HEBP1 - An early trigger for neuronal cell death and circuit dysfunction in Alzheimer's disease

Identification of Potential Biomarkers and Therapeutic Targets for Periodontitis

BACKGROUND

Periodontitis is a chronic and multifactorial inflammatory disease. However, existing medications often lack sufficient therapeutic effects. The aim is to identify potential biomarkers and efficient therapeutic targets using Mendelian randomisation (MR) and single-cell analysis.

METHODS

MR analysis was conducted based on the cis-expression quantitative trait loci (cis-eQTLs) extracted from the eQTLGen Consortium and genome-wide association study (GWAS) data of periodontitis sourced from the Gene Lifestyle Interactions in Dental Endpoints (GLIDE) consortium (17,353 cases, 28,210 controls). Subsequently, colocalisation analysis was employed to detect whether genes and periodontitis shared the same casual variant. Finally, enrichment analysis, protein-protein interaction (PPI) networks, drug prediction, phenome-wide association study (PheWAS), molecular docking, and single-cell analysis were conducted to validate the significance of target genes.

RESULTS

Fourteen drug targets were significant related with periodontitis in MR analysis. Following the colocalisation and summary-data-based MR (SMR) analysis, 3 targets (S100A12, S100A9, and S100A8) were classified into tier 1 with strong evidence, 6 therapeutic targets (ADAM12, ADHFE1, BLK, HEBP1, SERPINE2, and TEK) were classified into tier 2 with moderate evidence, and 5 therapeutic targets (LY86, MMEL1, S100B, SPP1, and TRIB3) were classified into tier 3 with convincing evidence. PheWAS analysis showed that only TEK and SPP1 in tier 2 may induce side effects, including cardiometabolic and oncological issues. Molecular docking demonstrated strong binding between drugs and their respective protein targets. In the single-cell analysis, 5 target genes (HEBP1, LY86, S100A8, S100A9, and S100A12) exhibited enrichment in monocytes, while BLK and LY86 were primarily enriched in B cells.

CONCLUSION

The study identified 14 potential therapeutic targets for periodontitis. Among these, 3 therapeutic targets (S100A12, S100A9, and S100A8) demonstrated robust and well-supported results. Drugs designed to target these genes have a higher possibility of success in clinical trials, which are hopeful for prioritising periodontitis drug development.

Lifestyle, Environment, and Dietary Measures Impacting Cognitive Impairment: The Evidence Base for Cognitive Subtypes

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Cognition includes all phases of valid functions and processes, e.g., sensitivity, judgment, assessment, and decision-making. Thinking is also a cognitive procedure since it involves considering potential opportunities. There are various types of cognition. Hot cognition involves mental procedures where emotion plays a role, while cold cognition includes mental processes that do not include feelings or emotions. Cognitive memories of various types include sensor memory, sensing touch, smell, and sight; short-term memory allows one to recall, e.g., what one had for lunch a few days ago; working memory includes remembering telephone numbers or directions to a destination; and long-term memory comprises of major milestones in life and recalling one’s childhood events. These are further classified as episodic, e.g., the first day in primary school, and semantic memories, such as recalling the capital city of a country and filling out crossword puzzles. Declarative memories include remembering significant past events, such as global information. Cognition is affected by factors, such as nutrition, aging, addiction, environment, mental health, physical activity, smoking, and keeping the brain active. Consumption of plant- based foods plays a prominent role in the prevention of cognitive memory. Playing games and instruments, reading books, and being socially active make life more satisfying, thus assisting in the preservation of mental function and slowing mental decline.

