Genetics in Medicine

Purpose Children with suspected rare genetic disorders often remain undiagnosed after exome, gene panel, or chromosomal microarray testing. We sought to define recurrent missed-diagnosis mechanisms and evaluate an integrated clinical-genomic reanalysis framework. Methods We studied 75 participants with rare or striking pediatric-onset phenotypes who remained undiagnosed after prior genetic testing. Trio genome sequencing evaluated SNVs, indels and copy-number variants. RNA sequencing was performed in 63 participants to assess aberrant expression and splicing, with targeted follow-up assays used selectively for prioritized variants. Clinician-genome scientist review integrated longitudinal phenotyping, physician input, and inheritance. Unresolved cases underwent research-level candidate prioritization. Results Clinically reportable findings were returned in 9, including two with multilocus findings: 5 explained the primary phenotype and 4, while not fully explanatory, were clinically relevant and informing surveillance, management, or family follow-up. Previously missed findings reflected technical limitations, including deep intronic splice-altering variants supported by transcriptome analysis and a genomic deletion, and interpretive limitations related to incomplete phenotype integration or narrowly scoped prior testing. Research-level analysis prioritized six candidate genes, including biallelic ACHE variants with reduced enzymatic activity. Conclusion Integrated clinical-genomic reanalysis framework identified diagnostic gaps, recovered care-informing findings, and prioritized candidate genes for rare disease discovery.

Neurodevelopmental disorders (NDDs) are clinically and genetically heterogeneous, and evidence linking additional genes to disease evolves rapidly. We developed SysNDD, an open-access, expert-curated resource that represents distinct gene-inheritance-disease associations as entities with standardized confidence, phenotype, and variant annotations. Each entity retains its curation history, so its evidence category can change as evidence accumulates. Currently, SysNDD contains 4,275 entities curated from 4,932 publications. Of these, 3,758 entities involving 3,271 genes describe NDDs; the remainder record non-NDD disorders, nearly all linked to NDD-associated genes, included for completeness. Regarding NDD evidence categories, 1,838 genes are Definitive, 179 Moderate, 1,248 Limited, and 6 Refuted. The entity model captures inheritance-specific disorders, including 220 genes with both autosomal dominant and autosomal recessive NDD associations. Comparison with seven other NDD gene resources showed complementary coverage, and evidence categories largely agreed with those of ClinGen, Gene2Phenotype, and PanelApp for shared gene-disease pairs. NDD genes formed distinct molecular modules, whereas associated disorders formed broad, overlapping phenotype groups that corresponded to those modules only selectively. SysNDD provides a continuously maintained, programmatically accessible framework for gene-disease evidence assessment, inheritance-aware interpretation, and systematic NDD research.

Goh et al. recently reported that most recurrent copy number variants (CNVs) are far less penetrant for intellectual disability (ID) than previously estimated, and recommended that fourteen should no longer be reported. We show that the lower estimates arise mainly from assuming the population prevalence of ID alone, while case counts derive from broad diagnostic referral cohorts in which about half of individuals were referred for other indications. The proposed formula estimates a risk difference rather than penetrance, and cases and controls were selected, assayed and phenotyped differently. Restricting the outcome to ID also leaves the analysis unable to inform risk for autism, epilepsy, psychiatric, cardiac and other phenotypes. We recommend that families receive phenotype-specific absolute risks for carriers alongside background risks, and that reporting decisions be made locus by locus by guideline bodies, considering all relevant phenotypes. The recalculated estimates inform this debate but are not yet sufficient grounds for changing reporting practice.

