Frontiers in Genetics最新文献

Background: Neurofibromatosis type 1 (NF1) is a rare autosomal dominant disorder that presents complex physical, emotional, and social challenges. Despite clear diagnostic criteria, NF1 is often diagnosed late due to vague early symptoms, everyday or non-medical interpretations of early signs, and limited access to specialists and genetic testing. This study explores how individuals with NF1 experience the diagnostic process in this context.

Methods: Ninety-three adults with medically confirmed NF1 participated in in-depth interviews conducted between August 1 and 31 December 2020. Data were analyzed using reflexive thematic analysis, following Braun and Clarke's six-phase framework to explore patterns in participants' experiences and meaning-making related to diagnosis.

Results: The diagnostic pathway for NF1 was often prolonged, fragmented, and emotionally taxing. Delays frequently stemmed from the normalization of early signs (e.g., café-au-lait macules or subcutaneous nodules) by both families and physicians. Many participants received their diagnosis incidentally, or only after persistent self-advocacy, parental initiative, or the diagnosis of their child. While some family members, particularly mothers, played an active diagnostic role, others responded with denial, minimization, or reluctance to discuss symptoms, which in turn prolonged the search for answers. Structural factors, such as limited NF1-specific familiarity among primary care providers, constrained referral pathways, and regional disparities, further complicated the diagnostic odyssey. The unpredictability and burden of diagnosis often led to frustration and emotional fatigue, particularly among those who lacked a family history of the disease.

Conclusion: This study emphasizes the need for earlier NF1 recognition through enhanced clinician awareness, better diagnostic coordination, and access to genetic and psychosocial support. It also highlights the role of patient agency and the emotional cost of delayed diagnosis in rare diseases. These findings point to several actionable priorities, including the need to strengthen NF1-specific training for primary care physicians, implement clearer referral pathways, and expand access to genetic counselling and psychosocial support.

Introduction: Protein-protein interaction (PPI) networks serve as the central framework for deciphering the modular structure of cellular functions and signal transduction mechanisms. While established network topological Measures (such as degree centrality, betweenness centrality, and closeness centrality) can statically characterize nodal connectivity density or pathway intermediation capacity, they fail to dynamically capture cascade following node failure.

Method: This study employs systems biology approaches to quantitatively analyze network resilience based on bacterial PPI network data obtained from the Stanford Network Analysis Platform (SNAP). First, a progressive node removal strategy was implemented to simulate cascading failure propagation and evaluate system-level resilience degradation dynamics. Subsequently, single-node knockout experiments were systematically conducted to quantify local topological disruption effects, with network fragmentation metrics (e.g., giant component size decay rate) being integrated to establish the Node Resilience (NR) index. To validate the biological relevance of NR, we developed a multidimensional analytical framework that performs cross-correlation analysis between NR and classical centrality measures [Degree centrality (DC), Betweenness centrality (BC), Closeness centrality (CC), Eigenvector centrality (EC)], enabling systematic revelation of consensus vital nodes identified by both approaches, and unique sensitive nodes detectable only through resilience-oriented perturbation analysis.

Results and discussion: Our systematic node removal simulations revealed biphasic resilience degradation across bacterial PPI networks: progressive node failure induced gradual resilience decay whereas exceeding a critical threshold for each network triggered accelerated collapse. This phase transition aligns with evolutionary design principles - modular architectures buffer localized perturbations through functional redundancy, but inter-modular bridge depletion beyond criticality propagates cascading failures via weakly coupled connections. Notably, NR exhibited a strong negative correlation with BC, contrasting with weak associations for DC, CC, and EC. This dichotomy arises because BC quantifies cross-modular information brokerage - high-BC nodes act as structural keystones whose removal disconnects functional modules, drastically reducing global entropy. Conversely, for DC, CC, and EC primarily reflect local connectivity patterns with limited cascade propagation potential.

Predicting drug-diseases associations provides hints in developing new drugs. Various computational methods have been developed. To develop better models for predicting drug-disease associations, two types of key resources must be obtained, the benchmarking dataset and the baseline performances. Collecting these resources usually requires extensive labors in reading literatures and extracting relevant information from the literature manually. We developed DDA-Bench databases services, which curates commonly used benchmarking datasets and up-to-date performance values from baseline studies. We analyzed data records in DDA-Bench database. We proposed that performance variations for a given method in the context of different reports should be noticed. The impact of dataset density on predictive performance exists, and should be considered in future studies. In addition, we release the DDA-Bench database to the public. The DDA-Bench database saves time and efforts in constructing data basis for developing new models for predicting drug-disease associations. The DDA-Bench database can be accessed at https://dda.csbios.net.

