The Role of Biomarkers in Alzheimer's Disease Drug Development

Unraveling the genetic architecture of blood unfolded p-53 among non-demented elderlies: novel candidate genes for early Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a heritable neurodegenerative disease whose long asymptomatic phase makes the early diagnosis of it pivotal. Blood U-p53 has recently emerged as a superior predictive biomarker for AD in the early stages. We hypothesized that genetic variants associated with blood U-p53 could reveal novel loci and pathways involved in the early stages of AD.

RESULTS

We performed a blood U-p53 Genome-wide association study (GWAS) on 484 healthy and mild cognitively impaired subjects from the ADNI cohort using 612,843 Single nucleotide polymorphisms (SNPs). We performed a pathway analysis and prioritized candidate genes using an AD single-cell gene program. We fine-mapped the intergenic SNPs by leveraging a cell-type-specific enhancer-to-gene linking strategy using a brain single-cell multimodal dataset. We validated the candidate genes in an independent brain single-cell RNA-seq and the ADNI blood transcriptome datasets. The rs279686 between AASS and FEZF1 genes was the most significant SNP (p-value = 4.82 × 10-7). Suggestive pathways were related to the immune and nervous systems. Twenty-three candidate genes were prioritized at 27 suggestive loci. Fine-mapping of 5 intergenic loci yielded nine cell-specific candidate genes. Finally, 15 genes were validated in the independent single-cell RNA-seq dataset, and five were validated in the ADNI blood transcriptome dataset.

CONCLUSIONS

We underlined the importance of performing a GWAS on an early-stage biomarker of AD and leveraging functional omics datasets for pinpointing causal genes in AD. Our study prioritized nine genes (SORCS1, KIF5C, TMEFF2, TMEM63C, HLA-E, ATAT1, TUBB, ARID1B, and RUNX1) strongly implicated in the early stages of AD.

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.

Genetic and epigenetic targets of natural dietary compounds as anti-Alzheimer's agents

Alzheimer's disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults. Pathogenic factors, such as oxidative stress, an increase in acetylcholinesterase activity, mitochondrial dysfunction, genotoxicity, and neuroinflammation are present in this syndrome, which leads to neurodegeneration. Neurodegenerative pathologies such as Alzheimer's disease are considered late-onset diseases caused by the complex combination of genetic, epigenetic, and environmental factors. There are two main types of Alzheimer's disease, known as familial Alzheimer's disease (onset < 65 years) and late-onset or sporadic Alzheimer's disease (onset ≥ 65 years). Patients with familial Alzheimer's disease inherit the disease due to rare mutations on the amyloid precursor protein (APP), presenilin 1 and 2 (PSEN1 and PSEN2) genes in an autosomal-dominantly fashion with closely 100% penetrance. In contrast, a different picture seems to emerge for sporadic Alzheimer's disease, which exhibits numerous non-Mendelian anomalies suggesting an epigenetic component in its etiology. Importantly, the fundamental pathophysiological mechanisms driving Alzheimer's disease are interfaced with epigenetic dysregulation. However, the dynamic nature of epigenetics seems to open up new avenues and hope in regenerative neurogenesis to improve brain repair in Alzheimer's disease or following injury or stroke in humans. In recent years, there has been an increase in interest in using natural products for the treatment of neurodegenerative illnesses such as Alzheimer's disease. Through epigenetic mechanisms, such as DNA methylation, non-coding RNAs, histone modification, and chromatin conformation regulation, natural compounds appear to exert neuroprotective effects. While we do not purport to cover every in this work, we do attempt to illustrate how various phytochemical compounds regulate the epigenetic effects of a few Alzheimer's disease-related genes.

Evolving therapeutic interventions for the management and treatment of Alzheimer's disease

Alzheimer's Disease (AD) patients experience diverse symptoms, including memory loss, cognitive impairment, behavioral abnormalities, mood changes, and mental issues. The fundamental objective of this review is to discuss novel therapeutic approaches, with special emphasis on recently approved marketed formulations for the treatment of AD, especially Aducanumab, the first FDA approved moiety that surpasses the blood-brain barrier (BBB) and reduces amyloid plaques in the brain, thereby reducing associated cognitive decline. However, it is still in the phase IV trial and is to be completed by 2030. Other drugs such as lecanemab are also under clinical trial and has recently been approved by the FDA and is also discussed here. In this review, we also focus on active and passive immunotherapy for AD as well as several vaccines, such as amyloid-beta epitope-based vaccines, amyloid-beta DNA vaccines, and stem cell therapy for AD, which are in clinical trials. Furthermore, ongoing pre-clinical trials associated with AD and other novel strategies such as curcumin-loaded nanoparticles, Crispr/ cas9, precision medicine, as well as some emerging therapies like anti-sense therapy are also highlighted. Additionally, we discuss some off-labeled drugs like non-steroidal anti-inflammatory drugs (NSAID), anti-diabetic drugs, and lithium, which can manage symptoms of AD and different non-pharmacological approaches are also covered which can help to manage AD. In summary, we have tried to cover all the therapeutic interventions which are available for the treatment and management of AD under sections approved, clinical phase, pre-clinical phase or futuristic interventions, off-labelled drugs, and non-pharmacological interventions for AD, offering positive findings and well as challenges that remain.

Alzheimer's Disease-Related Epigenetic Changes: Novel Therapeutic Targets

Aging is a significant risk factor for Alzheimer's disease (AD), although the precise mechanism and molecular basis of AD are not yet fully understood. Epigenetic mechanisms, such as DNA methylation and hydroxymethylation, mitochondrial DNA methylation, histone modifications, and non-coding RNAs (ncRNAs), play a role in regulating gene expression related to neuron plasticity and integrity, which are closely associated with learning and memory development. This review describes the impact of dynamic and reversible epigenetic modifications and factors on memory and plasticity throughout life, emphasizing their potential as target for therapeutic intervention in AD. Additionally, we present insight from postmortem and animal studies on abnormal epigenetics regulation in AD, as well as current strategies aiming at targeting these factors in the context of AD therapy.

Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease

The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. Recent accelerations in computing power and availability of big data, including electronic health records and multi-omics profiles, have converged to provide opportunities for scientific discovery and treatment development. Here, we review the potential utility of applying AI approaches to big data for discovery of disease-modifying medicines for AD/ADRD. We illustrate how AI tools can be applied to the AD/ADRD drug development pipeline through collaborative efforts among neurologists, gerontologists, geneticists, pharmacologists, medicinal chemists, and computational scientists. AI and open data science expedite drug discovery and development of disease-modifying therapeutics for AD/ADRD and other neurodegenerative diseases.

CSF protein ratios with enhanced potential to reflect Alzheimer's disease pathology and neurodegeneration

BACKGROUND

Amyloid and tau aggregates are considered to cause neurodegeneration and consequently cognitive decline in individuals with Alzheimer's disease (AD). Here, we explore the potential of cerebrospinal fluid (CSF) proteins to reflect AD pathology and cognitive decline, aiming to identify potential biomarkers for monitoring outcomes of disease-modifying therapies targeting these aggregates.

