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PubMed2026

Prader-Willi syndrome as a neurogenetic model for psychosis and obsessive-compulsive disorder: A review of clinical, behavioral, and biological insights.

Prader-Willi syndrome (PWS) is a complex neurodevelopmental disorder classically defined by hyperphagia and obesity. However, its profound psychiatric phenotype offers a unique genetic framework for understanding major mental illnesses. This review positions PWS as a potentially informative biological model for psychosis and obsessive-compulsive disorder (OCD), bridging the gap between 15q11-q13 imprinting defects and neural circuit dysfunction. We synthesize evidence demonstrating that psychosis in PWS is not a uniform trait but is disproportionately linked to the maternal uniparental disomy (mUPD) subtype. This genotype-phenotype correlation suggests that overexpression of maternally imprinted genes and loss of paternal expression disrupt cortical excitatory-inhibitory balance, resembling the "schizophrenia-bipolar" genomic architecture. Furthermore, synthesized evidence characterizes the repetitive, ritualistic behaviors in PWS not merely as behavioral challenges, but as a developmentally arrested OCD-spectrum phenotype driven by distinct serotonergic-oxytocinergic imbalances and hypothalamic-limbic dysconnectivity. Mechanistic insights from preclinical models of MAGEL2, SNORD116, and NDN deficiency are integrated with clinical findings to highlight shared neurobiological substrates. Finally, we outline a roadmap for precision psychiatry in PWS, emphasizing the necessity of pharmacogenomics in antipsychotic management and the potential of targeted circuit-based therapeutics. By deconstructing the psychiatric comorbidities of PWS, we provide a framework for translating genomic architecture into mechanistic understanding and targeted treatment for complex neuropsychiatric disorders.

15q11-q13↗

PubMed2026

Expanding the clinical spectrum of ARV1-related disease beyond classical developmental and epileptic encephalopathy.

PURPOSE: Biallelic pathogenic variants in ARV1 are classically associated with developmental and epileptic encephalopathy-38 (DEE38), a severe infantile-onset disorder characterized by drug-resistant epilepsy, profound neurodevelopmental impairment, and early mortality. However, emerging evidence suggests broader phenotypic variability. We aimed to expand the clinical and molecular spectrum of ARV1-related disease through a retrospective case series and structured literature review. METHODS: We retrospectively identified five unrelated Saudi Arabian families with biallelic pathogenic or likely pathogenic ARV1 variants confirmed by whole-exome sequencing. Clinical, neurodevelopmental, neurophysiological, neuroimaging, and multisystem findings were reviewed. A structured literature review was performed to integrate previously reported cases. RESULTS: We identified marked clinical heterogeneity, including a novel ARV1 missense variant (c.214G>T; p.Asp72Tyr), which remains classified as a variant of uncertain significance according to ACMG/AMP criteria despite multiple computational predictions supporting a deleterious effect. Clinical severity ranged from severe developmental and epileptic encephalopathy with drug-resistant epilepsy and early mortality to milder static neurodevelopmental phenotypes with sustained seizure remission and long-term survival into adulthood. Families harboring the same homozygous frameshift variant exhibited markedly different clinical severity, supporting the absence of a strict genotype-phenotype correlation. Multisystem involvement included neurological, cardiac, skeletal, sensory, gastrointestinal, and genitourinary manifestations, and metabolic phenocopies contributed to diagnostic delays. CONCLUSION: Our findings demonstrate that ARV1-related disease represents a broad multisystem clinical spectrum, with classical DEE38 representing its most severe presentation rather than its sole manifestation. Recognition of milder phenotypes, prolonged seizure remission, and marked phenotypic variability has important implications for diagnosis, prognostic counseling, and multidisciplinary long-term surveillance. Early genomic testing should be considered in patients with early-onset epilepsy and multisystem involvement, particularly in consanguineous populations.

ARV1↗

PubMed2026

Population-scale disease-associated tandem repeat analysis reveals locus and ancestry-specific insights.

