Why do trials for Alzheimer's disease drugs keep failing? A discontinued drug perspective for 2010-2015

Olanzapine attenuates amyloid-β-induced microglia-mediated progressive neurite lesions

The accumulation of amyloid-β (Aβ) in the brain is the first pathological mechanism to initiate Alzheimer's disease (AD) pathogenesis. However, the precise role of Aβ in the disease progression remains unclear. Through decades of research, prolonged inflammation has emerged as an important core pathology in AD. Previously, a study has demonstrated the neurotoxic effect of Aβ-induced neuroinflammation in neuron-glia co-culture at 72 h. Here, we hypothesise that initial stage Aβ may trigger microglial inflammation, synergistically contributing to the progression of neurite lesions relevant to AD progression. In the present study, we aimed to determine whether olanzapine, an antipsychotic drug possessing anti-inflammatory properties, can ameliorate Aβ-induced progressive neurite lesions. Our study reports that Aβ induces neurite lesions with or without inflammatory microglial cells in vitro. More intriguingly, the present study revealed that Aβ exacerbates neurite lesions in synergy with microglia. Moreover, the time course study revealed that Aβ promotes microglia-mediated neurite lesions by eliciting the secretion of pro-inflammatory cytokines. Furthermore, our study shows that olanzapine at lower doses prevents Aβ-induced microglia-mediated progressive neurite lesions. The increase in pro-inflammatory cytokines induced by Aβ is attenuated by olanzapine administration, associated with a reduction in microglial inflammation. Finally, this study reports that microglial senescence induced by Aβ was rescued by olanzapine. Thus, our study provides the first evidence that 1 µM to 5 µM of olanzapine can effectively prevent Aβ-induced microglia-mediated progressive neurite lesions by modulating microglial inflammation. These observations reinforce the potential of targeting microglial remodelling to slow disease progression in AD.

S100A9 inhibits and redirects prion protein 89-230 fragment amyloid aggregation

Protein aggregation in the form of amyloid fibrils has long been associated with the onset and development of various amyloidoses, including Alzheimer's, Parkinson's or prion diseases. Recent studies of their fibril formation process have revealed that amyloidogenic protein cross-interactions may impact aggregation pathways and kinetic parameters, as well as the structure of the resulting aggregates. Despite a growing number of reports exploring this type of interaction, they only cover just a small number of possible amyloidogenic protein pairings. One such pair is between two neurodegeneration-associated proteins: the pro-inflammatory S100A9 and prion protein, which are known to co-localize in vivo. In this study, we examined their cross-interaction in vitro and discovered that the fibrillar form of S100A9 modulated the aggregation pathway of mouse prion protein 89-230 fragment, while non-aggregated S100A9 also significantly inhibited its primary nucleation process. These results complement previous observations of the pro-inflammatory protein's role in amyloid aggregation and highlight its potential role against neurodegenerative disorders.

Alzheimer's disease genetic pathways impact cerebrospinal fluid biomarkers and imaging endophenotypes in non-demented individuals

INTRODUCTION

Unraveling how Alzheimer's disease (AD) genetic risk is related to neuropathological heterogeneity, and whether this occurs through specific biological pathways, is a key step toward precision medicine.

METHODS

We computed pathway-specific genetic risk scores (GRSs) in non-demented individuals and investigated how AD risk variants predict cerebrospinal fluid (CSF) and imaging biomarkers reflecting AD pathology, cardiovascular, white matter integrity, and brain connectivity.

RESULTS

CSF amyloidbeta and phosphorylated tau were related to most GRSs. Inflammatory pathways were associated with cerebrovascular disease, whereas quantitative measures of white matter lesion and microstructure integrity were predicted by clearance and migration pathways. Functional connectivity alterations were related to genetic variants involved in signal transduction and synaptic communication.

DISCUSSION

This study reveals distinct genetic risk profiles in association with specific pathophysiological aspects in predementia stages of AD, unraveling the biological substrates of the heterogeneity of AD-associated endophenotypes and promoting a step forward in disease understanding and development of personalized therapies.

HIGHLIGHTS

Polygenic risk for Alzheimer's disease encompasses six biological pathways that can be quantified with pathway-specific genetic risk scores, and differentially relate to cerebrospinal fluid and imaging biomarkers. Inflammatory pathways are mostly related to cerebrovascular burden. White matter health is associated with pathways of clearance and membrane integrity, whereas functional connectivity measures are related to signal transduction and synaptic communication pathways.

Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease

Background

Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored.

Methods

The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses.

Results

Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development.

Conclusion

To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.

Dynamic microglia alterations associate with hippocampal network impairments: A turning point in amyloid pathology progression

Alzheimer's disease is a progressive neurological disorder causing memory loss and cognitive decline. The underlying causes of cognitive deterioration and neurodegeneration remain unclear, leading to a lack of effective strategies to prevent dementia. Recent evidence highlights the role of neuroinflammation, particularly involving microglia, in Alzheimer's disease onset and progression. Characterizing the initial phase of Alzheimer's disease can lead to the discovery of new biomarkers and therapeutic targets, facilitating timely interventions for effective treatments. We used the AppNL-G-F knock-in mouse model, which resembles the amyloid pathology and neuroinflammatory characteristics of Alzheimer's disease, to investigate the transition from a pre-plaque to an early plaque stage with a combined functional and molecular approach. Our experiments show a progressive decrease in the power of cognition-relevant hippocampal gamma oscillations during the early stage of amyloid pathology, together with a modification of fast-spiking interneuron intrinsic properties and postsynaptic input. Consistently, transcriptomic analyses revealed that these effects are accompanied by changes in synaptic function-associated pathways. Concurrently, homeostasis- and inflammatory-related microglia signature genes were downregulated. Moreover, we found a decrease in Iba1-positive microglia in the hippocampus that correlates with plaque aggregation and neuronal dysfunction. Collectively, these findings support the hypothesis that microglia play a protective role during the early stages of amyloid pathology by preventing plaque aggregation, supporting neuronal homeostasis, and overall preserving the oscillatory network's functionality. These results suggest that the early alteration of microglia dynamics could be a pivotal event in the progression of Alzheimer's disease, potentially triggering plaque deposition, impairment of fast-spiking interneurons, and the breakdown of the oscillatory circuitry in the hippocampus.

CCADD: An online webserver for Alzheimer's disease detection from brain MRI

Alzheimer's disease (AD) imposes a growing burden on public health due to its impact on memory, cognition, behavior, and social skills. Early detection using non-invasive brain magnetic resonance images (MRI) is vital for disease management. We introduce CCADD (Corpus Callosum-based Alzheimer's Disease Detection), a user-friendly webserver that automatically identifies and segments the corpus callosum (CC) region from brain MRI slices. Extracted shape and size-based features of CC are fed into Support Vector Machines (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) classifiers to predict AD or Mild Cognitive Impairment (MCI). Exhaustive benchmarking on ADNI data reveals high prediction accuracies for different AD severity levels. CCADD empowers clinicians and researchers for AD detection. This server is available at: http://www.hpppi.iicb.res.in/add.

Pharmacoepidemiology evaluation of bumetanide as a potential candidate for drug repurposing for Alzheimer's disease

INTRODUCTION

Bumetanide, a loop diuretic, was identified as a candidate drug for repurposing for Alzheimer's disease (AD) based on its effects on transcriptomic apolipoprotein E signatures. Cross-sectional analyses of electronic health records suggest that bumetanide is associated with decreased prevalence of AD; however, temporality between bumetanide exposure and AD development has not been established.

METHODS

We evaluated Medicare claims data using Cox proportional hazards regression to evaluate the association between time-dependent use of bumetanide and time to first AD diagnosis while controlling for patient characteristics. Multiple sensitivity analyses were conducted to test the robustness of the findings.

RESULTS

We sampled 833,561 Medicare beneficiaries, 60.8% female, with mean (standard deviation) age of 70.4 (12). Bumetanide use was not significantly associated with AD risk (hazard ratio 1.05; 95% confidence interval, 0.99-1.10).

DISCUSSION

Using a nationwide dataset and a retrospective cohort study design, we were not able to identify a time-dependent effect of bumetanide lowering AD risk.

HIGHLIGHTS

Bumetanide was identified as a candidate for repurposing for Alzheimer's disease (AD). We evaluated the association between bumetanide use and risk of AD. We used Medicare data and accounted for duration of bumetanide use. Bumetanide use was not significantly associated with risk of AD.

