LncRNAs as the Regulators of Brain Function and Therapeutic Targets for Alzheimer’s Disease

Epigenetic Mechanisms of Aluminum-Induced Neurotoxicity and Alzheimer's Disease: A Focus on Non-Coding RNAs

Aluminum (Al) is known to induce neurotoxic effects, potentially contributing to Alzheimer's disease (AD) pathogenesis. Recent studies suggest that epigenetic modification may contribute to Al neurotoxicity, although the mechanisms are still debatable. Therefore, the objective of the present study was to summarize existing data on the involvement of epigenetic mechanisms in Al-induced neurotoxicity, especially AD-type pathology. Existing data demonstrate that Al exposure induces disruption in DNA methylation, histone modifications, and non-coding RNA expression in brains. Alterations in DNA methylation following Al exposure were shown to be mediated by changes in expression and activity of DNA methyltransferases (DNMTs) and ten-eleven translocation proteins (TETs). Al exposure was shown to reduce histone acetylation by up-regulating expression of histone deacetylases (HDACs) and impair histone methylation, ultimately contributing to down-regulation of brain-derived neurotrophic factor (BDNF) expression and activation of nuclear factor κB (NF-κB) signaling. Neurotoxic effects of Al exposure were also associated with aberrant expression of non-coding RNAs, especially microRNAs (miR). Al-induced patterns of miR expression were involved in development of AD-type pathology by increasing amyloid β (Aβ) production through up-regulation of Aβ precursor protein (APP) and β secretase (BACE1) expression (down-regulation of miR-29a/b, miR-101, miR-124, and Let-7c expression), increasing in neuroinflammation through NF-κB signaling (up-regulation of miR-9, miR-125b, miR-128, and 146a), as well as modulating other signaling pathways. Furthermore, reduced global DNA methylation, altered histone modification, and aberrant miRNA expression were associated with cognitive decline in Al-exposed subjects. However, further studies are required to evaluate the contribution of epigenetic mechanisms to Al-induced neurotoxicity and/or AD development.

Differentially expressed lncRNAs in SOD1G93A mice skeletal muscle: H19, Myhas and Neat1 as potential biomarkers in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating neuromuscular disease characterized by progressive motor function and muscle mass loss. Despite extensive research in the field, the underlying causes of ALS remain incompletely understood, contributing to the absence of specific diagnostic and prognostic biomarkers and effective therapies. This study investigates the expression of long-non-coding RNAs (lncRNAs) in skeletal muscle as a potential source of biomarkers and therapeutic targets for the disease. The expression profiles of 12 lncRNAs, selected from the literature, were evaluated across different disease stages in tissue and muscle biopsies from the SOD1G93A transgenic mouse model of ALS. Nine out of the 12 lncRNAs were differentially expressed, with Pvt1, H19 and Neat1 showing notable increases in the symptomatic stages of the disease, and suggesting their potential as candidate biomarkers to support diagnosis and key players in muscle pathophysiology in ALS. Furthermore, the progression of Myhas and H19 RNA levels across disease stages correlated with longevity in the SOD1G93A animal model, effectively discriminating between long- and short-term survival individuals, thereby highlighting their potential as prognostic indicators. These findings underscore the involvement of lncRNAs, especially H19 and Myhas, in ALS pathophysiology, offering novel insights for diagnostic, prognostic and therapeutic targets.

The roles of long non-coding RNAs in Alzheimer's disease diagnosis, treatment, and their involvement in Alzheimer's disease immune responses

Alzheimer's disease (AD) is the most frequent type of dementia, presenting a substantial danger to the health and well-being of the aged population. It has arisen as a significant public health problem with considerable socioeconomic repercussions. Unfortunately, no effective treatments or diagnostic tools are available for Alzheimer's disease. Despite substantial studies on the pathophysiology of Alzheimer's, the molecular pathways underpinning its development remain poorly understood. Long non-coding RNAs (lncRNAs) vary in size from 200 nucleotides to over 100 kilobytes and have been found to play critical roles in various vital biological processes that play critical in developing Alzheimer's disease. This review intends to examine the functions of long non-coding RNAs in diagnosing and treating Alzheimer's disease and their participation in immunological responses associated with AD.

