The Future of Precision Medicine in the Cure of Alzheimer's Disease

Infections, genetics, and Alzheimer's disease: Exploring the pathogenic factors for innovative therapies

Alzheimer's disease (AD) is a progressive neurodegenerative condition that creates a significant global health challenge and profoundly affects patients and their families. Recent research has highlighted the critical role of microorganisms, particularly viral infections, in the pathogenesis of AD. The involvement of viral infections in AD pathogenesis is predominantly attributed to their ability to induce neuroinflammation and amyloid beta (Aβ) deposition in the brain. The extant research exploring the relationship between viruses and AD has focused largely on Herpesviridae family. Traces of Herpesviruses, such as Herpes Simplex Virus-1 and Epstein Barr Virus, have been found in the brains of patients with AD. These viruses are thought to contribute to the disease progression by triggering chronic inflammatory responses in the brain. They can remain dormant in the brain, and become reactivated due to stress, a secondary viral infection, or immune-senescence in older adults. This review focuses on the association between Herpesviridae and bacterial infections with AD. We explore the genetic factors that might regulate viral illness and discuss clinical trials investigating antiviral and anti-inflammatory agents as possible therapeutic strategies to mitigate cognitive decline in patients with AD. In summary, understanding the interplay between infections, genetic factors, and AD pathogenesis may pave the way for novel therapeutic approaches, facilitating better management and possibly even prevent this debilitating disease.

Unraveling the Complexity of Alzheimer's Disease: Insights into Etiology and Advancements in Treatment Strategies

Alzheimer's disease, a complex and progressive neurological disorder, is the leading cause of late-life dementia. Pathologically, it is marked by the presence of amyloid plaques and neurofibrillary tangles in the brain. Over the past two decades, advancements in understanding the disease's pathogenesis have spurred research into new pharmacological treatments that target its underlying mechanisms. Currently available drugs, such as acetylcholinesterase inhibitors (rivastigmine, galantamine, donepezil) and the NMDA receptor antagonist memantine, primarily address symptoms and are effective only in the later stages of the disease. While these medications can slow disease progression and provide symptomatic relief, they do not offer a cure. Despite having a clear understanding of Alzheimer's neuropathology, the precise mechanisms driving the disease remain elusive. The lack of effective treatments that can stop the start and progression of the disease may be caused by our incomplete understanding of the pathogenic process. New therapeutic targets are now available due to the significant advancements made in pathophysiology over the past few years, which should allow for a direct attack on the underlying illness process. The various pathophysiological pathways that underlie Alzheimer's disease and how it is managed by conventional medication therapy, including current exploratory therapeutic options, are covered in this review article. Innovative, beneficial policies are essential to determine and progress therapeutic molecules to defend against AD.

A novel Alzheimer detection rapid-testing low-cost technique by a gate engineered gate stack dual-gate FET device

This study explores a quick, low-cost method to detect Alzheimer's disease (AD) by evaluating the accomplishment of a Gate-Stack (GS) Field Effect Transistor (FET). We investigate Single-Metal (SM), Dual-Metal (DM), and Tri-Metal Double Gate (DG) configurations, where cavities have been created by etching the oxide layer underneath the gate to immobilize grey matter samples collected through Solid-phase microextraction (SPME). Healthy and AD-affected grey matter have different dielectric characteristics at high frequencies. The dielectric constant of the etched nanocavities changes when the sample, which was formerly filled with air, is immobilized in the nanocavities. The alteration in the device drain current as well as performance at 2.4 GHz has been connected to the specimen's modified dielectric constant. To distinguish between the grey matter samples from AD patients and healthy individuals, the ION/IOFF of the suggested device along with the variation in device drain current, has been utilized as the foundation for the identification. The SM configuration has been examined by varying the cavity orientation and gate oxide stacking. To monitor the functioning of the suggested devices, the gate metal of the DM and TM devices has been altered, and a comparison has been made between SM, DM, and TM structures. The other recorded work from literature has been compared with the suggested detection technique. To ascertain whether the sample is impacted by AD, the proposed method can be used as a point of care (POC) diagnosis.

Exploring interdisciplinary perspectives on the implementation of personalized medicine and patient-orchestrated care in Alzheimer's disease: A qualitative study within the ABOARD research project

BackgroundThe concepts of 'personalized medicine' and 'patient-orchestrated care' in Alzheimer's disease (AD) lack standard conceptualization, which presents challenges for collaborative and interdisciplinary care.ObjectiveWe explored the interpretations and perspectives of professionals involved in interdisciplinary work on a large-scale project, "ABOARD", with the aim to implement personalized medicine and patient-orchestrated care in AD.MethodsSemi-structured interviews were conducted with 30 professionals and audio-recorded. Two researchers independently coded the data inductively, followed by a thematic analysis.ResultsAccording to professionals across different disciplinary backgrounds (mean age 45.7 years; 53.3% female), personalized medicine pertains to the relevant options that an individual has, informed by biomedical and psychosocial factors, whereas patient-orchestrated care captures factors relevant to the decision-making process. Professionals differed in their views on patient-orchestrated care regarding its desirability and feasibility. The concepts were viewed as similar by professionals, as both involve personal preferences while ultimately assigning responsibility to the clinician. However, implementation challenges persist, and no thematic differences were found between clinicians and other AD-related professionals.ConclusionsAD professionals have shared interpretations and perspectives on implementation of personalized medicine but differed in their views on patient-orchestrated care. Personal preferences are seen as part of personalized medicine, but not yet reflected in definitions in the AD field and beyond. Critical discussions on the challenges and existing doubts are necessary for both personalized medicine and patient-orchestrated care. Multi-level implementation changes are needed for both concepts, which warrants stakeholder involvement as well as support and resources from the entire AD field.

A real-world safety surveillance study of aducanumab through the FDA adverse event reporting system

Background

Alzheimer's disease poses a major public health challenge, with aducanumab's approval in 2021 as the first disease-modifying therapy raising important safety considerations. This study analyzed the Food Drug Administration Adverse Event Reporting System (FAERS) database to evaluate aducanumab's real-world safety profile and identify potential risk factors.

Methods

We conducted a comprehensive pharmacovigilance study using the FAERS database from January 2004 to June 2024, analyzing 510 aducanumab-associated reports from integrated databases containing over 18 million demographic records and 66 million drug records. Safety signals were evaluated using four complementary disproportionality methods: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). Analyses were stratified by age and sex, with adverse events examined at both System Organ Class (SOC) and Preferred Term (PT) levels using SAS 9.4.

Results

Among 510 aducanumab-associated adverse event reports, predominantly from elderly patients (55.49% aged ≥65 years), nervous system disorders were the most frequent (53.24%, n = 583). Amyloid related imaging abnormality-oedema/effusion (ARIA-E) and Amyloid related imaging abnormality-microhaemorrhages and haemosiderin deposits (ARIA-H) emerged as the most significant safety signals (ROR: 53,538.3 and 38,187.9, respectively). Sex-stratified analysis showed comparable safety profiles between males and females, with ARIA-E related events, ARIA-H related events, maintaining strong signals across all age groups, particularly in patients ≥75 years. The median time to adverse event onset was 146.0 days (IQR: 80.0-195.0). Temporal analysis revealed increasing signal strength for ARIA-related events from 2004-2024, with notable intensification during 2022-2023.