Engineered Antibodies to Improve Efficacy against Neurodegenerative Disorders

Antibodies that can selectively remove rogue proteins in the brain are an obvious choice to treat neurodegenerative disorders (NDs), but after decades of efforts, only two antibodies to treat Alzheimer's disease are approved, dozens are in the testing phase, and one was withdrawn, and the other halted, likely due to efficacy issues. However, these outcomes should have been evident since these antibodies cannot enter the brain sufficiently due to the blood-brain barrier (BBB) protectant. However, all products can be rejuvenated by binding them with transferrin, preferably as smaller fragments. This model can be tested quickly and at a low cost and should be applied to bapineuzumab, solanezumab, crenezumab, gantenerumab, aducanumab, lecanemab, donanemab, cinpanemab, and gantenerumab, and their fragments. This paper demonstrates that conjugating with transferrin does not alter the binding to brain proteins such as amyloid-β (Aβ) and α-synuclein. We also present a selection of conjugate designs that will allow cleavage upon entering the brain to prevent their exocytosis while keeping the fragments connected to enable optimal binding to proteins. The identified products can be readily tested and returned to patients with the lowest regulatory cost and delays. These engineered antibodies can be manufactured by recombinant engineering, preferably by mRNA technology, as a more affordable solution to meet the dire need to treat neurodegenerative disorders effectively.

Identification of Prodromal Parkinson Disease: We May Be Able to But Should We?

Parkinson disease (PD) remains a progressive and incurable disease. Research over the past decade provides strong evidence of a detectible phase before the clinical diagnosis, known as the prodromal phase of PD (pPD). In this article, we review the debate about disclosure of risk of progression to PD and related disorders to individuals through the perspectives of the pillars of medical ethics: beneficence, nonmaleficence, autonomy, and justice. There is evidence that lifestyle modification may have positive effects on onset and progression of PD, providing justification of potential benefit. From a societal perspective, a diagnosis of pPD could allow targeted recruitment to disease-modifying trials. Regarding nonmaleficence, direct evidence that catastrophic reactions are scarce is largely derived from studies of monogenic conditions, which may not be generalizable. Diagnosis of PD can be traumatic, and appropriate communication and evaluation of circumstances to weigh up disclosure is crucial. Future research should therefore examine the potential harms of early and of false-positive diagnoses and specifically examine these matters in diverse populations. Autonomy balances the right to know and the right not to know, so an individualized patient-centered approach and shared decision-making is essential, acknowledging that knowledge of being in the prodromal phase could prolong autonomy in the longer term. Distributive justice brings focus toward health care and related planning at the individual and societal level and affects the search for disease modification in PD. We must acknowledge that waiting for established disease states is likely to be too little, too late and results in failures of expensive trials and wasted participant and researcher effort. Ultimately, clinicians must arrive at a decision with the patient that solicits and integrates patients' goals, taking into account their individual life circumstances, perspectives, and philosophies, recognizing that one size cannot fit all.

Measuring the replicability of our own research

In the study of transgenic mouse models of neurodevelopmental and neurodegenerative disorders, we use batteries of tests to measure deficits in behaviour and from the results of these tests, we make inferences about the mental states of the mice that we interpret as deficits in "learning", "memory", "anxiety", "depression", etc. This paper discusses the problems of determining whether a particular transgenic mouse is a valid mouse model of disease X, the problem of background strains, and the question of whether our behavioural tests are measuring what we say they are. The problem of the reliability of results is then discussed: are they replicable between labs and can we replicate our results in our own lab? This involves the study of intra- and inter- experimenter reliability. The variables that influence replicability and the importance of conducting a complete behavioural phenotype: sensory, motor, cognitive and social emotional behaviour are discussed. Then the thorny question of failure to replicate is examined: Is it a curse or a blessing? Finally, the role of failure in research and what it tells us about our research paradigms is examined.

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank

BACKGROUND

Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts.

METHODS

This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates.

RESULTS

A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels.

CONCLUSIONS

These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses

INTRODUCTION

Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level.

METHODS

We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample).

RESULTS

People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; β's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline.

DISCUSSION

Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.

Improved intraindividual variability in cognitive performance following cognitive and exercise training in older adults

OBJECTIVE

Increased intraindividual variability (IIV) of cognitive performance is a marker of cognitive decline in older adults. Whether computerized cognitive training (CCT) and aerobic exercise counteracts cognitive decline by reducing IIV is unknown. We investigated the effects of CCT with or without aerobic exercise on IIV in older adults.

METHODS

This was a secondary analysis of an 8-week randomized controlled trial. Older adults (aged 65-85 years) were randomized to CCT alone (n = 41), CCT with aerobic exercise (n = 41), or an active control group (n = 42). The CCT group trained using the Fit Brains® platform 3×/week for 1 hr (plus 3×/week of home-based training). The CCT with aerobic exercise group received 15 min of walking plus 45 min of Fit Brains® 3×/week (plus 3×/week of home-based training). The control group received sham exercise and cognitive training (3×/week for 1 hr). We computed reaction time IIV from the Dimensional Change Card Sort Test, Flanker Inhibitory Control and Attention Test (Flanker), and Pattern Comparison Processing Speed Test (PACPS).

RESULTS

Compared with the control group, IIV reduced in a processing speed task (PACPS) following CCT alone (mean difference [95% confidence interval]: -0.144 [-0.255 to -0.034], p < 0.01) and CCT with aerobic exercise (-0.113 [-0.225 to -0.001], p < 0.05). Attention (Flanker congruent) IIV was reduced only after CCT with aerobic exercise (-0.130 [-0.242 to -0.017], p < 0.05).

CONCLUSIONS

A CCT program promoted cognitive health via reductions in IIV of cognitive performance and combining it with aerobic exercise may result in broader benefits.

Nanotechnology-based delivery of therapeutics through the intranasal pathway and the blood-brain barrier for Alzheimer's disease treatment

Background: drugs for Alzheimer's disease (AD) fail to exhibit efficacy in clinical trials for a number of reasons, a major one being blood-brain barrier (BBB) permeability. Meanwhile, the increasing incidence of this disease emphasizes the need for effective therapeutics. Herein, we discuss novel nanoplatform technologies developed for the effective delivery of AD drugs by traversing the BBB. Main text: the interfacial and surface chemistry of nanomaterials is utilized in several industries, including pharmaceutical, and has drawn considerable attention in the field of nanotechnology. Various reports have suggested the potential of nanotechnology for AD treatment, describing unique drug carriers that improve drug stability and solubility while maintaining therapeutic dosages. These nanotechnologies are harnessed for the transport of drugs across the BBB, with or without surface modifications. We also discuss the transfer of drugs via the nose-to-brain pathway, as intranasal delivery enables direct drug distribution in the brain. In addition, nanomaterial modifications that prolong drug delivery and improve safety following intranasal administration are addressed. Conclusion: although several studies have yielded promising results, limited efforts have been undertaken to translate research findings into clinical contexts. Nevertheless, nanomaterials hold considerable potential for the development of novel effective therapeutic solutions against AD.

Restoring cellular copper homeostasis in Alzheimer disease: a novel peptide shuttle is internalized by an ATP-dependent endocytosis pathway involving Rab5- and Rab14-endosomes

CPPs, or Cell-Penetrating Peptides, offer invaluable utility in disease treatment due to their ability to transport various therapeutic molecules across cellular membranes. Their unique characteristics, such as biocompatibility and low immunogenicity, make them ideal candidates for delivering drugs, genes, or imaging agents directly into cells. This targeted delivery enhances treatment efficacy while minimizing systemic side effects. CPPs exhibit versatility, crossing biological barriers and reaching intracellular targets that conventional drugs struggle to access. This capability holds promise in treating a wide array of diseases, including cancer, neurodegenerative disorders, and infectious diseases, offering a potent avenue for innovative and targeted therapies, yet their precise mechanism of cell entry is far from being fully understood. In order to correct Cu dysregulation found in various pathologies such as Alzheimer disease, we have recently conceived a peptide Cu(II) shuttle, based on the αR5W4 CPP, which, when bound to Cu(II), is able to readily enter a neurosecretory cell model, and release bioavailable Cu in cells. Furthermore, this shuttle has the capacity to protect cells in culture against oxidative stress-induced damage which occurs when Cu binds to the Aβ peptide. The aim of this study was therefore to characterize the cell entry route used by this shuttle and determine in which compartment Cu is released. Pharmacological treatments, siRNA silencing and colocalization experiments with GFP-Rab fusion proteins, indicate that the shuttle is internalized by an ATP-dependent endocytosis pathway involving both Rab5 and Rab14 endosomes route and suggest an early release of Cu from the shuttle.