Background Short-read genome sequencing generates the signal necessary to detect balanced reciprocal translocations at single-nucleotide resolution, but standard structural variant callers represent them as breakend pairs. Structural variant callers produce thousands of breakend records per genome, the majority of which are false positives arising from segmental duplications, repetitive elements, and reference assembly artifacts. This specificity problem has prevented balanced translocation detection from entering routine genome sequencing workflows. We developed a highly specific pipeline to resolve balanced reciprocal translocations and applied it across five clinically distinct cohorts to characterize the prevalence and diagnostic contribution of balanced reciprocal translocations. Methods Short-read genome sequencing data from 16,131 individuals across five cohorts were analyzed: healthy participants from the 1000 Genomes Project (n=3,202), probands with structural birth defects and their family members (CHOP BDB cohort; n=2,875, including 1017 probands), probands enrolled in the GREGoR consortium (GREGoR cohort; n=3,574 probands), probands with undiagnosed disease and their family members enrolled in the Undiagnosed Diseases Network (UDN cohort; n=6,071 including 2,027 probands) and neonates who underwent rapid genome sequencing (CHOP Baby Eagle cohort; n=409). A computational pipeline was developed to characterize breakend events from standard structural variant callers to high-confidence balanced translocation calls by exploiting well-characterized properties of true balanced translocation signatures in short-read data. Translocation breakpoints were resolved to single-nucleotide precision and interrogated for disruption of known disease genes or potential regulatory consequence otherwise. A subset of the identified breakpoints was confirmed by Sanger sequencing. Results Balanced reciprocal translocations were identified in 0.196% of structural birth defect probands (2/1,017), 0.25% of the GREGoR probands (9/3,574), 0.39% of the UDN probands (8/2,027) and 0.24% of neonates who underwent rapid genome sequencing (1/409). Parental carrier frequency in the birth defects cohort was 0.269% (5/1,858), consistent with previously reported estimates in similarly ascertained families, and 0.098% (3/3,040) in the UDN cohort. All six translocations identified in the birth defects cohort were orthogonally validated using Sanger sequencing, confirming pipeline specificity. Approximately 31% of translocations across the three affected cohorts disrupted a known disease gene at the breakpoint, establishing or refining a molecular diagnosis in five cases previously unresolved. The single translocation identified in the newborn cohort disrupted no disease gene and was classified as a variant of uncertain significance.

Abstract INTRODUCTION Despite major advances in genomic sequencing and analytical pipelines for rare disorders, more than 50% of affected individuals remain without a molecular diagnosis. One challenge is the interpretation of inherited variants exhibiting incomplete penetrance (IP). MATERIALS AND METHODS We developed a pipeline to systematically investigate inherited variants as the cause of rare disease in 4,325 families, consisting of affected probands and unaffected parents, from the Broad Center for Mendelian Genomics, part of the GREGoR Consortium. As a proof-of-concept of further omics follow-up, epigenomic and transcriptomic analyses were performed in one family harboring an inherited disease-causing frameshift variant in CHD8. RESULTS We identified 81 families where the affected proband harbored a putative disease-causing variant inherited from a reportedly unaffected parent. Clinical re-evaluation identified 30 families in which an inherited variant was considered diagnostic, including six previously missed diagnoses. In this cohort, inherited IP variants account for 1.6% of the diagnosed cases, with an overall diagnostic yield of 0.4% in the cohort. Methylation analysis of the CHD8 family confirmed a positive CHD8 clinical episignature in the male proband, but also in the reportedly unaffected mother. Transcriptomic analysis showed that despite similar CHD8 haploinsufficiency, the proband and mother displayed divergent downstream transcriptional effects. DISCUSSION This study highlights the importance of considering parentally inherited IP variants in rare disease, with at least 1 in 60 diagnostic variants inherited from a reportedly unaffected parent, and demonstrates the potential of integrating omics evaluation to improve variant interpretation.

PurposeTo describe the development of - and outcomes from - an institution-level initiative supporting access to innovative genetic medicines information and opportunities. MethodsWe developed and implemented a Genetic Medicines Patient Assessment Pathway for rare genetic conditions at a large public hospital, with multidisciplinary teams collaborating to evaluate a patients molecular and clinical amenability to experimental and/or to-be-developed genetic medicines (primarily nucleic acid therapeutics). A Genetic Medicines Consult Clinic operating in parallel offered no-cost specialized consultations and counseling to families regarding genetic medicines inquiries and Pathway outcomes. We retrospectively reviewed submissions, decisions, and outcomes over a >2-year period. ResultsA total of 63 submissions were reviewed in the Patient Assessment Pathway. Most submissions were classified as eligible or potentially eligible for at least one genetic medicines approach (42/63; 67%). Recommendations generated 87 discrete actions, such as outreach to potential collaborators (n = 28), offering participation in existing research studies (n = 23), or referral to the Consult Clinic (n = 19). Two patients have been approved for therapeutic program initiation or clinical trial enrolment. ConclusionFindings to date support feasibility and high uptake of a structured, multidisciplinary, medical genetics-led model for assessing patient-level opportunities for genetic medicines.

