Characterizing the pathogenicity of genetic variants: the consequences of context.
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ABSTRACT:
SUBMITTER: Ciesielski TH
PROVIDER: S-EPMC10776585 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Publications
Characterizing the pathogenicity of genetic variants: the consequences of context.
Ciesielski Timothy H TH Sirugo Giorgio G Iyengar Sudha K SK Williams Scott M SM
NPJ genomic medicine 20240109 1
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Project description:Advancements in genetic screening have generated massive amounts of data on genetic variation; however, a lack of clear pathogenic stratification has left most variants classified as being of unknown significance. This is a critical limitation for translating genetic data into clinical practice. Genetic screening is currently recommended in the guidelines for diagnosis and treatment of cardiac channelopathies, which are major contributors to sudden cardiac death in young people. We propose to characterize the pathogenicity of genetic variants associated with cardiac channelopathies using a stratified scoring system. The development of this system was considered by using all of the tools currently available to define pathogenicity. The use of this scoring system could help clinicians to understand the limitations of genetic associations with a disease, and help them better define the role that genetics can have in their clinical routine.
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Project description:Mutations in the leucine-rich repeat kinase 2 (LRRK2) have been known to be a major genetic component affecting Parkinson's disease (PD). However, the pathogenicity of many of the LRRK2 variants is unclear because they have been detected in single patients or also in patients and controls. Here, we selected 5 exonic variants (L1165P, T1410M, M1646T, L2063X, and Y2189C) from each of the protein domain of LRRK2 and analysed their possible association with pathogenicity using in vitro functional assays. Point mutations representing each of these variants were incorporated into the LRRK2 gene, and functional aspects such as the percentage of cell survival upon application of stress and kinase activity were measured. Our results showed that all 5 variants had a significantly negative effect on the survival of cells, in both presence and absence of stress, as compared to the wild-type. In addition, there was also a slight increase in kinase activity in most of the variants in comparison to the wild-type. A negative correlation between cell survival and kinase activity was observed. These data suggest that most of the variants despite being located in different domains of LRRK2 appear to exert a potential pathogenic effect possibly through an increased kinase activity, supporting a gain of function mechanism.
| S-EPMC4363499 | biostudies-literature
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that posttranscriptionally regulate the expression of most genes. They are involved in regulating many physiological processes, and aberrations in the levels of different miRNAs play an important role in the development of many diseases, including autoimmune diseases, neuropsychiatric diseases, and cancers. Although miRNAs are being intensively studied and levels of many miRNAs are either specifically increased or decreased in particular diseases, very little is known about the genetic variations of miRNA genes and their impact on the functioning of miRNA genes and human diseases. To shed more light on the potential effects of genetic variants in miRNA genes, we review here representative examples of SNPs, mutations linked to Mendelian diseases, and cancer somatic mutations located in miRNA genes and discuss their potential effects on the expression of miRNA genes, i.e., the structure and processing of miRNA precursors, the levels of generated miRNAs, miRNA target recognition/silencing, and impact on human diseases.
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Project description:Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since >90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors.
| S-EPMC5886469 | biostudies-literature
Project description:Current methods for annotating and interpreting human genetic variation tend to exploit a single information type (for example, conservation) and/or are restricted in scope (for example, to missense changes). Here we describe Combined Annotation-Dependent Depletion (CADD), a method for objectively integrating many diverse annotations into a single measure (C score) for each variant. We implement CADD as a support vector machine trained to differentiate 14.7 million high-frequency human-derived alleles from 14.7 million simulated variants. We precompute C scores for all 8.6 billion possible human single-nucleotide variants and enable scoring of short insertions-deletions. C scores correlate with allelic diversity, annotations of functionality, pathogenicity, disease severity, experimentally measured regulatory effects and complex trait associations, and they highly rank known pathogenic variants within individual genomes. The ability of CADD to prioritize functional, deleterious and pathogenic variants across many functional categories, effect sizes and genetic architectures is unmatched by any current single-annotation method.
