Challenges and progress in research, diagnostics, and therapeutics in Alzheimer's disease and related dementias

Advances in blood biomarkers for Alzheimer disease (AD): A review

Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aβ) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.

Blood-based therapies to combat neurodegenerative diseases

Neurodegeneration, known as the progressive loss of neurons in terms of their structure and function, is the principal pathophysiological change found in the majority of brain-related disorders. Ageing has been considered the most well-established risk factor in most common neurodegenerative diseases, such as Parkinson's disease (PD) and Alzheimer's disease (AD). There is currently no effective treatment or cure for these diseases; the approved therapeutic options to date are only for palliative care. Ageing and neurodegenerative diseases are closely intertwined; reversing the aspects of brain ageing could theoretically mitigate age-related neurodegeneration. Ever since the regenerative properties of young blood on aged tissues came to light, substantial efforts have been focused on identifying and characterizing the circulating factors in the young and old systemic milieu that may attenuate or accentuate brain ageing and neurodegeneration. Later studies discovered the superiority of old plasma dilution in tissue rejuvenation, which is achieved through a molecular reset of the systemic proteome. These findings supported the use of therapeutic blood exchange for the treatment of degenerative diseases in older individuals. The first objective of this article is to explore the rejuvenating properties of blood-based therapies in the ageing brains and their therapeutic effects on AD. Then, we also look into the clinical applications, various limitations, and challenges associated with blood-based therapies for AD patients.

Research progress of PROTACs for neurodegenerative diseases therapy

Neurodegenerative diseases (NDD) are characterized by the gradual deterioration of neuronal function and integrity, resulting in an overall decline in brain function. The existing therapeutic options for NDD, including Alzheimer's disease, Parkinson's disease, and Huntington's disease, fall short of meeting the clinical demand. A prominent pathological hallmark observed in numerous neurodegenerative disorders is the aggregation and misfolding of proteins both within and outside neurons. These abnormal proteins play a pivotal role in the pathogenesis of neurodegenerative diseases. Targeted degradation of irregular proteins offers a promising avenue for NDD treatment. Proteolysis-targeting chimeras (PROTACs) function via the ubiquitin-proteasome system and have emerged as a novel and efficacious approach in drug discovery. PROTACs can catalytically degrade "undruggable" proteins even at exceptionally low concentrations, allowing for precise quantitative control of aberrant protein levels. In this review, we present a compilation of reported PROTAC structures and their corresponding biological activities aimed at addressing NDD. Spanning from 2016 to present, this review provides an up-to-date overview of PROTAC-based therapeutic interventions. Currently, most protein degraders intended for NDD treatment remain in the preclinical research phase. Overcoming several challenges is imperative, including enhancing oral bioavailability and permeability across the blood-brain barrier, before these compounds can progress to clinical research or eventually reach the market. However, armed with an enhanced comprehension of the underlying pathological mechanisms and the emergence of innovative scaffolds for protein degraders, along with further structural optimization, we are confident that PROTAC possesses the potential to make substantial breakthroughs in the field of neurodegenerative diseases.

Detecting Alzheimer's Disease Stages and Frontotemporal Dementia in Time Courses of Resting-State fMRI Data Using a Machine Learning Approach

Early, accurate diagnosis of neurodegenerative dementia subtypes such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) is crucial for the effectiveness of their treatments. However, distinguishing these conditions becomes challenging when symptoms overlap or the conditions present atypically. Resting-state fMRI (rs-fMRI) studies have demonstrated condition-specific alterations in AD, FTD, and mild cognitive impairment (MCI) compared to healthy controls (HC). Here, we used machine learning to build a diagnostic classification model based on these alterations. We curated all rs-fMRIs and their corresponding clinical information from the ADNI and FTLDNI databases. Imaging data underwent preprocessing, time course extraction, and feature extraction in preparation for the analyses. The imaging features data and clinical variables were fed into gradient-boosted decision trees with fivefold nested cross-validation to build models that classified four groups: AD, FTD, HC, and MCI. The mean and 95% confidence intervals for model performance metrics were calculated using the unseen test sets in the cross-validation rounds. The model built using only imaging features achieved 74.4% mean balanced accuracy, 0.94 mean macro-averaged AUC, and 0.73 mean macro-averaged F1 score. It accurately classified FTD (F1 = 0.99), HC (F1 = 0.99), and MCI (F1 = 0.86) fMRIs but mostly misclassified AD scans as MCI (F1 = 0.08). Adding clinical variables to model inputs raised balanced accuracy to 91.1%, macro-averaged AUC to 0.99, macro-averaged F1 score to 0.92, and improved AD classification accuracy (F1 = 0.74). In conclusion, a multimodal model based on rs-fMRI and clinical data accurately differentiates AD-MCI vs. FTD vs. HC.

Special Issue 'Advances in Neurodegenerative Diseases Research and Therapy 2.0'

Neurodegenerative disorders (NDs) and the development of various therapeutic strategies to combat them have received increased attention in recent decades [...].

Anti-dementia drugs: what is the evidence in advanced stages?

Dementia is a major public health concern due to its increasing prevalence, substantial caregiver burden, and high financial costs. Currently, the anti-dementia drugs aim only at a symptomatic effect. The subject of prescribing these drugs in advanced stages is a matter of considerable debate, with different countries making distinct recommendations. In this review article, we analyzed the evidence regarding cognitive and functional outcomes, adverse events, health-related costs, and caregiver burden in patients with advanced Alzheimer disease (AD) and mixed dementia. We included 35 studies. Most studies are heterogeneous, focus exclusively on AD, and show small benefits in terms of cognitive and functional scales. The overall evidence seems to suggest a benefit in introducing or maintaining anti-dementia drugs in patients with advanced dementia, but clinical meaningfulness is difficult to ascertain. The issue of costs and caregiver burden is significantly underexplored in this field but also seems to favor treatment continuation, despite a reduced overall effect. The decision of introducing or withdrawing anti-dementia drugs in advanced stages of dementia should be individualized. Future studies with homogeneous designs and outcomes are warranted.

Role of long non-coding RNAs in the pathophysiology of Alzheimer's disease and other dementias

Dementia is the term used to describe a group of cognitive disorders characterized by a decline in memory, thinking, and reasoning abilities that interfere with daily life activities. Examples of dementia include Alzheimer's Disease (AD), Frontotemporal dementia (FTD), Amyotrophic lateral sclerosis (ALS), Vascular dementia (VaD) and Progressive supranuclear palsy (PSP). AD is the most common form of dementia. The hallmark pathology of AD includes formation of β-amyloid (Aβ) oligomers and tau hyperphosphorylation in the brain, which induces neuroinflammation, oxidative stress, synaptic dysfunction, and neuronal apoptosis. Emerging studies have associated long non-coding RNAs (lncRNAs) with the pathogenesis and progression of the neurodegenerative diseases. LncRNAs are defined as RNAs longer than 200 nucleotides that lack the ability to encode functional proteins. LncRNAs play crucial roles in numerous biological functions for their ability to interact with different molecules, such as proteins and microRNAs, and subsequently regulate the expression of their target genes at transcriptional and post-transcriptional levels. In this narrative review, we report the function and mechanisms of action of lncRNAs found to be deregulated in different types of dementia, with the focus on AD. Finally, we discuss the emerging role of lncRNAs as biomarkers of dementias.