Human Genomics最新文献

{"title":"Outcomes of the national premarital genetic screening program for cystic fibrosis, homocystinuria, and spinal muscular atrophy in Qatar.","authors":"Sara Khalid AlMarzooqi, Reem Ibrahim Bux, Juby Ann Joy, Nazmul Islam, Tawfeg Ben-Omran, Ali Alawi Al-Hashimi, Moza Alkowari, Mashael Al-Shafai","doi":"10.1186/s40246-026-00937-8","DOIUrl":"10.1186/s40246-026-00937-8","url":null,"abstract":"<p><p>BACKGROUND: Premarital screening (PMS) programs have been increasingly implemented in various countries due to their potential to reduce the incidence of genetic conditions. In Qatar, a PMS program has been in place as a mandatory prerequisite for marriage since 2009 and its outcomes have not been explored. AIM: To assess the outcomes of the national premarital screening for cystic fibrosis (CF), Homocystinuria (HCU), and Spinal Muscular Atrophy (SMA) in Qatar and to provide insights and guide program’s improvements. METHODS: A retrospective population-based study on the PMS testing results for CF, HCU and SMA from 2009 to 2023. RESULTS: A total of 75,767 tests were initiated within this period with 99% of samples belonging to nationals. Testing for CF (47%) and HCU (48%) was similarly high compared to SMA which was significantly lower (5%), consistent with SMA’s optional screening status. The most common age at marriage was 20–30 years for females and 31–40 years for males. Carrier rates were highest for SMA (4.47%), followed by HCU (2.06%) and CF (1.46%). Among high-risk couples, 43.5% were positive for SMA, 30.5% for HCU, and 25.9% for CF. Consanguinity was reported in 46% of high-risk couples (where data was available) and was significantly associated with a higher likelihood of positive results (p < 0.001). More than half (53.6%) of high-risk couples continued with marriage. Among those, 85.2% had no affected children reported. Use of reproductive assistance with genetic testing was observed in 35.7% of positive couples, while 21.4% did not use it. Importantly, use of such technology was significantly associated with a reduced incidence of affected children (P = 0.024). CONCLUSION: Qatar’s PMS program was effective in reducing the incidence of the specified conditions. However, the absence of affected children among high-risk couples may be influenced by various factors. Therefore, while the results are encouraging, they should be interpreted with caution. Our findings highlight the need for enhanced risk counseling after positive results, and the need for public educational campaigns on the importance of premarital testing, the potential risks associated with consanguinity and the availability of reproductive technologies that may be utilized as a preventative option. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13040869/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147305323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response to Letter to the Editor.","authors":"Hiba Alblooshi, Najla Aljaberi","doi":"10.1186/s40246-025-00866-y","DOIUrl":"10.1186/s40246-025-00866-y","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"20 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12933965/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147283509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing prostate cancer diagnosis: a machine learning-based biomarker approach.","authors":"Patricia Porras-Quesada, Alberto Ramírez-Mena, Verónica Arenas-Rodríguez, Fernando Vázquez-Alonso, Jesús Alcalá-Fdez, Beatriz Álvarez-González, Luis Javier Martínez-González, María Jesús Álvarez-Cubero","doi":"10.1186/s40246-026-00939-6","DOIUrl":"10.1186/s40246-026-00939-6","url":null,"abstract":"<p><p>BACKGROUND: The lack of reliable screening biomarkers for prostate cancer (PC) diagnosis makes tissue biopsy the gold-standard strategy. However, its frequent inconclusive results often lead to repeated procedures, increasing patient burden and healthcare costs. In this context, machine learning (ML) presents a novel approach for identifying gene signatures associated with tumor presence, offering a promising avenue for improved PC detection. Therefore, the present study explored the diagnostic potential of an ML-based gene signature and its applicability in tissue and plasma samples. METHODS: This study evaluated the clinical applicability of an ML-based algorithm developed using TCGA data (n = 608) and tested in an independent dataset (n = 349). The eleven candidate genes that contributed most to the predictive model were initially profiled by targeted RNA-Seq in prostate tissue validation cohort (n = 141) and further