Mild cognitive impairment due to Alzheimer disease: Contemporary approaches to diagnostics and pharmacological intervention

Neuromodulatory effects of leukotriene receptor antagonists: A comprehensive review

Cysteinyl leukotrienes (CysLTs) are central to the pathophysiology of asthma and various inflammatory disorders. Leukotriene receptor antagonists (LTRAs) effectively treat respiratory conditions by targeting cysteinyl leukotriene receptors, CysLT1 and CysLT2 subtypes. This review explores the multifaceted effects of LTs, extending beyond bronchoconstriction. CysLT receptors are not only present in the respiratory system but are also crucial in neuronal signaling pathways. LTRAs modulate these receptors, influencing downstream signaling, calcium levels, inflammation, and oxidative stress (OS) within neurons hinting at broader implications. Recent studies identify novel molecular targets, sparking interest in repurposing LTRAs for therapeutic use. Clinical trials are investigating their potential in neuroinflammation control, particularly in Alzheimer's disease (AD) and Parkinson's diseases (PD). However, montelukast, a long-standing LTRA since 1998, raises concerns due to neuropsychiatric adverse drug reactions (ADRs). Despite widespread use, understanding montelukast's metabolism and underlying ADR mechanisms remains limited. This review comprehensively examines LTRAs' diverse biological effects, emphasizing non-bronchoconstrictive activities. It also analyses plausible mechanisms behind LTRAs' neuronal effects, offering insights into their potential as neurodegenerative disease modulators. The aim is to inform clinicians, researchers, and pharmaceutical developers about LTRAs' expanding roles, particularly in neuroinflammation control and their promising repurposing for neurodegenerative disease management.

Drug Development for Alzheimer's and Parkinson's Disease: Where Do We Go Now?

Neurodegenerative diseases (NDs) are a set of progressive, chronic, and incurable diseases characterized by the gradual loss of neurons, culminating in the decline of cognitive and/or motor functions. Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common NDs and represent an enormous burden both in terms of human suffering and economic cost. The available therapies for AD and PD only provide symptomatic and palliative relief for a limited period and are unable to modify the diseases' progression. Over the last decades, research efforts have been focused on developing new pharmacological treatments for these NDs. However, to date, no breakthrough treatment has been discovered. Hence, the development of disease-modifying drugs able to halt or reverse the progression of NDs remains an unmet clinical need. This review summarizes the major hallmarks of AD and PD and the drugs available for pharmacological treatment. It also sheds light on potential directions that can be pursued to develop new, disease-modifying drugs to treat AD and PD, describing as representative examples some advances in the development of drug candidates targeting oxidative stress and adenosine A2A receptors.

Effects of dance therapy on cognitive and mental health in adults aged 55 years and older with mild cognitive impairment: a systematic review and meta-analysis

BACKGROUND

Individuals with mild cognitive impairment are at high risk of developing dementia. Dance therapy has promising applications in delaying cognitive decline. However, the effectiveness of dance therapy for older adults with mild cognitive impairment is unclear. The objective of this review was to evaluate the effectiveness of dance therapy on global cognitive function, specific cognitive subdomains, quality of life, and mental health in older adults with mild cognitive impairment to enrich health management strategies for dementia.

METHODS

Electronic databases and grey literature were searched from inception up to September 23, 2023. The language was limited to English and Chinese. Relevant studies were screened and assessed for risk of bias. A meta-analysis and subgroup analyses stratified by measurement instrument, dance type, intervention duration, and frequency were conducted using the STATA 16.0 software. This review was conducted in accordance with the PRISMA guidelines.

RESULTS

Ten studies involving 984 participants aged 55 years and over who met the eligibility criteria were included. Dance therapy significantly improved global cognitive function, memory, executive function, attention, language, and mental health (i.e., depression and neuropsychiatric symptoms). However, the effects of dance therapy on processing speed, visuospatial ability, and quality of life in older adults with mild cognitive impairment remain inconclusive. Moreover, dance interventions of longer duration (> 3 months) improved global cognition more than shorter interventions.

CONCLUSION

This review reported that dance therapy was effective in improving global cognitive function, memory, executive function, attention, language, and mental health (i.e., depression and neuropsychiatric symptoms). Hence, it may be an effective non-pharmacological complementary treatment for older adults with mild cognitive impairment.

Review of microbiota gut brain axis and innate immunity in inflammatory and infective diseases

The microbiota gut brain (MGB) axis has been shown to play a significant role in the regulation of inflammatory and infective diseases. Exploring the structure and communication mode of MGB axis is crucial for understanding its role in diseases, and studying the signaling pathways and regulatory methods of MGB axis regulation in diseases is also of profound significance for future clinical research. This article reviews the composition, communication mechanism of MGB axis and its role in inflammatory and infective diseases, including Parkinson's disease (PD), Alzheimer's disease (AD), multiple sclerosis (MS), autism spectrum disorder (ASD), depression, psoriasis, irritable bowel syndrome (IBS), and inflammatory bowel diseases (IBD). In addition, our investigation delved into the regulatory functions of the inflammasome, IFN-I, NF-κB, and PARK7/DJ-1 innate immune signaling pathway in the context of inflammatory and infective diseases. Ultimately, we discussed the efficacy of various interventions, including fecal microbiota transplantation (FMT), antibiotics, probiotics, prebiotics, synbiotics, and postbiotics, in the management of inflammatory and infective diseases. Understanding the role and mechanism of the MGB axis might make positive effects in the treatment of inflammatory and infective diseases.

