Hypertrophic cardiomyopathy (HCM) is a cardiovascular pathology that is caused by variants in genes encoding sarcomere-associated proteins. However, the clinical significance of numerous variants in HCM-associated genes is still unknown. CRISPR/Cas9 is a tool of nucleotide sequence editing that allows for the unraveling of different biological tasks. In this study, introducing a mutation with CRISPR/Cas9 into induced pluripotent stem cells (iPSCs) of a healthy donor and the directed differentiation of the isogenic iPSC lines into cardiomyocytes were used to assess the pathogenicity of a variant of unknown significance, p.M659I (c.1977G > A) in MYH7, which was found previously in an HCM patient. Using two single-stranded donor oligonucleotides with and without the p.M659I (c.1977G > A) mutation, together with CRISPR/Cas9, an iPSC line heterozygous at the p.M659I (c.1977G > A) variant in MYH7 was generated. No CRISPR/Cas9 off-target activity was observed. The iPSC line with the introduced p.M659I (c.1977G > A) mutation in MYH7 retained its pluripotent state and normal karyotype. Compared to the isogenic control, cardiomyocytes derived from the iPSCs with the introduced p.M659I (c.1977G > A) mutation in MYH7 recapitulated known HCM features: enlarged size, elevated diastolic calcium level, changes in the expression of HCM-related genes, and disrupted energy metabolism. These findings indicate the pathogenicity of the variant.

BACKGROUND: CFTR-related disorder (CFTR-RD) is a clinical entity associated to complex diagnostic paths and newly upgraded standard of care. In CFTR-RD, CFTR genotyping represents a diagnostic surrogate marker. In case of novel haplotype, the diagnosis could represents an area of concern. We described the molecular evaluation of the rare CFTR variant E583G identified in trans with the F508del in a novel haplotype.
RESULTS: An adult woman was referred to our pulmonary unit for persistent respiratory symptoms. CFTR Next Generation Sequencing was performed to evaluate full-gene mutational status. The variant identified was evaluated for its pathogenicity integrating clinical evidences with dedicated bioinformatics analyses. Clinical evaluation of patient matched with a mono-organ CFTR-RD diagnosis. Genotyping revealed the novel CFTR haplotype F508del/E583G. Multiple evidences of a deleterious effect of the CFTR E583G rare variant emerged from the bioinformatics analyses performed.
CONCLUSIONS: Guidelines for CFTR-RD are available with the purpose of harmonizing clinical and molecular investigations. In such context, the identification of novel CFTR haplotype need to a deeper evaluation with a combination of skills. The novel E583G variant could be considered of clinical interest and overall a CFTR-RD Variants of Varying Clinical Consequences.

Despite recent efforts to issue clinical guidelines outlining strategies to define the pathogenicity of genomic variants, there is currently no standardized framework for which to make these assertions. This review does not present a step-by-step methodology, but rather takes a holistic approach to discuss many aspects which should be taken into consideration when determining variant pathogenicity. Categorization should be curated to reflect relevant findings within the scope of the specific medical context. Functional characterization should evaluate all available information, including results from literature reviews, different classes of genomic data repositories, and applicable computational predictive algorithms. This article further proposes a multidimensional view to infer pathogenic status from many genomic measurements across multiple axes. Notably, tumor suppressors and oncogenes exhibit fundamentally different biology which helps refine the importance of effects on splicing, mutation interactions, copy number thresholds, rearrangement annotations, germline status, and genome-wide signatures. Understanding these relevant datapoints with thoughtful perspective could aid in the reclassification of variants of unknown significance (VUS), which are ambiguously understood and currently have uncertain clinical implications. Ongoing assessments of VUS examining these relevant biological axes could lead to more accurate classification of variant pathogenicity interpretation in diagnostic oncology.

BACKGROUND: In the era of next-generation sequencing, clinicians frequently encounter variants of unknown significance (VUS) in genetic testing. VUS may be reclassified over time as genetic knowledge grows. We know little about how best to approach VUS in the maturity-onset diabetes of the young (MODY). Therefore, our study aimed to determine the utility of reanalysis of previous VUS results in genetic confirmation of MODY.
METHODS: A single-center retrospective chart review identified 85 subjects with a MODY clinical diagnosis. We reanalyzed genetic testing in 10 subjects with 14 unique VUS on MODY genes that was performed >3 years before the study. Demographic, clinical, and biochemical data was collected for those individuals.
RESULTS: After reanalysis, 43% (6/14) of the gene variants were reclassified to a different category: 7% (1/14) were \"likely pathogenic\" and 36% (5/14) were \"benign\" or \"likely benign.\" The reclassified pathogenic variant was in HNF1A and all reclassified benign variants were in HNF1A, HNF1B and PDX1. The median time between MODY testing and reclassification was 8 years (range: 4-10 years).
CONCLUSIONS: In sum, iterative reanalyzing the genetic data from VUS found during MODY testing may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses.

Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfatase A (ARSA) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning tools in Python, demonstrated superior performance among submissions. Furthermore, the study observed that state-of-the-art deep learning methods provided small but statistically significant improvement in predictive performance compared to less elaborate techniques. These findings underscore the utility of variant effect prediction, and the potential for models trained with modest resources to accurately classify VUS in genetic and clinical research.