validated in replication tissue (n = 75) and plasma (n = 50) cohorts by qPCR and dPCR, respectively. RESULTS: Gene expression analysis in prostate tissue led to the identification of a six-gene signature (DLX1, TDRD1, AMACR, HPN, HOXC6, and OR51E2) with high diagnostic performance (AUC = 95.9%). Expression patterns supported the gene signature’s potential to identify false-negative cases and correctly classify inconclusive biopsy results. In plasma, AMACR demonstrated added diagnostic value as a non-invasive biomarker when integrated with clinical parameters (AUC = 93.21%). CONCLUSIONS: These findings demonstrate that our ML-based gene signature can accurately distinguish PC from non-tumoral tissue and resolve ambiguous biopsy results. Its integration alongside histopathology has the potential to reduce diagnostic uncertainty, improving PC early detection and guiding clinical decision-making. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13040917/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147283467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Therapeutic rewiring of ceRNA networks: a computational pipeline for drug repurposing in acute kidney injury via circRNA-miRNA-mRNA axis disruption.","authors":"Ming Wang, Feng Gao","doi":"10.1186/s40246-026-00930-1","DOIUrl":"10.1186/s40246-026-00930-1","url":null,"abstract":"<p><p>This review synthesizes current evidence on competing endogenous RNA (ceRNA) regulation in acute kidney injury (AKI) and proposes a practical, reproducible framework for computationally guided drug repurposing that aims to rewire pathogenic circRNA–miRNA–mRNA axes. We summarize the ceRNA concept and its biological rationale in renal injury, anchored to foundational descriptions of the ceRNA hypothesis. Building on curated circRNA resources and drug–gene mapping platforms, we present and critically evaluate a five-stage computational framework: (1) multi-omics data mining and ceRNA triplet inference, (2) network pharmacology mapping to drug–gene resources, (3) RNA-aware molecular docking to candidate structured RNA motifs, (4) molecular dynamics (MD) refinement and rescoring, and (5) integrative prioritization with explicit experimental filters for renal safety and tractability. We synthesize methodological best practices and limitations for each stage, with particular attention to the emerging field of RNA-targeted small molecules and their experimental validation. Three illustrative case studies demonstrate how distinct repurposing logics (direct RNA engagement, network/miRNA modulation, pathway-level modulation) can be mapped onto this pipeline and what orthogonal assays are required to progress candidates from in silico nomination to biochemical and in vivo testing. The review concludes with a pragmatic experimental roadmap, clear caveats (RNA structural dynamics, cellular context dependency, miRNA redundancy), and proposals to integrate single-cell and systems-pharmacology approaches to improve replicability and translational potential. By collating the literature and proposing a transparent, stepwise framework with validation benchmarks, this review aims to generate testable, prioritized in-silico hypotheses for RNA-aware repurposing in AKI that require rigorous biochemical and preclinical validation before any consideration of clinical testing. Because AKI arises from multiple, biologically distinct etiologies (for example ischemia–reperfusion injury, sepsis, nephrotoxic injury such as cisplatin exposure, and obstructive causes), candidate drugs and circRNA/miRNA targets must be evaluated in etiology-matched cellular and animal models; the pipeline therefore explicitly recommends etiology-aware filtering and model selection to avoid overgeneralizing findings across all AKI types.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13041499/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147283462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rare variant analyses provide insights into the genetic architecture of endometriosis.","authors":"Yuanyuan Gui, Yuhan Xie, Xiaomei Tong, Hongyu Zhao","doi":"10.1186/s40246-026-00934-x","DOIUrl":"10.1186/s40246-026-00934-x","url":null,"abstract":"<p><p>BACKGROUND: Endometriosis (EMs) is a prevalent gynecologic disorder that often causes severe chronic pelvic pain and infertility. Although genome-wide association studies have identified common variants of EMs, the contribution of rare variants remains unclear. RESULTS: We conducted an exome-wide analysis in 87,100 unrelated female participants of European ancestry from the UK Biobank. Single