Search Results (15)

Background/Objectives: Krabbe disease (KD) is a hereditary lysosomal disorder whose hallmark is progressive demyelination, with variable involvement of the central nervous system. It is caused by pathogenic variants in the GALC gene that disrupt the function of its gene product, the lysosomal enzyme galactosylceramidase. We analyzed two unrelated cases (one early infantile and one adult) with a clinical suspicion of KD. Methods: We used a combination of biochemical techniques (high-performance liquid chromatography–tandem mass spectrometry), NGS (resequencing gene panels), splicing assays, and molecular modeling to identify and analyze the pathogenicity of the variants underlying the disorder. Results: The two probands were compound heterozygotes for disease-causing variants in the GALC gene, encoding the lysosomal hydrolase galactosylceramidase. Three of the variants were novel and caused aberrant splicing, either by exon skipping (c.908+5G>A and c.1034-1G>C) or by inclusion of a cryptic, deep intronic pseudoexon (c.621+772G>C). The fourth variant was a known missense change (c.956A>G, p.(Tyr319Cys)) with conflicting interpretations of pathogenicity in the databases. Conclusions: We demonstrated the pathogenicity of the three novel splicing variants, all with strong impact on galactosylceramidase function. We also concluded that the c.956A>G missense variant is a hypomorph usually underlying the later-onset, milder phenotypes of KD. Our results stress the importance of integrated approaches combining clinical, biochemical, and genetic testing to obtain a definitive diagnosis of lysosomal diseases. Full article

Voltage-gated potassium channels Kv7.1, encoded by the gene KCNQ1, play critical roles in various physiological processes. In cardiomyocytes, the complex Kv7.1-KCNE1 mediates the slow component of the delayed rectifier potassium current that is essential for the action potential repolarization. Over 1000 KCNQ1 missense variants, many of which are associated with long QT syndrome, are reported in ClinVar and other databases. However, over 600 variants are of uncertain clinical significance (VUS), have conflicting interpretations of pathogenicity, or lack germline information. Computational prediction of the damaging potential of such variants is important for the diagnostics and treatment of cardiac disease. Here, we collected 1750 benign and pathogenic missense variants of Kv channels from databases ClinVar, Humsavar, and Ensembl Variation and tested 26 bioinformatics tools in their ability to identify known pathogenic or likely pathogenic (P/LP) variants. The best-performing tool, AlphaMissense, predicted the pathogenicity of 195 VUSs in Kv7.1. Among these, 79 variants of 66 wildtype residues (WTRs) are also reported as P/LP variants in sequentially matching positions of at least one hKv7.1 paralogue. In available cryoEM structures of Kv7.1 with activated and deactivated voltage-sensing domains, 52 WTRs form intersegmental contacts with WTRs of ClinVar-listed variants, including 21 WTRs with P/LP variants. ClinPred and paralogue annotation methods consistently predicted that 21 WTRs of KCNE1 have 34 VUSs with damaging potential. Among these, 8 WTRs are contacting 23 Kv7.1 WTRs with 13 ClinVar-listed variants in the AlphaFold3 model. Analysis of intersegmental contacts in CryoEM and AlphaFold3 structures suggests atomic mechanisms of dysfunction for some VUSs. Full article

The leading causes of pediatric arterial ischemic stroke (PAIS) are arteriopathies, which refer to pathologies of the arterial walls in the brain. Since traditional risk factors for cardiovascular diseases in children play a smaller role than in adults, it can be supposed that genetic factors may be of particular importance in this age group. Therefore, this study aimed to identify mutations affecting the formation of vascular wall pathologies, which can subsequently lead to ischemic stroke. The study used a database of 92 Caucasian children diagnosed with ischemic stroke. From this group, 25 children with arteriopathies were selected. The study had an exploratory and descriptive design, with the aim of characterizing rare genetic variants in a selected cohort, without attempting formal statistical association testing. The sequencing was performed using the Illumina NextSeq 550 platform. A panel of 161 genes known to be associated with stroke or arteriopathies was selected for further analysis. We identified 10 pathogenic or likely pathogenic mutations in 15 patients. Among these, three are likely monogenic causes of stroke (ELN, SCN5A, and VHL genes), two are considered risk factors (FV and ADAMTS13), two have conflicting interpretations (ACAD9 and ENG), and three are most likely benign (CBS, PMM2, and PKD1). The frequency of genetic variants underlying ischemic stroke or acting as risk factors for the disease in the studied group is significantly higher than the estimated frequency of monogenic forms of stroke in young adults and higher than in the general population. NGS testing is worth considering, especially in patients who exhibit certain symptoms that may suggest the presence of mutations. Full article

