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PubMed2025

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.

PURPOSE: We previously developed an approach to calibrate computational tools for clinical variant classification, updating recommendations for the reliable use of variant impact predictors to provide evidence strength up to Strong. A new generation of tools using distinctive approaches has since been released, and these methods must be independently calibrated for clinical application. METHODS: Using our local posterior probability-based calibration and our established data set of ClinVar pathogenic and benign variants, we determined the strength of evidence provided by 3 new tools (AlphaMissense, ESM1b, and VARITY) and calibrated scores meeting each evidence strength. RESULTS: All 3 tools reached the Strong level of evidence for variant pathogenicity and Moderate for benignity, although sometimes for few variants. Compared with previously recommended tools, these yielded at best only modest improvements in the trade-offs between evidence strength and false-positive predictions. CONCLUSION: At calibrated thresholds, 3 new computational predictors provided evidence for variant pathogenicity at similar strength to the 4 previously recommended predictors (and comparable with functional assays for some variants). This calibration broadens the scope of computational tools for application in clinical variant classification. Their new approaches offer promise for future advancement of the field.

Humans↗

PubMed2026

LDLR Variant Classification Through Activity-Normalized Prime Editing Screening.

BACKGROUND: Inherited variants in the LDL (low-density lipoprotein) receptor (LDLR) gene are the most common cause of familial hypercholesterolemia, significantly increasing coronary artery disease risk. Early identification of pathogenic LDLR variants enables prompt lipid-lowering therapy and cascade testing of at-risk relatives; however, most LDLR variants observed in the population have uncertain or absent clinical classifications, leaving many patients without actionable information. METHODS: We developed the first activity-normalized prime editing screening pipeline to measure the impact of 5184 LDLR coding variants on LDL-cholesterol (LDL-C) uptake. Each prime editing guide RNA is paired with a genotypic outcome reporter to correct for variable editing efficiency, overcoming a key limitation of previous pooled genome editing screens. A statistical framework further improves variant effect estimates by jointly analyzing all missense variants at each amino acid position. RESULTS: We show that prime editing of the reporter construct correlates with endogenous variant installation frequency, validating the activity normalization approach. The resulting scores capture a continuous spectrum of functional effects, robustly separate pathogenic versus benign ClinVar variants, and show concordance with LDL-C levels in UK Biobank participants. We calibrate functional evidence strengths to the ACMG/AMP variant interpretation framework, enabling integration into a clinical variant classification workflow. By combining functional, computational, population, and contextual evidence, 322 of 434 LDLR variants currently classified as variants of uncertain significance, conflicting, or absent from ClinVar appear to meet evidence thresholds for reclassification and can be prioritized for expert review, substantially expanding the pool of actionable variant classifications. The screen also reveals a cluster of gain-of-function variants in LDLR class A repeat 5, at least some of which enhance LDL-C uptake through increased apolipoprotein B interaction, with implications for therapeutic genome editing. Last, prime editing uniquely detects splice-altering coding variants missed by cDNA-based screens and pathogenicity predictors, revealing an advantage of endogenous variant installation. CONCLUSIONS: Altogether, activity-normalized prime editing provides a scalable framework for LDLR variant classification that substantially expands the proportion of variants with evidence for genetic diagnosis and reveals novel biology with therapeutic relevance.

CRISPR screening↗

PubMed2025

Quantifying evidence for phenotypic specificity (PP4) for syndromic phenotypes: Large-scale integration of rare germline FH variants from diagnostic laboratory testing for HLRCC and renal cancer.

PURPOSE: Hereditary leiomyomatosis and renal cell cancer (HLRCC) is a rare cancer susceptibility syndrome exclusively attributable to pathogenic variants in FH (HGNC:3700). This article quantitatively weights the phenotypic context (PP4/PS4) of such very rare variants in FH. METHODS: We collated clinical diagnostic testing data on germline FH variants from 387 individuals with HLRCC and 1780 individuals with renal cancer and compared the frequency of "very-rare" variants in each phenotypic cohort with 562,295 population controls. We generated pan-gene very rare variant likelihood ratios (PG-VRV-LRs), domain-specific likelihood ratios for missense variants (DS-VRMV-LR) using spatial clustering analysis, and log2.08 likelihood ratios (LLRs) as applicable within the updated American College of Medical Genetics and Genomics/Association for Molecular Pathology variant classification framework. RESULTS: For HLRCC, the PG-VRV-LR was estimated to be 2669.4 (95% CI 1843.4-3881.2, LLR 10.77) for truncating variants and 214.7 (95% CI 185.0-246.9, LLR 7.33) for missense variants. For renal cancer, the PG-VRV-LR was 95.5 (95% CI 48.9-183.0, LLR 6.23) for truncating variants and 5.8 (95% CI 3.5-9.3, LLR 2.39) for missense variants. Clustering analysis in HLRCC cases revealed 3 "hotspot" regions wherein the DS-VRMV-LR increased to 1226.9. CONCLUSION: These data provide quantitative measures for very rare missense and truncating variants in FH, which reflect the differing phenotypic specificity of HLRCC and renal cancer and may be applicable in clinical variant classification.