variant association tests for rare variants and gene-based analyses were performed, with replication in the FinnGen and Biobank Japan cohorts. No single rare variants achieved genome-wide significance ([Formula: see text]). While gene-based analyses identified SOGA1 significantly associated with EMs at the Bonferroni-corrected threshold of [Formula: see text], which was replicated in both external cohorts. Functional analyses indicated involvement of implicated genes and interaction networks in regulating gluconeogenesis, muscle filament sliding, and autophagosome. We also observed expression differences of SOGA1 across various cell types and found significant cell type-specific enrichments for EMs. CONCLUSIONS: This study establishes the contribution of rare genetic variants to endometriosis pathogenesis through the discovery of a novel susceptibility gene, advancing the genetic understanding of this disease. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13001359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147283470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of miRNA biomarkers and development of predictive signatures for early detection and prognosis in cervical precancer and cancer.","authors":"Ebuka Onyenobi, Michael Zhong, Josephine Peitz, Kiranpreet Chawla, Amy Plotkin, Clement Adebamowo, Sally N Adebamowo","doi":"10.1186/s40246-026-00924-z","DOIUrl":"10.1186/s40246-026-00924-z","url":null,"abstract":"<p><p>BACKGROUND: Aberrant microRNA expression has been implicated in cervical carcinogenesis, making miRNAs promising biomarkers for early detection and risk stratification of cervical precancer and cancer. This study aimed to identify and validate miRNA expression profiles and signatures that distinguish benign, precancer, and cancer cervical tissues, providing insights into their potential utility in cervical cancer screening and diagnosis. METHODS: We analyzed miRNA expression from archival FFPE cervical tissues of 272 women (100 benign, 89 precancer, 83 invasive cancer) using next-generation sequencing. Differential expression was assessed using DESeq2 with significant miRNAs defined by an absolute log2 fold change ≥ 1 and an adjusted p-value < 0.05. Functional enrichment of miRNA targets was performed using multiMiR and DAVID, and protein-protein interaction (PPI) networks were constructed using STRING and Cytoscape. Machine learning classifiers were developed with recursive feature elimination (RFE) and XGBoost and evaluated in internal and external cohorts. miRNA signatures were further assessed for association with overall survival in the TCGA cervical cancer cohort using multivariable Cox regression models. RESULTS: Notably, hsa-miR-1246 was the most significant miRNA in cancer vs. benign (log₂FC = 5.58, p = 3.20 × 10⁻41) and cancer vs. precancer (log₂FC = 4.89, p = 5.23 × 10⁻33). hsa-miR-149-5p was most significant in benign vs. precancer (log₂FC = −1.48, p = 1.53 × 10⁻¹⁴). Enrichment analyses highlighted cancer-related pathways with hub genes including TP53, BCL2, STAT3, ESR1, and MYC. RFE with XGBoost identified a 26-miRNA panel for multiclass classification and a 4-miRNA panel for binary cancer vs. benign classification. The binary model achieved strong performance with an AUC of 0.97 and 0.91 in internal and external validation sets respectively. Both the 26-miRNA (p < 0.001) and 4-miRNA (p = 0.01) signatures were associated with poorer overall survival. CONCLUSION: Our findings identify distinct miRNAs and miRNA-based signatures that differentiate benign, precancer, and cancer cervical tissues, highlighting their potential clinical utility as diagnostic and prognostic biomarkers. Furthermore, the development of compact, biologically interpretable miRNA signatures demonstrates strong promise as robust classifiers for early cancer detection and tissue characterization, with possible therapeutic relevance. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13032331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146776254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genotype-phenotype correlations in phenylketonuria: PAH variants and BH4 responsiveness for treatment design.","authors":"Meryem Karaca, Asuman Gedikbasi, Arzu Selamioğlu, Alihan Yesil, Guven Toksoy, Cagri Gulec, Mehmet Cihan Balci, Dilek Güneş, Behiye Tuğçe Yıldırım, Gizem Kına, Volkan Karaman, Ayca Dilruba Aslanger, Birsen Karaman, Mubeccel Demirkol, Zehra Oya Uyguner, Gulden Fatma Gokcay","doi":"10.1186/s40246-026-00936-9","DOIUrl":"10.1186/s40246-026-00936-9","url":null,"abstract":"<p><p>BACKGROUND: Phenylketonuria (PKU) is