Conclusion

Our real-world analysis identified ARIA-related events as the primary safety concern for aducanumab, typically occurring within 146 days of treatment initiation, with comparable safety profiles across sex but heightened risks in patients ≥75 years. These findings support aducanumab's viability as a therapeutic option while emphasizing the critical importance of rigorous monitoring protocols, particularly for ARIA events during the first year of treatment.

Phenotyping to predict 12-month health outcomes of older general medicine patients

BACKGROUND

A variety of unsupervised learning algorithms have been used to phenotype older patients, enabling directed care and personalised treatment plans. However, the ability of the clusters to accurately discriminate for the risk of older patients, may vary depending on the methods employed.

AIMS

To compare seven clustering algorithms in their ability to develop patient phenotypes that accurately predict health outcomes.

METHODS

Data was collected for N = 737 older medical inpatients during their hospital stay for five different types of medical data (ICD-10 codes, ATC drug codes, laboratory, clinic and frailty data). We trialled five unsupervised learning algorithms (K-means, K-modes, hierarchical clustering, latent class analysis (LCA), and DBSCAN) and two graph-based approaches to create separate clusters for each method and datatype. These were used as input for a random forest classifier to predict eleven health outcomes: mortality at one, three, six and 12 months, in-hospital falls and delirium, length-of-stay, outpatient visits, and readmissions at one, three and six months.

RESULTS

The overall median area-under-the-curve (AUC) across the eleven outcomes for the seven methods were (from highest to lowest) 0.758 (hierarchical), 0.739 (K-means), 0.722 (KG-Louvain), 0.704 (KNN-Louvain), 0.698 (LCA), 0.694 (DBSCAN) and 0.656 (K-modes). Overall, frailty data was most important data type for predicting mortality, ICD-10 disease codes for predicting readmissions, and laboratory data the most important for predicting falls.

CONCLUSIONS

Clusters created using hierarchical, K-means and Louvain community detection algorithms identified well-separated patient phenotypes that were consistently associated with age-related adverse health outcomes. Frailty data was the most valuable data type for predicting most health outcomes.

Polymerase Chain Reaction Chips for Biomarker Discovery and Validation in Drug Development

Polymerase chain reaction (PCR) chips are advanced, microfluidic platforms that have revolutionized biomarker discovery and validation because of their high sensitivity, specificity, and throughput levels. These chips miniaturize traditional PCR processes for the speed and precision of nucleic acid biomarker detection relevant to advancing drug development. Biomarkers, which are useful in helping to explain disease mechanisms, patient stratification, and therapeutic monitoring, are hard to identify and validate due to the complexity of biological systems and the limitations of traditional techniques. The challenges to which PCR chips respond include high-throughput capabilities coupled with real-time quantitative analysis, enabling researchers to identify novel biomarkers with greater accuracy and reproducibility. More recent design improvements of PCR chips have further expanded their functionality to also include digital and multiplex PCR technologies. Digital PCR chips are ideal for quantifying rare biomarkers, which is essential in oncology and infectious disease research. In contrast, multiplex PCR chips enable simultaneous analysis of multiple targets, therefore simplifying biomarker validation. Furthermore, single-cell PCR chips have made it possible to detect biomarkers at unprecedented resolution, hence revealing heterogeneity within cell populations. PCR chips are transforming drug development, enabling target identification, patient stratification, and therapeutic efficacy assessment. They play a major role in the development of companion diagnostics and, therefore, pave the way for personalized medicine, ensuring that the right patient receives the right treatment. While this tremendously promising technology has exhibited many challenges regarding its scalability, integration with other omics technologies, and conformity with regulatory requirements, many still prevail. Future breakthroughs in chip manufacturing, the integration of artificial intelligence, and multi-omics applications will further expand PCR chip capabilities. PCR chips will not only be important for the acceleration of drug discovery and development but also in raising the bar in improving patient outcomes and, hence, global health care as these technologies continue to mature.

Promising Natural Remedies for Alzheimer's Disease Therapy

This study examines the intricacies of Alzheimer's disease (AD), its origins, and the potential advantages of various herbal extracts and natural compounds for enhancing memory and cognitive performance. Future studies into AD treatments are encouraged by the review's demonstration of the effectiveness of phytoconstituents that were extracted from a number of plants. In addition to having many beneficial effects, such as improved cholinergic and cognitive function, herbal medicines are also much less harmful, more readily available, and easier to use than other treatments. They also pass without difficulty through the blood-brain barrier (BBB). This study focused on natural substances and their effects on AD by using academic databases to identify peer-reviewed studies published between 2015 and 2024. According to the literature review, 66 phytoconstituents that were isolated from 21 distinct plants have shown efficacy, which could be encouraging for future research on AD therapies. Since most clinical trials produce contradictory results, the study suggests that larger-scale studies with longer treatment durations are necessary to validate or refute the therapeutic efficacy of herbal AD treatments.

Recent Insights into the Neurobiology of Alzheimer's Disease and Advanced Treatment Strategies

In recent years, significant advancements have been made in understanding Alzheimer's disease from both neurobiological and clinical perspectives. Exploring the complex systems underlying AD has unveiled insights that could potentially revolutionize therapeutic approaches. Recent investigations have highlighted intricate interactions among genetic, molecular, and environmental factors in AD. Optimism arises from neurobiological advancements and diverse treatment options, potentially slowing or halting disease progression. Amyloid-beta plaques and tau protein tangles crucially influence AD onset and progression. Emerging treatments involve diverse strategies, such as approaches targeting multiple pathways involved in AD pathogenesis, such as inflammation, oxidative stress, and synaptic dysfunction pathways. Clinical trials using humanized monoclonal antibodies, focusing on immunotherapies eliminating amyloid-beta, have shown promise. Nonpharmacological interventions such as light therapy, electrical stimulation, cognitive training, physical activity, and dietary changes have drawn attention for their potential to slow cognitive aging and enhance brain health. Precision medicine, which involves tailoring therapies to individual genetic and molecular profiles, has gained traction. Ongoing research and interdisciplinary collaboration are expected to yield more effective treatments.

Developing and applying potentially scalable recruitment strategies to accelerate ADRD research participation of Black adults

More than 2 million older Americans from underrepresented racial and ethnic minority groups (URGs) have early-stage Alzheimer's disease and related dementias (ADRD). There are very few scalable recruitment strategies, particularly for Black older adults, to accelerate participation in ADRD research. The Indiana Alzheimer's Disease Research Center (IADRC) and its Community Advisory Board developed and implemented the innovative RAAISE-D Framework. This Framework informed the creation of community-first recruitment strategies designed to accelerate participation of Black older adults in ADRD research. Preliminary outcomes from its implementation included the doubling of Black adult enrollment (46, 13.4% to 101, 26.9%) from April 2020 to April 2024. Black adults were more likely to have normal cognition, be female, and ≤ 12 years of education than non-Hispanic White adults. The RAAISE-D Framework identified key concepts for URG focused recruitment strategies which successfully accelerated enrollment of Black adults in ADRD research and could be generalized to other URGs. HIGHLIGHTS: RAAISE-D Framework provides adaptable URG recruitment strategies. IADRC CAB-researcher partnership was the foundation of community-first methodology. RAAISE-D Framework doubled the Black enrollment in the IADRC in 4 years.

