Current Genomics最新文献

{"title":"Precision Medicine in Neurodegenerative Diseases: Genomic Approaches to Target Amyloid-β, Tau, and Alpha-Synuclein Pathways.","authors":"Zaid Waqar, Pranshul Sethi, Divya Jain, Kuldeep Singh, Omar Awad Alsaidan, Sami I Alzarea, Jeetendra Kumar Gupta, Swati Saxena, Mukesh Chandra Sharma","doi":"10.2174/0113892029372437251010114053","DOIUrl":"10.2174/0113892029372437251010114053","url":null,"abstract":"<p><p>Neurodegenerative diseases, including Alzheimer's and Parkinson's disease, are characterized by the pathological aggregation of proteins such as amyloid-β, tau, and alpha-synuclein. These hallmark proteins play central roles in disease progression and represent promising targets for therapeutic intervention. Advances in precision medicine, driven by genomic technologies such as CRISPR-Cas systems, RNA-based therapies, and high-throughput sequencing, have enabled the development of tailored strategies to modulate these pathological pathways. This review examines the integration of genomic approaches in targeting amyloid-β, tau, and alpha-synuclein, emphasizing their potential to mitigate disease progression and improve patient outcomes. We highlight current progress in preclinical and clinical studies, discuss challenges associated with translating these therapies into clinical practice, and explore future directions for achieving therapeutic precision in neurodegenerative disorders. By examining the interplay of genetic, molecular, and therapeutic innovations, this review underscores the transformative potential of genomic medicine in addressing the unmet needs of neurodegenerative disease treatment.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"469-494"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147971231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple Confabulations Found in Bioinformatics Tasks Carried Out by Several Free Large Language Models.","authors":"Diego A Forero","doi":"10.2174/0113892029403403260112075225","DOIUrl":"10.2174/0113892029403403260112075225","url":null,"abstract":"<p><p>Bioinformatics is one of the main areas in the health sciences with great potential for the application of Large Language Models (LLMs), as it mainly involves computational analysis of results derived from experimental and high-throughput analysis of human, animal, and cellular models. Testing available general-purpose LLMs for the presence of inaccurate answers, such as confabulations, is of great interest in the fields of bioinformatics and computational genomics. In the current study, we carried out an analysis of the performance of six freely available LLMs (Gemini, ChatGPT, Grok, Claude, Llama, and DeepSeek) in a number of tasks commonly used in bioinformatics and computational genomics, with varying levels of difficulty. The selected tasks were: converting different identifiers (for two organisms), simulating a bisulfite conversion of DNA sequences, identifying the effects on amino acids of DNA polymorphisms, retrieving orthologues in mouse, identifying GO ontologies and KEGG pathways for lists of genes, interpreting a Volcano plot for gene expression, and automatically generating R code to visualize data. In general, our analysis identified a multiplicity of confabulations for different types of results generated by the tested LLMs. Our results highlighted a high number of errors in the output of the LLMs and identified automatic generation of code as a promising area. Future studies will be needed for a better understanding of the causes of confabulations of LLMs in research-related tasks.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"703-712"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Collagen Genetic Variability in Degenerative Disc Disease and Related Conditions.","authors":"Adulrahman M Bani Khaled, Abdelrahim Alqudah, Esam Qnais, Badriyah S Alotaibi, Baker Al-Shara, Alaa Aa Aljabali","doi":"10.2174/0113892029385458260414060252","DOIUrl":"10.2174/0113892029385458260414060252","url":null,"abstract":"<p><p>Degenerative Disc Disease (DDD) and related musculoskeletal disorders depend heavily on the structural integrity of collagen in the Extracellular Matrix (ECM) of connective tissues. The roles of collagen types I, II, IX, and XI in Intervertebral Disc (IVD) dynamics have been previously examined. Genetic polymorphisms in collagen-encoding genes are associated with susceptibility to DDD. These polymorphisms influence the quality and arrangement of collagen fibrils, thereby affecting the overall health of the connective tissues. CRISPR/Cas9 offers a viable method for correcting pathogenic genetic variants associated with collagen-related pathologies. This review also emphasizes the need for a deeper understanding of gene-environment interactions, which is critical for the development of personalized medicine for the treatment and management of DDD and related conditions. Expanding genetic studies and integrating insights into biomaterials and tissue engineering are essential for this purpose. A comprehensive genetic approach promises advances in predictive, preventive, and personalized health care.