BackgroundImmune checkpoint inhibitors (ICIs) have transformed cutaneous melanoma therapy, yet 50% of patients show primary or acquired resistance, and current biomarkers (PD-L1 and tumor mutational burden) lack precision. High-frequency ultrasound (HFUS), contrast-enhanced ultrasound (CEUS), and shear-wave elastography (SWE) are inexpensive and repeatable, but their relationship to the immune transcriptome and ICI outcomes is unknown.MethodsIn this single-center retrospective study, 218 patients with cutaneous melanoma who received first-line anti-PD-1-based ICIs and pretreatment ultrasound were divided into training (n = 153) and internal validation (n = 65) sets. HFUS/CEUS/SWE radiomic features were filtered for reproducibility and selected by LASSO to construct an ultrasound radiomic score (US-score). Across three public transcriptomic cohorts (TCGA-SKCM, GSE91061, and GSE78220) and a melanoma single-cell dataset (GSE115978), we combined differential expression, WGCNA, immune deconvolution, and LASSO-Cox to derive an IRGS. Four core genes (CXCL10, CD8A, IFNG, and CXCL9) were validated in vitro by RT-PCR in three ATCC melanoma cell lines after IFN-γ stimulation.ResultsThe objective response rate was 42.7% (median follow-up 28.4 months). The US-score independently predicted response (adjusted OR: 2.6; 95% CI: 1.7–3.9; validation AUC: 0.78). The IRGS stratified public cohorts into immune-hot/cold groups with distinct outcomes (TCGA-SKCM overall-survival HR: 2.14; 95% CI: 1.56–2.93; response AUC: 0.79). The US-score correlated with the IRGS (r = 0.58) and with CD8+ T-cell density on multiplex immunohistochemistry (r = 0.62). The combined nomogram outperformed any single biomarker (validation AUC: 0.88 vs. 0.78 [US], 0.76 [IRGS], and 0.68 [clinical]) with good calibration and net benefit and separated progression-free survival (median: 18.6 vs. 6.3 months; HR: 3.12, 95% CI: 2.08–4.68). In vitro, all four genes were significantly induced by IFN-γ (CXCL10 up to 8.3-fold; all p < 0.05).ConclusionUltrasound radiomics encodes information about the melanoma tumor-immune microenvironment; combined with an immune-related gene signature, it provides a non-invasive, biologically anchored tool for stratifying ICI response and resistance.
BackgroundSpinal muscular atrophy (SMA) and tuberous sclerosis complex (TSC) are both rare genetic disorders, and their co-occurrence is expected to be exceptionally uncommon. Although risdiplam has demonstrated efficacy in SMA, evidence regarding its use in preterm infants with complex genetic comorbidities remains limited.ResultsWe report preterm monozygotic twins born at 32+5 weeks of gestation with genetically confirmed SMA caused by homozygous deletion of SMN1 exons 7–8, with two copies of SMN2. During baseline evaluation prior to presymptomatic treatment, brain magnetic resonance imaging revealed incidental abnormalities, including cortical dysplasia and subependymal nodules, which prompted further genetic testing and led to the diagnosis of TSC with a TSC1 c.1041G>A variant. Presymptomatic risdiplam was initiated at a corrected gestational age of 38+5 weeks. Both twins showed marked improvement in motor function. By 12 months of age, they had achieved independent rolling, unsupported sitting, crawling, and pulling to stand, accompanied by substantial improvements in CHOP INTEND and HINE-2 scores. Risdiplam was well tolerated, and no commonly reported adverse events were observed during follow-up.ConclusionThis report describes the first documented co-occurrence of SMA and TSC in preterm monozygotic twins and suggests that presymptomatic risdiplam may be effective and well tolerated in this complex clinical setting over 1 year of follow-up. These findings also highlight the importance of comprehensive genetic evaluation in infants with SMA who present with atypical neuroimaging or neurological features. Longer-term follow-up is needed to clarify safety, efficacy, and optimal integrated management strategies in patients with complex genetic comorbidities.
BackgroundInflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) often present with overlapping gastrointestinal symptoms despite distinct pathophysiological mechanisms. Colonoscopy remains the diagnostic gold standard but is invasive, costly and frequently overutilized. Single biomarkers have limited diagnostic value because they do not fully reflect the complex metabolic and inflammatory alterations underlying intestinal diseases. We aimed to develop and validate an interpretable machine learning-based scoring system integrating multidimensional metabolism-related biomarkers for invasive examination triage.MethodsThis retrospective single-center study included 729 participants (313 healthy controls, 210 IBS, 100 ulcerative colitis and 106 Crohn’s disease patients) enrolled between July 2021 and November 2025. Demographic, clinical, and metabolism-related laboratory biomarkers reflecting inflammatory metabolism, nutritional metabolism, hepatic metabolic function, and renal metabolic homeostasis were collected. Correlation network analysis, least absolute shrinkage and selection operator (LASSO) regression, extreme gradient boosting (XGBoost), and a simplified nomogram-based scoring system were applied to differentiate IBD from non-IBD conditions.ResultsSignificant differences were observed across all clinical and metabolism-related variables (P < 0.001). IBD patients exhibited elevated inflammatory-metabolic-related biomarkers and dense inflammation-driven metabolic correlation networks, whereas IBS patients showed metabolic profiles similar to healthy controls. XGBoost achieved the best diagnostic performance (AUC = 0.992), followed by LASSO (AUC = 0.978). A simplified scoring system incorporating sex, age, log-transformed fecal calprotectin (LogFC), log-transformed C-reactive protein (LogCRP), hemoglobin (HB), albumin (ALB), white blood cell count (WBC) and platelet count (PLT) achieved an AUC of 0.910, outperforming fecal calprotectin (FC) alone (AUC = 0.844) and the FC-CRP combination (AUC = 0.855). The scoring system demonstrated substantial clinical net benefit and correlated with colonoscopic inflammation severity (AUC = 0.761). Inflammatory and metabolism-related biomarkers were the strongest predictors of IBD.ConclusionIBD is characterized by distinct multidimensional metabolism-related biomarker signatures. The proposed machine learning-based scoring system integrates these metabolism-related biomarkers into a reliable, non-invasive tool for invasive examination triage, potentially reducing unnecessary colonoscopies and improving clinical resource utilization.
Clarifying gene regulatory networks (GRNs) remains one of the central challenges of systems biology and is crucial for elucidating pathogenesis and curing diseases. Various machine learning techniques have been developed for gene regulatory network inference, but identifying intricate interactions is still a fundamental problem. Here, we propose a network structure refinement scheme, termed HSTXGB (a hyperparameter self-tuning XGBoost method integrating pre- and post-processing), to infer GRNs from time-course expression data by leveraging the nonlinear modeling capability of XGBoost while integrating prior knowledge (e.g., knockout data) and posterior statistics (e.g., regulation probabilities). Specifically, HSTXGB first calculates regulation relationship confidences using a self-tuning XGBoost model, which accounts for temporal dependencies in gene expression. Then, two novel strategies are designed to integrate information from prior data and to incorporate statistical information, which correspond to fluctuations in knockout experiments and to regulatory frequency and intensity, respectively. The confirmatory experiments on the benchmark datasets from the DREAM challenge as well as the E. coli datasets (8 networks in total) demonstrated that our HSTXGB scheme achieves significantly better performance compared with eight other state-of-the-art methods.
