Human Mutation

Heterozygous FOXL2 (non-)coding sequence and structural variants (SVs) lead to blepharophimosis, ptosis and epicanthus inversus syndrome (BPES), a rare, autosomal dominant developmental disorder characterized by a completely penetrant eyelid malformation and incompletely penetrant primary ovarian insufficiency (POI). We collected variants from our in-house database, generated via clinical genetic testing and downstream research testing in the Center for Medical Genetics Ghent, Belgium (2001-2024), and via literature and other resources in the same period. All retrieved variants were categorized using ACMG/AMP classifications to increase the knowledge of pathogenicity. We collected 413 unique genetic defects of the FOXL2 region, including 76 novel variants, in 864 index patients. Of these, 87% of patients were identified with a coding FOXL2 sequence variant. The polyalanine tract is a known mutational hotspot of FOXL2, illustrated here by the high percentage of pathogenic polyalanine expansions (24%). Furthermore, the molecular spectrum in typical BPES index patients is characterized by 8% coding deletions and 3% deletions located up- and downstream of FOXL2. The remaining 2% carry translocations along with chromosomal rearrangements of 3q23. This uniform and structured reclassification, incorporating the largest dataset of variants implicated in FOXL2-associated disease so far, will improve both the diagnosis as well as genetic counselling for individuals with BPES.

Severe combined immunodeficiency (SCID) is a heterogeneous, recessive disorder, associated with the onset of severe, recurrent infections in the first few months of life. SCID is fatal if left untreated, but outcomes can be significantly improved by prompt diagnosis and treatment, particularly prior to onset of infection. Consequently, SCID is already included in many newborn screening programmes around the world, as well as multiple international genomic newborn screening (gNBS) research programmes. However, there is a vital need to estimate penetrance of SCID variants in population cohorts, to mitigate the potential consequences of reporting low penetrance variants in a genotype-first gNBS setting. This study aimed to assess the penetrance and prevalence of these variants in the UK Biobank population cohort. Whole genome sequencing data from 490,640 individuals was used to interrogate 16 SCID genes for potentially causal variation. We identified 4206 carriers of single heterozygous pathogenic variants ([~]1% of cohort), but only 6 individuals double heterozygous, homozygous or hemizygous for relevant pathogenic variants. 3 individuals would be expected to require further testing had they been identified by gNBS, suggesting that fewer than 1 in 100,000 newborns might require follow-up testing due to SCID variants. Following detailed variant curation, we were able to identify only 2 unabected individuals likely to be harbouring biallelic pathogenic variants, potentially indicative of reduced penetrance. Nonetheless, SCID remains an excellent candidate for inclusion in gNBS studies, due its severity, clinical actionability and expected low false positive rate, although care should be taken when reporting hypomorphic variants.

MotivationFanconi anemia (FA) is a rare disease mainly caused by biallelic pathogenic variants, including structural variants such as large deletions and insertions in FA genes. Currently, variant detection is based on short-read sequencing and probe-based approaches. However, determining the exact genomic breakpoint or achieving allelic discrimination remains challenging. Nanopore-based long-read sequencing enables a comprehensive detection of FA variants, but a unified bioinformatic analysis platform for these data is missing. ResultsWe present FA-NIVA (Fanconi anemia - Nanopore Indel and Variant Analysis), an automated and adaptable analysis workflow tailored for Nanopore-based long-read sequencing data in FA genetic analysis. FA-NIVA integrates state-of-the-art tools to comprehensively detect both single nucleotide variants (SNVs) and structural variants (SVs). Our analysis platform enhances genotyping accuracy for biallelic variants by a joint SNV-SV based phasing in FA associated genes. Built within the Nextflow ecosystem and powered by containerized Docker images, FA-NIVA ensures reproducibility, flexibility, scalability and transparency across different computing environments. Together, FA-NIVA provides a robust end-to-end solution for the automated analysis of SVs and SNVs and high-resolution phasing analysis in FA genes, enabling an accurate and efficient pipeline for genetic analysis. AvailabilityFA-NIVA is available on GitHub at: https://github.com/UKWgenommedizin/FA-NIVA.

PurposeWhile genomic testing is integral to pediatric inborn errors of immunity (IEI) care, few studies have examined strategies to support its optimal delivery. This study aimed to characterize a pediatric IEI cohort and assess the impact of implementing a mainstream model-of-care (MoC). Materials/MethodsComprehensive chart audit was conducted for patients ([&le;]18y) who received IEI genomic testing in Queensland, Australia, from 2017-2025. Descriptive analyses captured demographic and clinical characteristics, genomic testing and results, and management outcomes. Inferential analyses assessed changes in genomic practices pre-MoC (<2021) and post-MoC ([&ge;]2021). Results322 patients met eligibility criteria (n=481 genomic test). Diagnostic yield (27.6%) varied by testing indication, with the highest rate among phagocytic defects (n=4/4;100%) and severe combined immunodeficiency (n=8/10;80%). Very-early-onset inflammatory bowel disease had the lowest diagnostic yield (n=3/68;4.4%), prompting changes to testing criteria. Molecular diagnosis resulted in management changes for 90.5% patients. Genomic testing was widely used pre-MoC (n=251 genomic tests). All outcomes significantly improved pre-and post-MoC (p<0.05): duplicate testing decreased (13.9% to 0%); variants of uncertain significance reduced (37.7% to 7.1%); informed consent documentation increased (70.5% to 88.4%); and diagnostic yield increased (16.2% to 27.4%). ConclusionTargeted interventions are needed to support delivery of genomic testing and strengthen service effectiveness.