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 7","pages":"741-770"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RNA Modifications as Drug Targets: Unlocking the Therapeutic Potential of the Epitranscriptome.","authors":"Dhananjay Taumar, Atul Pratap Singh, Himanchal Sharma, Vatan Chaudhary","doi":"10.2174/0113892029406032260414100243","DOIUrl":"10.2174/0113892029406032260414100243","url":null,"abstract":"<p><strong>Introduction: </strong>The epitranscriptome covers reversible changes to RNA. These changes help control gene expression by making RNA more stable, easier to use, or more prone to degradation. They are increasingly implicated in disease development and offer a promising target for treatment. This review covers RNA alterations and their potential clinical applications.</p><p><strong>Methods: </strong>The systematic analysis of the peer-reviewed literature was performed, including experimental, clinical, and computational research. The biochemical properties and biological functions were used to classify RNA modifications. In addition, we evaluated current therapeutic options, including small molecules, CRISPR/Cas-based technologies, and RNA-targeted approaches.</p><p><strong>Results: </strong>RNA undergoes immense changes, including N6-methyladenosine (m6A), 5-methylcytosine (m5C), and pseudouridine. By these modifications, the genes are regulated by coordinated writers, erasers, and readers. Targeted therapeutics aim to regulate changes in cancer, neurodegenerative disease, and viral diseases. Several limitations remain, including overly general framing, suboptimal clarity in conveying the message, and inadequate response mechanisms.</p><p><strong>Discussion: </strong>The epitranscriptome provides an additional regulatory layer with significant therapeutic applications. New techniques appear to be successful. Researchers, in turn, should be more specific. These therapies require improved delivery vehicles and reduced side effects not associated with the treatment to be safe and effective for the patient.</p><p><strong>Conclusion: </strong>Therapy targeting RNA-based modifications is a breakthrough in disease treatment. These chemical modifications affect gene function and expression patterns. The next step in the research requires overcoming current limitations to fully realize the therapeutic potential of epitranscriptomics-based interventions.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 7","pages":"802-818"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDT1 is a Potential Therapeutic Target for the Progression of NAFLD to HCC and the Exacerbation of Cancer.","authors":"Xingyu He, Jun Ma, Xue Yan, Xiangyu Yang, Ping Wang, Lijie Zhang, Na Li, Zheng Shi","doi":"10.2174/0113892029313473240919105819","DOIUrl":"10.2174/0113892029313473240919105819","url":null,"abstract":"<p><strong>Aims: </strong>This study aimed to identify potential therapeutic targets in the progression from non-alcoholic fatty liver disease (NAFLD) to hepatocellular carcinoma (HCC), with a focus on genes that could influence disease development and progression.</p><p><strong>Background: </strong>Hepatocellular carcinoma, significantly driven by non-alcoholic fatty liver disease, represents a major global health challenge due to late-stage diagnosis and limited treatment options. This study utilized bioinformatics to analyze data from GEO and TCGA, aiming to uncover molecular biomarkers that bridge NAFLD to HCC. Through identifying critical genes and pathways, our research seeks to advance early detection and develop targeted therapies, potentially improving prognosis and personalizing treatment for NAFLD-HCC patients.</p><p><strong>Objectives: </strong>Identify key genes that differ between NAFLD and HCC; Analyze these genes to understand their roles in disease progression; Validate the functions of these genes in NAFLD to HCC transition.</p><p><strong>Methods: </strong>Initially, we identified a set of genes differentially expressed in both NAFLD and HCC using second-generation sequencing data from the GEO and TCGA databases. We then employed a Cox proportional hazards model and a Lasso regression model, applying machine learning techniques to the large sample data from TCGA. This approach was used to screen for key disease-related genes, and an external dataset was utilized for model validation. Additionally, pseudo-temporal sequencing analysis of single-cell sequencing data was performed to further examine the variations in these genes in NAFLD and HCC.