an autosomal recessive disorder caused by PAH alterations, leading to elevated phenylalanine (Phe) and neurotoxicity. Newborn screening (NBS) and early therapy improve outcomes. This study aimed to characterize the molecular and phenotypic spectrum of PKU, explore genotype–phenotype correlations, and evaluate the relationship between PAH variants and BH4 responsiveness to guide personalized treatment. METHODS: Medical and genetic records of 171 patients diagnosed with hyperphenylalaninemia via NBS were reviewed. Demographic data, diagnostic Phe and tyrosine (Tyr) levels, BH4 loading test results, and genetic analyses including Sanger sequencing, MLPA, and array CGH were assessed. Allelic and genotype–phenotype values were used to estimate variant severity. RESULTS: 168 carried ≥ 1 PAH variant; three had BH4 metabolism disorders. A total of 63 distinct PAH variants were identified; MLPA detected large deletions in three patients. Five variants (c.1066-11G > A, c.782G > A, c.143T > C, c.898G > T, c.1208 C > T) accounted for > 50% of the cohort. Among 100 patients tested, 41% responded to BH4, with c.782G > A most common (21%). Overall, 68.5% received dietary and/or BH4 therapy. CONCLUSION: This study contributes to our understanding of PKU’s molecular and phenotypic landscape, highlighting the importance of utilising both genotype and response to the BH4 loading test in the design of personalised treatments, beyond the initial Phe level. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13081264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146776277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing the diagnostic gap through deep phenotyping.","authors":"John Guozhuang Li, Kexin Xu, Bin Xiao, Jingnan Li, Yi-Cheng Zhu, Hongzhong Jin, Qingwei Qi, Lianlei Wang, Lina Zhao, Zhihong Wu, Sen Zhao, Terry Jianguo Zhang, Nan Wu","doi":"10.1186/s40246-026-00925-y","DOIUrl":"10.1186/s40246-026-00925-y","url":null,"abstract":"<p><p>BACKGROUND: Rare diseases remain a substantial challenge for healthcare systems worldwide, and 80% are attributable to genetic factors. Although exome sequencing (ES) and genome sequencing (GS) have become routine and widely accessible in our current clinical practice due to reduced costs and policy support, progress in systematically capturing deep and structured phenotypic data has lagged behind, limiting diagnostic accuracy. Integrating deep phenotyping with genomic analysis may help close the diagnostic gap. However, its value has not been comprehensively assessed in clinical practice, particularly in the absence of a systematic medical geneticist program in our current clinical settings. METHODS: We accessed and reviewed the clinical and sequencing data of patients with a rare or suspected genetic disorder assessed at our center between 2022 and 2024. Through detailed case vignettes, we evaluated how granular bedside data influenced the diagnostic outcomes. Expert consensus and literature review were then used to construct a continually updated Recommended Phenotypes Panel and to build a nine-domain framework termed iDREAMS (integrating Deep phenotyping with genetic analysis for Rare disease Evaluation And Management Strategies). RESULTS: Deep phenotyping uncovered diagnostic clues missed by standard assessments across all nine domains, guiding genome analysis, shortening the diagnostic odyssey, and refining counselling in numerous cases. The panel streamlined data capture for clinicians, improved multidisciplinary case discussions, and fed directly into the iDREAMS framework, offering a reproducible pathway from phenotype to genotype. CONCLUSIONS: Systematic deep phenotyping is pivotal for closing the “sequencing-analysis” gap in rare disease diagnostics. The iDREAMS framework provides a practical, scalable model that enhances diagnostic accuracy, lowers the entry barrier for resource-limited settings, and extends the reach of precision medicine to patients who had long remained undiagnosed.