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PubMed2025

Screening rare genetic diagnoses for amenability to bespoke antisense oligonucleotide therapy development: A retrospective cohort study.

PURPOSE: To estimate the proportion of molecular genetic diagnoses in a real-world, phenotypically heterogeneous patient cohort that are amenable to antisense oligonucleotide (ASO) treatment. METHODS: We retrospectively applied the N=1 Collaborative's Variant Assessments toward Eligibility for Antisense Oligonucleotide Treatment guidelines to all diagnostic variants found by clinical genome-wide sequencing at a single pediatric hospital in 532 patients over a 6-year period. Variants were classified as either "eligible," "likely eligible," "unlikely eligible," or "not eligible" in relation to the different ASO approaches, or "unable to assess." RESULTS: In total, 25 unique variants across 26 patients (4.9% of 532 patients) were eligible or likely eligible for ASO treatment at a molecular genetic level, via canonical exon skipping (4), splice correction (3), or messenger RNA knockdown (19). Only 8 of these molecular genetic diagnoses were made within a year of symptom onset. After considering disease and delivery related factors, 11 diagnoses were still considered candidates for bespoke ASO development. CONCLUSION: A meaningful proportion of genetic diagnoses identified by genome-wide sequencing may be amenable to ASO treatment. These results underscore the importance of timely diagnosis, and the proactive identification and accelerated functional testing of genetic variants amenable to ASO treatments.

Humans↗
PubMed2026

FGF14 (GAA) repeat expansion-associated Ataxia (SCA27B): Expanding the clinical and diagnostic spectrum from the first genetically confirmed case in Argentina.

Spinocerebellar ataxia 27B (SCA27B), caused by an FGF14 GAA repeat expansion, is an emerging cause of late-onset ataxia. We report the first genetically confirmed Argentinean case, initially misdiagnosed as alcoholic cerebellar degeneration. This case highlights diagnostic challenges, phenotypic heterogeneity, and the importance of genetic testing for this treatable disorder.

4-Aminopyridine↗
PubMed2026

Sitosterolemia: evolving strategies for earlier diagnosis.

PURPOSE OF REVIEW: Sitosterolemia is a rare autosomal recessive lipid disorder caused by biallelic pathogenic variants in ABCG5 or ABCG8 , resulting in excessive intestinal absorption and impaired biliary excretion of plant sterols. Although historically considered exceptionally rare, recent genetic studies suggest the disorder is substantially underdiagnosed, with marked phenotypic heterogeneity ranging from xanthomas and premature atherosclerosis to hematologic abnormalities, and frequently mimics familial hypercholesterolemia. This review summarizes recent advances in the clinical, biological, and genetic diagnosis of sitosterolemia, with a focus on strategies that may facilitate earlier detection. RECENT FINDINGS: Phytosterol quantification, particularly sitosterol, campesterol, and stigmasterol, remains indispensable for accurate diagnosis. Hematologic abnormalities, including hemolytic anemia, stomatocytosis, and macrothrombocytopenia, are increasingly recognized as valuable diagnostic clues complementing the biochemical approach. Expanded variant catalogs for ABCG5/ABCG8 and genome-wide association studies have revealed potentially polygenic contributions to phytosterol metabolism extending beyond these two genes. However, no specific guidelines have yet been established for cascade screening. SUMMARY: Earlier diagnosis requires integration of clinical, biochemical, hematologic, and genetic data. Plasma phytosterol measurement remains the diagnostic cornerstone. Improved disease awareness, broader access to sterol testing, and expanded genetic screening may reduce diagnostic delays and enable timely management, including ezetimibe and dietary phytosterol restriction.

Humans↗
PubMed2023

Serine-threonine phosphoregulation by PknB and Stp contributes to quiescence and antibiotic tolerance in Staphylococcus aureus.