Different types of information are combined during variation interpretation. Computational predictors, most often pathogenicity predictors, provide one type of information for this purpose. These tools are based on various kinds of algorithms. Although the American College of Genetics and the Association for Molecular Pathology guidelines classify variants into five categories, practically all pathogenicity predictors provide binary pathogenic/benign predictions. We developed a novel artificial intelligence-based tool, PON-P3, on the basis of a carefully selected training dataset, meticulous feature selection, and optimization. We started with 1526 features describing variations, their sequence and structural context, and parameters for the affected genes and proteins. The final random boosting method was tested and compared with a total of 23 predictors. PON-P3 performed better than recently introduced predictors, which utilize large language models or structural predictions. PON-P3 was better than methods that use evolutionary data alone or in combination with different gene and protein properties. PON-P3 classifies cases into three categories as benign, pathogenic, and variants of uncertain significance (VUSs). When binary test data were used, some metapredictors performed slightly better than PON-P3; however, in real-life situations, with patient data, those methods overpredict both pathogenic and benign cases. We predicted with PON-P3 all possible amino acid substitutions in all human proteins encoded from MANE transcripts. The method was also used to predict all unambiguous VUSs (i.e., without conflicts) in ClinVar. A total of 12.9% were predicted to be pathogenic, and 49.9% were benign. Full article

Background/Objectives: ETV6-related thrombocytopenia (ETV6-RT) is a rare autosomal dominant disorder characterized by mild thrombocytopenia since birth and an increased predisposition to hematologic malignancies. ETV6 functions as a transcriptional repressor, and its pathogenic variants, predominantly within the ETS domain, disrupt nuclear localization and transcriptional activity. In individuals with congenital thrombocytopenia, we identified two missense variants: c.1110A>G, p.Ile370Met, a novel variant, and c.1133G>A, p.Arg378Gln, a known variant with conflicting pathogenicity interpretations, for which functional characterization is necessary to provide an accurate molecular diagnosis. Methods: In silico bioinformatic tools and structural modeling were used to predict the impact of the variants. Functional assays included a dual-luciferase reporter assay to measure transcriptional activity and immunofluorescence/immunoblotting to assess intracellular localization in transfected HEK293T and HeLa cells. Results: Bioinformatic predictions and structural analyses suggested that the two variants might play a role in altering the folding or function of the ETS domain. Functional analysis revealed that p.Ile370Met abolished the ETV6 transcriptional repression activity, confirming its pathogenicity. p.Arg378Gln had no effect on the reporter gene levels, and, as expected, it localized in the nucleus. Interestingly, unlike the known mutations, which fail to enter the nucleus, p.Ile370Met retained partial nuclear localization. Conclusions: Since we described the first ETV6 mutation localized in the ETS domain that causes a loss of transcriptional activity, although it maintains the ability to enter the nucleus, we suggest that both transcriptional activity and intracellular localization assays are important for the accurate classification of ETV6 variants by functional studies. Full article