Humans↗

PubMed2025

acmgscaler: an R package and Colab for standardized gene-level variant effect score calibration within the ACMG/AMP framework.

MOTIVATION: A genome-wide variant effect calibration method was recently developed under the guidelines of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP), following ClinGen recommendations for variant classification. While genome-wide approaches offer clinical utility, emerging evidence highlights the need for gene- and context-specific calibration to improve accuracy. Building on previous work, we have developed an algorithm tailored to converting functional scores from both multiplexed assays of variant effects (MAVEs) and computational variant effect predictors (VEPs) into ACMG/AMP evidence strengths. RESULTS: Our method is designed to deliver consistent performance across different genes and score distributions, with all variables adaptively determined from the input data, preventing selective adjustments or overfitting that could inflate evidence strengths beyond empirical support. To facilitate adoption, we introduce acmgscaler, a lightweight R package and a plug-and-play Google Colab notebook for the calibration of custom datasets. This algorithmic framework bridges the gap between MAVEs/VEPs and clinically actionable variant classification. AVAILABILITY AND IMPLEMENTATION: The R package and Colab notebook are available at https://github.com/badonyi/acmgscaler.

Software↗

PubMed2025

Extracting and calibrating evidence of variant pathogenicity from population biobank data.

Genomic medicine requires a robust evidence base of variant phenotypic impacts, which remains incomplete even in extensively studied genes with monogenic disease associations. Here, we evaluated the broad potential of using population cohort data to identify evidence that can be used in variant assessment. Across 41 genes related to 18 clinically actionable monogenic phenotypes, we calculated variant-level odds ratios of disease enrichment using data from 469,803 UK Biobank participants. We found significant differences in odds ratio values between ClinVar-labeled pathogenic and benign variants in 11 phenotypes, spanning both common and rare disorders. To facilitate clinical translation, we calibrated the strength of evidence provided by variant-level odds ratios to align with American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) interpretation guidelines (PS4 criterion) and found that odds ratios may reach "moderate," "strong," or "very strong" evidence, varying by phenotype and gene. Overall, we found that 2.6% (N = 12,350) of participants harbor a rare variant of uncertain significance (VUS) with at least moderate evidence of pathogenicity-an indication of potentially unrecognized disease risk. Finally, by incorporating computational and functional data alongside population-based odds ratios, we identified variants that met the criteria for clinical reclassification. Notably, using this approach, we identified that 12.4% of rare VUSs in LDLR seen in participants meet diagnostic criteria to be classified as likely pathogenic, demonstrating its potential to scale the reclassification of VUSs.

Humans↗

PubMed2025

Imprecision medicine: Systematic gaps in reporting variants of uncertain significance (VUS) and their reclassifications.

PURPOSE: Variants of uncertain significance (VUS) are frequently encountered during clinical genetic testing. To explore the clinical burden of VUS, we developed the Brotman Baty Institute Clinical Variant Database, which is an electronic health record (EHR)-linked database of clinical germline genetic variant information from patients with rare genetic disorders seen at 2 tertiary academic medical centers. METHODS: We retrospectively reviewed EHRs and genetic testing reports from 5158 patients seen across diverse adult genetics practices at these institutions from 2015 to 2024. We also compared these EHR-based variant classifications with those in ClinVar. RESULTS: The number of reported VUS relative to pathogenic or likely pathogenic variants can vary by over 14-fold depending on the primary indication for genetic testing and 3-fold depending on self-reported race. Furthermore, at least 1.6% of variant classifications used in the EHR for clinical care are outdated based on ClinVar variant classifications, including 26 instances in which the testing lab updated ClinVar, but the reclassification was never communicated to the patient. CONCLUSION: Our findings reveal that the clinical burden of VUS in adult medical genetics is unequally distributed across patients. We also highlight a deficiency in existing systems for communicating variant reclassifications to ClinVar, patients, and providers.