Staphylococcus aureus can cause infections that are often chronic and difficult to treat, even when the bacteria are not antibiotic resistant because most antibiotics act only on metabolically active cells. Subpopulations of persister cells are metabolically quiescent, a state associated with delayed growth, reduced protein synthesis, and increased tolerance to antibiotics. Serine-threonine kinases and phosphatases similar to those found in eukaryotes can fine-tune essential bacterial cellular processes, such as metabolism and stress signaling. We found that acid stress-mimicking conditions that S. aureus experiences in host tissues delayed growth, globally altered the serine and threonine phosphoproteome, and increased threonine phosphorylation of the activation loop of the serine-threonine protein kinase B (PknB). The deletion of stp, which encodes the only annotated functional serine-threonine phosphatase in S. aureus, increased the growth delay and phenotypic heterogeneity under different stress challenges, including growth in acidic conditions, the intracellular milieu of human cells, and abscesses in mice. This growth delay was associated with reduced protein translation and intracellular ATP concentrations and increased antibiotic tolerance. Using phosphopeptide enrichment and mass spectrometry-based proteomics, we identified targets of serine-threonine phosphorylation that may regulate bacterial growth and metabolism. Together, our findings highlight the importance of phosphoregulation in mediating bacterial quiescence and antibiotic tolerance and suggest that targeting PknB or Stp might offer a future therapeutic strategy to prevent persister formation during S. aureus infections.

Animals↗
PubMed2026

ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.

UNLABELLED: Resolving bacterial strain diversity from shotgun metagenomic data is fundamental to understanding intra-host evolution, transmission dynamics, and phenotypic heterogeneity. However, current probabilistic approaches face a severe "identifiability limit" when disentangling highly similar genomes. Under high-noise conditions, sequencing errors, coverage overdispersion, and collinearity confound standard expectation-maximization algorithms, resulting in overfitting and spurious "ghost" strains. Here, we introduce zero-inflated latent allocation for strain reconstruction from metagenomes with adaptive sparsity regularization (ZILA-SRM) to overcome this barrier through three innovations. First, we integrate a zero-inflated Poisson mixture model to decouple "structural zeros" (true strain absence) from "sampling zeros" (stochastic dropout), addressing overdispersion in standard Poisson-based tools. Second, we impose a convex adaptive sparsity regularization penalty that leverages biological sparsity priors to shrink noise artifacts dynamically. Third, we implement a graph-theoretic refinement step using maximal clique enumeration to resolve haplotype collinearity. Benchmarking against StrainFinder and MixtureS on 702 synthetic data sets shows that ZILA-SRM achieves a 20% improvement in precision in high-complexity scenarios while maintaining over 80% recall for minor variants at 0.5% abundance. Re-analysis of deep-sequencing data from 195 Mycobacterium tuberculosis clinical samples reveals cryptic low-abundance drug-resistant variants in 12% of patients, including a minor clone carrying the rpoB S450L mutation. Furthermore, application to skin microbiome data sets further reveals a strong negative correlation between dominant Staphylococcus aureus and Staphylococcus epidermidis strains, providing genomic evidence for competitive exclusion. These findings establish ZILA-SRM as a robust tool for resolving strain-level diversity in complex metagenomes. IMPORTANCE: Understanding microbial communities at the strain level is critical because closely related strains can differ dramatically in traits such as drug resistance, virulence, and ecological interactions. However, resolving individual strains from metagenomic sequencing data remains difficult, especially when strains are highly similar or present at low abundance. As a result, biologically meaningful diversity is often obscured or misinterpreted as noise. In this study, we introduce a new framework that improves the reliability of strain reconstruction from complex metagenomic data. By reducing false-positive strain detection while preserving sensitivity to rare variants, our approach enables more accurate characterization of microbial populations. This improved resolution reveals previously hidden subpopulations in clinical and microbiome datasets, providing clearer insights into microbial evolution, competition, and the emergence of clinically relevant traits such as antibiotic resistance.

Metagenomics↗
PubMed2025

Genetic analysis of four cases of Poirier Bienvenu neurodevelopmental syndrome associated with CSNK2B variant.