CACNA1A-related disorders arise from altered function of the P/Q-type calcium channel Cav2.1 and encompass a broad spectrum of neurological phenotypes, including developmental and epileptic encephalopathy, familial hemiplegic migraine type 1 and episodic ataxia type 2. Although loss-of-function and gain-of-function mechanisms have both been implicated, interpretation of rare CACNA1A missense variants remains challenging because clinical presentation is heterogeneous and many variants identified through diagnostic sequencing remain classified as variants of uncertain significance. To generate clinically interpretable functional evidence, we developed a calibrated high-throughput automated patch-clamp assay to assess the CACNA1A variants. Twenty-six curated benign/likely benign and 30 curated pathogenic/likely pathogenic missense variants were expressed in Flp-In HEK293 cells with CACNB4 and CACNA2D1. We quantified current density, {Lambda}V0.5 activation,{Lambda}V0.5 inactivation and recovery from inactivation (T0.5 RFI), and used benign controls to define parameter-specific normal ranges with {+/-}3 Z-score thresholds. This multi-parameter framework classified all benign controls as functionally normal and 29 of 30 pathogenic controls as abnormal, yielding 100% specificity and 96.7% sensitivity. Current density identified 19 pathogenic controls with loss of function, while gating and recovery from inactivation identified additional abnormal variants with preserved or partially preserved current density. The assay generated likelihood ratios of 0.033 for normal function and 25.13 for abnormal function, supporting BS3 and PS3 functional evidence, respectively. Application to 23 CACNA1A variants identified in Australian patients showed abnormal function in all four variants already classified as pathogenic or likely pathogenic. Among 19 variants of uncertain significance, 11 were functionally abnormal and nine were reclassified as likely pathogenic after integration of PS3 evidence with other ACMG/AMP criteria. These data show that CACNA1A missense variants can produce loss-of-function, gain-of-function or mixed effects, and that multi-parameter functional assessment is required for accurate interpretation. This calibrated automated patch-clamp framework provides clinically interpretable evidence for refining CACNA1A variant classification in diagnostic practice.

To evaluate the clinical implementation of long-read genome sequencing (lrGS) and establish the population reference resources needed to support its use in diagnostics, we integrate two complementary initiatives: Genome of Sweden (GoS), Sweden's contribution to Genome of Europe (GoE), and the Genomic Medicine Sweden - Rare Diseases (GMS-RD) long-read sequencing pilot. The initial GoS release of 576 individuals provides population-scale maps of genetic and epigenetic variation. Among 485 GMS-RD probands, 161 (33.2%) receive a molecular diagnosis, with lrGS providing added clinical value in 40 (24.8%). As a first-line test, lrGS could have avoided at least 42 follow-up analyses and an additional testing cycle in 7.2% of probands, reducing costs and the burden on patients. By integrating population and clinical long-read genomics, Sweden establishes a national ecosystem for genomic research and clinical diagnostics. Our findings support the clinical implementation of lrGS and offer a scalable model for national collaboration.

Background: Recent work has brought large language models (LLMs) into clinical variant interpretation. In most existing approaches, the model is confined to text-level operations, retrieving, extracting, compacting, and summarizing heterogeneous evidence, while the genuine genetic evaluation is delegated to a separate deterministic engine. Other tools employ LLMs to mine functional evidence for a single ACMG criterion, to rerank a classifier's output, or to answer isolated variant questions. Integrative genetic reasoning, by contrast, demands multi-source evidence weighing for each variant, reconciliation of inheritance with observed zygosity and parental genotypes, joint interpretation of variants in the same gene, and the derivation of a case-level conclusion. Moreover, to protect patient privacy, this must be done on hospital premises. Methods: o build an end-to-end variant interpreter that runs on local infrastructure, we benchmarked 13 small language models (SLMs) on 150 multiple-choice genetics questions and selected Qwen3.5-9B. In IVA (Intelligent Variant Analyser), a four-stage pipeline, the model assigns ACMG/AMP criteria, applies de novo, dominant, recessive, and X-linked inheritance logic to trios, and writes a structured report, while deterministic code handles retrieval, phasing, point summation, citation checking, and formatting. We evaluated IVA on synthetic scenarios, 16 solved trios, and 327 solved singleton cases of visual impairment, on a single GPU. Results: On the benchmark, Qwen3.5-9B reached a mean accuracy of 0.81, compared with 0.89 for a 1.6-trillion-parameter cloud model. In the 16 trios, IVA reported every previously identified pathogenic, likely pathogenic, or uncertain-significance variant of interest (sensitivity 100%; precision 39.5%). In the 327 singleton cases, it recovered 93% of the expert-reported causative variants and classified 82% of them as pathogenic or likely pathogenic (precision 43%). Failures fell into four recurrent classes: omission, unverified mechanism, mismatch between reasoning and label, and arithmetic errors. Conclusions: A small language model running on local hardware can serve as the reasoning layer for case-level and trio-based variant interpretation when it is surrounded by deterministic safeguards. Because its outputs are not deterministic, analyst review and prospective multicenter validation remain necessary.