Background: The accurate interpretation of the BRCA1/2 variant is critical for diagnosing and treating hereditary breast and ovarian cancers. ClinVar is a widely used public database for genetic variants. Conflicting classifications of pathogenicity can occur when different submitters categorize the same genetic variant inconsistently as pathogenic (PV), likely pathogenic (LPV), likely benign (LBV), benign (BV), or a variant of uncertain significance (VUS). The conflicting ClinVar BRCA1/2 variant classifications hinder clinical decision making. We reinterpreted 450 BRCA1 missense variants with conflicting interpretations in ClinVar (accessed on 20 December 2022). Methods: VarSome and the BRCA1/BRCA2: CanVIG-UK gene-specific guidance (CanVIG-UK) classifications were compared, and the five original classifications were consolidated into three categories (PV/LPV, VUS, and BV/LBV). Consensus analysis was performed between re-extracted ClinVar data and VarSome and CanVIG-UK results. Results: The three-category classification of the variants resulted in an overall concordance rate of 58.9% for BRCA1 missense variant interpretation between CanVIG-UK and VarSome, with VarSome having rates of 11.3, 24.7, and 64.0% for PV/LPV, VUS, and BV/LBV classifications and CanVIG-UK having rates of 11.1, 51.6, and 37.3% for P/LPV, VUS, and BV/LBV classifications, respectively. No variants classified as PV/LPV in VarSome were classified as BV/LBV in CanVIG-UK and vice versa. By 1 May 2024, 3.8% (17/450) of these conflicting variants reached a consensus classification in ClinVar and were definitively classified (9 PV/LPV, 1 VUS, and 7 BV/LBV). Conclusions: VarSome and CanVIG-UK have different features that help improve the accuracy of pathogenicity classification, highlighting the potential complementary use of both tools to support clinical decision making. Full article

The identification of the genetic causes of inherited disorders from next-generation sequencing (NGS) data remains a complicated process, in particular due to challenges in interpretation of the vast amount of generated data and hundreds of candidate variants identified. Inconsistencies in variant classification, where genetic centers classify the same variant differently, can hinder accurate diagnoses for rare diseases. Publicly available databases that collect data on human genetic variations and their association with diseases provide ample opportunities to discover conflicts in variant interpretation worldwide. In this study, we explored patterns of variant classification discrepancies using data from ClinVar, a public archive of variant interpretations. We found that 5.7% of variants have conflicting interpretations (COIs) reported, and the vast majority of interpretation conflicts arise for variants of uncertain significance (VUS). As many as 78% of clinically relevant genes harbor variants with COIs, and genes with high COI rates tended to have more exons and longer transcripts, with a greater proportion of genes linked to several distinct conditions. The enrichment analysis of COI-enriched genes revealed that the products of these genes are involved in cardiac disorders, muscle development, and function. To improve diagnoses, we believe that specific variant interpretation rules could be developed for such genes. Additionally, our findings underscore the need for the publication of variant pathogenicity evidence and the importance of considering every variant as VUS unless proven otherwise. Full article

Germline BRCA1/2 alteration has been linked to an increased risk of hereditary breast and ovarian cancer syndromes. As a result, genetic testing, based on NGS, allows us to identify a high number of variants of uncertain significance (VUS) or conflicting interpretation of pathogenicity (CIP) variants. The identification of CIP/VUS is often considered inconclusive and clinically not actionable for the patients’ and unaffected carriers’ management. In this context, their assessment and classification remain a significant challenge. The aim of the study was to investigate whether the in silico prediction tools (PolyPhen-2, SIFT, Mutation Taster and PROVEAN) could predict the potential clinical impact and significance of BRCA1/2 CIP/VUS alterations, eventually impacting the clinical management of Breast Cancer subjects. In a cohort of 860 BC patients, 10.6% harbored BRCA1 or BRCA2 CIP/VUS alterations, mostly observed in BRCA2 sequences (85%). Among them, forty-two out of fifty-five alterations were predicted as damaging, with at least one in silico that used tools. Prediction agreement of the four tools was achieved in 45.5% of patients. Moreover, the highest consensus was obtained in twelve out of forty-two (28.6%) mutations by considering three out of four in silico algorithms. The use of prediction tools may help to identify variants with a potentially damaging effect. The lack of substantial agreement between the different algorithms suggests that the bioinformatic approaches should be combined with the personal and family history of the cancer patients. Full article

