Frontiers in Genetics最新文献

{"title":"Generalized information criteria for personalized gene network inference.","authors":"Heewon Park, Seiya Imoto, Sadanori Konishi","doi":"10.3389/fgene.2025.1583756","DOIUrl":"10.3389/fgene.2025.1583756","url":null,"abstract":"<p><p>Identifying individual genomic characteristics is a critical focus in personalized therapies. To reveal targets in such therapies, we considered personalized gene network analysis using kernel-based <math> <mrow> <msub><mrow><mi>L</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> </math> -type regularization methods. In kernel-based <math> <mrow> <msub><mrow><mi>L</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> </math> -type regularized modeling, selecting optimal regularization parameters is crucial because edge selection and weight estimation depend heavily on such parameters. Furthermore, selecting a kernel bandwidth that controls sample weighting is vital for personalized modeling. Although cross-validation and information criteria (i.e., AIC and BIC) are often used for parameter selection, such traditional techniques are computationally expensive or unsuitable for approaches based on estimation techniques other than maximum likelihood estimation. To overcome these issues, we introduced a novel evaluation criterion in line with the generalized information criterion (GIC), which relaxes the assumption of maximum likelihood estimation, making it suitable for personalized gene network analysis based on various estimation techniques. Monte Carlo simulations demonstrated that the proposed GIC outperforms existing evaluation criteria in terms of edge selection and weight estimation. Acute myeloid leukemia (AML) drug sensitivity-specific gene network analysis revealed critical molecular interactions to uncover ALM drugs resistant mechanism. Notably, PIK3CD activation and RARA/RELA suppression are crucial markers for improving AML chemotherapy efficacy. We also applied our strategy for gastric cancer drug sensitivity analysis and uncovered personalized therapeutic targets. We expect that the proposed sample specific GIC will be a useful tool for evaluating personalized modeling, including in sample characteristic-specific gene networks analysis.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1583756"},"PeriodicalIF":2.8,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144575328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics.","authors":"Xiaojuan Yang, Yutao Duan, Lei Qiu, Xia Huang, Fei Li","doi":"10.3389/fgene.2025.1567173","DOIUrl":"10.3389/fgene.2025.1567173","url":null,"abstract":"<p><strong>Background: </strong>Research has demonstrated that the homeostasis of mitochondria and programmed cell death (PCD) are intimately linked to chronic obstructive pulmonary disease (COPD). Consequently, identifying biomarkers of COPD from mitochondria-related genes (MRGs) and programmed cell death-related genes (PCD-RGs) is of paramount importance.</p><p><strong>Methods: </strong>Differentially expressed genes (DEGs) from the GSE42057 dataset and COPD-related genes (COPD-RGs) via weighted gene co-expression network analysis (WGCNA) were intersected with MRGs and PCD-RGs to select candidates. Machine learning identified biomarkers, validated across GSE42057 and GSE94916 datasets. Pathway enrichment, immune infiltration, and drug prediction analyses were performed.</p><p><strong>Results: </strong>Eight candidate genes were derived from intersecting DEGs, COPD-RGs, MRGs, and PCD-RGs. Five biomarkers (BCL2, CCR7, FAM162A, FOXO1, RPS3) were identified, showing consistent dysregulation in COPD. These biomarkers activated the \"ribosome\" pathway. CCR7 and FOXO1 correlated positively with naïve B cells, while BCL2 negatively correlated with M0 macrophages. BCL2 exhibited strong binding to dolastatin 10, beauvericin, and micellar paclitaxel. RT-qPCR confirmed biomarker expression.</p><p><strong>Conclusion: </strong>BCL2, CCR7, FAM162A, FOXO1, and RPS3 are biomarkers for COPD, providing a new breakthrough point for the treatment of this disease.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1567173"},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12222144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two novel variants in <i>CNNM2</i> disrupts magnesium efflux leading to neurodevelopmental disorders.","authors":"Huijuan Li, Jing Liu, Yingdi Liu, Yaning Liu, Kehui Lu, Juan Wen, Huimin Zhu, Desheng Liang, Zhuo Li, Lingqian Wu","doi":"10.3389/fgene.2025.1600877","DOIUrl":"10.3389/fgene.2025.1600877","url":null,"abstract":"<p><strong>Background: </strong>Hypomagnesemia, seizures, and impaired intellectual development 1 (HOMGSMR1) is a rare neurodevelopmental disorder associated with magnesium homeostasis disruption, caused by mutations in the <i>CNNM2</i> gene. HOMGSMR1 demonstrates considerable clinical heterogeneity, but the genotype-phenotype relationship remains insufficient.</p><p><strong>Methods: </strong>We recruited two unrelated families with NDDs, and potential variants were identified through whole exome sequencing and confirmed by Sanger sequencing. Quantitative PCR, Western blotting, immunofluorescent staining, and flow cytometry were used to assess functional changes in candidate <i>CNNM2</i> variants.