.97; 95% confidence interval, 1.36-2.85; P < 0.001), as well as within the apolipoprotein E ε3/ε3 group (adjusted odds ratio, 1.78; 95% confidence interval, 1.20-2.63; P = 0.001), whereas the FTD group showed no difference in Aβ+ prevalence. Aβ+ was associated with a worse cognitive trajectory in SVCI (adjusted β-coefficient = -0.6424; P < 0.001), but not in FTD.

CONCLUSIONS

These findings contribute to our understanding of Aβ biomarker traits in various dementias in Korea.

Identifying Alzheimer's disease-associated genes using PhenoGeneRanker

Alzheimer's disease (AD) is a neurogenerative disease that affects millions worldwide with no effective treatment. Several studies have been conducted to decipher to genomic underpinnings of AD. Due to its complex nature, many genes have been found to be associated with AD. Despite these findings, the pathophysiology of the disease is still elusive. To discover new putative AD-associated genes, in this study, we integrated multimodal gene and phenotype datasets of AD using network biology methods to prioritize potential AD-related genes. We constructed a multiplex heterogeneous network composed of patient and gene similarity networks utilizing phenotypic and omics datasets of AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We applied PhenoGeneRanker to traverse this network to discover potential AD-associated genes. To assess the impact of each network layer and seed gene, we also run PhenoGeneRanker on different variants of the network and seed genes. Our results showed that top-ranked genes captured several known AD-related genes and were enriched in Gene Ontology (GO) terms related to AD. We also observed that several top-ranked genes that are not in AD-associated gene list had literature supporting their potential relevance to AD.

Ethnic differences in the prevalence of amyloid positivity and cognitive trajectories

INTRODUCTION

We investigated the prevalence of amyloid beta (Aβ) positivity (+) and cognitive trajectories in Koreans and non-Hispanic Whites (NHWs).

METHODS

We included 5121 Koreans from multiple centers across South Korea and 929 NHWs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent Aβ positron emission tomography and were categorized into cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia stages. Age, sex, education, and apolipoprotein E. genotype were adjusted using multivariable logistic regression and stabilized inverse probability of treatment weights based on the propensity scores to mitigate imbalances in these variables.

RESULTS

The prevalence of Aβ+ was lower in CU Koreans than in CU NHWs (adjusted odds ratio 0.60). Aβ+ Koreans showed a faster cognitive decline than Aβ+ NHWs in the CU (B = -0.314, p = .004) and MCI stages (B = -0.385, p < .001).

DISCUSSION

Ethnic characteristics of Aβ biomarkers should be considered in research and clinical application of Aβ-targeted therapies in diverse populations.

HIGHLIGHTS

Koreans have a lower prevalence of Aβ positivity compared to NHWs in the CU stage. The effects of Alzheimer's risk factors on Aβ positivity differ between Koreans and NHWs. Aβ-positive (Aβ+) Koreans show faster cognitive decline than Aβ+ NHWs in the CU and MCI stages.

Amyloid PET detects the deposition of brain Aβ earlier than CSF fluid biomarkers

INTRODUCTION

Understanding the relationship between amyloid beta (Aβ) positron emission tomography (PET) and Aβ cerebrospinal fluid (CSF) biomarkers will define their potential utility in Aβ treatment. Few population-based or neuropathologic comparisons have been reported.

METHODS

Participants 50+ years with Aβ PET and Aβ CSF biomarkers (phosphorylated tau [p-tau]181/Aβ42, n = 505, and Aβ42/40, n = 54) were included from the Mayo Clinic Study on Aging. From these participants, an autopsy subgroup was identified (n = 47). The relationships of Aβ PET and Aβ CSF biomarkers were assessed cross-sectionally in all participants and longitudinally in autopsy data.

RESULTS

Cross-sectionally, more participants were Aβ PET+ versus Aβ CSF- than Aβ PET- versus Aβ CSF+ with an incremental effect when using Aβ PET regions selected for early Aβ deposition. The sensitivity for the first detection of Thal phase ≥ 1 in longitudinal data was higher for Aβ PET (89%) than p-tau181/Aβ42 (64%).

DISCUSSION

Aβ PET can detect earlier cortical Aβ deposition than Aβ CSF biomarkers. Aβ PET+ versus Aβ CSF- findings are several-fold greater using regional Aβ PET analyses and in peri-threshold-standardized uptake value ratio participants.