A Holistic Analysis of Alzheimer's Disease-Associated lncRNA Communities Reveals Enhanced lncRNA-miRNA-RBP Regulatory Triad Formation Within Functionally Segregated Clusters

Recent studies on the regulatory networks implicated in Alzheimer's disease (AD) evince long non-coding RNAs (lncRNAs) as crucial regulatory players, albeit a poor understanding of the mechanism. Analyzing differential gene expression in the RNA-seq data from the post-mortem AD brain hippocampus, we categorized a list of AD-dysregulated lncRNA transcripts into functionally similar communities based on their k-mer profiles. Using machine-learning-based algorithms, their subcellular localizations were mapped. We further explored the functional relevance of each community through AD-dysregulated miRNA, RNA-binding protein (RBP) interactors, and pathway enrichment analyses. Further investigation of the miRNA-lncRNA and RBP-lncRNA networks from each community revealed the top RBPs, miRNAs, and lncRNAs for each cluster. The experimental validation community yielded ELAVL4 and miR-16-5p as the predominant RBP and miRNA, respectively. Five lncRNAs emerged as the top-ranking candidates from the RBP/miRNA-lncRNA networks. Further analyses of these networks revealed the presence of multiple regulatory triads where the RBP-lncRNA interactions could be augmented by the enhanced miRNA-lncRNA interactions. Our results advance the understanding of the mechanism of lncRNA-mediated AD regulation through their interacting partners and demonstrate how these functionally segregated but overlapping regulatory networks can modulate the disease holistically.

Integrative Analysis of the Age-Related Dysregulated Genes Reveals an Inflammation and Immunity-Associated Regulatory Network in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disease with a long incubation period. While extensive research has led to the construction of long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) regulatory networks, which primarily derived from differential analyses between clinical AD patients and control individuals or mice, there remains a critical knowledge gap pertaining to the dynamic alterations in transcript expression profiles that occur with age, spanning from the pre-symptomatic stage to the onset of AD. In the present study, we examined the transcriptomic changes in AD model mice at three distinct stages: the unaffected (un-) stage, the pre-onset stage, and the late-onset stage, and identified 14, 57, and 99 differentially expressed mRNAs (DEmRs) in AD model mice at 3, 6, and 12 months, respectively. Among these, we pinpointed 16 mRNAs closely associated with inflammation and immunity and excavated their lncRNA-mRNA regulatory network based on a comprehensive analysis. Notably, our preliminary analysis suggested that four lncRNAs (NONMMUT102943, ENSMUST00000160309, NONMMUT083044, and NONMMUT126468), eight miRNAs (miR-34a-5p, miR-22-5p, miR-302a/b-3p, miR-340-5p, miR-376a/b-5p, and miR-487b-5p), and four mRNAs (C1qa, Cd68, Ctss, and Slc11a1) may play pivotal roles in orchestrating immune and inflammatory responses during the early stages of AD. Our study has unveiled age-related AD risk genes, and provided an analytical framework for constructing lncRNA-mRNA networks using time series data and correlation analysis. Most notably, we have successfully constructed a comprehensive regulatory ceRNA network comprising genes intricately linked to inflammatory and immune functions in AD.