BackgroundThird-generation epidermal growth factor receptor tyrosine kinase inhibitor osimertinib serves as the gold standard therapy for treating NSCLC patients harboring EGFR T790M mutations. The clinical utility of this agent, however, faces considerable constraints due to the unavoidable emergence of acquired resistance mechanisms. Understanding the molecular basis of osimertinib resistance holds paramount importance for determining optimal follow-up treatment approaches.MethodsClinical information from 86 lung adenocarcinoma patients carrying EGFR T790M mutations who showed disease advancement following osimertinib therapy was examined retrospectively, spanning the period from January 2018 through December 2023. Genomic characterization was conducted via next-generation sequencing on tissue or liquid biopsy specimens collected after resistance developed. Protein expression alterations were assessed through immunohistochemical staining, while critical resistance pathways underwent validation using cell line models.ResultsAmong the 86-patient cohort, the median duration before disease progression reached 14.2 months. Genomic characterization identified these predominant resistance pathways: C797S mutations in EGFR (23.3%), amplification of MET (15.1%), amplification of HER2 (8.1%), mutations in PIK3CA (7.0%), transformation to small cell lung cancer (9.3%), and epithelial-mesenchymal transition (12.8%). Concurrent presence of multiple resistance mechanisms was detected in 24.4% of the patient population. Within the C797S mutation subset, 65.0% exhibited C797S/T790M in cis arrangement, 30.0% demonstrated trans arrangement, and 5.0% showed mixed configurations. Laboratory validation established that MET amplification confers resistance via bypass activation of both ERK and AKT signaling cascades. The poorest clinical outcomes were observed among patients undergoing histological transformation (median overall survival from confirmed progression: 8.3 months).ConclusionRemarkable heterogeneity characterizes the resistance mechanisms emerging against osimertinib in EGFR T790M-positive lung adenocarcinoma, with EGFR secondary mutations, bypass signaling pathway activation, and histological transformation representing the primary categories. Detection of specific resistance mechanisms enables tailored subsequent therapeutic approaches, with potential outcome improvements achievable through combination strategies incorporating targeted agents or immunotherapy.
Sound scientific sample diversity will require attention to cultivating trust among populations underrepresented as biobank participants. While no particular group is the focus of this report, the observations presented may be particularly helpful for cultivating trust necessary for enrollment of underrepresented populations. Community engagement strategies indicate that such trust is built through relationships extending across the spectrum of biomedicine rather than focused exclusively on a particular research project. Central to these relationships are communication behaviors reflected in both research and clinical encounters. This ‘brief research report’ presents preliminary clinical research findings from a pilot analysis of return of genetic results conversations relevant to the cultivation of trust.
IntroductionAnterior cruciate ligament (ACL) rupture is a common orthopaedic disease in dogs, with varying prevalence and genetic susceptibility across different breeds. Here we investigate the association between genomic structural variation (SV) and ACL rupture risk in the Labrador Retriever and Rottweiler breeds.MethodsWe used 1,058 Labrador Retrievers (464 cases, 594 controls) and 108 Rottweilers (83 cases, 25 controls). Using breed‐specific de novo genome assemblies, we first characterized SV between Labrador Retriever and Rottweiler genomes to provide genomic context for breed-level differences. We then quantified runs of homozygosity (ROH) and evaluated the association between homozygosity measures (nROH, AVGROH, and FROH) and ACL rupture risk using breed‐specific and combined‐breed logistic regression models.ResultsThe association between homozygosity parameters and ACL rupture in the Labrador Retriever was not significant (P > 0.05 for all models). In contrast, inbreeding coefficient (FROH) was significantly associated with increased ACL rupture risk (OR = 2.011, 95% CI:1.120‐3.98, P‐value = 0.026) in the Rottweiler when sex and interaction effects were included in the model.ConclusionThese findings suggest a potential association between inbreeding and ACL rupture risk in Rottweilers. In addition, joint analysis of Labrador Retriever and Rottweiler data revealed multicollinearity between breed and homozygosity content, which highlights the heterogeneity of genetic risk factors across breeds. Our findings suggest that breed‐specific genetic models are crucial for understanding the genetic contribution to ACL rupture and for developing accurate genetic risk prediction tools. Given the relatively small and imbalanced Rottweiler dataset, independent validation in larger populations is warranted to further explore the potential breed‐specific genetic loci contributing to ACL rupture in the Rottweiler.