BACKGROUND: CSNK2B deficiency underlies the pathogenesis of Poirier-Bienvenu neurodevelopmental syndrome (POBINDS). In this study, we present four cases of pediatric seizures caused by de novo variants in CSNK2B, with the aim to reinforce the clinical and variant data pertaining to early genetic factors associated with epilepsy. METHODS: Trio whole exome sequencing were used to detect variants in the proband and her family members, and bioinformatics annotation was performed for the variant. Sanger sequencing and CSNK2B cDNA sequencing were employed to ascertain the carrier status of additional family members and evaluate the potential impact of variants on splicing. RESULTS: All four cases presented with epilepsy as the initial manifestation, accompanied by global developmental delay, particularly in language and motor developmental delay. Cases 1, 3 and 4 exhibited full-scale tonic-clonic seizures, while case 2 displayed myoclonic and typical absence seizures. Furthermore, case 2 demonstrated delayed growth and development compared to age-matched peers. No abnormality was detected in the head magnetic resonance imaging (MRI). Genetic analysis revealed novel heterozygous variants in the CSNK2B gene in all four cases, including c.175 + 1G > A, c.73-2A > G, c.291 + 1G > A and c.481delA. In case 2, reverse transcription analysis of CSNK2B mRNA revealed the retention of the 3' end sequence of Intron 2 and deletion of the 5' end sequence of Exon 3. In treatment, four case received a combination of one to three types of antiseizure medication and rehabilitation training individually. Case 1 continued to experience seizures to varying degrees, while cases 2-4 demonstrated effective seizure control. Overall motor and intellectual development improved in all four cases, however, there was slow recovery in language function. CONCLUSION: This study elucidates the molecular etiology of epilepsy in four cases with POBINDS and expands the mutational spectrum of pathogenic variants in the CSNK2B, highlighting their impact on splicing. The highly genetic heterogeneous phenotype of POBINDS relies on the detection of pathogenic variants in CSNK2B. Conventional antiseizure medication effectively control seizures, while rehabilitation treatment can significantly improve intelligence and motor function to varying degrees; however, language recovery tends to be relatively slow.

Humans↗
PubMed2025

Charting the phenotypic landscape of mitochondrial diseases through a systematic evaluation of pathogenic mitochondrial DNA and nuclear gene variants.

PURPOSE: Primary mitochondrial diseases (PMD) arise from variants in the mitochondrial or nuclear genomes. Phenotype-based recognition of specific PMD genotypes remains difficult, prolonging the diagnostic odyssey. We expanded the MitoPhen database to characterize phenotypic variation across PMD more systematically. METHODS: Individual-level data on mitochondrial DNA disorders, nuclear-encoded mitochondrial diseases, and single large-scale mitochondrial DNA deletions were manually curated with Human Phenotype Ontology (HPO) terms to produce MitoPhen v2. Principal-component analysis summarized system-level abnormalities; HPO-level enrichment and mean phenotype-similarity scores were then used to distinguish common PMD genotypes. RESULTS: MitoPhen v2 adds 3940 individuals to the original release, now encompassing 1597 publications, 10,626 individuals, and 117 genotypes. Among 7586 affected cases, 72,861 HPO terms were recorded. Principal-component analysis revealed 6 phenotype dimensions capturing most system-level variance. At the HPO level, we observed genotype-specific enrichments and identified 111 gene-phenotype links absent from the current HPO database. Using MT-TL1, single large-scale mitochondrial DNA deletions, and POLG as exemplars, phenotype-similarity scores reliably separated individuals with these genotypes from those without. CONCLUSION: MitoPhen v2 enabled systematic, genotype-aware analysis of heterogeneous PMD phenotypes and highlighted the diagnostic value of structured, individual-level data. Phenotype-similarity metrics from such data sets can refine variant interpretation in large rare-disease cohorts and provide a transferable framework for other phenotypically complex genetic disorders.

Humans↗
PubMed2026

Maternal genetic variants associated with aneuploid conception: a narrative review.

