European Journal of Human Genetics

Background As part of Singapore's effort towards precision medicine tailored to Asian diversity, we describe the implementation of a nationwide reproductive carrier screening program. Using a customised 112-gene panel, incorporating population-specific recessive genetic diseases, we outline the overall program design, and initial efforts of community and stakeholder engagement, to inform culturally appropriate implementation. Methods Participants receive culturally tailored online education regarding our reproductive screening program and are provided results with genetic counselling and reproductive options. Community and stakeholder perspectives were assessed through questionnaires and consultations with religious leaders. Results Recruitment is nation-wide, and since initiation of our pilot phase in September 2024, 1,619 couples have registered interest, with 60% uptake of those deemed eligible. Among the 456 couples that have received results to date, four couples (0.9%) were identified to be at increased risk. Community questionnaire responses (n=1002), involving couples who participated in the program as well as the general public, indicated interest is high (59%) across the cohort but awareness, intent to participate and implications for reproductive options differed by sociodemographic factors such as ancestry and religion. Healthcare professional respondents (n=113) acknowledged carrier screening will be routine in medical care, but report limited confidence and resources. Engagement with religious leaders indicated support for the program. Conclusion These early program outcomes and community engagement are guiding the implementation of expanding population-based carrier screening in Singapore, contingent on addressing practical challenges through equitable outreach and professional training.

Genotype-phenotype databases are essential for variant interpretation and disease gene discovery. Genetic variation differs among human populations, mainly in allele frequencies and haplotype patterns shaped by ancestry and demographic history. Population-specific genotypes can influence traits and disease risk; this makes population specific characterization important. Most existing resources focus on the characterization of a population's genetic background, but do not represent the resulting phenotypes. We have developed PAVS (Phenotype-Associated Variants in Saudi Arabia), a curated, publicly accessible database that integrates 5,132 Saudi clinical cases from four Saudi cohorts and 522 cases from analysis of a mixed-population cohort, together with 1,856 cases from the Deciphering Developmental Disorders study (DDD) and 9,588 literature phenopackets. Each case record describes patient-level phenotypes, encoded with the Human Phenotype Ontology (HPO), and links them to genomic variants, gene identifiers, zygosity, pathogenicity classifications, and disease diagnoses mapped to standardized disease terminologies. The data is represented in Phenopackets format and as a knowledge graph in RDF. Additionally, a web interface provides phenotype-based similarity search, gene and variant browsers, and an HPO hierarchy explorer. We evaluate the utility of the phenotype annotations for gene prioritization using semantic similarity. While there are clear differences to global literature-curated databases, phenotypes in PAVS can successfully rank the correct gene at high rank (ROCAUC: 0.89). PAVS addresses a gap in population-specific genotype-phenotype resources and provides a benchmark for phenotype-driven variant prioritization in under-represented populations.

Background: Mainstreaming genetic testing has emerged as a strategy to improve access and reduce wait times for patients who may benefit from genetic testing. Ensuring patients fully grasp the implications of testing when formal genetic counselling is not provided, remains a focus for ongoing research. Methods: Patients diagnosed with hypertrophic or dilated cardiomyopathy were offered genetic testing between September 2024 and September 2025 through either the mainstreaming model conducted in cardiology clinics or a referral to Medical Genetics where patients attended an online webinar or a one-on-one genetic counselling appointment. Uptake of testing, time to testing, informed choice and patient satisfaction were evaluated. Results: Among patients offered genetic testing, uptake was higher in the mainstreaming pathway (82%) compared with a referral to Medical Genetics (69%). The difference in access was predominately due to patients not following through with their Genetics referral. Mainstreaming reduced wait times where patients referred to Genetics waited a median of 94-185 additional days to be offered genetic testing. Despite improved access, only 62% of mainstreamed patients were considered informed, compared to 91% of patients that attended a patient webinar through Medical Genetics (p < 0.01). Satisfaction with decision-making was high across both pathways. Conclusion: Integrating genetic testing into cardiology practices increased access and reduced wait times; however, patients demonstrated significantly lower rates of informed decision making compared to those who attended a patient webinar offered through Medical Genetics. These findings highlight the importance of structured education to support informed decision making within mainstreaming pathways.