Current and future therapeutic strategies for Alzheimer's disease: an overview of drug development bottlenecks

Alzheimer's disease (AD) is the most common chronic neurodegenerative disease worldwide. It causes cognitive dysfunction, such as aphasia and agnosia, and mental symptoms, such as behavioral abnormalities; all of which place a significant psychological and economic burden on the patients' families. No specific drugs are currently available for the treatment of AD, and the current drugs for AD only delay disease onset and progression. The pathophysiological basis of AD involves abnormal deposition of beta-amyloid protein (Aβ), abnormal tau protein phosphorylation, decreased activity of acetylcholine content, glutamate toxicity, autophagy, inflammatory reactions, mitochondria-targeting, and multi-targets. The US Food and Drug Administration (FDA) has approved five drugs for clinical use: tacrine, donepezil, carbalatine, galantamine, memantine, and lecanemab. We have focused on the newer drugs that have undergone clinical trials, most of which have not been successful as a result of excessive clinical side effects or poor efficacy. Although aducanumab received rapid approval from the FDA on 7 June 2021, its long-term safety and tolerability require further monitoring and confirmation. In this literature review, we aimed to explore the possible pathophysiological mechanisms underlying the occurrence and development of AD. We focused on anti-Aβ and anti-tau drugs, mitochondria-targeting and multi-targets, commercially available drugs, bottlenecks encountered in drug development, and the possible targets and therapeutic strategies for future drug development. We hope to present new concepts and methods for future drug therapies for AD.

The Crosstalk between Gut Microbiota and Nervous System: A Bidirectional Interaction between Microorganisms and Metabolome

Several studies have shown that the gut microbiota influences behavior and, in turn, changes in the immune system associated with symptoms of depression or anxiety disorder may be mirrored by corresponding changes in the gut microbiota. Although the composition/function of the intestinal microbiota appears to affect the central nervous system (CNS) activities through multiple mechanisms, accurate epidemiological evidence that clearly explains the connection between the CNS pathology and the intestinal dysbiosis is not yet available. The enteric nervous system (ENS) is a separate branch of the autonomic nervous system (ANS) and the largest part of the peripheral nervous system (PNS). It is composed of a vast and complex network of neurons which communicate via several neuromodulators and neurotransmitters, like those found in the CNS. Interestingly, despite its tight connections to both the PNS and ANS, the ENS is also capable of some independent activities. This concept, together with the suggested role played by intestinal microorganisms and the metabolome in the onset and progression of CNS neurological (neurodegenerative, autoimmune) and psychopathological (depression, anxiety disorders, autism) diseases, explains the large number of investigations exploring the functional role and the physiopathological implications of the gut microbiota/brain axis.

Acupuncture on mild cognitive impairment: A systematic review of neuroimaging studies

Mild cognitive impairment (MCI) is a multifactorial and complex central neurodegenerative disease. Acupuncture appears to be an effective method for cognitive function improvement in MCI patients. Neural plasticity remaining in the MCI brain implies that acupuncture-associated benefits may not be limited to the cognitive function. Instead, neurological alternations in the brain play a vital role in corresponding to the cognitive improvement. However, previous studies have mainly focused on the effects of cognitive function, leaving neurological findings relatively unclear. This systematic review summarized existing studies that used various brain imaging techniques to explore the neurological effect regarding acupuncture use for MCI treatment. Potential neuroimaging trials were searched, collected, and identified independently by two researchers. Four Chinese databases, four English databases, and additional sources were searched to identify studies reporting the use of acupuncture for MCI from the inception of databases until 1 June 2022. Methodological quality was appraised using the Cochrane risk-of-bias tool. In addition, general, methodological, and brain neuroimaging information was extracted and summarized to investigate the potential neural mechanisms by which acupuncture affects patients with MCI. In total, 22 studies involving 647 participants were included. The methodological quality of the included studies was moderate to high. The methods used included functional magnetic resonance imaging, diffusion tensor imaging, functional near-infrared spectroscopy, and magnetic resonance spectroscopy. Acupuncture-induced brain alterations observed in those patients with MCI tended to be observable in the cingulate cortex, prefrontal cortex, and hippocampus. The effect of acupuncture on MCI may play a role in regulating the default mode network, central executive network, and salience network. Based on these studies, researchers could extend the recent research focus from the cognitive domain to the neurological level. Future researches should develop additional relevant, well-designed, high-quality, and multimodal neuroimaging researches to detect the effects of acupuncture on the brains of MCI patients.

Alzheimer's Disease: Treatment Strategies and Their Limitations

Alzheimer's disease (AD) is the most frequent case of neurodegenerative disease and is becoming a major public health problem all over the world. Many therapeutic strategies have been explored for several decades; however, there is still no curative treatment, and the priority remains prevention. In this review, we present an update on the clinical and physiological phase of the AD spectrum, modifiable and non-modifiable risk factors for AD treatment with a focus on prevention strategies, then research models used in AD, followed by a discussion of treatment limitations. The prevention methods can significantly slow AD evolution and are currently the best strategy possible before the advanced stages of the disease. Indeed, current drug treatments have only symptomatic effects, and disease-modifying treatments are not yet available. Drug delivery to the central nervous system remains a complex process and represents a challenge for developing therapeutic and preventive strategies. Studies are underway to test new techniques to facilitate the bioavailability of molecules to the brain. After a deep study of the literature, we find the use of soft nanoparticles, in particular nanoliposomes and exosomes, as an innovative approach for preventive and therapeutic strategies in reducing the risk of AD and solving problems of brain bioavailability. Studies show the promising role of nanoliposomes and exosomes as smart drug delivery systems able to penetrate the blood-brain barrier and target brain tissues. Finally, the different drug administration techniques for neurological disorders are discussed. One of the promising therapeutic methods is the intranasal administration strategy which should be used for preclinical and clinical studies of neurodegenerative diseases.