HIGHLIGHTS

Amyloid beta (Aβ) positron emission tomography (PET) has greater sensitivity for Aβ deposition than Aβ cerebrospinal fluid (CSF) in early Aβ development. A population-based sample of participants (n = 505) with PET and CSF tests was used. Cortical regions showing early Aβ on Aβ PET were also used in these analyses. Neuropathology was used to validate detection of Aβ by Aβ PET and Aβ CSF biomarkers.

Opportunities for use of neuroimaging in de-risking drug development and improving clinical outcomes in psychiatry: an industry perspective

Neuroimaging, across positron emission tomography (PET), electroencephalography (EEG), and magnetic resonance imaging (MRI), has been a mainstay of clinical neuroscience research for decades, yet has penetrated little into psychiatric drug development beyond often underpowered phase 1 studies, or into clinical care. Simultaneously, there is a pressing need to improve the probability of success in drug development, increase mechanistic diversity, and enhance clinical efficacy. These goals can be achieved by leveraging neuroimaging in a precision psychiatry framework, wherein effects of drugs on the brain are measured early in clinical development to understand dosing and indication, and then in later-stage trials to identify likely drug responders and enrich clinical trials, ultimately improving clinical outcomes. Here we examine the key variables important for success in using neuroimaging for precision psychiatry from the lens of biotechnology and pharmaceutical companies developing and deploying new drugs in psychiatry. We argue that there are clear paths for incorporating different neuroimaging modalities to de-risk subsequent development phases in the near to intermediate term, culminating in use of select neuroimaging modalities in clinical care for prescription of new precision drugs. Better outcomes through neuroimaging biomarkers, however, require a wholesale commitment to a precision psychiatry approach and will necessitate a cultural shift to align biopharma and clinical care in psychiatry to a precision orientation already routine in other areas of medicine.

Development and assessment of algorithms for predicting brain amyloid positivity in a population without dementia

BACKGROUND

The accumulation of amyloid-β (Aβ) peptide in the brain is a hallmark of Alzheimer's disease (AD), occurring years before symptom onset. Current methods for quantifying in vivo amyloid load involve invasive or costly procedures, limiting accessibility. Early detection of amyloid positivity in non-demented individuals is crucial for aiding early AD diagnosis and for initiating anti-amyloid immunotherapies at early stages. This study aimed to develop and validate predictive models to identify brain amyloid positivity in non-demented patients, using routinely collected clinical data.

METHODS

Predictive models for amyloid positivity were developed using data from 853 non-demented participants in the MEMENTO cohort. Amyloid levels were measured potentially repeatedly during study course through Positron Emision Tomography or CerebroSpinal Fluid analysis. The probability of amyloid positivity was modelled using mixed-effects logistic regression. Predictors included demographic information, cognitive assessments, visual brain MRI evaluations of hippocampal atrophy and lobar microbleeds, AD-related blood biomarkers (Aβ42/40 and P-tau181), and ApoE4 status. Models were subjected to internal cross-validation and external validation using data from the Amsterdam Dementia Cohort. Performance also was evaluated in a subsample that met the main criteria of the Appropriate Use Recommendations (AUR) for lecanemab.

RESULTS

The most effective model incorporated demographic data, cognitive assessments, ApoE status, and AD-related blood biomarkers, achieving AUCs of 0.82 [95%CI 0.81-0.82] in MEMENTO sample and 0.90 [95%CI 0.86-0.94] in the external validation sample. This model significantly outperformed a reference model based solely on demographic and cognitive data, with an AUC difference in MEMENTO of 0.10 [95%CI 0.10-0.11]. A similar model without ApoE genotype achieved comparable discriminatory performance. MRI markers did not improve model performance. Performances in AUR of lecanemab subsample were comparable.

CONCLUSION

A predictive model integrating demographic, cognitive, and blood biomarker data offers a promising method to help identify amyloid status in non-demented patients. ApoE genotype and brain MRI data were not necessary for strong discriminatory ability, suggesting that ApoE genotyping may be deferred when assessing the risk-benefit ratio of immunotherapies in amyloid-positive patients who desire treatment. The integration of this model into clinical practice could reduce the need for lumbar puncture or PET examinations to confirm amyloid status.