Introduction: Accurate estimation of disease prevalence is crucial for public health and therapeutic development, but traditional methods are often inaccurate. Genetic prevalence, which estimates the proportion of a population with a causal genotype, using allele frequencies from population data, offers an important alternative. Methods: We partnered with 18 Rare As One patient organizations to estimate genetic prevalence for 22 autosomal recessive conditions using population data from two releases of the Genome Aggregation Database (gnomAD). To standardize and democratize these analyses, we developed the Genetic Prevalence Estimator (GeniE), a publicly available tool, for accessible calculations. Results: Conservative carrier frequencies in gnomAD v4.1 ranged from 1/164 to 1/11,888. The median change in genetic prevalence frequency between v2.1 to v4.1 was 0.806. Partnership with patient advocacy groups provided critical real-world context that refined the interpretation of these estimates. Discussion: These findings highlight that genetic prevalence is not a static figure but a dynamic, evolving measure with important caveats that need to be considered. Our study underscores the necessity of re-evaluations as databases expand. By integrating patient-partnered insights with the GeniE platform, we empower the genomics community to maintain transparent, up-to-date, and actionable data for rare disease advocacy and drug development.

Objective The decline of the perinatal demise rate is slowing and demises are often unexplained. Significant research has been done regarding diagnostic yield and genetic causes of demise, but little is known about how Geneticist involvement impacts outcomes. The goal of the study was to evaluate post-mortem genetic testing practices and effects of the geneticists involvement. Methods Retrospective data from 111 perinatal demise cases was examined, including rates of prenatal genetic counseling, post-delivery genetics consult, genetic testing, and autopsy investigation. Results In this cohort 54% received genetic testing and 25% received a genetics consult. When compared to those without, cases with genetic specialist involvement were associated with significant increases in testing uptake (p=0.007), diagnostic yield (p<0.001), and patient education (p<0.001). Second trimester stillbirths and those with fewer ultrasound (US) abnormalities were less likely to receive genetic testing (both p values <0.001) and consults (p<0.001, p=0.020). Conclusion Though it was not possible to avoid ascertainment bias, this data demonstrates that geneticist involvement correlates with a higher rate of testing, greater diagnostic yield, and more thorough counseling. These findings underscore the importance of integrating genetics providers into perinatal postmortem healthcare teams.

Abstract Background Spontaneous coronary artery dissection (SCAD) is a well-recognised cause of acute coronary syndrome particularly among women without conventional cardiovascular risk factors. Increasing evidence indicates a genetic contribution; however, the underlying genetic architecture of SCAD remains insufficiently understood. Objective The aim of this study was to assess the prevalence of rare variants in previously reported SCAD associated genes and to explore the potential presence of novel genetic alterations in well-characterised Swedish patients with SCAD. Methods The study comprised 201 patients enrolled in SweSCAD, a national project examining the clinical characteristics, aetiology, and outcomes of SCAD. All individuals had a confirmed diagnosis based on invasive coronary angiography. Comprehensive exome sequencing was performed to identify rare variants contributing to disease susceptibility. Results Genetic variants that have been associated with SCAD according to current clinical genetics practice for variant reporting were identified in approximately 4 % of patients. In addition, rare potentially relevant variants were detected in almost 60 % of patients in genes associated with vascular integrity and vascular remodelling. Conclusion This study supports SCAD as a genetically complex arteriopathy, driven by rare high?impact variants together with broader polygenic susceptibility. Variants in collagen, vascular extracellular matrix, and oestrogen?responsive pathways provide biologically plausible links to female?predominant disease. Although the diagnostic yield of clearly actionable variants is modest, these findings support broader genomic evaluation beyond overt syndromic presentations and highlight the need for larger integrative genomic and functional studies to refine risk stratification and management.