A Prospective Viewpoint on Neurological Diseases and Their Biomarkers

Neurodegenerative diseases (NDDs) are disorders that affect both the central and peripheral nervous systems. To name a few causes, NDDs can be caused by ischemia, oxidative and endoplasmic reticulum (ER) cell stress, inflammation, abnormal protein deposition in neural tissue, autoimmune-mediated neuron loss, and viral or prion infections. These conditions include Alzheimer's disease (AD), Lewy body dementia (LBD), and Parkinson's disease (PD). The formation of β-sheet-rich aggregates of intra- or extracellular proteins in the CNS hallmarks all neurodegenerative proteinopathies. In systemic lupus erythematosus (SLE), numerous organs, including the central nervous system (CNS), are affected. However, the inflammatory process is linked to several neurodegenerative pathways that are linked to depression because of NDDs. Pro-inflammatory signals activated by aging may increase vulnerability to neuropsychiatric disorders. Viruses may increase macrophages and CCR5+ T cells within the CNS during dementia formation and progression. Unlike medical symptoms, which are just signs of a patient's health as expressed and perceived, biomarkers are reproducible and quantitative. Therefore, this current review will highlight and summarize the neurological disorders and their biomarkers.

Bis-Amiridines as Acetylcholinesterase and Butyrylcholinesterase Inhibitors: N-Functionalization Determines the Multitarget Anti-Alzheimer’s Activity Profile

Using two ways of functionalizing amiridine—acylation with chloroacetic acid chloride and reaction with thiophosgene—we have synthesized new homobivalent bis-amiridines joined by two different spacers—bis-N-acyl-alkylene (3) and bis-N-thiourea-alkylene (5) —as potential multifunctional agents for the treatment of Alzheimer’s disease (AD). All compounds exhibited high inhibitory activity against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with selectivity for BChE. These new agents displayed negligible carboxylesterase inhibition, suggesting a probable lack of untoward drug–drug interactions arising from hydrolytic biotransformation. Compounds 3 with bis-N-acyl-alkylene spacers were more potent inhibitors of both cholinesterases compared to compounds 5 and the parent amiridine. The lead compounds 3a–c exhibited an IC₅₀(AChE) = 2.9–1.4 µM, IC₅₀(BChE) = 0.13–0.067 µM, and 14–18% propidium displacement at 20 μM. Kinetic studies of compounds 3a and 5d indicated mixed-type reversible inhibition. Molecular docking revealed favorable poses in both catalytic and peripheral AChE sites. Propidium displacement from the peripheral site by the hybrids suggests their potential to hinder AChE-assisted Aβ₄₂ aggregation. Conjugates 3 had no effect on Aβ₄₂ self-aggregation, whereas compounds 5c–e (m = 4, 5, 6) showed mild (13–17%) inhibition. The greatest difference between conjugates 3 and 5 was their antioxidant activity. Bis-amiridines 3 with N-acylalkylene spacers were nearly inactive in ABTS and FRAP tests, whereas compounds 5 with thiourea in the spacers demonstrated high antioxidant activity, especially in the ABTS test (TEAC = 1.2–2.1), in agreement with their significantly lower HOMO-LUMO gap values. Calculated ADMET parameters for all conjugates predicted favorable blood–brain barrier permeability and intestinal absorption, as well as a low propensity for cardiac toxicity. Thus, it was possible to obtain amiridine derivatives whose potencies against AChE and BChE equaled (5) or exceeded (3) that of the parent compound, amiridine. Overall, based on their expanded and balanced pharmacological profiles, conjugates 5c–e appear promising for future optimization and development as multitarget anti-AD agents.

Predicted Cognitive Conversion in Guiding Early Decision-Tailoring on Patients With Cognitive Impairment

Background

Cognitive decline is the most dominant and patient-oriented symptom during the development of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This study was designed to test the feasibility of hybrid convolutional neural networks and long-short-term memory (CNN-LSTM) modeling driven early decision-tailoring with the predicted long-term cognitive conversion in AD and MCI.

Methods

Characteristics of patients with AD or MCI covering demographic features, clinical features, and time-dependent neuropsychological-related features were fused into the hybrid CNN-LSTM modeling to predict cognitive conversion based on a 4-point change in the AD assessment scale-cognition score. Treatment reassignment rates were estimated based on the actual and predicted cognitive conversion at 3 and 6 months according to the prespecified principle; that is if the ADAS-cog score of the patient declines less than 4 points or increases at either follow-up time point, the medical treatment recommended upon their diagnosis would be considered insufficient. Therefore, it is recommended to upgrade the medical treatment upon diagnosis. Actual and predicted treatment reassignment rates were compared in the general population and subpopulations categorized by age, gender, symptom severity, and the intervention subtypes.

Results

A total of 224 patients were included in the analysis. The hybrid CNN-LSTM model achieved the mean AUC of 0.735 (95% CI: 0.701–0.769) at 3 months and 0.853 (95% CI: 0.814–0.892) at 6 months in predicting cognitive conversion status. The AUC at 6 months was significantly impacted when data collected at 3 months were withdrawn. The predicted cognitive conversion suggested a revision of medical treatment in 46.43% (104/224) of patients at 3 months and 54.02% (121/224) at 6 months as compared with 62.05% (139/224) at 3 months (p = 0.001) and 62.50% (140/224) at 6 months (p = 0.069) according to their actual cognitive conversion. No significant differences were detected between treatment reassignment rates estimated based on actual and predicted cognitive conversion in all directions at 6 months.

