A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers

The Association Between Postural Sway and Preclinical Alzheimer Disease Among Community-Dwelling Older Adults

BACKGROUND

It is unknown whether older adults with preclinical Alzheimer disease (AD) experience changes in postural sway compared with those without preclinical AD. The purpose of this study was to understand the effect of dual tasking on standing balance, or postural sway, for people with and without preclinical AD.

METHODS

A cross-sectional analysis of baseline data from a longitudinal cohort study. Participants were cognitively normal older adults with and without preclinical AD. Postural sway (path length) was tested using a force plate under standard and dual task balance conditions. Dual task cost (DTC) was calculated to examine performance change in balance conditions. Logistic regression models were used to predict preclinical AD status as a function of DTC.

RESULTS

203 participants (65 preclinical AD+) were included. DTC for path length was significantly greater for participants with preclinical AD (DTC path length mean difference 19.8, 95% CI 2.6-37.0, t(201) = 2.29, p = .024). Greater DTC was significantly associated with increased odds of having preclinical AD (adjusted odds ratio for a 20-unit increase in DTC 1.16, 95% CI 1.02-1.32).

CONCLUSIONS

Older adults with preclinical AD are more likely to demonstrate significantly greater DTC in postural sway than those without preclinical AD. Dual tasking should be integrated into balance and fall risk assessments and may inform early detection of preclinical AD.

Evaluating the Effect of Alzheimer's Disease-Related Biomarker Change in Corticobasal Syndrome and Progressive Supranuclear Palsy

OBJECTIVES

To evaluate the effect of Alzheimer's disease (AD) -related biomarker change on clinical features, brain atrophy and functional connectivity of patients with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP).

METHODS

Data from patients with a clinical diagnosis of CBS, PSP, and AD and healthy controls were obtained from the 4-R-Tauopathy Neuroimaging Initiative 1 and 2, the Alzheimer's Disease Neuroimaging Initiative, and a local cohort from the Toronto Western Hospital. Patients with CBS and PSP were divided into AD-positive (CBS/PSP-AD) and AD-negative (CBS/PSP-noAD) groups based on fluid biomarkers and amyloid PET scans. Cognitive, motor, and depression scores; AD fluid biomarkers (cerebrospinal p-tau, t-tau, and amyloid-beta, and plasma ptau-217); and neuroimaging data (amyloid PET, MRI and fMRI) were collected. Clinical features, whole-brain gray matter volume and functional networks connectivity were compared across groups.

RESULTS

Data were analyzed from 87 CBS/PSP-noAD and 23 CBS/PSP-AD, 18 AD, and 30 healthy controls. CBS/PSP-noAD showed worse performance in comparison to CBS/PSP-AD in the PSPRS [mean(SD): 34.8(15.8) vs 23.3(11.6)] and the UPDRS scores [mean(SD): 34.2(17.0) vs 21.8(13.3)]. CBS/PSP-AD demonstrated atrophy in AD signature areas and brainstem, while CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas, globus pallidus, and brainstem compared to healthy controls. The default mode network showed greatest disconnection in CBS/PSP-AD compared with CBS/PSP-no AD and controls. The thalamic network connectivity was most affected in CBS/PSP-noAD.

INTERPRETATION

AD biomarker positivity may modulate the clinical presentation of CBS/PSP, with evidence of distinctive structural and functional brain changes associated with the AD pathology/co-pathology. ANN NEUROL 2024;96:99-109.

Does resistance training in older adults lead to structural brain changes associated with a lower risk of Alzheimer's dementia? A narrative review

Dementia, particularly Alzheimer's Disease (AD), has links to several modifiable risk factors, especially physical inactivity. When considering the relationship between physcial activity and dementia risk, cognitive benefits are generally attributed to aerobic exercise, with resistance exercise (RE) receiving less attention. This review aims to address this gap by evaluating the impact of RE on brain structures and cognitive deficits associated with AD. Drawing insights from randomized controlled trials (RCTs) utilizing structural neuroimaging, the specific influence of RE on AD-affected brain structures and their correlation with cognitive function are discussed. Preliminary findings suggest that RE induces structural brain changes in older adults that could reduce the risk of AD or mitigate AD progression. Importantly, the impacts of RE appear to follow a dose-response effect, reversing pathological structural changes and improving associated cognitive functions if performed at least twice per week for at least six months, with greatest effects in those already experiencing some element of cognitive decline. While more research is eagerly awaited, this review contributes insights into the potential benefits of RE for cognitive health in the context of AD-related changes in brain structure and function.

The criteria used to rule out mild cognitive impairment impact dementia incidence rates in subjective cognitive decline

BACKGROUND

The research criteria for subjective cognitive decline (SCD) exclude mild cognitive impairment (MCI), but do not stipulate the use of specific MCI criteria. This study compared different approaches to defining (i.e., excluding) MCI during the ascertainment of SCD, focusing on the impact on dementia incidence rates in SCD.

METHODS

This cohort study utilized routine healthcare data collected in the Essex Memory Clinic from 1999 to 2023. Two different operationalizations of the SCD criteria were used to categorize the cohort into two SCD patient samples. One sample was based on local clinical practice - MCI was excluded according to the Winblad criteria (this sample was termed SCDWinblad). The other sample was created via the retrospective application of the Jak/Bondi criteria for the exclusion of MCI (termed SCDJak/Bondi). Only patients aged ≥ 55 years at baseline with ≥ 12 months follow-up were considered for inclusion. The initial clinical/demographic characteristics of the samples were compared. Rates of incident dementia were calculated for each sample, and unadjusted and Mantel-Haenszel-adjusted incidence rate ratios were calculated to compare dementia incidence between the SCD samples.