Introduction Lung cancer is rare before age 45, and its inherited genetic basis remains poorly defined. Methods We performed whole-genome sequencing in 171 predominantly young-onset lung cancer patients and integrated these data with whole-exome sequencing from six major lung cancer consortia, yielding 9,065 patients. After quality control, analyses focused on 6,545 individuals of European ancestry, the largest ancestral group. We compared the prevalence of rare pathogenic and likely pathogenic (P/LP) germline variants between 186 young-onset (age <45 years) and 6,359 older patients at gene and gene-set levels using Fisher's exact test, stratified by histology, sex, and smoking status. Polygenic risk scores (PRS) derived from common variants were also evaluated. Results Young-onset patients carried a higher burden of rare germline P/LP variants in DNA damage response (DDR) genes (including BRIP1, ERCC6, MSH5), and in cilia-related genes, notably GPR161. At the pathway level, DDR genes were significantly enriched (OR=1.66, p=0.007), with the strongest signal in the Fanconi Anemia pathway and among females (OR=1.96, p=0.01). Enrichment was also observed in inborn errors of immunity pathways, with strongest signals in antibody deficiency and the complement system genes. Young-onset patients additionally exhibited higher lung cancer PRS. Conclusion Young-onset lung cancer exhibits a distinct germline genetic architecture, characterized by enrichment of rare P/LP variants in DDR, cilia-related, and immune pathways, and an elevated lung cancer PRS. These findings support a greater role for inherited susceptibility in early-onset disease and have implications for risk stratification, earlier screening, and precision prevention.

Loeys-Dietz syndrome (LDS) is an autosomal dominant connective-tissue disorder caused by genetic variants in TGF-{beta} pathway genes, most often TGFBR1/2. While pathogenic TGFBR2 genetic mutations usually cluster in the kinase domain and disrupt SMAD signalling, distinguishing with confidence those with functional impact on TGFBR2 function from rare benign genetic alterations represents one of the most important ongoing challenges for accurate genetic testing. Therefore, there is a pressing need to develop methods that can improve functional variant interpretation. Here, we describe and characterize the functional impact of a novel genetic variant in the TGFBR2 kinase domain (E431K), in a patient with the clinical diagnosis of syndromic genetic aortopathy. We assessed the structural and functional consequences of this variant using AI-driven molecular modelling and in vitro cell-based assays. A high-quality homology-based model of TGFBR2 was generated and computational mutagenesis based on the structural context and evolutionary conservation was used to forecast variant pathogenicity. Relative to wild type, the variant affects protein stability by disrupting intramolecular interactions and likely induces conformational changes that may affect kinase activity and thus TGF-{beta} signalling. This was experimentally confirmed by showing abnormal protein level and alteration of canonical TGF-{beta} pathway activation. Overall, our results establish that the E431K variant leads to aberrant TGF-{beta} signalling and confirm the diagnosis of Loeys-Dietz syndrome type 2 in this patient.

While pregnancy intentions are increasingly recognised as complex and dynamic, unexpected pregnancies are often studied cross-sectionally, and a life course perspective is lacking. This study aimed to explore the salient themes and patterns in 1) the life course trajectories of individuals experiencing an unexpected pregnancy and 2) the transition surrounding an unexpected pregnancy. We conducted semi-structured qualitative interviews with 22 individuals (15 women and 7 men) experiencing unexpected pregnancies. Two interviews were held: during pregnancy and six months after childbirth. The respondents' life course trajectories were mapped using visual timelines and the transition was explored using Schlossberg's transition theory. Interviews were thematically analysed in an iterative process: applying open coding to three interviews followed by thematic coding and comparison of themes within and across life course trajectories. Life course trajectories varied considerably, distinguished by the absence or presence of critical life events, with patterns characterised by clustering life events within the domains of family, mental health or frequent residential mobility. The transition process of unexpected pregnancy was characterised by three patterns of adjustment - shift (instant adjustment), spark (triggered adjustment) and unfolding (ambiguous adjustment) - in which respectively, all life course trajectories, trajectories with clustering of life events and mainly stable trajectories were present. This study contributes to the literature through the unfolding pattern, showing that adjustment to unexpected pregnancy may be an ambiguous process that is not finished when the baby has arrived, especially if individuals have strong aspirations in light of a relatively stable life course.