BackgroundDuchenne muscular dystrophy (DMD) is an X-linked recessive disorder caused by mutations in the DMD gene. Understanding the carrier frequency and mutation spectrum in specific populations is critical for genetic counseling and early intervention. However, data on DMD carrier frequency among women of childbearing age and early pregnancy in Yueyang City, China, remain limited. This study aimed to characterize the carrier rate and mutation profile to support preventive strategies and reduce disease incidence.MethodsA total of 25,611 women of childbearing age or early pregnancy from Yueyang City were enrolled. Combined next-generation sequencing and multiplex ligation-dependent probe amplification were used to detect pathogenic/likely pathogenic (P/LP) variants, copy number variants (CNVs), and small indels. Variants were classified per established guidelines. Carrier rates and geographical distribution were analyzed. Prenatal diagnosis was offered to identified carriers with follow-up to assess outcomes.ResultsTwenty-eight women were identified as P/LP carriers (0.11%), representing 25 distinct variants. CNVs constituted the majority (71.43%), with exon 45–55 deletions (64.29%) predominating over duplications (7.14%); notably, 13/18 CNVs clustered in this hotspot. SNVs and small indels accounted for the remaining 28.57%. Intra-regional variation was marked, with the highest rate in Yunxi District (0.74%). Additionally, 81 VUSs (51 distinct types) were detected, 66.67% being missense. One male fetus inheriting a maternal VUS developed DMD-like features postpartum. Overall, 12 variants (1 LP, 11 VUSs) were previously unreported, including a nonsense variant c.3502G>T (p.E1168*) classified as LP.ConclusionThis first population-based study in Yueyang City, China, characterized the DMD carrier frequency (0.11%) and mutation spectrum among women of childbearing age or in early pregnancy. It revealed geographical heterogeneity and a high prevalence of CNVs, especially exon 45–55 deletions. Crucially, it highlights the underappreciated screening value of VUS. We recommend focused attention on VUS, particularly those with Bayesian scores ≥3, in genetic counseling and prenatal diagnosis to improve preventive strategies and reduce DMD incidence.
Thyroid cancer is the most common type of endocrine malignancy, and its aggressive types are diagnosed at advanced stage due to limited treatment options. This study aimed to identify upregulated SLC7A5 across thyroid cancer cell types using an integrated transcriptomics approach. Total RNA was extracted from different samples. Differential expression analysis was performed through DESeq2. Functional enrichment analyses were performed to explore key pathways. The PPI network was built using the STRING database to investigate the functional relationships among significantly differentially expressed genes. Differential expression analysis revealed that SLC7A5 was significantly upregulated in KTC-1. GO and KEGG analyses were enriched with cell adhesion, protein binding, extracellular exosome, RNA processing, ECM-receptor interactions, and focal adhesion. The PPI network analysis showed the interaction of SLC7A5 with TERF1, CARD10, PSAT1, SIRPA, and MYC. Western blot analysis revealed that expression of mTOR was not elevated in KTC-1. Overall, these results could provide valuable insights for further validation in thyroid cancer therapy.
Glycogen storage disease type VII (GSD-VII), or Tarui disease, is a rare autosomal recessive disorder caused by biallelic loss-of-function variants in the PFKM gene encoding the muscle isoform of phosphofructokinase (PFK), a key enzyme of the glycolytic pathway. PFK deficiency impairs glycogen and glucose metabolism in skeletal muscle and erythrocytes, causing exercise intolerance, exertional myalgia, and myoglobinuria, and, in some cases, fixed proximal muscle weakness, as well as haemolytic anaemia. We report the case of an Italian woman with genetically confirmed GSD-VII harbouring a homozygous missense variant in PFKM (NM_000289.6:c.550C>T, p.Arg184Trp). This variant was previously identified in Wachtelhund dogs, a spontaneous animal model of PFK deficiency, but never reported in patients so far. PFK activity in skeletal muscle (PFKM) was found severely decreased and ultrastructural analysis revealed glycogen accumulation and mitochondrial alteration, supporting the pathogenetic role of the identified variant.