ObjectiveTo evaluate usability and workflow implications of Pheno+, an electronic health record- (EHR) embedded natural language processing tool that extracts patient phenotypes and maps them to Human Phenotype Ontology (HPO) terms. Materials and MethodsThis study performed a mixed-methods formative evaluation of Pheno+ in the context of rapid genome sequencing in the neonatal intensive care unit. Two rounds of think-aloud interviews and surveys were conducted with neonatologists, advanced practice providers, medical geneticists, genetic counselors, non-genetics pediatric subspecialists and laboratory molecular geneticists. Usability was assessed using the System Usability Scale (SUS). Structured data were analyzed descriptively. Qualitative data underwent hybrid deductive-inductive thematic analysis. ResultsTwenty-eight interviewees participated in two rounds of data collection. Users retained an average of 24.2 HPO terms from an average of 45.6 terms per patient. Mean time curating terms was 8:59 per patient. Final SUS score was 76 (above scale mean). Qualitative themes included: burden of curating terms; interpretation of phenotypes; adding information to phenotypes; role of genetics expertise; and tool uses beyond the original core use case for Pheno+. DiscussionPheno+ demonstrated positive usability but required curation effort to reduce erroneous terms. Participant responses indicate that effective use may depend on knowledge of HPO structure and laboratory workflows. Automated phenotyping seems likely to reduce net clinician workload, while also reshaping clinical responsibilities, expertise requirements, and communication in genetic testing. ConclusionTools like Pheno+ can support scalable genomic medicine. Design and implementation may benefit from addressing curation burden, phenotype contextualization, expertise requirements, and other workflow needs.

Background: Current Lynch syndrome (LS) prediction models do not account for detailed family structure and tumour mismatch repair (MMR) status. We developed LynchRisk, a Bayesian model that estimates individualized LS probability from pedigree, cancer history and tumour MMR test results. Methods: LynchRisk combines Mendelian inheritance, age- and sex-specific cancer hazards, affected and unaffected relatives, and detailed MMR status. Parameters were derived from the literature. Results: In two simulated cases of probands with LS-associated cancers, family structure and MMR status markedly changed LS probability estimates, with implications for germline testing decisions. LynchRisk also identified situations in which a negative germline result might be considered sufficient to rule out LS or, conversely, prompt further investigations such as somatic MMR or long-read sequencing. Discussion: LynchRisk gives individualized LS probability by combining clinical, family, and tumour data at different stages of the diagnostic process. Further work will focus on recalibrating cancer hazard functions, validating model performance through simulations, and developing an R package for use by interested research groups.

FBXO31 encodes the substrate receptor of an SCF (SKP1-CUL1-F-box) E3 ubiquitin ligase that recognizes C-terminal amide-bearing proteins (CTAPs) and targets them for proteasomal degradation, a function of particular importance in neurons. A recurrent de novo missense variant, c.1000G>A p.(Asp334Asn), reprograms FBXO31 substrate specificity and causes an autosomal-dominant neurodevelopmental disorder with spastic cerebral palsy through a neomorphic gain-of-function mechanism. By contrast, biallelic loss of function has tentatively been linked to a recessive disorder. Here we report a female patient, born to consanguineous parents, with moderate intellectual disability, developmental delay and dysmorphic features, who carries a homozygous 54.3 kb deletion removing exons 2-8 and the coding part of exon 9 of FBXO31. The deletion retains only the exon 1-encoded F-box domain, while removing the coding sequence for the entire C-terminal substrate-recognition region. It is predicted to result in loss of function. Segregation is consistent with autosomal-recessive inheritance, with both parents and three of five unaffected siblings being heterozygous carriers. Together with two previously reported recessive families and the experimentally established neomorphic action of p.(Asp334Asn), the homozygous deletion supports an FBXO31 allelic series comprising dominant gain of function and recessive biallelic loss of function.