</p><p><strong>Results: </strong>The machine learning analysis identified IGSF3, CENPW, CDT1, and CDC6 as key genes. Furthermore, constructing a machine learning model for CDT1 revealed it to be the most critical gene, with model validation yielding an ROC value greater than 0.80. The single-cell sequencing data analysis confirmed significant variations in the four predicted key genes between the NAFLD and HCC groups.</p><p><strong>Conclusion: </strong>Our study underscores the pivotal role of CDT1 in the progression from NAFLD to HCC. This finding opens new avenues for early diagnosis and targeted therapy of HCC, highlighting CDT1 as a potential therapeutic target.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 3","pages":"225-243"},"PeriodicalIF":1.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12107793/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APP Gene-based Strategies to Combat Alzheimer's Disease in Down Syndrome.","authors":"Xu-Qiao Chen","doi":"10.2174/0113892029360836250127103637","DOIUrl":"10.2174/0113892029360836250127103637","url":null,"abstract":"","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 4","pages":"245-248"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12606666/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of Long Noncoding RNA Dio3os in Glycolipid Metabolism.","authors":"Xinchen Wang, Shiyun Zeng, Yuting Liu, Yulan Shi, Fenghua Qu, Li Li, Qirui Zhang, Ding Yuan, Chengfu Yuan","doi":"10.2174/0113892029345945241125064704","DOIUrl":"10.2174/0113892029345945241125064704","url":null,"abstract":"<p><strong>Introduction: </strong>Recent investigations have underscored the importance of long non-coding RNAs (lncRNAs), which exhibit more specific expression in tissues and cells than mRNA and are involved in gene regulation during development, pathology, and other processes through various mechanisms. Despite the predominant focus on the role of lncRNA Dio3os in cancer research, there has been relatively limited exploration of its potential involvement in glycolipid metabolism. Therefore, this study aims to consolidate existing knowledge on the function of Dio3os in glycolipid metabolism and calls for a broader investigation into its physiological roles.</p><p><strong>Methods: </strong>This review synthesizes available literature to detail the gene characteristics of lncRNA Dio3os and its expression patterns. It also compiles recent insights and mechanisms pertaining to Dio3os's involvement in glycolipid metabolism, particularly its participation in the ceRNA regulatory network.</p><p><strong>Results: </strong>Recent studies demonstrate that lncRNA Dio3os regulates glycolysis in cancer cells and impacts obesity, potentially serving as an indicator for diabetic peripheral neuropathy. Furthermore, its diminished expression has been noted in atherosclerotic plaques.</p><p><strong>Conclusion: </strong>lncRNA Dio3os exerts a significant regulatory influence on glycolipid metabolism, with variations in its expression levels potentially affecting disease presentations. Further investigations are warranted to elucidate the precise relationship between lncRNA Dio3os and its associated pathologies.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 4","pages":"260-272"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12606660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YY2 Serves as a Novel Prognostic Biomarker Correlated with Immune Microenvironment and Glycolysis in Esophageal Carcinoma.","authors":"Haimei Gou, Hui Yang, Jiao Cheng, Shuang He, Can Luo, Xin Chen, Xiaowu Zhong","doi":"10.2174/0113892029358348250124064940","DOIUrl":"10.2174/0113892029358348250124064940","url":null,"abstract":"<p><strong>Background: </strong>Yin Yang 2 (YY2) plays a pivotal role in various tumorigenic processes; however, its specific involvement in esophageal carcinoma (ESCA) remains elusive. This study aims to investigate the expression and potential functional significance of YY2 in ESCA.</p><p><strong>Methods: </strong>The expression and functions of YY2 in ESCA were analyzed using a broad range of bioinformatics databases and tools, including TCGA, TIMER, TISIDB, QUANTISEQ, cBioPortal, DNMIVD, LinkedOmics, DAVID, GSEA, GEPIA2, LASSO, miRWalk, miRDB, and TargetScan. Furthermore, RT-qPCR, immunohistochemical staining, western blot, CCK8 assay, and wound healing assay were employed to validate the involvement of YY2 in ESCA pathogenesis.