RESULTS

The Essex Memory Clinic database included 2,233 patients in total. The SCD and study eligibility criteria were used to select SCDWinblad (n = 86) and SCDJak/Bondi (n = 185) samples from the database. Median follow-up (3 years) did not differ between the two samples. The SCDJak/Bondi sample was significantly older than the SCDWinblad at first assessment (median age: 74 versus 70 years) and had poorer scores on tests of global cognition, immediate and delayed verbal recall, and category fluency. Following adjustment for age, the dementia incidence rate ratio [95% confidence interval] was 3.7 [1.5 to 9.3], indicating a significantly greater rate of progression to dementia in SCDJak/Bondi.

CONCLUSIONS

This study highlights that the approach used to ascertain SCD has important implications for both SCD phenotypes and prognosis. This underscores the importance of how MCI is operationalized within SCD studies. More broadly, the findings add to a growing body of work indicating that objective cognition should not be overlooked in SCD, and offer a potential explanation for the heterogeneity across the SCD prognostic literature.

LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer's Disease

Background

With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer's disease (AD) pathology in preclinical stages.

Objective

To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD.

Methods

We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A-) and to ATN model (A-T-N-; A+T-N-; A+T+N-/A+T+N+).

Results

Performance on the LAM-test was significantly correlated with CSF Aβ ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A- (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer's continuum, with significant differences between ATN groups.

Conclusions

Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests.

Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup

The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.

The why and how of the SynNerGe criteria of Parkinson´s disease

In pursuit of early therapeutic interventions for Parkinson's disease, the proposed SynNeurGe classification system integrates α-synuclein pathology (S), neurodegeneration evidence (N), and pathogenic gene variants (G). This approach aims to address the disease's complexity and biological diversity. It suggests categorizing patients based on the presence or absence of α-synuclein pathology in tissues or cerebrospinal fluid, neurodegeneration indicators from specific imaging techniques, and identification of pathogenic gene variants associated with Parkinson's disease. The proposed system emphasizes the future need for precision medicine and aims to facilitate both basic and clinical research toward disease-modifying therapies. However, the authors stress that initial implementation should be confined to research settings, considering ethical implications and current limitations. Prospective validation of these criteria is deemed necessary to ensure their efficacy and ethical application in clinical practice.

Functional network centrality indicates interactions between APOE4 and age across the clinical spectrum of AD

Advanced age is the most important risk factor for Alzheimer's disease (AD), and carrier-status of the Apolipoprotein E4 (APOE4) allele is the strongest known genetic risk factor. Many studies have consistently shown a link between APOE4 and synaptic dysfunction, possibly reflecting pathologically accelerated biological aging in persons at risk for AD. To test the hypothesis that distinct functional connectivity patterns characterize APOE4 carriers across the clinical spectrum of AD, we investigated 128 resting state functional Magnetic Resonance Imaging (fMRI) datasets from the Alzheimer's Disease Neuroimaging Initiative database (ADNI), representing all disease stages from cognitive normal to clinical dementia. Brain region centralities within functional networks, computed as eigenvector centrality, were tested for multivariate associations with chronological age, APOE4 carrier status and clinical stage (as well as their interactions) by partial least square analysis (PLSC). By PLSC analysis two distinct brain activity patterns could be identified, which reflected interactive effects of age, APOE4 and clinical disease stage. A first component including sensorimotor regions and parietal regions correlated with age and AD clinical stage (p < 0.001). A second component focused on medial-frontal regions and was specifically related to the interaction between age and APOE4 (p = 0.032). Our findings are consistent with earlier reports on altered network connectivity in APOE4 carriers. Results of our study highlight promise of graph-theory based network centrality to identify brain connectivity linked to genetic risk, clinical stage and age. Our data suggest the existence of brain network activity patterns that characterize APOE4 carriers across clinical stages of AD.

Differences between Alzheimer's disease and mild cognitive impairment using brain networks from magnetic resonance texture analysis

Several studies have aimed at identifying biomarkers in the initial phases of Alzheimer's disease (AD). Conversely, texture features, such as those from gray-level co-occurrence matrices (GLCMs), have highlighted important information from several types of medical images. More recently, texture-based brain networks have been shown to provide useful information in characterizing healthy individuals. However, no studies have yet explored the use of this type of network in the context of AD. This work aimed to employ texture brain networks to investigate the distinction between groups of patients with amnestic mild cognitive impairment (aMCI) and mild dementia due to AD, and a group of healthy subjects. Magnetic resonance (MR) images from the three groups acquired at two instances were used. Images were segmented and GLCM texture parameters were calculated for each region. Structural brain networks were generated using regions as nodes and the similarity among texture parameters as links, and graph theory was used to compute five network measures. An ANCOVA was performed for each network measure to assess statistical differences between groups. The thalamus showed significant differences between aMCI and AD patients for four network measures for the right hemisphere and one network measure for the left hemisphere. There were also significant differences between controls and AD patients for the left hippocampus, right superior parietal lobule, and right thalamus-one network measure each. These findings represent changes in the texture of these regions which can be associated with the cortical volume and thickness atrophies reported in the literature for AD. The texture networks showed potential to differentiate between aMCI and AD patients, as well as between controls and AD patients, offering a new tool to help understand these conditions and eventually aid early intervention and personalized treatment, thereby improving patient outcomes and advancing AD research.

Alzheimer's disease approaches - Focusing on pathology, biomarkers and clinical trial candidates

The strategy for the development of new drugs for Alzheimer's disease (AD) recognizes that an effective therapy requires early therapeutic intervention and a multifactorial approach that considers the individual initiators of AD development. Current knowledge of AD includes the understanding of pathophysiology, risk factors, biomarkers, and the evolving patterns of biomarker abnormalities. This knowledge is essential in identifying potential molecular targets for new drug development. This review summarizes promising AD drug candidates, many of which are currently in phase 2 or 3 clinical trials. New agents are classified according to the Common Alzheimer's Disease Research Ontology (CADRO). The main targets of new drugs for AD are processes related to amyloid beta and tau neurotoxicity, neurotransmission, inflammation, metabolism and bioenergetics, synaptic plasticity, and oxidative stress. These interventions are aimed at preventing disease onset and slowing or eliminating disease progression. The efficacy of pharmacotherapy may be enhanced by combining these drugs with other treatments, antioxidants, and dietary supplements. Ongoing research into AD pathophysiology, risk factors, biomarkers, and the dynamics of biomarker abnormalities may contribute to the understanding of AD and offer hope for effective therapeutic strategies in the near future.