CUB and Sushi domains-containing CSMD proteins are involved in neuron development. Variants in the CSMD1-3 paralogs were GWAS-associated with cognition, attention-deficit hyperactivity disorder (ADHD), schizophrenia and brain structure, suggesting that these genes could be linked to neurodevelopmental disorders (NDD). Indeed, rare biallelic variants in all three CSMD paralogs were recently associated with epilepsy, while rare biallelic variants in CSMD1 were also linked with intellectual disability and cortical malformations. We identified nine individuals from eight families carrying CSMD2 biallelic missense variants in developmental delay/intellectual disability cohorts. Affected individuals presented with autism spectrum disorder (ASD), ADHD and brain anomalies. Consistent with gnomAD metrics that suggest CSMD2 haploinsufficiency, we also report two families segregating monoallelic CSMD2 frameshift variants, which complement a described de novo truncation variant in an ASD proband. We concomitantly report two phenotypically overlapping individuals with de novo CSMD2 missense variants and compare them to twelve de novo CSMD2 cases identified in published trio analyses. UK Biobank analyses showed nominally significant enrichment of ADHD, ASD and neuroticism in volunteers carrying at least one rare CSMD2 variant. In silico modelling and immunofluorescence assays showed that mutated residues in affected individuals with biallelic and de novo missense variants are clustering in two regions and that the encoded proteins showed impaired membrane localization and an increased cytoplasmic aggregation. Zebrafish crispant larvae for the orthologous csmd2 presented with microcephaly, smaller cerebellum, and reduced Purkinje cell size. Larvae also displayed decreased swimming velocity, diminished connectivity between the optic tecta, and abnormal peripheral neuronal branching. We demonstrate that rare, likely pathogenic variants in CSMD2 are associated with both autosomal recessive and dominant forms of NDD further substantiating the functional significance of CSMD paralogs in neurogenesis/synapse formation.

Genetic prediction of clinically defined disease subtypes could advance precision medicine, but polygenic risk scores (PRSs) often show limited ability to distinguish subtypes, either because the subtypes share genetic architecture or because available PRSs are inaccurate. We introduce GenSep, a statistical framework that estimates the oracle case-case AUC attainable if the true additive genetic values of both subtypes were known, and the proportion of this genetic separation recovered by subtype-specific PRSs. Across 18 subtype pairs in UK Biobank, oracle AUCs ranged from 0.605 to 1.000, whereas current PRSs achieved a median observed case-case AUC of only 0.530 (range, 0.510-0.754), corresponding to recovery of a median of 4.1% (range, 0.3-15.5%) of the genetic separation variance available to a perfect predictor. Oracle AUCs were generally consistent across UK Biobank, All of Us, FinnGen and the Million Veteran Program, and across European, African and Admixed American ancestry groups. FinnGen-trained PRSs, despite 2.6-to 3.9-fold larger discovery samples, performed no better than internally trained PRSs, and substantially larger consortium GWAS raised case-case AUC by 0.06 on average (range, 0.003-0.089). GenSep separates subtype pairs limited by intrinsic genetic overlap from those limited by current PRS accuracy, identifying where larger studies and better predictors could improve genetic discrimination.

Polygenic risk scores (PRS) are rapidly developing, enabling estimates of genetic risk for developing psychiatric disorders. Psychiatric PRS are also increasingly entering consumer and clinical settings. Yet, little is known about how adults with psychiatric disorders perceive their potential use. Here, we conducted semi-structured interviews with 29 adults with psychiatric disorders to examine their perspectives on hypothetically receiving psychiatric PRS for themselves and their current or future children. Key themes emerged around perceived utility, motivations and deterrents to genetic testing, interpretation of PRS, and anticipated responses to results. In particular, participants expressed hope that PRS could support self-understanding, inform better psychiatric care, and enable earlier recognition of difficulties for their children. Participants however raised multiple concerns, including those of privacy, stigma, discrimination, eugenics, and the risk of self-fulling prophecies. Together, these findings offer critical empirical evidence to inform guidance on the responsible use of psychiatric PRS in clinical and consumer settings.