BACKGROUND: Human aneuploid conception, a leading cause of infertility, pregnancy loss, and congenital disorders (e.g. Down's syndrome), arises from errors in chromosome segregation during oocyte meiosis or embryonic mitosis. While advanced maternal age is a well-established risk factor, significant inter-individual variation exists among younger women, suggesting a substantial role for maternal genetic determinants. OBJECTIVE AND RATIONALE: This review summarizes the identified maternal genetic variants associated with aneuploid conceptions and highlights directions for future research. SEARCH METHODS: We systematically searched PubMed, Embase, and the Cochrane Library (up to 12 January 2026), using key terms related to maternal genetics, genetic variants, aneuploidy, and pregnancy. Inclusion criteria were human studies, genetic confirmation of aneuploidy (in oocytes/embryos/products of conception/fetal cells), maternal variants (rare single-nucleotide variations, single-nucleotide polymorphisms, and small indels [≤50 bp]), and English-language publications. Exclusion criteria were non-human studies, structural/non-aneuploid numerical abnormalities, paternal factors, and conference abstracts. Extracted data items included study identifiers, population characteristics, variant details, detection methods, clinical phenotypes, type and origin of aneuploidy, pathogenicity or effect assessment, and gene inclusion in currently commercially available infertility next-generation sequencing (NGS) panels. Rare variants were classified per American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines, whereas common variants were evaluated based on effect estimates and functional validation. Study quality was appraised using a modified Newcastle-Ottawa Scale. Supplementary searches explored associations between the identified genes and a broader range of reproductive phenotypes. OUTCOMES: From 28 studies covering the broad clinical spectrum of aneuploid pregnancies (including embryo arrest, implantation failure, pregnancy loss, hydatidiform mole, and fetal aneuploidy), we identified maternal variants associated with aneuploid conceptions. These were functionally categorized into meiotic recombination, spindle dynamics, checkpoint enforcement, and the maternal-to-zygotic transition. Among them, variants in several genes are supported by higher-quality evidence, including likely pathogenic rare variants in KIF18A, ELL3, and CEP120, as well as common variants in PLK4 and CCDC66. Although some identified genes (HFM1, MCM9, MEI1, BUB1B, NLRP2, NLRP7, and TLE6) are included in commercial infertility NGS panels, their direct association with aneuploidy requires further validation. WIDER IMPLICATIONS: This review proposes that 'aneuploidy predisposition' constitutes a critical, mechanism-driven dimension for the genetic diagnosis of infertility, complementing phenotype-based frameworks. This approach would best serve women with unexplained infertility and a normal karyotype who have either a history of recurrent aneuploidy or heterogeneous reproductive phenotypes across different cycles. Adopting this perspective refines clinical genetic testing paradigms and underscores the need to prioritize artificial intelligence-enhanced clinico-genomic association studies and develop polygenic risk models integrated with clinical factors. PROSPERO REGISTRATION NUMBER: CRD42025636217.

Humans↗
PubMed2025

Extrachromosomal DNA-Driven Oncogene Dosage Heterogeneity Promotes Rapid Adaptation to Therapy in MYCN-Amplified Cancers.

UNLABELLED: Extrachromosomal DNA (ecDNA) amplification enhances intercellular oncogene dosage variability and accelerates tumor evolution by violating foundational principles of genetic inheritance through its asymmetric mitotic segregation. Spotlighting high-risk neuroblastoma, we demonstrate how ecDNA amplification undermines the clinical efficacy of current therapies in cancers with extrachromosomal MYCN amplification. Integrating theoretical models of oncogene copy number-dependent fitness with single-cell ecDNA quantification and phenotype analyses, we reveal that ecDNA copy-number heterogeneity drives phenotypic diversity and determines treatment sensitivity through mechanisms unattainable by chromosomal oncogene amplification. We demonstrate that ecDNA copy number directly influences cell fate decisions in cancer cell lines, patient-derived xenografts, and primary neuroblastomas, illustrating how extrachromosomal oncogene dosage-driven phenotypic diversity offers a strong evolutionary advantage under therapeutic pressure. Furthermore, we identify senescent cells with reduced ecDNA copy numbers as a source of treatment resistance in neuroblastomas and outline a strategy for their targeted elimination to improve the treatment of MYCN-amplified cancers. SIGNIFICANCE: ecDNA-driven tumor genome evolution provides a major challenge to curative cancer therapies. We demonstrate that ecDNA copy-number dynamics drives treatment resistance by promoting oncogene dosage-dependent phenotypic heterogeneity in MYCN-amplified cancers. Exploiting phenotype-specific vulnerabilities of ecDNA cells, therefore, presents a powerful strategy to overcome treatment resistance. See related commentary by Korsah, p. 1979.

Humans↗
PubMed2026

Familial short stature: genetic architecture, risk stratification, and precision management.