Chronic evoked seizures in young pre-symptomatic APP/PS1 mice induce serotonin changes and accelerate onset of Alzheimer's disease-related neuropathology

OBJECTIVE

Hyperexcitability is intimately linked to Alzheimer's disease (AD) pathology, but the precise timing and contributions of neuronal hyperexcitability to disease progression is unclear. Seizure induction in rodent AD models can uncover new therapeutic targets. Further, investigator-evoked seizures can directly establish how hyperexcitability and AD-associated risk factors influence neuropathological hallmarks and disease course at presymptomatic stages.

METHODS

Corneal kindling is a well-characterized preclinical epilepsy model that allows for precise control of seizure history to pair to subsequent behavioral assessments. 2-3-month-old APP/PS1, PSEN2-N141I, and transgenic control male and female mice were thus sham or corneal kindled for 2 weeks. Seizure-induced changes in glia, serotonin pathway proteins, and amyloid β levels in hippocampus and prefrontal cortex were quantified.

RESULTS

APP/PS1 females were more susceptible to corneal kindling. However, regardless of sex, APP/PS1 mice experienced extensive seizure-induced mortality versus kindled Tg- controls. PSEN2-N141I mice were not negatively affected by corneal kindling. Mortality correlated with a marked downregulation of hippocampal tryptophan hydroxylase 2 and monoamine oxidase A protein expression versus controls; these changes were not detected in PSEN2-N141I mice. Kindled APP/PS1 mice also exhibited soluble amyloid β upregulation and glial reactivity without plaque deposition.

SIGNIFICANCE

Evoked convulsive seizures and neuronal hyperexcitability in pre-symptomatic APP/PS1 mice promoted premature mortality without pathological Aβ plaque deposition, whereas PSEN2-N141I mice were unaffected. Disruptions in serotonin pathway metabolism in APP/PS1 mice was associated with increased glial reactivity without Aβ plaque deposition, demonstrating that neuronal hyperexcitability in early AD causes pathological Aβ overexpression and worsens long-term outcomes through a serotonin-related mechanism.

Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

BACKGROUND

Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD.

METHODS

445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants.

FINDINGS

We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β = 0.59), but then tau burden elevated relative to spread (β = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83).

INTERPRETATION

Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design.

FUNDING

This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

The Role of Reactive Oxygen Species in Alzheimer's Disease: From Mechanism to Biomaterials Therapy

Alzheimer's disease (AD) is a chronic, insidious, and progressive neurodegenerative disease that remains a clinical challenge for society. The fully approved drug lecanemab exhibits the prospect of therapy against the pathological processes, while debatable adverse events conflict with the drug concentration required for the anticipated therapeutic effects. Reactive oxygen species (ROS) are involved in the pathological progression of AD, as has been demonstrated in much research regarding oxidative stress (OS). The contradiction between anticipated dosage and adverse event may be resolved through targeted transport by biomaterials and get therapeutic effects through pathological progression via regulation of ROS. Besides, biomaterials fix delivery issues by promoting the penetration of drugs across the blood-brain barrier (BBB), protecting the drug from peripheral degradation, and elevating bioavailability. The goal is to comprehensively understand the mechanisms of ROS in the progression of AD disease and the potential of ROS-related biomaterials in the treatment of AD. This review focuses on OS and its connection with AD and novel biomaterials in recent years against AD via OS to inspire novel biomaterial development. Revisiting these biomaterials and mechanisms associated with OS in AD via thorough investigations presents a considerable potential and bright future for improving effective interventions for AD.

Modeling sporadic Alzheimer's disease in mice by combining Apolipoprotein E4 risk gene with environmental risk factors

Introduction

Developing effective treatment for Alzheimer's disease (AD) remains a challenge. This can be partially attributed to the fact that the mouse models used in preclinical research largely replicate familial form of AD, while majority of human cases are sporadic; both forms differ widely in the onset and origin of pathology, therefore requiring specific/targeted treatments.

Methods

In this study, we aimed to model sporadic AD in mice by combining two of the many risk factors that are strongly implicated in AD: ApoE4, a major genetic risk factor, together with an inflammatory stimuli. Accordingly, we subjected ApoE4 knock in (KI) mice, expressing humanized ApoE4, to low doses of Lipopolysaccharide (LPS) injections (i.p, weekly, for 4 months).

Results

We assessed these animals for behavioral impairments at 6 months of age using Open Field, Y-maze, and Barnes Maze Test. LPS induced hypoactivity was observed in the Open Field and Y-maze test, whereas spatial learning and memory was intact. We then quantified differences in dendritic spine density, which is a strong correlate of AD. ApoE4KI mice showed a significant reduction in the number of spines after treatment with LPS, whereas there were no obvious differences in the total number of microglia and astrocytes.

Discussion

To conclude, in the current study the APoEe4 risk gene increases the vulnerability of hippocampal neurons to inflammation induced spine loss, laying a foundation for an early sporadic AD mouse model.

Investigating lysozyme amyloid fibril formation and structural variability dependence on its initial folding state under different pH conditions

Protein fibril formation and accumulation are associated with dozens of amyloidoses, including the widespread and yet-incurable Alzheimer's and Parkinson's diseases. Currently, there are still several aspects of amyloid aggregation that are not fully understood, which negatively contributes to the development of disease-altering drugs and treatments. One factor which requires a more in-depth analysis is the effect of the environment on both the initial state of amyloidogenic proteins and their aggregation process and resulting fibril characteristics. In this work, we examine how lysozyme's folding state influences its amyloid formation kinetics and resulting aggregate structural characteristics under several different pH conditions, ranging from acidic to neutral. We demonstrate that both the initial state of the protein and the solution's pH value have a significant combined effect on the variability of the resulting aggregate secondary structures, as well as their stabilities, interactions with amyloid-specific dye molecules, and self-replication properties.

A Chronic Increase in Blood-Brain Barrier Permeability Facilitates Intraneuronal Deposition of Exogenous Bloodborne Amyloid-Beta1-42 Peptide in the Brain and Leads to Alzheimer's Disease-Relevant Cognitive Changes in a Mouse Model

Background

Increased blood-brain barrier (BBB) permeability and amyloid-β (Aβ) peptides (especially Aβ1-42) (Aβ42) have been linked to Alzheimer's disease (AD) pathogenesis, but the nature of their involvement in AD-related neuropathological changes leading to cognitive changes remains poorly understood.

Objective

To test the hypothesis that chronic extravasation of bloodborne Aβ42 peptide and brain-reactive autoantibodies and their entry into the brain parenchyma via a permeable BBB contribute to AD-related pathological changes and cognitive changes in a mouse model.

Methods

The BBB was rendered chronically permeable through repeated injections of Pertussis toxin (PT), and soluble monomeric, fluorescein isothiocyanate (FITC)-labeled or unlabeled Aβ42 was injected into the tail-vein of 10-month-old male CD1 mice at designated intervals spanning ∼3 months. Acquisition of learned behaviors and long-term retention were assessed via a battery of cognitive and behavioral tests and linked to neuropathological changes.

Results

Mice injected with both PT and Aβ42 demonstrated a preferential deficit in the capacity for long-term retention and an increased susceptibility to interference in selective attention compared to mice exposed to PT or saline only. Immunohistochemical analyses revealed increased BBB permeability and entry of bloodborne Aβ42 and immunoglobulin G (IgG) into the brain parenchyma, selective neuronal binding of IgG and neuronal accumulation of Aβ42 in animals injected with both PT and Aβ42 compared to controls.

Conclusion

Results highlight the potential synergistic role of BBB compromise and the influx of bloodborne Aβ42 into the brain in both the initiation and progression of neuropathologic and cognitive changes associated with AD.

Plasma Neurofilament Light Relates to Divergent Default and Salience Network Connectivity in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia

Background

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD.

Objective

Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD.

