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The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes m...
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Purpose of Review
Prostate cancer is the most frequently diagnosed non-cutaneous malignancy of men in the USA; notably, the incidence is higher among men of African, followed by European and Asian ancestry. Germline mutations and, in particular, mutations in DNA damage repair genes (DDRGs) have been implicated in the pathogenesis of prostate cancer...
Citations
... These apoproteins are essential components of LDL and VLDL particles. Since this frameshift variant is absent from control populations (Genome Aggregation Database, 1000 Genomes Project, and Human Gene Mutation Database) [23][24][25] and segregated with a phenotype in 3 informative meiosis in the proband's family, the c.89_92dup variant was classified as pathogenic (PVS1, PM2, PP1 and PP4) according to the ACMG guidelines [26,27]. ...
Background
Familial hypercholesterolemia (FH) is a common inherited metabolic disease that causes premature atherosclerosis, cardiovascular disease, and even death at a young age. Approximately 95% of FH-causing genetic variants that have been identified are in the LDLR gene. However, only 10% of the FH population worldwide has been diagnosed and adequately treated, due to the existence of numerous unidentified variants, uncertainties in the pathogenicity scoring of many variants, and a substantial number of individuals lacking access to genetic testing.
Objective
The aim of this study was to identify a novel variant in the LDLR gene that causes FH in a Chinese family, thereby expanding the spectrum of FH-causing variants.
Methods
Patients were recruited from Beijing Anzhen Hospital, Capital Medical University. FH diagnosis was made according to the Dutch Lipid Clinical Network (DLCN) criteria. Whole-exome sequencing (WES) was conducted to identify the FH-causing variant in the proband, and amplicon sequencing was used to verify the variant in his family members.
Results
A three-generation Chinese family was recruited, and two FH patients were clinically diagnosed, both without known FH-causing variants. These two FH patients and another possible patient carried a novel variant, NC_000019.9(NM_000527.5):c.89_92dup (NP_000518.1:p.Phe32Argfs*21), in the ligand-binding domain of the low-density lipoprotein (LDL) receptor that led to a frameshift. The FH adults in the family showed severe clinical symptoms and statin therapy resistance.
Conclusion
This study identified a novel pathogenic LDLR variant, c.89_92dup, associated with severe FH clinical manifestations and statin therapy resistance.
... We curated a dataset of rare (allele frequency < 0.05) missense variants classified in ClinVar [8] as either Pathogenic or Benign with at least one star, or listed as disease-causing (DM) entries in the Human Gene Mutation Database (HGMD) [9]. Our dataset was restricted to variants that were newly added to these databases after the close of the CAGI6 Annotate-All-Missense challenge in October 2021. ...
... We created an evaluation dataset by incorporating variants from both the April 4, 2023 version of ClinVar [8], which contains both pathogenic and benign variants, and the 2023.1 Professional version of the Human Gene Mutation Database (HGMD) [9], which contains only pathogenic variants. ...
Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.
... LPL is located on vascular endothelial cells in adipose tissue, the heart, and muscles, hydrolyzing TG-rich lipoproteins, such as chylomicrons and very low-density lipoproteins (VLDL), facilitating their clearance from the blood (7). To date, 250 distinct variants have been reported in the LPL gene, among these the most common being missense/nonsense pathogenic variants (8,9). Diagnosis of LPL deficiency can be challenging due to variations in biochemical parameters and often overlapping phenotypes with other etiologically different HTGs (10). ...
Introduction
Hypertriglyceridemia (HTG) is a complex disorder caused by genetic and environmental factors that frequently results from loss-of-function variants in the gene encoding lipoprotein lipase (LPL). Heterozygous patients have a range of symptoms, while homozygous LPL deficiency presents with severe symptoms including acute pancreatitis, xanthomas, and lipemia retinalis.
Methods
We described the clinical characteristics of three Slovenian patients (an 8-year-old female, an 18-year-old man, and a 57-year-old female) and one Pakistani patient (a 59-year-old male) with LPL deficiency. We performed next-generation sequencing (NGS) targeting all coding exons and intron-exon boundaries of the LPL gene, and Sanger sequencing for variant confirmation. In addition, we performed a systematic literature review of all cases with three identified variants and described their clinical characteristics.