BACKGROUND: Familial short stature (FSS) has traditionally been considered a benign growth pattern characterized by short stature clustering within families and has often been regarded as a normal variant of growth. However, recent advances in genomic technologies have demonstrated that a subset of children presenting with an FSS phenotype harbor identifiable monogenic variants, particularly in genes involved in growth plate development and skeletal growth. These findings challenge the traditional phenotype-based understanding of FSS and support an etiology-oriented diagnostic framework. OBJECTIVE: To summarize current knowledge regarding the genetic architecture of FSS, review existing clinical risk stratification frameworks for genetic evaluation, and evaluate available evidence regarding treatment outcomes across different genetic etiologies. METHODS: A literature search was performed in PubMed, Embase, and Web of Science from inception to May 2026, using keywords including "familial short stature," "familial idiopathic short stature," "genetic testing," "ACAN," "SHOX," and "NPR2". Relevant original studies and review articles addressing genotype-phenotype correlations, diagnostic yield of genetic testing, or responses to recombinant human growth hormone (rhGH) therapy were considered. RESULTS: Emerging evidence indicates that monogenic variants can be identified in a subset of children with an FSS phenotype, especially among those with more severe short stature and autosomal dominant inheritance patterns. Variants affecting growth plate biology represent some of the most frequently reported genetic causes of FSS, with ACAN, SHOX, and NPR2 being the most frequently implicated genes. Existing clinical frameworks based on parental height patterns and inheritance characteristics may help stratify patients with FSS according to the likelihood of monogenic etiology and guide selection of individuals who may benefit from genetic testing. Available evidence suggests that rhGH therapy may improve growth outcomes in several monogenic forms of FSS, although treatment responses vary according to genetic etiology. CONCLUSIONS: FSS should be regarded as a heterogeneous clinical phenotype rather than a single diagnostic entity. Integration of existing clinical risk stratification approaches with molecular diagnosis may enable more precise identification of underlying genetic causes and facilitate individualized therapeutic decision-making. Future advances in FSS management will likely depend on precision medicine approaches linking phenotype, genotype, and treatment response.

Humans↗
PubMed2026

Molecular Pathways, Target Landscape, and Translational Models in Heart Failure with Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) is a substantial global health burden and the greatest unmet medical need for cardiovascular diseases. It is marked by pronounced clinical heterogeneity and complex multi-system pathophysiology with limited therapeutic options. Progress in developing effective therapeutics is constrained by the inadequacy of experimental models to fully recapitulate the multifactorial nature of the disease. Recent evidence underscores the significant involvement of inflammatory, oxidative, and mitochondrial pathways in the pathogenesis of HFpEF, with non-coding RNAs and epigenetic regulation serving as crucial modulators and prospective therapeutic targets. This review maps the HFpEF target landscape, while critically assessing the mechanistic contributions, translational fidelity, and limitations of existing in vivo and in vitro models. Further, advances are noted among the in vitro technologies, including human cardiac organoids and engineered heart tissues integrated with high-throughput multi-omics and computational modeling, enabling in-depth examination of HFpEF mechanisms. Finally, we underscore the necessity of integrative, systems-level approaches and multi-marker strategies to enhance translational relevance, improve risk stratification, and accelerate development of mechanism-based therapies. Collectively, this review supports phenotypic-guided and mechanism-informed therapeutic development for HFpEF, and provides a roadmap for next generation model development and therapeutic innovation.

Humans↗
PubMed2026

Expression patterns of potential targets for antibody-directed therapy in metastatic castration-resistant prostate cancer patients.

INTRODUCTION: Survival in metastatic castration-resistant prostate cancer (mCRPC) patients remains limited and treatment is complicated by tumor heterogeneity. As antibody-based therapeutics emerge, identifying actionable antigen targets and patient subgroups most likely to benefit is essential. MATERIALS & METHODS: Gene expression of 62 antibody-targetable proteins was analyzed in 296 mCRPC biopsies. These genes encode proteins targeted by approved or investigational antibody-based cancer therapeutics. Associations between target expression with genomic classifications and transcriptomic subtypes were evaluated. Target expression was also assessed in tumors with low expression of established mCRPC targets. Subgroup-specific targets were validated in an independent cohort and single-cell transcriptomics. RESULTS: Established targets KLK2, FOLH1 (PSMA) and STEAP1 showed the highest median expression across the cohort. Target expression did not correlate with genomic classifications, including homologous recombination deficiency, microsatellite instability, CDK12, TP53, PTEN or AR alterations Target expression did associate with transcriptomic subtypes: CRPC-AR (driven by androgen receptor-signaling) and CRPC-SCL (stem cell-like features, AP-1/YAP/TAZ-driven), displayed the highest expression of multiple targets, including KLK2, FOLH1, and SLC44A4. CRPC-NE (neuroendocrine phenotype) showed heterogeneous expression, with high CD46 expression, whereas CRPC-WNT (Wnt-signaling driven) generally showed low target expression. Notably, CD46 was highly expressed in tumors with low KLK2, FOLH1, and STEAP1 expression, a subgroup associated with poor prognosis. CONCLUSIONS: Although several antibody targets showed broad expression in mCRPC-tumors, expression varied by transcriptomic subtype. Subgroups such as CRPC-WNT expressed fewer targets, suggesting the need for alternative therapeutic strategies. CD46 emerged as a promising target, with wide expression across multiple subtypes, including clinically challenging CRPC-NE and mCRPC tumors lacking expression of established targets.

