Protein-protein interactions underlying the behavioral and psychological symptoms of dementia (BPSD) and Alzheimer's disease

A Six-Gene Signature Related to Liquid-Liquid Phase Separation for Diagnosis of Alzheimer's Disease

BACKGROUND

Liquid-liquid phase separation (LLPS) has been increasingly recognized as a crucial mechanism in the pathogenesis of various neurodegenerative disorders, including Alzheimer's disease (AD). There remains a paucity of effective diagnostic biomarkers for this condition. This study aims to develop and validate a novel LLPS-related molecular signature to enhance the diagnostic accuracy and early detection of AD.

METHODS

LLPS-related genes were identified from online databases and subjected to bioinformatic analyses, including protein-protein interaction (PPI) network analysis and least absolute shrinkage and selection operator (LASSO) regression. Based on the optimal LLPS-related genes, a diagnosis risk model was constructed, and the diagnostic ability was evaluated using a receiver operator characteristic (ROC) curve. To elucidate the biological functions of the identified LLPS-related genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted.

RESULTS

A total of 149 LLPS-related genes were screened, which were found to be involved in functions related to oxidative stress, apoptosis, and cancer progression. The 149 genes were refined to six optimal candidates through PPI network analysis and LASSO regression: Activator of HSP90 ATPase Activity 1 (AHSA1), Eukaryotic Translation Initiation Factor 2 Alpha Kinase 2 (EIF2AK2), Heat Shock Protein Family A (Hsp70) Member 4 (HSPA4), Notch Receptor 1 (NOTCH1), Superoxide Dismutase 1 (SOD1), and Thioredoxin (TXN). Based on the six optimal genes, a diagnostic risk model was constructed, and the diagnostic ability was verified to be promising in AD both in training, internal validation, and two external validation datasets, with area under ROC curve (AUC) above 0.8. Furthermore, significant correlations were observed between the expression of these genes and tumor immune cell infiltration.

CONCLUSIONS

A six-gene diagnosis model was constructed and verified to exhibit robust diagnostic ability in AD.

Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by the aggregation of β-amyloid (Aβ) and tau in the brain. Breakthroughs in disease-modifying treatments targeting Aβ bring new hope for the management of AD. But to effectively modify and someday even prevent AD, a better understanding is needed of the biological mechanisms that underlie and link Aβ and tau in AD. Developments of high-throughput omics, including genomics, proteomics, and transcriptomics, together with molecular imaging of Aβ and tau with positron emission tomography (PET), allow us to discover and understand the biological pathways that regulate the aggregation and spread of Aβ and tau in living humans. The field of integrated omics and PET studies of Aβ and tau in AD is growing rapidly. We here provide an update of this field, both in terms of biological insights and in terms of future clinical implications of integrated omics-molecular imaging studies.

NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation

Transcription factor (TF) coordination plays a key role in target gene (TG) regulation via protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell technologies facilitate gene expression measurement for individual cells and cell-type identification, yet the connection between TF coordination and TG regulation of various cell types remains unclear. To address this, we have developed a novel computational approach, Network Regression Embeddings (NetREm), to reveal cell-type TF-TF coordination activities for TG regulation. NetREm leverages network-constrained regularization using prior knowledge of direct and/or indirect PPIs among TFs to analyze single-cell gene expression data. We test NetREm by simulation data and benchmark its performance in 4 real-world applications that have gold standard TF-TG networks available: mouse (mESCs) and simulated human (hESCs) embryonic stem (ESCs), human hematopoietic stem (HSCs), and mouse dendritic (mDCs) cells. Further, we use NetREm to prioritize valid novel TF-TF coordination links in human Peripheral Blood Mononuclear cell (PBMC) sub-types. We apply NetREm to analyze various cell types in both central (CNS) and peripheral (PNS) nerve system (NS) (e.g. neuronal, glial, Schwann cells (SCs)) as well as in Alzheimers disease (AD). Our findings uncover cell-type coordinating TFs and identify new TF-TG candidate links. We validate our top predictions using Cut&Run and knockout loss-of-function expression data in rat/mouse models and compare results with additional functional genomic data, including expression quantitative trait loci (eQTL) and Genome-Wide Association Studies (GWAS) to link genetic variants (single nucleotide polymorphisms (SNPs)) to TF coordination.