Humans↗

PubMed1975

[Clinical picture and variants in the course of chronic postinfarction aneurysms of the heart].

The study is based on the analysis of 268 patients with chronic postinfarction aneurysms of the heart, 190 of whom were operated. Clinical characteristics of postinfarction cardiac aneurysms are presented, and several symptoms typical for this pathology are singled out: pericardial pulsation, low pulse volume, tachycardia, outward shift of the left margin of the heart, galloping atrial rhythm. Proceeding from a careful analysis of the clinical material an original classification of the variants of the clinical course of chronic postinfarction carrdiac aneurysms is introduced: 1) with prevailing chronic coronary insufficiency; 2) with combined chronic coronary and cardiac insufficiency; 3) with prevailing cardiac insufficiency.

Adult↗

PubMed2025

Federated learning for the pathogenicity annotation of genetic variants in multi-site clinical settings.

MOTIVATION: Rare diseases collectively affect 5% of the population. However, fewer than 50% of rare disease patients receive a molecular diagnosis after whole genome sequencing. Supervised machine learning is a valuable approach for the pathogenicity scoring of human genetic variants. However, existing methods are often trained on curated but limited central repositories, resulting in poor accuracy when tested on external cohorts. Yet, large collections of variants generated at hospitals and research institutions remain inaccessible to machine-learning purposes because of privacy and legal constraints. Federated learning (FL) algorithms have been recently developed enabling institutions to collaboratively train models without sharing their local datasets. RESULTS: Here, we present a proof-of-concept study evaluating the effectiveness of FL for the clinical classification of genetic variants. A comprehensive array of diverse FL strategies was assessed for coding and non-coding Single Nucleotide Variants as well as Copy Number Variants. Our results showed that federated models generally achieved comparable or superior performance to traditional centralized learning. In addition, federated models reached a robust generalization to independent sets with smaller data fractions as compared to their centralized model counterparts. Our findings support the adoption of FL to establish secure multi-institutional collaborations in human variant interpretation. AVAILABILITY AND IMPLEMENTATION: All source code required to reproduce the results presented in this article, implemented in Python, is available under the GNU General Public License v3 at https://github.com/RausellLab/FedLearnVar.

Humans↗

PubMed2026

Targeted reflex RNA sequencing for enhanced variant classification on exome and genome sequencing improves patient outcomes.

RNA sequencing (RNA-seq) has been utilized to provide functional evidence regarding the impact of splicing variants. This study explores the utility of targeted reflex RNA-seq to inform classification of predicted splicing variants identified through clinical exome sequencing (ES) and genome sequencing (GS). A retrospective analysis was conducted on consecutive ES/GS cases completed at a single center in which targeted reflex RNA-seq was performed following identification of eligible variants. There were 131 cases (4.1%) that had at least one RNA-seq eligible variant reported, with eight of these cases having two unique eligible variants. Of the 139 eligible variants, 125 were classified as variants of uncertain significance (VUS). Sixty-four cases had targeted reflex RNA-seq completed with 27 cases having at least one variant reclassified (42.2%). After reclassification, 23 cases had positive results, and two cases had a likely diagnosis of an autosomal recessive condition. Clinical outcomes data regarding positive RNA-seq cases showed that 71% (10/14) had clinical management changes and 43% (6/14) had treatment changes. Incorporation of targeted reflex RNA-seq analysis into the diagnostic pipeline of rare diseases enhances variant classification and resolves uncertainty regarding predicted splice variants, leading to an estimated 1.6% increase in diagnostic yield of clinical ES/GS.

Journal Article↗

PubMed2024

Classification of variants of reduced penetrance in high-penetrance cancer susceptibility genes: Framework for genetics clinicians and clinical scientists by CanVIG-UK (Cancer Variant Interpretation Group-UK).