Conclusion

Using the synergistic advances of deep learning modeling and featured longitudinal information, our hypothesis was preliminarily verified with the comparable predictive performance in cognitive conversion. Results provided the possibility of reassigned recommended treatment for those who may suffer from cognitive decline in the future. Considering the limited diversity of treatment strategies applied in this study, the real-world medical situation should be further simulated.

A Comprehensive Review on the Role of the Gut Microbiome in Human Neurological Disorders

The human body is full of an extensive number of commensal microbes, consisting of bacteria, viruses, and fungi, collectively termed the human microbiome. The initial acquisition of microbiota occurs from both the external and maternal environments, and the vast majority of them colonize the gastrointestinal tract (GIT). These microbial communities play a central role in the maturation and development of the immune system, the central nervous system, and the GIT system and are also responsible for essential metabolic pathways. Various factors, including host genetic predisposition, environmental factors, lifestyle, diet, antibiotic or nonantibiotic drug use, etc., affect the composition of the gut microbiota. Recent publications have highlighted that an imbalance in the gut microflora, known as dysbiosis, is associated with the onset and progression of neurological disorders. Moreover, characterization of the microbiome-host cross talk pathways provides insight into novel therapeutic strategies. Novel preclinical and clinical research on interventions related to the gut microbiome for treating neurological conditions, including autism spectrum disorders, Parkinson's disease, schizophrenia, multiple sclerosis, Alzheimer's disease, epilepsy, and stroke, hold significant promise. This review aims to present a comprehensive overview of the potential involvement of the human gut microbiome in the pathogenesis of neurological disorders, with a particular emphasis on the potential of microbe-based therapies and/or diagnostic microbial biomarkers. This review also discusses the potential health benefits of the administration of probiotics, prebiotics, postbiotics, and synbiotics and fecal microbiota transplantation in neurological disorders.

Gut and Brain: Investigating Physiological and Pathological Interactions Between Microbiota and Brain to Gain New Therapeutic Avenues for Brain Diseases

Brain physiological functions or pathological dysfunctions do surely depend on the activity of both neuronal and non-neuronal populations. Nevertheless, over the last decades, compelling and fast accumulating evidence showed that the brain is not alone. Indeed, the so-called "gut brain," composed of the microbial populations living in the gut, forms a symbiotic superorganism weighing as the human brain and strongly communicating with the latter via the gut-brain axis. The gut brain does exert a control on brain (dys)functions and it will eventually become a promising valuable therapeutic target for a number of brain pathologies. In the present review, we will first describe the role of gut microbiota in normal brain physiology from neurodevelopment till adulthood, and thereafter we will discuss evidence from the literature showing how gut microbiota alterations are a signature in a number of brain pathologies ranging from neurodevelopmental to neurodegenerative disorders, and how pre/probiotic supplement interventions aimed to correct the altered dysbiosis in pathological conditions may represent a valuable future therapeutic strategy.

Effects of Dance Interventions on Cognition, Psycho-Behavioral Symptoms, Motor Functions, and Quality of Life in Older Adult Patients With Mild Cognitive Impairment: A Meta-Analysis and Systematic Review

Background: Dance interventions are considered beneficial for older patients with mild cognitive impairment in many aspects. We conducted a comprehensive systematic review and meta-analysis to assess the effects of dance on different aspects (cognitive function, emotions, physical function, and quality of life) of this population. Methods: A systematic search of PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, Embase, American Psychological Association PsycInfo, ProQuest, Scopus, Cumulative Index to Nursing and Allied Health Literature, the Chinese BioMedical Literature Database, the VIP Database for Chinese Technical Periodicals, China National Knowledge Infrastructure, and Wanfang Data database was performed. Two reviewers independently assessed the study quality. Results: Fourteen studies were retrieved from the databases for analysis. The pooled results showed that dance interventions significantly improved global cognition (standardized mean difference [SMD] = 0.73, 95% confidence interval [CI]: 0.47 to 0.99, P < 0.00001), rote memory (mean difference [MD] = -2.12, 95% CI: -4.02 to -0.21, P = 0.03), immediate recall (SMD = 0.54, 95% CI: 0.30 to 0.78, P < 0.0001), delayed recall (SMD = 0.56, 95% CI: 0.26 to 0.86, P = 0.0002) and attention (SMD = 0.38, 95% CI: 0.13 to 0.64, P = 0.003). No significant improvement was found in executive function, language, depression, anxiety, dementia-related behavioral symptoms, motor function, and quality of life. Conclusion: Dance interventions benefit most aspects of cognitive functions. The evidence for the effects of dance on psycho-behavioral symptoms, motor function and quality of life remains unclear. More trials with rigorous study designs are necessary to provide this evidence.

Conjugation of Aminoadamantane and γ-Carboline Pharmacophores Gives Rise to Unexpected Properties of Multifunctional Ligands

A new series of conjugates of aminoadamantane and γ-carboline, which are basic scaffolds of the known neuroactive agents, memantine and dimebon (Latrepirdine) was synthesized and characterized. Conjugates act simultaneously on several biological structures and processes involved in the pathogenesis of Alzheimer’s disease and some other neurodegenerative disorders. In particular, these compounds inhibit enzymes of the cholinesterase family, exhibiting higher inhibitory activity against butyrylcholinesterase (BChE), but having almost no effect on the activity of carboxylesterase (anti-target). The compounds serve as NMDA-subtype glutamate receptor ligands, show mitoprotective properties by preventing opening of the mitochondrial permeability transition (MPT) pore, and act as microtubule stabilizers, stimulating the polymerization of tubulin and microtubule-associated proteins. Structure–activity relationships were studied, with particular attention to the effect of the spacer on biological activity. The synthesized conjugates showed new properties compared to their prototypes (memantine and dimebon), including the ability to bind to the ifenprodil-binding site of the NMDA receptor and to occupy the peripheral anionic site of acetylcholinesterase (AChE), which indicates that these compounds can act as blockers of AChE-induced β-amyloid aggregation. These new attributes of the conjugates represent improvements to the pharmacological profiles of the separate components by conferring the potential to act as neuroprotectants and cognition enhancers with a multifunctional mode of action.