Recurrent spontaneous abortion (RSA), defined as two or more consecutive pregnancy losses, affects 1%-5% of couples and poses a significant challenge to reproductive health. Despite its prevalence, the underlying etiology remains elusive in approximately half of all cases, hindering the development of targeted therapies. The emerging field of epitranscriptomics, particularly the dynamic and reversible N6-methyladenosine (m6A) RNA modification, offers a novel lens through which to investigate the complex gene-environment interactions underlying RSA. This review systematically synthesizes current knowledge on the pivotal roles of m6A modification in key processes essential for a successful pregnancy: gametogenesis and early embryo quality, placental development and function, and the establishment of immune tolerance at the maternal-fetal interface. We critically evaluate the direct and indirect evidence linking dysregulation of specific m6A regulators to the pathophysiology of RSA, drawing from human tissue studies, RSA animal models, and insights extrapolated from related fields.Furthermore, we discuss the translational potential and considerable challenges of targeting the m6A machinery for therapeutic intervention in RSA. This review aims not only to summarize the current landscape but also to provide a critical framework to guide future mechanistic and clinical research in this promising area.

Background: Primary coenzyme Q10 (CoQ10) deficiency is a rare, treatable mitochondrial disorder often caused by biallelic pathogenic variants in COQ8A gene (also known as ADCK3). It typically manifests as childhood-onset cerebellar ataxia with variable multisystem involvement. Early recognition is critical, as CoQ10 supplementation has potential to significantly alleviate clinical manifestations and modify natural progression of the disease. Here, we provide a rare phenotype of paroxysmal dyskinesias caused by compound heterozygous variants of COQ8A gene.

Case: A 21-year-old man presented with myoclonic tremor, mild dysarthria, ataxia and emotional instability. The brain MRI showed cerebellar atrophy. Biochemical workup revealed low plasma CoQ10 levels. Whole-exome sequencing identified compound heterozygous COQ8A variants: two novel missense substitutions [NM_020247.5:c.641T>A (p.Leu214Gln), NM_020247.5:c.1621T>C (p.Ser541Pro)], each inherited from an asymptomatic parent. The patient was initiated on oral CoQ10 at a dose of 200 mg twice daily, accompanied by supportive interventions targeting emotional regulation. A marked improvement in tremor symptoms was observed shortly after treatment initiation; however, intermittent muscle tremors persisted during periods of emotional agitation. At 1-year follow-up, the patient remained on CoQ10 at 300 mg twice daily and levetiracetam at 500 mg twice daily, with sustained symptom control.

Conclusion: This case highlights that COQ8A-related CoQ10 deficiency can present with serious neurological crises among young people and underscores the importance of rapid genetic diagnosis in such scenarios. Early and aggressive CoQ10 supplementation led to clinical stabilization in our patient, reinforcing that primary CoQ10 deficiency is a reversible cause of neurodegenerative disease. We emphasize genotype-phenotype diversity in COQ8A disease and the crucial need for early detection and treatment to improve prognosis. We propose that clinicians maintain a high index of suspicion for primary CoQ10 deficiency in patients presenting with unexplained dystonia or ataxia, as timely intervention may significantly improve clinical outcomes.

Background: This study aims to elucidate the pathogenicity of the TPM1 mutation (NM_001018005.2:c.541G>A, p. Glu181Lys) in restrictive cardiomyopathy (RCM), establish its ACMG pathogenicity classification, and report for the first time its association with sporadic RCM and underlying molecular mechanisms. The research focuses on delineating how this mutation triggers myocardial pathology via disruption of the CaMKII/HDAC4 signaling pathway.

Methods: Protein 3D modeling predicted structural alterations induced by the mutation. TPM1-wild-type (WT) and mutant (p.E181K) plasmids were transfected into AC16 cardiomyocyte cell lines. Quantitative PCR (qPCR) and Western blotting (WB) analyzed gene/protein expression levels. Intracellular calcium transients were detected using Rhod-2 AM fluorescent probes. F-actin cytoskeletal reorganization was assessed by Phalloidin-488 staining. Phosphorylation status of key CaMKII/HDAC4 pathway components and troponin (Tn) activity were evaluated to define functional mechanisms.

Results: Bioinformatic analysis revealed disruption of hydrogen bonding and electrostatic potential at the mutation site. TPM1-p.E181K did not alter overall protein expression or mitochondrial activity but significantly suppressed intracellular Ca²⁺ transients and inhibited CaMKII/HDAC4 phosphorylation. Impaired troponin activity and abnormal cardiomyocyte contractility were observed.

Conclusion: This study establishes a novel link between TPM1-p.E181K and sporadic RCM. We demonstrate that its pathogenesis is mediated through a cascade of events: calcium dyshomeostasis leads to the suppression of CaMKII/HDAC4 phosphorylation, which subsequently causes sarcomere structural disruption, and ultimately results in myocardial hypercontractility. This identified signaling axis may represent a promising therapeutic target for RCM.