PURPOSE: Current practice is to report and manage likely pathogenic/pathogenic variants in a given cancer susceptibility gene as though having equivalent penetrance, despite increasing evidence of intervariant variability in risk associations. Using existing variant interpretation approaches, largely based on full-penetrance models, variants in which reduced penetrance is suspected may be classified inconsistently and/or as variants of uncertain significance. We aimed to develop a national consensus approach for such variants within the Cancer Variant Interpretation Group UK (CanVIG-UK) multidisciplinary network. METHODS: A series of surveys and live polls were conducted during and between CanVIG-UK monthly meetings on various scenarios potentially indicating reduced penetrance. These informed the iterative development of a framework for the classification of variants of reduced penetrance by the CanVIG-UK Steering and Advisory Group working group. RESULTS: CanVIG-UK recommendations for amendment of the 2015 ACMG/AMP variant interpretation framework were developed for variants in which (A) active evidence suggests a reduced-penetrance effect size (eg, from case-control or segregation data) and (B) reduced penetrance effect is inferred from weaker/potentially inconsistent observed data. CONCLUSION: CanVIG-UK propose a framework for the classification of variants of reduced penetrance in high-penetrance genes. These principles, although developed for cancer susceptibility genes, are potentially applicable to other clinical contexts.

Humans↗

PubMed2026

'Truthsets' for clinical validation of large-scale functional assays: Practice recommendations from Cancer Variant Interpretation Group UK (CanVIG-UK).

BACKGROUND: Large-scale functional assays, including multiplex assays of variant effect, have substantial potential to resolve variants of uncertain significance (VUS), particularly for rare missense variants where clinical and population evidence are limited. The ClinGen assay-level clinical validation framework described by Brnich et al provided baseline guidance for the use of functional data for variant classification. However, clear consensus regarding construction of variant 'truthsets' by which to clinically validate functional data remains lacking. METHODS: CanVIG-UK developed consensus recommendations for truthset construction through an iterative national consultation process involving the CanVIG Steering Advisory Group (CStAG), wider CanVIG-UK membership, and engagement with international functional genomics experts. Consultation was based on previous analyses of 2,120 truthset constructions examining the impact of truthset composition on evidence point allocation within the ClinGen assay-level clinical validation framework. RESULTS: Across several consultations, CanVIG-UK established nine guiding principles and seven best-practice recommendations for assay-level clinical validation, using the assumed context of an assay for a cancer susceptibility gene where loss-of-function is the mechanism of pathogenicity. The principal recommendation stipulates, where assays are intended for use in interpretation of largely missense variants, the truthset used to validate should comprise only missense variants. Rather than mixtures of different variant types which may serve to over-estimate assay performance. Additional recommendations support option for relaxation of truthset stringency to improve power, augmentation of benign missense truthsets with systematically derived 'proxy-clinical' benign variants, independent clinical validation separate from assayist-defined validation, and careful evaluation of missense score distributions against that of protein-truncating and synonymous variants. Guidance is also provided for scenarios with limited pathogenic truthset availability and for assays reporting multiple deleterious zones or readouts. CONCLUSIONS: The CanVIG-UK principles and recommendations for truthset construction upon the ClinGen assay-level clinical validation framework, while aiming to form a baseline for future discussion regarding other functional and disease contexts and helping to address the gap between publication of new data and routine clinical implementation.

Journal Article↗

PubMedDate not supplied

[A case of GM-Gangliosidosis (atypical form of the AB variant)].

A case of GM-gangliosidosis, variant AB, with some atypical feautres is reported in a male child, who died at the age of 4 years and 3 months. When he was 2 and a half years old, he showed signs of progressive cerebral disease with increasing motor and mental impairment. The clinical signs suggested a form of neurolipidosis; however the data of the enzymatic activities of the peripheral blood leucocytes did not show any deficit related to these forms. More specifically the values of the exosaminides A and B were normal, although the component A was near the lowest limit of the range. The anatomical, histological, histochemical, ultrastructural and chemical studies showed that it was a form of GM-gangliosidosis with visceral involvement. In the crude lipid extracts of various organs there was not only GM-ganglioside, but also a compound not previously demonstrated in these forms of neurolipidosis. Chemically this compound may be considered a phosphoglyco-lipid-and protein complex. From the enzymatic data in the peripheral blood leucocytes, the case may be a variant AB of the Sandhoff and al. classification (1971). However some clinical signs make our case closer to the 3th type of the O'Brien and al, classification while some histopathological aspects are similar to Tay-Sachs disease (i.e. to the variant B of the Sandhoff et al. classification; i.e. to the 1th type of the O'Brien et al. classification). These data, and the presence of an 'unknown compound', not yet demonstrated in the known forms of GM-gangliosidosis, support the hypothesis that our case may be considered as an 'atypical' form of the variant AB of the gangliosidosis GM and that further studies are necessary to reach a final nosography of these entities.