Non-coding RNAs in the pathogenesis of Alzheimer's disease: β-amyloid aggregation, Tau phosphorylation and neuroinflammation

Alzheimer's disease is a progressive neurodegenerative disorder primarily affecting individuals aged 65 and older, characterized by cognitive decline and diminished quality of life. The molecular hallmarks of AD include extracellular β-amyloid plaques, intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein, and chronic neuroinflammation. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), have emerged as potential therapeutic targets due to their regulatory roles in AD pathogenesis. For example, miR-124 has been shown to modulate Aβ levels, while lncRNAs such as BACE1-AS regulate the expression of BACE1, a crucial enzyme in Aβ production. Transcriptomic studies of AD patients have revealed dysregulation of ncRNA expression, further supporting their involvement in disease progression. This review examines the regulatory functions of ncRNAs in AD, focusing on their impact on Aβ, tau hyperphosphorylation, and neuroinflammation. Additionally, we discuss the emerging role of ncRNAs in liquid-liquid phase separation and the formation of protein aggregates, key processes contributing to AD pathology.

Weight trajectories in aging humanized APOE mice with translational validity to human Alzheimer's risk population: A retrospective analysis

Translational validity of mouse models of Alzheimer's disease (AD) is variable. Because change in weight is a well-documented precursor of AD, we investigated whether diversity of human AD risk weight phenotypes was evident in a longitudinally characterized cohort of 1,196 female and male humanized APOE (hAPOE) mice, monitored up to 28 months of age which is equivalent to 81 human years. Autoregressive Hidden Markov Model (AHMM) incorporating age, sex, and APOE genotype was employed to identify emergent weight trajectories and phenotypes. In the hAPOE-AD mouse cohort, five distinct weight trajectories emerged: three trajectories were associated with a weight loss phenotype (36% of mice, n = 426), one with weight gain (13% of mice, n = 152), and one trajectory of no change in weight (34% of mice, n = 403). The AHMM model findings were validated with post-hoc survival analyses, revealing differences in survival rates across the five identified phenotypes. Further validation was performed using body composition and plasma β-amyloid data from mice within the identified gain, loss and stable weight trajectories. Weight gain trajectory was associated with elevated plasma β-amyloid levels, higher body fat composition, lower survival rates and a greater proportion of APOE4/4 carriers. In contrast, weight loss was associated with greater proportion of hAPOE3/4 carriers, better survival rates and was predominantly male. The association between weight change and AD risk observed in humans was mirrored in the hAPOE-AD mouse model. Weight trajectories of APOE3/3 mice were equally distributed across weight gain, loss and stability. Surprisingly, despite genetic uniformity, comparable housing, diet and handling, distinct weight trajectories and divergence points emerged for subpopulations. These data are consistent with the heterogeneity observed in the human population for change in body weight during aging and highlight the importance of longitudinal phenotypic characterization of mouse aging to advance the translational validity of preclinical AD mouse models.

Beyond Amyloid and Tau: The Critical Role of Microglia in Alzheimer's Disease Therapeutics

Alzheimer's disease (AD) is traditionally viewed through the lens of the amyloid cascade hypothesis, implicating amyloid-beta and tau protein aggregates as the main pathological culprits. However, burgeoning research points to the brain's resident immune cells, microglia, as critical players in AD pathogenesis, progression, and potential therapeutic interventions. This review examines the dynamic roles of microglia within the intricate framework of AD. We detail the involvement of these immune cells in neuroinflammation, explaining how their activation and response fluctuations may influence the disease trajectory. We further elucidate the complex relationship between microglia and amyloid-beta pathology. This study highlights the dual nature of these cells, which contribute to both aggregation and clearance of the amyloid-beta protein. Moreover, an in-depth analysis of the interplay between microglia and tau unveils the significant, yet often overlooked, impact of this interaction on neurodegeneration in AD. Shifting from the conventional therapeutic approaches, we assess the current AD treatments primarily targeting amyloid and tau and introduce novel strategies that involve manipulating microglial functions. These innovative methods herald a potential paradigm shift in the management of AD. Finally, we explore the burgeoning field of precision diagnosis and the pursuit of robust AD biomarkers. We underline how a more profound comprehension of microglial biology could enrich these essential areas, potentially paving the way for more accurate diagnostic tools and tailored treatment strategies. In conclusion, this review expands on the conventional perspective of AD pathology and treatment, drawing attention to the multifaceted roles of microglia. As we continue to enhance our understanding of these cells, microglial-focused therapeutic interventions emerge as a promising frontier to bolster our arsenal to fight against AD.

Exploring sex differences in Alzheimer's disease: a comprehensive analysis of a large patient cohort from a memory unit

BACKGROUND

Alzheimer's disease (AD) stands as the leading cause of dementia worldwide, and projections estimate over 150 million patients by 2050. AD prevalence is notably higher in women, nearly twice that of men, with discernible sex differences in certain risk factors. To enhance our understanding of how sex influences the characteristics of AD patients and its potential impact on the disease trajectory, we conducted a comprehensive analysis of demographic, clinical, cognitive, and genetic data from a sizable and well-characterized cohort of AD dementia patients at a memory clinic in Barcelona, Spain.

METHODS

The study cohort comprised individuals with probable and possible AD dementia with a Clinical Dementia Rating (CDR) score between 1 and 3 diagnosed at the Memory Unit from Ace Alzheimer Center Barcelona, Spain, between 2008 and 2018. We obtained cognitive baseline data and follow up scores for the Mini-Mental State Examination (MMSE), the CDR scale, and the neuropsychological battery used in our center (NBACE). We employed various statistical techniques to assess the impact of sex on cognitive evolution in these dementia patients, accounting for other sex-related risk factors identified through Machine Learning methods.

RESULTS

The study cohort comprised a total of 6108 individuals diagnosed with AD dementia during the study period (28.4% males and 71.6% females). MMSE scores exhibited an average decline of approximately two units per year, unaffected by sex. Similarly, the decline in most neuropsychological functions assessed by NBACE did not exhibit significant differences between males and females. However, we observed that women diagnosed with mild AD dementia progressed more rapidly based on their CDR score (HR = 2.57, 95%CI:2.33-2.84) than men (HR = 2.03, 95%CI: 1.71-2.41) (p-interaction = 0.01).