Tandem repeat (TR) expansions, including short TRs (motifs ≤6 bp) and variable number TRs (motifs >6 bp), underlie many monogenic disorders, with variable length and sequence influencing pathogenicity, penetrance, severity, and onset. Accurate genotype-phenotype correlation and disease prevalence estimation require characterization beyond repeat length. Here we present a population-scale analysis of 66 disease-associated TR loci using long-read assemblies from 2530 diverse haplotypes from 1265 unaffected donors. Integrating repeat length, motif composition, local ancestry, linkage disequilibrium, and phylogenetic analyses, we reveal extensive locus-, population-, and allele-specific variation shaping disease risk. Up to 8.5% of individuals carry expansions above established pathogenic thresholds, many containing interrupting motifs or sequence structures that attenuate pathogenicity. After excluding alleles from loci with uncertain disease association, non-pathogenic interrupted expansions, and carrier states inconsistent with inheritance patterns, ~4% carried expansions predicted to confer disease risk, largely at adult-onset loci with reduced penetrance. Ancestry-resolved analyses uncover population-specific TR architectures contributing to epidemiological disparities in repeat expansion disorders. Phylogenetic analyses identify conserved ancestral alleles and loci with recent instability. We describe variable linkage disequilibrium patterns and recombination signatures around specific disease-associated TR loci. Our findings emphasize integrating sequence, ancestry, and evolutionary context to understand the complex landscape of disease-associated TRs.

Humans↗

PubMed2026

An EHR-based framework for modeling growth curves and constructing growth centile charts for genetic disorders.

Growth modeling is central to human genetics, as deviations from typical growth can signal an underlying disorder. In this cohort study, we developed a generalizable framework for generating growth charts across genetic conditions using electronic health records (EHR). Leveraging 22 years of longitudinal EHR data from 452,470 patients across 15 genetic conditions and unaffected individuals, we generated sex- and condition-specific growth charts using Generalized Additive Models for Location, Scale, and Shape, and quantified differences in size, timing, and intensity using SuperImposition by Translation and Rotation (SITAR). SITAR-derived growth parameters showed strong concordance with established annotations in OMIM and Orphanet, and identified previously unreported growth patterns. We stratified cystic fibrosis by CFTR functional class and observed greater growth impairment in individuals with homozygous minimal-function variants compared to those with residual function. This framework provides a generalizable approach for leveraging EHR data to refine genotype-phenotype relationships and enable continuous updating of growth charts across genetic conditions.

Journal Article↗

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

Single-cell profiling of mitochondrial phenotyping-coupled mtDNA genotyping.

Simultaneously profiling mitochondrial DNA (mtDNA) heteroplasmy and phenotypic variability at the single-cell level remains a challenge due to the absence of integrated methods that map mitochondrial genotypes alongside their functional states. We introduce human single-cell mitochondrial phenotype-coupled mtDNA sequencing (scMPCDS), a platform that quantifies mtDNA mutations and heteroplasmy together with mitochondrial membrane potential and reactive oxygen species within individual cells. Unlike bulk sequencing or separate single-omics techniques, scMPCDS directly correlates mitochondrial genomic instability with functional outcomes. Using this approach, we demonstrate that DdCBE-mediated mtDNA editing induces cell-specific off-target mutations in the mitochondrial genome, which coincide with diverse phenotypic changes. Applying scMPCDS to HeLa cells and clear cell renal cell carcinoma tissues, we identify single-cell subpopulations exhibiting distinct mtDNA mutation burdens and altered bioenergetic profiles, implicating potential mitochondrial heterogeneity-driven tumor evolution. Overall, scMPCDS serves as a versatile tool to unravel mitochondrial genotype-phenotype relationships at the single-cell level in both normal and disease states, thereby advancing precise mitochondrial diagnostics and therapeutics.

Humans↗

PubMed2026

GiGCN: a network-based framework for uncovering synthetic lethal and viable genetic interactions.

Genetic interactions (GIs) underpin the functional connectivity of genes and pathways, and are important for dissecting genotype-phenotype relationships and identifying therapeutic targets for diseases. However, the scale of the human genome restricts systematic experimental interrogation of GIs. Existing computational tools focus on predicting synthetic lethality (SL) and synthetic viability (SV), the two primary forms of GIs, yet their accuracy and biological interpretability are compromised by inadequate modeling of the molecular mechanisms behind positive and negative interactions, as well as the limitation of negative samples. To overcome these challenges, we developed Genetic Interaction Graph Convolutional Network (GiGCN), a signed network modeling framework for the joint identification of gene pairs with SL and SV. We built a high-confidence signed genetic network by integrating verified GIs, and non-interacting gene pairs, together with gene semantic similarity derived from biological processes. By leveraging disentangled subspace decomposition, this framework separately models distinct functional dimensions within gene networks, enabling robust representation of context-dependent regulatory relationships and accurate discrimination of SL and SV events. Benchmark experiments demonstrate that GiGCN outperforms state-of-the-art approaches (area under receiver operating-characteristic curve: 0.978, and area under precision-recall curve: 0.944). Further analyses reveal biologically meaningful insights, including known and novel SL interactions centered on the oncogene MYC Proto-Oncogene (MYC), as well as SV interactions linked to autophagy and mitophagy pathways. This study provides a robust and interpretable network-based strategy for systematically exploring GIs. The GiGCN framework not only improves the precision of SL and SV prediction, but also offers mechanistic insights into gene functional relationships, thereby supporting the discovery of actionable therapeutic targets for cancer and other human diseases.