Results
Two Slovenian patients with a heterozygous pathogenic variant NM_000237.3:c.984G>T (p.Met328Ile) were diagnosed within the first three years of life and had triglyceride (TG) values of 16 and 20 mmol/L. An asymptomatic Pakistani patient with TG values of 36.8 mmol/L until the age of 44 years, was identified as heterozygous for a pathogenic variant NM_000237.3:c.724G>A (p.Asp242Asn). His TG levels dropped to 12.7 mmol/L on dietary modifications and by using fibrates. A Slovenian patient who first suffered from pancreatitis at the age of 18 years with a TG value of 34 mmol/L was found to be homozygous for NM_000237.3:c.337T>C (p.Trp113Arg).
Conclusions
Patients with LPL deficiency had high TG levels at diagnosis. Homozygous patients had worse outcomes. Good diet and medication compliance can reduce severity.
... (v3) (controls/biobanks subsets); the Leiden Open Variation Database (LOVD) version 2.0 and version 3.0; the Human Genetic Mutation Database (HGMD) Public version; and ClinVar (the websites of these resources can be found in the Web Resources section) (all accessed in February 2023). A biomedical literature search (MEDLINE/PubMed) using the term "PAX6" and focusing on articles between 2021 and 2023 was also undertaken [16][17][18][19][20]. We excluded duplicates and VUS (including "likely disease-causing mutation with questionable pathogenicity" (DM?) in HGMD), and then categorized the remaining variants into: "Primary Dataset Neutral" and "Primary Dataset Disease" (Fig. 1). ...
The PAX6 gene encodes a highly-conserved transcription factor involved in eye development. Heterozygous loss-of-function variants in PAX6 can cause a range of ophthalmic disorders including aniridia. A key molecular diagnostic challenge is that many PAX6 missense changes are presently classified as variants of uncertain significance. While computational tools can be used to assess the effect of genetic alterations, the accuracy of their predictions varies. Here, we evaluated and optimised the performance of computational prediction tools in relation to PAX6 missense variants. Through inspection of publicly available resources (including HGMD, ClinVar, LOVD and gnomAD), we identified 241 PAX6 missense variants that were used for model training and evaluation. The performance of ten commonly used computational tools was assessed and a threshold optimization approach was utilized to determine optimal cut-off values. Validation studies were subsequently undertaken using PAX6 variants from a local database. AlphaMissense, SIFT4G and REVEL emerged as the best-performing predictors; the optimized thresholds of these tools were 0.967, 0.025, and 0.772, respectively. Combining the prediction from these top-three tools resulted in lower performance compared to using AlphaMissense alone. Tailoring the use of computational tools by employing optimized thresholds specific to PAX6 can enhance algorithmic performance. Our findings have implications for PAX6 variant interpretation in clinical settings.
... Variants were initially filtered based on frequency, focusing on rare variants with a Minor Allele Frequency (MAF) of ≤1% or unreported in the Non-Finnish European population (NFE) in the Genome Aggregation Database v2.1.1 (gnomAD; [28]). Pathogenic or likely pathogenic variants were defined as null variants (stop-gain, start loss, frameshift, canonical splice sites ±2 bp from exons) and missense variants reported as pathogenic/likely pathogenic in ClinVar [29] or in the Human Gene Mutation Database (HGMD) [30]. Emphasis was placed on well-known cancer genes [31], other putative cancer-related genes, and DNA repair genes [32] potentially associated with cancer predisposition (Supplementary Table S2). ...
Background: Primary bilateral uveal melanoma (BUM) is an exceptionally rare form of uveal melanoma (UM). This study aimed to explore the potential existence of a genetic predisposition towards the development of BUM. Methods: We employed an exome sequencing approach on germline DNA from four unrelated patients diagnosed with BUM, seeking pathogenic or likely pathogenic variants indicative of a genetic predisposition to UM. Results: None of the patients exhibited pathogenic variants in the BAP1 gene. However, loss-of-function (LoF) variants in the TERF2IP and BAX genes were identified in two of the BUM patients. For patients BUM1 and BUM2, no pathogenic/likely pathogenic variants of significant clinical relevance to BUM were found to warrant inclusion in this report. Conclusions: Our findings suggest the presence of yet-to-be-discovered genes that may contribute to UM predisposition, as evidenced by the absence of pathogenic variants in known UM predisposition genes among the four BUM patients studied. The TERF2IP and BAX genes emerge as noteworthy candidates for further investigation regarding their role in genetic predisposition to UM. Specifically, the potential role of UM as a candidate cancer within the spectrum of cancers linked to pathogenic variants in the TERF2IP gene and other genes associated with the shelterin complex warrants further examination. Additional functional studies are necessary to support or challenge this hypothesis.