CONCLUSIONS

Our findings do not strongly support the notion that sex significantly modifies the clinical progression of AD dementia based on cognitive data. Further research is essential to validate whether women with mild AD dementia indeed progress more rapidly than men at a similar stage and to delve into the potential underlying reasons for this finding.

Retinal Microstructural and Microvascular Changes in Alzheimer Disease: A Review

"The eyes are a window to the brain," prompting the investigation of whether retinal biomarkers can indicate Alzheimer disease (AD) and cognitive impairment. AD is a neurodegenerative condition with a lengthy preclinical phase where pathologic changes in the central nervous system (CNS) occur before clinical symptoms. Mild cognitive impairment (MCI) often precedes AD. As part of the CNS, the retina exhibits similar pathologic changes related to AD as those seen in the brains of patients with MCI. Noninvasive imaging technologies such as optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) allow high-resolution visualization of the retina, providing an opportunity to screen and monitor AD noninvasively. In this review, we summarize the relationship between AD and retinal pathology detected by OCT and OCTA. The most common findings in patients with AD include peripapillary retinal nerve fiber layer thinning, decreased macular thickness, an enlarged foveal avascular zone, and decreased vascular densities in the superficial and deep capillary plexuses. These retinal changes correlate with magnetic resonance imaging (MRI) findings of cerebral atrophy, positron emission tomography (PET) findings of increased amyloid load, and neuropsychological testing results suggesting cognitive dysfunction. We conclude that retinal microstructural and microvascular abnormalities may serve as biomarkers for the early detection and clinical monitoring of AD and as tools for evaluating potential treatment effects. Future studies should focus on standardizing protocols for in vivo ophthalmic imaging to measure retinal pathology in AD and MCI.

The Role of GFAP in Post-Mortem Analysis of Traumatic Brain Injury: A Systematic Review

Traumatic brain injuries (TBIs) are a leading cause of mortality and morbidity, particularly in forensic settings where determining the cause of death and timing of injury is critical. Glial fibrillary acidic protein (GFAP), a biomarker specific to astrocytes, has emerged as a valuable tool in post-mortem analyses of TBI. A PRISMA-based literature search included studies examining GFAP in human post-mortem samples such as brain tissue, cerebrospinal fluid (CSF), serum, and urine. The results highlight that GFAP levels correlate with the severity of brain injury, survival interval, and pathological processes such as astrocyte damage and blood-brain barrier disruption. Immunohistochemistry, ELISA, and molecular techniques were commonly employed for GFAP analysis, with notable variability in protocols and thresholds among studies. GFAP demonstrated high diagnostic accuracy in distinguishing TBI-related deaths from other causes, particularly when analyzed in CSF and serum. Furthermore, emerging evidence supports its role in complementing other biomarkers, such as S100B and NFL, to improve diagnostic precision. However, the review also identifies significant methodological heterogeneity and gaps in standardization, which limit the generalizability of findings. Future research should focus on establishing standardized protocols, exploring biomarker combinations, and utilizing advanced molecular tools to enhance the forensic application of GFAP.

Epigenetic biomarkers in Alzheimer's disease: Diagnostic and prognostic relevance

Alzheimer's disease (AD) is a leading cause of cognitive decline in the aging population, presenting a critical need for early diagnosis and effective prognostic tools. Epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNAs, have emerged as promising biomarkers for AD due to their roles in regulating gene expression and potential for reversibility. This review examines the current landscape of epigenetic biomarkers in AD, emphasizing their diagnostic and prognostic relevance. DNA methylation patterns in genes such as APP, PSEN1, and PSEN2 are highlighted for their strong associations with AD pathology. Alterations in DNA methylation at specific CpG sites have been consistently observed in AD patients, suggesting their utility in early detection. Histone modifications, such as acetylation and methylation, also play a crucial role in chromatin remodelling and gene expression regulation in AD. Dysregulated histone acetylation and methylation have been linked to AD progression, making these modifications valuable biomarkers. Non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), further contribute to the epigenetic regulation in AD. miRNAs can modulate gene expression post-transcriptionally and have been found in altered levels in AD, while lncRNAs can influence chromatin structure and gene expression. The presence of these non-coding RNAs in biofluids like blood and cerebrospinal fluid positions them as accessible and minimally invasive biomarkers. Technological advancements in detecting and quantifying epigenetic modifications have propelled the field forward. Techniques such as next-generation sequencing, bisulfite sequencing, and chromatin immunoprecipitation assays offer high sensitivity and specificity, enabling the detailed analysis of epigenetic changes in clinical samples. These tools are instrumental in translating epigenetic research into clinical practice. This review underscores the potential of epigenetic biomarkers to enhance the early diagnosis and prognosis of AD, paving the way for personalized therapeutic strategies and improved patient outcomes. The integration of these biomarkers into clinical workflows promises to revolutionize AD management, offering hope for better disease monitoring and intervention.

Targeting inflammation and gut microbiota with antibacterial therapy: Implications for central nervous system health

The complex symbiotic relationship between inflammation, the gut microbiota, and the central nervous system (CNS) has become a pivotal focus of contemporary biomedical research. Inflammation, as a physiological defense mechanism, plays a dual role as both a protective and pathological factor, and is intricately associated with gut microbiota homeostasis, often termed the "second brain." The gutbrain axis (GBA) exemplifies this multifaceted interaction, where gut health exerts significantly regulatory effects on CNS functions. Antibacterial therapies represent both promising and challenging strategies for modulating inflammation and gut microbiota composition to confer CNS benefits. However, while such therapies may exert positive modulatory effects on the gut microbiota, they also carry the potential to disrupt microbial equilibrium, potentially exacerbating neurological dysfunction. Recent advances have provided critical insights into the therapeutic implications of antibacterial interventions; nevertheless, the application of these therapies in the context of CNS health warrants a judicious and evidence-based approach. As research progresses, deeper investigation into the microbial-neural interface is essential to fully realize the potential of therapies targeting inflammation and the gut microbiota for CNS health. Future efforts should focus on refining antibacterial interventions to modulate the gut microbiota while minimizing disruption to microbial balance, thereby reducing risks and enhancing efficacy in CNS-related conditions. In conclusion, despite challenges, a more comprehensive understanding of the GBA, along with precise modulation through targeted antibacterial therapies, offers significant promise for advancing CNS disorder treatment. Continued research in this area will lead to innovative interventions and improved patient outcomes.