Background: Saudi Arabia bears a disproportionate burden of autosomal recessive genetic disorders, driven by consanguineous marriage rates of 50 to 58% and elevated carrier frequencies for conditions such as sickle cell disease (carrier rate up to 25%), betathalassemia (12%), and spinal muscular atrophy (6%). The existing premarital screening program screens for only two conditions. We developed SafeGene, a computational platform that expands predictive genetic screening to 50+ conditions using region specific population genetics. Methods: SafeGene integrates five risk calculation engines: (1) Mendelian inheritance models for AR, AD, XR, and XD conditions; (2) Hardy Weinberg equilibrium based carrier probability estimation using Saudi, Gulf, and global databases; (3) a six level consanguinity coefficient calculator (F = 0 to 1/8) with risk amplification multipliers; (4) multifactorial polygenic risk models for 12 complex diseases; and (5) maternal age dependent trisomy risk curves. Built using React.js, Node.js/Express, and MongoDB with bilingual Arabic/English support. Results: The platform encompasses 50 genetic conditions across 12 categories. Validation against published Saudi data demonstrated concordance with observed disease frequencies. Economic modeling projects that expanding screening could prevent 2,800 to 4,200 affected births annually, yielding savings of SAR 1.2 to 2.8 billion ($320 to 746 million USD) per year. Conclusions: SafeGene represents a scalable, evidence-based digital health solution for comprehensive genetic screening addressing the unique population genetics of consanguineous Gulf societies. The platform is protected under pending patent applications in South Africa (CIPC) and Saudi Arabia (SAIP).

Introduction: Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a common congenital malformation with complex etiology involving both genetic and environmental factors. Epigenetic mechanisms may mediate environmental contributions, but separating genetic from environmental effects remains challenging. Methods: We present an epigenome-wide association study with 32 monozygotic and 22 dizygotic twin pairs discordant for NSCL/P on blood and saliva samples. Differential methylation analysis was conducted using linear models to identify CpG sites showing significant methylation differences between affected and unaffected twins followed by functional annotation and pathway enrichment analysis. Results: The top-ranked finding is a differentially methylated region comprising two CpG sites at the CYP26A1 locus, cg12110262 (P = 3.21x10-7) and cg15055355 (P = 1.39x10-3). CYP26A1 is essential for retinoic acid catabolism and craniofacial patterning. The chromatin regulator ANKRD11, which causes KBG syndrome featuring cleft palate was the second best hit. Differentially methylated CpG sites showed significant enrichment in craniofacial enhancers and overlap with multiple GWAS-validated cleft genes including VAX1, PVRL1, SMAD3, and PRDM16. Conclusions: Our findings implicate retinoic acid signaling and chromatin regulation in NSCL/P etiology and demonstrate the value of discordant twin designs for distinguishing environmental from genetic epigenetic contributions to complex malformations.

To date, FBRSL1-related disorder has been reported in five individuals with congenital abnormalities and severe postnatal impairment with or without epilepsy; however, the full extent of the phenotypic and genotypic spectrum remains unclear. Previously reported cases involved small truncating variants apparently escaping nonsense-mediated decay, suggesting either a haploinsufficiency or a dominant-negative mechanism. We report the first case of a complex structural variant at the FBRSL1 locus, resulting in an additional, partially truncated copy of the gene, providing strong evidence for a dominant-negative mechanism. RNA-Seq supported the expression of the additional truncated gene copy. The patient is an infant girl with a profound developmental and epileptic encephalopathy (DEE). The child presented at birth with intrauterine growth restriction, respiratory insufficiency, severe swallowing dysfunction, spasticity, contractures, optic nerve hypoplasia, facial dysmorphism, and atrial septal defect. She developed severe postnatal growth restriction with microcephaly and profound developmental impairment. She has a DEE with frequent neonatal focal seizures evolving to infantile epileptic spasms syndrome (IESS). Our patient has congenital abnormalities in common with previously reported cases, along with a profound DEE, not associated previously with FBRSL1. Our case expands both the phenotypic and genotypic spectrum of FBRSL1-related disorder.