METHOD

We used a multiplex antibody-based suspension bead array to measure the levels of 49 proteins in CSF from the Swedish GEDOC memory clinic cohort at the Karolinska University Hospital. The cohort comprised 148 amyloid- and tau-negative individuals (A-T-) and 65 amyloid- and tau-positive individuals (A+T+). An independent sample set of 26 A-T- and 26 A+T+ individuals from the Amsterdam Dementia Cohort was used for validation. The measured proteins were clustered based on their correlation to CSF amyloid beta peptides, tau and NfL levels. Further, we used support vector machine modelling to identify protein pairs, matched based on their cluster origin, that reflect AD pathology and cognitive decline with improved performance compared to single proteins.

RESULTS

The protein-clustering revealed 11 proteins strongly correlated to t-tau and p-tau (tau-associated group), including mainly synaptic proteins previously found elevated in AD such as NRGN, GAP43 and SNCB. Another 16 proteins showed predominant correlation with Aβ42 (amyloid-associated group), including PTPRN2, NCAN and CHL1. Support vector machine modelling revealed that proteins from the two groups combined in pairs discriminated A-T- from A+T+ individuals with higher accuracy compared to single proteins, as well as compared to protein pairs composed of proteins originating from the same group. Moreover, combining the proteins from different groups in ratios (tau-associated protein/amyloid-associated protein) significantly increased their correlation to cognitive decline measured with cognitive scores. The results were validated in an independent cohort.

CONCLUSIONS

Combining brain-derived proteins in pairs largely enhanced their capacity to discriminate between AD pathology-affected and unaffected individuals and increased their correlation to cognitive decline, potentially due to adjustment of inter-individual variability. With these results, we highlight the potential of protein pairs to monitor neurodegeneration and thereby possibly the efficacy of AD disease-modifying therapies.

Early ultrasonic vocalization deficits and related thyroarytenoid muscle pathology in the transgenic TgF344-AD rat model of Alzheimer's disease

Background

Alzheimer's disease (AD) is a progressive neurologic disease and the most common cause of dementia. Classic pathology in AD is characterized by inflammation, abnormal presence of tau protein, and aggregation of β-amyloid that disrupt normal neuronal function and lead to cell death. Deficits in communication also occur during disease progression and significantly reduce health, well-being, and quality of life. Because clinical diagnosis occurs in the mid-stage of the disease, characterizing the prodrome and early stages in humans is currently challenging. To overcome these challenges, we use the validated TgF344-AD (F344-Tg(Prp-APP, Prp-PS1)19/Rrrc) transgenic rat model that manifests cognitive, behavioral, and neuropathological dysfunction akin to AD in humans.

Objectives

The overarching goal of our work is to test the central hypothesis that pathology and related behavioral deficits such as communication dysfunction in part manifest in the peripheral nervous system and corresponding target tissues already in the early stages. The primary aims of this study are to test the hypotheses that: (1) changes in ultrasonic vocalizations (USV) occur in the prodromal stage at 6 months of age and worsen at 9 months of age, (2) inflammation as well as AD-related pathology can be found in the thyroarytenoid muscle (TA) at 12 months of age (experimental endpoint tissue harvest), and to (3) demonstrate that the TgF344-AD rat model is an appropriate model for preclinical investigations of early AD-related vocal deficits.

Methods

USVs were collected from male TgF344-AD (N = 19) and wildtype (WT) Fischer-344 rats (N = 19) at 6 months (N = 38; WT: n = 19; TgF344-AD: n = 19) and 9 months of age (N = 18; WT: n = 10; TgF344-AD: n = 8) and acoustically analyzed for duration, mean power, principal frequency, low frequency, high frequency, peak frequency, and call type. RT-qPCR was used to assay peripheral inflammation and AD-related pathology via gene expressions in the TA muscle of male TgF344-AD rats (n = 6) and WT rats (n = 6) at 12 months of age.

Results

This study revealed a significant reduction in mean power of ultrasonic calls from 6 to 9 months of age and increased peak frequency levels over time in TgF344-AD rats compared to WT controls. Additionally, significant downregulation of AD-related genes Uqcrc2, Bace2, Serpina3n, and Igf2, as well as downregulation of pro-inflammatory gene Myd88 was found in the TA muscle of TgF344-AD rats at 12 months of age.

Discussion

Our findings demonstrate early and progressive vocal deficits in the TgF344-AD rat model. We further provide evidence of dysregulation of AD-pathology-related genes as well as inflammatory genes in the TA muscles of TgF344-AD rats in the early stage of the disease, confirming this rat model for early-stage investigations of voice deficits and related pathology.

Analysis of Resting-State Functional Magnetic Resonance Imaging in Alzheimer's Disease

Alzheimer's disease (AD) has been characterized by widespread network disconnection among brain regions, widely overlapping with the hallmarks of the disease. Functional connectivity has been studied with an upward trend in the last two decades, predominantly in AD among other neuropsychiatric disorders, and presents a potential biomarker with various features that might provide unique contributions to foster our understanding of neural mechanisms of AD. The resting-state functional MRI (rs-fMRI) is usually used to measure the blood-oxygen-level-dependent signals that reflect the brain's functional connectivity. Nevertheless, the rs-fMRI is still underutilized, which might be due to the fairly complex acquisition and analytic methodology. In this chapter, we presented the common methods that have been applied in rs-fMRI literature, focusing on the studies on individuals in the continuum of AD. The key methodological aspects will be addressed that comprise acquiring, processing, and interpreting rs-fMRI data. More, we discussed the current and potential implications of rs-fMRI in AD.

Identifying individuals with non-Alzheimer's disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer's disease

INTRODUCTION

Biomarkers remain mostly unavailable for non-Alzheimer's disease neuropathological changes (non-ADNC) such as transactive response DNA-binding protein 43 (TDP-43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA).

METHODS

A multilabel non-ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP-43, LBD, and CAA in an autopsy-confirmed cohort (N = 214).

RESULTS

A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [Aβ+] and tau+) in autopsy-confirmed participants showed accuracies of 84% for TDP-43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), Aβ and tau explained 33% to 43% of variance in cognitive decline; imputed non-ADNC explained an additional 16% to 26%. Accounting for non-ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%.

DISCUSSION

Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design.

Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer's Disease: A Multi-Database Validation Study

BACKGROUND

Pilot study showed that Alzheimer's disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia.

OBJECTIVE

The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender.

METHODS

AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance.

RESULTS

The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment.

CONCLUSIONS

AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.

Toward the right treatment at the right time: Modeling the trajectory of cognitive decline to identify the earliest age of change in people with Alzheimer's disease

Introduction

Age is the greatest risk factor for Alzheimer's disease (AD). A limitation of randomized control trials in AD is a lack of specificity in the age ranges of participants who are enrolled in studies of disease-modifying therapies. We aimed to apply Emax (i.e., maximum effect) modeling as a novel approach to identity ideal treatment windows.

Methods

Emax curves were fitted to longitudinal cognitive data of 101 participants with AD and 1392 healthy controls. We included the Mini-Mental State Examination (MMSE) and tests of verbal fluency and executive functioning.

Results

In people with AD, the earliest decline in the MMSE could be detected in the 67-71 age band while verbal fluency declined from the 41-45 age band. In healthy controls, changes in cognition showed a later trajectory of decline.