Protocol for a double-blind placebo-controlled randomised controlled trial assessing the impact of oral semaglutide in amyloid positivity (ISAP) in community dwelling UK adults

INTRODUCTION

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), currently marketed for type 2 diabetes and obesity, may offer novel mechanisms to delay or prevent neurotoxicity associated with Alzheimer's disease (AD). The impact of semaglutide in amyloid positivity (ISAP) trial is investigating whether the GLP-1 RA semaglutide reduces accumulation in the brain of cortical tau protein and neuroinflammation in individuals with preclinical/prodromal AD.

METHODS AND ANALYSIS

ISAP is an investigator-led, randomised, double-blind, superiority trial of oral semaglutide compared with placebo. Up to 88 individuals aged ≥55 years with brain amyloid positivity as assessed by positron emission tomography (PET) or cerebrospinal fluid, and no or mild cognitive impairment, will be randomised. People with the low-affinity binding variant of the rs6971 allele of the Translocator Protein 18 kDa (TSPO) gene, which can interfere with interpreting TSPO PET scans (a measure of neuroinflammation), will be excluded.At baseline, participants undergo tau, TSPO PET and MRI scanning, and provide data on physical activity and cognition. Eligible individuals are randomised in a 1:1 ratio to once-daily oral semaglutide or placebo, starting at 3 mg and up-titrating to 14 mg over 8 weeks. They will attend safety visits and provide blood samples to measure AD biomarkers at weeks 4, 8, 26 and 39. All cognitive assessments are repeated at week 26. The last study visit will be at week 52, when all baseline measurements will be repeated. The primary end point is the 1-year change in tau PET signal.

ETHICS AND DISSEMINATION

The study was approved by the West Midlands-Edgbaston Research Ethics Committee (22/WM/0013). The results of the study will be disseminated through scientific presentations and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ISRCTN71283871.

Assessment of brain-derived extracellular vesicle enrichment for blood biomarker analysis in age-related neurodegenerative diseases: An international overview

INTRODUCTION

Brain-derived extracellular vesicles (BEVs) in blood allows for minimally-invasive investigations of central nervous system (CNS) -specific markers of age-related neurodegenerative diseases (NDDs). Polymer-based EV- and immunoprecipitation (IP)-based BEV-enrichment protocols from blood have gained popularity. We systematically investigated protocol consistency across studies, and determined CNS-specificity of proteins associated with these protocols.

METHODS

NDD articles investigating BEVs in blood using polymer-based and/or IP-based BEV enrichment protocols were systematically identified, and protocols compared. Proteins used for BEV-enrichment and/or post-enrichment were assessed for CNS- and brain-cell-type-specificity, extracellular domains (ECD+), and presence in EV-databases.

RESULTS

A total of 82.1% of studies used polymer-based (ExoQuick) EV-enrichment, and 92.3% used L1CAM for IP-based BEV-enrichment. Centrifugation times differed across studies. A total of 26.8% of 82 proteins systematically identified were CNS-specific: 50% ECD+, 77.3% were listed in EV-databases.

CONCLUSIONS

We identified protocol steps requiring standardization, and recommend additional CNS-specific proteins that can be used for BEV-enrichment or as BEV-biomarkers.

HIGHLIGHTS

Across NDDs, we identified protocols commonly used for EV/BEV enrichment from blood. We identified protocol steps showing variability that require harmonization. We assessed CNS-specificity of proteins used for BEV-enrichment or found in BEV cargo. CNS-specific EV proteins with ECD+ or without were identified. We recommend evaluation of blood-BEV enrichment using these additional ECD+ proteins.

ECAS correlation with metabolic alterations on FDG-PET imaging in ALS

Background: Cognitive impairment is observed in up to 50% of patients with amyotrophic lateral sclerosis (ALS). The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is an ALS-specific multi-domain screening tool. Few studies have examined the relationship between ECAS scores and [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) findings. Objective: To assess the relationship between ECAS scores and glucose metabolism patterns on [18F]FDG -PET images in ALS. Methods: We collected [18F]FDG-PET images from 65 patients with ALS and 39 healthy controls. ECAS scores were collected on all patients and we calculated the correlation to [18F]FDG-PET in order to investigate the potential links between cognition and glucose metabolism. Results: We observed hypometabolism in the frontal cortex, insula, and limbic system, together with hypermetabolism in the cerebellum in patients with ALS compared to controls. A lower ECAS total score was associated with lower glucose metabolism in the right orbitofrontal gyrus and higher glucose metabolism in lateral occipital, medial occipital, and cerebellar regions, among patients with ALS. Similar results, although less widespread, were observed in the analyses of ECAS ALS-specific scores. Conclusions: The metabolic patterns in [18F]FDG -PET show that changes in the glucose metabolism of corresponding areas are related to cognitive dysfunction in ALS, and can be detected using the ECAS.

Evaluation of Neurodegenerative Disorders with Amyloid-β, Tau, and Dopaminergic PET Imaging: Interpretation Pitfalls

Antiamyloid therapies for Alzheimer disease recently entered clinical practice, making imaging biomarkers for Alzheimer disease even more relevant to guiding patient management. Amyloid and tau PET are valuable tools that can provide objective evidence of Alzheimer pathophysiology in living patients and will increasingly be used to complement 18F-FDG PET in the diagnostic evaluation of cognitive impairment and dementia. Parkinsonian syndromes, also common causes of dementia, can likewise be evaluated with a PET imaging biomarker,18F-DOPA, allowing in vivo assessment of the presynaptic dopaminergic neurons. Understanding the role of these PET biomarkers will help the nuclear medicine physician contribute to the appropriate diagnosis and management of patients with cognitive impairment and dementia. To successfully evaluate brain PET examinations for neurodegenerative diseases, knowledge of the necessary protocol details for obtaining a reliable imaging study, inherent limitations for each PET radiopharmaceutical, and pitfalls in image interpretation is critical. This review will focus on underlying concepts for interpreting PET examinations, important procedural details, and guidance for avoiding potential interpretive pitfalls for amyloid, tau, and dopaminergic PET examinations.