... Mutations in the ITGA2B gene encoding the αIIb subunit were collected from the databases, like HGMD (www.hgmd.cf.ac.uk) 22 , Uniprot (www.uniprot.org) 23 , ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) ...
Integrin αIIbβ3 is the predominant receptor for fibrinogen which mediates platelet aggregation, an important step in hemostasis and thrombosis. Several mutations have been reported in the genes encoding αIIb and β3 subunits among patients with Glanzmann thrombasthenia, of which 177 are in the β-propeller domain. The two subunits form a heterodimer at the interface between β-propeller and β-I domains of αIIb and β3 respectively with their stability critical for intracellular trafficking, surface expression, and ligand binding. Our study was aimed at retrieving the β-propeller mutations from various databases and study structural variations due to select mutations upon interaction with fibrinogen using molecular docking and molecular dynamics. Mutations were studied for their impact on phenotypic severity, structural stability, and evolutionary conservation. Molecular docking analysis and molecular dynamics simulations were carried out for αIIb-β3 complexes as well as αIIbβ3-fibrinogen complexes; in particular, E355K structure had more deviations, fluctuations, and other changes which compromised its structural stability and binding affinity when compared to both wild-type and G401C structures. Our comprehensive in silico analysis clearly reiterates that mutations in the β-propeller are not only responsible for structural changes in this domain but also have implications on the overall structure and function of integrin αIIbβ3.
... The discovery of novel gene-disease associations relies on the identification of predicted deleterious genetic variants. Frameshift variants caused by small insertions and deletions (indels ≤50bp) are frequently categorized as predicted deleterious and they constitute the second most common class of variants underlying monogenic disorders (Stenson et al. 2020). The recommendation is therefore to apply "Very Strong" evidence of pathogenicity if the indel is in a gene where loss-of-function is a known mechanism of disease (Richards et al. 2015). ...
Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides “regional AF” (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10⁻⁴ and rAF>10⁻⁴) as “rAF-hi” indels. Notably, a high percentage of rare indels were “rAF-hi”, with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels’ parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.
... We included 142 genes from the merged signals of the genome-wide significant loci (P < 5 × 10 −8 ) from Jostins et al. [36], as well as 15 genes from the 95% credible set of the fine-mapping results by Huang et al. [35]. For the set of known PD genes, we extracted genes associated with PD from the Human Gene Mutation Database (HGMD) Professional v. 2022.4 [38], which is the largest database currently available of high-quality and manually curated pathogenic variants. We specifically used the HGMD disease-causing mutations with the highest confidence only based on experimental evidence (DM), resulting in the identification of 103 known PD genes. ...
... Afterwards, we searched these 25 LRRK2 variants in HGMD and found that 16 variants had been reported to be associated with PD at varying confidence levels (Additional file 2: Table S5) [38]. Among those, 6 variants (E334K, R793M, S1228T, R1325Q, G2019S, and Y2189C) were associated with PD and classified under the DM category. ...
... Previous studies have already reported L119P, S1228T, R1628P, M1646T, and Y2189C as PD risk variants [66][67][68][69], while I1371V has been shown to cause increased phosphorylation and aggregation of α-synuclein in neurons [70]. Additionally, P1542S is a common variant (gnomAD MAF = 0.03) and has been listed as a CD-associated polymorphism in HGMD [38]. E334K, R1325Q, and R1628P have been previously shown to increase the LRRK2-dependent Rab10 Thr73 phosphorylation, which is used as an indicator of increased LRRK2 kinase activity conferring higher risk of PD [48]. ...