Up-regulation of myelin-associated glycoprotein is associated with the ameliorating effect of omega-3 polyunsaturated fatty acids on Alzheimer's disease progression in APP-PS1 transgenic mice

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive behavioral and cognitive impairments. Despite growing evidence of the neuroprotective action of omega-3 polyunsaturated fatty acids (PUFAs), the effects and mechanism of omega-3 PUFAs on AD control are yet to be clarified. By crossing male heterozygous fat-1 mice with female APP/PS1 mice, we assessed whether elevated tissue omega-3 PUFA levels could alleviate AD progression and their underlying mechanism among the offspring WT, APP/PS1 and APP/PS1 × fat-1 groups at various stages. We found that the fat-1 transgene significantly increased brain omega-3 PUFA and docosahexaenoic acid (DHA) levels, and cognitive deficits together with brain Aβ-40 and Aβ-42 levels in 6-month-old APP/PS1 × fat-1 mice were significantly lower than those in APP/PS1 mice. Subsequently, the tandem mass tag (TMT) method revealed the elevated expression of cortex and hippocampus myelin-associated glycoprotein (MAG) in APP/PS1 × fat-1 mice at 2-6 months. Furthermore, GO and KEGG pathway enrichment analysis suggested that the MAG-related myelin sheath pathway and its interaction with AD were regulated by omega-3 PUFAs. Moreover, subsequent western blot assays showed that both increased endogenous omega-3 levels and in vitro supplemented DHA up-regulated MAG expression, and the AD-protective effects of DHA on LPS-induced BV2 cells were significantly weakened when MAG was inhibited by si-RNA transfection. In summary, our study suggested that omega-3 PUFAs might protect against AD by up-regulating MAG expression.

Therapeutic Potential of Ramalin Derivatives with Enhanced Stability in the Treatment of Alzheimer's Disease

Alzheimer's disease (AD) remains a significant public health challenge with limited effective treatment options. Ramalin, a compound derived from Antarctic lichens, has shown potential in the treatment of AD because of its strong antioxidant and anti-inflammatory properties. However, its instability and toxicity have hindered the development of Ramalin as a viable therapeutic agent. The primary objective of this study was to synthesize and evaluate novel Ramalin derivatives with enhanced stabilities and reduced toxic profiles, with the aim of retaining or improving their therapeutic potential against AD. The antioxidant, anti-inflammatory, anti-BACE-1, and anti-tau activities of four synthesized Ramalin derivatives (i.e., RA-Hyd-Me, RA-Hyd-Me-Tol, RA-Sali, and RA-Benzo) were evaluated. These derivatives demonstrated significantly improved stabilities compared to the parent compound, with RA-Sali giving the most promising results. More specifically, RA-Sali exhibited a potent BACE-1 inhibitory activity and effectively reduced tau phosphorylation, a critical factor in AD pathology. Despite exhibiting reduced antioxidant activities compared to the parent compound, these derivatives represent a potential multi-targeted approach for AD treatment, marking a significant step forward in the development of stable and effective AD therapeutics.

Personalized Medicine Approach to Proteomics and Metabolomics of Cytochrome P450 Enzymes: A Narrative Review

Cytochrome P450 enzymes (CYPs) represent a diverse family of heme-thiolate proteins involved in the metabolism of a wide range of endogenous compounds and xenobiotics. In recent years, proteomics and metabolomics have been used to obtain a comprehensive insight into the role of CYPs in health and disease aspects. The objective of the present work is to better understand the status of proteomics and metabolomics in CYP research in optimizing therapeutics and patient safety from a personalized medicine approach. The literature used in this narrative review was procured by electronic search of PubMed, Medline, Embase, and Google Scholar databases. The following keywords were used in combination to identify related literature: "proteomics," "metabolomics," "cytochrome P450," "drug metabolism," "disease conditions," "proteome," "liquid chromatography-mass spectrometry," "integration," "metabolites," "pathological conditions." We reviewed studies that utilized proteomics and metabolomics approaches to explore the multifaceted roles of CYPs in identifying disease markers and determining the contribution of CYP enzymes in developing treatment strategies. The applications of various cutting-edge analytical techniques, including liquid chromatography-mass spectrometry, nuclear magnetic resonance, and bioinformatics analyses in CYP proteomics and metabolomics studies, have been highlighted. The identification of CYP enzymes through metabolomics and/or proteomics in various disease conditions provides key information in the diagnostic and therapeutic landscape. Leveraging both proteomics and metabolomics presents a powerful approach for an exhaustive exploration of the multifaceted roles played by CYP enzymes in personalized medicine. Proteomics and metabolomics have enabled researchers to unravel the complex connection between CYP enzymes and metabolic markers associated with specific diseases. As technology and methodologies evolve, an integrated approach promises to further elucidate the role of CYPs in human health and disease, potentially ushering in a new era of personalized medicine.

Recent Advances in Therapeutics for the Treatment of Alzheimer's Disease

The most prevalent chronic neurodegenerative illness in the world is Alzheimer's disease (AD). It results in mental symptoms including behavioral abnormalities and cognitive impairment, which have a substantial financial and psychological impact on the relatives of the patients. The review discusses various pathophysiological mechanisms contributing to AD, including amyloid beta, tau protein, inflammation, and other factors, while emphasizing the need for effective disease-modifying therapeutics that alter disease progression rather than merely alleviating symptoms. This review mainly covers medications that are now being studied in clinical trials or recently approved by the FDA that fall under the disease-modifying treatment (DMT) category, which alters the progression of the disease by targeting underlying biological mechanisms rather than merely alleviating symptoms. DMTs focus on improving patient outcomes by slowing cognitive decline, enhancing neuroprotection, and supporting neurogenesis. Additionally, the review covers amyloid-targeting therapies, tau-targeting therapies, neuroprotective therapies, and others. This evaluation specifically looked at studies on FDA-approved novel DMTs in Phase II or III development that were carried out between 2021 and 2024. A thorough review of the US government database identified clinical trials of biologics and small molecule drugs for 14 agents in Phase I, 34 in Phase II, and 11 in Phase III that might be completed by 2028.

The role of inflammation in neurological disorders: a brief overview of multiple sclerosis, Alzheimer's, and Parkinson's disease'

Neuroinflammation is a central feature in the pathophysiology of several neurodegenerative diseases, including MS, AD, and PD. This review aims to synthesize current research on the role of inflammation in these conditions, emphasizing the potential of inflammatory biomarkers for diagnosis and treatment. We highlight recent findings on the mechanisms of neuroinflammation, the utility of biomarkers in disease differentiation, and the implications for therapeutic strategies. Advances in understanding inflammatory pathways offer promising avenues for developing targeted interventions to improve patient outcomes. Future research should focus on validating these biomarkers in larger cohorts and integrating them into clinical practice to enhance diagnostic accuracy and therapeutic efficacy.

Network dynamics-based subtyping of Alzheimer's disease with microglial genetic risk factors

BACKGROUND

The potential of microglia as a target for Alzheimer's disease (AD) treatment is promising, yet the clinical and pathological diversity within microglia, driven by genetic factors, poses a significant challenge. Subtyping AD is imperative to enable precise and effective treatment strategies. However, existing subtyping methods fail to comprehensively address the intricate complexities of AD pathogenesis, particularly concerning genetic risk factors. To address this gap, we have employed systems biology approaches for AD subtyping and identified potential therapeutic targets.

METHODS

We constructed patient-specific microglial molecular regulatory network models by utilizing existing literature and single-cell RNA sequencing data. The combination of large-scale computer simulations and dynamic network analysis enabled us to subtype AD patients according to their distinct molecular regulatory mechanisms. For each identified subtype, we suggested optimal targets for effective AD treatment.