Aβ status assessment in a hypothetical scenario prior to treatment with disease-modifying therapies: Evidence from 10-year real-world experience at university memory clinics

INTRODUCTION

With the advent of disease-modifying therapies, accurate assessment of biomarkers indicating the presence of disease-associated amyloid beta (Aβ) pathology becomes crucial in patients with clinically suspected Alzheimer's disease (AD). We evaluated Aβ levels in cerebrospinal fluid (Aβ CSF) and Aβ levels in positron emission tomography (Aβ PET) biomarkers in a real-world memory-clinic setting to develop an efficient algorithm for clinical use.

METHODS

Patients were evaluated for AD-related Aβ pathology from two independent cohorts (Ludwig Maximilian University [LMU], n = 402, and Medical University of Vienna [MUV], n = 144). Optimal thresholds of CSF biomarkers were deduced from receiver operating characteristic curves and validated against Aβ PET positivity.

RESULTS

In both cohorts, a CSF Aβ42/40 ratio ≥ 7.1% was associated with a low risk of a positive Aβ PET scan (negative predictive value: 94.3%). Implementing two cutoffs revealed 14% to 16% of patients with intermediate results (CSF Aβ42/40 ratio: 5.5%-7.1%), which had a strong benefit from Aβ PET imaging (44%-52% Aβ PET positivity).

DISCUSSION

A two-cutoff approach for CSF Aβ42/40 including Aβ PET imaging at intermediate results provides an effective assessment of Aβ pathology in real-world settings.

Highlights

We evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) amyloid beta (Aβ) biomarkers for Alzheimer's disease in real-world cohorts.A CSF Aβ 42/40 ratio between 5.5% and 7.1% defines patients at borderline levels.Patients at borderline levels strongly benefit from additional Aβ PET imaging.Two-cutoff CSF Aβ 42/40 and PET will allow effective treatment stratification.

Evaluation of the EUROIMMUN automated chemiluminescence immunoassays for measurement of four core biomarkers for Alzheimer's disease in cerebrospinal fluid

Introduction

Robust immunoassays for quantification of Alzheimer's disease (AD)-specific biomarkers are required for routine diagnostics. We report analytical performance characteristics of four new chemiluminescence immunoassays (ChLIA, EUROIMMUN) running on closed, fully automated random-access instruments for quantification of Aβ1-40, Aβ1-42, tTau, and pTau(181) in human cerebrospinal fluid (CSF).

Methods

ChLIAs were validated according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). Optimal cut-offs for biomarkers and biomarker ratios were determined using samples from 219 AD patients and 220 patients with AD-related symptoms. For performance comparison, biomarker concentrations were measured in 110 diagnostic leftover samples using the ChLIAs and established Lumipulse G assays (Fujirebio).

Results

All ChLIAs met CLSI criteria. Overall agreement between assays was 89.0%-97.3 % with highly correlating results (Pearson's correlation coefficients: 0.82-0.99). Passing-Bablok regression analysis revealed systematic differences.

Discussion

EUROIMMUN ChLIAs showed good analytical performances and represent new valuable tools for diagnostics of AD.

AD plasma biomarkers are stable for an extended period at -20°C: implications for resource-constrained environments

Standard procedures for measuring Alzheimer's disease (AD) plasma biomarkers include storage at -80°C. This is challenging in countries lacking research infrastructure, such -80°C freezer. To investigate stability of AD biomarkers from plasma stored at -20°C, we compared aliquots stored at -80°C and others at -20°C for two, four, six, fifteen, and thirty-five weeks. pTau181, Aβ42, Aβ40, NfL, and GFAP were measured for each timepoint. pTau181 and Aβ42/Aβ40 ratios showed minimal variation for up to 15 weeks. NfL and GFAP had higher variability. This finding of 15-week stability at -20°C enables greater participation in AD biomarker studies in resource constrained environments.

Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions

A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.

ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images

Detection and measurement of amyloid-beta (Aβ) in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aβ cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aβ PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aβ. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aβ CSF values correlated with measured Aβ CSF values (r = 0.92; q < 0.01), SUVR (rAV45 = -0.64, rFBB = -0.69; q < 0.01) and episodic memory measures (0.33 < r < 0.44; q < 0.01). For both classifications, cerebral white matter significantly contributed to CSF prediction (q < 0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, the brain stem, subcortical areas, cortical lobes, limbic lobe and basal forebrain made more significant contributions (q < 0.01). Considering cortical grey matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aβ CSF concentration from Aβ PET scans, offering potential clinical utility for Aβ level determination.

Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

Amyloid brain-dedicated PET images can diagnose Alzheimer's pathology with Centiloid Scale

PURPOSE

To evaluate whether the Centiloid Scale may be used to diagnose Alzheimer's Disease (AD) pathology effectively with the only use of amyloid PET imaging modality from a brain-dedicated PET scanner.

METHODS

This study included 26 patients with amyloid PET images with 3 different radiotracers. All patients were acquired both on a PET/CT and a brain-dedicated PET scanner (CareMiBrain, CMB), from which 4 different reconstructions were implemented. A new pipeline was proposed and used for the PET image analysis based on the original Centiloid Scale processing pipeline, but with only PET images. The Youden's Index was employed to calculate the optimal cutoffs for diagnosis and evaluated by the AUC, accuracy, precision, and recall metrics.

RESULTS

The Centiloid Scale (CL) processing pipeline was validated with and without the use of MR images. The CL cutoffs for AD pathology diagnosis on the PET/CT and the 4 CMB reconstructions were 34.4 ± 2.2, 43.5 ± 3.5, 51.9 ± 12.5, 57.5 ± 6.8 and 41.8 ± 1.2 respectively. Overall, for these cutoffs all metrics obtained the maximum score.

CONCLUSION

The Centiloid scale applied to PET images allows for AD pathology diagnosis. The CMB scanner can be used with the Centiloid scale to automatically assist in the diagnosis of AD pathology, relieving the large burden of neurodegenerative diseases on a traditional PET/CT.

Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis

BACKGROUND

Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination.

METHODS

A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature.

RESULTS

A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]).

CONCLUSIONS

Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age.

TRIAL REGISTRATION

The study was registered in PROSPERO (ID: CRD42021288100).

Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease

Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

INTRODUCTION

White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.

METHODS

Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.

RESULTS

VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001).

DISCUSSION

Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter.

HIGHLIGHTS

Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Biomarkers for Managing Neurodegenerative Diseases

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track responses to therapy, and parse the causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD).

Association of plasma biomarkers with cognition, cognitive decline, and daily function across and within neurodegenerative diseases: Results from the Ontario Neurodegenerative Disease Research Initiative

INTRODUCTION

We investigated whether novel plasma biomarkers are associated with cognition, cognitive decline, and functional independence in activities of daily living across and within neurodegenerative diseases.

METHODS

Glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau (p-tau)181 and amyloid beta (Aβ)42/40 were measured using ultra-sensitive Simoa immunoassays in 44 healthy controls and 480 participants diagnosed with Alzheimer's disease/mild cognitive impairment (AD/MCI), Parkinson's disease (PD), frontotemporal dementia (FTD) spectrum disorders, or cerebrovascular disease (CVD).

RESULTS

GFAP, NfL, and/or p-tau181 were elevated among all diseases compared to controls, and were broadly associated with worse baseline cognitive performance, greater cognitive decline, and/or lower functional independence. While GFAP, NfL, and p-tau181 were highly predictive across diseases, p-tau181 was more specific to the AD/MCI cohort. Sparse associations were found in the FTD and CVD cohorts and for Aβ42/40 .

DISCUSSION

GFAP, NfL, and p-tau181 are valuable predictors of cognition and function across common neurodegenerative diseases, and may be useful in specialized clinics and clinical trials.

Diagnosis of Alzheimer's disease via optimized lightweight convolution-attention and structural MRI

Alzheimer's disease (AD) poses a substantial public health challenge, demanding accurate screening and diagnosis. Identifying AD in its early stages, including mild cognitive impairment (MCI) and healthy control (HC), is crucial given the global aging population. Structural magnetic resonance imaging (sMRI) is essential for understanding the brain's structural changes due to atrophy. While current deep learning networks overlook voxel long-term dependencies, vision transformers (ViT) excel at recognizing such dependencies in images, making them valuable in AD diagnosis. Our proposed method integrates convolution-attention mechanisms in transformer-based classifiers for AD brain datasets, enhancing performance without excessive computing resources. Replacing multi-head attention with lightweight multi-head self-attention (LMHSA), employing inverted residual (IRU) blocks, and introducing local feed-forward networks (LFFN) yields exceptional results. Training on AD datasets with a gradient-centralized optimizer and Adam achieves an impressive accuracy rate of 94.31% for multi-class classification, rising to 95.37% for binary classification (AD vs. HC) and 92.15% for HC vs. MCI. These outcomes surpass existing AD diagnosis approaches, showcasing the model's efficacy. Identifying key brain regions aids future clinical solutions for AD and neurodegenerative diseases. However, this study focused exclusively on the AD Neuroimaging Initiative (ADNI) cohort, emphasizing the need for a more robust, generalizable approach incorporating diverse databases beyond ADNI in future research.

Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals

BACKGROUND

The pathophysiology of Alzheimer's disease (AD) involves β -amyloid (A β ) accumulation. Early identification of individuals with abnormal β -amyloid levels is crucial, but A β quantification with positron emission tomography (PET) and cerebrospinal fluid (CSF) is invasive and expensive.

METHODS

We propose a machine learning framework using standard non-invasive (MRI, demographics, APOE, neuropsychology) measures to predict future A β -positivity in A β -negative individuals. We separately study A β -positivity defined by PET and CSF.

RESULTS

Cross-validated AUC for 4-year A β conversion prediction was 0.78 for the CSF-based and 0.68 for the PET-based A β definitions. Although not trained for the clinical status-change prediction, the CSF-based model excelled in predicting future mild cognitive impairment (MCI)/dementia conversion in cognitively normal/MCI individuals (AUCs, respectively, 0.76 and 0.89 with a separate dataset).

CONCLUSION

Standard measures have potential in detecting future A β -positivity and assessing conversion risk, even in cognitively normal individuals. The CSF-based definition led to better predictions than the PET-based definition.

Sleep disorders and Alzheimer's disease pathophysiology: The role of the Glymphatic System. A scoping review

BACKGROUND

Alzheimer's disease (AD) is highly intertwined with sleep disturbances throughout its whole natural history. Sleep consists of a major compound of the functionality of the glymphatic system, as the synchronized slow-wave activity during NREM facilitates cerebrospinal and interstitial long-distance mixing.

OBJECTIVE

The present study undertakes a scoping review of research on the involvement of the glymphatic system in AD-related sleep disturbances.

DESIGN

we searched Medline, Embase, PsychInfo and HEAL-link databases, without limitations on date and language, along with reference lists of relevant reviews and all included studies. We included in vivo, in vitro and post-mortem studies examining glymphatic implications of sleep disturbances in human populations with AD spectrum pathology. A thematic synthesis of evidence based on the extracted content was applied and presented in a narrative way.

RESULTS

In total, 70 original research articles were included and were grouped as following: a) Protein aggregation and toxicity, after sleep deprivation, along with its effects on sleep architecture, b) Glymphatic Sequalae in SDB, yielding potential glymphatic markers c) Circadian Dysregulation, d) Possible Interventions.

CONCLUSIONS

this review sought to provide insight into the role of sleep disturbances in AD pathogenesis, in the context of the glymphatic disruption.

Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

BACKGROUND

Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort.

METHODS

We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2.

FINDINGS

We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%).

INTERPRETATION

These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity.

FUNDING

None.

Cortical microstructural associations with CSF amyloid and pTau

Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.

Extracellular vesicle proteome unveils cathepsin B connection to Alzheimer's disease pathogenesis

Extracellular vesicles (EVs) are membrane vesicles that are released extracellularly and considered to be implicated in the pathogenesis of neurodegenerative diseases including Alzheimer's disease. Here, CSF EVs of 16 ATN-classified cases were subjected to quantitative proteome analysis. In these CSF EVs, levels of 11 proteins were significantly altered during the ATN stage transitions (P < 0.05 and fold-change > 2.0). These proteins were thought to be associated with Alzheimer's disease pathogenesis and represent candidate biomarkers for pathogenic stage classification. Enzyme-linked immunosorbent assay analysis of CSF and plasma EVs revealed altered levels of cathepsin B (CatB) during the ATN transition (seven ATN groups in validation set, n = 136). The CSF and plasma EV CatB levels showed a negative correlation with CSF amyloid-β42 concentrations. This proteomic landscape of CSF EVs in ATN classifications can depict the molecular framework of Alzheimer's disease progression, and CatB may be considered a promising candidate biomarker and therapeutic target in Alzheimer's disease amyloid pathology.

Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans

STUDY OBJECTIVES

Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aβ) and cognition in an African American (AA) cohort.

METHODS

In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aβ40, Aβ42, and the Aβ42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aβ and cognitive performance levels and change over time.

RESULTS

One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ± 8.51 years. 69.6% self-identified as female. SRSD was 6.4 ± 1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aβ. Associations with level and trajectory of cognitive test performance varied by measure of sleep health.