Pangenomics: A new era in the field of neurodegenerative diseases

A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.

Generating Potential Protein-Protein Interaction Inhibitor Molecules Based on Physicochemical Properties

Protein-protein interactions (PPIs) are associated with various diseases; hence, they are important targets in drug discovery. However, the physicochemical empirical properties of PPI-targeted drugs are distinct from those of conventional small molecule oral pharmaceuticals, which adhere to the "rule of five (RO5)". Therefore, developing PPI-targeted drugs using conventional methods, such as molecular generation models, is challenging. In this study, we propose a molecular generation model based on deep reinforcement learning that is specialized for the production of PPI inhibitors. By introducing a scoring function that can represent the properties of PPI inhibitors, we successfully generated potential PPI inhibitor compounds. These newly constructed virtual compounds possess the desired properties for PPI inhibitors, and they show similarity to commercially available PPI libraries. The virtual compounds are freely available as a virtual library.

Tailoring the therapeutic interventions for behavioral and psychological symptoms of dementia

INTRODUCTION

Behavioral and psychological symptoms of dementia (BPSD) are symptoms of non-cognitive nature, which frequently develop during the course and different stages of dementia. The diagnosis of BPSD is complex due to symptom variety, and relies on detailed clinical evaluation and medical history. Accurate assessment of BPSD is crucial in order to tailor therapeutic intervention (non-pharmacological and pharmacological) for each individual and monitor patient response to therapy.

AREAS COVERED

This review encompasses the epidemiology, classification, assessment and etiology of BPSD, as well as their impact on caregiver distress, and gives an overview of current and emerging non-pharmacological and pharmacological therapeutic options, as well as potential BPSD biomarkers, in order to provide a framework for improving BPSD diagnosis and developing novel, targeted and specific therapeutic strategies for BPSD.

EXPERT OPINION

Due to the large heterogeneity of BPSD and of the fact that drugs available only alleviate symptoms, finding an adequate treatment is very challenging and often involves a polytherapeutic approach. Non-pharmacologic interventions have shown promising results in improving BPSD, however further research is needed to confirm their beneficial effects. Thus, the modification of pre-existancing as well as the development of novel pharmacologic and non-pharmacologic solutions should be considered for BPSD therapy.

Research Hotspots and Trends in Music Therapy Intervention for Patients With Dementia: A Bibliometrics and Visual Analysis of Papers Published From 2010 to 2021

BACKGROUND

As a serious public health problem, dementia has placed a heavy burden on society and families. Evidence suggests that the use of music therapy as a non-pharmacological intervention has certain advantages with respect to reducing the behavioral and psychological symptoms of dementia (BPSD) and improving the cognition and mental status of dementia patients. However, research trends and hotspots regarding music therapy intervention for dementia analysis have not been systematically studied via bibliometric analysis.

METHODS

We searched the Web of Science Core Collection (WoSCC) for texts published between January 1, 2010, and October 31, 2021, and visualized country, institution, journal, keyword co-occurrence, keyword emergence and keyword clustering.

RESULTS

A total of 217 articles from the WoSCC database were analyzed. In this research field, the annual number of publications has generally shown a slowly increasing trend, and the United States has the most publications and the most frequent cooperation among countries. University College London (UCL) has the most extensive influence among research institutions. Among articles, those published in the JOURNAL OF ALZHEIMER'S DISEASE were the most numerous, with 20 such articles being published, accounting for 9.22% (20/217) of the total. Comprehensive analysis of five clusters via biclustering shows that the research hotspots in this field during the past 11 years have mainly focused on the autobiographical memory, cognitive function, mental state and BPSD of dementia patients.