Differential atrophy along the longitudinal hippocampal axis in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the hippocampus. Since hippocampal studies have highlighted a differential subregional regulation along its longitudinal axis, a more detailed analysis addressing subregional changes along the longitudinal hippocampal axis has the potential to provide new relevant biomarkers. This study included structural brain MRI data of 583 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cognitively normal (CN) subjects, mild cognitively impaired (MCI) subjects and AD patients were conveniently selected considering the age and sex match between clinical groups. Structural MRI acquisitions were pre-processed and analysed with a new longitudinal axis segmentation method, dividing the hippocampus in three subdivisions (anterior, intermediate, and posterior). When normalizing the volume of hippocampal sub-divisions to total hippocampus, the posterior hippocampus negatively correlates with age only in CN subjects (r = -.31). The longitudinal ratio of hippocampal atrophy (anterior sub-division divided by the posterior one) shows a significant increase with age only in CN (r = .25). Overall, in AD, the posterior hippocampus is predominantly atrophied early on. Consequently, the anterior/posterior hippocampal ratio is an AD differentiating metric at early disease stages with potential for diagnostic and prognostic applications.

p75 neurotrophin receptor modulation in mild to moderate Alzheimer disease: a randomized, placebo-controlled phase 2a trial

p75 neurotrophin receptor (p75NTR) signaling pathways substantially overlap with degenerative networks active in Alzheimer disease (AD). Modulation of p75NTR with the first-in-class small molecule LM11A-31 mitigates amyloid-induced and pathological tau-induced synaptic loss in preclinical models. Here we conducted a 26-week randomized, placebo-controlled, double-blinded phase 2a safety and exploratory endpoint trial of LM11A-31 in 242 participants with mild to moderate AD with three arms: placebo, 200 mg LM11A-31 and 400 mg LM11A-31, administered twice daily by oral capsules. This trial met its primary endpoint of safety and tolerability. Within the prespecified secondary and exploratory outcome domains (structural magnetic resonance imaging, fluorodeoxyglucose positron-emission tomography and cerebrospinal fluid biomarkers), significant drug-placebo differences were found, consistent with the hypothesis that LM11A-31 slows progression of pathophysiological features of AD; no significant effect of active treatment was observed on cognitive tests. Together, these results suggest that targeting p75NTR with LM11A-31 warrants further investigation in larger-scale clinical trials of longer duration. EU Clinical Trials registration: 2015-005263-16 ; ClinicalTrials.gov registration: NCT03069014 .

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults

Background and Objectives

Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia.

Methods

Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics.

Results

A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT.

Discussion

Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease

BACKGROUND AND PURPOSE

A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD.

METHODS

Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5).

RESULTS

Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language.

CONCLUSION

This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.

Radionuclide Imaging of the Neuroanatomical and Neurochemical Substrate of Cognitive Decline in Parkinson's Disease

Cognitive impairment is a frequent manifestation of Parkinson's disease (PD), resulting in decrease in patients' quality of life and increased societal and economic burden. However, cognitive decline in PD is highly heterogenous and the mechanisms are poorly understood. Radionuclide imaging techniques like positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been used to investigate the neurochemical and neuroanatomical substrate of cognitive decline in PD. These techniques allow the assessment of different neurotransmitter systems, changes in brain glucose metabolism, proteinopathy, and neuroinflammation in vivo in PD patients. Here, we review current radionuclide imaging research on cognitive deficit in PD with a focus on predicting accelerating cognitive decline. This research could assist in the development of prognostic biomarkers for patient stratification and have utility in the development of ameliorative or disease-modifying therapies targeting cognitive deficit in PD.

The Miami Framework for ALS and related neurodegenerative disorders: an integrated view of phenotype and biology

Increasing appreciation of the phenotypic and biological overlap between amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, alongside evolving biomarker evidence for a pre-symptomatic stage of disease and observations that this stage of disease might not always be clinically silent, is challenging traditional views of these disorders. These advances have highlighted the need to adapt ingrained notions of these clinical syndromes to include both the full phenotypic continuum - from clinically silent, to prodromal, to clinically manifest - and the expanded phenotypic spectrum that includes ALS, frontotemporal dementia and some movement disorders. The updated clinical paradigms should also align with our understanding of the biology of these disorders, reflected in measurable biomarkers. The Miami Framework, emerging from discussions at the Second International Pre-Symptomatic ALS Workshop in Miami (February 2023; a full list of attendees and their affiliations appears in the Supplementary Information) proposes a classification system built on: first, three parallel phenotypic axes - motor neuron, frontotemporal and extrapyramidal - rather than the unitary approach of combining all phenotypic elements into a single clinical entity; and second, biomarkers that reflect different aspects of the underlying pathology and biology of neurodegeneration. This framework decouples clinical syndromes from biomarker evidence of disease and builds on experiences from other neurodegenerative diseases to offer a unified approach to specifying the pleiotropic clinical manifestations of disease and describing the trajectory of emergent biomarkers.

Exploring the significance of lipids in Alzheimer's disease and the potential of extracellular vesicles

Lipids play a significant role in maintaining central nervous system (CNS) structure and function, and the dysregulation of lipid metabolism is known to occur in many neurological disorders, including Alzheimer's disease. Here we review what is currently known about lipid dyshomeostasis in Alzheimer's disease. We propose that small extracellular vesicle (sEV) lipids may provide insight into the pathophysiology and progression of Alzheimer's disease. This stems from the recognition that sEV likely contributes to disease pathogenesis, but also an understanding that sEV can serve as a source of potential biomarkers. While the protein and RNA content of sEV in the CNS diseases have been studied extensively, our understanding of the lipidome of sEV in the CNS is still in its infancy.