E2F1 Mediates Traumatic Brain Injury and Regulates BDNF-AS to Promote the Progression of Alzheimer's Disease

Traumatic brain injury (TBI) is one of the important risk factors for the development of Alzheimer's disease (AD). However, the molecular mechanism by which TBI promotes the progression of AD is not elucidated. In this study, we showed that the abnormal production of E2F1 is a major factor in promoting the neuropathological and cognitive deterioration of AD post-TBI. We found that repeated mild TBI can aggravate the neuropathology of AD in APP/PS1 mice. At the same time, the co-expression of E2F1 and beta-site APP cleaving enzyme 1 (BACE1) was upregulated when the mouse hippocampus was dissected. BACE1 is recognized as a rate-limiting enzyme for the production of Aβ. Here, we speculate that E2F1 may play a role in promoting BACE1 expression in AD. Therefore, we collected peripheral blood from patients with AD. Interestingly, there is a positive correlation between E2F1 and brain-derived neurotrophic factor-antisense (BDNF-AS), whereas BDNF-AS in AD can promote the expression of BACE1 and exhibit a neurotoxic effect. We established a cell model and found a regulatory relationship between E2F1 and BDNF-AS. Therefore, based on our results, we concluded that E2F1 regulates BDNF-AS, promotes the expression of BACE1, and affects the progression of AD. Furthermore, E2F1 mediates the TBI-induced neurotoxicity of AD.

Cognition-associated long noncoding RNAs are dysregulated upon severe COVID-19

Severe COVID-19 leads to widespread transcriptomic changes in the human brain, mimicking diminished cognitive performance. As long noncoding RNAs (lncRNAs) play crucial roles in the regulation of gene expression, identification of the lncRNAs differentially expressed upon COVID-19 may nominate key regulatory nodes underpinning cognitive changes. Here we identify hundreds of lncRNAs differentially expressed in the brains of COVID-19 patients relative to uninfected age/sex-matched controls, many of which are associated with decreased cognitive performance and inflammatory cytokine response. Our analyses reveal pervasive transcriptomic changes in lncRNA expression upon severe COVID-19, which may serve as key regulators of neurocognitive changes in the brain.

The Role of Non-coding RNAs in Alzheimer's Disease: Pathogenesis, Novel Biomarkers, and Potential Therapeutic Targets

Long non-coding RNAs (IncRNAs) are regulatory RNA transcripts that have recently been associated with the onset of many neurodegenerative illnesses, including Alzheimer's disease (AD). Several IncRNAs have been found to be associated with AD pathophysiology, each with a distinct mechanism. In this review, we focused on the role of IncRNAs in the pathogenesis of AD and their potential as novel biomarkers and therapeutic targets. Searching for relevant articles was done using the PubMed and Cochrane library databases. Studies had to be published in full text in English in order to be considered. Some IncRNAs were found to be upregulated, while others were downregulated. Dysregulation of IncRNAs expression may contribute to AD pathogenesis. Their effects manifest as the synthesis of beta-amyloid (Aβ) plaques increases, thereby altering neuronal plasticity, inducing inflammation, and promoting apoptosis. Despite the need for more investigations, IncRNAs could potentially increase the sensitivity of early detection of AD. Until now, there has been no effective treatment for AD. Hence, InRNAs are promising molecules and may serve as potential therapeutic targets. Although several dysregulated AD-associated lncRNAs have been discovered, the functional characterization of most lncRNAs is still lacking.

Enhancing Alzheimer's Disease Diagnosis and Care by Focusing on Plasma Biomarkers for Identifying Mild Cognitive Impairment

Biomarkers that accurately identify mild cognitive impairment (MCI) are of greater importance for Alzheimer's disease (AD) management and treatment. On the other hand, blood-based biomarkers are not only more practical but also less invasive than the common cerebrospinal fluid biomarkers. In their report in the Journal of Alzheimer's Disease, Wang and collaborators identified 67 upregulated and 220 downregulated long noncoding RNAs (lncRNAs). They further demonstrated that 4 of these lncRNAs could discriminate MCI from cognitively healthy individuals. Apart from their significance as potential biomarkers for MCI diagnosis, these lncRNAs can offer additional information on the cellular mechanisms of AD pathology.