Discussion

Emax modeling could be used to design more efficient trials which has implications for randomized control trials targeting the earlier stages of AD.

AAAKB: A manually curated database for tracking and predicting genes of Abdominal aortic aneurysm (AAA)

Abdominal aortic aneurysm (AAA), an extremely dangerous vascular disease with high mortality, causes massive internal bleeding due to aneurysm rupture. To boost the research on AAA, efforts should be taken to organize and link the information about AAA-related genes and their functions. Currently, most researchers screen through genetic databases manually, which is cumbersome and time-consuming. Here, we developed "AAAKB" a manually curated knowledgebase containing genes, SNPs and pathways associated with AAA. In order to facilitate researchers to further explore the mechanism network of AAA, AAAKB provides predicted genes that are potentially associated with AAA. The prediction is based on the protein interaction information of genes collected in the database, and the random forest algorithm (RF) is used to build the prediction model. Some of these predicted genes are differentially expressed in patients with AAA, and some have been reported to play a role in other cardiovascular diseases, illustrating the utility of the knowledgebase in predicting novel genes. Also, AAAKB integrates a protein interaction visualization tool to quickly determine the shortest paths between target proteins. As the first knowledgebase to provide a comprehensive catalog of AAA-related genes, AAAKB will be an ideal research platform for AAA. Database URL: http://www.lqlgroup.cn:3838/AAAKB/.

Pathophysiological Aspects and Therapeutic Armamentarium of Alzheimer's Disease: Recent Trends and Future Development

Alzheimer's disease (AD) is the primary cause of dementia and is characterized by the death of brain cells due to the accumulation of insoluble amyloid plaques, hyperphosphorylation of tau protein, and the formation of neurofibrillary tangles within the cells. AD is also associated with other pathologies such as neuroinflammation, dysfunction of synaptic connections and circuits, disorders in mitochondrial function and energy production, epigenetic changes, and abnormalities in the vascular system. Despite extensive research conducted over the last hundred years, little is established about what causes AD or how to effectively treat it. Given the severity of the disease and the increasing number of affected individuals, there is a critical need to discover effective medications for AD. The US Food and Drug Administration (FDA) has approved several new drug molecules for AD management since 2003, but these drugs only provide temporary relief of symptoms and do not address the underlying causes of the disease. Currently, available medications focus on correcting the neurotransmitter disruption observed in AD, including cholinesterase inhibitors and an antagonist of the N-methyl-D-aspartate (NMDA) receptor, which temporarily alleviates the signs of dementia but does not prevent or reverse the course of AD. Research towards disease-modifying AD treatments is currently underway, including gene therapy, lipid nanoparticles, and dendrimer-based therapy. These innovative approaches aim to target the underlying pathological processes of AD rather than just managing the symptoms. This review discusses the novel aspects of pathogenesis involved in the causation of AD of AD and in recent developments in the therapeutic armamentarium for the treatment of AD such as gene therapy, lipid nanoparticles, and dendrimer-based therapy, and many more.

Grape juice reduces the effects of amyloid β aggregation phenotype and extends the longevity in Caenorhabditis elegans

OBJECTIVES

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the presence of aggregated amyloid-β (Aβ) peptides. Several natural compounds have been proposed against this disease and grape products are among these. However, little is known about grape juice potential. Transgenic Caenorhabditis elegans (C. elegans) strains that express human Aβ have been used as an in vivo model for AD.

METHODS

In this study, we have exposed CL2006 worms to nine different juices obtained from different cultivars.

RESULTS

Cora, Bordo, Isabel, Isabel Precoce, BRS-Magna, BRS-Rubea and BRS-Violeta juices improved the behavioral phenotype (paralysis) that is caused by Aβ aggregation in the transgenic animals at the concentrations tested and no toxic effects were found. Some juices were also able to increase the worm's lifespan. We could not attribute lifespan increase and paralysis reduction with any specific compound found in the phytochemical analysis.

DISCUSSION

Our data indicate that the rich constitution of the juices is responsible for attenuating the phenotype caused by Aβ aggregation in C. elegans.

Alzheimer's Disease: Novel Targets and Investigational Drugs for Disease Modification

Novel agents addressing non-amyloid, non-tau targets in Alzheimer's Disease (AD) comprise 70% of the AD drug development pipeline of agents currently in clinical trials. Most of the target processes identified in the Common Alzheimer's Disease Research Ontology (CADRO) are represented by novel agents in trials. Inflammation and synaptic plasticity/neuroprotection are the CADRO categories with the largest number of novel candidate therapies. Within these categories, there are few overlapping targets among the test agents. Additional categories being evaluated include apolipoprotein E [Formula: see text] 4 (APOE4) effects, lipids and lipoprotein receptors, neurogenesis, oxidative stress, bioenergetics and metabolism, vascular factors, cell death, growth factors and hormones, circadian rhythm, and epigenetic regulators. We highlight current drugs being tested within these categories and their mechanisms. Trials will be informative regarding which targets can be modulated to produce a slowing of clinical decline. Possible therapeutic combinations of agents may be suggested by trial outcomes. Biomarkers are evolving in concert with new targets and novel agents, and biomarker outcomes offer a means of supporting disease modification by the putative treatment. Identification of novel targets and development of corresponding therapeutics offer an important means of advancing new treatments for AD.

An automated, geometry-based method for hippocampal shape and thickness analysis

The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention.

Amyloid β-based therapy for Alzheimer's disease: challenges, successes and future

Amyloid β protein (Aβ) is the main component of neuritic plaques in Alzheimer's disease (AD), and its accumulation has been considered as the molecular driver of Alzheimer's pathogenesis and progression. Aβ has been the prime target for the development of AD therapy. However, the repeated failures of Aβ-targeted clinical trials have cast considerable doubt on the amyloid cascade hypothesis and whether the development of Alzheimer's drug has followed the correct course. However, the recent successes of Aβ targeted trials have assuaged those doubts. In this review, we discussed the evolution of the amyloid cascade hypothesis over the last 30 years and summarized its application in Alzheimer's diagnosis and modification. In particular, we extensively discussed the pitfalls, promises and important unanswered questions regarding the current anti-Aβ therapy, as well as strategies for further study and development of more feasible Aβ-targeted approaches in the optimization of AD prevention and treatment.

Plasma Biomarkers of Alzheimer's Disease: A Review of Available Assays, Recent Developments, and Implications for Clinical Practice

Recently, low-sensitive plasma assays have been replaced by new ultra-sensitive assays such as single molecule enzyme-linked immunosorbent assay (Simoa), the Mesoscale Discovery (MSD) platform, and immunoprecipitation-mass spectrometry (IP-MS) with higher accuracy in the determination of plasma biomarkers of Alzheimer's disease (AD). Despite the significant variability, many studies have established in-house cut-off values for the most promising available biomarkers. We first reviewed the most used laboratory methods and assays to measure plasma AD biomarkers. Next, we review studies focused on the diagnostic performance of these biomarkers to identify AD cases, predict cognitive decline in pre-clinical AD cases, and differentiate AD cases from other dementia. We summarized data from studies published until January 2023. A combination of plasma Aβ_42/40 ratio, age, and APOE status showed the best accuracy in diagnosing brain amyloidosis with a liquid chromatography-mass spectrometry (LC-MS) assay. Plasma p-tau217 has shown the best accuracy in distinguishing Aβ-PET+ from Aβ-PET-even in cognitively unimpaired individuals. We also summarized the different cut-off values for each biomarker when available. Recently developed assays for plasma biomarkers have undeniable importance in AD research, with improved analytical and diagnostic performance. Some biomarkers have been extensively used in clinical trials and are now clinically available. Nonetheless, several challenges remain to their widespread use in clinical practice.