Machine learning-based gene expression biomarkers to distinguish Zika and Dengue virus infections: implications for diagnosis

Zika virus (ZIKV) and Dengue virus (DENV) infections cause severe disease in humans and are significant socio-economic burden worldwide. These flavivirus infections are difficult to diagnose serologically due to antigenic overlap. The phylogenetic analysis shows that ZIKV clusters with DENVs at a higher node of the phylogenetic tree with significant genomic and structural similarity. Our study aims to identify gene biomarkers for the classification of Dengue and Zika viral infections using machine learning algorithms and bioinformatics analysis. The gene expression count matrix for single-cell RNA sequencing dataset GSE110496 was analyzed using binary classifiers, namely Logistic regression, Support Vector Machines, Random Forest, and Decision trees. The GSE110496 dataset represents a unique study of the transcriptional and translational dynamics of DENV and ZIKV infections at 4-, 12-, 24-, and 48-h time points for human hepatoma (Huh7) cells. Out of which 24-h time point has been analyzed in this study, at the optimal threshold of viral molecules. Feature selection was performed using two different approaches Random Forest Classifier (RFC) for gene ranking and Recursive Feature Elimination (RFE). Out of which RFE, showed more accuracy and precision. The classification accuracy of 89.4% and the precision of 90% were obtained using selected 10 gene features. SCY1 Like Pseudokinase 3 (SCYL3), Chromosome 1 Open Reading Frame 112 (C1orf112), Complement factor H (CFH), Heme-binding protein 1 (HEBP1), Cadherin 1 (CDH1), Nibrin (NBN), Histone deacetylase 5 (HDAC5), nuclear receptor subfamily 0, group B, member 2 (NR0B2), Annexin A9 (ANXA9) and Alcohol dehydrogenase 6 (ADH6) are the proposed gene biomarkers in this study. The functional analysis of the reported biomarkers was performed using KEGG and GO with the WEB-based Gene SeT AnaLysis Toolkit (WebGestalt). The relationship of the selected biomarkers with DENV and ZIKV infections analyzed using a gene-gene interaction network showed important interactions for viral entry, replication, translation, and metabolic pathways. These biomarkers are potential diagnostic markers for DENV and ZIKV infections based on machine learning analysis and need further experimental validation.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-024-00885-8.

Association between genetically plasma proteins and osteonecrosis: a proteome-wide Mendelian randomization analysis

Background

Previous studies have explored the role of plasma proteins on osteonecrosis. This Mendelian randomization (MR) study further assessed plasma proteins on osteonecrosis whether a causal relationship exists and provides some evidence of causality.

Methods

Summary-level data of 4,907 circulating protein levels were extracted from a large-scale protein quantitative trait loci study including 35,559 individuals by the deCODE Genetics Consortium. The outcome data for osteonecrosis were sourced from the FinnGen study, comprising 1,543 cases and 391,037 controls. MR analysis was conducted to estimate the associations between protein and osteonecrosis risk. Additionally, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets.

Results

We totally assessed the effect of 1,676 plasma proteins on osteonecrosis risk, of which 71 plasma proteins had a suggestive association with outcome risk (P < 0.05). Notably, Heme-binding protein 1 (HEBP1) was significant positively associated with osteonecrosis risk with convening evidence (OR, 1.40, 95% CI, 1.19 to 1.65, P = 3.96 × 10-5, P FDR = 0.044). This association was further confirmed in other MR analysis methods and did not detect heterogeneity and pleiotropy (all P > 0.05). To comprehensively explore the health effect of HEBP1, the phenome-wide MR analysis found it was associated with 136 phenotypes excluding osteonecrosis (P < 0.05). However, no significant association was observed after the false discovery rate adjustment.

Conclusion

This comprehensive MR study identifies 71 plasma proteins associated with osteonecrosis, with HEBP1, ITIH1, SMOC1, and CREG1 showing potential as biomarkers of osteonecrosis. Nonetheless, further studies are needed to validate this candidate plasma protein.

Prediction of Alzheimer's disease stages based on ResNet-Self-attention architecture with Bayesian optimization and best features selection

Alzheimer's disease (AD) is a neurodegenerative illness that impairs cognition, function, and behavior by causing irreversible damage to multiple brain areas, including the hippocampus. The suffering of the patients and their family members will be lessened with an early diagnosis of AD. The automatic diagnosis technique is widely required due to the shortage of medical experts and eases the burden of medical staff. The automatic artificial intelligence (AI)-based computerized method can help experts achieve better diagnosis accuracy and precision rates. This study proposes a new automated framework for AD stage prediction based on the ResNet-Self architecture and Fuzzy Entropy-controlled Path-Finding Algorithm (FEcPFA). A data augmentation technique has been utilized to resolve the dataset imbalance issue. In the next step, we proposed a new deep-learning model based on the self-attention module. A ResNet-50 architecture is modified and connected with a self-attention block for important information extraction. The hyperparameters were optimized using Bayesian optimization (BO) and then utilized to train the model, which was subsequently employed for feature extraction. The self-attention extracted features were optimized using the proposed FEcPFA. The best features were selected using FEcPFA and passed to the machine learning classifiers for the final classification. The experimental process utilized a publicly available MRI dataset and achieved an improved accuracy of 99.9%. The results were compared with state-of-the-art (SOTA) techniques, demonstrating the improvement of the proposed framework in terms of accuracy and time efficiency.

