Biology subjects

Gorokhova, S.

Publications and source records attributed to Gorokhova, S..

5 recordsLinked to original sources

bioRxiv2024

Expert Panel Curation of 31 Genes in Relation to Limb Girdle Muscular Dystrophy

IntroductionLimb girdle muscular dystrophies (LGMDs) are a group of genetically heterogeneous autosomal conditions with some degree of phenotypic homogeneity. LGMD is defined as having onset >2 years of age with progressive proximal weakness, elevated serum creatine kinase levels and dystrophic features on muscle biopsy. Advances in massively parallel sequencing have led to a surge in genes linked to LGMD. MethodsThe ClinGen Muscular Dystrophies and Myopathies gene curation expert panel (MDM GCEP, formerly Limb Girdle Muscular Dystrophy GCEP) convened to evaluate the strength of evidence supporting gene-disease relationships (GDR) using the ClinGen gene-disease clinical validity framework to evaluate 31 genes implicated in LGMD. ResultsThe GDR was exclusively LGMD for 17 genes, whereas an additional 14 genes were related to a broader phenotype encompassing congenital weakness. Four genes (CAPN3, COL6A1, COL6A2, COL6A3) were split into two separate disease entities, based on each displaying both dominant and recessive inheritance patterns, resulting in curation of 35 GDRs. Of these, 30 (86%) were classified as Definitive, 4 (11%) as Moderate and 1 (3%) as Limited. Two genes, POMGNT1 and DAG1, though definitively related to myopathy, currently have insufficient evidence to support a relationship specifically with LGMD. ConclusionsThe expert-reviewed assertions on the clinical validity of genes implicated in LGMDs form an invaluable resource for clinicians and molecular geneticists. We encourage the global neuromuscular community to publish case-level data that help clarify disputed or novel LGMD associations.

genetics↗

bioRxiv2024

System-level analysis of genes mutated in muscular dystrophies reveals a functional pattern associated with muscle weakness distribution

Muscular dystrophies (MDs) are inherited genetic diseases causing weakness and degeneration of muscles. The distribution of muscle weakness differs between MDs, involving distal muscles or proximal muscles. While the mutations in most of the MD-associated genes lead to either distal or proximal onset, there are also genes whose mutations can cause both types of onsets. We hypothesized that the genes associated with different MD onsets code proteins with distinct cellular functions. To investigate this, we collected the MD-associated genes and assigned them to three onset groups: genes mutated only in distal onset dystrophies, genes mutated only in proximal onset dystrophies, and genes mutated in both types of onsets. We then systematically evaluated the cellular functions of these gene sets with computational strategies based on functional enrichment analysis and biological network analysis. Our analyses demonstrate that genes mutated in either distal or proximal onset MDs code proteins linked with two distinct sets of cellular processes. Interestingly, these two sets of cellular processes are relevant for the genes that are associated with both onsets. Moreover, the genes associated with both onsets display high centrality and connectivity in the network of muscular dystrophy genes. Our findings support the hypothesis that the proteins associated with distal or proximal onsets have distinct functional characteristics, whereas the proteins associated with both onsets are multifunctional.

bioinformatics↗

bioRxiv2020

An AI-powered blood test to detect cancer using nanoDSF

We describe a novel cancer diagnostic method based on plasma denaturation profiles obtained by a non-conventional use of Differential Scanning Fluorimetry. We show that 84 glioma patients and 63 healthy controls can be automatically classified using denaturation profiles with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool from a simple blood test.

cancer biology↗

bioRxiv2020

Splicing impact of deep exonic missense variants in CAPN3 explored systematically by minigene functional assay

Improving the accuracy of variant interpretation during diagnostic sequencing is a major goal for genomic medicine. In order to explore an often overlooked splicing effect of missense variants, we developed the functional assay ("minigene") for the majority of exons of CAPN3, the gene responsible for Limb Girdle Muscular Dystrophy (LGMD). By systematically screening 21 missense variants distributed along the gene, we found that eight clinically relevant missense variants located at a certain distance from the exon/intron borders (deep exonic missense variants) disrupted normal splicing of CAPN3 exons. Several recent machine learning based computational tools failed to predict splicing impact for the majority of these deep exonic missense variants, highlighting the importance of including variants of this type in the training sets during the future algorithm development. Overall, 24 variants in CAPN3 gene were explored, leading to the change in the ACMG classification of seven of them when results of the "minigene" functional assay were taken into account. Our findings reveal previously unknown splicing impact of several clinically important variants in CAPN3 and draw attention to the existence of deep exonic variants with a disruptive effect on gene splicing that could be overlooked by the current approaches in clinical genetics.

genetics↗

bioRxiv2019

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports.

In order to properly interpret the results of a diagnostic gene panel sequencing test, gene coverage needs to be taken into consideration. If coverage is too low, an additional re-sequencing test is needed to make sure that a pathogenic variant is not missed. To facilitate the interpretation of coverage data, we designed CovReport, a novel easy-to-use visualization tool. CovReport generates a concise coverage summary that allows one-glance assessment of the sequencing test performance. Both gene-level and exon-level coverage can be immediately appreciated and taken into consideration for further medical decisions. CovReport does not require complex installation and can thus be easily implemented in any diagnostic laboratory setting. A user-friendly interface generates a graphic summary of coverage that can be directly included in the diagnostic report. In addition to a stand-alone version, we also provide a command line version of CovReport that can be integrated into any bioinformatics pipeline. This flexible tool is now part of routine sequencing analysis at the Department of Medical Genetics at La Timone Hospital (Marseille, France).\n\nAvailability and implementationCovReport is available at http://jdotsoft.com/CovReport.php. It is implemented in Java and supported on Windows, Mac OS X and Linux.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC=\"FIGDIR/small/671511v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (29K):\norg.highwire.dtl.DTLVardef@8d77bborg.highwire.dtl.DTLVardef@1afcb9dorg.highwire.dtl.DTLVardef@60c0aborg.highwire.dtl.DTLVardef@942c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