Frontiers in Genetics最新文献

{"title":"Rapid forensic ancestry inference in selected Northeast Asian populations: a Y-STR based attention-based ensemble framework for initial investigation guidance.","authors":"Kyo-Chan Koo","doi":"10.3389/fgene.2025.1631529","DOIUrl":"10.3389/fgene.2025.1631529","url":null,"abstract":"<p><strong>Introduction: </strong>Rapid inference of ancestral origin fromDNA evidence is critical in time-sensitive forensic investigations, particularly during the initial hours when crucial investigative decisions must be made. Although comprehensive analyses using multiple genetic markers provide thorough results, they often require significant processing time and resources. Y-chromosome short tandem repeats (Y-STRs) exhibit population-specific allelic distributions that facilitate rapid analysis, making them particularly valuable for initial screening in forensic contexts.</p><p><strong>Methods: </strong>This study aims to enhance population classification accuracy using Y-STR profile analysis, with a particular focus on Northeast Asian populations that are often merged into a single group by commercial ancestry panels. We developed a machine learning architecture centered on an attention-based ensemble mechanism that incorporates three complementary algorithms: a One-vs-Rest Random Forest, XGBoost, and Logistic Regression, each configured to effectively manage imbalanced datasets.</p><p><strong>Results: </strong>Utilizing only Y-STR data, the model achieved an overall accuracy of 80%-81% and demonstrated high stability. Notably, the model effectively processes imbalanced datasets, generating reliable outcomes for rapid ancestry assessment in time-critical investigations.</p><p><strong>Discussion: </strong>By addressing a key limitation in commercial ancestry panels--their failure to differentiate among Northeast Asian subpopulations--this framework provides valuable preliminary guidance in forensic cases involving Asian individuals. Consequently, our approach enhances rapid screening capabilities, which can inform early-stage investigations while complementing subsequent, more comprehensive genetic analyses.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1631529"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485621/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212540","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":"Genetic and <i>in silico</i> functional characterization of a novel structural variant in the <i>PAH</i> gene by long-reads sequencing and structural modeling.","authors":"Viviana Gallardo, Alexis Gaete, Jonathan Maldonado, Paulina Morales, Angela Peña, Valerie Hamilton, Víctor Faundes, Lorena Santa María","doi":"10.3389/fgene.2025.1669007","DOIUrl":"10.3389/fgene.2025.1669007","url":null,"abstract":"<p><strong>Introduction: </strong>Phenylketonuria (PKU) is an inherited metabolic disorder caused by biallelic variants in the <i>PAH</i> gene, leading to phenylalanine accumulation and progressive neuronal damage. Over 3,000 variants have been described worldwide; however, a previously unreported exon duplication was identified in Chile, whose genetic and functional characteristics remained unknown.</p><p><strong>Methods: </strong>A patient carrying a duplication of exon 2 in the <i>PAH</i> gene, previously detected by MLPA, was analyzed using nanopore sequencing coupled with CRISPR/Cas9 enrichment (nCATS) to determine the location, size, and orientation of the variant. Specific fragment amplification by PCR and Sanger sequencing was subsequently performed on samples from this patient and seven additional individuals to confirm the presence of the structural variant. Structural modelling of the resulting PAH protein was also conducted to predict functional consequences.</p><p><strong>Results: </strong>The nCATS technique identified a ∼18 kb tandem duplication between exons 1 and 3 of the <i>PAH</i> gene. This exon duplication was confirmed by PCR and Sanger sequencing in all eight patients. Additionally, an adenine insertion was detected at the junction site of the duplication. Structural modelling predicted an additional N-terminal segment that would likely interfere with sensing of phenylalanine.</p><p><strong>Discussion: </strong>The clinical, genetic and <i>in silico</i> functional characterization of this variant, using nCATS and structural modeling, suggests a mild, but relevant alteration in PAH enzymatic function. These findings support the delineation of genotype-phenotype correlations for complex structural variants, which may contribute to the development of personalized therapeutic strategies, while enriching both national and international PKU variant databases.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1669007"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483855/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212457","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":"Panoramic analysis of the biological function and clinical value of SLC38A2 in human cancers: a study based on pan-cancer and single-cell analysis.","authors":"Mao Liao, Yuqing Rao, Molan Li, Jiayang Guo, Kun Guo, Kaiyue Li, Rui Zheng, Yifan Liu, Qianyi Wang, Manni Wang, Duo Chen, Meng Zhang, Yongfeng Wang, Yanzong Zhao, Sheng Li","doi":"10.3389/fgene.2025.1658299","DOIUrl":"10.3389/fgene.2025.1658299","url":null,"abstract":"<p><strong>Background: </strong>Glutamine metabolic reprogramming is a hallmark of tumor progression and is highly correlated with poor clinical outcomes. The excessive uptake of glutamine by tumor cells is a key factor contributing to widespread invasion, metastasis, and immune suppression. SLC38A2, an amino acid transporter widely expressed on the surface of tumor cells, has not been thoroughly studied regarding its function and prognostic significance in tumor progression. Our objective is to employ bioinformatics methods to conduct a comprehensive and in-depth analysis of SLC38A2 across various cancers, aiming to elucidate its role and prognostic value in tumor biology.