BackgroundExome sequencing (ES) has become a key diagnostic tool for rare diseases (RDs). However, most evidence on ES performance comes from high-income countries and patients from European ancestry. In countries such as Chile, limited access to next generation sequencing amplifies health disparities and highlights the need to identify which patients are most likely to benefit from ES. MethodsThis study presents the second phase of the Chilean DECIPHERD project, in which we performed ES in a new group of patients with RDs presenting with multiple congenital anomalies (MCA), neurodevelopmental disorders (NDD), and/or suspected inborn errors of immunity. To identify clinical and demographic factors associated with an increased probability of obtaining an informative ES result, we conducted a logistic regression analysis, combining the results of the first and second phases of the project. We also objectively evaluated global ancestry measured using ADMIXTURE, as a potential factor. ResultsSixty-seven patients participated in this second phase of DECIPHERD with a median age of 6 years (range: 0-27); 55.2% were female, with an average ({+/-} s.d.) proportion of Native American ancestry of 0.615 {+/-} 0.18. Clinically, 52.2% presented with both MCA and NDD, and the rest had other phenotype combinations. An informative result, including pathogenic or likely pathogenic variants in genes consistent with the patients phenotype, was identified in 34.3% of the cohort; 61% of these variants had not been previously reported in databases such as ClinVar. By combining the two phases of the study, we reached a total of 167 patients, in whom the presence of NDD and/or MCA significantly increased the probability of achieving an informative ES outcome. In contrast, previous use of gene panel testing was associated with a decreased likelihood of receiving an informative result. Ancestry was not associated with diagnostic yield. ConclusionsThis study demonstrates the utility of ES in achieving a diagnosis in a clinically diverse cohort of Chilean patients with RDs, and characterized features associated with a higher diagnostic yield. These findings may contribute to evidence-based patient prioritization strategies in settings with limited access to NGS resources.

Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive bone marrow failure, congenital malformations, and cancer predisposition. Early identification of individuals with FA is critical for timely clinical management, yet phenotype-driven approaches to FA identification are hindered by inconsistencies in existing phenotypic profiles. We compared the Human Phenotype Ontology (HPO) annotations for FA in OMIM (215 terms across 22 complementation group entries) and Orphanet (106 terms in a single entry, ORPHA:84), quantifying overlap and anatomical system coverage. To address identified gaps, we developed a comprehensive custom HPO profile by extracting phenotypic terms from the entire Fanconi Cancer Foundation (FCF) Clinical Care Guidelines using OntoGPT, an LLM-based ontology extraction tool, followed by manual curation to ensure accuracy and clinical relevance. OMIM and Orphanet shared only 36 HPO terms (12.6% of their combined 285 unique terms), demonstrating substantial discordance. Our custom profile comprises 264 unique HPO terms, of which 161 (61.0%) are novel and not present in either existing source. The novel terms expand coverage particularly in musculoskeletal (39 terms, 23.8%), genitourinary (26 terms, 15.9%), limb (26 terms, 15.9%), head or neck (20 terms 12.2%), and digestive system (17 terms, 10.4%) phenotypes. Community-curated phenotypic profiles derived from clinical practice guidelines can substantially augment existing disease annotations. Our FA profile, the most comprehensive HPO-based phenotypic characterization of FA to date, is publicly available and provides a foundation for improved clinical decision support and EHR-based computable phenotyping that can accelerate diagnosis for individuals with FA. Furthermore, the LLM-assisted approach offers generalizable methods to improve the diagnostic odyssey for all rare diseases.