Amiridine-piperazine hybrids as cholinesterase inhibitors and potential multitarget agents for Alzheimer's disease treatment

We synthesized eleven new amiridine-piperazine hybrids 5a-j and 7 as potential multifunctional agents for Alzheimer's disease (AD) treatment by reacting N-chloroacetylamiridine with piperazines. The compounds displayed mixed-type reversible inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Conjugates were moderate inhibitors of equine and human BChE with negligible fluctuation in anti-BChE activity, whereas anti-AChE activity was substantially dependent on N4-substitution of the piperazine ring. Compounds with para-substituted aromatic moieties (5g, 5h, and bis-amiridine 7) had the highest anti-AChE activity in the low micromolar range. Top-ranked compound 5h, N-(2,3,5,6,7,8-hexahydro-1H-cyclopenta[b]quinolin-9-yl)-2-[4-(4-nitro-phenyl)-piperazin-1-yl]-acetamide, had an IC₅₀ for AChE = 1.83 ± 0.03 μM (K_i = 1.50 ± 0.12 and αK_i = 2.58 ± 0.23 μM). The conjugates possessed low activity against carboxylesterase, indicating a likely absence of unwanted drug-drug interactions in clinical use. In agreement with analysis of inhibition kinetics and molecular modeling studies, the lead compounds were found to bind effectively to the peripheral anionic site of AChE and displace propidium, indicating their potential to block AChE-induced β-amyloid aggregation. Similar propidium displacement activity was first shown for amiridine. Two compounds, 5c (R = cyclohexyl) and 5e (R = 2-MeO-Ph), exhibited appreciable antioxidant capability with Trolox equivalent antioxidant capacity values of 0.47 ± 0.03 and 0.39 ± 0.02, respectively. Molecular docking and molecular dynamics simulations provided insights into the structure-activity relationships for AChE and BChE inhibition, including the observation that inhibitory potencies and computed pK_a values of hybrids were generally lower than those of the parent molecules. Predicted ADMET and physicochemical properties of conjugates indicated good CNS bioavailability and safety parameters comparable to those of amiridine and therefore acceptable for potential lead compounds at the early stages of anti-AD drug development.

Health Science Community Will Miss This Bright and Uniting Star: In Memory of Professor Gjumrakch Aliev, M.D, Ph.D

It is with deep sadness that we offer our memorial on the unexpected demise of our dear colleague, Professor Gjumrakch Aliev [...].

Trajectories of Multiple Behavioral Risk Factors and Their Associations With Cognitive Function Trajectories Among Older African Americans and White Americans

Objectives: This study examined the joint trajectories of behavioral risk factors (smoking, alcohol drinking, and body mass index) and their associations with cognitive function trajectories among older African Americans and white Americans. Methods: Data from the Health and Retirement Study (1998-2014) were used. Group-based mixture modeling and multinomial logistic regression analysis were performed. Results: Three joint trajectories of behavioral risk factors (overweight, smoking and drinking, and drinking and overweight) and three cognitive function trajectories (low, moderate, and high) were identified. A significantly higher percentage of African Americans were in the "overweight," "smoking and drinking," and "low" cognitive functioning groups as measured by the total cognition composite score compared to white Americans. After accounting for covariates, the "drinking and overweight" group was associated with the "moderate" or "high" cognitive functioning group. Discussion: Future interventions targeting the combinations of behavioral risk factors are needed to promote healthy aging among high-risk populations.

A bioisostere of Dimebon/Latrepirdine delays the onset and slows the progression of pathology in FUS transgenic mice

Aims

To assess effects of DF402, a bioisostere of Dimebon/Latrepirdine, on the disease progression in the transgenic model of amyotrophic lateral sclerosis (ALS) caused by expression of pathogenic truncated form of human FUS protein.

Methods

Mice received DF402 from the age of 42 days and the onset of clinical signs, the disease duration and animal lifespan were monitored for experimental and control animals, and multiple parameters of their gait were assessed throughout the pre‐symptomatic stage using CatWalk system followed by a bioinformatic analysis. RNA‐seq was used to compare the spinal cord transcriptomes of wild‐type, untreated, and DF402‐treated FUS transgenic mice.

Results

DF402 delays the onset and slows the progression of pathology. We developed a CatWalk analysis protocol that allows detection of gait changes in FUS transgenic mice and the effect of DF402 on their gait already at early pre‐symptomatic stage. At this stage, a limited number of genes significantly change expression in transgenic mice and for 60% of these genes, DF402 treatment causes the reversion of the expression pattern.

Conclusion

DF402 slows down the disease progression in the mouse model of ALS, which is consistent with previously reported neuroprotective properties of Dimebon and its other bioisosteres. These results suggest that these structures can be considered as lead compounds for further optimization to obtain novel medicines that might be used as components of complex ALS therapy.