Humans↗

PubMed2025

HAP-SAMPLE2: data-based resampling for association studies with admixture.

MOTIVATION: HAP-SAMPLE2 extends the functionality of the original HAP-SAMPLE tool for simulating genotype-phenotype data, now with features to handle population admixture and rare variant analysis. It allows users to define parameters such as disease prevalence and allele effect sizes for both common and rare variant simulations. RESULTS: HAP-SAMPLE2 provides an efficient means for simulating complex datasets, suitable for large-scale projects like the 1000 Genomes Project. Its capabilities for population admixture allow users to create admixed populations or preserve substructures while introducing novel variation through artificial recombination. Additionally, the tool supports burden testing for rare variants using fixed and Madsen-Browning weighting schemes. AVAILABILITY AND IMPLEMENTATION: The software, along with a detailed vignette, is available on GitHub: https://github.com/M3dical/HAPSAMPLE2.

Software↗

PubMed2026

Bridging ancestry gaps in genomic risk prediction with tabular foundation models.

MOTIVATION: Models deployed for genomic prediction of diseases perform unevenly across populations, limiting clinical utility. Two factors drive this limitation: large imbalances in sample availability across ancestry groups and non-stationarity of genotype-phenotype effect sizes across the ancestry continuum. While tabular foundation models with in-context learning (ICL) have shown strong sample efficiency in other domains, their effectiveness for genotype-to-phenotype prediction and their robustness to ancestry-driven effect heterogeneity remain unclear. RESULTS: Using large, ancestrally diverse biobank data, we show that ICL-capable tabular foundation models reduce performance degradation in under-sampled ancestry groups compared to conventional supervised approaches. However, we find that prevailing models trained on existing synthetic tabular tasks fail when allele effect sizes vary across ancestry space. Treating genetic ancestry as a continuous variable, we introduce an instruction-tuning framework that exposes models to synthetic tasks with ancestry-dependent non-stationary effects. Instruction-tuned models achieve improved and more stable predictive performance across the genetic ancestry continuum, including for individuals distant from in-context exemplars in ancestry space. AVAILABILITY AND IMPLEMENTATION: All code for instruction-tuning models, synthetic task generation, data wrangling, and model evaluation, is publicly available at https://github.com/ai4pm/Bridging-Ancestry-Gaps-in-Genomic-Risk-Prediction-with-Tabular-Foundation-Models. The final instruction-tuned model (ICL-NS-G2P-proto) is also released in this repository. Detailed documentation is provided, including environment setup instructions and guidelines for running various parts. The instruction-tuning task datasets are available at https://zenodo.org/records/18309187.

Humans↗

PubMed2026

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

PubMed2026

Clinical Variability and Genotype-Driven Outcomes in CHRND-Related Congenital Myasthenic Syndrome.

BACKGROUND: Congenital myasthenic syndromes (CMS) caused by pathogenic variants in CHRND, encoding the δ-subunit of the nicotinic acetylcholine receptor (AChR), are rare, and data on genotype-phenotype correlations and long-term outcomes are limited. METHODS: We performed a retrospective, multicenter study of nine patients with genetically confirmed CHRND-related CMS from specialized neuromuscular centers. Clinical, electrophysiological, genetic, and therapeutic data were systematically collected. All diagnoses were established by exome sequencing during routine clinical work-up. RESULTS: Eight patients were compound heterozygous and one was homozygous for pathogenic CHRND variants, including nonsense, missense, splice-site variants, and one microdeletion. Disease onset ranged from the neonatal period (n = 7) to adolescence (n = 2). Three patients were followed longitudinally for 22-43 years. Ocular involvement, particularly ptosis and ophthalmoparesis, was present in all patients. Generalized fatigable weakness was common, whereas bulbar and respiratory involvement occurred in a subset and reflected overall disease severity. Genotypes including a null allele or a homozygous missense variant tended to be associated with more severe phenotypes, while compound heterozygous missense variants were linked to a broader and generally milder spectrum, sometimes limited to ocular symptoms. Long-term outcomes ranged from minimal symptoms under therapy to severe motor impairment with respiratory insufficiency, highlighting substantial interindividual variability. CONCLUSIONS: This study expands the phenotypic and genotypic spectrum of CHRND-related CMS and underscores the critical role of genotype in determining disease severity. Comprehensive genetic testing, longitudinal phenotyping, and genotype-informed management are essential for optimal diagnosis and care in this rare disorder.