STUDY QUESTION[Do structural genomic variants, that can be identified by using optical genome mapping, contribute to male infertility?] SUMMARY ANSWER[By using optical genome mapping we can identify several types of structural variants, both known and new, that may contribute to male infertility.] WHAT IS KNOWN ALREADY[Traditional approaches such as karyotyping, CFTR and chromosome Y microdeletion testing are successful in explaining clinical findings in [~]30% of MI patients, leaving the rest without a genetic diagnosis. Recent research suggests at least 265 genes may play a role in male fertility. While the assessment of the roles of copy number variants and single nucleotide variants in monogenic forms of disease in these genes is underway, much less is known about structural variants.] STUDY DESIGN, SIZE, DURATION[We performed a longitudinal case/control study on a total of 220 individuals; 88 patients with male infertility, negative for cytogenetic abnormalities using karyotyping, and molecular testing for chrY microdeletions, and CFTR gene variants, and 132 healthy male individuals that underwent optical genomic mapping for other reasons. Exclusion criteria for the control cohort were low-sperm quality and/or inclusion in IVF procedures. The study was approved by the National Medical Ethics Committee of the Republic of Slovenia (reference number: 0120-213/2022/6). Optical genome mapping was performed from an aliquot of whole blood collected for routine testing purposes at the Clinical Institute of Genomic Medicine (CIGM), UMC Ljubljana from January 2023 to November 2024.] PARTICIPANTS/MATERIALS, SETTING, METHODS[We examined structural variants in 220 participants by using optical genome mapping, which was performed with DLE-1 SP-G2 chemistry and the Saphyr instrument. The de novo assembly and Variant Annotation Pipeline were executed on Bionano Solve3.7_20221013_25 while reporting and direct visualization of structural variants was done on Bionano Access 1.7.2. All obtained variants were filtered using the Bionano Access software and in-house generated gene/regions of interest panel bed files. The first filter was applied to include variants below a population frequency of 10%, and overlapping the regions of interest. Subsequently, all variants occurring with frequency 0% in the internal manufacturer variant dataset were manually evaluated for possible involvement of the overlapping genes or regions in biological processes involved in MI. The male infertility cohort also underwent research whole exome analyses as previously reported. All results of optical genomic mapping were confirmed by an appropriate alternative method where available.] MAIN RESULTS AND THE ROLE OF CHANCE[We show that the overall number of structural variants in MI patients does not differ from that of healthy individuals. By looking in detail at genes and regions associated with MI, we identified 21 rare variants absent from controls in 25.0 % of MI patients, of which five were likely causative, and two would be missed by using traditional approaches. These variants include inversions, duplications, amplifications, deletions (e.g. SPAG1), and insertions/expansions (e.g. DMPK), that were validated using additional methods. While the remaining SV cannot be currently classified as pathogenic according to existing criteria, they open a new avenue in genetic research of MI. LARGE SCALE DATA[Variants reported in this study were deposited into ClinVar under accession numbers SUB15650956 (https://www.ncbi.nlm.nih.gov/clinvar/)] LIMITATIONS, REASONS FOR CAUTION[Technical limitations of optical genome mapping include the lack of DLE-1 labelling of centromeric and telomeric regions, the inability to detect Robertsonian translocations, the unclear exact location of smaller structural variants located between the DLE-1 labels, and unclear boundaries in case of their location in segmentally duplicated regions (this limitation is shared with other methods). The ACGM criteria of rarity are also hard to apply, as the fertility status of the individuals in healthy population databases such as GnomAD and DGV is unknown. Similarly, gene-associated phenotype and the proposed inheritance model both need to be considered as parts of the ACMG criteria, but for many candidate genes associated with MI, no model of inheritance has yet been proposed.] WIDER IMPLICATIONS OF THE FINDINGS[Currently, with the established diagnostic approaches we are able to resolve [~]30% of male infertility cases, with [~]70% of patients remaining undiagnosed. The significance of our work is in showing that rare structural variants can be identified in MI, by using optical genome mapping, opening new avenues of research of the genetics of this important contributor to human fertility.] STUDY FUNDING/COMPETING INTEREST(S)[All authors declare having no conflict of interest in regard to this research. This work was funded by the Slovenian Research and Innovation Agency (ARIS) Programme grant P3-0326: Gynecology and Reproduction: Genomics for personalized medicine] Lay summaryMale infertility affects about 5% of adult males and has complex causes, including genetic ones, such as mutations in the CFTR gene, small deletions on chromosome Y, and balanced translocations, but currently we can only find a genetic cause in [~]30% of patients. This means [~]70% of cases remain undiagnosed but potentially, they too may have a yet unknown genetic cause. Indeed, so far research has shown at least 265 genes have been proposed to play a role in male fertility. In these genes, there has so far been limited research of single nucleotide variants and of copy number variants, but many structural variants are not visible using commonly used methods in clinical genetic testing. Therefore, apart from chromosome Y microdeletions and chromosomal numerical and structural anomalies, such as balanced translocations, the role of smaller structural variants in male infertility is unknown, but based from what we know from other diseases, they also may play a role in male infertility. Optical genome mapping is a novel method for the detection of structural variants, such as balanced and unbalanced translocations, insertions, duplications, deletions, and complex structural rearrangements in a wide range of sizes. By using optical genome mapping to test a cohort of 88 infertile men and 132 healthy controls, we aimed to provide the first insights into the range of SV that may be associated with MI. We found, by using optical genome mapping, the overall number of structural variants in MI patients not to be significantly different to the control group. However, by looking at genes and regions associated with MI, we can find rare structural variants that are absent from controls in 25.0% of MI patients. These variants include inversions, duplications, amplifications, deletions (e.g. deletion in SPAG1), and insertions/expansions (e.g. in DMPK), that were validated using additional methods. Five of these variants (5.6%) were likely causative, and two would be missed by traditional approaches. While the remaining SV cannot be currently classified as pathogenic according to existing criteria, they open a new avenue in genetic research of MI.