Background
Inflammatory bowel disease (IBD) and Parkinson’s disease (PD) are chronic disorders that have been suggested to share common pathophysiological processes. LRRK2 has been implicated as playing a role in both diseases. Exploring the genetic basis of the IBD-PD comorbidity through studying high-impact rare genetic variants can facilitate the identification of the novel shared genetic factors underlying this comorbidity.
Methods
We analyzed whole exomes from the BioMe BioBank and UK Biobank, and whole genomes from a cohort of 67 European patients diagnosed with both IBD and PD to examine the effects of LRRK2 missense variants on IBD, PD and their co-occurrence (IBD-PD). We performed optimized sequence kernel association test (SKAT-O) and network-based heterogeneity clustering (NHC) analyses using high-impact rare variants in the IBD-PD cohort to identify novel candidate genes, which we further prioritized by biological relatedness approaches. We conducted phenome-wide association studies (PheWAS) employing BioMe BioBank and UK Biobank whole exomes to estimate the genetic relevance of the 14 prioritized genes to IBD-PD.
Results
The analysis of LRRK2 missense variants revealed significant associations of the G2019S and N2081D variants with IBD-PD in addition to several other variants as potential contributors to increased or decreased IBD-PD risk. SKAT-O identified two significant genes, LRRK2 and IL10RA, and NHC identified 6 significant gene clusters that are biologically relevant to IBD-PD. We observed prominent overlaps between the enriched pathways in the known IBD, PD, and candidate IBD-PD gene sets. Additionally, we detected significantly enriched pathways unique to the IBD-PD, including MAPK signaling, LPS/IL-1 mediated inhibition of RXR function, and NAD signaling. Fourteen final candidate IBD-PD genes were prioritized by biological relatedness methods. The biological importance scores estimated by protein–protein interaction networks and pathway and ontology enrichment analyses indicated the involvement of genes related to immunity, inflammation, and autophagy in IBD-PD. Additionally, PheWAS provided support for the associations of candidate genes with IBD and PD.
Conclusions
Our study confirms and uncovers new LRRK2 associations in IBD-PD. The identification of novel inflammation and autophagy-related genes supports and expands previous findings related to IBD-PD pathogenesis, and underscores the significance of therapeutic interventions for reducing systemic inflammation.
... PTCs introduce a stop codon within a gene's protein-coding region, prematurely terminating gene translation and producing truncated, non-functional proteins. Several debilitating and life-threatening conditions, such as cystic fibrosis and Duchenne muscular dystrophy, are caused by nonsense mutations (Stenson et al., 2020). In addition to inherited mutations, PTCs can originate from somatic mutations, causing diseases like cancer (Zhang et al., 2021). ...
... To faithfully restore protein synthesis from a PTC-containing gene, the sup-tRNA must be aminoacylated with the corresponding amino acid. The PTC-related diseases involve all three stop codons, which generally emerge from mutations of Arg, Gln, Ser, Glu, Tyr, Lys, Trp, Gly, Leu, and Cys codons (Stenson et al., 2020). Correction of each PTC would require a panel of sup-tRNAs with identities for each amino acid. ...
Suppressor transfer RNAs (sup-tRNAs) are receiving renewed attention for their promising therapeutic properties in treating genetic diseases caused by nonsense mutations. Traditionally, sup-tRNAs have been created by replacing the anticodon sequence of native tRNAs with a suppressor sequence. However, due to their complex interactome, considering other structural and functional tRNA features for design and engineering can yield more effective sup-tRNA therapies. For over 2 decades, the field of genetic code expansion (GCE) has created a wealth of knowledge, resources, and tools to engineer sup-tRNAs. In this Mini Review, we aim to shed light on how existing knowledge and strategies to develop sup-tRNAs for GCE can be adopted to accelerate the discovery of efficient and specific sup-tRNAs for medical treatment options. We highlight methods and milestones and discuss how these approaches may enlighten the research and development of tRNA medicines.
... Este cambio ha sido previamente descrito como mutación patogénica asociada a displasia cleidocraneal, en las bases de datos de mutaciones ClinVar-NCBI y HGMD (Human Gene Mutation Database) con ID CM992614. (Stenson et al., 2020). ...
Revista GICOS. Volumen 9, Número 1 (2024): enero-abril