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13019781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146226572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative genomics establishes GNL3 as a pleiotropic hub and causal gene for osteoarthritis.","authors":"Tianhao Qu, Yan Zhong, Yonghuan Zhou, Lin Liu, Zheng Ye","doi":"10.1186/s40246-026-00920-3","DOIUrl":"10.1186/s40246-026-00920-3","url":null,"abstract":"<p><p>BACKGROUND: Osteoarthritis (OA) is a leading cause of disability, yet there are no approved disease-modifying therapies (DMOADs) capable of halting its progression. While genome-wide association studies (GWAS) have robustly linked the 3q21 locus to OA, the causal effector gene and its underlying mechanism have remained elusive, hindering translational progress. METHODS: We implemented a multi-tiered, systematic integrative genomics strategy to proceed from genetic association to causal mechanism. By integrating summary statistics from large-scale OA GWAS with multi-tissue molecular quantitative trait loci (QTL) and single-cell expression QTL (sc-eQTL) data, we employed a combination of Bayesian colocalization and Mendelian randomization (MR) to establish a robust chain of causal evidence. RESULTS: Our analysis identifies GNL3 as the causal effector gene at the 3q21 locus. MR analysis formally demonstrated that genetically predicted higher GNL3 expression is causally protective against both knee and hip OA (e.g., Knee OA: Odds Ratio = 0.85, p = 4.4e-4). Further single-cell causal inference pinpointed this protective effect to specific cellular contexts, most prominently in activated T-cells, neural cells under cellular stress, and developmental progenitors. Moreover, we establish this locus as a pleiotropic hub, showing that its causal variants are shared with systemic OA risk factors, including Body Mass Index (BMI) and vitamin D levels. CONCLUSION: This study establishes, for the first time, a coherent chain of evidence from a shared genetic signal to the regulation of GNL3 expression in specific cell types and, ultimately, to a causal impact on OA risk. Our findings converge on a novel mechanistic model: GNL3 acts as a master regulator of systemic homeostasis, where its genetically determined expression level modulates immune and neural cell responses to stress, thereby dictating an individual’s susceptibility to OA. This work validates GNL3 as a high-confidence therapeutic target and provides a new framework for developing DMOADs aimed at reinforcing systemic homeostatic pathways. </p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13014845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146206970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From enrichment to interpretation: PS4-driven reclassification in Taiwanese inherited retinal degeneration.","authors":"Yu-Shu Huang, Chien-Yu Lin, Yu-An Chen, Chieh-Yu Lee, Chang-Hao Yang, Jacob Shujui Hsu, Ta-Ching Chen, Pei-Lung Chen","doi":"10.1186/s40246-026-00923-0","DOIUrl":"10.1186/s40246-026-00923-0","url":null,"abstract":"<p><strong>Background: </strong>Inherited retinal degeneration (IRD) comprises a diverse group of monogenic disorders characterized by marked genetic and phenotypic heterogeneity. Although next-generation sequencing (NGS) enables the identification of candidate variants, many remain classified as variants of uncertain significance (VUS). Ancestry-matched population data can strengthen comparative evidence, and the emergence of national biobanks provides new opportunities to operationalize ACMG/AMP criterion PS4 through case-control analyses.</p><p><strong>Methods: </strong>We integrated an IRD cohort of 802 probands with whole-genome allele frequency data from 1,492 individuals in the Taiwan Biobank. An allele-based case-control framework was applied, assigning PS4 when the Haldane-Anscombe-corrected odds ratio was ≥ 5 and the 95% confidence interval excluded 1. Post-PS4 triage required variants to: (i) reside in IRD-associated genes, (ii) be rare in East Asian populations in gnomAD v4.1, and (iii) be annotated in RefSeq as exonic, untranslated regions, or splicing (± 20 bp). Baseline ACMG/AMP classifications were generated using GeneBe and finalized through expert curation.</p><p><strong>Results: </strong>Incorporation of PS4 substantially refined variant interpretation, upgrading two variants from Likely Pathogenic to Pathogenic and six from VUS to Likely Pathogenic. Homozygous exemplar variants, including CNGB1 (NM_001297.5): c.2921T > G and CFAP410 (NM_004928.3): c.340_351dup, demonstrated strong genotype-phenotype concordance with confirmatory sequencing, illustrating an end-to-end workflow from statistical enrichment to clinical reporting.</p><p><strong>Conclusion: </strong>An ancestry-aware case-control framework enables effective implementation of PS4 and improves the accuracy of IRD variant classification. This reproducible strategy supports the integration of population-specific genomic data into clinical workflows and is applicable to other monogenic disorders.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13011756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146201472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}