Anti-Amyloid Monoclonal Antibodies are Transformative Treatments that Redefine Alzheimer's Disease Therapeutics

Two anti-amyloid monoclonal antibodies (MABs)-lecanemab (Leqembi®) and aducanumab (Aduhelm®)-have been approved in the USA for the treatment of Alzheimer's disease (AD). Anti-amyloid monoclonal antibodies are the first disease-modifying therapies for AD that achieve slowing of clinical decline by intervening in the basic biological processes of the disease. These are breakthrough agents that can slow the inevitable progression of AD into more severe cognitive impairment. The results of trials of anti-amyloid MABs support the amyloid hypothesis and amyloid as a target for AD drug development. The success of MABs reflects a relentless application of neuroscience knowledge to solving major challenges facing humankind. The success of these transformative agents will foster the development of more anti-amyloid MABs, other types of anti-amyloid therapies, treatments of other targets of AD biology, and new approaches to therapies for an array of neurodegenerative disorders. Monoclonal antibodies have side effects and, during the period of treatment initiation, patients must be closely monitored for the occurrence of amyloid-related imaging abnormalities (ARIA) and infusion reactions. A successful first step in the development of disease-modifying therapy for AD defines desirable features for the next phase of therapeutic development including less frequent ARIA, more convenient administration, and greater efficacy. Unprecedented agents make new demands on patients and care partners, clinicians, payers, and health care systems. Collaboration among stakeholders is essential to take advantage of the therapeutic benefits offered by these agents and to make them widely available. Monoclonal antibodies usher in a new era in AD therapy and define a new landscape of what is possible for therapeutic development for neurodegenerative disorders.

Role of Tau in Various Tauopathies, Treatment Approaches, and Emerging Role of Nanotechnology in Neurodegenerative Disorders

A few protein kinases and phosphatases regulate tau protein phosphorylation and an imbalance in their enzyme activity results in tau hyper-phosphorylation. Aberrant tau phosphorylation causes tau to dissociate from the microtubules and clump together in the cytosol to form neurofibrillary tangles (NFTs), which lead to the progression of neurodegenerative disorders including Alzheimer's disease (AD) and other tauopathies. Hence, targeting hyperphosphorylated tau protein is a restorative approach for treating neurodegenerative tauopathies. The cyclin-dependent kinase (Cdk5) and the glycogen synthase kinase (GSK3β) have both been implicated in aberrant tau hyperphosphorylation. The limited transport of drugs through the blood-brain barrier (BBB) for reaching the central nervous system (CNS) thus represents a significant problem in the development of drugs. Drug delivery systems based on nanocarriers help solve this problem. In this review, we discuss the tau protein, regulation of tau phosphorylation and abnormal hyperphosphorylation, drugs in use or under clinical trials, and treatment strategies for tauopathies based on the critical role of tau hyperphosphorylation in the pathogenesis of the disease. Pathology of neurodegenerative disease due to hyperphosphorylation and various therapeutic approaches including nanotechnology for its treatment.

Multi-Site Cross-Site Inter-Rater and Test-Retest Reliability and Construct Validity of the MarkVCID White Matter Hyperintensity Growth and Regression Protocol

BACKGROUND

White matter hyperintensities (WMH) that occur in the setting of vascular cognitive impairment and dementia (VCID) may be dynamic increasing or decreasing volumes or stable over time. Quantifying such changes may prove useful as a biomarker for clinical trials designed to address vascular cognitive-impairment and dementia and Alzheimer's Disease.

OBJECTIVE

Conducting multi-site cross-site inter-rater and test-retest reliability of the MarkVCID white matter hyperintensity growth and regression protocol.

METHODS

The NINDS-supported MarkVCID Consortium evaluated a neuroimaging biomarker developed to track WMH change. Test-retest and cross-site inter-rater reliability of the protocol were assessed. Cognitive test scores were analyzed in relation to WMH changes to explore its construct validity.

RESULTS

ICC values for test-retest reliability of WMH growth and regression were 0.969 and 0.937 respectively, while for cross-site inter-rater ICC values for WMH growth and regression were 0.995 and 0.990 respectively. Word list long-delay free-recall was negatively associated with WMH growth (p < 0.028) but was not associated with WMH regression.

CONCLUSIONS

The present data demonstrate robust ICC validity of a WMH growth/regression protocol over a one-year period as measured by cross-site inter-rater and test-retest reliability. These data suggest that this approach may serve an important role in clinical trials of disease-modifying agents for VCID that may preferentially affect WMH growth, stability, or regression.

Early Diagnosis of Alzheimer's Disease with Blood Test; Tempting but Challenging

The increasing prevalence of Alzheimer's disease (AD) has led to a health crisis. According to official statistics, more than 55 million people globally have AD or other types of dementia, making it the sixth leading cause of death. It is still difficult to diagnose AD and there is no definitive diagnosis yet; post-mortem autopsy is still the only definite method. Moreover, clinical manifestations occur very late in the course of disease progression; therefore, profound irreversible changes have already occurred when the disease manifests. Studies have shown that in the preclinical stage of AD, changes in some biomarkers are measurable prior to any neurological damage or other symptoms. Hence, creating a reliable, fast, and affordable method capable of detecting AD in early stage has attracted the most attention. Seeking clinically applicable, inexpensive, less invasive, and much more easily accessible biomarkers for early diagnosis of AD, blood-based biomarkers (BBBs) seem to be an ideal option. This review is an inclusive report of BBBs that have been shown to be altered in the course of AD progression. The aim of this report is to provide comprehensive insight into the research status of early detection of AD based on BBBs.

Understanding the Intricate Role of Exosomes in Pathogenesis of Alzheimer's Disease

Alzheimer's disease causes loss of memory and deterioration of mental abilities is utmost predominant neurodegenerative disease accounting 70-80% cases of dementia. The appearance of plaques of amyloid-β and neurofibrillary tangles in the brain post-mortems of Alzheimer's patients established them as key participants in the etiology of Alzheimer's disease. Exosomes exist as extracellular vesicles of nano-size which are present throughout the body. Exosomes are known to spread toxic hyperphosphorylated tau and amyloid-β between the cells and are linked to the loss of neurons by inducing apoptosis. Exosomes have progressed from cell trashcans to multifunctional organelles which are involved in various functions like internalisation and transmission of macromolecules such as lipids, proteins, and nucleic acids. This review covers current findings on relationship of exosomes in biogenesis and angiogenesis of Alzheimer's disease and functions of exosomes in the etiology of AD. Furthermore, the roles of exosomes in development, diagnosis, treatment, and its importance as therapeutic targets and biomarkers for Alzheimer's disease have also been highlighted.