Background: MUTYH germline monoallelic variants have been detected in a number of patients affected by breast/ovarian cancer or endometrial cancer, suggesting a potential susceptibility role, though their significance remains elusive since the disease mechanism is normally recessive. Hence, the aim of this research was to explore the hypothesis that a second hit could have arisen in the other allele in the tumor tissue. Methods: we used Sanger sequencing and immunohistochemistry to search for a second MUTYH variant in the tumoral DNA and to assess protein expression, respectively. Results: we detected one variant of unknown significance, one variant with conflicting interpretation of pathogenicity and three benign/likely benign variants; the MUTYH protein was not detected in the tumor tissue of half of the patients, and in others, its expression was reduced. Conclusions: our results fail to demonstrate that germinal monoallelic MUTYH variants increase cancer risk through a LOH (loss of heterozygosity) mechanism in the somatic tissue; however, the absence or partial loss of the MUTYH protein in many tumors suggests its dysregulation regardless of MUTYH genetic status. Full article

POT1 (Protection of Telomeres 1) is a key component of the six-membered shelterin complex that plays a critical role in telomere protection and length regulation. Germline variants in the POT1 gene have been implicated in predisposition to cancer, primarily to melanoma and chronic lymphocytic leukemia (CLL). We report the identification of POT1 p.(I78T), previously ranked with conflicting interpretations of pathogenicity, as a founder pathogenic variant among Ashkenazi Jews (AJs) and describe its unique clinical landscape. A directed database search was conducted for individuals referred for genetic counselling from 2018 to 2023. Demographic, clinical, genetic, and pathological data were collected and analyzed. Eleven carriers, 25 to 67 years old, from ten apparently unrelated families were identified. Carriers had a total of 30 primary malignancies (range 1–6); nine carriers (82%) had recurrent melanoma between the ages of 25 and 63 years, three carriers (27%) had desmoid tumors, three (27%) had papillary thyroid cancer (PTC), and five women (63% of female carriers) had breast cancer between the ages of 44 and 67 years. Additional tumors included CLL; sarcomas; endocrine tumors; prostate, urinary, and colorectal cancers; and colonic polyps. A review of a local exome database yielded an allelic frequency of the variant of 0.06% among all ethnicities and of 0.25% in AJs. A shared haplotype was found in all carriers tested. POT1 p.(I78T) is a founder disease-causing variant associated with early-onset melanoma and additional various solid malignancies with a high tumor burden. We advocate testing for this variant in high-risk patients of AJ descent. The inclusion of POT1 in germline panels for various types of cancer is warranted. Full article

Cutaneous T-cell lymphoma (CTCL) is a devastating, potentially fatal T-lymphocyte malignancy affecting the skin. Despite all efforts, the etiology of this disease remains unknown. Infectious agents have long been suspected as factors or co-factors in CTCL pathogenesis. This review deals with the panel of bacterial and viral pathogens that have been investigated so far in an attempt to establish a potential link between infection/carriage and CTCL development. A special focus is given to a recently discovered human protoparvovirus, namely the cutavirus (CutaV), which has emerged as a plausible CTCL etiological agent. Available evidence in support of this hypothesis as well as alternative interpretations and uncertainties raised by some conflicting data are discussed. The complexity and multifacetedness of the Parvoviridae family of viruses are illustrated by presenting another protoparvovirus, the rat H-1 parvovirus (H-1PV). H-1PV belongs to the same genus as the CutaV but carries considerable potential for therapeutic applications in cutaneous lymphoma. Full article

The incidence of cystic fibrosis (CF) and the spectrum of cystic fibrosis transmembrane conductance regulator (CFTR) gene variants differ among geographic regions. Differences in CF carrier distribution are also reported among Italian regions. We described the spectrum of the CFTR variants observed in a large group of subjects belonging from central–southern Italy. We also provide a predictive evaluation of the novel variants identified. CFTR screening was performed in a south–central Italian cohort of 770 subjects. We adopted a next-generation sequencing (NGS) approach using the Devyser CFTR NGS kit on the Illumina MiSeq System coupled with Amplicon Suite data analysis. Bioinformatics evaluation of the impact of novel variants was described. Overall, the presence of at least one alternative allele in the CFTR gene was recorded for 23% of the subjects, with a carrier frequency of CF pathogenic variants of 1:12. The largest sub-group corresponded to the heterozygous carriers of a variant with a conflicting interpretation of pathogenicity. The common CFTR p.(Phe508del) pathogenic variants were identified in 37% of mutated subjects. Bioinformatics prediction supported a potential damaging effect for the three novel CFTR variants identified: p.(Leu1187Phe), p.(Pro22Thr), and c.744-3C > G. NGS applied to CF screening had the benefit of: effectively identifying asymptomatic carriers. It lies in a wide overview of CFTR variants and gives a comprehensive picture of the carrier prevalence. The identification of a high number of unclassified variants may represent a challenge whilst at the same time being of interest and relevance for clinicians. Full article

Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL 1.0.0, a machine learning (ML)-based software for the interpretation of rare BRCA1 and BRCA2 germline variants. MARGINAL software classifies variants into three categories, namely, (likely) pathogenic, of uncertain significance and (likely) benign, implementing the criteria established by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP). We first annotated BRCA1 and BRCA2 variants using various sources. Then, we automatically implemented the ACMG-AMP criteria, and we finally constructed the ML model for variant classification. To maximize accuracy, we compared the performance of eight different ML algorithms in a classification scheme based on a serial combination of two classifiers. The model showed high predictive abilities with maximum accuracy of 92% and 98%, recall of 92% and 98% and specificity of 90% and 98% for the first and second classifiers, respectively. Our results indicate that using a gene and disease-specific ML automated software for clinical variant evaluation can minimize conflicting interpretations. Full article

ClinVar is a web platform that stores ∼789,000 genetic associations with complex diseases. A partial set of these cataloged genetic associations has challenged clinicians and geneticists, often leading to conflicting interpretations or uncertain clinical impact significance. In this study, we addressed the (re)classification of genetic variants by AmazonForest, which is a random-forest-based pathogenicity metaprediction model that works by combining functional impact data from eight prediction tools. We evaluated the performance of representation learning algorithms such as autoencoders to propose a better strategy. All metaprediction models were trained with ClinVar data, and genetic variants were annotated with eight functional impact predictors cataloged with SnpEff/SnpSift. AmazonForest implements the best random forest model with a one hot data-encoding strategy, which shows an Area Under ROC Curve of ≥0.93. AmazonForest was employed for pathogenicity prediction of a set of ∼101,000 genetic variants of uncertain significance or conflict of interpretation. Our findings revealed ∼24,000 variants with high pathogenic probability ($R{F}_{prob}\ge 0.9$). In addition, we show results for Alzheimer’s Disease as a demonstration of its application in clinical interpretation of genetic variants in complex diseases. Lastly, AmazonForest is available as a web tool and R object that can be loaded to perform pathogenicity predictions. Full article

Joubert syndrome (OMIM #213300) is a rare neurodevelopmental disease characterized by abnormal breathing patterns, intellectual impairment, ocular findings, renal cysts, and hepatic fibrosis. It is classified as a ciliopathy disease, where cilia function or structure in various organs are affected. Here, we report a 17-year-old male whose main clinical findings are oculomotor apraxia and truncal ataxia. Magnetic resonance imaging revealed the characteristic molar tooth sign of Joubert syndrome. He also has obsessive–compulsive disorder concomitantly, which is not a known feature of Joubert syndrome. Molecular genetic analysis revealed a homozygous c.2106G>A (p.(Thr702=)) variation in the Abelson helper integration 1 (AHI1) gene and another homozygous c.1739C>T (p.Thr580Ile) variation in the coiled-coil and C2 domain-containing protein 1A (CC2D1A) gene. Even though certain AHI1 variations were previously associated with Joubert syndrome (JS), c.2106G>A (p.(Thr702=)) was only reported in one patient in trans with another known pathogenic JS variant. The CC2D1A c.1739C>T (p.Thr580Ile) variation, on the other hand, has been reported to cause autosomal recessive nonsyndromic mental retardation, but there are conflicting interpretations about its pathogenicity. Overall, to our knowledge, this is the first patient representing a severe ciliopathy phenotype caused by a homozygous synonymous AHI1 variation. Further investigations should be performed to determine any involvement of the CC2D1A gene in ciliopathy phenotypes such as Joubert syndrome. Full article