Methods

Plasma NfL and neuroimaging data from patients with bvFTD (n = 16) and AD or mild cognitive impairment (n = 38; AD + MCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients.

RESULTS

We demonstrated divergent associations between NfL and functional connectivity in AD + MCI and bvFTD patients. Specifically, AD + MCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in AD + MCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores.

CONCLUSIONS

Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.

The Potential of a Stratified Approach to Drug Repurposing in Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurodegenerative condition that is characterized by the build-up of amyloid-beta plaques and neurofibrillary tangles. While multiple theories explaining the aetiology of the disease have been suggested, the underlying cause of the disease is still unknown. Despite this, several modifiable and non-modifiable factors that increase the risk of developing AD have been identified. To date, only eight AD drugs have ever gained regulatory approval, including six symptomatic and two disease-modifying drugs. However, not all are available in all countries and high costs associated with new disease-modifying biologics prevent large proportions of the patient population from accessing them. With the current patient population expected to triple by 2050, it is imperative that new, effective, and affordable drugs become available to patients. Traditional drug development strategies have a 99% failure rate in AD, which is far higher than in other disease areas. Even when a drug does reach the market, additional barriers such as high cost and lack of accessibility prevent patients from benefiting from them. In this review, we discuss how a stratified medicine drug repurposing approach may address some of the limitations and barriers that traditional strategies face in relation to drug development in AD. We believe that novel, stratified drug repurposing studies may expedite the discovery of alternative, effective, and more affordable treatment options for a rapidly expanding patient population in comparison with traditional drug development methods.

High-throughput target trial emulation for Alzheimer's disease drug repurposing with real-world data

Target trial emulation is the process of mimicking target randomized trials using real-world data, where effective confounding control for unbiased treatment effect estimation remains a main challenge. Although various approaches have been proposed for this challenge, a systematic evaluation is still lacking. Here we emulated trials for thousands of medications from two large-scale real-world data warehouses, covering over 10 years of clinical records for over 170 million patients, aiming to identify new indications of approved drugs for Alzheimer's disease. We assessed different propensity score models under the inverse probability of treatment weighting framework and suggested a model selection strategy for improved baseline covariate balancing. We also found that the deep learning-based propensity score model did not necessarily outperform logistic regression-based methods in covariate balancing. Finally, we highlighted five top-ranked drugs (pantoprazole, gabapentin, atorvastatin, fluticasone, and omeprazole) originally intended for other indications with potential benefits for Alzheimer's patients.

Mistranslation-associated perturbations of proteostasis do not promote accumulation of amyloid beta and plaque deposition in aged mouse brain

A common perception in age-related neurodegenerative diseases posits that a decline in proteostasis is key to the accumulation of neuropathogenic proteins, such as amyloid beta (Aβ), and the development of sporadic Alzheimer's disease (AD). To experimentally challenge the role of protein homeostasis in the accumulation of Alzheimer's associated protein Aβ and levels of associated Tau phosphorylation, we disturbed proteostasis in single APP knock-in mouse models of AD building upon Rps9 D95N, a recently identified mammalian ram mutation which confers heightened levels of error-prone translation together with an increased propensity for random protein aggregation and which is associated with accelerated aging. We crossed the Rps9 D95N mutation into knock-in mice expressing humanized Aβ with different combinations of pathogenic mutations (wild-type, NL, NL-F, NL-G-F) causing a stepwise and quantifiable allele-dependent increase in the development of Aβ accumulation, levels of phosphorylated Tau, and neuropathology. Surprisingly, the misfolding-prone environment of the Rps9 D95N ram mutation did not affect Aβ accumulation and plaque formation, nor the level of phosphorylated Tau in any of the humanized APP knock-in lines. Our findings indicate that a misfolding-prone environment induced by error-prone translation with its inherent perturbations in protein homeostasis has little impact on the accumulation of pathogenic Aβ, plaque formation and associated phosphorylated Tau.

Urine-derived cells from the aged donor for the 2D/3D modeling of neural cells via iPSCs

Human neural cell models derived from induced pluripotent stem cells (iPSCs) have been widely accepted to model various neurodegenerative diseases such as Alzheimer's disease (AD) in vitro. Although the most common sources of iPSCs are fibroblasts and peripheral blood mononuclear cells, the collection of these cells is invasive. To reduce the donor's burden, we propose the use of urine-derived cells (UDCs), which can be obtained non-invasively from a urine sample. However, the collection of UDCs from elderly donors suffering from age-related diseases such as AD has not been reported, and it is unknown whether these UDCs from the donor aged over 80 years old can be converted into iPSCs and differentiated into neural cells. In this study, we reported a case of using the UDCs from the urine sample of an 89-year-old AD patient, and the UDCs were successfully reprogrammed into iPSCs and differentiated into neural cells in four different ways: (i) the dual SMAD inhibition with small-molecules via the neural progenitor precursor stage, (ii) the rapid induction method using transient expression of Ngn2 and microRNAs without going through the neural progenitor stage, (iii) the cortical brain organoids for 3D culture, and (iv) the human astrocytes. The accumulation of phosphorylated Tau proteins, which is a pathological hallmark of AD, was examined in the neuronal models generated from the UDCs of the aged donor. The application of this cell source will broaden the target population for disease modeling using iPS technology.

Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment

Although a variety of cognitive training has been performed, its optimally personalized delivery is still unknown. This study established the mental workload classification model using a convolutional neural network based on functional near-infrared spectroscopy-derived data. The dorsolateral prefrontal cortex (DLPFC) while thirty individuals with mild cognitive impairment (MCI) performed spatial working memory testing was found to be a considerable indicator to classify 3 levels of mental workload with an accuracy of over 86%. In the next step, forty subjects with MCI were randomly allocated into the experimental group (EG) that received cognitive training with mental workload-based difficulty adjustment or the control group (CG) that received conventional cognitive training. To compare both groups, the Trail Making Test Part B (TMT-B) and hemodynamic responses in the DLPFC during the TMT-B were measured. After the 16 training sessions, the EG subjects achieved a greater improvement in the TMT-B than the CG subjects (p < 0.05). Also, the EG subject showed a significantly lower DLPFC activity during the TMT-B than the CG subject (p < 0.05). In sum, the EG subjects better performed executive function with lower energy from the DLPFC. These findings imply that the importance of mental workload monitoring to provide personalized cognitive training.

Spatial association between distributed β-amyloid and tau varies with cognition

Several PET studies have explored the relationship between β-amyloid load and tau uptake at the early stages of Alzheimer's disease (AD) progression. Most of these studies have focused on the linear relationship between β-amyloid and tau at the local level and their synergistic effect on different AD biomarkers. We hypothesize that patterns of spatial association between β-amyloid and tau might be uncovered using alternative association metrics that account for linear as well as more complex, possible nonlinear dependencies. In the present study, we propose a new Canonical Distance Correlation Analysis (CDCA) to generate distinctive spatial patterns of the cross-correlation structure between tau, as measured by [18F]flortaucipir PET, and β-amyloid, as measured by [18F]florbetapir PET, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We found that the CDCA-based β-amyloid scores were not only maximally distance-correlated to tau in cognitively normal (CN) controls and mild cognitive impairment (MCI), but also differentiated between low and high levels of β-amyloid uptake. The most distinctive spatial association pattern was characterized by a spread of β-amyloid covering large areas of the cortex and localized tau in the entorhinal cortex. More importantly, this spatial dependency varies according to cognition, which cannot be explained by the uptake differences in β-amyloid or tau between CN and MCI subjects. Hence, the CDCA-based scores might be more accurate than the amyloid or tau SUVR for the enrollment in clinical trials of those individuals on the path of cognitive deterioration.

Probing neural circuit mechanisms in Alzheimer's disease using novel technologies

The study of Alzheimer's Disease (AD) has traditionally focused on neuropathological mechanisms that has guided therapies that attenuate neuropathological features. A new direction is emerging in AD research that focuses on the progressive loss of cognitive function due to disrupted neural circuit mechanisms. Evidence from humans and animal models of AD show that dysregulated circuits initiate a cascade of pathological events that culminate in functional loss of learning, memory, and other aspects of cognition. Recent progress in single-cell, spatial, and circuit omics informs this circuit-focused approach by determining the identities, locations, and circuitry of the specific cells affected by AD. Recently developed neuroscience tools allow for precise access to cell type-specific circuitry so that their functional roles in AD-related cognitive deficits and disease progression can be tested. An integrated systems-level understanding of AD-associated neural circuit mechanisms requires new multimodal and multi-scale interrogations that longitudinally measure and/or manipulate the ensemble properties of specific molecularly-defined neuron populations first susceptible to AD. These newly developed technological and conceptual advances present new opportunities for studying and treating circuits vulnerable in AD and represent the beginning of a new era for circuit-based AD research.