Tandem repeat expansions cause more than 60 Mendelian disorders but are difficult to detect and size accurately with short-read sequencing because of their length and repetitive structure. Long-read sequencing (LRS) resolves these loci directly, yet analytic tooling for nanopore sequencing data has lagged behind that available for other long-read platforms. Here we present Mahi-mahi, a tandem repeat genotyper designed for nanopore reads that reports allele-level repeat length, motif composition, interruptions, and read-level flags for systematic basecalling artifacts. Across six Genome in a Bottle samples, whole-genome and adaptive sampling (real-time targeted) data returned calls within one repeat unit of each other for 829 of 832 alleles, and Mahi-mahi calls were within one repeat unit of orthogonal HiFi data at 95.6% of compared alleles after excluding three loci at which the two tools define the repeat differently. In 245 samples from the 1000 Genomes Project, Mahi-mahi calls were within one repeat unit of assembly-derived calls for 98.6% of 10,927 alleles at 57 loci, and Mahi-mahi distinguished pathogenic from nonpathogenic RFC1 alleles of overlapping size by motif. Across 14 Coriell reference lines, Mahi-mahi identified the expected expansion in every line and agreed with orthogonal assays to within two repeat units at HTT, ATXN1, DMPK, and PABPN1. Finally, in 103 samples from three laboratories, Mahi-mahi detected an expanded allele in all samples in which prior testing had reported a pathogenic expansion, assigned the same category as the referring laboratory for 98% of 180 genotypes, and identified known ATXN1 interruption structure. Our results demonstrate that Mahi-mahi accurately identifies repeat expansions at disease-associated loci and could serve as a single assay to evaluate repeat expansions.

Background: Rapid genome sequencing (rGS) is a first-tier test in the neonatal intensive care unit (NICU). Implementation strategies to scale rGS for clinical care may change clinician roles. We analyzed the NICU rGS workflow to understand challenges rGS poses for clinical roles and responsibilities. Methods: The study took a qualitative approach to understanding the rGS workflow in Level III and Level IV NICUs. The five workflow phases studied included: i) identification of a patient with a suspected genetic disorder, ii) subspecialist consultation, iii) test selection and ordering, iv) return of results, and v) disclosure. Data were collected via job task journals, interviews, and workflow diagram construction with clinicians involved in rGS. Analysis included participant-guided workflow diagram refinement, qualitative thematic analysis, and identification of rGS workflow challenges. Results: We documented issues related to decision-making authority and scope of responsibility for clinicians, with the majority relating to complexities of subspecialist consultations. Issues included differences in: criteria for triggering consultations, expectations of consulted subspecialists' roles, test selection preferences, and responsibility for documenting clinical interpretations and disclosure. Conclusion: Subspecialist consultations in clinical rGS involved significant role ambiguity and communication challenges, requiring intentional implementation efforts to ensure clear clinical roles and responsibilities.

Isolated focal dystonia is a rare movement disorder characterized by abnormalities in brain structure and function. The genes underlying isolated focal dystonia are not fully elucidated, and genetic studies are constrained by incomplete penetrance and small family sizes. Neuroimaging endophenotypes shared by patients and unaffected relatives can reveal genetic liability independently of clinical manifestation and offer a strategy for advancing gene discovery. We developed DystoniaGeneNet, a 3D convolutional neural network that predicts familial status from T1-weighted brain MRIs. We then used its predictions to guide genetic analyses in isolated focal dystonia. DystoniaGeneNet was trained on 40 patients with familial laryngeal dystonia and 40 healthy controls, then applied to independent cohorts of 21 patients with familial isolated focal dystonia, 364 patients with sporadic dystonia, and 98 unaffected relatives. Model predictions were incorporated into variant prioritization and segregation analysis in 214 individuals with whole-exome sequencing data, and results were replicated in another 738 independent exomes, in genetic data from a hospital-based biobank (892 dystonia cases, 2,475 controls), and in the All of Us Research Program genetic data (1,343 dystonia cases, 6,840 controls). DystoniaGeneNet discriminated familial dystonia from healthy controls in the training set and correctly classified 85.7% of independent familial cases, using a biomarker centred on the corpus callosum and inferior temporal gyrus. Across the discovery and replication cohorts, we identified rare, likely pathogenic genetic variants in RAP1GAP and TNN segregating with disease in families. Additional variants were found in singletons with isolated focal dystonia. In patients with clinically sporadic dystonia but predicted to have familial features, we observed multiple rare variants in ITSN2, including three high-confidence loss-of-function variants, and an enrichment of damaging missense variants in its Dbl homology domain. To determine the functional impact of discovered genetic variants, we assessed gene expression and splicing via qPCR and RNA sequencing (n = 74), revealing reduced RAP1GAP and ITSN2 expression in variant carriers. At the pathway level, rare nonsynonymous variants in brain-expressed matrisome genes were associated with dystonia (P = 0.012). Our strategy utilizing a deep learning-derived neuroimaging endophenotype to empower gene discovery uncovered RAP1GAP, TNN, and ITSN2 as novel genes associated with isolated focal dystonia. These genes converge on perisynaptic extracellular matrix-synapse signalling, implicating a mechanism linked to synaptic plasticity deficits, and identifying a molecular substrate for network-level brain abnormalities that characterize this disorder. Further, we exemplify a generalizable framework for leveraging endophenotypes in rare neurogenetic diseases with incomplete penetrance.