BackgroundHypoxia-driven vascular, immune, and metabolic remodeling is a key biological process involved in cardiovascular diseases, cancer, and other complex systemic disorders. Acute mountain sickness (AMS) is an acute manifestation of hypobaric hypoxia, but its systemic molecular features remain incompletely defined.MethodsWe performed integrated plasma proteomic and metabolomic profiling in 81 healthy Han Chinese male participants after rapid high-altitude exposure. Differential analysis, weighted gene co-expression network analysis (WGCNA), tissue-specific protein mapping, regulatory network reconstruction, machine learning, and druggability assessment were applied to characterize AMS-associated molecular alterations and identify candidate biomarkers and targets.ResultsMulti-omics profiling identified 3,137 proteins and 4,104 metabolites and showed clear separation between AMS and non-AMS participants. AMS was characterized by coordinated thrombo-inflammatory activation, coagulation-related disturbance, and metabolic reprogramming, including suppression of oxidative phosphorylation-related signatures. WGCNA identified symptom associated proteomic and metabolomic modules linked to headache severity, oxygen saturation, and hemodynamic traits. Tissue-specific protein mapping revealed a liver-centered but multi-organ circulating proteomic architecture, suggesting hepatic secretory remodeling with additional neural and immune-system contributions. Regulatory network analysis highlighted NOTCH1 as a candidate upstream regulatory hub, whereas druggability analysis prioritized NOTCH1 and the antioxidant-related protein GSTA1 as translational candidates. An mRMR plus logistic regression classifier integrating 15 proteomic features and SpO2 achieved good discriminatory performance, with an AUC of 0.968 in the training cohort and 0.913 in the test cohort.ConclusionThis study defines a multi-layer molecular framework of human acute hypoxic stress, linking vascular regulation, inflammation, coagulation, metabolic remodeling, tissue origin, and biomarker prioritization. These findings provide mechanistic insight into AMS and support multi-omics-based biomarker discovery and target prioritization in hypoxia-associated systemic diseases.
BackgroundFrequent intravitreal administration of antivascular endothelial growth factor Vascular endothelial growth factor agents remains a major limitation in the management of wet age-related macular degeneration (wAMD). This study evaluated whether suprachoroidal delivery of an engineered recombinant adeno-associated viral (rAAV)-aflibercept vector could achieve sustained, targeted expression with improved efficacy and safety compared with intravitreal administration.MethodsAL-001, an engineered rAAV vector expressing aflibercept, was developed and characterized. Its expression profile was first assessed in New Zealand white rabbits following suprachoroidal space (SCS) injection. Efficacy, pharmacokinetics, and safety were then evaluated in a nonhuman primate model of laser-induced choroidal neovascularization (CNV), comparing SCS and intravitreal (IVT) administration routes.ResultsAL-001 efficiently expressed aflibercept in relevant ocular cells in vitro. In rabbits, SCS administration produced sustained aflibercept levels in ocular tissues. In the nonhuman primate CNV model, a single SCS injection of AL-001 showed favorable efficacy to IVT injection and a notable mild inflammatory response. At week 4, grade IV lesion incidence was 0% (0/48) after SCS administration versus 14.3% (6/42) after IVT administration (absolute difference, −14.3 percentage points; 95% CI, 3.7%–27.8%; P = 0.0258). Throughout follow-up, mean leakage area and grade IV lesion incidence remained 0 with SCS, versus IVT peaks of approximately 0.3 mm2 and 33.0%, respectively, declining to 0.03 mm2 and 2.0% by day 100. Both the medium and high doses decreased pathological vascular leakage and subretinal hyperreflective material. Vector administration preceded laser-induced CNV modeling, demonstrating that sustained intraocular aflibercept expression in the retina and choroid provided durable antiangiogenic protection. Pharmacokinetic analysis confirmed distinct ocular exposure profiles between routes, with viral genomes confined predominantly to the injected eye and no significant systemic accumulation. AL-001 was well tolerated, without sustained intraocular pressure elevation or severe ocular inflammation, and only mild-to-moderate treatment-emergent adverse events. Low pre-existing anti-AAV2 immunity and time-dependent neutralizing antibody responses postdosing, informing a translational model for patient stratification and redosing feasibility.ConclusionSuprachoroidal administration of AL-001 is well tolerated and provides durable, targeted aflibercept expression with pronounced antiangiogenic efficacy. These results support AL-001 as a promising, long-acting therapeutic candidate for wAMD.