IntroductionAdverse drug reactions (ADRs) remain a major public health issue, and genetic factors contribute importantly to interindividual variability in drug response. Pharmacogenetic testing helps reduce ADR risk by optimizing drug selection and dosage, particularly in monogenic disorders. Material and MethodsWhole-exome sequencing of 6,739 samples from the Russian population was performed using the MGIEasy Universal DNA Library Prep Set on the DNBSEQ-G400 platform (MGI). Variants in 48 genes were examined, focusing on inherited arrhythmias (Long QT syndrome, Short QT syndrome, Timothy syndrome, Andersen-Tawil syndrome, Brugada syndrome, Atrial fibrillation, Catecholaminergic polymorphic ventricular tachycardia), enzyme deficiencies (Glucose-6-Phosphate Dehydrogenase Deficiency [G6PDD], Porphyrias), Dravet Syndrome (DS) and Malignant Hyperthermia (MH). All identified variants had been reported at least once as pathogenic (P) or likely pathogenic (LP) in ClinVar, along with those occasionally classified as variants of uncertain significance (VUS). Each variant was manually re-evaluated according to ACMG criteria. ResultsA total of 75 unique variants in 18 genes were observed in 119 individuals (1.77%), including 21 carriers and 13 women with a G6PD mutation. Of these, 46 variants were classified as P, 21 as LP, and 8 as VUS. Missense variants accounted for the largest proportion (73.33%). The most affected genes were KCNQ1 (24/119), which exhibited the highest number of unique variants (18), G6PD (20/119), SCN1A (15/119), and RYR1 (14/119). Regarding associated conditions, mutations linked to arrhythmias were found in 51 individuals, MH in 27, G6PDD in 20, DS in 15, and Porphyrias in 6. ConclusionsIncorporating genetic information on both common and rare clinically actionable variants into therapeutic decision-making has the potential to improve medication safety, reduce preventable ADRs, and enhance the effectiveness of personalized pharmacotherapy.

RNA sequencing (RNA-seq) provides a powerful complement to DNA sequencing for uncovering pathogenic defects affecting gene expression and splicing in individuals with genetically undiagnosed rare disorders. However, as large rare disease consortia adopt RNA-seq, challenges arise due to cohort heterogeneity, variability in tissues and sample sizes, and differences in interpretation practices. Here, we present a harmonized analytical and interpretation framework developed by the pan-European Solve-RD consortium to address these challenges. We analyzed 521 RNA-seq samples from whole blood, fibroblasts, muscle and peripheral blood mononuclear cells collected across more than 30 clinics and five European Reference Networks. Aberrant expression and splicing events were identified using OUTRIDER and FRASER 2.0 and analysed through a standardized four-level scoring framework that encompassed RNA-seq outlier reliability, phenotype relevance, variant mechanism, and segregation evidence, captured in structured reports for interpretation. Regular meetings, and collaborative "Solvathon" workshops were used to evaluate variant pathogenicity. This effort resulted in molecular diagnoses for 19 families out of 248 (7.7%) for whom DNA analyses had been inconclusive. Furthermore, three cases diagnosed using DNA analyses were confirmed, and 49 candidate events and five novel candidate disease genes were identified in the remaining families. Our results demonstrate the feasibility and impact of large-scale, standardized RNA-seq analysis in a transnational research setting. This framework provides a model for other international initiatives such as the Undiagnosed Diseases Network and ERDERA, paving the way for broader clinical implementation of transcriptome-based rare disease diagnostics.

PurposeFuchs endothelial corneal dystrophy (FECD) is a common corneal disease and a leading indication for endothelial keratoplasty (EK). Although CTG18.1 repeat expansion is a major genetic risk factor, the contribution of polygenic background to disease progression remains unclear. We evaluated whether combining CTG18.1 expansion status with a FECD-specific polygenic risk score (PRS) enables genomic prediction of progression to EK. MethodsWe retrospectively analysed 589 individuals with FECD from two European centers, with replication in an independent cohort of 185 individuals. Association of CTG18.1 expansion ([&ge;]50 repeats) and PRS with time to EK were evaluated using Cox models adjusted for sex and ancestry. ResultsExpansion-positive status was associated with earlier EK (HR 2.30; 95% CI 1.62- 3.26; P<.001). Addition of PRS improved prediction (C-index 0.614 vs 0.602; P=.014). Each 1-SD increase in PRS was associated with earlier EK (HR 1.16; 95% CI 1.03-1.30; P=.015), with replication in the validation cohort (HR 1.42; 95% CI 1.15-1.75; P=.001). ConclusionIntegration of monogenic and polygenic risk enables genomic prediction of FECD progression, supporting clinical genomic risk stratification to inform individualized monitoring and timing of intervention.

BackgroundMitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA-based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis. RNA sequencing (RNA-seq) provides a complementary layer of evidence by revealing functional consequences of genetic variation, thereby improving diagnostic yield. MethodsWe performed RNA-seq on skin fibroblasts from 140 pediatric patients with suspected mitochondrial disease who remained genetically undiagnosed after whole exome sequencing (WES). Aberrant RNA expression and splicing were identified using the detection of RNA outliers pipeline (DROP). Based on WES findings, patients were stratified into a candidate group (n=28), in which RNA-seq evaluated the pathogenicity of WES-identified variants of uncertain significance and an unsolved group (n=112), in which RNA-seq was used to pinpoint candidate genes. In six cases where RNA-seq identified the aberrant RNA-event but WES did not detect the causative variants, whole genome sequencing (WGS) was performed. ResultsIntegrative RNA-seq, WES, and WGS analysis resulted in a genetic diagnosis in 25% of patients overall (20/28 [71%] in the candidate group; 15/112 [13%] in the unsolved group). Aberrant splicing explained most candidate-group diagnoses, including variants misclassified by in silico predictors such as SpliceAI. Fourteen percent of protein-truncating variants predicted to undergo nonsense-mediated decay (NMD) escaped degradation, highlighting the functional limits of current predictions. The variants identified in the unsolved cohort included synonymous, missense, deep intronic, near-splice-site variants, and large deletions. The most frequent amongst them was a recurrent synonymous East Asian founder mutation in ECHS1, accounting for seven cases. Interestingly, across 231 pathogenic variants associated with aberrant RNA phenotypes compiled from this study and prior reports, half were non-coding and half were coding variants. ConclusionRNA-seq substantially enhances molecular diagnosis in mitochondrial disease by exposing cryptic splicing, regulatory, and NMD-escape events invisible to DNA sequencing alone. These data advocate transcriptome analysis as an essential component of comprehensive genomic diagnostics in neuro-metabolic disease. Significance StatementMitochondrial diseases remain among the most challenging inherited metabolic disorders to diagnose, with nearly half of patients unresolved despite advanced DNA sequencing. By integrating transcriptome profiling into the diagnostic workflow, this study demonstrates that RNA sequencing can reveal pathogenic mechanisms invisible to exome or genome analysis, including cryptic splicing, regulatory variants, and transcripts that escape nonsense-mediated decay. The findings establish RNA-seq as a decisive bridge between genotype and phenotype, uncovering functional consequences of genetic variation and redefining molecular diagnostics for mitochondrial and other neuro-metabolic diseases.

BackgroundKlebsiella pneumoniae is a common cause of neonatal sepsis in Africa, and is frequently hospital acquired. We recently reported an outbreak of multidrug-resistant K. pneumoniae sepsis amongst neonates at a rural hospital in The Gambia, West Africa, involving 57 cases and case fatality of 60%. Here we undertook a retrospective pathogen genomic epidemiology study of clinical and environmental K. pneumoniae isolated during the outbreak, to identify the outbreak strain, refine the epidemic curve, confirm the environmental sources of contamination, monitor control of the outbreak, and characterise the outbreak strain in the context of the local and global pathogen population. Methods and FindingsWe sequenced all blood culture isolates identified as K. pneumoniae from patients aged 0-59 months (n=51 available, 77% from neonates), together with K. pneumoniae cultured from environmental samples during the outbreak investigation (n=16), and 56 stored blood culture surveillance isolates available from the previous decade (34 from neonates). Sequencing was performed using Oxford Nanopore Technologies (ONT) Mk10 flowcells and a PromethION instrument, yielding mostly complete genomes (79%). Genomic analysis revealed 23% of isolates were K. quasipneumoniae and identified the outbreak strain as K. pneumoniae ST39 with capsular (K) locus KL62. This strain was responsible for 29 cases (16 fatalities) and was identified in three samples of intravenous fluids collected from the neonatal ward during the investigation. It harboured a [~]187 kbp IncF plasmid carrying the extended-spectrum beta-lactamase (ESBL) gene blaCTX-M-15 and aac(3)-IId, encoding resistance to third-generation cephalosporins and gentamicin, respectively. The outbreak strain was not identified amongst historical surveillance isolates, and it was distinct from a KL23-ST39 strain responsible for an earlier outbreak at the Sir Edward Francis Small Teaching Hospital in Banjul, the countrys capital 7 years prior. Comparing the outbreak strain with publicly available genome data for ST39 and its associated sublineage (SL) 39, we observed SL39 has diversified into three common clonal groups, each associated with multiple K types, that have spread across Africa, Asia and Europe and have been associated with outbreaks of neonatal sepsis in Africa and elsewhere. We find SL39 is typically multidrug resistant, however the specific ESBL and carbapenemase genes vary by geographic location. ConclusionsPathogen whole-genome sequencing refined our understanding of the outbreak, allowing more precise identification to refine case numbers and case fatality calculations, and for precise identification of multi-use intravenous fluid bags as the source of the outbreak despite other samples being culture-positive for unrelated K. pneumoniae. This highlights the importance of infection prevention and control in reducing neonatal fatalities in low-resource settings, and the critical risk associated with multi-use reagents and equipment when caring for vulnerable neonates. The genomic analysis enabled us to identify and characterise the outbreak strain at high resolution, and together with global data highlights SL39 as an emerging high-risk multidrug-resistant, globally distributed clone of K. pneumoniae, capable of sustained transmission and high fatality.