Putative Molecular Mechanisms Underpinning the Inverse Roles of Mitochondrial Respiration and Heme Function in Lung Cancer and Alzheimer's Disease

Mitochondria are the powerhouse of the cell. Mitochondria serve as the major source of oxidative stress. Impaired mitochondria produce less adenosine triphosphate (ATP) but generate more reactive oxygen species (ROS), which could be a major factor in the oxidative imbalance observed in Alzheimer's disease (AD). Well-balanced mitochondrial respiration is important for the proper functioning of cells and human health. Indeed, recent research has shown that elevated mitochondrial respiration underlies the development and therapy resistance of many types of cancer, whereas diminished mitochondrial respiration is linked to the pathogenesis of AD. Mitochondria govern several activities that are known to be changed in lung cancer, the largest cause of cancer-related mortality worldwide. Because of the significant dependence of lung cancer cells on mitochondrial respiration, numerous studies demonstrated that blocking mitochondrial activity is a potent strategy to treat lung cancer. Heme is a central factor in mitochondrial respiration/oxidative phosphorylation (OXPHOS), and its association with cancer is the subject of increased research in recent years. In neural cells, heme is a key component in mitochondrial respiration and the production of ATP. Here, we review the role of impaired heme metabolism in the etiology of AD. We discuss the numerous mitochondrial effects that may contribute to AD and cancer. In addition to emphasizing the significance of heme in the development of both AD and cancer, this review also identifies some possible biological connections between the development of the two diseases. This review explores shared biological mechanisms (Pin1, Wnt, and p53 signaling) in cancer and AD. In cancer, these mechanisms drive cell proliferation and tumorigenic functions, while in AD, they lead to cell death. Understanding these mechanisms may help advance treatments for both conditions. This review discusses precise information regarding common risk factors, such as aging, obesity, diabetes, and tobacco usage.

Precursor ions-guided comprehensive profiling of triterpenoid saponins from the Eleutherococcus senticosus stems and their neuroprotective effect evaluation

Triterpenoid saponins (TS) are the main constituents of Eleutherococcus senticosus, also termed as Siberian ginseng or Ciwujia, a widely used herb in China, Japan, Korea, and Russia for its beneficial effects on memory enhancement, tonifying, heart-nourishing, and tranquilizing. Although the stems, rhizomes, and roots are used identically, a preliminary experiment found TS were specifically distributed in stems rather than the underground parts. However, a comprehensive profiling of the TS compounds in E. senticosus stems (ESS) is still absent. In this study, an MS/MS molecular networking (MN)-based precursor ions (PIs) discovery strategy was applied to fast track the TS compounds from ESS extract. A total of 80 TS were tracked and characterized, among which 78 ones were reported for the first time in ESS. Furthermore, the TS-rich fraction (ESS-TS) was prepared by a series of chromatography separation, and was found with significant neuralprotective effects on attenuating Aβ25-35-induced neurite atrophy, and promoting the outgrowth of damaged neurite in the Aβ25-35-induced primary cortical neuronal damage model. In conclusion, this study highlighted the existence of TS compounds in ESS, a major medicinal parts nowadays adopted as Ciwujia by the Chinese Pharmacopiea and market. In addition, the TS was found with determined roles in the outgrowth of neuritis, and was proposed as crucial constituent when the E. senticosus was used as the therapeutic agents for neural diseases. These results supplies scientific data for the quality control of E. senticosus and the further development of ESS-TS as memory enhancement agents.