ObjectiveThis study aimed to assess the diagnostic yield, clinical indications, and utility of next-generation sequencing (NGS) testing since its implementation through collaboration between the University of Rijeka Faculty of Medicine and the Clinical Hospital Centre Rijeka.Materials and MethodsThis retrospective study included patients referred between 2018 and 2023 from the Clinical Hospital Centre Rijeka to the University of Rijeka Faculty of Medicine for genetic testing, primarily using exome sequencing.ResultsBetween April 2018 and December 2023, 412 patients were referred for exome sequencing, of whom 353 (85.7%) underwent diagnostic genetic testing. A notable increase in tests ordered was observed over time. Patients were most frequently referred from Pediatrics (55.0%), Neurology (29.5%), Cardiology (7.4%), Ophthalmology (3.4%), and others (4.7%). A diagnosis was confirmed in 103/353 patients, corresponding to an overall diagnostic yield of 29.2%, and an adjusted diagnostic yield of 27.2% after collapsing related individuals into single family units. In these confirmed cases, 83 distinct disorders involving 71 unique genes were identified, with most patients showing heterozygous variants and several recurrent disorders and genes. Variants of uncertain significance were reported in 35/353 (9.9%) patients.ConclusionThe 27.2% diagnostic yield demonstrates effective integration of NGS into tertiary clinical practice. The recent introduction of medical genetics specialization is expected to further improve referral quality, variant interpretation, and overall diagnostic outcomes.
BackgroundImmune checkpoint inhibitors (ICIs) yield heterogeneous benefit in metastatic castration-resistant prostate cancer (mCRPC), underscoring the unmet need for robust predictive biomarkers. DNA damage repair (DDR) gene defects encompass mechanistically distinct subtypes—homologous recombination repair (HRR) deficiency, mismatch repair deficiency/microsatellite instability-high (MMRd/MSI-H), and CDK12 inactivation—that may differentially modulate anti-tumor immunity. This study evaluated the combined predictive value of DDR mutation profiles, tumor mutational burden (TMB), and PD-L1 expression for ICI efficacy in mCRPC.MethodsIn this single-center retrospective cohort study conducted at PKUCare CNOOC Hospital (Tianjin, China), 152 patients with mCRPC who received ICI-containing therapy following ≥2 prior lines of systemic treatment were enrolled (January 2018–December 2023). Of these, 127 (83.6%) underwent tissue-based profiling with a validated 520-gene targeted NGS panel, and 25 (16.4%) were profiled by a validated 168-gene liquid biopsy panel. Patients were classified into four DDR subgroups: HRR-deficient, MMRd/MSI-H, CDK12-mutant, and DDR wild-type. Primary endpoints were objective response rate (ORR) and progression-free survival (PFS). Secondary endpoints included overall survival (OS), disease control rate (DCR), and prostate-specific antigen (PSA) response. Kaplan-Meier analysis, multivariate Cox regression, and ROC analysis were performed.ResultsAmong 152 patients, 101 (66.4%) harbored DDR alterations: 58 HRR-deficient (38.2%), 24 MMRd/MSI-H (15.8%), and 19 CDK12-mutant (12.5%). ORR was highest in MMRd/MSI-H (50.0%), followed by CDK12-mutant (26.3%), HRR-deficient (22.4%), and DDR wild-type (9.8%; p < 0.001). Median PFS was significantly longer across all DDR-mutant groups versus DDR wild-type (MMRd/MSI-H: 8.1 months; HR 0.31, 95% CI 0.18–0.53; p < 0.001). On multivariate analysis, DDR mutation subtype, TMB ≥10 mut/Mb, and liver metastasis were independent predictors of PFS. A composite biomarker integrating DDR status, TMB, and PD-L1 achieved the highest predictive accuracy (AUC 0.83, 95% CI 0.75–0.91). irAE rates did not differ significantly across subgroups (p = 0.614).ConclusionDDR gene mutation profiling, integrated with TMB and PD-L1 expression, provides clinically actionable stratification of mCRPC patients for ICI therapy. A composite DDR/TMB/PD-L1 biomarker panel warrants prospective validation in dedicated clinical trials.
IntroductionIn the United States (US), Tribes are sovereign nations and have the right to oversee research conducted with Tribal citizens. However, it is unclear who should approve research protocols when data from American Indian and Alaska Native (AIAN) people are collected off Tribal lands. As genetic research continues to advance and transform the delivery of healthcare, equitable inclusion of AIAN people is necessary, but oversight of research needs clarity.MethodsWe held a 3-day workshop with US thought leaders on genetic and other health research with AIAN people in urban areas to explore views and values on this issue and to discuss potential policy and practice solutions.ResultsThirty-six individuals attended. Solidarity surfaced as a foundational motivation for Tribal Nations to review research conducted with AIAN people, whether on Tribal lands or not. Understanding data from Indigenous perspectives was identified as a way to ensure appropriate AIAN community protections are in place. Three discrete areas to improve policy were suggested–Tribal, Academic Institution, and National–to protect AIAN people participating in research both on and off Tribal lands.DiscussionResearchers, whether Indigenous or not, must recognize Tribal sovereignty and operate in solidarity with the applicable and most appropriate ethical principles and regulations.