Humans↗
PubMed2025

Complex IV deficiency due to COX4I1 deep intronic and de novo variants results in progressive motor impairment and Leigh syndrome.

COX4I1 gene encodes cytochrome c oxidase subunit 4 isoform 1, involved in the early assembly stages of mitochondrial respiratory chain complex IV. To date, COX4I1 pathogenic variants have been reported in only a few cases, each exhibiting heterogeneous clinical phenotypes and limited functional data. Here, we describe the fourth reported case of COX4I1 deficiency associated with human disease, expanding the phenotypic and genetic spectrum of this rare mitochondrial disorder and providing novel clinical, molecular, and functional data. The herein reported individual presented with progressive deterioration of motor skills, intellectual disability and brain imaging abnormalities compatible with Leigh syndrome. Genetic studies combining short and long read next generation sequencing uncovered a peculiar genetic combination in this patient, harboring a de novo COX4I1 nonsense substitution in trans with an inherited deep intronic variant (c.[64C>T];[73+1511A>G]; p.[Arg22Ter];[Glu25ValfsTer9]). Functional studies performed in patient's tissues and transiently transfected cell lines demonstrated that the identified variants mainly exert their pathogenic effect by targeting COX4I1 protein levels, thereby impairing the proper assembly and activity of complex IV.Additionally, proteomic data in patient's fibroblasts suggested an underlying pathomechanism that involves not only the regulation of complex IV function but also the levels of mitoribosomal proteins. In summary, our findings shed light to clarify some of the main clinical features associated with COX4I1 deficiency and the molecular mechanisms involved in the pathogenesis of this disorder.

Humans↗
PubMed2025

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Single-Cell Analysis↗
PubMed2025

Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma.

Epigenetic mechanisms play a crucial role in driving transcript expression and shaping the phenotypic plasticity of glioblastoma stem cells (GSCs), contributing to tumor heterogeneity and therapeutic resistance. These mechanisms dynamically regulate the expression of key oncogenic and stemness-associated genes, enabling GSCs to adapt to environmental cues and evade targeted therapies. Importantly, epigenetic reprogramming allows GSCs to transition between cellular states, including therapy-resistant mesenchymal-like phenotypes, underscoring the need for epigenetic-targeting strategies to disrupt these adaptive processes. Understanding these epigenetic drivers of gene expression provides a foundation for novel therapeutic interventions aimed at eradicating GSCs and improving glioblastoma outcomes. Using machine learning (ML), we employ cross-patient prediction of transcript expression in GSCs by combining epigenetic features from various sources, including ATAC-seq, CTCF ChIP-seq, RNAPII ChIP-seq, H3K27Ac ChIP-seq, and RNA-seq. We investigate different ML and deep learning (DL) models for this task and ultimately build our final pipeline using XGBoost. The model trained on one patient generalizes to other 11 patients with high performance. Notably, H3K27Ac alone from a single patient is sufficient to predict gene expression in all 11 patients. Furthermore, the distribution of H3K27Ac peaks across the genomes of all patients is remarkably similar. These findings suggest that GSCs share a common distributional pattern of enhancer activity characterized by H3K27Ac, which can be utilized to predict gene expression in GSCs across patients. In summary, while GSCs are known for their transcriptomic and phenotypic heterogeneity, we propose that they share a common epigenetic pattern of enhancer activation that defines their underlying transcriptomic expression pattern. This pattern can predict gene expression across patient samples, providing valuable insights into the biology of GSCs.

Glioblastoma↗
PubMed2026

A single-cell lens into the co-evolution of genotypes and phenotypes in cancer.