Bioinformatics tools and data resources for assay development of fluid protein biomarkers

Fluid protein biomarkers are important tools in clinical research and health care to support diagnosis and to monitor patients. Especially within the field of dementia, novel biomarkers could address the current challenges of providing an early diagnosis and of selecting trial participants. While the great potential of fluid biomarkers is recognized, their implementation in routine clinical use has been slow. One major obstacle is the often unsuccessful translation of biomarker candidates from explorative high-throughput techniques to sensitive antibody-based immunoassays. In this review, we propose the incorporation of bioinformatics into the workflow of novel immunoassay development to overcome this bottleneck and thus facilitate the development of novel biomarkers towards clinical laboratory practice. Due to the rapid progress within the field of bioinformatics many freely available and easy-to-use tools and data resources exist which can aid the researcher at various stages. Current prediction methods and databases can support the selection of suitable biomarker candidates, as well as the choice of appropriate commercial affinity reagents. Additionally, we examine methods that can determine or predict the epitope - an antibody’s binding region on its antigen - and can help to make an informed choice on the immunogenic peptide used for novel antibody production. Selected use cases for biomarker candidates help illustrate the application and interpretation of the introduced tools.

Diabetes: Risk factor and translational therapeutic implications for Alzheimer's disease

Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) commonly co-occur. T2DM increases the risk for AD by approximately twofold. Animal models provide one means of interrogating the relationship of T2DM to AD and investigating brain insulin resistance in the pathophysiology of AD. Animal models show that persistent hyperglycaemia results in chronic low-grade inflammation that may contribute to the development of neuroinflammation and accelerate the pathobiology of AD. Epidemiological studies suggest that patients with T2DM who received treatment with specific anti-diabetic agents have a decreased risk for the occurrence of AD and all-cause dementia. Agents such as metformin ameliorate T2DM and may have other important systemic effects that lower the risk of AD. Glucagon-like peptide 1 (GLP-1) agonists have been associated with a decreased risk for AD in patients with T2DM. Both insulin and non-insulin anti-diabetic treatments have been evaluated for the treatment of AD in clinical trials. In most cases, patients included in the trials have clinical features of AD but do not have T2DM. Many of the trials were conducted prior to the use of diagnostic biomarkers for AD. Trials have had a wide range of durations and population sizes. Many of the agents used to treat T2DM do not cross the blood brain barrier, and the effects are posited to occur via lowering of peripheral hyperglycaemia and reduction of peripheral and central inflammation. Clinical trials of anti-diabetic agents to treat AD are ongoing and will provide insight into the therapeutic utility of these agents.

Cognitive and biological effects of citrus phytochemicals in subjective cognitive decline: a 36-week, randomized, placebo-controlled trial

Background

Auraptene (AUR) and naringenin (NAR) are citrus-derived phytochemicals that influence several biological mechanisms associated with cognitive decline, including neuronal damage, oxidative stress and inflammation. Clinical evidence of the efficacy of a nutraceutical with the potential to enhance cognitive function in cohorts at risk of cognitive decline would be of great value from a preventive perspective. The primary aim of this study is to determine the cognitive effects of a 36-week treatment with citrus peel extract standardized in levels of AUR and NAR in older adults experiencing subjective cognitive decline (SCD). The secondary aim is to determine the effects of these phytochemicals on blood-based biomarkers indicative of neuronal damage, oxidative stress, and inflammation.

Methods

Eighty older persons with SCD will be recruited and randomly assigned to receive the active treatment (400 mg of citrus peel extract containing 0.1 mg of AUR and 3 mg of NAR) or the placebo at a 1:1 ratio for 36 weeks. The primary endpoint is a change in the Repeatable Battery for the Assessment of Neuropsychological Status score from baseline to weeks 18 and 36. Other cognitive outcomes will include changes in verbal and nonverbal memory, attention, executive and visuospatial functions. Blood samples will be collected from a consecutive subsample of 60 participants. The secondary endpoint is a change in interleukin-8 levels over the 36-week period. Other biological outcomes include changes in markers of neuronal damage, oxidative stress, and pro- and anti-inflammatory cytokines.

Conclusion

This study will evaluate whether an intervention with citrus peel extract standardized in levels of AUR and NAR has cognitive and biological effects in older adults with SCD, facilitating the establishment of nutrition intervention in people at risk of cognitive decline.

Trial registration

The trial is registered with the United States National Library of Medicine at the National Institutes of Health Registry of Clinical Trials under the code NCT04744922 on February 9^th, 2021 (https://www.clinicaltrials.gov/ct2/show/NCT04744922).

Neuroprotection in neurodegenerations of the brain and eye: Lessons from the past and directions for the future

Background

Neurological and ophthalmological neurodegenerative diseases in large part share underlying biology and pathophysiology. Despite extensive preclinical research on neuroprotection that in many cases bridges and unifies both fields, only a handful of neuroprotective therapies have succeeded clinically in either.

Main body

Understanding the commonalities among brain and neuroretinal neurodegenerations can help develop innovative ways to improve translational success in neuroprotection research and emerging therapies. To do this, analysis of why translational research in neuroprotection fails necessitates addressing roadblocks at basic research and clinical trial levels. These include optimizing translational approaches with respect to biomarkers, therapeutic targets, treatments, animal models, and regulatory pathways.

Conclusion

The common features of neurological and ophthalmological neurodegenerations are useful for outlining a path forward that should increase the likelihood of translational success in neuroprotective therapies.

Designing the next-generation clinical care pathway for Alzheimer's disease

The reconceptualization of Alzheimer's disease (AD) as a clinical and biological construct has facilitated the development of biomarker-guided, pathway-based targeted therapies, many of which have reached late-stage development with the near-term potential to enter global clinical practice. These medical advances mark an unprecedented paradigm shift and requires an optimized global framework for clinical care pathways for AD. In this Perspective, we describe the blueprint for transitioning from the current, clinical symptom-focused and inherently late-stage diagnosis and management of AD to the next-generation pathway that incorporates biomarker-guided and digitally facilitated decision-making algorithms for risk stratification, early detection, timely diagnosis, and preventative or therapeutic interventions. We address critical and high-priority challenges, propose evidence-based strategic solutions, and emphasize that the perspectives of affected individuals and care partners need to be considered and integrated.

Recent advances in pre-clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia with currently no known cures or disease modifying treatments (DMTs), despite much time and effort from the field. Diagnosis and intervention of AD during the early pre-symptomatic phase of the disease is thought to be a more effective strategy. Therefore, the detection of biomarkers has emerged as a critical tool for monitoring the effect of new AD therapies, as well as identifying patients most likely to respond to treatment. The establishment of the amyloid/tau/neurodegeneration (A/T/N) framework in 2018 has codified the contexts of use of AD biomarkers in neuroimaging and bodily fluids for research and diagnostic purposes. Furthermore, a renewed drive for novel AD biomarkers and innovative methods of detection has emerged with the goals of adding additional insight to disease progression and discovery of new therapeutic targets. The use of biomarkers has accelerated the development of AD drugs and will bring new therapies to patients in need. This review highlights recent methods utilized to diagnose antemortem AD.