Abstract Background Understanding the phenotypic spectrum of disease-associated genes is essential for accurate diagnosis and targeted therapy. FRMPD4 (FERM and PDZ Domain Containing 4) has previously been associated with intellectual disability and epilepsy. However, its potential role in non-syndromic hearing loss has not been explored. Methods We performed genetic analysis in two unrelated families presenting with non-syndromic sensorineural hearing loss, identifying maternally inherited missense variants in FRMPD4. Clinical phenotyping included audiological assessment and evaluation for neurodevelopmental involvement. Cross-species expression analyses were conducted in Drosophila, zebrafish, and mouse. Functional characterization included quantitative evaluation of sound-evoked responses in Drosophila nicht gut hoerend (ngh) mutants, assessment of neuronal development and acoustic startle responses in zebrafish loss of function models, and morphological cochlear analyses with auditory brainstem response measurements in knockout mice. Results Three affected males from two unrelated families presented with prelingual, bilaterally symmetrical sensorineural hearing loss, with confirmed congenital onset in one individual and no evidence of neurodevelopmental abnormalities. Cross-species analyses demonstrated evolutionarily conserved expression of FRMPD4 in auditory structures. In Drosophila, quantitative analysis of sound-evoked responses in ngh mutants revealed impaired auditory function. Zebrafish loss of function models exhibited reduced neuronal populations in the otic vesicle and posterior lateral line, abnormal neuromast development, and diminished acoustic startle responses. In mice, Frmpd4 knockout resulted in high-frequency hearing loss and cochlear abnormalities consistent with the human phenotype. Conclusions Our findings expand the phenotypic spectrum of FRMPD4 to include non-syndromic sensorineural hearing loss and establish its evolutionarily conserved role in auditory function. These results have direct implications for genetic diagnosis and variant interpretation in patients with hearing loss.

Genome-wide association studies of idiopathic pulmonary fibrosis (IPF) have identified 35 common genetic risk loci associated with IPF susceptibility. In this study, we evaluated the effects of the reported variants in clinically curated non-European individuals. Despite limited sample sizes, we observed partial replication, limited transferability of some variants and evidence of ancestry-specific effects. The MUC5B promoter variant rs35705950 emerged as the dominant and most consistent signal across ancestries. Our findings highlight the need for larger, well-characterised studies in understudied populations to support robust discovery and translation.

Background: Idiopathic pulmonary fibrosis (IPF) is a rare disease with a poor prognosis. Disease risk involves rare and common genetic variants. However, an inverse association have been described between them. Accordingly, IPF patients with a higher polygenic risk score (PRS) for IPF are less likely to carry rare deleterious variants and vice versa. Here, we evaluate weather PRS of IPF could serve as an additional criterion to patient prioritisation for rare variant discovery. Methods: We identified carriers based on the presence of rare qualifying variants (QVs) in genes linked to monogenic forms of pulmonary fibrosis in 888 IPF patients from the Pulmonary Fibrosis Foundation Patient Registry (PFF-PR). Genome-wide association study (GWAS) summary statistics from independent cohorts were used to construct a whole-genome PRS (WG-PRS) using a clumping and thresholding method (C+T) and a Bayesian method (SBayesRC). PRS were also derived from 19 known common sentinel IPF variants (Sentinel-PRS). Logistic regression models were used to evaluate associations between PRS and carrier status. Discriminatory performance was evaluated using area under the curve (AUC) analysis, and comparisons were made with DeLong test. Validation was performed in 472 IPF individuals from the UK PROFILE cohort. Results: IPF-PRS were strongly associated with the QVs carrier status: Odds Ratio [OR] 0.65 (95% Confidence Interval [CI] 0.53-0.79) for WG-PRSC+T, OR 0.71 (95% CI 0.59-0.86) for WG-PRSSBayesRC, and OR 0.77 (95% CI 0.63-0.94) for Sentinel-PRS. Adding WG-PRS to the patient personal clinical history improved the prediction of QVs carriers: AUC=0.62 for the clinical model, AUC=0.68 for WG-PRSC+T (DeLong test, p=9.54x10-4) and AUC=0.66 for WG-PRSSBayesRC (DeLong test, p=0.02). Adding of IPF-PRS to clinical variables correctly reclassified 22.8% of carriers when using WG-PRSC+T, 20.8% when using Sentinel-PRS, and 16.7% for WG-PRSSBayesRC. WG-PRSSBayesRC and the Sentinel-PRS also demonstrated improved prediction of QVs carriers in telomere-related genes in PROFILE. Conclusions: Incorporating IPF-PRS into a model based on the patient clinical history improves the identification of QVs carriers. Although the overall discriminatory power was moderate, these findings raise de the possibility of using WG-PRS as useful criterion for rare variant discovery in patients with IPF and enhance decision-making.