IntroductionFibrosis can affect organs throughout the body and is present in a wide range of diseases. Recent research has suggested that there could be shared biological mechanisms that lead to fibrosis in different organs. MethodsWe performed genome-wide association studies using UK Biobank for fibrosis in 12 different organ-systems and meta-analysed results with previously published studies of fibrotic diseases. We considered genetic associations that colocalised across [&ge;]3 organs as those likely to be involved in general fibrotic mechanisms and also identified novel genetic variants not previously reported as associated with fibrosis. Genetic correlation of fibrosis between organs was calculated using linkage disequilibrium score regression (LDSC). Discovery analyses were performed using European ancestry individuals and results were tested further in African, South Asian and East Asian ancestry groups. ResultsWe identified eight genetic loci that colocalised across three or more organs. One of these signals, located near the SH2B3 and ATXN2 genes, showed evidence of a shared causal variant for fibrosis across five organs. We also identified two novel fibrotic associations, one implicating alternative splicing of TFCP2L1 for urinary fibrosis and another implicating a missense variant in FAM180A for intestinal-pancreatic fibrosis. We observed significant genetic correlations for all organs, particularly for liver and skeletal fibrosis. ConclusionWe found evidence of shared genetic associations for fibrosis across organs, both at individual genetic loci and genome-wide. This highlights specific genes that may contribute to fibrosis across organs and diseases, which may facilitate the development of new therapies.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) bases its drug-gene recommendations on the assignment of star alleles, which map known genotypes to defined functional categories and corresponding drug dosage guidelines. The star allele framework, first proposed in 1996 for the CYP gene family and later formalized with CPICs establishment in 2010 [1, 2], remains foundational to pharmacogenomics. However, this system has notable limitations. Its dependence on a restricted set of benchmark single nucleotide polymorphisms (SNPs) excludes rare or novel pathogenic variants that can invalidate a star allele call and lead to incorrect dosing recommendations. Furthermore, nearby non-pathogenic variants can interfere with haplotype interpretation, introducing additional risk of misclassification. To address these gaps, we developed PHARMWATCH, a multistep pharmacogenomics workflow for comprehensive variant analysis, allele tracking, and contextual interpretation. PHARMWATCH incorporates two algorithmic safeguards designed to identify genomic alterations that compromise star allele accuracy: (1) de novo germline variant screening using the ACMG-based BIAS-2015 classifier and (2) variant interpretation in context (VIIC) to validate the functional integrity of star allele-defining SNPs [3]. Together, these layers enhance the reliability of pharmacogenomic reporting, enabling safe, automated, and review-ready recommendations that extend beyond the constraints of traditional star allele-based approaches.

ObjectivesTo screen the entire genome for genes associated with risk for lateral epicondylopathy and improve understanding of underlying biological mechanisms and inform future research aimed at risk stratification and personalized prevention and treatment strategies. MethodsA genome-wide association study was conducted using UK Biobank data. Lateral epicondylopathy cases were identified based on electronic health records from individuals of European ancestry. Logistic regression tested associations between single-nucleotide polymorphisms and disease status, adjusting for sex, age, height, weight and ancestry principal components. Previously-identified candidate genes from the literature were also tested for association with lateral epicondylopathy. ResultsAmong 20,390 cases of lateral epicondylopathy, two loci reached genome-wide significance: one comprising 144 linked SNPs and one single SNP. The first locus, led by rs13127477 (p=7.7x10-12; OR 0.93, 95% CI 0.91 to 0.95), is located near three SIBLING genes (IBSP, MEPE and SPP1) involved in extracellular matrix remodelling at fibrocartilaginous entheses. The risk allele was associated with increased SIBLING gene expression, suggesting that excessive entheseal matrix remodelling contributes to disease susceptibility. The second locus was defined by rs138254824 (p=3.69x10-8; OR 3.42, 95% CI 2.23 to 5.25) near NEDD9 and TMEM170B. Previously reported collagen gene associations were not replicated. ConclusionIn the first genome-wide screen for lateral epicondylopathy, two loci were identified. These loci provide insight regarding the pathophysiology of lateral epicondylopathy and a roadmap for preventing and treating this injury with personalized medicine. Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSLateral epicondylopathy is a common and disabling overuse tendon condition, yet its genetic basis has remained poorly characterised, with prior studies limited to small candidate gene analyses. What this study addsThis study provides the first genome-wide association analysis of lateral epicondylopathy, identifying two risk loci on chromosomes 4 and 6 and implicating SIBLING genes (IBSP, MEPE, and SPP1) involved in entheseal extracellular matrix remodelling. How this study might affect research, practice or policyThese findings offer new biological insight into disease susceptibility and challenge previously reported collagen gene associations.