The detection of variants of unknown significance (VUS) in familial Mediterranean fever (FMF) is common; however, their diagnostic value remains elusive, and the interpretation of multiple VUS remains difficult. Therefore, we examined FMF diagnosis-associated factors 1-year post-genetic testing in patients with only VUS and assessed the impact of multiple VUS on diagnosis and clinical features. A 1-year follow-up was conducted on patients clinically suspected of having FMF without confirmatory diagnosis owing to the presence of only VUS. Clinical features were compared between patients with a single VUS and those with multiple VUS among patients diagnosed with FMF. Among 261 patients followed up, 202 were diagnosed with FMF based on clinical judgment. No specific clinical symptoms or variant patterns at genetic testing were associated with diagnosis at 1 year. Multiple VUS was significantly and independently associated with a lower response to colchicine than single VUS among patients diagnosed with FMF. However, clinical symptoms showed no correlation with the number of VUS. In conclusion, predicting FMF diagnosis 1-year post-genetic testing in patients with only VUS remains challenging. Moreover, the impact of multiple VUS on FMF may be limited owing to the lack of correlation with clinical features, except colchicine response.

New technologies in genetic diagnostics have revolutionized the understanding and management of rare diseases. This review highlights the significant advances and latest developments in genetic diagnostics in inborn errors of immunity (IEI), which encompass a diverse group of disorders characterized by defects in the immune system, leading to increased susceptibility to infections, autoimmunity, autoinflammatory diseases, allergies, and malignancies. Various diagnostic approaches, including targeted gene sequencing panels, whole exome sequencing, whole genome sequencing, RNA sequencing, or proteomics, have enabled the identification of causative genetic variants of rare diseases. These technologies not only facilitated the accurate diagnosis of IEI but also provided valuable insights into the underlying molecular mechanisms. Emerging technologies, currently mainly used in research, such as optical genome mapping, single cell sequencing or the application of artificial intelligence will allow even more insights in the aetiology of hereditary immune defects in the near future. The integration of genetic diagnostics into clinical practice significantly impacts patient care. Genetic testing enables early diagnosis, facilitating timely interventions and personalized treatment strategies. Additionally, establishing a genetic diagnosis is necessary for genetic counselling and prognostic assessments. Identifying specific genetic variants associated with inborn errors of immunity also paved the way for the development of targeted therapies and novel therapeutic approaches. This review emphasizes the challenges related with genetic diagnosis of rare diseases and provides future directions, specifically focusing on IEI. Despite the tremendous progress achieved over the last years, several obstacles remain or have become even more important due to the increasing amount of genetic data produced for each patient. This includes, first and foremost, the interpretation of variants of unknown significance (VUS) in known IEI genes and of variants in genes of unknown significance (GUS). Although genetic diagnostics have significantly contributed to the understanding and management of IEI and other rare diseases, further research, exchange between experts from different clinical disciplines, data integration and the establishment of comprehensive guidelines are crucial to tackle the remaining challenges and maximize the potential of genetic diagnostics in the field of rare diseases, such as IEI.

Fabry disease (FD) is a life-limiting disorder characterized by intracellular globotriaosylceramide (Gb3) accumulations. The underlying α-galactosidase A (α-GAL A) deficiency is caused by variants in the gene GLA. Variants of unknown significance (VUS) are frequently found in GLA and challenge clinical management. Here, we investigated a 49-year old man with cryptogenic lacunar cerebral stroke and the chance finding of the VUS S126G, who was sent to our center for diagnosis and initiation of a costly and life-long FD-specific treatment. We combined clinical examination with in vitro investigations of dermal fibroblasts (HDF), induced pluripotent stem cells (iPSC), and iPSC-derived sensory neurons. We analyzed α-GAL A activity in iPSC, Gb3 accumulation in all three cell types, and action potential firing in sensory neurons. Neurological examination and small nerve fiber assessment was normal except for reduced distal skin innervation. S126G iPSC showed normal α-GAL A activity compared to controls and no Gb3 deposits were found in all three cell types. Baseline electrophysiological characteristics of S126G neurons showed no difference compared to healthy controls as investigated by patch-clamp recordings. We pioneer multi-level cellular characterization of the VUS S126G using three cell types derived from a patient and provide further evidence for the benign nature of S126G in GLA, which is of great importance in the management of such cases in clinical practice.

Introduction: Physicians face diagnostic dilemmas upon reports indicating disease variants of unknown significance (VUS). The most puzzling cases are patients with rare diseases, where finding another matched genotype and phenotype to associate their results is challenging. This study aims to prove the value of updating patient files with new classifications, potentially leading to better assessment and prevention. Methodology: We recruited retrospective phenotypic and genotypic data from King Saud Medical City, Riyadh, Kingdom of Saudi Arabia. Between September 2020 and December 2021, 1,080 patients\' genetic profiles were tested in a College of American Pathologists accredited laboratory. We excluded all confirmed pathogenic variants, likely pathogenic variants and copy number variations. Finally, we further reclassified 194 VUS using different local and global databases, employing in silico prediction to justify the phenotype-genotype association. Results: Of the 194 VUS, 90 remained VUS, and the other 104 were reclassified as follows: 16 pathogenic, 49 likely pathogenic, nine benign, and 30 likely benign. Moreover, most of these variants had never been observed in other local or international databases. Conclusion: Reclassifying the VUS adds value to understanding the causality of the phenotype if it has been reported in another family or population. The healthcare system should establish guidelines for re-evaluating VUS, and upgrading VUS should reflect on individual/family risks and management strategies.

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