CONCLUSIONS

SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aβ, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia.

CLINICAL TRIAL INFORMATION

Not applicable.

Characteristics of very late-onset schizophrenia-like psychosis classified with the biomarkers for Alzheimer's disease: a retrospective cross-sectional study

OBJECTIVES

We aimed to investigate the association between very late-onset schizophrenia-like psychosis (VLOSLP), a schizophrenia spectrum disorder with an onset of ≥60 years, and Alzheimer's disease (AD) using biomarkers.

DESIGN

Retrospective cross-sectional study.

SETTING

Neuropsychology clinic of Osaka University Hospital in Japan.

PARTICIPANTS

Thirty-three participants were classified into three groups: eight AD biomarker-negative VLOSLP (VLOSLP-AD), nine AD biomarker-positive VLOSLP (VLOSLP+AD), and sixteen amnestic mild cognitive impairment due to AD without psychosis (aMCI-P+AD) participants.

MEASUREMENTS

Phosphorylated tau levels in the cerebrospinal fluid and 18F-Florbetapir positron emission tomography results were used as AD biomarkers. Several scales (e.g. the Mini-Mental State Examination (MMSE), Wechsler Memory Scale-Revised (WMS-R) Logical Memory (LM) I and II, and Neuropsychiatric Inventory (NPI)-plus) were conducted to assess clinical characteristics.

RESULTS

Those in both VLOSLP-AD and +AD groups scored higher than those in aMCI-P+AD in WMS-R LM I. On the other hand, VLOSLP+AD participants scored in between the other two groups in the WMS-R LM II, with only VLOSLP-AD participants scoring significantly higher than aMCI-P+AD participants. There were no significant differences in sex distribution and MMSE scores among the three groups or in the subtype of psychotic symptoms between VLOSLP-AD and +AD participants. Four VLOSLP-AD and five VLOSLP+AD participants harbored partition delusions. Delusion of theft was shown in two VLOSLP-AD patients and five VLOSLP+AD patients.

CONCLUSION

Some VLOSLP patients had AD pathology. Clinical characteristics were different between AD biomarker-positive and AD biomarker-negative VLOSLP, which may be helpful for detecting AD pathology in VLOSLP patients.

Alzheimer's Disease: Models and Molecular Mechanisms Informing Disease and Treatments

Alzheimer's Disease (AD) is a complex neurodegenerative disease resulting in progressive loss of memory, language and motor abilities caused by cortical and hippocampal degeneration. This review captures the landscape of understanding of AD pathology, diagnostics, and current therapies. Two major mechanisms direct AD pathology: (1) accumulation of amyloid β (Aβ) plaque and (2) tau-derived neurofibrillary tangles (NFT). The most common variants in the Aβ pathway in APP, PSEN1, and PSEN2 are largely responsible for early-onset AD (EOAD), while MAPT, APOE, TREM2 and ABCA7 have a modifying effect on late-onset AD (LOAD). More recent studies implicate chaperone proteins and Aβ degrading proteins in AD. Several tests, such as cognitive function, brain imaging, and cerebral spinal fluid (CSF) and blood tests, are used for AD diagnosis. Additionally, several biomarkers seem to have a unique AD specific combination of expression and could potentially be used in improved, less invasive diagnostics. In addition to genetic perturbations, environmental influences, such as altered gut microbiome signatures, affect AD. Effective AD treatments have been challenging to develop. Currently, there are several FDA approved drugs (cholinesterase inhibitors, Aß-targeting antibodies and an NMDA antagonist) that could mitigate AD rate of decline and symptoms of distress.

The Clinical Aspects of COVID and Alzheimer's Disease: A Round-Up of Where Things Stand and Are Headed

 The link between long COVID-19 and brain/cognitive impairments is concerning and may foster a worrisome worldwide emergence of novel cases of neurodegenerative diseases with aging. This review aims to update the knowledge, crosstalk, and possible intersections between the Post-COVID Syndrome (PCS) and Alzheimer's disease (AD). References included in this review were obtained from PubMed searches conducted between October 2023 and November 2023. PCS is a very heterogenous and poorly understood disease with recent evidence of a possible association with chronic diseases such as AD. However, more scientific data is required to establish the link between PCS and AD.