Inner-ear genetics has expanded rapidly, yet the supporting evidence remains dispersed across a vast literature and across resources that typically emphasise loci, variants, or expression data rather than integrated biological interpretation. Here we present the Inner Ear Knowledge Base (IEKB; https://earkb.org), an open database that unifies curated associations, cochlear interaction evidence, candidate prioritisation, explainable support relations, and network exploration for inner-ear research. IEKB was built with an automated agent-assisted curation workflow that combines schema-constrained literature extraction, continuous human monitoring, and final expert review by inner-ear genetics researchers. By systematically analysing 250,696 PubMed-indexed records retrieved across 16,563 screened genes, IEKB curates 6,051 gene-phenotype-disease associations from 2,494 genes across 43 phenotype categories and 4,102 cochlear gene-gene interactions with pathway, cell-type, and experimental context. IEKB further includes a Bayesian "dark matter" module that prioritises 243,071 candidate gene-phenotype associations for 13,229 genes across all 43 phenotypes (global AUC-ROC = 0.8603; global AUC-PR = 0.1674), together with a supervised dark-relation layer that ranks phenotype-specific known-gene support for each candidate and a multi-entity scientific network containing nearly 4,000 entities, 28,616 deterministic edges, and 83,712 literature-derived relational links. The web resource supports interactive search, multi-parameter filtering, gene-detail pages, bibliometric exploration, domain-specific enrichment against IEKB phenotype and disease gene sets, network visualisation, bulk download in CSV, JSON, SQLite, and XLSX formats, and natural-language evidence-grounded question answering through a companion conversational interface (IEKB QA). To our knowledge, IEKB is the first openly accessible inner-ear resource that integrates curated associations, cochlear interactions, probabilistic candidate prioritisation, auditable known-gene support relations for novel candidates, and a multi-entity scientific network within a single database. All data are released without registration under the CC BY 4.0 license.

The geographical and familial origins of Christopher Columbus have remained a subject of intense historiographical debate for over five centuries. Despite numerous hypotheses, empirical genetic evidence capable of resolving his ancestral history or place of birth has been absent from the literature until now. This study presents the third stage of the first forensic genetic analysis performed on skeletal remains belonging to several direct descendants of Columbus, spanning the 16th to 18th centuries. By applying Massively Parallel Sequencing (MPS) to analyse autosomal, X- and Y- chromosome DNA markers, and integrating the results with multidisciplinary evidence from historical, genealogical, archaeological, and anthropological research implicated in this project, the identification of several individuals founded in the Crypt of Santa Maria de Gracia located in Gelves (Sevilla, Spain) has been achieved. The analysis of their biological relatedness enabled the reconstruction of kinship networks among the individuals interred in the crypt, which, when interpreted in the context of documented genealogical lineages, provides indirect but consistent evidence pointing toward the debated origin of the discoverer.

Background: Diagnosing the over 700 known rare bone diseases (RBDs) is inherently challenging and often requires extensive time and multiple clinical visits. Effective treatment, particularly for RBDs with approved therapies, depends on early and precise identification of the specific RBD type. Image recognition artificial intelligence (AI) has the potential to significantly enhance diagnostic processes and improve patient outcomes. Many of these disorders cause characteristic skeletal changes, especially in the hands, and are associated with growth abnormalities. Consequently, affected children routinely undergo hand radiographs for bone age assessment, making these images a widely available yet underutilized diagnostic resource. Materials and Methods: We retrospectively compiled 5,623 multi-institutional hand radiographs from 2,471 patients with 45 different RBDs and 1,382 unaffected controls. We trained two deep learning models: a binary classifier to differentiate between RBD and non-RBD hand radiographs, and a multi-class classifier covering ten RBDs (or RBD groups), using 5-fold cross-validation. Preprocessing included masking, normalization, and data augmentation. Additionally, we applied occlusion sensitivity mapping to visualize class-specific features and evaluated the learned representations through cosine-based retrieval and UMAP projections of the feature space. Results: The affected versus unaffected classifier achieved a balanced accuracy of 85.5% on the test dataset. The ten-class classifier reached a balanced (top-1) accuracy of 76.6%, with top-3 accuracy exceeding 90%. Disorders with highly distinctive phenotypes, such as achondroplasia, achieved accuracies above 95%, whereas phenotypically overlapping disorders, such as ACAN- and SHOX-related short stature, were more frequently confused. Feature space analysis showed that validation samples clustered closely with their respective training distributions, supporting the consistency and generalizability of the learned embeddings. Conclusion: This manuscript presents a proof of principle for the development of Bone2Gene, a next-generation phenotyping (NGP) tool for the detection and differential diagnosis of RBDs, currently based on hand radiographs. Ongoing efforts focus on expanding the dataset to include additional RBDs or RBD groups in the current multi-class classifier for differential diagnosis and to further evaluate its generalizability. The Bone2Gene study is open to collaboration.