Brain Chemistry↗

PubMed2026

Comprehensive evaluation of ACMG/AMP-based variant classification tools.

MOTIVATION: The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines represent the gold standard for clinical variant interpretation. Despite the widespread adoption of ACMG/AMP guidelines, a comprehensive comparison of the software tools designed to implement them has been lacking. This represents a significant gap, as clinicians require evidence-based guidance on which tools to use in their practice. RESULTS: We benchmarked four ACMG/AMP-based tools (Franklin, InterVar, TAPES, Genebe) selected from 22 tools, and compared their performance with LIRICAL, a top-performing phenotype-driven tool, using 151 expert-curated datasets from Mendelian disorders. Selection criteria included free availability, VCF compatibility, operational reliability, and not being disease-specific. Our evaluation framework assessed top-N accuracy (N = 1, 5, 10, 20, 50), retention rates, precision, recall, F1 scores, and area under the curve (AUC). Statistical validation employed bootstrap confidence intervals (n = 1000) and Friedman tests. LIRICAL (68.21%) and Franklin (61.59%) demonstrated superior top-10 variant prioritization accuracy in Mendelian disorders, significantly outperforming other tools (P = .0000). Results demonstrate that tools with advanced phenotypic integration significantly outperform those relying primarily on genomic features. AVAILABILITY AND IMPLEMENTATION: All data and source code required to reproduce the findings of this study are openly available in the Code Ocean repository at https://doi.org/10.24433/CO.6562438.v1.

Software↗

PubMed2026

CanVar-UK: A collaborative platform for germline interpretation in cancer susceptibility genes.

Germline variants in cancer susceptibility genes (CSGs) are typically inherited rather than arising de novo. Hence, wide cascade testing of families across geographies is common, meaning consistency in variant classification is particularly critical. Variant interpretation requires collation of variant-level data from diverse sources, as well as assembly of comprehensive clinical data, often necessitating sharing of information between genomic testing centers. Here, we describe CanVar-UK, a freely accessible web platform bespoke designed to support interpretation of germline CSG variants. CanVar-UK contains variant-level data for over 1.1 million single-nucleotide variants (SNVs), comprising all possible coding SNVs in 116 established CSGs. The data sources with which variants are annotated include in silico scores from 11 clinically relevant tools, population allele frequencies from gnomAD v4.1, case counts from multiple cohorts, including National Health Service (NHS) clinical laboratory testing, variant-level readouts from 47 selected functional and splicing datasets across 19 CSGs, genetic epidemiology studies, and live linkage to existing consensus classifications in the ClinVar database. The diagnostic discussion forum is only available to registered diagnostic scientist users. Through this, a variant-tagged email message can be dispatched in real time across the diagnostic forum community of >1,500 users, with all exchanges and classifications captured and stored in the platform. Already widely used by NHS diagnostic clinical scientists in the UK, CanVar-UK has a rapidly growing international diagnostic user base (>800 UK and >600 non-UK registered users). Survey of the NHS diagnostic user community illustrates the wide-ranging utility of CanVar-UK within their clinical workflows for interpretation of germline CSG variants.

Journal Article↗

PubMed2025

Pathogenicity assessment of genetic variants identified in patients with severe hypertriglyceridemia: Novel cases of familial chylomicronemia syndrome from the Dyslipidemia Registry of the Spanish Atherosclerosis Society.

PURPOSE: Genetic testing is required to confirm a diagnosis of familial chylomicronemia syndrome (FCS). We assessed the pathogenicity of variants identified in the FCS canonical genes to diagnose FCS cases. METHODS: 245 patients with severe hypertriglyceridemia underwent next-generation sequencing. Preliminary variant pathogenicity criteria and classification, based on the American College of Medical Genetics and Genomics guidelines, were obtained online and verified. Phenotype evaluation was based on lipoprotein lipase activity deficiency, a clinical score, and/or type I hyperlipoproteinemia determined in 25 patients. RESULTS: Twenty-four biallelic variants were analyzed. Evidence-based criteria allowed the reclassification of 8 likely pathogenic (LP) variants in the LPL, APOA5, and LMF1 genes into pathogenic (P) and the change of 2 variants of uncertain significance (VUS) to LP. Conversely, 2 variations in LMF1 remained as VUS. Additionally, 1 variant in LPL and 2 in GPIHBP1 were likely benign. Twenty FCS cases had biallelic P/LP variants and 1 patient, with an FCS phenotype, harbored biallelic VUS. FCS was excluded from 4 patients with pathogenic/likely benign combinations. CONCLUSION: The analysis of the clinical and biochemical features of patients with variants in the FCS canonical genes allowed a confident variant classification that helped in the diagnosis of novel FCS cases.