Therapeutic Effects of Plant Anthocyanin against Alzheimer's Disease and Modulate Gut Health, Short-Chain Fatty Acids

Alzheimer's disease (AD) is the most common form of dementia and neurogenerative disease (NDD), and it is also one of the leading causes of death worldwide. The number of AD patients is over 55 million according to 2020 Alzheimer's Disease International (ADI), and the number is increasing drastically without any effective cure. In this review, we discuss and analyze the potential role of anthocyanins (ACNs) against AD while understanding the molecular mechanisms. ACNs have been reported as having neuroprotective effects by mitigating cognitive impairments, apoptotic markers, neuroinflammation, aberrant amyloidogenesis, and tauopathy. Taken together, ACNs could be an important therapeutic agent for combating or delaying the onset of AD.

Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network

Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitating cognitive impairment and even memory loss. Amyloid biomarkers have been extensively used in the diagnosis of AD. However, amyloid proteins offer limited information about the disease process and accurate diagnosis depends on the presence of a substantial accumulation of amyloid deposition which significantly impedes the early screening of AD. In this study, we have combined plasma proteomics with an ensemble learning model (CatBoost) to develop a cost-effective and non-invasive diagnostic method for AD. A longitudinal panel has been identified that can serve as reliable biomarkers across the entire progression of AD. Simultaneously, we have developed a neural network algorithm that utilizes plasma proteins to detect stages of Alzheimer's disease. Based on the developed longitudinal panel, the CatBoost model achieved an area under the operating curve of at least 0.90 in distinguishing mild cognitive impairment from cognitively normal. The neural network model was utilized for the detection of three stages of AD, and the results demonstrated that the neural network model exhibited an accuracy as high as 0.83, surpassing that of the traditional machine learning model.

The neutrophil to lymphocyte ratio associates with markers of Alzheimer's disease pathology in cognitively unimpaired elderly people

BACKGROUND

An elevated neutrophil-lymphocyte ratio (NLR) in blood has been associated with Alzheimer's disease (AD). However, an elevated NLR has also been implicated in many other conditions that are risk factors for AD, prompting investigation into whether the NLR is directly linked with AD pathology or a result of underlying comorbidities. Herein, we explored the relationship between the NLR and AD biomarkers in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) subjects. Adjusting for sociodemographics, APOE4, and common comorbidities, we investigated these associations in two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the M.J. de Leon CSF repository at NYU. Specifically, we examined associations between the NLR and cross-sectional measures of amyloid-β42 (Aβ42), total tau (t-tau), and phosphorylated tau181 (p-tau), as well as the trajectories of these CSF measures obtained longitudinally.

RESULTS

A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aβ-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aβ42 (β = -12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (β = 26.812, p = 0.019) and p-tau (β = 3.441, p = 0.015), but not Aβ42. In the NYU cohort alone, subjects classified as Aβ + (n = 38) displayed a stronger association between the NLR and t-tau (β = 100.476, p = 0.037) compared to Aβ- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data.

CONCLUSIONS

We report associations between the NLR and Aβ42 in the older ADNI cohort, and between the NLR and t-tau and p-tau in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.

Neurofilament Light Chain as a Biomarker of Global Cognition in Individuals With Possible Vascular Mild Cognitive Impairment

BACKGROUND

Neurofilament Light Chain (NfL) is a biomarker of axonal injury elevated in mild cognitive impairment (MCI) and Alzheimer's disease dementia. Blood NfL also inversely correlates with cognitive performance in those conditions. However, few studies have assessed NfL as a biomarker of global cognition in individuals demonstrating mild cognitive deficits who are at risk for vascular-related cognitive decline.

OBJECTIVE

To assess the relationship between blood NfL and global cognition in individuals with possible vascular MCI (vMCI) throughout cardiac rehabilitation (CR). Additionally, NfL levels were compared to age/sex-matched cognitively unimpaired (CU) controls.

METHOD

Participants with coronary artery disease (vMCI or CU) were recruited at entry to a 24-week CR program. Global cognition was measured using the Montreal Cognitive Assessment (MoCA) and plasma NfL level (pg/ml) was quantified using a highly sensitive enzyme-linked immunosorbent assay.

RESULTS

Higher plasma NfL was correlated with worse MoCA scores at baseline (β = -.352, P = .029) in 43 individuals with vMCI after adjusting for age, sex, and education. An increase in NfL was associated with worse global cognition (b[SE] = -4.81[2.06], P = .023) over time, however baseline NfL did not predict a decline in global cognition. NfL levels did not differ between the vMCI (n = 39) and CU (n = 39) groups (F(1, 76) = 1.37, P = .245).

CONCLUSION

Plasma NfL correlates with global cognition at baseline in individuals with vMCI, and is associated with decline in global cognition during CR. Our findings increase understanding of NfL and neurobiological mechanisms associated with cognitive decline in vMCI.

Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients

BACKGROUND

Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI).

METHODS

Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity.

RESULTS

Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity.

CONCLUSIONS

Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

Data-driven subtypes of mixed semantic-logopenic primary progressive aphasia: Linguistic features, biomarker profiles and brain metabolic patterns

Mixed primary progressive aphasia (mPPA) accounts for a substantial proportion of primary progressive aphasia (PPA) cases. However, the lack of a standardised definition of this condition has resulted in misclassification of PPA cases. In this study, we enrolled 55 patients diagnosed with PPA, comprising 12 semantic variant (svPPA), 23 logopenic variant (lvPPA), and 20 mPPA cases with linguistic characteristics consistent with both svPPA and lvPPA (s/lvPPA). All patients underwent language assessments, evaluation of Alzheimer's disease biomarkers (via cerebrospinal fluid analysis or Amyloid-PET), and 18F-FDG-PET brain scans. An agglomerative hierarchical clustering (AHC) analysis based on linguistic characteristics revealed two distinct clusters within the s/lvPPA group: cluster k1 (n = 10) displayed an AD-like biomarker profile, with lower levels of Aβ42 and Aβ42/Aβ40 ratio, along with higher levels of t-tau and p-tau compared to cluster k2 (n = 10). Interestingly, k1 exhibited linguistic features that were similar to those of svPPA. Both clusters exhibited extensive temporoparietal hypometabolism. These findings support the hypothesis that a subgroup of s/lvPPA may represent a clinical manifestation of AD-related PPA.

Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (β-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

Compositional structural brain signatures capture Alzheimer's genetic risk on brain structure along the disease continuum

INTRODUCTION

Traditional brain imaging genetics studies have primarily focused on how genetic factors influence the volume of specific brain regions, often neglecting the overall complexity of brain architecture and its genetic underpinnings.

METHODS

This study analyzed data from participants across the Alzheimer's disease (AD) continuum from the ALFA and ADNI studies. We exploited compositional data analysis to examine relative brain volumetric variations that (i) differentiate cognitively unimpaired (CU) individuals, defined as amyloid-negative (A-) based on CSF profiling, from those at different AD stages, and (ii) associated with increased genetic susceptibility to AD, assessed using polygenic risk scores.

RESULTS

Distinct brain signatures differentiated CU A-individuals from amyloid-positive MCI and AD. Moreover, disease stage-specific signatures were associated with higher genetic risk of AD.

DISCUSSION

The findings underscore the complex interplay between genetics and disease stages in shaping brain structure, which could inform targeted preventive strategies and interventions in preclinical AD.

Chlamydia pneumoniae in Alzheimer's disease pathology

While recent advances in diagnostics and therapeutics offer promising new approaches for Alzheimer's disease (AD) diagnosis and treatment, there is still an unmet need for an effective remedy, suggesting new avenues of research are required. Besides many plausible etiologies for AD pathogenesis, mounting evidence supports a possible role for microbial infections. Various microbes have been identified in the postmortem brain tissues of human AD patients. Among bacterial pathogens in AD, Chlamydia pneumoniae (Cp) has been well characterized in human AD brains and is a leading candidate for an infectious involvement. However, no definitive studies have been performed proving or disproving Cp's role as a causative or accelerating agent in AD pathology and cognitive decline. In this review, we discuss recent updates for the role of Cp in human AD brains as well as experimental models of AD. Furthermore, based on the current literature, we have compiled a list of potential mechanistic pathways which may connect Cp with AD pathology.

APOE ε4 is associated with decreased synaptic density in cognitively impaired participants

INTRODUCTION

We aimed to investigate the effect of apolipoprotein E4 (APOE) ε4 on synaptic density in cognitively impaired (CI) participants.

METHODS

One hundred ten CI participants underwent amyloid positron emission tomography (PET) with 18F-florbetapir and synaptic density PET with 18F-SynVesT-1. We evaluated the influence of APOE ε4 allele on synaptic density and investigated the effects of ε4 genotype on the associations of synaptic density with Alzheimer's disease (AD) biomarkers. The mediation effects of AD biomarkers on ε4-associated synaptic density loss were analyzed.

RESULTS

Compared with non-carriers, APOE ε4 allele carriers exhibited significant synaptic loss in the medial temporal lobe. Amyloid beta (Aβ) and tau pathology mediated the effects of APOE ε4 on synaptic density to different extents. The associations between synaptic density and tau pathology were regulated by the APOE ε4 genotype.

DISCUSSION

The APOE ε4 allele was associated with decreased synaptic density in CI individuals and may be driven by AD biomarkers.

Multifunctional Nanocarriers for Alzheimer's Disease: Befriending the Barriers

Neurodegenerative diseases (NDDs) have been increasing in incidence in recent years and are now widespread worldwide. Neuronal death is defined as the progressive loss of neuronal structure or function which is closely associated with NDDs and represents the intrinsic features of such disorders. Amyotrophic lateral sclerosis, frontotemporal dementia, Alzheimer's, Parkinson's, and Huntington's diseases (AD, PD, and HD, respectively) are considered neurodegenerative diseases that affect a large number of people worldwide. Despite the testing of various drugs, there is currently no available therapy that can remedy or effectively slow the progression of these diseases. Nanomedicine has the potential to revolutionize drug delivery for the management of NDDs. The use of nanoparticles (NPs) has recently been developed to improve drug delivery efficiency and is currently subjected to extensive studies. Nanoengineered particles, known as nanodrugs, can cross the blood-brain barrier while also being less invasive compared to the most treatment strategies in use. Polymeric, magnetic, carbonic, and inorganic NPs are examples of NPs that have been developed to improve drug delivery efficiency. Primary research studies using NPs to cure AD are promising, but thorough research is needed to introduce these approaches to clinical use. In the present review, we discussed the role of metal-based NPs, polymeric nanogels, nanocarrier systems such as liposomes, solid lipid NPs, polymeric NPs, exosomes, quantum dots, dendrimers, polymersomes, carbon nanotubes, and nanofibers and surfactant-based systems for the therapy of neurodegenerative diseases. In addition, we highlighted nanoformulations such as N-butyl cyanoacrylate, poly(butyl cyanoacrylate), D-penicillamine, citrate-coated peptide, magnetic iron oxide, chitosan (CS), lipoprotein, ceria, silica, metallic nanoparticles, cholinesterase inhibitors, an acetylcholinesterase inhibitors, metal chelators, anti-amyloid, protein, and peptide-loaded NPs for the treatment of AD.

Disease staging of Alzheimer's disease using a CSF-based biomarker model

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aβ42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aβ-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

The spatial extent of tauopathy on [18F]MK-6240 tau PET shows stronger association with cognitive performances than the standard uptake value ratio in Alzheimer's disease

PURPOSE

[18F]MK-6240, a second-generation tau PET tracer, is increasingly used for the detection and the quantification of in vivo cerebral tauopathy in Alzheimer's disease (AD). Given that neurological symptoms are better explained by the topography rather than by the nature of brain lesions, our study aimed to evaluate whether cognitive impairment would be more closely associated with the spatial extent than with the intensity of tau-PET signal, as measured by the standard uptake value ratio (SUVr).