Background: Artificial intelligence (AI)-driven variant prioritization has demonstrated substantial utility in expediting genetic diagnosis by ranking the most likely causative variants. While a variety of tools have been developed, few address the unique clinical and technical constraints in prenatal genetic diagnosis. Methods: We introduce Berrylyzer, a novel, end-to-end variant prioritization system applied to prenatal diagnosis.Inspired by clinician's reasoning process during variant interpretation, Berrylyzer applies a modular, stepwise scoring architecture that jointly integrates phenotypic and genomic evidence and delivers a ranked list of candidate variants, achieving high computational efficiency without compromising analytical rigor. Moreover, Berrylyzer natively supports both structured ontologies and free-text clinical narratives, enabling flexible integration into diverse clinical environments. Its performance was rigorously evaluated across two independent, real-world prenatal cohorts and benchmarked against three state-of-the-art methods: Xrare, Exomiser, and PhenIX. Results: Across the two datasets, Berrylyzer ranked 56.41% and 58.12% of diagnostic variants first, and achieved recall rates of 94.02% and 97.42% within top 20, respectively. Berrylyzer outperformed Xrare (85.19% and 87.08%), Exomiser (84.90% and 85.98%), and PhenIX (82.05% and 88.93%). Stratified analysis consistently demonstrated superior performance across diverse disease categories, inheritance patterns, and analytical strategies. Notably, Berrylyzer exhibited robustness regardless of phenotype forms, yielding comparable top 20 recall rates for free-text descriptions and standardized terminologies. Conclusion: Berrylyzer represents an accurate, interpretable, and computationally lightweight variant prioritization system for prenatal genetic diagnosis. The superior performance across heterogeneous diagnostic contexts enables it as a practical solution for seamless integration into clinical pipelines, thereby advancing precision medicine in prenatal settings.

ObjectiveSNP heritability estimates vary substantially across estimation strategies, yet the downstream consequences for polygenic risk score (PRS) construction remain poorly characterised. We systematically benchmarked heritability estimation configurations and assessed their propagation into downstream PRS performance. MethodsWe benchmarked 86 heritability-estimation configurations spanning six tool families (GEMMA, GCTA, LDAK, DPR, LDSC, SumHer) and ten method groups across 10 UK Biobank phenotypes, yielding 844 configuration-level estimates. Each estimate was propagated into GCTA-SBLUP and LDpred2-lassosum2 PRS frameworks and evaluated across five cross-validation folds using null, PRS-only, and full models. Eleven binary analytical contrasts were tested using Mann-Whitney U tests to identify drivers of heritability variability. ResultsHeritability ranged from -0.862 to 2.735 (mean = 0.134, SD = 0.284), with 133 of 844 estimates (15.8%) negative and concentrated in unconstrained estimation regimes. Ten of eleven analytical contrasts significantly affected heritability magnitude, with algorithm choice and GRM standardisation showing the largest effects. Despite this upstream variability, downstream PRS test performance was only weakly coupled to heritability magnitude: pooled Pearson correlations between h2 and test AUC were r = -0.023 for GCTA-SBLUP and r = +0.014 for LDpred2-lassosum2 (both non-significant). ConclusionSNP heritability is best interpreted as a configuration-sensitive modelling parameter rather than a universally stable scalar input. Heritability estimates should always be reported alongside their full estimation specification, and downstream PRS performance is comparatively robust to moderate variation in the heritability input. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/716079v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@112929borg.highwire.dtl.DTLVardef@573c36org.highwire.dtl.DTLVardef@132170borg.highwire.dtl.DTLVardef@1871363_HPS_FORMAT_FIGEXP M_FIG C_FIG