Alzheimer's Disease: An Attempt of Total Recall

This review is an attempt to compile existing hypotheses on the mechanisms underlying the initiation and progression of Alzheimer's disease (AD), starting from sensory impairments observed in AD and concluding with molecular events that are typically associated with the disease. These events include spreading of amyloid plaques and tangles of hyperphosphorylated tau and formation of Hirano and Biondi bodies as well as the development of oxidative stress. We have detailed the degenerative changes that occur in several neuronal populations, including the cholinergic neurons in the nucleus basalis of Meynert, the histaminergic neurons in the tuberomammillary nucleus, the serotonergic neurons in the raphe nuclei, and the noradrenergic neurons in the locus coeruleus. Furthermore, we discuss the potential role of iron accumulation in the brains of subjects with AD in the disease progression which served as a basis for the idea that iron chelation in the brain may mitigate oxidative stress and decelerate disease development. We also draw attention to possible role of sympathetic system and, more specifically, noradrenergic neurons of the superior cervical ganglion in triggering of the disease. We also explore the alternative possibility of compensatory protective changes that may occur in these neurons to support cholinergic function in the forebrain of subjects with AD.

Correlation Between Amyloid PET Imaging and Discordant Cerebrospinal Fluid Biomarkers Results in Patients with Suspected Alzheimer's Disease

BACKGROUND

Although the concordance between cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers and amyloid-PET findings is well known, there are no data regarding the concordance of amyloid-PET with inconclusive CSF values of amyloid-β (Aβ)1 - 42 and p-tau for the diagnosis of AD.

OBJECTIVE

To investigate the relationship between the amyloid-PET results with discordant AD biomarkers values in CSF (Aβ1 - 42+/p-tau-or Aβ1 - 42-/p-tau+).

METHODS

An observational retrospective study, including 62 patients with mild cognitive impairment (32/62) or dementia (30/62), suspicious of AD who had undergone a lumbar puncture to determine CSF AD biomarkers, and presented discordant values in CSF between Aβ1 - 42 and p-tau (Aβ1 - 42+/p-tau-or Aβ1 - 42-/p-tau+). All of them, underwent an amyloid-PET with 18F-Florbetaben. An extensive neuropsychological testing as part of their diagnostic process (MMSE and TMA-93), was performed, and it was also obtained the Global Deterioration Scale.

RESULTS

Comparing the discordant CSF results of each patient with the cerebral amyloid-PET results, we found that in the group with Aβ1 - 42+ and p-tau-CSF values, the amyloid-PET was positive in 51.2% and negative in 48.8% of patients, while in the group with Aβ1 - 42-and p-Tau+ CSF values, the amyloid-PET was positive in 52.6% of patients and negative in 47.4% of them. No significant association was found (p = 0.951) between the results of amyloid-PET and the two divergent groups in CSF.

CONCLUSIONS

No significant relationship was observed between the results of discordant AD biomarkers in CSF and the result of amyloid-PET. No trend in amyloid-PET results was observed in relation to CSF biomarker values.

Plasma Biomarkers of Alzheimer's Disease and Neurodegeneration According to Sociodemographic Characteristics and Chronic Health Conditions

Ultrasensitive assays have been developed which enable biomarkers of Alzheimer's disease pathology and neurodegeneration to be measured in blood. These biomarkers can aid in diagnosis, and have been used to predict risk of cognitive decline and Alzheimer's disease. The ease and cost-effectiveness of blood collections means that these biomarkers could be applied more broadly in population-based screening, however it is critical to first understand what other factors could affect blood biomarker levels. The aim of this review was to determine the extent that sociodemographic, lifestyle and health factors have been associated with blood biomarkers of Alzheimer's disease and neuropathology. Of the 32 studies included in this review, all but one measured biomarker levels in plasma, and age and sex were the most commonly investigated factors. The most consistent significant findings were a positive association between age and neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), and females had higher GFAP than men. Apolipoprotein ε4 allele carriers had lower Aβ42 and Aβ42/40 ratio. Body mass index was negatively associated with GFAP and NfL, and chronic kidney disease with higher levels of all biomarkers. Too few studies have investigated other chronic health conditions and this requires further investigation. Given the potential for plasma biomarkers to enhance Alzheimer's disease diagnosis in primary care, it is important to understand how to interpret the biomarkers in light of factors that physiologically impact blood biomarker levels. This information will be critical for the establishment of reference ranges and thus the correct interpretation of these biomarkers in clinical screening.