RESULTS

To investigate heterogeneity in AD and identify potential therapeutic targets, we constructed a microglia molecular regulatory network model. The network model incorporated 20 known risk factors and crucial signaling pathways associated with microglial functionality, such as inflammation, anti-inflammation, phagocytosis, and autophagy. Probabilistic simulations with patient-specific genomic data and subsequent dynamics analysis revealed nine distinct AD subtypes characterized by core feedback mechanisms involving SPI1, CASS4, and MEF2C. Moreover, we identified PICALM, MEF2C, and LAT2 as common therapeutic targets among several subtypes. Furthermore, we clarified the reasons for the previous contradictory experimental results that suggested both the activation and inhibition of AKT or INPP5D could activate AD through dynamic analysis. This highlights the multifaceted nature of microglial network regulation.

CONCLUSIONS

These results offer a means to classify AD patients by their genetic risk factors, clarify inconsistent experimental findings, and advance the development of treatments tailored to individual genotypes for AD.

Genomic Insights into Dementia: Precision Medicine and the Impact of Gene-Environment Interaction

The diagnosis, treatment, and management of dementia provide significant challenges due to its chronic cognitive impairment. The complexity of this condition is further highlighted by the impact of gene-environment interactions. A recent strategy combines advanced genomics and precision medicine methods to explore the complex genetic foundations of dementia. Utilizing the most recent research in the field of neurogenetics, the importance of precise genetic data in explaining the variation seen in dementia patients can be investigated. Gene-environment interactions are important because they influence genetic susceptibilities and aid in the development and progression of dementia. Modified to each patient's genetic profile, precision medicine has the potential to detect groups at risk and make previously unheard-of predictions about the course of diseases. Precision medicine techniques have the potential to completely transform treatment and diagnosis methods. Targeted medications that target genetic abnormalities will probably appear, providing the possibility for more efficient and customized medical interventions. Investigating the relationship between genes and the environment may lead to preventive measures that would enable people to change their surroundings and minimize the risk of dementia, leading to the improved lifestyle of affected people. This paper provides a comprehensive overview of the genomic insights into dementia, emphasizing the pivotal role of precision medicine, and gene-environment interactions.

Development of a robust parallel and multi-composite machine learning model for improved diagnosis of Alzheimer's disease: correlation with dementia-associated drug usage and AT(N) protein biomarkers

Introduction

Machine learning (ML) algorithms and statistical modeling offer a potential solution to offset the challenge of diagnosing early Alzheimer's disease (AD) by leveraging multiple data sources and combining information on neuropsychological, genetic, and biomarker indicators. Among others, statistical models are a promising tool to enhance the clinical detection of early AD. In the present study, early AD was diagnosed by taking into account characteristics related to whether or not a patient was taking specific drugs and a significant protein as a predictor of Amyloid-Beta (Aβ), tau, and ptau [AT(N)] levels among participants.

Methods

In this study, the optimization of predictive models for the diagnosis of AD pathologies was carried out using a set of baseline features. The model performance was improved by incorporating additional variables associated with patient drugs and protein biomarkers into the model. The diagnostic group consisted of five categories (cognitively normal, significant subjective memory concern, early mildly cognitively impaired, late mildly cognitively impaired, and AD), resulting in a multinomial classification challenge. In particular, we examined the relationship between AD diagnosis and the use of various drugs (calcium and vitamin D supplements, blood-thinning drugs, cholesterol-lowering drugs, and cognitive drugs). We propose a hybrid-clinical model that runs multiple ML models in parallel and then takes the majority's votes, enhancing the accuracy. We also assessed the significance of three cerebrospinal fluid biomarkers, Aβ, tau, and ptau in the diagnosis of AD. We proposed that a hybrid-clinical model be used to simulate the MRI-based data, with five diagnostic groups of individuals, with further refinement that includes preclinical characteristics of the disorder. The proposed design builds a Meta-Model for four different sets of criteria. The set criteria are as follows: to diagnose from baseline features, baseline and drug features, baseline and protein features, and baseline, drug and protein features.

Results

We were able to attain a maximum accuracy of 97.60% for baseline and protein data. We observed that the constructed model functioned effectively when all five drugs were included and when any single drug was used to diagnose the response variable. Interestingly, the constructed Meta-Model worked well when all three protein biomarkers were included, as well as when a single protein biomarker was utilized to diagnose the response variable.

Discussion

It is noteworthy that we aimed to construct a pipeline design that incorporates comprehensive methodologies to detect Alzheimer's over wide-ranging input values and variables in the current study. Thus, the model that we developed could be used by clinicians and medical experts to advance Alzheimer's diagnosis and as a starting point for future research into AD and other neurodegenerative syndromes.

More than a number: Incorporating the aged phenotype to improve in vitro and in vivo modeling of neurodegenerative disease

Age is the number one risk factor for developing a neurodegenerative disease (ND), such as Alzheimer's disease (AD) or Parkinson's disease (PD). With our rapidly ageing world population, there will be an increased burden of ND and need for disease-modifying treatments. Currently, however, translation of research from bench to bedside in NDs is poor. This may be due, at least in part, to the failure to account for the potential effect of ageing in preclinical modelling of NDs. While ageing can impact upon physiological response in multiple ways, only a limited number of preclinical studies of ND have incorporated ageing as a factor of interest. Here, we evaluate the aged phenotype and highlight the critical, but unmet, need to incorporate aspects of this phenotype into both the in vitro and in vivo models used in ND research. Given technological advances in the field over the past several years, we discuss how these could be harnessed to create novel models of ND that more readily incorporate aspects of the aged phenotype. This includes a recently described in vitro panel of ageing markers, which could help lead to more standardised models and improve reproducibility across studies. Importantly, we cannot assume that young cells or animals yield the same responses as seen in the context of ageing; thus, an improved understanding of the biology of ageing, and how to appropriately incorporate this into the modelling of ND, will ensure the best chance for successful translation of new therapies to the aged patient.

Mild Cognitive Impairment Detection through Gait Analysis and Standard Cameras

Alzheimer's disease (AD) is a progressive neurodegenerative disease impacting older adults' cognitive and functional abilities. Early detection in the mild cognitive impairment (MCI) stage is vital for timely interventions to slow down the disease progression to AD. This study introduces a novel MCI detection that emphasizes accessibility and ease of use, utilizing a regular camera and pose estimation. Using the OpenPose algorithm, we analyzed 25 body joints during walking and extracted 48 gait features, identifying 17 key features that significantly distinguish MCI from healthy controls (HC). Our approach, combining statistical analysis, signal processing, and a machine learning model using a support vector machine, achieved an accuracy and F-score of 86.81% and 82.35%, respectively. This confirms the effectiveness of everyday camera data and pose estimation in detecting significant gait differences between MCI and HC, offering an easy, cost-effective solution for early MCI detection and monitoring in non-clinical settings. It removes the barriers of sophisticated equipment and specialized expertise, paving the way for practical remote monitoring and AD early intervention.