</p><p><strong>Results: </strong>Two novel variants, p.E298del and p.P360R, in <i>CNNM2</i> gene were identified. The unique facial features of proband 1 may broaden the known phenotypic spectrum of HOMGSMR1. Functional studies confirmed that the p.E298del and p.P360R variants increased <i>CNNM2</i> transcription and protein levels, impairing the proper localization of the CNNM2 protein to the cell membrane. Two variant proteins accumulated in the cytoplasm and formed clumps. Furthermore, intracellular Mg²⁺ levels were higher in cells with these variants, disrupting magnesium homeostasis and potentially contributing to hypomagnesemia. Notably, the proteins of these two variants exhibited reduced stability and were prone to degradation, potentially providing new insights into the pathogenic mechanisms of <i>CNNM2</i>.</p><p><strong>Conclusion: </strong>Our study expands the mutation and phenotypic spectrum, as well as the functional studies of <i>CNNM2</i>, and contributes to genetic testing and prenatal diagnosis in families with HOMGSMR1.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1600877"},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12222124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GTMALoc: prediction of miRNA subcellular localization based on graph transformer and multi-head attention mechanism.","authors":"Xindi Huang, Jipu Jiang, Lifen Shi, Cheng Yan","doi":"10.3389/fgene.2025.1623008","DOIUrl":"10.3389/fgene.2025.1623008","url":null,"abstract":"<p><p>MicroRNAs (miRNAs) play a crucial role in regulating gene expression, and their subcellular localization is essential for understanding their biological functions. However, accurately predicting miRNA subcellular localization remains a challenging task due to their short sequences, complex structures, and diverse functions. To improve prediction accuracy, this study proposes a novel model based on a graph transformer and a multi-head attention mechanism. The model integrates multi-source features which include the miRNA sequence similarity network, miRNA functional similarity network, miRNA-mRNA association network, miRNA-drug association network, and miRNA-disease association network. Specifically, we first apply the node2vec algorithm to extract features from these biological networks. Then, we use a graph transformer to capture relationships between nodes within the networks, enabling a better understanding of miRNA functions across different biological contexts. Next, a multi-head attention mechanism is implemented to combine miRNA features from multiple networks, allowing the model to capture deeper feature relationships and enhance prediction performance. Performance evaluation shows that the proposed method achieves significant improvements over current approaches on open-access datasets, achieving high performance with an AUC (area of receiver operating characteristic curve) of 0.9108 and AUPR(area of precision-recall curve) of 0.8102. It not only significantly improves prediction accuracy but also exhibits strong generalization and stability.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1623008"},"PeriodicalIF":2.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12222170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epigenetic mechanisms linking atherosclerosis to ischemic stroke: insights from DNA methylation and transcriptome integration.","authors":"Binrong Ding, Yiqun Wang, Junfeng Li, Xuewei Zhang, Zhengqing Wan, Hao Wang","doi":"10.3389/fgene.2025.1567951","DOIUrl":"10.3389/fgene.2025.1567951","url":null,"abstract":"<p><strong>Background: </strong>Ischemic stroke (IS) is a major cause of mortality and disability, with atherosclerosis (AS) as a primary risk factor. DNA methylation plays a critical role in AS development, but its regulatory mechanisms remain unclear. This study aims to investigate the epigenetic regulatory mechanisms linking AS and IS by integrating DNA methylation and transcriptome data from public databases.</p><p><strong>Methods: </strong>This study integrated DNA methylation (GSE46394) and transcriptome data (GSE111782 and GSE162955) from public databases to investigate the molecular mechanisms linking AS and IS. Differentially methylated CpG positions (DMPs) and differentially expressed genes (DEGs) were identified (p < 0.05). Subsequent gene annotation and enrichment analyses were performed to uncover potential molecular mechanisms underlying the relationship between AS and IS.</p><p><strong>Results: </strong>A total of 5,396 consistent DMPs were identified in aortic and carotid atherosclerotic lesions, with enriched pathways such as MAPK signaling and Hippo signaling. Transcriptome analysis revealed 1,147 DEGs in AS plaques and 1,321 DEGs in IS brain tissues, enriched in pathways including neuroactive ligand-receptor interactions, calcium signaling, and vascular smooth muscle contraction. Overlapping analyses identified shared processes like actin filament polymerization, cell migration, and MAPK cascade regulation, as well as pathways such as adrenergic signaling, and apelin signaling.</p><p><strong>Conclusion: </strong>This study highlights the pivotal role of epigenetic regulation in AS and IS, uncovering key pathways and molecular processes involved in their progression. Future studies should validate these findings in larger cohorts and integrate multi-omics approaches for a comprehensive understanding.