Unique trans-kingdom microbiome structural and functional signatures predict cognitive decline in older adults

The prevalence of age-related cognitive disorders/dementia is increasing, and effective prevention and treatment interventions are lacking due to an incomplete understanding of aging neuropathophysiology. Emerging evidence suggests that abnormalities in gut microbiome are linked with age-related cognitive decline and getting acceptance as one of the pillars of the Geroscience hypothesis. However, the potential clinical importance of gut microbiome abnormalities in predicting the risk of cognitive decline in older adults is unclear. Till now the majority of clinical studies were done using 16S rRNA sequencing which only accounts for analyzing bacterial abundance, while lacking an understanding of other crucial microbial kingdoms, such as viruses, fungi, archaea, and the functional profiling of the microbiome community. Utilizing data and samples of older adults with mild cognitive impairment (MCI; n = 23) and cognitively healthy controls (n = 25). Our whole-genome metagenomic sequencing revealed that the gut of older adults with MCI harbors a less diverse microbiome with a specific increase in total viruses and a decrease in bacterial abundance compared with controls. The virome, bacteriome, and microbial metabolic signatures were significantly distinct in subjects with MCI versus controls. Selected bacteriome signatures show high predictive potential of cognitive dysfunction than virome signatures while combining virome and metabolic signatures with bacteriome boosts the prediction power. Altogether, the results from our pilot study indicate that trans-kingdom microbiome signatures are significantly distinct in MCI gut compared with controls and may have utility for predicting the risk of developing cognitive decline and dementia- debilitating public health problems in older adults.

Novel small molecules inhibit proteotoxicity and inflammation: Mechanistic and therapeutic implications for Alzheimer's Disease, healthspan and lifespan- Aging as a consequence of glycolysis

Inflammation drives many age-related, especially neurological, diseases, and likely mediates age-related proteotoxicity. For example, dementia due to Alzheimer's Disease (AD), cerebral vascular disease, many other neurodegenerative conditions is increasingly among the most devastating burdens on the American (and world) health system and threatens to bankrupt the American health system as the population ages unless effective treatments are developed. Dementia due to either AD or cerebral vascular disease, and plausibly many other neurodegenerative and even psychiatric conditions, is driven by increased age-related inflammation, which in turn appears to mediate Abeta and related proteotoxic processes. The functional significance of inflammation during aging is also supported by the fact that Humira, which is simply an antibody to the pro-inflammatory cytokine TNF-a, is the best-selling drug in the world by revenue. These observations led us to develop parallel high-throughput screens to discover small molecules which inhibit age-related Abeta proteotoxicity in a C. elegans model of AD AND LPS-induced microglial TNF-a. In the initial screen of 2560 compounds (Microsource Spectrum library) to delay Abeta proteotoxicity, the most protective compounds were, in order, phenylbutyrate, methicillin, and quetiapine, which belong to drug classes (HDAC inhibitors, beta lactam antibiotics, and tricyclic antipsychotics, respectably) already robustly implicated as promising to protect in neurodegenerative diseases, especially AD. RNAi and chemical screens indicated that the protective effects of HDAC inhibitors to reduce Abeta proteotoxicity are mediated by inhibition of HDAC2, also implicated in human AD, dependent on the HAT Creb binding protein (Cbp), which is also required for the protective effects of both dietary restriction and the daf-2 mutation (inactivation of IGF-1 signaling) during aging. In addition to methicillin, several other beta lactam antibiotics also delayed Abeta proteotoxicity and reduced microglial TNF-a. In addition to quetiapine, several other tricyclic antipsychotic drugs also delayed age-related Abeta proteotoxicity and increased microglial TNF-a, leading to the synthesis of a novel congener, GM310, which delays Abeta as well as Huntingtin proteotoxicity, inhibits LPS-induced mouse and human microglial and monocyte TNF-a, is highly concentrated in brain after oral delivery with no apparent toxicity, increases lifespan, and produces molecular responses highly similar to those produced by dietary restriction, including induction of Cbp inhibition of inhibitors of Cbp, and genes promoting a shift away from glycolysis and toward metabolism of alternate (e.g., lipid) substrates. GM310, as well as FDA-approved tricyclic congeners, prevented functional impairments and associated increase in TNF-a in a mouse model of stroke. Robust reduction of glycolysis by GM310 was functionally corroborated by flux analysis, and the glycolytic inhibitor 2-DG inhibited microglial TNF-a and other markers of inflammation, delayed Abeta proteotoxicity, and increased lifespan. These results support the value of phenotypic screens to discover drugs to treat age-related, especially neurological and even psychiatric diseases, including AD and stroke, and to clarify novel mechanisms driving neurodegeneration (e.g., increased microglial glycolysis drives neuroinflammation and subsequent neurotoxicity) suggesting novel treatments (selective inhibitors of microglial glycolysis).

Addressing the Chronic Pain-Early Cognitive Decline Comorbidity Among Older Adults: Protocol for the Active Brains Remote Efficacy Trial

BACKGROUND

Chronic pain and early cognitive decline, which are costly to treat and highly prevalent among older adults, commonly co-occur, exacerbate one another over time, and can accelerate the development and progression of Alzheimer disease and related dementias. We developed the first mind-body activity program (Active Brains [AB]) tailored to the needs of older adults with chronic pain and early cognitive decline. Results from our previous study strongly supported the feasibility of conducting AB remotely and provided evidence for improvements in outcomes.

OBJECTIVE

We are conducting a single-blinded, National Institutes of Health stage-2, randomized clinical trial to establish the efficacy of AB versus a time-matched and dose-matched education control (Health Enhancement Program [HEP]) in improving self-reported and objective outcomes of physical, cognitive, and emotional functions in 260 participants. The methodology described in this paper was informed by the lessons learned from the first year of the trial.

METHODS

Participants are identified and recruited through multidisciplinary clinician-referred individuals (eg, pain psychologists and geriatricians), the Rally Research platform, social media, and community partnerships. Interested participants complete eligibility screening and electronic informed consent. Baseline assessments include self-report, performance-based measures (eg, 6-min walk test) and objective measures (eg, Repeatable Battery for the Assessment of Neuropsychological Status). Participants are mailed a wrist-worn ActiGraph device (ActiGraph LLC) to passively monitor objective function (eg, steps) during the week between the baseline assessment and the beginning of the programs, which they continue to wear throughout the programs. After baseline assessments, participants are randomized to either AB or HEP and complete 8 weekly, remote, group sessions with a Massachusetts General Hospital psychologist. The AB group receives a Fitbit (Fitbit Inc) to help reinforce increased activity. Assessments are repeated after the intervention and at the 6-month follow-up. Coprimary outcomes include multimodal physical function (self-report, performance based, and objective). Secondary outcomes are cognitive function (self-report and objective), emotional function, and pain.

RESULTS

We began recruitment in July 2022 and recruited 37 participants across 4 cohorts. Of them, all (n=37, 100%) have completed the baseline assessment, 26 (70%) have completed the posttest assessment, and 9 (24%) are actively enrolled in the intervention (total dropout: n=2, 5%). In the three cohorts (26/37, 70%) that have completed the AB or HEP, 26 (100%) participants completed all 8 group sessions (including minimal makeups), and watch adherence (1937/2072, 93.48%, average across ActiGraph and Fitbit devices) has been excellent. The fourth cohort is ongoing (9/37, 24%), and we plan to complete enrollment by March 2026.

CONCLUSIONS

We aim to establish the efficacy of the AB program over a time-matched and dose-matched control in a live video-based trial and test the mechanisms through theoretically driven mediators and moderators. Findings will inform the development of a future multisite effectiveness-implementation trial.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05373745; https://classic.clinicaltrials.gov/ct2/show/NCT05373745.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47319.