Update on the Cognitive Presentations of iNPH for Clinicians

This mini-review focuses on cognitive impairment in iNPH. This symptom is one of the characteristic triad of symptoms in a condition long considered to be the only treatable dementia. We present an update on recent developments in clinical, neuropsychological, neuroimaging and biomarker aspects. Significant advances in our understanding have been made, notably regarding biomarkers, but iNPH remains a difficult diagnosis. Stronger evidence for permanent surgical treatment is emerging but selection for treatment remains challenging, particularly with regards to cognitive presentations. Encouragingly, there has been increasing interest in iNPH, but more research is required to better define the underlying pathology and delineate it from overlapping conditions, in order to inform best practise for the clinician managing the cognitively impaired patient. In the meantime, we strongly encourage a multidisciplinary approach and a structured service pathway to maximise patient benefit.

Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation

Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.

Toward the Noninvasive Diagnosis of Alzheimer's Disease: Molecular Basis for the Specificity of Curcumin for Fibrillar Amyloid-β

Recent studies show that curcumin, a naturally fluorescent dye, can be used for the noninvasive optical imaging of retinal amyloid-β (Aβ) plaques. We investigated the molecular basis for curcumin's specificity for hierarchical Aβ structures using molecular dynamics simulations, with a focus on how curcumin is able to detect and discriminate different amyloid morphologies. Curcumin inhibits and breaks up β-sheet formation in Aβ monomers. With disordered Aβ structures, curcumin forms a coarse-grained composite structure. With an ordered fibril, curcumin's interaction is highly specific, and the curcumin molecules are deposited in the fibril groove. Curcumin tends to self-aggregate, which is finely balanced with its affinity for Aβ. This tendency concentrates curcumin molecules at Aβ deposition sites, potentially increasing the fluorescence signal. This is probably why curcumin is such an effective amyloid imaging agent.

Autoantibodies targeting neuronal proteins as biomarkers for neurodegenerative diseases

Neurodegenerative diseases (NDDs) are associated with the accumulation of a range of misfolded proteins across the central nervous system and related autoimmune responses, including the generation of antibodies and the activation of immune cells. Both innate and adaptive immunity become mobilized, leading to cellular and humoral effects. The role of humoral immunity in disease onset and progression remains to be elucidated with rising evidence suggestive of positive (protection, repair) and negative (injury, toxicity) outcomes. In this study, we review advances in research of neuron-targeting autoantibodies in the most prevalent NDDs. We discuss their biological origin, molecular diversity and changes in the course of diseases, consider their relevance to the initiation and progression of pathology as well as diagnostic and prognostic significance. It is suggested that the emerging autoimmune aspects of NDDs not only could facilitate the early detection but also might help to elucidate previously unknown facets of pathobiology with relevance to the development of precision medicine.

Alzheimer's disease drug development pipeline: 2022

Introduction

Alzheimer's disease (AD) represents a global health crisis. Treatments are needed to prevent, delay the onset, slow the progression, improve cognition, and reduce behavioral disturbances of AD. We review the current clinical trials and drugs in development for the treatment of AD.

Methods

We searched the governmental website clinicaltrials.gov where are all clinical trials conducted in the United States must be registered. We used artificial intelligence (AI) and machine learning (ML) approaches to ensure comprehensive detection and characterization of trials and drugs in development. We use the Common Alzheimer's Disease Research Ontology (CADRO) to classify drug targets and mechanisms of action of drugs in the pipeline.

Results

As of January 25, 2022 (index date for this study) there were 143 agents in 172 clinical trials for AD. The pipeline included 31 agents in 47 trials in Phase 3, 82 agents in 94 trials in Phase 2, and 30 agents in 31 trials in Phase 1. Disease-modifying therapies represent 83.2% of the total number of agents in trials; symptomatic cognitive enhancing treatments represent 9.8% of agents in trials; and drugs for the treatment of neuropsychiatric symptoms comprise 6.9%. There is a diverse array of drug targets represented by agents in trials including nearly all CADRO categories. Thirty-seven percent of the candidate agents in the pipeline are repurposed drugs approved for other indications. A total of 50,575 participants are needed to fulfill recruitment requirements for all currently active clinical trials.

Discussion

The AD drug development pipeline has agents representing a substantial array of treatment mechanisms and targets. Advances in drug design, outcome measures, use of biomarkers, and trial conduct promise to accelerate the delivery of new and better treatments for patients with AD.

Highlights

There are 143 drugs in the current Alzheimer's disease (AD) drug development pipeline.Disease-modifying therapies represent 83.2% of the candidate treatments.Current trials require 50,575 participants who will donate 3,878,843 participant-weeks to clinical trials.The biopharmaceutical industry sponsors 50% of all clinical trials including 68% of Phase 3 trials.Sixty-three percent of Phase 3 trials and 46% of Phase 2 trials include non-North American clinical trial site locations indicating the global ecosystem required for AD drug development.

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies

Advances in biotechnology have enabled us to assay human tissue and cells to a depth and resolution that was never possible before, redefining what we know as the “biomarker”, and how we define a “disease”. This comes along with the shift of focus from a “one-drug-fits-all” to a “personalized approach”, placing the drug development industry in a highly dynamic landscape, having to navigate such disruptive trends. In response to this, innovative clinical trial designs have been key in realizing biomarker-driven drug development. Regulatory approvals of cancer genome sequencing panels and associated targeted therapies has brought personalized medicines to the clinic. Increasing availability of sophisticated biotechnologies such as next-generation sequencing (NGS) has also led to a massive outflux of real-world genomic data. This review summarizes the current state of biomarker-driven drug development and highlights examples showing the utility and importance of the application of real-world data in the process. We also propose that all stakeholders in drug development should (1) be conscious of and efficiently utilize real-world evidence and (2) re-vamp the way the industry approaches drug development in this era of personalized medicines.

Syndecan-3 as a Novel Biomarker in Alzheimer's Disease

Early diagnosis of Alzheimer’s disease (AD) is of paramount importance in preserving the patient’s mental and physical health in a fairly manageable condition for a longer period. Reliable AD detection requires novel biomarkers indicating central nervous system (CNS) degeneration in the periphery. Members of the syndecan family of transmembrane proteoglycans are emerging new targets in inflammatory and neurodegenerative disorders. Reviewing the growing scientific evidence on the involvement of syndecans in the pathomechanism of AD, we analyzed the expression of the neuronal syndecan, syndecan-3 (SDC3), in experimental models of neurodegeneration. Initial in vitro studies showed that prolonged treatment of tumor necrosis factor-alpha (TNF-α) increases SDC3 expression in model neuronal and brain microvascular endothelial cell lines. In vivo studies revealed elevated concentrations of TNF-α in the blood and brain of APPSWE-Tau transgenic mice, along with increased SDC3 concentration in the brain and the liver. Primary brain endothelial cells and peripheral blood monocytes isolated from APPSWE-Tau mice exhibited increased SDC3 expression than wild-type controls. SDC3 expression of blood-derived monocytes showed a positive correlation with amyloid plaque load in the brain, demonstrating that SDC3 on monocytes is a good indicator of amyloid pathology in the brain. Given the well-established role of blood tests, the SDC3 expression of monocytes could serve as a novel biomarker for early AD detection.