Exploratory Tau PET/CT with [11C]PBB3 in Patients with Suspected Alzheimer's Disease and Frontotemporal Lobar Degeneration: A Pilot Study on Correlation with PET Imaging and Cerebrospinal Fluid Biomarkers

Accurately diagnosing Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) is challenging due to overlapping symptoms and limitations of current imaging methods. This study investigates the use of [11C]PBB3 PET/CT imaging to visualize tau pathology and improve diagnostic accuracy. Given diagnostic challenges with symptoms and conventional imaging, [11C]PBB3 PET/CT's potential to enhance accuracy was investigated by correlating tau pathology with cerebrospinal fluid (CSF) biomarkers, positron emission tomography (PET), computed tomography (CT), amyloid-beta, and Mini-Mental State Examination (MMSE). We conducted [11C]PBB3 PET/CT imaging on 24 patients with suspected AD or FTLD, alongside [11C]PiB PET/CT (13 patients) and [18F]FDG PET/CT (15 patients). Visual and quantitative assessments of [11C]PBB3 uptake using standardized uptake value ratios (SUV-Rs) and correlation analyses with clinical assessments were performed. The scans revealed distinct tau accumulation patterns; 13 patients had no or faint uptake (PBB3-negative) and 11 had moderate to pronounced uptake (PBB3-positive). Significant inverse correlations were found between [11C]PBB3 SUV-Rs and MMSE scores, but not with CSF-tau or CSF-amyloid-beta levels. Here, we show that [11C]PBB3 PET/CT imaging can reveal distinct tau accumulation patterns and correlate these with cognitive impairment in neurodegenerative diseases. Our study demonstrates the potential of [11C]PBB3-PET imaging for visualizing tau pathology and assessing disease severity, offering a promising tool for enhancing diagnostic accuracy in AD and FTLD. Further research is essential to validate these findings and refine the use of tau-specific PET imaging in clinical practice, ultimately improving patient care and treatment outcomes.

Chemistry, Biological Activities, and Pharmacological Properties of Gastrodin: Mechanism Insights

Gastrodin, a bioactive compound derived from the rhizome of the orchid Gastrodia elata, exhibits a diverse range of biological activities. With documented neuroprotective, anti-inflammatory, antioxidant, anti-apoptotic, and anti-tumor effects, gastrodin stands out as a multifaceted therapeutic agent. Notably, it has demonstrated efficacy in protecting against neuronal damage and enhancing cognitive function in animal models of Alzheimer's disease, Parkinson's disease, and cerebral ischemia. Additionally, gastrodin showcases immunomodulatory effects by mitigating inflammation and suppressing the expression of inflammatory cytokines. Its cytotoxic activity involves the inhibition of angiogenesis, suppression of tumor growth, and induction of apoptosis. This comprehensive review seeks to elucidate the myriad potential effects of Gastrodin, delving into the intricate molecular mechanisms underpinning its pharmacological properties. The findings underscore the therapeutic potential of gastrodin in addressing various conditions linked to neuroinflammation and cancer.

Therapeutic approaches in proteinopathies

A family of maladies known as amyloid disorders, proteinopathy, or amyloidosis, are characterized by the accumulation of abnormal protein aggregates containing cross-β-sheet amyloid fibrils in many organs and tissues. Often, proteins that have been improperly formed or folded make up these fibrils. Nowadays, most treatments for amyloid illness focus on managing symptoms rather than curing or preventing the underlying disease process. However, recent advances in our understanding of the biology of amyloid diseases have led to the development of innovative therapies that target the emergence and accumulation of amyloid fibrils. Examples of these treatments include the use of small compounds, monoclonal antibodies, gene therapy, and others. In the end, even if the majority of therapies for amyloid diseases are symptomatic, greater research into the biology behind these disorders is identifying new targets for potential therapy and paving the way for the development of more effective treatments in the future.

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.

Alzheimer's Disease: A Suitable Case for Treatment with Precision Medicine?

Alzheimer's disease (AD) is the most common cause of neurodegenerative impairment in elderly people. Clinical characteristics include short-term memory loss, confusion, hallucination, agitation, and behavioural disturbance. Owing to evolving research in biomarkers AD can be discovered at early onset, but the disease is currently considered a continuum, which suggests that pharmacotherapy is most efficacious in the preclinical phase, possibly 15 - 20 years before discernible onset. Present developments in AD therapy aim to respond to this understanding and go beyond the drug families that relieve clinical symptoms. Another important factor in this development is the emergence of precision medicine that aims to tailor treatment to specific patients or patient subgroups. This relatively new platform would categorize AD patients on the basis of parameters like clinical aspects, brain imaging, genetic profiling, clinical genetics and epidemiological factors. This review enlarges on recent progress in the design and clinical use of antisense molecules, antibodies, antioxidants, small molecules and gene editing to stop AD progress and possibly reverse the disease on the basis of relevant biomarkers.

Molecular Mechanisms Linking Osteoarthritis and Alzheimer's Disease: Shared Pathways, Mechanisms and Breakthrough Prospects

Alzheimer's disease (AD) is a progressive neurodegenerative disease mostly affecting the elderly population. It is characterized by cognitive decline that occurs due to impaired neurotransmission and neuronal death. Even though deposition of amyloid beta (Aβ) peptides and aggregation of hyperphosphorylated TAU have been established as major pathological hallmarks of the disease, other factors such as the interaction of genetic and environmental factors are believed to contribute to the development and progression of AD. In general, patients initially present mild forgetfulness and difficulty in forming new memories. As it progresses, there are significant impairments in problem solving, social interaction, speech and overall cognitive function of the affected individual. Osteoarthritis (OA) is the most recurrent form of arthritis and widely acknowledged as a whole-joint disease, distinguished by progressive degeneration and erosion of joint cartilage accompanying synovitis and subchondral bone changes that can prompt peripheral inflammatory responses. Also predominantly affecting the elderly, OA frequently embroils weight-bearing joints such as the knees, spine and hips leading to pains, stiffness and diminished joint mobility, which in turn significantly impacts the patient's standard of life. Both infirmities can co-occur in older adults as a result of independent factors, as multiple health conditions are common in old age. Additionally, risk factors such as genetics, lifestyle changes, age and chronic inflammation may contribute to both conditions in some individuals. Besides localized peripheral low-grade inflammation, it is notable that low-grade systemic inflammation prompted by OA can play a role in AD pathogenesis. Studies have explored relationships between systemic inflammatory-associated diseases like obesity, hypertension, dyslipidemia, diabetes mellitus and AD. Given that AD is the most common form of dementia and shares similar risk factors with OA-both being age-related and low-grade inflammatory-associated diseases, OA may indeed serve as a risk factor for AD. This work aims to review literature on molecular mechanisms linking OA and AD pathologies, and explore potential connections between these conditions alongside future prospects and innovative treatments.