Antibody-Mediated Clearance of Brain Amyloid-β: Mechanisms of Action, Effects of Natural and Monoclonal Anti-Aβ Antibodies, and Downstream Effects

Immunotherapeutic efforts to slow the clinical progression of Alzheimer's disease (AD) by lowering brain amyloid-β (Aβ) have included Aβ vaccination, intravenous immunoglobulin (IVIG) products, and anti-Aβ monoclonal antibodies. Neither Aβ vaccination nor IVIG slowed disease progression. Despite conflicting phase III results, the monoclonal antibody Aducanumab received Food and Drug Administration (FDA) approval for treatment of AD in June 2021. The only treatments unequivocally demonstrated to slow AD progression to date are the monoclonal antibodies Lecanemab and Donanemab. Lecanemab received FDA approval in January 2023 based on phase II results showing lowering of PET-detectable Aβ; phase III results released at that time indicated slowing of disease progression. Topline results released in May 2023 for Donanemab's phase III trial revealed that primary and secondary end points had been met. Antibody binding to Aβ facilitates its clearance from the brain via multiple mechanisms including promoting its microglial phagocytosis, activating complement, dissolving fibrillar Aβ, and binding of antibody-Aβ complexes to blood-brain barrier receptors. Antibody binding to Aβ in peripheral blood may also promote cerebral efflux of Aβ by a peripheral sink mechanism. According to the amyloid hypothesis, for Aβ targeting to slow AD progression, it must decrease downstream neuropathological processes including tau aggregation and phosphorylation and (possibly) inflammation and oxidative stress. This review discusses antibody-mediated mechanisms of Aβ clearance, findings in AD trials involving Aβ vaccination, IVIG, and anti-Aβ monoclonal antibodies, downstream effects reported in those trials, and approaches which might improve the Aβ-clearing ability of monoclonal antibodies.

How can we discover developable antibody-based biotherapeutics?

Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.

Early prediction of Alzheimer's disease and related dementias using real-world electronic health records

INTRODUCTION

This study aims to explore machine learning (ML) methods for early prediction of Alzheimer's disease (AD) and related dementias (ADRD) using the real-world electronic health records (EHRs).

METHODS

A total of 23,835 ADRD and 1,038,643 control patients were identified from the OneFlorida+ Research Consortium. Two ML methods were used to develop the prediction models. Both knowledge-driven and data-driven approaches were explored. Four computable phenotyping algorithms were tested.

RESULTS

The gradient boosting tree (GBT) models trained with the data-driven approach achieved the best area under the curve (AUC) scores of 0.939, 0.906, 0.884, and 0.854 for early prediction of ADRD 0, 1, 3, or 5 years before diagnosis, respectively. A number of important clinical and sociodemographic factors were identified.

DISCUSSION

We tested various settings and showed the predictive ability of using ML approaches for early prediction of ADRD with EHRs. The models can help identify high-risk individuals for early informed preventive or prognostic clinical decisions.

A dynamical systems approach for multiscale synthesis of Alzheimer's pathogenesis

Alzheimer's disease (AD) is a spatially dynamic pathology that implicates a growing volume of multiscale data spanning genetic, cellular, tissue, and organ levels of the organization. These data and bioinformatics analyses provide clear evidence for the interactions within and between these levels. The resulting heterarchy precludes a linear neuron-centric approach and necessitates that the numerous interactions are measured in a way that predicts their impact on the emergent dynamics of the disease. This level of complexity confounds intuition, and we propose a new methodology that uses non-linear dynamical systems modeling to augment intuition and that links with a community-wide participatory platform to co-create and test system-level hypotheses and interventions. In addition to enabling the integration of multiscale knowledge, key benefits include a more rapid innovation cycle and a rational process for prioritization of data campaigns. We argue that such an approach is essential to support the discovery of multilevel-coordinated polypharmaceutical interventions.

Sexual dimorphism in the peripheral metabolic homeostasis and behavior in the TgF344-AD rat model of Alzheimer's disease

Alzheimer's disease (AD), a prevalent form of dementia, is characterized by the decline of cognitive abilities with age. Available treatment options for AD are limited, making it a significant public health concern. Recent research suggests that metabolic dysfunction plays a role in the development of AD. In addition, insulin therapy has been shown to improve memory in patients with cognitive decline. In this study, we report the first examination of body composition, peripheral insulin sensitivity, and glucose tolerance in relation to behavioral assessments of learning, memory, and anxiety in the TgF344-AD rat model of AD. Results from glucose and insulin tolerance tests show that female TgF344-AD rats exhibit impaired glucose clearance and reduced insulin sensitivity at both 9 and 12 months of age, while males display no differences at 9 months and even improved glucose clearance at 12 months. Results from the Morris Water Maze assessment of learning and memory reveal that male TgF344-AD rats display impairments at both 9 and 12 months of age, while female TgF344-AD rats only show impairments at 12 months. Furthermore, results from open field and elevated plus maze tests suggest that female TgF344-AD rats display increased anxiety at 9 months of age; however, no differences were detected in males or at 12 months of age. Overall, our findings suggest that impairments in metabolism, commonly associated with type 2 diabetes, occur before or simultaneously with cognitive decline and anxiety in a sexually dimorphic manner in the TgF344-AD rat model.

Viruses - a major cause of amyloid deposition in the brain

INTRODUCTION

Clinically, Alzheimer's disease (AD) is a syndrome with a spectrum of various cognitive disorders. There is a complete dissociation between the pathology and the clinical presentation. Therefore, we need a disruptive new approach to be able to prevent and treat AD.

AREAS COVERED

In this review, the authors extensively discuss the evidence why the amyloid beta is not the pathological cause of AD which makes therefore the amyloid hypothesis not sustainable anymore. They review the experimental evidence underlying the role of microbes, especially that of viruses, as a trigger/cause for the production of amyloid beta leading to the establishment of a chronic neuroinflammation as the mediator manifesting decades later by AD as a clinical spectrum. In this context, the emergence and consequences of the infection/antimicrobial protection hypothesis are described. The epidemiological and clinical data supporting this hypothesis are also analyzed.

EXPERT OPINION

For decades, we have known that viruses are involved in the pathogenesis of AD. This discovery was ignored and discarded for a long time. Now we should accept this fact, which is not a hypothesis anymore, and stimulate the research community to come up with new ideas, new treatments, and new concepts.

Investigation of Potential Drug Targets for Cholesterol Regulation to Treat Alzheimer's Disease

Despite extensive research and seven approved drugs, the complex interplay of genes, proteins, and pathways in Alzheimer's disease remains a challenge. This implies the intricacies of the mechanism for Alzheimer's disease, which involves the interaction of hundreds of genes, proteins, and pathways. While the major hallmarks of Alzheimer's disease are the accumulation of amyloid plaques and tau protein tangles, excessive accumulation of cholesterol is reportedly correlated with Alzheimer's disease patients. In this work, protein-protein interaction analysis was conducted based upon the genes from a clinical database to identify the top protein targets with most data-indicated involvement in Alzheimer's disease, which include ABCA1, CYP46A1, BACE1, TREM2, GSK3B, and SREBP2. The reactions and pathways associated with these genes were thoroughly studied for their roles in regulating brain cholesterol biosynthesis, amyloid beta accumulation, and tau protein tangle formation. Existing clinical trials for each protein target were also investigated. The research indicated that the inhibition of SREBP2, BACE1, or GSK3B is beneficial to reduce cholesterol and amyloid beta accumulation, while the activation of ABCA1, CYP46A1, or TREM2 has similar effects. In this study, Sterol Regulatory Element-Binding Protein 2 (SREBP2) emerged as the primary protein target. SREBP2 serves a pivotal role in maintaining cholesterol balance, acting as a transcription factor that controls the expression of several enzymes pivotal for cholesterol biosynthesis. Novel studies suggest that SREBP2 performs a multifaceted role in Alzheimer's disease. The hyperactivity of SREBP2 may lead to heightened cholesterol biosynthesis, which suggested association with the pathogenesis of Alzheimer's disease. Lowering SREBP2 levels in an Alzheimer's disease mouse model results in reduced production of amyloid-beta, a major contributor to Alzheimer's disease progression. Moreover, its thoroughly analyzed crystal structure allows for computer-aided screening of potential inhibitors; SREBP2 is thus selected as a prospective drug target. While more protein targets can be added onto the list in the future, this work provides an overview of key proteins involved in the regulation of brain cholesterol biosynthesis that may be further investigated for Alzheimer's disease intervention.