</p><p><strong>Results: </strong>Bioinformatics analyses revealed that the YY2 gene is upregulated in ESCA tissues, with its high expression significantly associated with poor prognosis and elevated levels of M2 macrophages, NK cells, Tregs, CTLA4, TIGIT, and Siglec-15. Validating the ESCA samples demonstrated that knockdown of YY2 effectively inhibited cell proliferation and migration in ESCA cells. The biological functions of YY2 and its co-expressed genes were primarily associated with transcriptional regulation, DNA methylation, glycometabolism, and ubiquitination. Moreover, the regulatory network of YY2 in the glycolysis pathway was found to involve multiple genes and miRNAs. Finally, a prognostic model based on YY2 and its associated glycolysis genes revealed a strong inverse correlation between higher risk scores and lower survival rates in esophageal adenocarcinoma (EAC).</p><p><strong>Conclusion: </strong>YY2 may serve as a promising prognostic biomarker and an innovative therapeutic target for patients with ESCA, regulating cell proliferation, migration, immune microenvironment, and glycolysis.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 4","pages":"312-328"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12606659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MLA-ac4C: A N4-Acetylcytidine Site Prediction Model Based on Multi-Layer Attention, Bidirectional GRU, and DenseNet.","authors":"Jianhua Jia, Guanding Li, Mingwei Sun","doi":"10.2174/0113892029407030251229080710","DOIUrl":"10.2174/0113892029407030251229080710","url":null,"abstract":"<p><strong>Introduction: </strong>N4-acetylcytidine (ac4C) is a highly conserved post-transcriptional modification found in mRNA, known to play a critical role in the regulation of mRNA translation. Traditional experimental approaches for identifying ac4C sites are both time-consuming and costly, underscoring the need for more efficient computational prediction methods. Although various deep learning models have been proposed for ac4C site prediction, most rely on ordinary encoding strategies and simplistic network architectures, which limit their ability to capture high-dimensional features of mRNA sequences. In this study, we propose a novel framework that combines multiple encoding schemes with a hierarchical network structure to improve prediction accuracy.</p><p><strong>Methods: </strong>We developed a new deep learning model, MLA-ac4C, based on a dual-pathway architecture. In the first pathway, one-hot encoding combined with positional encoding is used to represent the sequence, followed by a Bidirectional Gated Recurrent Unit (Bi-GRU) network to extract global features. In the second pathway, a hybrid encoding scheme integrating nucleotide chemical property (NCP), Electron-Ion Interaction Pseudopotential (EIIP), and Pseudo K-Tuple Nucleotide Composition (PseKNC) is used, and local features are extracted using Densely Connected Convolutional Networks (DenseNet). A multi-layer attention mechanism is then applied to integrate the features from both pathways and capture high-level representations for classification.</p><p><strong>Results: </strong>Rigorous evaluation on an independent test dataset shows that MLA-ac4C achieves superior performance, with Sensitivity (Sn), Specificity (Sp), Accuracy (Acc), Matthews correlation coefficient (MCC), and Area Under The ROC Curve (AUROC) reaching 83.88%, 85.14%, 84.51%, 69.03%, and 92.74%, respectively. These results outperform those of existing state-of-the-art models.</p><p><strong>Conclusion: </strong>We present MLA-ac4C, a deep learning model based on Bi-GRU, DenseNet, and a multi-layer attention mechanism. Experimental results demonstrate that it provides a more accurate and efficient approach for predicting ac4C modification sites compared to existing methods.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 6","pages":"713-725"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurological Insights into 16p11.2- And 22q11.2-Related Disorders: A Mini-Review.","authors":"Yung-Hsiu Lu, Yann-Jang Chen, Shan-Ju Lin, Ting-Rong Hsu, Dau-Ming Niu, Wei-Sheng Lin","doi":"10.2174/0113892029338299241211063307","DOIUrl":"10.2174/0113892029338299241211063307","url":null,"abstract":"<p><p>Copy Number Variations (CNVs) involving 16p11.2 or 22q11.2 are often linked to neurodevelopmental and neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, cognitive impairment, epilepsy, and schizophrenia. The pathogenetic mechanisms underlying these neurological phenotypes remain incompletely understood, partly due to the multitude of genes involved and the complex gene-gene interactions at these loci. Nonetheless, recent advances in experimental technology and bioinformatics have greatly enhanced our understanding of the neurobiology of 16p11.2- and 22q11.2-related disorders. Herein, we aim to provide an updated mini-review on neurological aspects of these disease-associated CNVs, with emphasis on clinical and mechanistic insights as well as potential therapeutic implications.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"26 4","pages":"249-259"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12606657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}