METHODS

[18F]MK6240 tau-PET data from 82 participants in the AD spectrum were quantified in three different brain regions (Braak ≤ 2, Braak ≤ 4, and Braak ≤ 6) using SUVr and the extent of tauopathy (EOT, percentage of voxels with SUVr ≥ 1.3). PET data were first compared between diagnostic categories, and ROC curves were computed to evaluate sensitivity and specificity. PET data were then correlated to cognitive performances and cerebrospinal fluid (CSF) tau values.

RESULTS

The EOT in the Braak ≤ 2 region provided the highest diagnostic accuracies, distinguishing between amyloid-negative and positive clinically unimpaired individuals (threshold = 9%, sensitivity = 79%, specificity = 82%) as well as between prodromal AD and preclinical AD (threshold = 38%, sensitivity = 81%, specificity = 93%). The EOT better correlated with cognition than SUVr (∆R2 + 0.08-0.09) with the best correlation observed for EOT in the Braak ≤ 4 region (R2 = 0.64). Cognitive performances were more closely associated with PET metrics than with CSF values.

CONCLUSIONS

Quantifying [18F]MK-6240 tau PET in terms of EOT rather than SUVr significantly increases the correlation with cognitive performances. Quantification in the mesiotemporal lobe is the most useful to diagnose preclinical AD or prodromal AD.

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study

BACKGROUND

In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease.

METHODS

In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid.

FINDINGS

We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease.

INTERPRETATION

Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression.

FUNDING

None.

Utilization of fluid-based biomarkers as endpoints in disease-modifying clinical trials for Alzheimer's disease: a systematic review

BACKGROUND

Clinical trials in Alzheimer's disease (AD) had high failure rates for several reasons, including the lack of biological endpoints. Fluid-based biomarkers may present a solution to measure biologically relevant endpoints. It is currently unclear to what extent fluid-based biomarkers are applied to support drug development.

METHODS

We systematically reviewed 272 trials (clinicaltrials.gov) with disease-modifying therapies starting between 01-01-2017 and 01-01-2024 and identified which CSF and/or blood-based biomarker endpoints were used per purpose and trial type.

RESULTS

We found that 44% (N = 121) of the trials employed fluid-based biomarker endpoints among which the CSF ATN biomarkers (Aβ (42/40), p/tTau) were used most frequently. In blood, inflammatory cytokines, NFL, and pTau were most frequently employed. Blood- and CSF-based biomarkers were used approximately equally. Target engagement biomarkers were used in 26% (N = 72) of the trials, mainly in drugs targeting inflammation and amyloid. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis and, gut-brain axis targeting drugs. Positive biomarker results did not always translate to cognitive effects, most commonly the small significant reductions in CSF tau isoforms that were seen following anti-Tau treatments. On the other hand, the positive anti-amyloid trials results on cognitive function were supported by clear effect in most fluid markers.

CONCLUSIONS

As the field moves towards primary prevention, we expect an increase in the use of fluid-based biomarkers to determine disease modification. Use of blood-based biomarkers will rapidly increase, but CSF markers remain important to determine brain-specific treatment effects. With improving techniques, new biomarkers can be found to diversify the possibilities in measuring treatment effects and target engagement. It remains important to interpret biomarker results in the context of the trial and be aware of the performance of the biomarker. Diversifying biomarkers could aid in the development of surrogacy biomarkers for different drug targets.

Expression of regional brain amyloid-β deposition with [18F]Flutemetamol in Centiloid scale -a multi-site study

PURPOSE

The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL.

METHODS

Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity.

RESULTS

14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases.

CONCLUSION

The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL.

Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in Alzheimer's disease

Current diagnostic systems for Alzheimer's disease (AD) rely upon clinical signs and symptoms, despite the fact that the multiplicity of clinical symptoms renders various neuropsychological assessments inadequate to reflect the underlying pathophysiological mechanisms. Since putative neuroimaging biomarkers play a crucial role in understanding the etiology of AD, we sought to stratify the diverse relationships between AD biomarkers and cognitive decline in the aging population and uncover risk factors contributing to the diversities in AD. To do so, we capitalized on a large amount of neuroimaging data from the ADNI study to examine the inflection points along the dynamic relationship between cognitive decline trajectories and whole-brain neuroimaging biomarkers, using a state-of-the-art statistical model of change point detection. Our findings indicated that the temporal relationship between AD biomarkers and cognitive decline may differ depending on the synergistic effect of genetic risk and biological sex. Specifically, tauopathy-PET biomarkers exhibit a more dynamic and age-dependent association with Mini-Mental State Examination scores (p<0.05), with inflection points at 72, 78, and 83 years old, compared with amyloid-PET and neurodegeneration (cortical thickness from MRI) biomarkers. In the landscape of health disparities in AD, our analysis indicated that biological sex moderates the rate of cognitive decline associated with APOE4 genotype. Meanwhile, we found that higher education levels may moderate the effect of APOE4, acting as a marker of cognitive reserve.

Gut instincts: Unveiling the connection between gut microbiota and Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder marked by neuroinflammation and gradual cognitive decline. Recent research has revealed that the gut microbiota (GM) plays an important role in the pathogenesis of AD through the microbiota-gut-brain axis. However, the mechanism by which GM and microbial metabolites alter brain function is not clearly understood. GM dysbiosis increases the permeability of the intestine, alters the blood-brain barrier permeability, and elevates proinflammatory mediators causing neurodegeneration. This review article introduced us to the composition and functions of GM along with its repercussions of dysbiosis in relation to AD. We also discussed the importance of the gut-brain axis and its role in communication. Later we focused on the mechanism behind gut dysbiosis and the progression of AD including neuroinflammation, oxidative stress, and changes in neurotransmitter levels. Furthermore, we highlighted recent developments in AD management, such as microbiota-based therapy, dietary interventions like prebiotics, probiotics, and fecal microbiota transplantation. Finally, we concluded with challenges and future directions in AD research based on GM.