</p><p><strong>Methods: </strong>By comprehensively incorporating gene expression and clinical data from the TCGA tumor database, GTEx database, Human Protein Atlas, and GEO database, we analyzed the expression profile, mutations, and established prognostic models for SLC38A2 across various cancers. Additionally, we investigated the enrichment of SLC38A2 at the single-cell level in 12 types of cancer and analyzed its temporal expression patterns in different cell subgroups in breast and pancreatic cancer. We also studied the correlation between SLC38A2 and glutathione metabolism.</p><p><strong>Results: </strong>Compared to normal tissues, SLC38A2 exhibits significant differential expression in 15 types of cancer and serves as a prognostic risk factor in BRCA (HR = 1.597, <i>p</i> < 0.05), LUAD (HR = 1.650, <i>p</i> < 0.01), MESO (HR = 2.007, <i>p</i> < 0.05), and PAAD (HR = 1.761, <i>p</i> < 0.05), while acting as a protective factor in KIRC (HR = 0.625, <i>p</i> < 0.05). Furthermore, SLC38A2 is positively correlated with tumor and stromal cells, negatively correlated with immune cell infiltration, and associated with immune exhaustion. In BRCA, SLC38A2 is highly expressed during early differentiation of malignant and stromal cells, and enriched in late differentiation of immune cells. Moreover, the expression of SLC38A2 shows a general positive correlation with glutathione metabolism genes in BRCA, LUAD, MESO, and PAAD, demonstrating diagnostic value.</p><p><strong>Conclusion: </strong>SLC38A2 shows widespread changes in expression patterns within tumor tissues, making it an effective diagnostic and prognostic biomarker. It is enriched in malignant cells and tumor-infiltrating stromal cells, while negatively correlated with the infiltration of many cells involved in anti-tumor immunity. Targeting SLC38A2 presents a viable therapeutic strategy by inhibiting glutamine competition and relieving immune suppression in the tumor microenvironment.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1658299"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483874/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212449","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":"BioSemAF-BiLSTM: a protein sequence feature extraction framework based on semantic and evolutionary information.","authors":"Zihan Zhang, Yixuan Wang","doi":"10.3389/fgene.2025.1616880","DOIUrl":"10.3389/fgene.2025.1616880","url":null,"abstract":"<p><p>S-sulfenylation is a critical post-translational modification that plays an important role in regulating protein function, redox signaling, and maintaining cellular homeostasis. Accurate identification of S-sulfenylation sites is essential for understanding its biological significance and relevance to disease. However, the exclusive detection of S-sulfenylation sites through experimental methods remains challenging, as these approaches are often time-consuming and costly. Motivated by this issue, the present work proposed a deep learning-based computational framework, named BioSemAF-BiLSTM, which integrated evolutionary and semantic features to improve the prediction performance of S-sulfenylation sites. The framework employed fastText to generate subword-based sequence embeddings that captured local contextual information, and employed position-specific scoring matrices (PSSMs) to extract evolutionary conservation features. Importantly, we also quantitatively evaluated feature sufficiency at the protein sequence level using a sequence compression-based measure approximating Kolmogorov complexity, revealing an 11% information loss rate in predictive modeling using these features. These representations were subsequently fed into a bidirectional long short-term memory (BiLSTM) network to model long-range dependencies, and were further refined via an adaptive feature fusion module to enhance feature interaction. Experimental results on a benchmark dataset demonstrated that the model significantly outperformed conventional machine learning methods and current state-of-the-art deep learning approaches, achieving an accuracy of 89.32% on an independent test. It demonstrated improved sensitivity and specificity, effectively bridging the gap between bioinformatics and deep learning, and offered a robust computational tool for predicting post-translational modification sites.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1616880"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483914/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212470","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":"Uncovering compound heterozygous <i>DYSF</i> variants in a Chinese family affected by limb-girdle muscular dystrophy type 2B.","authors":"Jinlan Li, Jie Zhou, Chunbo Ji, Siqing Ma, Jianying Zhu, Tiejun Yang, Danyang Dong, Yang Ping","doi":"10.3389/fgene.2025.1664086","DOIUrl":"10.3389/fgene.2025.1664086","url":null,"abstract":"<p><p>This case concerns a Chinese female patient who was referred to our clinic having complained of weakness in her lower limbs. Following a series of diagnostic procedures, including electrophysiology, muscle biopsy and genetic analysis, the patient was diagnosed with limb-girdle muscular dystrophy type 2B (LGMD2B). Genetic testing revealed compound heterozygous mutations in the <i>DYSF</i> gene, specifically the missense mutation c.6313G>A (p.Ala2105Thr). Another variant, c.4444del (p.Glu1482Serfs*43), is a frameshift mutation. This case provides further confirmation of the LGMD2B diagnosis. It also identifies novel compound heterozygous <i>DYSF</i> mutations. These findings have significant implications for the diagnosis and research of genetic diseases, the management of at-risk individuals and the development of new therapies.