Machine Learning Algorithms and Statistical Approaches for Alzheimer's Disease Analysis Based on Resting-State EEG Recordings: A Systematic Review

Alzheimer's Disease (AD) is a neurodegenerative disorder and the most common type of dementia with a great prevalence in western countries. The diagnosis of AD and its progression is performed through a variety of clinical procedures including neuropsychological and physical examination, Electroencephalographic (EEG) recording, brain imaging and blood analysis. During the last decades, analysis of the electrophysiological dynamics in AD patients has gained great research interest, as an alternative and cost-effective approach. This paper summarizes recent publications focusing on (a) AD detection and (b) the correlation of quantitative EEG features with AD progression, as it is estimated by Mini Mental State Examination (MMSE) score. A total of 49 experimental studies published from 2009 until 2020, which apply machine learning algorithms on resting state EEG recordings from AD patients, are reviewed. Results of each experimental study are presented and compared. The majority of the studies focus on AD detection incorporating Support Vector Machines, while deep learning techniques have not yet been applied on large EEG datasets. Promising conclusions for future studies are presented.

Design and Application in Delivery System of Intranasal Antidepressants

One of the major reasons why depressed patients fail their treatment course is the existence of the blood-brain barrier (BBB), which prevents drugs from being delivered to the central nervous system (CNS). In recent years, nasal drug delivery has achieved better systemic bioavailability and activity in low doses in antidepressant treatment. In this review, we focused on the latest strategies for delivery carriers (or formation) of intranasal antidepressants. We began this review with an overview of the nasal drug delivery systems, including nasal drug delivery route, absorption mechanism, advantages, and limitations in the nasal drug delivery route. Next, we introduced the development of nasal drug delivery devices, such as powder devices, liquid-based devices, and so on. Finally, intranasal delivery carriers of antidepressants in clinical studies, including nanogels, nanostructured lipid, liposomes nanoparticles, nanoemulsions/microemulsion, were summarized. Moreover, challenges and future perspectives on recent progress of intranasal delivery carriers in antidepressant treatments were discussed.

Adiponectin Role in Neurodegenerative Diseases: Focus on Nutrition Review

Adiponectin is an adipokine produced by adipose tissue. It has numerous beneficial effects. In particular, it improves metabolic effects and glucose homeostasis, lipid profile, and is involved in the regulation of cytokine profile and immune cell production, having anti-inflammatory and immune-regulatory effects. Adiponectin’s role is already known in immune diseases and also in neurodegenerative diseases. Neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease, are a set of diseases of the central nervous system, characterized by a chronic and selective process of neuron cell death, which occurs mainly in relation to oxidative stress and neuroinflammation. Lifestyle is able to influence the development of these diseases. In particular, unhealthy nutrition on gut microbiota, influences its composition and predisposition to develop many diseases such as neurodegenerative diseases, given the importance of the “gut-brain” axis. There is a strong interplay between Adiponectin, gut microbiota, and brain-gut axis. For these reasons, a healthy diet composed of healthy nutrients such as probiotics, prebiotics, polyphenols, can prevent many metabolic and inflammatory diseases such as neurodegenerative diseases and obesity. The special Adiponectin role should be taken into account also, in order to be able to use this component as a therapeutic molecule.

Prediction of transition from mild cognitive impairment to Alzheimer's disease based on a logistic regression-artificial neural network-decision tree model

AIM

To develop a logistic regression model, artificial neural network (ANN) model and decision tree (DT) model for the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) to compare the performance of the three models.

METHODS

A total of 425 patients with MCI were screened from the original cohort. The actual follow up included 361 patients, with AD as the outcome variable. Three kinds of prediction models were developed: a logistic regression model, ANN model and DT model. The performance of all three models was measured with accuracy, sensitivity, positive predictive value and area under the receiver operating characteristic curve.

RESULTS

A total of 121 patients with MCI developed AD, and the average conversion rate was 9.49% per year. The ANN model had higher accuracy (89.52 ± 0.36%), area under the receiver operating characteristic curve (92.08 ± 0.12), sensitivity (82.11 ± 0.42%) and positive predictive value (75.26 ± 0.86%) than the other two models. The first five important predictors of the ANN model were, in order, ADL score, age, urine AD-associated neuronal thread protein, alcohol consumption and smoking. For the DT model, they were age, activities of daily living score, family history of dementia, urine AD-associated neuronal thread protein and alcohol consumption. For the logistic regression model, they were age, sex, activities of daily living score, alcohol consumption and smoking.

CONCLUSION

The logistic regression, ANN and DT models performed well at predicting the transition from MCI to AD with ideal stability. However, the ANN model had the best predictive value. Increased age, activities of daily living score, urine AD-associated neuronal thread protein, alcohol consumption, smoking and sex were important factors. Geriatr Gerontol Int 2021; 21: 43-47.

You Talking to Me? Says the Enteric Nervous System (ENS) to the Microbe. How Intestinal Microbes Interact with the ENS

Mammalian organisms form intimate interfaces with commensal and pathogenic gut microorganisms. Increasing evidence suggests a close interaction between gut microorganisms and the enteric nervous system (ENS), as the first interface to the central nervous system. Each microorganism can exert a different effect on the ENS, including phenotypical neuronal changes or the induction of chemical transmitters that interact with ENS neurons. Some pathogenic bacteria take advantage of the ENS to create a more suitable environment for their growth or to promote the effects of their toxins. In addition, some commensal bacteria can affect the central nervous system (CNS) by locally interacting with the ENS. From the current knowledge emerges an interesting field that may shape future concepts on the pathogen-host synergic interaction. The aim of this narrative review is to report the current findings regarding the inter-relationships between bacteria, viruses, and parasites and the ENS.

