Editorial: Decoding novel therapeutic targets, biomarkers, and drug development strategies against neurodegenerative disorders-A multi-omics approach.
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ABSTRACT:
SUBMITTER: Srinivasan E
PROVIDER: S-EPMC10325664 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
Publications
Editorial: Decoding novel therapeutic targets, biomarkers, and drug development strategies against neurodegenerative disorders-A multi-omics approach.
Srinivasan E E Nagaraj Siranjeevi S Rajendran Sakthi S Rajasekaran R R
Frontiers in computational neuroscience 20230622
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| S-EPMC8602358 | biostudies-literature
Project description:Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.
| S-EPMC10562578 | biostudies-literature
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| S-EPMC10599139 | biostudies-literature
Project description:Pyrazolines are a significant class of heterocyclic compounds with essential biological activities. They are quite stable, which has inspired medicinal chemists to experiment with the ring's structure in many different ways to create a variety of pharmacological activities. The structures of numerous commercially available therapeutic agents contain a pyrazoline ring. Pyrazolines are well-known for their ability to treat neurodegenerative diseases. The neurodegenerative diseases that affect huge populations globally include Alzheimer's disease (AD), Parkinson's disease (PD), and psychiatric disorders. The neuroprotective properties of pyrazolines published since 2003 are covered in the current review. Structure-activity relationships (SARs), molecular docking simulation, anticholinesterase (anti-AChE), and monoamine oxidase (MAO A/B) inhibitory actions are all covered in this article. Pyrazolines were discovered to have beneficial effects in the management of AD and were revealed to be inhibitors of acetylcholine esterase (AChE) and beta-amyloid (Aβ) plaques. They were discovered to be efficient against PD and also targeted MAO B and COMT. It was discovered that the pyrazolines block MAO A to treat psychiatric diseases. Pyrazolines are significant heteroaromatic scaffolds with a variety of biological functions. They were discovered to be remarkably stable and serve as an indispensable anchor for the development of new drugs. By blocking AChE and MAOs, they may be used to treat neurodegenerative diseases. The discussion outlined here is an essential and helpful resource for medicinal chemists who are investigating and applying pyrazolines in neurodegenerative research initiatives as well as to expedite future research programs on neurodegenerative disorders.
| S-EPMC9631758 | biostudies-literature
Project description:Many potential immune therapeutic targets are similarly affected in adult-onset neurodegenerative diseases, such as Alzheimer's (AD) disease, Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD), as well as in a seemingly distinct Niemann-Pick type C disease with primarily juvenile onset. This strongly argues for an overlap in pathogenic mechanisms. The commonly researched immune targets include various immune cell subsets, such as microglia, peripheral macrophages, and regulatory T cells (Tregs); the complement system; and other soluble factors. In this review, we compare these neurodegenerative diseases from a clinical point of view and highlight common pathways and mechanisms of protein aggregation, neurodegeneration, and/or neuroinflammation that could potentially lead to shared treatment strategies for overlapping immune dysfunctions in these diseases. These approaches include but are not limited to immunisation, complement cascade blockade, microbiome regulation, inhibition of signal transduction, Treg boosting, and stem cell transplantation.
| S-EPMC10604382 | biostudies-literature
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| S-EPMC9258957 | biostudies-literature
Project description:The success of seed germination and the successful establishment of seedlings across diverse environmental conditions depends on seed vigour, which is of both economic and ecologic importance. The smoke-derived exogenous compound karrikins (KARs) and the endogenous plant hormone strigolactone (SL) are two classes of butanolide-containing molecules that follow highly similar signalling pathways to control diverse biological activities in plants. Unravelling the precise mode-of-action of these two classes of molecules in model species has been a key research objective. However, the specific and dynamic expression of biomolecules upon stimulation by these signalling molecules remains largely unknown. Genomic and post-genomic profiling approaches have enabled mining and association studies across the vast genetic diversity and phenotypic plasticity. Here, we review the background of smoke-assisted germination and vigour and the current knowledge of how plants perceive KAR and SL signalling and initiate the crosstalk with the germination-associated hormone pathways. The recent advancement of 'multi-omics' applications are discussed in the context of KAR signalling and with relevance to their adoption for superior agronomic trait development. The remaining challenges and future opportunities for integrating multi-omics datasets associated with their application in KAR-dependent seed germination and abiotic stress tolerance are also discussed.