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1664086"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483885/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212529","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":"Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.","authors":"Xiaoyuan Meng, Zhongcheng Han, Wuerkan Yeerken, Zhigang Wang, Le Ma, Hongbo Liu","doi":"10.3389/fgene.2025.1588581","DOIUrl":"10.3389/fgene.2025.1588581","url":null,"abstract":"<p><strong>Background: </strong>Long-term clinical outcomes for patients with osteosarcoma have shown little improvement over the past few decades. Identifying novel molecular targets to inhibit osteosarcoma cell growth remains an urgent challenge.</p><p><strong>Methods: </strong>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. The Network Analyst tool was used to analyze GSE73120. Differentially expressed genes (DEGs) were identified using GEO2R and analyzed using NetworkAnalyst. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using Metascape and WebGestalt. A protein-protein interaction (PPI) network was constructed through the STRING database and visualized with Cytoscape. The MCODE algorithm was used to identify key modules, and CytoHubba was applied to determine hub genes. Validation of hub genes was conducted using the GEPIA database.</p><p><strong>Results: </strong>A total of 104 DEGs were identified, including 89 upregulated and 15 downregulated genes. GO and KEGG analyses revealed that these DEGs were enriched in pathways related to connective tissue development, collagen trimer, and extracellular matrix structural components. The PPI network analysis identified seven hub genes. Among them, COL1A1, PDGFRB, and SPARC were confirmed as sarcoma-related genes using the GEPIA database.</p><p><strong>Conclusion: </strong>Our findings suggest that COL1A1, PDGFRB, and SPARC may be involved in mtRNA-driven tumorigenesis and could serve as promising therapeutic targets for osteosarcoma.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1588581"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212557","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":"Genomic prediction powered by multi-omics data.","authors":"Osval A Montesinos-López, Abelardo Montesinos-López, Brandon Alejandro Mosqueda-González, Iván Delgado-Enciso, Moises Chavira-Flores, José Crossa, Susanne Dreisigacker, Jin Sun, Rodomiro Ortiz","doi":"10.3389/fgene.2025.1636438","DOIUrl":"10.3389/fgene.2025.1636438","url":null,"abstract":"<p><p>Genomic selection (GS) has transformed plant breeding by enabling early and accurate prediction of complex traits. However, its predictive performance is often constrained by the limited information captured through genomic markers alone, especially for traits influenced by intricate biological pathways. To address this, the integration of complementary omics layers-such as transcriptomics and metabolomics-has emerged as a promising strategy to enhance prediction accuracy by providing a more comprehensive view of the molecular mechanisms underlying phenotypic variation. We used three datasets, each collected under a single-environment condition, which allowed us to isolate the effects of omics integration without the confounding influence of genotype-by-environment interaction. We assessed 24 integration strategies combining three omics layers: genomics, transcriptomics, and metabolomics. These strategies encompassed both early data fusion (concatenation) and model-based integration techniques capable of capturing non-additive, nonlinear, and hierarchical interactions across omics layers. The evaluation was conducted using three real-world datasets from maize and rice, which varied in population size, trait complexity, and omics dimensionality. Our results indicate that specific integration methods-particularly those leveraging model-based fusion-consistently improve predictive accuracy over genomic-only models, especially for complex traits. Conversely, several commonly used concatenation approaches did not yield consistent benefits and, in some cases, underperformed. These findings underscore the importance of selecting appropriate integration strategies and suggest that more sophisticated modeling frameworks are necessary to fully exploit the potential of multi-omics data. Overall, this work highlights both the value and limitations of multi-omics integration for genomic prediction and offers practical insights into the design of omics-informed selection strategies for accelerating genetic gain in plant breeding programs.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1636438"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212399","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":"The hidden in plain sight: global, regional, and national trends in the pediatric burden of Klinefelter syndrome, 1990-2021.","authors":"Guoqian Ma, Yuan Li, Fan Jia","doi":"10.3389/fgene.2025.1639699","DOIUrl":"10.3389/fgene.2025.1639699","url":null,"abstract":"<p><strong>Background: </strong>Klinefelter syndrome (KS) is the most common sex chromosome aneuploidy in males, but its epidemiology in children and adolescents remains poorly characterized worldwide. This study provides the first comprehensive global, regional, and national assessment of KS prevalence and disability-adjusted life years (DALYs) in individuals under 20 years from 1990 to 2021.