| S-EPMC3992975 | biostudies-literature
Project description:BackgroundLeft ventricular non-compaction (LVNC) is a rare cardiomyopathy. Many genetic variants have been associated with LVNC. However, the number of the previous LVNC-associated variants that are common in the background population remains unknown. The aim of this study was to provide an updated list of previously reported LVNC-associated variants with biologic description and investigate the prevalence of LVNC variants in healthy general population to find false-positive LVNC-associated variants.Methods and resultsThe Human Gene Mutation Database and PubMed were systematically searched to identify all previously reported LVNC-associated variants. Thereafter, the Exome Sequencing Project (ESP) and the Exome Aggregation Consortium (ExAC), that both represent the background population, was searched for all variants. Four in silico prediction tools were assessed to determine the functional effects of these variants. The prediction results of those identified in the ESP and ExAC and those not identified in the ESP and ExAC were compared. In 12 genes, 60 LVNC-associated missense/nonsense variants were identified. MYH7 was the predominant gene, encompassing 24 of the 60 LVNC-associated variants. The ESP only harbored nine and ExAC harbored 18 of the 60 LVNC-associated variants. In total, eight out of nine ESP-positive variants overlapped with the 18 variants identified in ExAC database.ConclusionsIn this article, we identified 9 ESP-positive and 18 ExAC-positive variants of 60 previously reported LVNC-associated variants, suggesting that these variants are not necessarily the monogenic cause of LVNC.
| S-EPMC4799875 | biostudies-literature
Project description:BackgroundWe aimed to provide a set of previously reported PAH-associated missense and nonsense variants, and evaluate the pathogenicity of those variants.MethodsThe Human Gene Mutation Database, PubMed, and Google Scholar were searched for previously reported PAH-associated genes and variants. Thereafter, both exome sequencing project and exome aggregation consortium as background population searched for previously reported PAH-associated missense and nonsense variants. The pathogenicity of previously reported PAH-associated missense variants evaluated by using four in silico prediction tools.ResultsIn total, 14 PAH-associated genes and 180 missense and nonsense variants were gathered. The BMPR2, the most frequent reported gene, encompasses 135 of 180 missense and nonsense variants. The exome sequencing project comprised 9, and the exome aggregation consortium counted 25 of 180 PAH-associated missense and nonsense variants. The TOPBP1 and ENG genes are unlikely to be the monogenic cause of PAH pathogenesis based on allele frequency in background population and prediction analysis.ConclusionThis is the first evaluation of previously reported PAH-associated missense and nonsense variants. The BMPR2 identified as the major gene out of 14 PAH-associated genes. Based on findings, the ENG and TOPBP1 gene are not likely to be the monogenic cause of PAH.
| S-EPMC6160702 | biostudies-literature
Project description:Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F(16) advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.
| S-EPMC3169520 | biostudies-literature
Project description:BackgroundSince the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This research analyzes the mutation trend in various RBD samples from Indonesia published in the Global Initiative on Sharing All Influenza Data (GISAID) database using genomic profiling.MethodPatients in Indonesia infected with SARS-CoV-2, whose samples have been published in genomic databases, were selected for this research. The collected data were processed for analysis following several bioinformatics protocols: visualization into phylogenetic trees, 3D rendering, and the assessment of mutational impact.ResultsIn Indonesia, there are 25 unique SARS-CoV-2 clades and 318 unique SARS-CoV-2 RBD mutations from the earliest COVID-19 sample to samples collected in 2022, with T478K being the most prevalent RBD mutation and 22B being the most abundant clade. The Omicron variant has a lower docking score, higher protein destabilization, and higher KD than the Delta variant and the original virus.ConclusionsThe study findings reveal a decreasing trend in virus pathogenicity as a potential trade-off to increase transmissibility via mutations in RBD over the years.
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Project description:Thoracic aortic aneurysm and dissection (TAAD) significantly impact cardiovascular morbidity and mortality. A large subset of TAAD cases, particularly those with an earlier onset, is linked to heritable genetic defects. Despite progress in characterizing genes associated with both syndromic and non-syndromic heritable TAAD, the causative gene remains unknown in most cases. Another important bottleneck in the correct and timely diagnosis of TAAD is the large proportion of variants of unknown significance (VUS) that are routinely encountered upon medical genetic testing. Reliable functional modeling data is required to accurately identify new causal genes and to determine the pathogenicity of VUS. To address this gap, our collaborative effort-comprising teams from Yale University, University of Kentucky, and Ghent University-explores a novel approach: modeling TAAD in zebrafish. Leveraging the unique advantages of this animal model promises to allow for accelerated variant pathogenicity assessment, ultimately enhancing patient care. In this review, we critically explore the currently available zebrafish-based approaches that can be used for testing pathogenicity of genes and variants related to TAAD, and we offer an outlook on the implementation of these strategies for clinical applications.
| S-EPMC11892108 | biostudies-literature