Cohort profile: rationale and methods of UK Biobank repeat imaging study eye measures to study dementia

PURPOSE

The retina provides biomarkers of neuronal and vascular health that offer promising insights into cognitive ageing, mild cognitive impairment and dementia. This article described the rationale and methodology of eye and vision assessments with the aim of supporting the study of dementia in the UK Biobank Repeat Imaging study.

PARTICIPANTS

UK Biobank is a large-scale, multicentre, prospective cohort containing in-depth genetic, lifestyle, environmental and health information from half a million participants aged 40-69 enrolled in 2006-2010 across the UK. A subset (up to 60 000 participants) of the cohort will be invited to the UK Biobank Repeat Imaging Study to collect repeated brain, cardiac and abdominal MRI scans, whole-body dual-energy X-ray absorptiometry, carotid ultrasound, as well as retinal optical coherence tomography (OCT) and colour fundus photographs.

FINDINGS TO DATE

UK Biobank has helped make significant advances in understanding risk factors for many common diseases, including for dementia and cognitive decline. Ophthalmic genetic and epidemiology studies have also benefited from the unparalleled combination of very large numbers of participants, deep phenotyping and longitudinal follow-up of the cohort, with comprehensive health data linkage to disease outcomes. In addition, we have used UK Biobank data to describe the relationship between retinal structures, cognitive function and brain MRI-derived phenotypes.

FUTURE PLANS

The collection of eye-related data (eg, OCT), as part of the UK Biobank Repeat Imaging study, will take place in 2022-2028. The depth and breadth and longitudinal nature of this dataset, coupled with its open-access policy, will create a major new resource for dementia diagnostic discovery and to better understand its association with comorbid diseases. In addition, the broad and diverse data available in this study will support research into ophthalmic diseases and various other health outcomes beyond dementia.

Lycopene destabilizes preformed Aβ fibrils: Mechanistic insights from all-atom molecular dynamics simulation

The therapeutic strategy employing destabilization of the preformed Aβ fibril by various natural compounds, as studied by experimental and computational methods, has been reported significant in curing Alzheimer's disease (AD). However, lycopene (a carotenoid), from terpenes family, needs investigation for its destabilization potential of Aβ fibril. The highest antioxidant potential and ability to cross blood brain barrier makes lycopene a preferred choice as drug lead for treating AD. The current study focuses on investigating the destabilization potential and underpinning mechanism of lycopene on different polymorphic forms of Aβ fibril via Molecular Dynamics (MD) simulation. The key findings highlight binding of lycopene to the outer surface of the chain F of the fibril (2NAO). Herein G9, K16 and V18 residues were found to be involved in van der Waals with the methyl groups of the lycopene. Additionally, Y10 and F20 residues were observed to interact via π-π interactions with CC bonds of the lycopene. The surface mediated binding of lycopene to the fibril is attributed to the large size and structural rigidity of lycopene along with the bulky size of 2NAO and narrow space of fibrillar cavity. The destabilization of the fibril is evident by breakage of inherent H-bonds and hydrophobic interactions in the presence of one lycopene molecule. The lesser β-sheet content explains disorganization of the fibril and bars the higher order aggregation curbing neurotoxicity of the fibril. The higher concentration of the lycopene is not found to be linearly correlated with the extent of destabilization of the fibril. Lycopene is also observed to destabilize the other polymorphic form of Aβ fibril (2BEG), by accessing the fibrillar cavity and lowering the β-sheet content. The destabilization observed by lycopene on two major polymorphs of Aβ fibril explains its potency towards developing an effective therapeutic approach in treating AD.

Aβ1-6A2V(D) peptide, effective on Aβ aggregation, inhibits tau misfolding and protects the brain after traumatic brain injury

Alzheimer's disease (AD), the leading cause of dementia in older adults, is a double proteinopathy characterized by amyloid-β (Aβ) and tau pathology. Despite enormous efforts that have been spent in the last decades to find effective therapies, late pharmacological interventions along the course of the disease, inaccurate clinical methodologies in the enrollment of patients, and inadequate biomarkers for evaluating drug efficacy have not allowed the development of an effective therapeutic strategy. The approaches followed so far for developing drugs or antibodies focused solely on targeting Aβ or tau protein. This paper explores the potential therapeutic capacity of an all-D-isomer synthetic peptide limited to the first six amino acids of the N-terminal sequence of the A2V-mutated Aβ, Aβ1-6A2V(D), that was developed following the observation of a clinical case that provided the background for its development. We first performed an in-depth biochemical characterization documenting the capacity of Aβ1-6A2V(D) to interfere with the aggregation and stability of tau protein. To tackle Aβ1-6A2V(D) in vivo effects against a neurological decline in genetically predisposed or acquired high AD risk mice, we tested its effects in triple transgenic animals harboring human PS1(M146 V), APP(SW), and MAPT(P301L) transgenes and aged wild-type mice exposed to experimental traumatic brain injury (TBI), a recognized risk factor for AD. We found that Aβ1-6A2V(D) treatment in TBI mice improved neurological outcomes and reduced blood markers of axonal damage. Exploiting the C. elegans model as a biosensor of amyloidogenic proteins' toxicity, we observed a rescue of locomotor defects in nematodes exposed to the brain homogenates from TBI mice treated with Aβ1-6A2V(D) compared to TBI controls. By this integrated approach, we demonstrate that Aβ1-6A2V(D) not only impedes tau aggregation but also favors its degradation by tissue proteases, confirming that this peptide interferes with both Aβ and tau aggregation propensity and proteotoxicity.

Investigating the Theranostic Potential of Graphene Quantum Dots in Alzheimer's Disease

Alzheimer's disease (AD) is one of the leading causes of death worldwide, with no definitive diagnosis or known cure. The aggregation of Tau protein into neurofibrillary tangles (NFTs), which contain straight filaments (SFs) and paired helical filaments (PHFs), is a major hallmark of AD. Graphene quantum dots (GQDs) are a type of nanomaterial that combat many of the small-molecule therapeutic challenges in AD and have shown promise in similar pathologies. In this study, two sizes of GQDs, GQD7 and GQD28, were docked to various forms of Tau monomers, SFs, and PHFs. From the favorable docked poses, we simulated each system for at least 300 ns and calculated the free energies of binding. We observed a clear preference for GQD28 in the PHF6 (³⁰⁶VQIVYK³¹¹) pathological hexapeptide region of monomeric Tau, while GQD7 targeted both the PHF6 and PHF6* (²⁷⁵VQIINK²⁸⁰) pathological hexapeptide regions. In SFs, GQD28 had a high affinity for a binding site that is available in AD but not in other common tauopathies, while GQD7 behaved promiscuously. In PHFs, GQD28 interacted strongly near the protofibril interface at the putative disaggregation site for epigallocatechin-3-gallate, and GQD7 largely interacted with PHF6. Our analyses revealed several key GQD binding sites that may be used for detecting, preventing, and disassembling the Tau aggregates in AD.

Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records

The objective of this study was to investigate the potential association between the use of four frequently prescribed drug classes, namely antihypertensive drugs, statins, selective serotonin reuptake inhibitors, and proton-pump inhibitors, and the likelihood of disease progression from mild cognitive impairment (MCI) to dementia using electronic health records (EHRs). We conducted a retrospective cohort study using observational EHRs from a cohort of approximately 2 million patients seen at a large, multi-specialty urban academic medical center in New York City, USA between 2008 and 2020 to automatically emulate the randomized controlled trials. For each drug class, two exposure groups were identified based on the prescription orders documented in the EHRs following their MCI diagnosis. During follow-up, we measured drug efficacy based on the incidence of dementia and estimated the average treatment effect (ATE) of various drugs. To ensure the robustness of our findings, we confirmed the ATE estimates via bootstrapping and presented associated 95% confidence intervals (CIs). Our analysis identified 14,269 MCI patients, among whom 2501 (17.5%) progressed to dementia. Using average treatment estimation and bootstrapping confirmation, we observed that drugs including rosuvastatin (ATE = - 0.0140 [- 0.0191, - 0.0088], p value < 0.001), citalopram (ATE = - 0.1128 [- 0.125, - 0.1005], p value < 0.001), escitalopram (ATE = - 0.0560 [- 0.0615, - 0.0506], p value < 0.001), and omeprazole (ATE = - 0.0201 [- 0.0299, - 0.0103], p value < 0.001) have a statistically significant association in slowing the progression from MCI to dementia. The findings from this study support the commonly prescribed drugs in altering the progression from MCI to dementia and warrant further investigation.