Mitochondria as a promising target for developing novel agents for treating Alzheimer's disease

The mitochondria-targeting drugs can be conventionally divided into the following groups: those compensating for the energy deficit involved in neurodegeneration, including stimulants of mitochondrial bioenergetics and activators of mitochondrial biogenesis; and neuroprotectors, that are compounds increasing the resistance of mitochondria to opening of mitochondrial permeability transition (MPT) pores. Although compensating for the energy deficit and inhibition of MPT are obvious targets for drugs used in the very early stages of Alzheimer-like pathology, but their use as the monotherapy for patients with severe symptoms is unlikely to be sufficiently effective. It would be optimal to combine targets that would provide the cognitive-stimulating, the neuroprotective effects and the ability to affect specific disease-forming mechanisms. In the design of such drugs, assessment of their potential mitochondrial-targeted effects is of particular importance. The possibility of targeted drug design for simultaneous action on mitochondrial and neurotransmitter's receptors targets is, in particularly, based on the known interplay of various cellular pathways and the presence of common structural components. Of particular interest is directed search for multitarget drugs that would act simultaneously on mitochondrial calcium-dependent functions, the targets (receptors, enzymes, etc.) facilitating neurotransmission, and the molecular targets related to the action of so-called disease-modifying factors, in particular, the formation and overcoming of the toxicity of β-amyloid or hyperphosphorylated tau protein. The examples of such approaches realized on the level of preclinical and clinical trials are presented below.

Promising Molecular Targets for Pharmacological Therapy of Neurodegenerative Pathologies

Drug development for the treatment of neurodegenerative diseases has to confront numerous problems occurring, in particular, because of attempts to address only one of the causes of the pathogenesis of neurological disorders. Recent advances in multitarget therapy research are gaining momentum by utilizing pharmacophores that simultaneously affect different pathological pathways in the neurodegeneration process. The application of such a therapeutic strategy not only involves the treatment of symptoms, but also mainly addresses prevention of the fundamental pathological processes of neurodegenerative diseases and the reduction of cognitive abilities. Neuroinflammation and oxidative stress, mitochondrial dysfunction, dysregulation of the expression of histone deacetylases, and aggregation of pathogenic forms of proteins are among the most common and significant pathological features of neurodegenerative diseases. In this review, we focus on the molecular mechanisms and highlight the main aspects, including reactive oxygen species, the cell endogenous antioxidant system, neuroinflammation triggers, metalloproteinases, α-synuclein, tau proteins, neuromelanin, histone deacetylases, presenilins, etc. The processes and molecular targets discussed in this review could serve as a starting point for screening leader compounds that could help prevent or slow down the development of neurodegenerative diseases.

Insulin mediated novel therapies for the treatment of Alzheimer's disease

Alzheimer's disease, a progressive neurodegenerative disorder, is one of the leading causes of death in the USA, along with cancer and cardiac disorders. AD is characterized by various neurological factors like amyloid plaques, tau hyperphosphorylation, mitochondrial dysfunction, acetylcholine deficiency, etc. Together, impaired insulin signaling in the brain is also observed as essential factor to be considered in AD pathophysiology. Hence, currently researchers focused on studying the effect of brain insulin metabolism and relation of diabetes with AD. Based on the investigations, AD is also considered as type 3 or brain diabetes. Besides the traditional view of correlating AD with aging, a better understanding of various pathological factors and effects of other physical ailments is necessary to develop a promising therapeutic approach. There is a vast scope of studying the relation of systemic insulin level, insulin signaling, its neuroprotective potency and effect of diabetes on AD progression. The present work describes worldwide status of AD and its relation with diabetes mellitus and insulin metabolism; pathophysiology of AD; different metabolic pathways associating insulin metabolism with AD; insulin receptor and signaling in the brain; glucose metabolism; insulin resistance; and various preclinical and clinical studies reported insulin-based therapies to treat AD via systemic route and through direct intranasal delivery to the brain.

Methylglyoxal and Glyoxal as Potential Peripheral Markers for MCI Diagnosis and Their Effects on the Expression of Neurotrophic, Inflammatory and Neurodegenerative Factors in Neurons and in Neuronal Derived-Extracellular Vesicles

Methylglyoxal (MG) and glyoxal (GO) are suggested to be associated with the development of neurodegenerative pathologies. However, their peripheral levels in relation to cognitive decline and their effects on key factors in neuronal cells are poorly investigated. The aim of this study was to determine their serum levels in MCI (mild cognitive impairment) and Alzheimer’s disease (AD) patients, to analyze their effects on the neurotrophic and inflammatory factors, on neurodegenerative markers in neuronal cells and in neuronal derived-extracellular vesicles (nEVs). Our results show that MG and GO levels in serum, determined by HPLC, were higher in MCI. ROC (receiver-operating characteristic curves) analysis showed that the levels of MG in serum have higher sensitivity to differentiate MCI from controls but not from AD. Meanwhile, serum GO levels differentiate MCI from control and AD groups. Cells and nEVs levels of BDNF, PRGN, NSE, APP, MMP-9, ANGPTL-4, LCN2, PTX2, S100B, RAGE, Aβ peptide, pTau T181 and alpha-synuclein were quantified by luminex assay. Treatment of neuronal cells with MG or GO reduced the cellular levels of NSE, PRGN, APP, MMP-9 and ANGPTL-4 and the nEVs levels of BDNF, PRGN and LCN2. Our findings suggest that targeting MG and GO may be a promising therapeutic strategy to prevent or delay the progression of AD.