CONCLUSION

This study conducted a bibliometric and visual analysis of relevant studies concerning music therapy intervention for dementia patients. Psychological problems faced by dementia patients and the topics of quality of life, individualized music therapy, the mental state of caregivers and other related topics may be important research directions in the future. Therefore, the question of how to develop standardized research protocols and identify unified efficacy evaluation indicators should be a focus of and difficulty for future research.

Transcriptomic Changes in Hot Spring Frog Tadpoles (Buergeria otai) in Response to Heat Stress

Buergeria frog tadpoles exhibit high thermal tolerance and are occasionally found in water pools that temporarily exceed 40°C. With the aim of understanding how they can cope with the severe heat stress, we performed RNA-seq of three heat-treated (38°C) and three control (25°C) tadpoles and compared their transcriptomic profiles. We identified 382 differentially expressed transcripts. A protein-protein interaction (PPI) network analysis of these transcripts further identified hub proteins involved in protein degradation, stress granule assembly, and global suppression of DNA transcription and mRNA translation. Along with the avoidance behavior against high water temperature, these endurance mechanisms potentially support tadpoles to survive in high temperatures for short periods of time. Similar mechanisms may exist in many other amphibian species whose habitats are prone to high temperatures.

Characterization of functional protein complexes from Alzheimer's disease and healthy brain by mass spectrometry-based proteome analysis

Alzheimer's disease (AD) is a complex neurodegenerative disorder with impaired protein activities. Proteins in the form of complexes have a ubiquitous role in diverse range of cellular functions. The key challenge is to identify novel disease associated protein complexes and their potential role in the progression of AD pathology. Protein complexes were obtained from AD brain prefrontal cortex and age matched controls by Blue Native-Polyacrylamide Gel Electrophoresis. A proteomic analysis was performed using second dimension SDS-PAGE followed by nano LC-MS/MS. Differentially expressed proteins were mapped to existing biological networks by Ingenuity Pathway Analysis (IPA). A total of 13 protein complexes with their interacting proteins were resolved on SDS-PAGE. We identified 34 protein spots and found significant abundance difference between the two experimental samples. IPA analysis revealed degeneration of neurons and cell death as a major consequence of protein dysregulation. Furthermore, focused network analysis suggested an integrated regulation of the identified proteins through APP and MAPT dependent mechanisms. The interacting differentially expressed proteins in AD were found to be part of concomitant signaling cascades terminating in neuronal cell death. The identified protein networks and pathways warrant further research to study their actual contribution to AD pathology.

Diagnostic value of amygdala volume on structural magnetic resonance imaging in Alzheimer’s disease

BACKGROUND

The main clinical manifestation of Alzheimer’s disease (AD) is memory loss, which can be accompanied by neuropsychiatric symptoms at different stages of the disease. Amygdala is closely related to emotion and memory.

AIM

To evaluate the diagnostic value of amygdala on structural magnetic resonance imaging (sMRI) for AD.

METHODS

In this study, 22 patients with AD and 26 controls were enrolled. Their amygdala volumes were measured by sMRI and analyzed using an automatic analysis software.

RESULTS

The bilateral amygdala volumes of AD patients were significantly lower than those of the controls and were positively correlated with the hippocampal volumes. Receiver operating characteristic curve analyses showed that the sensitivity of the left and right amygdala volumes in diagnosing AD was 80.8% and 88.5%, respectively. Subgroup analyses showed that amygdala atrophy was more serious in AD patients with neuropsychiatric symptoms, which mainly included irritability (22.73%), sleep difficulties (22.73%), apathy (18.18%), and hallucination (13.64%).

CONCLUSION

Amygdala volumes measured by sMRI can be used to diagnose AD, and amygdala atrophy is more serious in patients with neuropsychiatric symptoms.