Is blood-brain barrier a probable mediator of non-invasive brain stimulation effects on Alzheimer's disease?

Alzheimer's disease (AD) is a complex neurodegenerative disease with no existing treatment leading to full recovery. The blood-brain barrier (BBB) breakdown usually precedes the advent of first symptoms in AD and accompanies the progression of the disease. At the same time deliberate BBB opening may be beneficial for drug delivery in AD. Non-invasive brain stimulation (NIBS) techniques, primarily transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have shown multiple evidence of being able to alleviate symptoms of AD. Currently, TMS/tDCS mechanisms are mostly investigated in terms of their neuronal effects, while their possible non-neuronal effects, including mitigation of the BBB disruption, are less studied. We argue that studies of TMS/tDCS effects on the BBB in AD are necessary to boost the effectiveness of neuromodulation in AD. Moreover, such studies are important considering the safety issues of TMS/tDCS use in the advanced AD stages when the BBB is usually dramatically deteriorated. Here, we elucidate the evidence of NIBS-induced BBB opening and closing in various models from in vitro to humans, and highlight its importance in AD.

Preclinical trials in Alzheimer's disease: Sample size and effect size for behavioural and neuropathological outcomes in 5xFAD mice

5xFAD transgenic (TG) mice are used widely in AD preclinical trials; however, data on sample sizes are largely unaddressed. We therefore performed estimates of sample sizes and effect sizes for typical behavioural and neuropathological outcome measures in TG 5xFAD mice, based upon data from single-sex (female) groups. Group-size estimates to detect normalisation of TG body weight to WT littermate levels at 5.5m of age were N = 9-15 depending upon algorithm. However, by 1 year of age, group sizes were small (N = 1 -<6), likely reflecting the large difference between genotypes at this age. To detect normalisation of TG open-field hyperactivity to WT levels at 13-14m, group sizes were also small (N = 6-8). Cued learning in the Morris water maze (MWM) was normal in Young TG mice (5m of age). Mild deficits were noted during MWM spatial learning and memory. MWM reversal learning and memory revealed greater impairment, and groups of up to 22 TG mice were estimated to detect normalisation to WT performance. In contrast, Aged TG mice (tested between 13 and 14m) failed to complete the visual learning (non-spatial) phase of MWM learning, likely due to a failure to recognise the platform as an escape. Estimates of group size to detect normalisation of this severe impairment were small (N = 6-9, depending upon algorithm). Other cognitive tests including spontaneous and forced alternation and novel-object recognition either failed to reveal deficits in TG mice or deficits were negligible. For neuropathological outcomes, plaque load, astrocytosis and microgliosis in frontal cortex and hippocampus were quantified in TG mice aged 2m, 4m and 6m. Sample-size estimates were ≤9 to detect the equivalent of a reduction in plaque load to the level of 2m-old TG mice or the equivalent of normalisation of neuroinflammation outcomes. However, for a smaller effect size of 30%, larger groups of up to 21 mice were estimated. In light of published guidelines on preclinical trial design, these data may be used to provide provisional sample sizes and optimise preclinical trials in 5xFAD TG mice.

The oDGal Mouse: A Novel, Physiologically Relevant Rodent Model of Sporadic Alzheimer's Disease

Sporadic Alzheimer's disease (sAD) represents a serious and growing worldwide economic and healthcare burden. Almost 95% of current AD patients are associated with sAD as opposed to patients presenting with well-characterized genetic mutations that lead to AD predisposition, i.e., familial AD (fAD). Presently, the use of transgenic (Tg) animals overexpressing human versions of these causative fAD genes represents the dominant research model for AD therapeutic development. As significant differences in etiology exist between sAD and fAD, it is perhaps more appropriate to develop novel, more sAD-reminiscent experimental models that would expedite the discovery of effective therapies for the majority of AD patients. Here we present the oDGal mouse model, a novel model of sAD that displays a range of AD-like pathologies as well as multiple cognitive deficits reminiscent of AD symptomology. Hippocampal cognitive impairment and pathology were delayed with N-acetyl-cysteine (NaC) treatment, which strongly suggests that reactive oxygen species (ROS) are the drivers of downstream pathologies such as elevated amyloid beta and hyperphosphorylated tau. These features demonstrate a desired pathophenotype that distinguishes our model from current transgenic rodent AD models. A preclinical model that presents a phenotype of non-genetic AD-like pathologies and cognitive deficits would benefit the sAD field, particularly when translating therapeutics from the preclinical to the clinical phase.

Comorbidity-driven multi-modal subtype analysis in mild cognitive impairment of Alzheimer's disease

BACKGROUND

Mild cognitive impairment (MCI) is a heterogeneous condition with high individual variabilities in clinical outcomes driven by patient demographics, genetics, brain structure features, blood biomarkers, and comorbidities. Multi-modality data-driven approaches have been used to discover MCI subtypes; however, disease comorbidities have not been included as a modality though multiple diseases including hypertension are well-known risk factors for Alzheimer's disease (AD). The aim of this study was to examine MCI heterogeneity in the context of AD-related comorbidities along with other AD-relevant features and biomarkers.

METHODS

A total of 325 MCI subjects with 32 AD-relevant comorbidities and features were considered. Mixed-data clustering is applied to discover and compare MCI subtypes with and without including AD-related comorbidities. Finally, the relevance of each comorbidity-driven subtype was determined by examining their MCI to AD disease prognosis, descriptive statistics, and conversion rates.

RESULTS

We identified four (five) MCI subtypes: poor-, average-, good-, and best-AD prognosis by including comorbidities (without including comorbidities). We demonstrated that comorbidity-driven MCI subtypes differed from those identified without comorbidity information. We further demonstrated the clinical relevance of comorbidity-driven MCI subtypes. Among the four comorbidity-driven MCI subtypes there were substantial differences in the proportions of participants who reverted to normal function, remained stable, or converted to AD. The groups showed different behaviors, having significantly different MCI to AD prognosis, significantly different means for cognitive test-related and plasma features, and by the proportion of comorbidities.

CONCLUSIONS

Our study indicates that AD comorbidities should be considered along with other diverse AD-relevant characteristics to better understand MCI heterogeneity.

Uncovering heterogeneous cognitive trajectories in mild cognitive impairment: a data-driven approach

BACKGROUND

Given the complex and progressive nature of mild cognitive impairment (MCI), the ability to delineate and understand the heterogeneous cognitive trajectories is crucial for developing personalized medicine and informing trial design. The primary goals of this study were to examine whether different cognitive trajectories can be identified within subjects with MCI and, if present, to characterize each trajectory in relation to changes in all major Alzheimer's disease (AD) biomarkers over time.

METHODS

Individuals with a diagnosis of MCI at the first visit and ≥ 1 follow-up cognitive assessment were selected from the Alzheimer's Disease Neuroimaging Initiative database (n = 936; age 73 ± 8; 40% female; 16 ± 3 years of education; 50% APOE4 carriers). Based on the Alzheimer's Disease Assessment Scale-Cognitive Subscale-13 (ADAS-Cog-13) total scores from baseline up to 5 years follow-up, a non-parametric k-means longitudinal clustering method was performed to obtain clusters of individuals with similar patterns of cognitive decline. We further conducted a series of linear mixed-effects models to study the associations of cluster membership with longitudinal changes in other cognitive measures, neurodegeneration, and in vivo AD pathologies.

RESULTS

Four distinct cognitive trajectories emerged. Cluster 1 consisted of 255 individuals (27%) with a nearly non-existent rate of change in the ADAS-Cog-13 over 5 years of follow-up and a healthy-looking biomarker profile. Individuals in the cluster 2 (n = 336, 35%) and 3 (n = 240, 26%) groups showed relatively mild and moderate cognitive decline trajectories, respectively. Cluster 4, comprising about 11% of our study sample (n = 105), exhibited an aggressive cognitive decline trajectory and was characterized by a pronouncedly abnormal biomarker profile.

CONCLUSIONS

Individuals with MCI show substantial heterogeneity in cognitive decline. Our findings may potentially contribute to improved trial design and patient stratification.