Humans↗

PubMed2025

Distinct rates of VUS reclassification are observed when subclassifying VUS by evidence level.

PURPOSE: Genetic testing commonly yields a plethora of variants of uncertain significance (VUS) that can lead to ongoing uncertainty for patients and their caregivers. Although all VUS hold uncertainty, some VUS have more evidence in support of pathogenicity, whereas others have more evidence of a benign role. Sharing these nuances can help guide the investment in follow-up clinical and research investigations and may, at times, influence medical decision making despite appreciated uncertainty. METHODS: Four clinical laboratories have been subclassifying VUS to help prioritize investigation and guide reporting decisions. Each laboratory developed a distinct approach for how these subclasses are used in their laboratories and, in some cases, displayed on reports. We examined the composition of each laboratory's VUS subclasses and the likelihood variants from each subclass were reclassified toward pathogenic or benign. RESULTS: We found that variants in the lowest subclass of VUS were never reclassified as likely pathogenic or pathogenic, whereas those in the highest subclass were much more likely to be reclassified as pathogenic or likely pathogenic. CONCLUSION: Given that forthcoming professional guidance in variant classification will advise the use of VUS subclasses, the experience of our laboratories in using VUS subclasses can inform future practices.

Humans↗

PubMed2025

What Should a Clinical Cardiologist Know About Cardiogenetics?

Inherited cardiovascular diseases are becoming increasingly prominent in clinical practice, significantly impacting diagnosis, risk assessment, and family screening strategies. Progress in genetic testing has broadened access to cardiogenetic evaluations, while also presenting new challenges in interpreting variants and incorporating findings into clinical care. This narrative review explores 20 essential questions that clinical cardiologists may face when dealing with suspected or confirmed inherited cardiac conditions. Organized as a practical, question-driven guide, it outlines when to consider a genetic cause, how to choose and interpret genetic tests, and how to manage patients regardless of their genetic test results. The review emphasizes variant classification based on American College of Medical Genetics and Genomics criteria, the importance of clinical context in interpreting uncertain results, and the principles behind family cascade screening. Particular attention is given to the management of relatives who carry a genetic variant but show no symptoms, and to the current limitations of genetic testing technologies (eg, performance). Ethical considerations, including the appropriate timing of testing in children minors, are also discussed. By connecting genetic insights with clinical cardiology, this review aims to support practical, informed decision making and promote effective collaboration with cardiogenetic specialists.

Humans↗

PubMed2026

Pragmatic Phenotype-Electrophysiology-Genomics Integration in Pediatric Congenital Myasthenic Syndromes: Insights From 36 Patients in a Single-Center Study in China.

AIMS: To characterize the clinical, electrophysiological, and genetic spectrum of pediatric CMS and evaluate genotype-informed outcomes using an integrated phenotype-electrophysiology-genomics approach. METHODS: We retrospectively reviewed 36 pediatric CMS patients evaluated at a single center between 2015 and 2025. Clinical features, RNS, targeted NGS/WES variants, ventilator use, treatments, ACMG/AMP classifications, and MG-ADL outcomes were analyzed. RESULTS: Of 36 patients, 28 (77.8%) developed symptoms in the neonatal period or infancy. Biallelic variants involved 17 CMS genes; postsynaptic CMS was most common (55.6%, 20/36). COLQ and CHRNE were the most frequent genes (13.9%, 5/36 each), followed by CHAT (11.1%, 4/36). VUS were detected in 19 patients (52.8%, 19/36), including 8 with biallelic VUS supported by phenotype, neuromuscular transmission findings, treatment response, and follow-up. RNS showed a ≥ 10% decrement in 16/21 tested patients (76.2%). CHAT-CMS was associated with higher ventilator use (3/4 vs. 6/32; p = 0.041) and early mortality (3/4 vs. 1/32; p = 0.002). Median MG-ADL improved from 5 to 3 after genotype-informed therapy. CONCLUSION: Pediatric CMS shows marked genetic heterogeneity and frequent VUS-related uncertainty. Integrating phenotype, electrophysiology, and genomics supports diagnosis and mechanism-guided therapy. CHAT-CMS is high risk for early respiratory failure and mortality.

Humans↗