The Moringin/α-CD Pretreatment Induces Neuroprotection in an In Vitro Model of Alzheimer's Disease: A Transcriptomic Study

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and represents the most common form of senile dementia. Autophagy and mitophagy are cellular processes that play a key role in the aggregation of β-amyloid (Aβ) and tau phosphorylation. As a consequence, impairment of these processes leads to the progression of AD. Thus, interest is growing in the search for new natural compounds, such as Moringin (MOR), with neuroprotective, anti-amyloidogenic, antioxidative, and anti-inflammatory properties that could be used for AD prevention. However, MOR appears to be poorly soluble and stable in water. To increase its solubility MOR was conjugated with α-cyclodextrin (MOR/α-CD). In this work, it was evaluated if MOR/α-CD pretreatment was able to exert neuroprotective effects in an AD in vitro model through the evaluation of the transcriptional profile by next-generation sequencing (NGS). To induce the AD model, retinoic acid-differentiated SH-SY5Y cells were exposed to Aβ_1-42. The MOR/α-CD pretreatment reduced the expression of the genes which encode proteins involved in senescence, autophagy, and mitophagy processes. Additionally, MOR/α-CD was able to induce neuronal remodeling modulating the axon guidance, principally downregulating the Slit/Robo signaling pathway. Noteworthy, MOR/α-CD, modulating these important pathways, may induce neuronal protection against Aβ_1-42 toxicity as demonstrated also by the reduction of cleaved caspase 3. These data indicated that MOR/α-CD could attenuate the progression of the disease and promote neuronal repair.

T-type Ca2+ channel enhancer SAK3 administration improves the BPSD-like behaviors in AppNL-G-F/NL-G-F knock-in mice

Alzheimer's disease (AD) accounts for the majority of dementia among the elderly. In addition to cognitive impairment, behavioral and psychological symptoms (BPSD) such as depression tendency and increased aggression impose a great burden on the patient. However, there is still no rational therapeutic drug for BPSD. Recently, we developed a novel AD therapeutic candidate, SAK3, and demonstrated that it improved cognitive dysfunction in AppNL-G-F/NL-G-F knock-in (NL-G-F) mice. In this study, we investigated whether acute SAK3 administration improved BPSD in addition to cognitive improvement. Acute SAK3 administration improved BPSD, including anxiolytic and depressive-like behaviors, and ameliorated aggressive behaviors. Furthermore, continuous SAK3 administration improved anxiolytic and depressive-like behaviors. Intriguingly, the anti-anxiolytic and cognitive improvement lasted two weeks after the withdrawal of SAK3, whereas the anti-depressive action did not. Taken together, SAK3 had comprehensive beneficial effects on BPSD behavior.

Current Challenges and Opportunities in Designing Protein-Protein Interaction Targeted Drugs

It has been noticed that the efficiency of drug development has been decreasing in the past few decades. To overcome the situation, protein-protein interactions (PPIs) have been identified as new drug targets as early as 2000. PPIs are more abundant in human cells than single proteins and play numerous important roles in cellular processes including diseases. However, PPIs have very different physicochemical features from the conventional drug targets, which make targeting PPIs challenging. Therefore, as of now, only a small number of PPI inhibitors have been approved or progressed to a stage of clinical trial. In this article, we first overview previous works that analyzed differences between PPIs with PPI targeting ligands and conventional drugs with their binding pockets. Then, we constructed an up-to-date list of PPI targeting drugs that have been approved or are currently under clinical trial and have bound drug-target structures available. Using the dataset, we analyzed the PPIs and their ligands using several scores of druggability. Druggability scores showed that PPI sites and their drugs targeting PPIs are less druggable than conventional binding pockets and drugs, which also indicates that PPI drugs do not follow the conventional rules for drug design, such as Lipinski's rule of five. Our analyses suggest that developing a new rule would be beneficial for guiding PPI-drug discovery.

Advances in Molecular Dynamics Simulations and Enhanced Sampling Methods for the Study of Protein Systems

Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Continuous modernization of simulation tools enables accurate prediction and characterization of the aforementioned mechanisms and these qualities are highly beneficial for the expedition of drug development when effectively applied to structure-based drug design (SBDD). In this review, current all-atom MD simulation methods, with focus on enhanced sampling techniques, utilized to examine protein structure, dynamics, and functions are discussed. This review will pivot around computer calculations of protein-ligand and protein-protein systems with applications to SBDD. In addition, we will also be highlighting limitations faced by current simulation tools as well as the improvements that have been made to ameliorate their efficiency.