| S-EPMC7593932 | biostudies-literature
Project description:Alzheimer's disease (AD) and Parkinson's disease (PD) are well-known neuronal degenerative disorders that share common pathological events. Approved medications alleviate symptoms but do not address the root cause of the disease. Energy dysfunction in the neuronal population leads to various pathological events and ultimately results in neuronal death. Identifying common therapeutic targets for these disorders may help in the drug discovery process. The Brodmann area 9 (BA9) region is affected in both the disease conditions and plays an essential role in cognitive, motor, and memory-related functions. Analyzing transcriptome data of BA9 provides deep insights related to common pathological pathways involved in AD and PD. In this work, we map the preprocessed BA9 fastq files generated by RNA-seq for disease and control samples with reference hg38 genomic assembly and identify common variants and differentially expressed genes (DEG). These variants are predominantly located in the 3' UTR (non-promoter) region, affecting the conserved transcription factor (TF) binding motifs involved in the methylation and acetylation process. We have constructed BA9-specific functional interaction networks, which show the relationship between TFs and DEGs. Based on expression signature analysis, we propose that MAPK1, VEGFR1/FLT1, and FGFR1 are promising drug targets to restore blood-brain barrier functionality by reducing neuroinflammation and may save neurons.
| S-EPMC8017312 | biostudies-literature
Project description:BackgroundIntervertebral disc degeneration (IVDD) is widely recognized as the primary etiological factor underlying low back pain, often necessitating surgical intervention as the sole recourse in severe cases. The metabolic pathway of arachidonic acid (AA), a pivotal regulator of inflammatory responses, influences the development and progression of IVDD.MethodsInitially, a comparative analysis was conducted to investigate the relationship between AA expression patterns and different stages of IVDD using single-cell sequencing (scRNA-seq) data. Additionally, three machine learning methods (LASSO, random forest, and support vector machine recursive feature elimination) were employed to identify hub genes associated with IVDD. Subsequently, a novel artificial intelligence prediction model was developed for IVDD based on an artificial neural network algorithm and validated using an independent dataset. The identified hub genes were further subjected to functional enrichment, immune infiltration, and Connectivity Map analysis. Moreover, external validation was performed using flow cytometry and real-time reverse transcription polymerase chain reaction analysis.ResultsBoth scRNA-seq and bulk RNA-seq data revealed a positive correlation between the severity of IVDD and the AA metabolic pathway. They also revealed increased AA metabolic activity in macrophages and neutrophils, as well as enhanced intercellular communication with nucleus pulposus cells. Utilizing advanced machine learning algorithms, five hub genes (AKR1C3, ALOX5, CYP2B6, EPHX2, and PLB1) were identified, and an incipient diagnostic model was developed with an AUC of 0.961 in the training cohort and 0.72 in the validation cohort. An in-depth exploration of the functionality of these hub genes revealed their notable association with inflammatory responses and immune cell infiltration. Lastly, AH6809 was found to delay IVDD by inhibiting AKR1C3.ConclusionsThis study offers comprehensive insights into potential biomarkers and small molecules associated with the early pathogenesis of IVDD. The identified biomarkers and the developed integrated diagnostic model hold great promise in predicting the onset of early IVDD. AH6809 was established as a therapeutic target for AKR1C3 in the treatment of IVDD, as evidenced by computer simulations and biological experiments.
| S-EPMC10675942 | biostudies-literature
Project description:BackgroundJuvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatic disease affecting children. Current medications merely alleviate symptoms rather than curing the disease. Hence, the identification and development of novel drug targets and biomarkers for JIA are imperative for enhancing treatment efficacy.MethodsWe employed two-sample Mendelian randomization (MR) analysis to investigate the causal effects of plasma proteins on JIA. Additionally, colocalization, bulk RNA-seq, and single-cell RNA-seq analyses were conducted to further investigate and validate the potential of candidate proteins as drug targets.ResultsThrough MR analysis, we successfully identified five plasma proteins that are causally linked to JIA. Genetically inferred lower levels of AIF1, TNF, and TNFSF11 were associated with an elevated risk of JIA, while higher levels of AGER and GP1BA proteins were positively correlated with JIA risk. Colocalization analysis further supported our findings on GP1BA (OR = 9.26, 95 % CI: 2.30-37.20) and TNFSF11 (OR = 0.18, 95 % CI: 0.07-0.45). Based on this evidence, we classified these five proteins into two tiers. Finally, we conducted a systematic evaluation of the druggability and current drug development progress for these identified candidate proteins.ConclusionsThis study employed MR analysis to reveal causal relationships between plasma proteins and JIA, identifying five potential candidate proteins as promising drug targets for JIA, particularly focusing on GP1BA and TNFSF11.
| S-EPMC11565427 | biostudies-literature