BackgroundNewborn screening (NBS) has progressively expanded through technological innovations, from tandem mass spectrometry enabling expanded NBS (eNBS) to the prospect of genomic NBS (gNBS). While these developments promise earlier diagnosis and richer information, they also raise concerns regarding actionability, uncertainty, equity and psychosocial impact. As technological feasibility alone does not ensure public confidence, parental perspectives are central to evaluating future expansions. Using acceptability concept as an anticipatory lens, this study assessed parental views on NBS expansion in France, examining its determinants, distinguishing test modalities, and exploring whether genomics raises specific concerns. MethodsA nationwide cross-sectional survey (September 2022-February 2023) included 1,640 parents recruited postpartum in maternity wards and through an online quota panel. Acceptability of eNBS and gNBS, intermediate evaluative components, and sociodemographic characteristics were assessed. Analyses combined descriptive statistics, multivariable regression, and thematic analysis of free-text comments. ResultsSupport was very high for eNBS (93%) and remained high for gNBS (89%), with genetics mainly shifting responses from complete to partial acceptability. Affective attitude and perceived effectiveness were the strongest predictors of both outcomes, while ethical concerns distinguished assured from conditional support. Most parents prioritised minimising uncertain results, whereas a smaller subgroup accepted greater ambiguity. Foreign-born and single parents reported lower levels of complete acceptability, while health-sector workers and parents with rare-disease experience were more supportive. No independent association with the age of the youngest child was observed. ConclusionParental acceptability of eNBS and gNBS is high but nuanced, shaped primarily by anticipated health benefits, emotional orientation and tolerance for uncertainty, with trust and social distance modulating support. As genomic expansion progresses, implementation will require proportionate, culturally adapted information and clear governance, and should be informed by real-world evidence from pilots such as PERIGENOMED. Trial registrationClinicalTrials.gov, NCT06111456. Last verified: October 2023.

PurposeGenetic diseases often present and are first diagnosed in the neonatal intensive care unit (NICU). Accurate identification of neonates with genetic diagnoses (GDs) in electronic health records (EHR) would enable a more complete understanding of their phenotypic spectrum, advancing care and personalized medicine. Prior research has used International Classification of Diseases (ICD) billing codes as proxies for GDs, though their accuracy for detecting confirmed GDs is uncertain. We evaluate the ICD codes for neonates with confirmed GDs and compare ICD billing code patterns between neonates with and without GD in two independent NICU cohorts. MethodsRetrospective analysis of patients admitted to the Boston Childrens Hospital (BCH) level IV NICU (1,344 neonates) and Nationwide Childrens Hospital (NCH)s neonatal network (33,315 neonates, mixed Level III/IV). For both cohorts, GDs captured by phecodes, aggregates of ICD codes, were compared with confirmed GDs. Two separate phenome-wide association studies (PheWAS) compared phecode patterns between neonates with GDs and those without, adjusting for sex, age at admission, gestational age, and NICU length of stay. ResultsGenetic phecodes were able to correctly identify 43.5% of neonates that received a GD in the BCH or NCH NICUs. Among 719 individuals with two or more genetic phecodes at BCH or NCH, 566 (78.72%) had a true GD. The BCH PheWAS analysis revealed a statistically significant positive association with atrioventricular septal defects and a negative association with bronchopulmonary dysplasia. The NCH pheWAS revealed 179 significantly associated phecodes, including many congenital anomalies. ConclusionThe use of ICD codes to identify NICU infants with GDs is neither sensitive nor accurate, though phecode analysis demonstrated stronger accuracy than sensitivity. Our data highlight clinical features of NICU infants more commonly seen in those that receive a GD (congenital heart defects) and those that are not (BPD). Our results can help to better predict and identify NICU neonates that receive a GD.

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from PharmGKB (levels of evidence 1A-2B), CPIC, and PharmVar. Additionally, WES limitations and the feasibility of imputing non-coding pharmacogenetic variants were evaluated. ResultsPopulation frequencies of alleles and metabolic phenotypes were determined for 13 Very Important Pharmacogenes (VIPs), along with the distribution of HLA class I and II alleles. The highest allelic and phenotypic variability was observed in CYP family genes, particularly CYP2D6, CYP2C19, and CYP2B6. A total of 663 pharmacogenomic annotations were identified, predominantly related to drug metabolism (50.38%) and toxicity (29.56%), including psychotropic agents, anticoagulants, statins, opioid analgesics, antineoplastic agents, and immunosuppressants. At least 32 drugs require pharmacogenetic testing based on variants located in non-coding regions, as well as accurate CYP2D6 copy number determination. Linkage disequilibrium analysis demonstrated the inability to reliably impute most non-coding pharmacogenetic variants from WES data. ConclusionThese findings represent one of the largest reference assessments to date of pharmacogenetically significant variant and HLA allele frequencies in the Russian population. The results confirm the utility of WES for population pharmacogenomic screening while simultaneously highlighting its fundamental limitations and the need for alternative genetic diagnostic methods in selected cases.