Blood-based biomarkers for Alzheimer's disease

Neurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever-increasing role in research, clinical trials, and in the clinical work-up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)-based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra-sensitive assays, the levels of pathological brain- and AD-related proteins can now be measured in blood, with recent work showing promising results. Plasma P-tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD-specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease-modifying therapies. This review provides an overview of the progress achieved thus far using AD blood-based biomarkers, highlighting key areas of application and unmet challenges.

Detection and quantification of Aβ-3-40 (APP669-711) in cerebrospinal fluid

Neurochemical biomarkers can support the diagnosis of Alzheimer's disease and may facilitate clinical trials. In blood plasma, the ratio of the amyloid-β (Aβ) peptides Aβ-3-40/Aβ1-42 can predict cerebral amyloid-β pathology with high accuracy (Nakamura et al., 2018). Whether or not Aβ-3-40 (aka. amyloid precursor protein (APP) 669-711) is also present in cerebrospinal fluid (CSF) is not clear. Here, we investigated whether Aβ-3-40 can be detected in CSF and to what extent the CSF Aβ-3-40/Aβ42 ratio is able to differentiate between individuals with or without amyloid-β positron emission tomography (PET) evidence of brain amyloid. The occurrence of Aβ-3-40 in human CSF was assessed by immunoprecipitation followed by mass spectrometry. For quantifying the CSF concentrations of Aβ-3-40 in 23 amyloid PET-negative and 17 amyloid PET-positive subjects, we applied a sandwich-type immunoassay. Our findings provide clear evidence of the presence of Aβ-3-40 and Aβ-3-38 in human CSF. While there was no statistically significant difference in the CSF concentration of Aβ-3-40 between the two diagnostic groups, the CSF Aβ-3-40/Aβ42 ratio was increased in the amyloid PET-positive individuals. We conclude that Aβ-3-40 appears to be a regular constituent of CSF and may potentially serve to accentuate the selective decrease in CSF Aβ42 in Alzheimer's disease.

Modulation of Amyloid-β and Tau in Alzheimer's Disease Plasma Neuronal-Derived Extracellular Vesicles by Cerebrolysin® and Donepezil

BACKGROUND

Plasma neuronal-derived extracellular vesicles (NDEV) contain proteins of pathological, diagnostic, and therapeutic relevance.

OBJECTIVE

We investigated the associations of six plasma NDEV markers with Alzheimer's disease (AD) severity, cognition and functioning, and changes in these biomarkers after Cerebrolysin®, donepezil, and a combination therapy in AD.

METHODS

Plasma NDEV levels of Aβ42, total tau, P-T181-tau, P-S393-tau, neurogranin, and REST were determined in: 1) 116 mild to advanced AD patients and in 20 control subjects; 2) 110 AD patients treated with Cerebrolysin®, donepezil, or combination therapy in a randomized clinical trial (RCT). Samples for NDEV determinations were obtained at baseline in the NDEV study and at baseline and study endpoint in the RCT. Cognition and functioning were assessed at the same time points.

RESULTS

NDEV levels of Aβ42, total tau, P-T181-tau, and P-S393-tau were higher and those of neurogranin and REST were lower in mild-to-moderate AD than in controls (p < 0.05 to p < 0.001). NDEV total tau, neurogranin, and REST increased with AD severity (p < 0.05 to p < 0.001). NDEV Aβ42 and P-T181-tau correlated negatively with serum BDNF (p < 0.05), and total-tau levels were associated to plasma TNF-α (p < 0.01) and cognitive impairment (p < 0.05). Combination therapy reduced NDEV Aβ42 with respect to monotherapies (p < 0.05); and NDEV total tau, P-T181-tau, and P-S396-tau were decreased in Cerebrolysin-treated patients compared to those on donepezil monotherapy (p < 0.05).

CONCLUSION

The present results demonstrate the utility of NDEV determinations of pathologic and synaptic proteins as effective AD biomarkers, as markers of AD severity, and as potential tools for monitoring the effects of anti-AD drugs.

Alzheimer Disease Biomarkers in Clinical Practice: A Blood-Based Diagnostic Revolution

An estimated 6.1 million Americans live with cognitive impairment-a number that is expected to triple by 2050. Alzheimer disease (AD) is the most common cause of impairment. The development of blood-based biomarkers capable of detecting pathological changes of AD in living patients has the potential to revolutionize the diagnostic approach to cognitive impairment by enabling screening for AD using accessible, non-invasive measures of amyloid and tau neuropathology, with accuracy that increasingly approaches that seen with "gold standard" positron emission tomography and cerebrospinal fluid measures. Demand for biomarker testing is expected to intensify with the emergence of effective treatments for AD and related dementias. Clinicians in all fields must prepare to meet this demand. Primary care practitioners are well positioned to support dementia diagnosis and management, including the application and interpretation of biomarkers. This article reviews the current uses of AD biomarkers and the potential applications of emerging blood-based AD biomarkers in clinical practice.

Blood Biomarkers from Research Use to Clinical Practice: What Must Be Done? A Report from the EU/US CTAD Task Force

Timely and accurate diagnosis of Alzheimer's disease (AD) in clinical practice remains challenging. PET and CSF biomarkers are the most widely used biomarkers to aid diagnosis in clinical research but present limitations for clinical practice (i.e., cost, accessibility). Emerging blood-based markers have the potential to be accurate, cost-effective, and easily accessible for widespread clinical use, and could facilitate timely diagnosis. The EU/US CTAD Task Force met in May 2022 in a virtual meeting to discuss pathways to implementation of blood-based markers in clinical practice. Specifically, the CTAD Task Force assessed: the state-of-art for blood-based markers, the current use of blood-based markers in clinical trials, the potential use of blood-based markers in clinical practice, the current challenges with blood-based markers, and the next steps needed for broader adoption in clinical practice.

Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models

Alzheimer's disease (AD) is a complex disease that is mediated by numerous factors and manifests in various forms. A systems biology approach to studying AD involves analyses of various body systems, biological scales, environmental elements, and clinical outcomes to understand the genotype to phenotype relationship that potentially drives AD development. Currently, there are many research investigations probing how modifiable and nonmodifiable factors impact AD symptom presentation. This review specifically focuses on how imaging modalities can be integrated into systems biology approaches using model mouse populations to link brain level functional and structural changes to disease onset and progression. Combining imaging and omics data promotes the classification of AD into subtypes and paves the way for precision medicine solutions to prevent and treat AD.

Amyloid-β PET Classification on Cognitive Aging Stages Using the Centiloid Scale

PROPOSE

This study aims to explore the use of the Centiloid (CL) method in amyloid-β PET quantification to evaluate distinct cognitive aging stages, investigating subjects' mismatch classification using different cut-points for amyloid-β positivity.