New screening approach for Alzheimer's disease risk assessment from urine lipid peroxidation compounds

Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. Therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. These prediction models achieved fair validated area under the receiver operating characteristics (AUC-ROCs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

Risk classification for conversion from mild cognitive impairment to Alzheimer's disease in primary care

There is a pressing need to identify individuals at high risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) based on available repeated cognitive measures in primary care. Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we applied a joint latent class mixed model (JLCM) to derive a 3-class solution: low risk (72.65%), medium risk (20.41%) and high risk (6.94%). In the low-risk group, individuals with lower daily activity and ApoEε4 carriers were at greater risk of conversion from MCI to AD. In the medium-risk group, being female, single, and an ApoEε4 carrier increased risk of conversion to AD. In the high-risk group, individuals with lower education level and single individuals were at greater risk of conversion to AD. Individual dynamic prediction for conversion from MCI to AD after 10 years was derived. Accurate identification of conversion from MCI to AD contributes to earlier close monitoring, appropriate management, and targeted interventions. Thereby, it can reduce avoidable hospitalizations for the high-risk MCI population. Moreover, it can avoid expensive follow-up tests that may provoke unnecessary anxiety for low-risk individuals and their families.

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification

Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population-based cohort. The AD-model and mild-AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate-AD-model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI-model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD-model (AUC = 0.611, p = 1.0). Within our population-based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI-based MCI detection on an individual basis. Our data indicate that multiparametric MRI-based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.

Impact of microbiota on central nervous system and neurological diseases: the gut-brain axis

Development of central nervous system (CNS) is regulated by both intrinsic and peripheral signals. Previous studies have suggested that environmental factors affect neurological activities under both physiological and pathological conditions. Although there is anatomical separation, emerging evidence has indicated the existence of bidirectional interaction between gut microbiota, i.e., (diverse microorganisms colonizing human intestine), and brain. The cross-talk between gut microbiota and brain may have crucial impact during basic neurogenerative processes, in neurodegenerative disorders and tumors of CNS. In this review, we discuss the biological interplay between gut-brain axis, and further explore how this communication may be dysregulated in neurological diseases. Further, we highlight new insights in modification of gut microbiota composition, which may emerge as a promising therapeutic approach to treat CNS disorders.

Nicotinamide ribose ameliorates cognitive impairment of aged and Alzheimer's disease model mice

Nicotinamide adenine dinucleotide (NAD) supplementation to repair the disabled mitochondria is a promising strategy for the treatment of Alzheimer's disease (AD) and other dementia. Nicotinamide ribose (NR) is a safe NAD precursor with high oral bioavailability, and has beneficial effects on aging. Here, we applied NR supplied food (2.5 g/kg food) to APP/PS1 transgenic AD model mice and aged mice for 3 months. Cognitive function, locomotor activity and anxiety level were assessed by standard behavioral tests. The change of body weight, the activation of microglia and astrocytes, the accumulation of Aβ and the level of serum nicotinamide phosphoribosyltransferase (NAMPT) were determined for the evaluation of pathological processes. We found that NR supplementation improved the short-term spatial memory of aged mice, and the contextual fear memory of AD mice. Moreover, NR supplementation inhibited the activation of astrocytes and the elevation of serum NAMPT of aged mice. For AD model mice, NR supplementation inhibited the accumulation of Aβ and the migration of astrocyte to Aβ. In addition, NR supplementation inhibit the body weight gain of aged and APP/PS1 mice. Thus, NR has selective benefits for both AD and aged mice, and the oral uptake of NR can be used to prevent the progression of dementia.

Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection

INTRODUCTION

Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role.

METHODS

Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment.

RESULTS

The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities.

CONCLUSION

A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

Development, Application, and Results from a Precision-medicine Platform that Personalizes Multi-modal Treatment Plans for Mild Alzheimer's Disease and At-risk Individuals

INTRODUCTION

Alzheimer's Disease (AD) is a progressive neurodegenerative condition in which individuals exhibit memory loss, dementia, and impaired metabolism. Nearly all previous single-treatment studies to treat AD have failed, likely because it is a complex disease with multiple underlying drivers contributing to risk, onset, and progression. Here, we explored the efficacy of a multi-therapy approach based on the disease risk factor status specific to individuals with AD diagnosis or concern.

METHODS

Novel software from uMETHOD Health was designed to execute a precision-medicinebased approach to develop personalized treatment recommendations with the goal of slowing or reversing biologic drivers of AD. AD-associated inputs encompassed genomic data, bio-specimen measurements, imaging data (such as MRIs or PET scans), medical histories, medications, allergies, co-morbidities, relevant lifestyle factors, and results of neuropsychological testing. Algorithms were then employed to prioritize physiologic and lifestyle states with the highest probability of contributing to disease status, and these priorities were incorporated into a personalized care plan, which was delivered to physicians and supported by health coaches to increase adherence. The sample included 40 subjects with Subjective Cognitive Decline patients (SCD), and Mild Cognitive Impairment Patients (MCI).

RESULTS

Software analysis was completed for 40 individuals. They remained on their treatment plan for an average of 8.4 months, equal to 2.8 iterations of care plans. 80% of individuals overall showed improved memory function scores or held steady, as measured by standardized cognitive evaluations. Cognitive assessments showed significant improvement in the SCD group (Composite P value .002, Executive P value .01), and the CNS-VS Executive domain showed significant results in the combined group as well (P value .01). There was also biomarker improvement over time observed from the blood panels. 8 out of 12 selected biomarkers showed slight, though statistically non-significant, improvement overall for symptomatic individuals, and 6 out of 12 for the overall population. Only one biomarker, homocysteine, showed significant improvement, though (P values .03, .04, .002).

CONCLUSIONS

Our analysis of these individuals lead to several interesting observations together suggesting that AD risk factors comprise a network of interlocking feedback loops that may be modifiable. Our findings indicate previously unidentified connectivity between AD risk factors, suggesting that treatment regimens should be tailored to the individual and multi-modal to simultaneously return several risk factors to a normative state. If successfully performed, the possibility to slow progression of AD and possibly reverse aspects of cognitive decline may become achievable.