This study aimed to understand the differential and tissue-specific immune responses of three different chicken strains [Vanraja, Kashmir Commercial Layer (KCL), and broiler] by assessing the CXCLi1 chemokine mRNA expression in different tissues (liver, spleen, and cecum) in Salmonella Typhimurium-challenged birds. In addition, hematological and biochemical parameters were also assessed. Salmonella enterica serovar Typhimurium culture was used for induction of infection. Differential expression of the CXCLi1 gene following induced infection was studied on different days post-infection (0, 1, 3, 5, 7, 9, 11, 13, and 15). An infection dose of 2 × 10⁸ CFU/mL produced the symptoms characteristics of salmonellosis. An immune response gene expression study revealed enhanced expression until the 5th-7th day post-infection, followed by a steady decrease until the 15th day post-infection. The overall gene expression was higher in broiler chicks than in KCL and Vanraja chicks. The tissue-specific response showed higher expression in the cecum followed by the spleen and liver. The real-time mRNA gene expression results indicated that commercial broilers are more susceptible than backyard chicks. Differential cellular responses revealed heterophilia and initial lymphopenia followed by lymphocytosis. Pronounced hemato-biochemical alterations were observed as the clinical indicators of Salmonella infection. These findings imply that the integration of disease-resistant alleles from indigenous or backyard poultry into high-performance exotic germplasm could improve Salmonella resistance in commercial poultry populations.

Background: Susceptibility to infectious diseases is a result of complex interactions between genomic, environmental, and clinical factors. COVID-19 severity and post-acute sequelae of COVID-19 (PASC) vary widely among individuals, yet its genetic determinants remain underexplored in Indian populations. In this article, we undertake an exploratory analysis to investigate candidate genetic variants and biological pathways underlying the clinical outcomes in COVID-19 severity and PASC.

Methods: Sixty individuals with a history of COVID-19 were genotyped, and their data were supplemented with publicly available datasets from the Genome Asia 100K and Gujarat Biotechnology Research Centre. Two case-control genome-wide association study (GWAS) models were analyzed: (i) COVID-19 severity (mild/asymptomatic vs. severe) and (ii) an exploratory, hypothesis-generating GWAS for PASC (presence vs. absence of post-COVID-19 complications). Candidate genes identified here were further compared with RNA-sequencing datasets derived from brain and lung tissues of SARS-CoV-2-infected hamsters. The population-specific genetic risk for PASC was estimated using the polygenic risk score algorithm PRSice-2.

Results: GWAS identified candidate genes common to both COVID-19 severity and PASC, including CNTNAP2, WWOX, and ADAMTS17, which are implicated in extracellular matrix remodeling and neurological and cognitive development. We identified 806 candidate genes shared between the severity and PASC cohorts. Of these, 30 protein-coding genes were associated with neuropsychiatric disorders, and 23 were linked to cardiovascular conditions. Notably, CACNA1C, SLC8A1, GRK5, PDE4B, and LRRK2 were identified in both categories, suggesting potential convergence of molecular pathways underlying neurological and cardiovascular dysfunction. Integration with transcriptomic data reinforced the involvement of shared molecular pathways disrupted by SARS-CoV-2 infection. Polygenic risk analysis revealed significant population-specific variation in genetic predisposition to PASC.

Conclusion: Genetic susceptibility to severe COVID-19 and PASC in Indian populations appears to be linked to dysregulation of pathways central to cardiac and neurological function. These findings, derived from an exploratory PASC GWAS, provide preliminary insights into the molecular mechanisms that may underlie the post-viral sequelae. These emphasize the need for population-wide genomic studies to validate the candidate associations, better understand PASC risk, and facilitate the development of precision diagnostics and therapeutics.

The purpose of this paper is to explore the mechanism of 18β glycyrrhetinic acid (18β-GRA) in treating gastric cancer. Firstly, the toxicological effects of 18β-GRA were predicted using the ProTox3.0 database. Then, candidate biomarkers for the anti-gastric cancer of 18β-GRA were screened using the weighted gene co-expression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), the support vector machine (SVM), the random forest algorithm combined with the TMT proteomics methods. Additionally, we explored the potential upstream transcription factors and downstream interacting proteins of the biomarkers. The WGCNA method yielded 269 targets, while TMT proteomics analysis identified 6,273 genes. Among these, 12 targets were identical. Using LASSO, SVM, and random forest algorithms, three candidate markers were identified: insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3), keratin 6B (KRT6B), and E3 ubiquitin-protein ligase NEDD4-like (NEDD4L). Based on molecular docking and molecular dynamics results, NEDD4L is believed to be a 18β-GRA biomarker, while sodium channel protein type 5 subunit alpha (SCN5A) and early growth response protein 1 (EGR1) are the potential upstream and downstream regulatory proteins, respectively. These findings provide a theoretical basis for future experimental verification.