PROCEDURES

The CL equation was applied in four groups of individuals: SuperAgers (SA), healthy age-matched controls (AC), healthy middle-aged controls (MC), and Alzheimer's disease (AD). The amyloid-β burden was calculated and compared between groups and quantitative variables. Three different cut-points (Jack CR, Wiste HJ, Weigand SD, et al., Alzheimer's Dement 13:205-216, 2017; Salvadó G, Molinuevo JL, Brugulat-Serrat A, et al., Alzheimer's Res Ther 11:27, 2019; and Amadoru S, Doré V, McLean CA, et al., Alzheimer's Res Ther 12:22, 2020) were applied in CL values to differentiate the earliest abnormal pathophysiological accumulation of Aβ and the established Aβ pathology.

RESULTS

The AD group exhibited a significantly increased Aβ burden compared to the MC, but not AC groups. Both healthy control (MC and AC) groups were not significantly different. Visually, the SA group showed a diverse distribution of CL values compared with MC; however, the difference was not significant. The CL values have a moderate and significant relationship between Aβ visual read, RAVLT DR and MMSE. Depending on the cut-point used, 10 CL, 19 CL, or 30 CL, 7.5% of our individuals had a different classification in the Aβ positivity. For the AC group, we obtained about 40 to 60% of the individuals classified as positive.

CONCLUSION

SuperAgers exhibited a similar Aβ load to AC and MC, differing in cognitive performance. Independently of cut-point used (10 CL, 19 CL, or 30 CL), three SA individuals were classified as Aβ positive, showing the duality between the individual's clinics and the biological definition of Alzheimer's. Different cut-points lead to Aβ positivity classification mismatch in individuals, and an extra care is needed for individuals who have a CL value between 10 and 30 CL.

Cognitive Effects of the BET Protein Inhibitor Apabetalone: A Prespecified Montreal Cognitive Assessment Analysis Nested in the BETonMACE Randomized Controlled Trial

Background:

Epigenetic changes may contribute importantly to cognitive decline in late life including Alzheimer’s disease (AD) and vascular dementia (VaD). Bromodomain and extra-terminal (BET) proteins are epigenetic “readers” that may distort normal gene expression and contribute to chronic disorders.

Objective:

To assess the effects of apabetalone, a small molecule BET protein inhibitor, on cognitive performance of patients 70 years or older participating in a randomized trial of patients at high risk for major cardiovascular events (MACE).

Methods:

The Montreal Cognitive Assessment (MoCA) was performed on all patients 70 years or older at the time of randomization. 464 participants were randomized to apabetalone or placebo in the cognition sub-study. In a prespecified analysis, participants were assigned to one of three groups: MoCA score≥26 (normal performance), MoCA score 25–22 (mild cognitive impairment), and MoCA score≤21 (dementia). Exposure to apabetalone was equivalent in the treatment groups in each MoCA-defined group.

Results:

Apabetalone was associated with an increased total MoCA score in participants with baseline MoCA score of≤21 (p = 0.02). There was no significant difference in change from baseline in the treatment groups with higher MoCA scores. In the cognition study, more patients randomized to apabetalone discontinued study drug for adverse effects (11.3% versus 7.9%).

Conclusion:

In this randomized controlled study, apabetalone was associated with improved cognition as measured by MoCA scores in those with baseline scores of 21 or less. BET protein inhibitors warrant further investigation for late life cognitive disorders.

Heterogeneity of Cerebrospinal Fluid Biomarkers Profiles in Individuals with Distinct Levels of Cognitive Decline: A Cross-Sectional Study

BACKGROUND

Decreased cerebrospinal fluid (CSF) concentrations of the amyloid-β (Aβ), along with increased total (T-tau) and phosphorylated tau protein (P-tau), are widely accepted as core biomarkers of Alzheimer's disease (AD) pathology. Nonetheless, there are a few remaining caveats that still preclude the full incorporation of AD biomarkers into clinical practice.

OBJECTIVE

To determine the frequency of clinical-biological mismatches in a clinical sample of older adults with varying degrees of cognitive impairment.

METHODS

204 participants were enrolled for a cross-sectional assessment and allocated into diagnostic groups: probable AD (n = 60, 29.4%); MCI (n = 84, 41.2%); or normal cognition (NC, n = 60, 29.4%). CSF concentrations of Aβ42, T-tau, and 181Thr-P-tau were determined, and Aβ42/P-tau ratio below 9.53 was used as a proxy of AD pathology. The AT(N) classification was further used as a framework to ascertain the biological evidence of AD.

RESULTS

The majority (73.7%) of patients in the AD group had the Aβ42/P-tau ratio below the cut-off score for AD, as opposed to a smaller proportion in the MCI (42.9%) and NC (23.3%) groups. In the latter, 21 subjects (35%) were classified as A+, 28 (46.7%) as T+, and 23 (38.3%) as N + . In the AD group, 66.7%of the cases were classified as A+, 78.3%as T+, and 80%as N+.

CONCLUSION

Analysis of CSF biomarkers was able to discriminate between AD, MCI, and NC. However, clinical-biological mismatches were observed in a non-negligible proportion of cases.

The Potential of Induced Pluripotent Stem Cells to Treat and Model Alzheimer's Disease

An estimated 6.2 million Americans aged 65 or older are currently living with Alzheimer's disease (AD), a neurodegenerative disease that disrupts an individual's ability to function independently through the degeneration of key regions in the brain, including but not limited to the hippocampus, the prefrontal cortex, and the motor cortex. The cause of this degeneration is not known, but research has found two proteins that undergo posttranslational modifications: tau, a protein concentrated in the axons of neurons, and amyloid precursor protein (APP), a protein concentrated near the synapse. Through mechanisms that have yet to be elucidated, the accumulation of these two proteins in their abnormal aggregate forms leads to the neurodegeneration that is characteristic of AD. Until the invention of induced pluripotent stem cells (iPSCs) in 2006, the bulk of research was carried out using transgenic animal models that offered little promise in their ability to translate well from benchtop to bedside, creating a bottleneck in the development of therapeutics. However, with iPSC, patient-specific cell cultures can be utilized to create models based on human cells. These human cells have the potential to avoid issues in translatability that have plagued animal models by providing researchers with a model that closely resembles and mimics the neurons found in humans. By using human iPSC technology, researchers can create more accurate models of AD ex vivo while also focusing on regenerative medicine using iPSC in vivo. The following review focuses on the current uses of iPSC and how they have the potential to regenerate damaged neuronal tissue, in the hopes that these technologies can assist in getting through the bottleneck of AD therapeutic research.

Alzheimer's disease drug development pipeline: 2021

INTRODUCTION

The number of individuals worldwide with Alzheimer's disease (AD) is growing at a rapid rate. New treatments are urgently needed. We review the current pipeline of drugs in clinical trials for the treatment of AD.

METHODS

We interrogated ClinicalTrials.gov, the federal registry of clinical trials to identify drugs in trials.

RESULTS

There are 126 agents in 152 trials assessing new therapies for AD: 28 treatments in Phase 3 trials, 74 in Phase 2, and 24 in Phase 1. The majority of drugs in trials (82.5%) target the underlying biology of AD with the intent of disease modification; 10.3% are putative cognitive enhancing agents; and 7.1% are drugs being developed to reduce neuropsychiatric symptoms.

DISCUSSION

This pipeline analysis shows that target biological processes are more diversified, biomarkers are more regularly used, and repurposed agents are being explored to determine their utility for the treatment of AD.