α-Synuclein: A Promising Biomarker for Parkinson's Disease and Related Disorders

Mutations in the SNCA gene, which encodes α-synuclein (α-syn), play a key role in the development of genetic Parkinson's disease (PD). α-Syn is a major component of Lewy bodies in PD and glial cytoplasmic inclusions in multiple system atrophy (MSA). Rapid eye movement sleep behavior disorder patients often progress to PD, dementia with Lewy bodies, or MSA, which are collectively known as α-synucleinopathies. The loss of dopaminergic neurons with Lewy bodies precedes motor dysfunction in these diseases, but the mechanisms of neurodegeneration due to α-syn aggregation are poorly understood. Monitoring α-syn aggregation in vivo could serve as a diagnostic biomarker and help elucidate pathogenesis, necessitating a simple and accurate detection method. Seed amplification assays (SAAs), such as real-time quaking-induced conversion and protein misfolding cyclic amplification, are used to detect small amounts of abnormally structured α-syn protofibrils, which are central to aggregation. These methods are promising for the early diagnosis of α-synucleinopathy. Differences in α-syn filament structures between α-synucleinopathies, as observed through transmission electron microscopy and cryo-electron microscopy, suggest their role in the pathogenesis of neurodegeneration. SAAs may differentiate between subtypes of α-synucleinopathy and other diseases. Efforts are also being made to identify α-syn from blood using various methods. This review introduces body fluid α-syn biomarkers based on pathogenic α-syn seeds, which are expected to redefine α-synucleinopathy diagnosis and staging, improving clinical research accuracy and facilitating biomarker development.

Age-related hearing loss is not linked to cerebrospinal fluid levels of β-amyloid or p-tau181

INTRODUCTION

As Hearing loss and dementia affect people with the same profile, several epidemiological studies have evaluated their relationship. However, the link between age-related hearing loss and Alzheimer's disease is still unclear.

METHODS

We selected subjects with no history of exposure to loud noises, blasts, head trauma with hearing loss, or sudden sensorineural hearing loss from a cohort intended to study preclinical phases of Alzheimer's disease. Participants are volunteers over 55 years without cognitive impairment. We correlated the results of an objective auditory evaluation with brain amyloid and p-tau181 levels and with the outcomes of a comprehensive neuropsychological assessment.

RESULTS

Fifty-five subjects at different stages of the Alzheimer's disease continuum were evaluated. There were no statistically significant correlations between amyloid-β and p-tau levels and any of the objective auditory measures. A weak but significant correlation was found between amyloid-β values and the Hearing Handicap Inventory for the Elderly. The neuropsychological domains more correlated to hearing loss were executive function and processing speed.

DISCUSSION

Age-related hearing loss is not linked to any pathological markers of Alzheimer's disease nor to neuropsychological domains typically affected in this disease. The Hearing Handicap Inventory for the Elderly has an important component of subjectivity and further studies are needed to explore its relationship with amyloid-β levels.

Cognitive and functional performance and plasma biomarkers of early Alzheimer's disease in Down syndrome

INTRODUCTION

People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials.

METHODS

This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years).

RESULTS

In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory.

DISCUSSION

Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.

Highlights

Plasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.

Personal value of Alzheimer's disease biomarker testing and result disclosure from the patient and care partner perspective

INTRODUCTION

We described patients' and care partners' experiences with Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing and result disclosure in routine care.

METHODS

IMPACT-AD BC is an observational study of clinic patients who underwent AD CSF biomarker testing as part of their routine medical care (n = 142). In the personal utility arm of the study, semi-structured phone interviews were conducted with a subset of patients (n = 34), and separately with their care partners (n = 31). Post-disclosure interviews were conducted ∼1 month and ∼6 months after biomarker result disclosure and investigated the patients' decision-making process around testing, impact of receiving results, wellness and lifestyle changes, and future planning.

RESULTS

A majority of patients (90%) rated their decision to undergo testing as "easy." Post-disclosure, the majority (82%) reported overall positive feelings from having greater certainty and the ability to plan ahead, and results spurred them to adopt/continue healthy behaviors such as exercise (84%) and cognitive activities (54%). Care partners expressed relief from having more diagnostic certainty, increased appreciation of future caregiving responsibilities, and a desire to connect with support resources.

DISCUSSION

Perspectives of persons with lived experience in dementia provide new insight into the value of biomarker testing and should be included as part of evidence-guided considerations for pre-test counseling and result disclosure. Moreover, study findings identify an interval when patients and care partners are highly receptive to positive lifestyle and medical interventions.

Efficacy and safety of repetitive Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation in memory deficits in patients with Alzheimer's disease: Meta-analysis and systematic review

Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are two of the most used non-pharmacological interventions for Alzheimer's Disease (AD). However, most of the clinical trials have focused on evaluating the effects on global cognition and not on specific cognitive functions. Therefore, considering that memory loss is one of the hallmark symptoms of AD, we aim to assess the efficacy and safety of tDCS and rTMS in memory deficits. For that, multilevel random effect models were performed considering the standardized mean difference (SMD) between active and sham stimulation. A total of 19 studies with 411 participants demonstrated positive effects in memory after tDCS (SMD=0.20, p = 0.04) and rTMS (SMD=0.44, p = 0.001). Subgroup analysis revealed that tDCS had greater efficacy when administered in temporal regions (SMD=0.32, p = 0.04), whereas rTMS was superior when applied in frontal regions (SMD=0.61, p < 0.001). Therefore, depending on the brain region of stimulation, both interventions produced a positive effect on memory symptoms in AD patients. Finally, the safety of both techniques was observed in the AD population after the reporting of almost no serious events.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.