A Review of the Common Neurodegenerative Disorders: Current Therapeutic Approaches and the Potential Role of Bioactive Peptides

Neurodegenerative disorders, which include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS), represent a significant and growing global health challenge. Current therapies predominantly focus on symptom management rather than altering disease progression. In this review, we discuss the major therapeutic strategies in practice for these disorders, highlighting their limitations. For AD, the mainstay treatments are cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists. For PD, dopamine replacement therapies, including levodopa, are commonly used. HD is managed primarily with symptomatic treatments, and reusable extends survival in ALS. However, none of these therapies halts or substantially slows the neurodegenerative process. In contrast, this review highlights emerging research into bioactive peptides as potential therapeutic agents. These naturally occurring or synthetically designed molecules can interact with specific cellular targets, potentially modulating disease processes. Preclinical studies suggest that bioactive peptides may mitigate oxidative stress, inflammation, and protein misfolding, which are common pathological features in neurodegenerative diseases. Clinical trials using bioactive peptides for neurodegeneration are limited but show promising initial results. For instance, hemiacetal, a γ-secretase inhibitor peptide, has shown potential in AD by reducing amyloid-beta production, though its development was discontinued due to side effects. Despite these advancements, many challenges remain, including identifying optimal peptides, confirming their mechanisms of action, and overcoming obstacles related to their delivery to the brain. Future research should prioritize the discovery and development of novel bioactive peptides and improve our understanding of their pharmacokinetics and pharmacodynamics. Ultimately, this approach may lead to more effective therapies for neurodegenerative disorders, moving beyond symptom management to potentially modify the course of these devastating diseases.

The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment

Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.

Alzheimer's disease: The role of proteins in formation, mechanisms, and new therapeutic approaches

Alzheimer's disease (AD) is a progressive neurological disorder that affects the central nervous system (CNS), leading to memory and cognitive decline. In AD, the brain experiences three main structural changes: a significant decrease in the quantity of neurons, the development of neurofibrillary tangles (NFT) composed of hyperphosphorylated tau protein, and the formation of amyloid beta (Aβ) or senile plaques, which are protein deposits found outside cells and surrounded by dystrophic neurites. Genetic studies have identified four genes associated with autosomal dominant or familial early-onset AD (FAD): amyloid precursor protein (APP), presenilin 1 (PS1), presenilin 2 (PS2), and apolipoprotein E (ApoE). The formation of plaques primarily involves the accumulation of Aβ, which can be influenced by mutations in APP, PS1, PS2, or ApoE genes. Mutations in the APP and presenilin (PS) proteins can cause an increased amyloid β peptides production, especially the further form of amyloidogenic known as Aβ42. Apart from genetic factors, environmental factors such as cytokines and neurotoxins may also have a significant impact on the development and progression of AD by influencing the formation of amyloid plaques and intracellular tangles. Exploring the causes and implications of protein aggregation in the brain could lead to innovative therapeutic approaches. Some promising therapy strategies that have reached the clinical stage include using acetylcholinesterase inhibitors, estrogen, nonsteroidal anti-inflammatory drugs (NSAIDs), antioxidants, and antiapoptotic agents. The most hopeful therapeutic strategies involve inhibiting activity of secretase and preventing the β-amyloid oligomers and fibrils formation, which are associated with the β-amyloid fibrils accumulation in AD. Additionally, immunotherapy development holds promise as a progressive therapeutic approach for treatment of AD. Recently, the two primary categories of brain stimulation techniques that have been studied for the treatment of AD are invasive brain stimulation (IBS) and non-invasive brain stimulation (NIBS). In this article, the amyloid proteins that play a significant role in the AD formation, the mechanism of disease formation as well as new drugs utilized to treat of AD will be reviewed.

A how-to guide for a precision medicine approach to the diagnosis and treatment of Alzheimer's disease

Article purpose

The clinical approach to Alzheimer's disease (AD) is challenging, particularly in high-functioning individuals. Accurate diagnosis is crucial, especially given the significant side effects, including brain hemorrhage, of newer monoclonal antibodies approved for treating earlier stages of Alzheimer's. Although early treatment is more effective, early diagnosis is also more difficult. Several clinical mimickers of AD exist either separately, or in conjunction with AD pathology, adding to the diagnostic complexity. To illustrate the clinical decision-making process, this study includes de-identified cases and reviews of the underlying etiology and pathology of Alzheimer's and available therapies to exemplify diagnostic and treatment subtleties.

Problem

The clinical presentation of Alzheimer's is complex and varied. Multiple other primary brain pathologies present with clinical phenotypes that can be difficult to distinguish from AD. Furthermore, Alzheimer's rarely exists in isolation, as almost all patients also show evidence of other primary brain pathologies, including Lewy body disease and argyrophilic grain disease. The phenotype and progression of AD can vary based on the brain regions affected by pathology, the coexistence and severity of other brain pathologies, the presence and severity of systemic comorbidities such as cardiac disease, the common co-occurrence with psychiatric diagnoses, and genetic risk factors. Additionally, symptoms and progression are influenced by an individual's brain reserve and cognitive reserve, as well as the timing of the diagnosis, which depends on the demographics of both the patient and the diagnosing physician, as well as the availability of biomarkers.

Methods

The optimal clinical and biomarker strategy for accurately diagnosing AD, common neuropathologic co-morbidities and mimickers, and available medication and non-medication-based treatments are discussed. Real-life examples of cognitive loss illustrate the diagnostic and treatment decision-making process as well as illustrative treatment responses.

Implications

AD is best considered a syndromic disorder, influenced by a multitude of patient and environmental characteristics. Additionally, AD existing alone is a unicorn, as there are nearly always coexisting other brain pathologies. Accurate diagnosis with biomarkers is essential. Treatment response is affected by the variables involved, and the effective treatment of Alzheimer's disease, as well as its prevention, requires an individualized, precision medicine strategy.

MicroRNA (miRNA) Complexity in Alzheimer's Disease (AD)

AD is a complex, progressive, age-related neurodegenerative disorder representing the most common cause of senile dementia and neurological dysfunction in our elderly domestic population. The widely observed heterogeneity of AD is a reflection of the complexity of the AD process itself and the altered molecular-genetic mechanisms operating in the diseased human brain and CNS. One of the key players in this complex regulation of gene expression in human pathological neurobiology are microRNAs (miRNAs) that, through their actions, shape the transcriptome of brain cells that normally associate with very high rates of genetic activity, gene transcription and messenger RNA (mRNA) generation. The analysis of miRNA populations and the characterization of their abundance, speciation and complexity can further provide valuable clues to our molecular-genetic understanding of the AD process, especially in the sporadic forms of this common brain disorder. Current in-depth analyses of high-quality AD and age- and gender-matched control brain tissues are providing pathophysiological miRNA-based signatures of AD that can serve as a basis for expanding our mechanistic understanding of this disorder and the future design of miRNA- and related RNA-based therapeutics. This focused review will consolidate the findings from multiple laboratories as to which are the most abundant miRNA species, both free and exosome-bound in the human brain and CNS, which miRNA species appear to be the most prominently affected by the AD process and review recent developments and advancements in our understanding of the complexity of miRNA signaling in the hippocampal CA1 region of AD-affected brains.