Identification of senescence-related lncRNA prognostic index correlating with prognosis and radiosensitivity in prostate cancer patients

BACKGROUND

An increasing number of studies are shown how crucial a role cellular senescence plays in tumor development. In this study, we developed a senescence-related lncRNA prognostic index (SRLPI) to forecast radiosensitivity and the probability of biochemical recurrence (BCR) in patients with prostate cancer (PCa).

METHODS

PCa cohorts in TCGA and GEO databases were downloaded. Senescence-and prognosis-related lncRNA with differential expression in tumor and normal samples were identified and used to establish the SRLPI score. Mutation landscape, function pathway, tumor stemness and heterogeneity and tumor immune microenvironment were also analyzed. We performed the analysis using R 3.6.3 and the appropriate tools.

RESULTS

A SRLPI score was constructed based on SNHG1 and MIAT in the TCGA cohort. Our classification of PCa patients into high- and low-risk groups was based on the median SRLPI score. When compared to the low-SRLPI group, the high-SRLPI group was more vulnerable to BCR (HR: 3.33). In terms of BCR-free survival and metastasis-free survival, the GSE116918 showed similar findings. Surprisingly, the SRLPI score demonstrated a high level of radiosensitivity for diagnosis (AUC: 0.98). Age, Gleason score, T stage, N stage, positive lymph nodes, and residual tumor were all significantly greater in patients with high SRLPI scores. Furthermore, this score was significantly related to markers of senescence. Protein secretion and androgen response were found to be substantially enriched in the low-SRLPI group, whereas E2F targets were found to be strongly enriched in the high-SRLPI group for pathway analysis. For the tumor microenvironment assessment, B cells, CD8+ T cells, immune score and TIDE score were positively related to SRLPI score while endothelial level was negatively associated with SRLPI score with statistical significance.

CONCLUSIONS

We developed a SRLPI score that was related to prognosis and radiosensitivity and might be helpful in clinical practice.

Development and validation of a kidney renal clear cell carcinoma prognostic model relying on pyroptosis-related LncRNAs-A multidimensional comprehensive bioinformatics exploration

BACKGROUND

Renal cell carcinoma (RCC) is a malignant tumour that may develop in the kidney. RCC is one of the most common kinds of tumours of this sort, and its most common pathological subtype is kidney renal clear cell carcinoma (KIRC). However, the aetiology and pathogenesis of RCC still need to be clarified. Exploring the internal mechanism of RCC contributes to diagnosing and treating this disease. Pyroptosis is a critical process related to cell death. Recent research has shown that pyroptosis is a critical factor in the initiation and progression of tumour formation. Thus far, researchers have progressively uncovered evidence of the regulatory influence that long noncoding RNAs (lncRNAs) have on pyroptosis.

METHODS

In this work, a comprehensive bioinformatics approach was used to produce a predictive model according to pyroptosis-interrelated lncRNAs for the purpose of predicting the overall survival and molecular immune specialties of patients diagnosed with KIRC. This model was verified from multiple perspectives.

RESULTS

First, we discovered pyroptosis-associated lncRNAs in KIRC patients using the TCGA database and a Sankey diagram. Then, we developed and validated a KIRC patient risk model based on pyroptosis-related lncRNAs. We demonstrated the grouping power of PLnRM through PCA and used PLnRM to assess the tumour immune microenvironment and response to immunotherapy. Immunological and molecular traits of diverse PLnRM subgroups were evaluated, as were clinical KIRC patient characteristics and predictive risk models. On this basis, a predictive nomogram was developed and analyzed, and novel PLnRM candidate compounds were identified. Finally, we investigated possible medications used by KIRC patients.

CONCLUSIONS

The results demonstrate that the model generated has significant value for KIRC in clinical practice.