Advances in Alzheimer's Disease Biomarkers

Alzheimer's disease (AD) is a neurodegenerative condition characterized by gradual onset and complex pathological mechanisms. Clinically, it presents with progressive cognitive decline and behavioral impairments, making it one of the most common causes of dementia. The intricacies of its pathogenesis are not fully understood, and current treatment options are limited, with diagnosis typically occurring at intermediate to advanced stages. The development of new biomarkers offers a crucial avenue for the early diagnosis of AD and improving patient outcomes. Several biomarkers with high specificity have been identified. This article reviews biomarkers related to tau protein, β-amyloid, and blood cells to deepen our understanding of AD and emphasize the advantages and disadvantages of various biomarkers in order to explore further and mine new biomarkers for AD diagnosis.

Alzheimer's disease biomarker utilization at first referral enhances differential diagnostic precision with simultaneous exclusion of Creutzfeldt-Jakob disease

Most suspected Creutzfeldt-Jakob disease (CJD) cases are eventually diagnosed with other disorders. We assessed the utility of investigating Alzheimer's disease (AD) biomarkers and neurofilament light (NfL) in patients when CJD is suspected. The study cohort consisted of cerebrospinal fluid (CSF) samples referred for CJD biomarker screening wherein amyloid beta 1-42 (Aβ1-42), phosphorylated tau 181 (p-tau181), and total tau (t-tau) could be assessed via Elecsys immunoassays (n = 419) and NfL via enzyme-linked immunosorbent assay (ELISA; n = 161). In the non-CJD sub cohort (n = 371), 59% (219/371) had A+T- (abnormal Aβ1-42 only) and 21% (79/371) returned A+T+ (abnormal Aβ1-42 and p-tau181). In the 48 CJD subjects, a similar AD biomarker profile distribution was observed. To partially address the prevalence of likely pre-symptomatic AD, NfL was utilized to assess for neuronal damage. NfL was abnormal in 76% (25/33) of A+T- subjects 40 to 69 years of age, 80% (20/25) of whom had normal t-tau. This study reinforces AD as an important differential diagnosis of suspected CJD, highlighting that incorporating AD biomarkers and NfL at initial testing is worthwhile.

Understanding the Episodic Memory and Executive Functioning Axis Impairment in MCI Patients: A Multicenter Study in Comparison with CSF Biomarkers

BACKGROUND

This study aimed to explore the association between a verbal learning task that evaluates the potential mutual dependency between memory and executive functions (i.e., the Test of Memory Strategies, TMS) and cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarkers.

METHODS

A sample of 47 mild cognitive impairment (MCI) participants from Poland and Spain were classified according to the Erlangen Score Diagnostic Algorithm (ESA) into CSF- (n = 16) and CSF+ (n = 31) groups. Correlation analyses between TMS word-list conditions and CSF biomarkers were conducted. Additionally, an analysis of covariance was performed to define the effect on ESA classification in the sample, using as a covariable the country of origin of the participants.

RESULTS

Significant associations between the TMS-3 condition and Aβ42, t-tau, and p-tau were observed for the whole sample. In addition, the CSF- participants obtained higher cognitive performance in TMS-3 compared to the CSF+ group. This outcome persisted if the groups were based on Aβ42 scores, but not t-tau or p-tau values.

CONCLUSIONS

These findings could indicate that poor performance on verbal learning tests may be affected by executive dysfunctions. Therefore, future intervention plans focused on training executive functions would be of interest to improve the ability of MCI patients to encode and organize information.

Few-shot prediction of amyloid β accumulation from mainly unpaired data on biomarker candidates

The pair-wise observation of the input and target values obtained from the same sample is mandatory in any prediction problem. In the biomarker discovery of Alzheimer's disease (AD), however, obtaining such paired data is laborious and often avoided. Accumulation of amyloid-beta (Aβ) in the brain precedes neurodegeneration in AD, and the quantitative accumulation level may reflect disease progression in the very early phase. Nevertheless, the direct observation of Aβ is rarely paired with the observation of other biomarker candidates. To this end, we established a method that quantitatively predicts Aβ accumulation from biomarker candidates by integrating the mostly unpaired observations via a few-shot learning approach. When applied to 5xFAD mouse behavioral data, the proposed method predicted the accumulation level that conformed to the observed amount of Aβ in the samples with paired data. The results suggest that the proposed model can contribute to discovering Aβ predictability-based biomarkers.