Multiplexed assays of variant effect (MAVEs) and computational methods have advanced variant classification but have struggled to distinguish the molecular mechanism of variants with sufficient accuracy, limiting utility for multi-mechanism genes. Here, we coupled single-cell RNA-seq profiling with supervised machine learning to predict the mechanism of variants in CASR, a gene in which gain of function (GOF) variants cause hypocalcemia and loss of function (LOF) variants cause hypercalcemia. We engineered endogenous CASR-depleted HEK293 cells to express a single exogenous variant copy, measured their transcriptional profiles at single-cell resolution, trained a multi-class machine learning model on 96 expert-annotated variants (25 benign, 35 LOF, 36 GOF), and predicted mechanism for 157 variants of uncertain significance, of which 16 were predicted GOF and 54 LOF. The model showed high performance (macro F1 0.98, overall accuracy 0.98), and its predictions were corroborated by clinical phenotype and serum calcium measurements across more than 300,000 patients in a commercial genetic testing database. These results highlight the effectiveness of using molecular mechanism annotations with scRNA-seq to train models that distinguish molecular mechanisms of pathogenicity. The approach has immediate relevance for clinical variant classification and establishes a foundation for mechanism-guided clinical management in disorders with mechanism-dependent interventions, with potential application to other multi-mechanism genes.

Purpose A significant proportion of cases with rare inherited retinal disease (IRD) remain genetically unresolved following short-read whole genome sequencing (WGS). This study aimed to increase the diagnostic yield of two cohorts in a research setting. One cohort was previously screened by short-read WGS (n=120 cases), while the second cohort (n=28 cases) was not included in any previous short-read WGS studies. In contrast to the larger cohort, these cases only underwent either exome sequencing (ES) or single-molecule molecular inversion probe (smMIPs) sequencing as pre-screening in earlier studies. For all cases, we performed a stepwise, case by case reanalysis in which short-read WGS was generated (n=28 cases) and (re)analyzed short-read WGS data using an optimized approach. For a subset of cases (n=20) that remained unresolved, this was followed by long read WGS. Together, these steps aimed to improve the diagnostic yield in these cohorts. Methods Short-read WGS data of 148 IRD-cases were (re)analyzed using updated allele frequency databases, new variant caller and variant predictor tools, as well as updated and extended gene-panels to identify causal single nucleotide variants (SNVs) and structural variants (SVs). For 20 genetically unresolved cases with sufficient high-quality DNA available, long-read WGS was performed. Results The (re)analysis of short-read WGS data in the 120 previously WGS-screened unresolved cases resulted in a diagnostic yield of 15% (18/120). For the 28 individuals without prior WGS, performing WGS analysis within this study provided an additional yield of 32% (9/28). Furthermore, long-read WGS contributed two genetic diagnoses among the 20 long-read WGS-sequenced probands. Amongst other reasons, new genetic diagnoses were attributed to pathogenic variants in genes newly associated with IRDs and in genes that were not included in the gene panels applied in previous WGS studies. The Mobile Element Locator Tool facilitated the identification of two pathogenic Alu insertions in short-read WGS. Long-read WGS identified two additional pathogenic variants. Conclusion These results support periodic reanalysis of existing short-read WGS data as a key component of IRD genetic diagnostics, with selective long-read WGS representing a valuable additional approach for unresolved cases. Together, these complementary strategies offer a practical framework for improving molecular diagnosis and narrowing the remaining diagnostic gap in IRDs.