BackgroundGenetic risk scores (GRS) for type 1 diabetes (T1D) have been developed primarily in European populations, limiting their generalisability across ancestries. Indians differ from Europeans in clinical characteristics of T1D and overall genetic architecture, yet systematic evaluation of T1D GRS performance in multi-regional Indian cohorts is lacking. MethodsThe study included 597 T1D patients and 3347 non-diabetic controls from different regions in India. Genotyping, imputation, quality control analysis, and construction of the 67-SNPs T1D GRS were performed using standardised pipelines. Discriminative performance was assessed using Receiver Operative Curve-Area under Curve (ROC-AUC) analysis, and optimal thresholds were derived using Youdens index. HLA-DQ diplotype frequencies were compared, and association analysis was conducted using multivariable logistic regression. FindingsT1D GRS showed consistent discriminative performance across Indian cohorts [ROC-AUC=0.84 (range=0{middle dot}78-0{middle dot}87)], supporting its comprehensive use for T1D classification in India. Notably, its performance was lower in islet cell autoantibody (IA) negative compared with IA positive T1D patients (ROC-AUC, 0{middle dot}75 vs 0{middle dot}85) and in adult-onset than in childhood-onset patients (0{middle dot}74 vs 0{middle dot}84). We observed a lower frequency of protective HLA-DQ diplotypes and a strong association of HLA-DQ81 containing diplotypes in childhood-onset T1D. Application of an India-specific T1D GRS score improved the sensitivity than the European cut-off. InterpretationT1D GRS is a valuable unified diagnostic tool in Indians, but its performance varies by islet cell autoantibody status and age at onset, likely reflecting population-specific HLA architecture. European-derived T1D GRS thresholds under-classify the genetic risk, highlighting the importance of ancestry-aware optimisation in Indians. FundingCDRC grant CDRC202111026 and CSIR Intramural Grant P50. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown that a 67-SNPs T1D genetic risk score (GRS) can distinguish T1D patients from non-diabetic controls and other forms of diabetes, but its performance varies across ancestries. Islet cell autoantibodies (IA) have important diagnostic value for classifying type 1 diabetes (T1D). However, their prevalence in India varies widely, with up to one-quarter of patients testing negative, limiting their clinical utility. Evidence supporting the use of the T1D GRS in India, combined with IA antibodies status is limited to a single cohort representing one linguistic group. The applicability of T1D GRS across multi-centric clinical settings has not been systematically evaluated. Added value of this studyThis study validates the 67-SNPs T1D GRS across multiple Indian cohorts representing major linguistic groups, supporting its use as a unified diagnostic tool. Differences in T1DGRS performance between childhood-and adult-onset T1D are linked to enrichment of protective HLA-DQ diplotypes in adult-onset disease, providing genetic insight into disease heterogeneity. The study also demonstrates that European-derived GRS thresholds systematically under-classify genetic risk in Indians and the population-specific threshold is essential. Implications of all the available evidenceThe European-derived T1D GRS can be applied across Indian clinical settings with consistent discriminative performance. However, its utility is influenced by islet cell autoantibody status and the age at onset of disease. Ancestry-aware threshold optimisation substantially improves diagnostic accuracy and is essential for equitable implementation of T1D GRS in Indians. Larger studies are needed to identify population-specific risk variants and further refine genetic tools for clinical diagnosis.

Rhabdomyolysis is the acute breakdown of skeletal muscle resulting from failure of cellular homeostasis in response to metabolic stress. Recurrent forms are frequently linked to inherited defects affecting energy metabolism or calcium handling. Ryanodine receptor type 3 (RyR3) is an intracellular calcium release channel, expressed in skeletal muscle, that contributes to the fine-tuning of calcium signaling. Although variants in other calcium-handling proteins have been implicated in rhabdomyolysis, the role of RyR3 has not been established. In this study, we report rare compound heterozygous missense variants in RYR3 identified in two unrelated individuals with severe, fever-triggered recurrent rhabdomyolysis. Muscle biopsies revealed mild structural changes with triadic disorganization, mitochondrial alterations, lipid accumulation, and autophagic material, while overall muscle architecture was largely preserved. Structural modeling supports the pathogenicity of the variants, and calcium flux analysis demonstrated significantly reduced ryanodine receptor-mediated calcium release in patient-derived myoblasts. Functional analyses showed that RyR3 deficiency impaired starvation-induced autophagy, characterized by defective autophagosome formation and reduced autophagic flux, and increased susceptibility to metabolic stress. Mitochondrial bioenergetic profiling revealed reduced oxidative phosphorylation capacity and decreased membrane potential under stress conditions, consistent with compromised mitochondrial adaptation. In zebrafish, ryr3 knockdown resulted in structural and functional muscle abnormalities, including reduced myotome area and decreased locomotor activity, associated with impaired autophagic flux. This study establishes a novel association between recessive RYR3 variants and recurrent rhabdomyolysis and identifies RyR3 as a critical regulator of skeletal muscle stress adaptation through calcium-dependent control of autophagy and mitochondrial homeostasis. More broadly, our findings further highlight autophagy as a central determinant of muscle resilience in the context of rhabdomyolysis.