Going beyond established model systems of Alzheimer's disease: companion animals provide novel insights into the neurobiology of aging

Alzheimer's disease (AD) is characterized by brain plaques, tangles, and cognitive impairment. AD is one of the most common age-related dementias in humans. Progress in characterizing AD and other age-related disorders is hindered by a perceived dearth of animal models that naturally reproduce diseases observed in humans. Mice and nonhuman primates are model systems used to understand human diseases. Still, these model systems lack many of the biological characteristics of Alzheimer-like diseases (e.g., plaques, tangles) as they grow older. In contrast, companion animal models (cats and dogs) age in ways that resemble humans. Both companion animal models and humans show evidence of brain atrophy, plaques, and tangles, as well as cognitive decline with age. We embrace a One Health perspective, which recognizes that the health of humans is connected to those of animals, and we illustrate how such a perspective can work synergistically to enhance human and animal health. A comparative biology perspective is ideally suited to integrate insights across veterinary and human medical disciplines and solve long-standing problems in aging.

Construction of lncRNA-ceRNA networks to reveal the potential role of Lfng/Notch1 signaling pathway in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) develops through a complex pathological process, in which many genes play a synergistic or antagonistic role. LncRNAs represent a kind of non-coding RNA, which can regulate gene expression at the epigenetic, transcriptional and post-transcriptional levels. Multiple lncRNAs have been found to have important regulatory functions in AD. Thus, their expression patterns, targets and functions should be explored as therapeutic targets.

METHODS

We used deep RNA-seq analysis to detect the dysregulated lncRNAs in the hippocampus of APP/PS1 mice. We performed Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to predict the biological roles and potential signaling pathways of dysregulated lncRNAs. Finally, we constructed lncRNA-miRNA-mRNA and lncRNA-mRNA co-expression networks to reveal the potential regulator roles in AD pathogenesis.

RESULTS

Our findings revealed 110 significantly dysregulated lncRNAs. GO and KEGG annotations showed the dysregulated lncRNAs to be closely related to the functions of axon and protein digestion and absorption. The lncRNA-mRNA network showed that 19 lncRNAs regulated App, Prnp, Fgf10 and Il33, while 5 lncRNAs regulated Lfng via the lncRNA-miR-3102-3p-Lfng axis. Furthermore, we preliminarily demonstrated the important regulatory role of the Lfng/Notch1 signaling pathway through lncRNA-ceRNA networks in AD.

CONCLUSION

We revealed the important regulatory roles of dysregulated lncRNAs in the etiopathogenesis of AD through lncRNA expression profiling. Our results showed that the mechanism involves the regulation of the Lfng/Notch1 signaling pathway.

Long Non-Coding RNAs, Extracellular Vesicles and Inflammation in Alzheimer's Disease

Alzheimer's Disease (AD) has currently no effective treatment; however, preventive measures have the potential to reduce AD risk. Thus, accurate and early prediction of risk is an important strategy to alleviate the AD burden. Neuroinflammation is a major factor prompting the onset of the disease. Inflammation exerts its toxic effect via multiple mechanisms. Amongst others, it is affecting gene expression via modulation of non-coding RNAs (ncRNAs), such as miRNAs. Recent evidence supports that inflammation can also affect long non-coding RNA (lncRNA) expression. While the association between miRNAs and inflammation in AD has been studied, the role of lncRNAs in neurodegenerative diseases has been less explored. In this review, we focus on lncRNAs and inflammation in the context of AD. Furthermore, since plasma-isolated extracellular vesicles (EVs) are increasingly recognized as an effective monitoring strategy for brain pathologies, we have focused on the studies reporting dysregulated lncRNAs in EVs isolated from AD patients and controls. The revised literature shows a positive association between pro-inflammatory lncRNAs and AD. However, the reports evaluating lncRNA alterations in EVs isolated from the plasma of patients and controls, although still limited, confirm the value of specific lncRNAs associated with AD as reliable biomarkers. This is an emerging field that will open new avenues to improve risk prediction and patient stratification, and may lead to the discovery of potential novel therapeutic targets for AD.