BackgroundCHARGE syndrome (OMIM #214800) is a rare autosomal dominant multisystem disorder, most commonly attributable to de novo heterozygous loss-of-function pathogenic variants in the CHD7 gene. Pathogenic Pathogenic variants of CHD7 are distributed throughout the entire coding region, with nonsense and frameshift pathogenic variants predominating, and the vast majority constitute private mutations. Owing to its broad phenotypic spectrum and marked variability in expressivity, early diagnosis remains challenging. This article presents the long-term follow-up data of a female patient with genetically confirmed CHARGE syndrome, with particular emphasis on her clinical trajectory and outcomes achieved through multidisciplinary management.Case presentationThe patient was a full-term female born via spontaneous vaginal delivery in 2017, presenting with respiratory distress and feeding difficulties immediately after birth. Comprehensive evaluation revealed multisystem abnormalities involving the respiratory, cardiovascular, neurological, and sensory systems. Trio-based whole-exome sequencing identified a de novo heterozygous nonsense pathogenic variant, c.6292(EXON31)C>T (p.Arg2098*), in the CHD7 gene. Literature review indicated that this pathogenic variant had been previously reported in cases that all resulted in infantile death. In contrast, our patient, following active multidisciplinary management, achieved significant improvement in multiple organ functions and survived to school age, where she now adapts well to a special education school environment. This case provides the first evidence that this pathogenic variant is compatible with a favorable long-term outcome, highlighting substantial phenotypic heterogeneity and prognostic diversity even among individuals carrying an identical genetic alteration.ConclusionThis case highlights the critical importance of early genetic diagnosis and coordinated multidisciplinary management in CHARGE syndrome. By presenting divergent outcomes associated with the same pathogenic variant, our findings enrich the clinical evidence on CHD7 genotype–phenotype correlations. Even with severe neonatal multisystem involvement, proactive and individualized management can achieve favorable long-term outcomes.
IntroductionChronic kidney disease (CKD) is a major public health challenge, affecting approximately 674 million people worldwide and representing one of the fastest-growing causes of mortality. Since CKD is frequently asymptomatic in its early stages, the identification of novel genetic biomarkers may improve early detection and risk stratification. Genome-Wide Association Studies (GWAS) have identified numerous genetic loci associated with CKD and related traits; however, their performance is often limited in small and imbalanced cohorts, where reduced statistical power increases both false-positive and false-negative findings. Machine learning (ML) approaches can complement conventional GWAS by prioritizing biologically relevant genetic signals from high-dimensional genomic data.MethodsIn this study, we implemented a nested ensemble (NCBC) model composed of an undersampler and a CatBoostClassifier (CBC) to prioritize candidate genetic variants associated with CKD in the INCIPE cohort. Prioritized variants were functionally annotated and evaluated through enrichment analyses, GTEx gene expression profiling, and protein-protein interaction network analyses. Genes identified by the CKDGen Consortium were analysed as an external reference set and used to validate the biological relevance of the prioritized results.ResultsThe NCBC model outperformed conventional ML classifiers, achieving a ROC AUC score of 87.77%, compared to 50%–53% for the other evaluated models. Among the prioritized genes, 56.25% showed protein-protein interactions with genes previously reported by the CKDGen Consortium, whereas only 1.9% of randomly generated gene sets showed interactions.DiscussionOur study demonstrates that the NCBC model improves the prioritization of biologically plausible candidate variants in a small and imbalanced CKD cohort. Functional analyses suggested ABC transporter-related genes, including ABCA13, ABCA4, and ABCC4 genes, as promising candidate for future validation, with ABCA4 showing substantial expression in kidney tissues. Overall, these findings support the integration of ML with GWAS to prioritize candidate genes and investigate the genetic architecture of complex diseases.