</p><p><strong>Methods: </strong>We extracted data on KS prevalence and DALYs for individuals under 20 years of age from the Global Burden of Disease (GBD) 2021 database, covering 204 countries and territories. We evaluated temporal trends using the estimated annual percentage change (EAPC), stratified by age group, geographic region, and sociodemographic index (SDI) level.</p><p><strong>Findings: </strong>Between 1990 and 2021, the global number of KS cases in children and adolescents increased from 589,674 (95% UI, 440,342-770,284) to 690,885 (518,462-899,583), a 17.2% rise, while the overall prevalence rate per 100,000 remained stable (26.1 in 1990 to 26.2 in 2021). The global DALY burden attributed to KS rose by 20% over three decades, with marked disparities across SDI levels: in 2021, prevalence rates ranged from 17.1 per 100,000 (low-SDI) to 32.5 per 100,000 (high-SDI), and DALY rates varied from 0.05 to 0.15 per 100,000 across regions. High-SDI countries reported higher prevalence and DALY rates, likely reflecting superior diagnostic capacity and access to genetic services. In contrast, most low- and middle-SDI regions showed minimal changes in prevalence rates, despite increases in absolute case numbers, suggesting persistent underdiagnosis. Notably, children under 1 year of age and adolescents aged 15-19 represented the groups with the highest (49.5 per 100,000) and lowest (17.6 per 100,000) prevalence, respectively.</p><p><strong>Interpretation: </strong>KS continues to represent a largely undetected pediatric health burden, especially in low- and middle-SDI settings. The findings highlight the urgent need for enhanced awareness, early detection strategies, and equitable access to genetic services in global child health policy. Timely diagnosis and intervention can help prevent long-term developmental and health-related consequences of KS.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1639699"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206251","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 and validation of three tumor suppressors associated with the immune response of acute myeloid leukemia.","authors":"Yueyuan Pan, Guocai Wu, Chenchen Liu, Minggui Chen, Tian Xia, Yonghua Ma, Zhigang Yang, Ruiting Wen","doi":"10.3389/fgene.2025.1652142","DOIUrl":"10.3389/fgene.2025.1652142","url":null,"abstract":"<p><strong>Background: </strong>Acute myeloid leukemia (AML) is a heterogeneous disorder marked by irregular expansion and maturation, giving rise to the aggregation of immature myeloid precursor cells. Although most patients achieve remission with initial treatment, the majority of relapses lead to poorer overall survival. The bone marrow (BM) immune microenvironment has been proven to significantly affect the progression of AML. However, the mechanisms that cause the imbalance of immune cell subsets and phenotypes remain partially obscure. Therefore, this research sought to explore the immune-regulatory genes and to determine their role in AML.</p><p><strong>Methods: </strong>Differentially expressed genes (DEGs) were obtained through differential analysis of the AML cohort. Enrichment analyses were applied to explore their biological functions. Weighted Gene Co-expression Network Analysis (WGCNA) was performed to identify the key module of AML. ROC curve analysis was performed to identify hub genes with good predictive power. CIBERSORT and the ESTIMATE algorithm were used to assess the correlation between hub genes and the immune microenvironment of AML. The impact of hub gene expression on the prognosis of AML was verified through prognostic traits and clinical samples.</p><p><strong>Results: </strong>Through differential analysis and WGCNA, seven genes were identified as markedly related to the development of AML. By mapping ROC curves, three hub genes were verified: CCR7, SLC16A6, and MS4A1, which have high diagnostic value for AML. Additionally, an imbalanced immune microenvironment was found to be common in AML. Three hub genes were significantly associated with immune components, including immune cells and immunomodulatory factors. Ultimately, through the validation of clinical samples and the analysis of prognostic characteristics, three genes were confirmed to be reduced in AML patients, and their high expression suggested a favorable prognosis.</p><p><strong>Conclusion: </strong>Our study identified and validated the efficacy of SLC16A6, CCR7, and MS4A1 as tumor suppressors implicated in AML progression and related to immune cell infiltration.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1652142"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479338/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206269","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":"The potential clinical and public health implications of presymptomatic genetic testing for transthyretin amyloidosis in African American/Black adults in the United States.","authors":"Inderjeet Bharaj, Simar J Singh, Juzer Munaim, Harneet Grewal, Sonia Sabrowsky, Andrew Boshara, Marc A Silver, Katherine H Brendish, Paul Underwood, Sandesh Dev, Mayowa A Osundiji","doi":"10.3389/fgene.2025.1658636","DOIUrl":"10.3389/fgene.2025.1658636","url":null,"abstract":"","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"16 ","pages":"1658636"},"PeriodicalIF":2.8,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12476993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199120","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}