Humans↗

PubMed2026

Epidermolysis Bullosa Classification and Current Approach to Diagnosis.

Epidermolysis bullosa (EB) is a heterogeneous group of rare genodermatoses marked by skin fragility and bullae formation induced by minor trauma. Pathologic variants in at least 21 genes are associated with EB, grouped into four major subtypes based predominantly on the plane of cleavage within the skin. EB simplex is characterized by epidermal bullae formation and is due to gene mutations that affect epidermal proteins, most commonly keratin filaments. Junctional EB is due to gene mutations affecting proteins in the basement membrane zone, causing a split within the lamina lucida of the dermal-epidermal junction. Dystrophic EB is characterized by subepidermal bullae formation and is due to mutations in the gene encoding type VII collagen, which makes up the anchoring fibrils in the papillary dermis. Kindler EB is the rarest subtype and may be associated with cleavage at various levels within the skin due to a mutation in the FERMT1 gene causing defects in kindlin-1, a protein associated with integrins and focal adhesions. Because EB is such a heterogeneous disease, an understanding of genotype-phenotype correlations is necessary to help guide management. Traditionally, the first step in diagnosis was inducing a blister that was biopsied for immunofluorescence mapping. Currently, the gold standard for diagnosis is a blood sample or buccal swab for extraction of genomic DNA via next-generation sequencing, which can identify the exact causative gene. A diagnosis of EB is life altering for patients and families alike. A firm understanding of EB classification and initial diagnostic workup can help dermatologists feel empowered to support and counsel families.

Humans↗

PubMed2026

Solid tumours in RASopathies: insights from a large monocentric cohort and systematic review of the literature.

BACKGROUND: Dysregulation of the RAS-mitogen-activated protein kinase signalling pathway underlies RASopathies, a family of neurodevelopmental disorders associated with variable cancer predisposition. However, the prevalence and spectrum of solid tumours and the contribution of specific variants to tumour susceptibility remain poorly defined. METHODS: We assessed solid tumour prevalence and spectrum in the largest single-centre cohort of individuals with RASopathies (n=138), excluding neurofibromatosis type 1 and integrated these findings with a systematic literature review to evaluate tumour distribution and genotype-phenotype correlations. RESULTS: In our cohort, at least one solid tumour was identified in 10.8% of individuals with Noonan syndrome (NS), 47.8% with Costello syndrome (CS) and 7.3% with cardiofaciocutaneous syndrome (CFCS). Malignant tumours occurred in 5.4%, 30.4% and 2.4%, respectively. CS showed the highest tumour burden, frequently with multiple primary tumours, predominantly of the bladder. In NS, low-grade central nervous system (CNS) tumours were most common, particularly among individuals carrying PTPN11 variants. Tumour onset occurred with a median age of 19, 14 and 13 years in NS, CS and CFCS, respectively. Literature data analysis identified candidate variants in HRAS, PTPN11 and SOS1 genes associated with increased risk for solid tumours, which differed from mutational hotspots reported in childhood leukaemia or sporadic cancers. CONCLUSION: Solid tumour risk in RASopathies is syndrome-dependent and genotype-dependent, with CS showing a high burden of bladder tumours and NS mainly associated with CNS tumours. These findings may support tailored surveillance strategies.

Human Genetics↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗

PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗

PubMed2026

A Novel Splice Variant in the COL1A1 Gene Leads to Exon 46 Skipping and Osteogenesis Imperfecta.

BACKGROUND: Osteogenesis imperfecta (OI) is a clinical and genetic disorder characterised by bone fragility, growth deficiency and skeletal deformity. Ninety per cent of OI cases are attributable to autosomal dominant variants in the COL1A1 and COL1A2 genes. METHODS: Candidate variants were identified and verified through trio whole-exome sequencing (trio-WES), copy number variation sequencing (CNV-seq) and Sanger sequencing. Minigene splicing assays were performed in HeLa and HEK293T cells with pcDNA3.1 and pcMINI-C vectors to investigate the function of the candidate variants. A systematic review of COL1A1 splicing variants and the corresponding genotype-phenotype spectrum was performed. RESULTS: Trio-WES revealed a novel heterozygous variant in the C-terminal region of the COL1A1 gene: NM_000088.4:c.3423+5G>A. Sanger sequencing confirmed the variant in both the proband (II-2) and her foetus (III-1) who were clinically suspected of having OI. The c.3423+5G>A variant causes complete skipping of Exon 46, as demonstrated by a minigene splicing assay. We retrieved 419 COL1A1 splicing variants from PubMed, excluded 15 without phenotypic data and 2 linked to Ehlers-Danlos syndrome and stratified the remaining 402 variants into three types on the basis of splice site location: (1) Variants at canonical splicing sites (77.8%, 313/402) mostly cause mild phenotypes, whereas a minority may be severe. (2) Intron variants in other locations, such as splice region variants (17.9%, 72/402), usually cause mild clinical phenotypes, and deep intronic splice variants (0.4%, 2/402) that may result in severe phenotypes. (3) Other variants (3.7%, 15/402), such as exon variants or fragment loss, are extremely rare. We also preliminarily discuss the mechanisms underlying phenotypic variability and the characteristics of C-terminal variants. CONCLUSIONS: This intron variant in COL1A1 was classified as likely pathogenic and was confirmed to disrupt COL1A1 expression. The summary analysis results also revealed a correlation among splicing variants, C-terminal region variants and disease, suggesting that variant location provides a useful framework for prognosis prediction.