Background Lymphangiogenesis promotes tumor dissemination and may shape the immune contexture of cervical cancer, yet lymphangiogenesis-related prognostic stratification and its immunometabolic implications remain insufficiently defined in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC).MethodsTCGA-CESC transcriptomes and clinical data were obtained from UCSC Xena and integrated with normal cervix tissues from the Genotype-Tissue Expression Project after batch correction. Prognostic LYMRGs were first identified from the differentially expressed set using univariable Cox proportional hazards analysis. Candidate genes were then reduced using an L1-regularized Cox model (Least Absolute Shrinkage and Selection Operator), and the remaining markers were entered into a multivariable Cox regression to obtain the final coefficients and compute an individualized risk score. The model’s prognostic value was further assessed in an independent Gene Expression Omnibus dataset. In addition, expression patterns of the signature genes were leveraged for molecular subtyping of TCGA samples via non-negative matrix factorization (NMF). Immune infiltration and immunotherapy-associated characteristics were interrogated through a multi-algorithm strategy (single-sample gene set enrichment analysis, CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore . Additional analyses included pathway enrichment (GSEA/GO/KEGG), drug sensitivity prediction (pRRophetic/CellMiner), and ceRNA network analysis.ResultsA six-gene LYMRG signature robustly stratified survival. High-risk patients had significantly worse overall survival in The Cancer Genome Atlas with AUCs of 0.819/0.801/0.801 at 1/3/5 years, and in GSE52903 (P = 0.001) with AUCs of 0.733/0.719/0.725. NMF identified two subtypes with distinct prognosis (P = 0.01) and divergent immune landscapes. Risk groups and subtypes exhibited consistent differences in immune infiltration, checkpoint expression, TIDE/IPS patterns, and pathway enrichment. Predicted chemosensitivity differed by risk group, and the ceRNA network suggested candidate upstream lncRNA regulators of the signature.ConclusionA lymphangiogenesis-related six-gene model enables clinically meaningful prognostic stratification of CESC and links lymphangiogenesis programs to distinct tumor immune phenotypes and therapeutic vulnerabilities.
IntroductionFeed efficiency (FE) is a complex trait which determines livestock production profitability, yet the molecular mechanisms behind it remain unclear. This study investigated the blood transcriptomic profile of lambs, alongside genotype data with the aim to uncover the genetic basis of FE traits such as absolute dry matter intake (DMIabsolute), DMI adjusted for body size (DMIadjusted), average daily live weight gain (ADG), and residual feed intake (RFI).Materials and MethodsBulk RNA-Seq and genotype data were analysed using three complementary approaches: differential gene expression (DGE) analysis, weighted gene co-expression network analysis (WGCNA), and cis-expression Quantitative Trait Loci (cis-eQTL) mapping. These methods were used independently to identify genes and regulatory networks associated with FE traits and to investigate evidence supporting multi-trait candidate gene selection.ResultsDGE analysis revealed 2, 24, 85 and 4 differentially expressed genes for DMIabsolute, DMIadjusted, ADG, and RFI (Padjusted < 0.05), functionally enriched in sensory perception, ATP-dependent chromatin remodeling, Notch signaling and immune response pathways. 9 gene modules significantly associated with the FE traits (P ≤ 0.05) with correlations ranging from r = -0.56 to 0.49, were identified using WGCNA. Single nucleotide polymorphism (SNP)-level cis-eQTL analysis identified 93 eSNPs associated with 74 genes (false discovery rate (FDR) < 0.05), while permutation-derived gene level analysis identified 280 eGenes (FDR < 0.2, empirical P < 0.03). Across the three analyses, applying thresholds of DGE (Padjusted < 0.05), WGCNA (correlation, P ≤ 0.05), and cis-eQTL gene-level significance (empirical P < 0.05), multiple overlapping genes were identified including DNMT3A, KANSL1, NCOR1 for DMIadjusted, ACOX2, FANCF, CIMIP2B, LOC101115106, ARMH2, LOC132657496 for ADG, and LOC114114576 for RFI representing regulators of variations in FE.DiscussionThe integration of DGE, WGCNA, and cis-eQTL analyses identified key genes and regulatory mechanisms associated with variation in FE traits. These results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.