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1567951"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel causative <i>RYR2</i> indel variant with exon and intron involvement inducing exon 13 skipping in a family exhibiting catecholaminergic polymorphic ventricular tachycardia.","authors":"Ju Hyeon Shin, Taek Kyu Park, Sung-A Chang, Shin Yi Jang, June Huh, Chang Ahn Seol, Kyoung-Jin Park, Sung Hoon Kim, Duk-Kyung Kim, Hye Bin Gwag, Mi-Ae Jang","doi":"10.3389/fgene.2025.1581535","DOIUrl":"10.3389/fgene.2025.1581535","url":null,"abstract":"<p><p>Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a genetic disorder marked by exercise or stress-induced arrhythmias that lead to syncope or sudden cardiac death. Mutations of the <i>RYR2</i> gene can cause either CPVT or calcium release deficiency syndrome, with varying impacts on calcium release in cardiomyocytes. These mutations are predominantly missense variants associated with a gain-of-function mechanism. In this report, we present a novel pathogenic <i>RYR2</i> indel variant in a family afflicted with CPVT based on comprehensive molecular investigations. The proband was a 15-year-old girl who suffered a cardiac arrest during exercise and exhibited frequent premature ventricular beats on a treadmill test, which was consistent with CPVT. Using next-generation sequencing and Sanger sequencing, a novel <i>RYR2</i> indel variant, NM_001035.3:c.1006-44_1007delinsATTTTG, was identified. Sanger sequencing confirmed the presence of this variant in her mother, who also showed frequent premature ventricular beats on a treadmill test. Further RNA analysis revealed that this variant caused aberrant splicing, resulting in the skipping of exon 13 (r.1006_1170del), which would disrupt the intramolecular domain interactions. This discovery led to the classification of the variant as a likely pathogenic variant. We identified a novel <i>RYR2</i> indel variant responsible for CPVT and expanded the mutational spectrum of <i>RYR2</i>-related CPVT, emphasizing the importance of comprehensive genetic approaches for variant classification.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1581535"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benchmarking of feed-forward neural network models for genomic prediction of quantitative traits in pigs.","authors":"Junjian Wang, Francesco Tiezzi, Yijian Huang, Christian Maltecca, Jicai Jiang","doi":"10.3389/fgene.2025.1618891","DOIUrl":"10.3389/fgene.2025.1618891","url":null,"abstract":"<p><p>Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These advanced modeling capabilities make them promising candidates for genomic prediction by potentially capturing the intricate relationships between genetic variants and phenotypes. Despite these theoretical advantages, neural networks have shown inconsistent performance across previous genomic prediction research, and limited studies have evaluated their performance and feasibility specifically for pig genomic predictions using large-scale data. We evaluated the predictive performance of feed-forward neural network (FFNN) models implemented in TensorFlow with architectures ranging from single-layer (no hidden layers) to four-layer structures (three hidden layers). These FFNN models were compared with five linear methods, including GBLUP, LDAK-BOLT, BayesR, SLEMM-WW, and scikit-learn's ridge regression. The evaluation utilized data from six quantitative traits: off-test body weight (WT), off-test back fat thickness (BF), off-test loin muscle depth (MS), number of piglets born alive (NBA), number of piglets born dead (NBD), and number of piglets weaned (NW). We also assessed the computational efficiency of FFNN models on both CPU and GPU. The benchmarking employed repeated random subsampling validation with sample sizes ranging from 3,290 individuals for reproductive traits to over 26,000 individuals for production traits, using data from a total of 27,481 genotyped pigs. Hyperband tuning was used to optimize the hyper-parameters and select the best model for each structure. Results showed that FFNN models consistently underperformed compared to linear methods across all architectures tested. The one-layer structure yielded the best predictive accuracy among the FFNN approaches. Of the five linear methods, SLEMM-WW demonstrated the best balance of computational efficiency and predictive ability. GPUs offered significant computational efficiency gains for multi-layer FFNN models compared to CPUs, though FFNN models remained more computationally demanding than most linear methods. In conclusion, FFNN models with up to four layers did not improve genomic predictions compared to routine linear methods for pig quantitative traits.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1618891"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.","authors":"Zhi-Chuan He, Zheng-Zheng Song, Zhe Wu, Peng-Fei Lin, Xin-Xing Wang","doi":"10.3389/fgene.2025.1584334","DOIUrl":"10.3389/fgene.2025.1584334","url":null,"abstract":"<p><strong>Background: </strong>Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer (BRCA) with limited therapeutic targets. This study aimed to identify T cell-related signatures for TNBC diagnosis and prognosis.