Female↗

PubMed2026

Genomic determinants of fluoroquinolone resistance in Escherichia coli in Nigeria: dominance of QRDR mutations and limited contribution of PMQR in a cross-sectional study.

BACKGROUND: Fluoroquinolone-resistant Escherichia coli is a major global clinical threat, particularly in low- and middle-income countries like Nigeria. However, the full genomic landscape, including the relative contributions of chromosomal mutations, plasmid-mediated resistance, and the role of high-risk clones, remains poorly characterized in this setting. This study aimed to define the genomic mechanisms, clonal distribution, and genotype-phenotype relationships of fluoroquinolone resistance in clinical E. coli isolates from Nigeria. METHODS: A cross-sectional study of 107 clinical E. coli isolates was conducted. Phenotypic susceptibility to ciprofloxacin and nalidixic acid was determined using VITEK 2 and broth microdilution. Whole-genome sequencing was performed, and analysis included detection of quinolone resistance determining region (QRDR) mutations (gyrA, parC, parE) and plasmid-mediated quinolone resistance (PMQR) genes, multilocus sequence typing (MLST), and phylogenetic analysis. Statistical associations were evaluated using chi-squared tests or Fisher's exact tests. RESULTS: Ciprofloxacin non-susceptibility was high at 86.0%. Resistance was primarily driven by a conserved chromosomal mutation profile; the combination of gyrA S83L, gyrA D87N, and parC S80I was present in 85 isolates and was associated with ciprofloxacin non-susceptibility in all affected isolates in this cohort. Isolates with only gyrA mutations were resistant to nalidixic acid but susceptible to ciprofloxacin, consistent with a stepwise resistance pathway. In this cohort, the triple QRDR signature (gyrA S83L + gyrA D87N/Y + parC S80I) was a perfect positive predictor of ciprofloxacin non-susceptibility (85/85; 100%). The ST131 lineage dominated, accounting for 21.5% of isolates and universally carrying the complete triple QRDR profile; notably, no ST131 isolate carried a PMQR determinant. Plasmid-mediated quinolone resistance (PMQR) genes were detected in 15.0% of isolates but were not independently associated with ciprofloxacin non-susceptibility in this cohort in the absence of concomitant QRDR mutations. Efflux pump genes were ubiquitous and non-predictive. Notably, six isolates, all from urine, were non-susceptible (R/I) despite lacking all known QRDR and PMQR determinants, pointing to uncharacterized mechanisms. In a multivariable logistic regression model that included ST131 status, PMQR carriage, and parE mutation status, ST131 was associated with ciprofloxacin non-susceptibility (adjusted OR 5.96, 95% CI 1.21-29.4, p = 0.028), whereas PMQR carriage was not (adjusted OR 0.94, 95% CI 0.18-4.85, p = 0.94). The triple QRDR signature was not included in this model because it perfectly predicted ciprofloxacin non-susceptibility in this cohort. Resistance patterns varied by clinical source, with the highest burden in bloodstream and wound infections. This stepwise hierarchy from first-step gyrA mutations to the classic triple QRDR profile is summarised in the graphical abstract, Fig. 1. CONCLUSIONS: Fluoroquinolone resistance in Nigerian clinical E. coli is predominantly driven by chromosomal QRDR mutations within successful clones like ST131. PMQR genes and efflux pumps appeared to play a supplementary role rather than being independent drivers of ciprofloxacin resistance in this cohort. These data support prioritising key QRDR mutations in genomic reporting and local stewardship decisions, while the QRDR-negative resistant urine isolates require further investigation.

Escherichia coli↗

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↗