Poly (ADP-Ribose) polymerase 1 and parthanatos in neurological diseases: From pathogenesis to therapeutic opportunities

Poly (ADP-ribose) polymerase-1 (PARP-1) is the most extensively studied member of the PARP superfamily, with its primary function being the facilitation of DNA damage repair processes. Parthanatos is a type of regulated cell death cascade initiated by PARP-1 hyperactivation, which involves multiple subroutines, including the accumulation of ADP-ribose polymers (PAR), binding of PAR and apoptosis-inducing factor (AIF), release of AIF from the mitochondria, the translocation of the AIF/macrophage migration inhibitory factor (MIF) complex, and massive MIF-mediated DNA fragmentation. Over the past few decades, the role of PARP-1 in central nervous system health and disease has received increasing attention. In this review, we discuss the biological functions of PARP-1 in neural cell proliferation and differentiation, memory formation, brain ageing, and epigenetic regulation. We then elaborate on the involvement of PARP-1 and PARP-1-dependant parthanatos in various neuropathological processes, such as oxidative stress, neuroinflammation, mitochondrial dysfunction, excitotoxicity, autophagy damage, and endoplasmic reticulum (ER) stress. Additional highlight contains PARP-1's implications in the initiation, progression, and therapeutic opportunities for different neurological illnesses, including neurodegenerative diseases, stroke, autism spectrum disorder (ASD), multiple sclerosis (MS), epilepsy, and neuropathic pain (NP). Finally, emerging insights into the repurposing of PARP inhibitors for the management of neurological diseases are provided. This review aims to summarize the exciting advancements in the critical role of PARP-1 in neurological disorders, which may open new avenues for therapeutic options targeting PARP-1 or parthanatos.

Advances in Amyloid-β Clearance in the Brain and Periphery: Implications for Neurodegenerative Diseases

This review examines the role of impaired amyloid-β clearance in the accumulation of amyloid-β in the brain and the periphery, which is closely associated with Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). The molecular mechanism underlying amyloid-β accumulation is largely unknown, but recent evidence suggests that impaired amyloid-β clearance plays a critical role in its accumulation. The review provides an overview of recent research and proposes strategies for efficient amyloid-β clearance in both the brain and periphery. The clearance of amyloid-β can occur through enzymatic or non-enzymatic pathways in the brain, including neuronal and glial cells, blood-brain barrier, interstitial fluid bulk flow, perivascular drainage, and cerebrospinal fluid absorption-mediated pathways. In the periphery, various mechanisms, including peripheral organs, immunomodulation/immune cells, enzymes, amyloid-β-binding proteins, and amyloid-β-binding cells, are involved in amyloid-β clearance. Although recent findings have shed light on amyloid-β clearance in both regions, opportunities remain in areas where limited data is available. Therefore, future strategies that enhance amyloid-β clearance in the brain and/or periphery, either through central or peripheral clearance approaches or in combination, are highly encouraged. These strategies will provide new insight into the disease pathogenesis at the molecular level and explore new targets for inhibiting amyloid-β deposition, which is central to the pathogenesis of sporadic AD (amyloid-β in parenchyma) and CAA (amyloid-β in blood vessels).

Recent Development in the Understanding of Molecular and Cellular Mechanisms Underlying the Etiopathogenesis of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that leads to dementia and patient death. AD is characterized by intracellular neurofibrillary tangles, extracellular amyloid beta (Aβ) plaque deposition, and neurodegeneration. Diverse alterations have been associated with AD progression, including genetic mutations, neuroinflammation, blood-brain barrier (BBB) impairment, mitochondrial dysfunction, oxidative stress, and metal ion imbalance.Additionally, recent studies have shown an association between altered heme metabolism and AD. Unfortunately, decades of research and drug development have not produced any effective treatments for AD. Therefore, understanding the cellular and molecular mechanisms underlying AD pathology and identifying potential therapeutic targets are crucial for AD drug development. This review discusses the most common alterations associated with AD and promising therapeutic targets for AD drug discovery. Furthermore, it highlights the role of heme in AD development and summarizes mathematical models of AD, including a stochastic mathematical model of AD and mathematical models of the effect of Aβ on AD. We also summarize the potential treatment strategies that these models can offer in clinical trials.