Genetic heterogeneity and clonal outgrowths are observed even in otherwise healthy human tissues, shaping the genetic composition of cell populations in non-malignant disease and during physiological ageing. This clonal mosaicism likely provides the pre-cancerous seeds for malignant transformation. Once a tumour arises, clonal evolution poses a major challenge to achieving cure, as clonal diversification provides an expanded number of substrates upon which therapy can act as a selective pressure, leading to the selection of resistant clones that ultimately fuel disease recurrence. Understanding somatic clonal evolution requires not only mapping genetic diversity but also defining the resulting phenotypes that provide a fitness advantage to mutated clones. This Review discusses multimodal single-cell technologies that enable the measurement of genotypes and additional molecular features from the same cell. These technologies unveil mutant-specific phenotypic traits, often show cell-state specificity in genotype-phenotype effects and can define therapeutic vulnerabilities for precision elimination of disease-propagating mutant cells. Furthermore, the combination of phylogenetic reconstruction with phenotypic measurements allows for the temporal mapping of clonal evolution and phenotypic plasticity. These breakthroughs have created a unique opportunity to define, directly in primary human samples, the mechanisms underlying clonal expansion in both healthy and malignant tissues.

Journal Article↗
PubMed2026

From genotype to phenotype: understanding the genetic basis of autism.

PURPOSE OF REVIEW: This paper covers some of the key findings on the topic of genetic influences in autism over the last 12-18 months, which consist of significant conceptual shifts and new insights from recent technological advances. RECENT FINDINGS: Autism is a highly heritable condition, with significant heterogeneity of the genes that influence the development of this condition. The heterogeneity of autism, and multiple pathways contributing to the development of an autistic phenotype, create challenges in our understanding, diagnosis, and management of this condition.Recent studies of common genetic variation and polygenic risk scores have focussed on resolving phenotypic heterogeneity and identifying meaningful autism subtypes. Rare-variant discovery has expanded across ancestries, the X chromosome, noncoding loci, structural variants, and tandem repeats, aided by long-read and pangenome-informed sequencing. Single-cell multiomics, spatial perturbation methods and human organoid models have connected genetic variation to cell-type-specific and developmental phenotypes, while also revealing substantial mutation-specific effects and methodological sensitivity. Genetic testing increasingly provides aetiological diagnoses and informs medical surveillance. Recent developments also illustrate the therapeutic potential of gene-first approaches for selected monogenic neurodevelopmental disorders. SUMMARY: Recent developments have expanded our understanding of the way the genetic basis of autism manifests phenotypically.

autism↗
PubMed2026

Diagnosis, treatment and monitoring of pediatric Behçet's disease: Systematic literature review informing the ISSAID/PRES recommendations.

BACKGROUND: Pediatric-onset Behçet's disease (BD) accounts for up to 20% of cases and represents a distinct clinical entity characterized by evolving phenotypes and age-specific patterns of organ involvement. This systematic literature review synthesizes current evidence on pediatric BD, informing forthcoming recommendations by the International Society of Systemic Auto-Inflammatory Diseases (ISSAID) and the Pediatric Rheumatology European Society (PReS). METHODS: A systematic search was conducted according to PRISMA guidelines. Observational studies reporting clinical features, diagnostic criteria, management strategies, and outcomes in BD patients diagnosed before the age of 16 years were included. Proportional meta-analysis was performed to give pooled estimates for organ system involvement. RESULTS: Fifty-two studies, encompassing 2929 patients, met inclusion criteria. Sex distribution was balanced, with a 1:1 male-to-female ratio. The age of onset differed, with 1 year old being the lowest median age of onset and 2 years the lowest median age of diagnosis. The pooled random-effects estimate demonstrated that 50% of patients were HLA-B51 positive (95% CI, 0.5-0.6). Mucocutaneous manifestations were nearly universal (97.8%) and frequently represented the initial feature (80.9%). Musculoskeletal (36%), ocular (35%), neurological (17.9%), gastrointestinal (20%), vascular (15.4%) manifestations showed substantial variability in prevalence. Therapeutic approaches varied widely and were extrapolated from adult practice, with treatment guided by organ involvement and severity. CONCLUSIONS: Pediatric BD encompasses a heterogeneous spectrum of phenotypes requiring harmonized diagnostic frameworks, structured phenotypic stratification, and standardized monitoring to improve long-term outcomes. The relative burden and combination of organ manifestations varied across cohorts, reflecting both biological heterogeneity and differences in study design.

Humans↗