</p><p><strong>Methods: </strong>Clinical data and transcriptomic profiles were obtained from the TCGA-BRCA dataset, and single-cell RNA sequencing (scRNA-seq) data were downloaded from the GEO database. Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. Immune cell infiltration patterns were analyzed between high- and low-LR score groups, and Kaplan-Meier analysis evaluated the prognostic significance of hub genes. Functional enrichment and pathway analysis were performed using GSEA, and scRNA-seq data further explored hub gene-related pathways in immune cells.</p><p><strong>Results: </strong>Three hub genes (<i>CACNA1H</i>, <i>KCNJ11</i>, and <i>S100B</i>) were identified with strong diagnostic and prognostic relevance in TNBC. The LR model based on these genes achieved an AUC of 0.917 in diagnosing TNBC from other BRCA subtypes. Low LR scores were associated with poorer overall survival and reduced immune cell infiltration, particularly CD8 T cells and cytotoxic lymphocytes. <i>S100B</i> showed strong associations with the cytokine-cytokine receptor interaction pathway, JAK-STAT signaling, and T cell receptor signaling.</p><p><strong>Conclusion: </strong><i>CACNA1H</i>, <i>KCNJ11</i>, and <i>S100B</i> are potential diagnostic and prognostic biomarkers in TNBC. Their immune-related functions highlight their potential for guiding targeted immunotherapy strategies.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1584334"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Case Report: A case of ALS type 6 associated with a <i>FUS</i> gene variant and right limb muscle weakness and atrophy as the initial symptom.","authors":"Xiuping Zhan, Tingting Xuan, Xiaoyan Chen, Jianhang He, Yazhou Ren, Yue Meng, Guisheng Chen, Haining Li","doi":"10.3389/fgene.2025.1578249","DOIUrl":"10.3389/fgene.2025.1578249","url":null,"abstract":"<p><p>Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive degeneration of upper and lower motor neurons. This degeneration results in increasing muscle weakness, ultimately culminating in respiratory failure and death. Mutations in the fused in sarcoma (<i>FUS</i>) gene have been identified as a significant cause of ALS. Here, we present the case of a 40-year-old woman who exhibited right limb muscle weakness and atrophy as her initial symptom. Whole genome sequencing revealed a mutation in the <i>FUS</i> gene, specifically c.1450_1456delinsCCC (p.Tyr484Profs*44), leading to a diagnosis of ALS type 6 (ALS6). The c.1450_1456delinsCCC (p.Tyr484Profs*44) mutation is a frameshift mutation resulting from a non-triplet base deletion in the coding region of the <i>FUS</i> gene. This mutation is novel and has not been previously reported in China or internationally. Furthermore, the onset of muscle weakness and atrophy exclusively in the ipsilateral limb is very rare among ALS patients, and we have found no related reports. This case report aims to enhance medical professionals' understanding of the complexities associated with ALS caused by <i>FUS</i> gene mutations and the onset of ALS symptoms, thereby facilitating more accurate clinical diagnosis and treatment.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1578249"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Case Report: A first case of desmin-related myofibrillar myopathy due to inheritance from a confirmed mosaic asymptomatic carrier.","authors":"Jelle Vlaeminck, Sophie Uyttebroeck, Elke De Schutter, Ann Cordenier, Shauni Wellekens, Erwin Ströker, Kelly De Rooms, Christine Helsen, Frederik J Hes, Philippe Giron","doi":"10.3389/fgene.2025.1597851","DOIUrl":"10.3389/fgene.2025.1597851","url":null,"abstract":"<p><p>Desmin-related myofibrillar myopathy is a hereditary disorder caused by pathogenic variants in the <i>DES</i> gene (MIM*125660), altering desmin, a muscle-specific intermediate filament which is crucial for sarcomere integrity. This condition presents with skeletal myopathy, cardiomyopathy, and conduction abnormalities. Genetic counselling for index patients and their family members is complicated by variable expressivity, incomplete penetrance, and <i>de novo</i> occurrence. Mosaicism in asymptomatic parents can obscure inheritance patterns, particularly when low-grade mosaic variants in blood may be missed. In case of <i>DES</i>, mosaic carriership has not been described before. We describe a case of a 24-year-old female diagnosed with desmin-related myopathy due to a heterozygous pathogenic NM_001927.4 (<i>DES</i>):c.1216C>T, p.Arg406Trp variant. Cascade testing using targeted Sanger sequencing of her asymptomatic parents suggested the mother is a mosaic carrier of the pathogenic variant, which was confirmed though next-generation sequencing. The proband's siblings did not carry the <i>DES</i> c.1216C>T variant. We report the first documented case of mosaic carriership of a pathogenic <i>DES</i> variant in an asymptomatic individual and subsequent inheritance by the offspring, leading to desmin-related myopathy. This report highlights the importance of cascade testing in hereditary disorders with a focus on mosaicism, even when the index's biological parents are asymptomatic, and <i>de novo</i> emergence is suspected.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1597851"},"PeriodicalIF":2.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12213651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}