In silico identification of genetic variants in glucocerebrosidase (GBA) gene involved in Gaucher's disease using multiple software tools

Phenotypic consequences of GBA1 pathological variant R463C (p.R502C)

Gaucher disease (GD) is an autosomal recessively inherited lysosomal storage disorder caused by biallelic pathological variants in the GBA1 gene. Patients present along a broad clinical spectrum, and phenotypes are often difficult to predict based on genotype alone. The variant R463C (p.Arg502Cys) exemplifies this challenge. To better characterize its different clinical presentations, we examined the records of 25 current and historical patients evaluated at the National Institutes of Health. Nine patients were classified as GD1, 14 were classified as GD3, and two had an ambiguous diagnosis between GD1 and GD3. In addition, we reviewed the published literature in PubMed and Web of Science through December 2023, identifying 62 cases with an R463C variant from 18 countries. Within the NIH cohort, the most common second variants were N370S (p.N409S) and L444P (p.L483P). R463C/L444P was encountered in patients with GD1 and GD3 in both the NIH cohort and worldwide. In the literature, R463C/R463C was also reported in both GD1 and GD3, although sparse phenotypic information was shared. Often the phenotype reflected what might be predicted for the second mutant allele. This diversity of phenotypes emphasizes the need for longitudinal follow-up to assess symptom development and neurological involvement.

Genotyping, in silico screening and molecular dynamics simulation of SNPs of MGMT and ERCC1 gene in lung cancer patients treated with platinum-based doublet chemotherapy

Lung cancer, the leading cause of death worldwide, arises from an intricate combination of genetic and environmental factors. Genetic variations can influence the chemotherapeutic response of lung cancer patients in DNA repair genes. This study examines the response to platinum-based drugs among lung cancer patients of North Indian descent who possess genetic variations in the MGMT and ERCC1 genes. P CR-RFLP method was used for genotypic analysis. MedCalc statistical software was used to calculate odds ratios and Median Survival Time (MST). GROMACS software was used to perform Molecular dynamic simulation. ADCC Patients revealed a significant association with MGMT in the heterozygous genotype (HR= 1.56, p=0.02) and also with ERCC1 in both mutant and combined variants (HR= 1.25, p=0.01; HR=0.78, p=0.03). SQCC subjects harbouring ERCC1 polymorphism also reported a 2-fold increase in hazard ratio and a corresponding decrease in survival time for heterozygous and combined variants (HR= 2.55, p=0.02; HR 2.33, p=0.01, respectively). MD simulation results demonstrate a lower RMSD, stable radius of gyration, and lower RMSF, indicating the mutated MGMT protein is more stable than the wild. Further, the docking score for DNA-Wild and DNA-L84F mutants are -201.6 and -131.8, respectively. MD Simulation of the complexes further validated the results. Our study concludes that MGMT and ERCC1 polymorphisms are associated with decreased overall survival. Further, computational analysis of MGMT (rs12917) polymorphism revealed that mutated MGMT cannot bind properly to the DNA and hence cannot properly repair DNA, resulting in lower overall survival.Communicated by Ramaswamy H. Sarma.

A scientific pharmacognosy on Gaucher's disease: an in silico analysis

From ancient times, studies on herbal medicine and pharmacognosy have increased gradually worldwide, due to the increased side effects, adverse drug reactions, and charge lines of modern medicines. Plants are well known for their medicinal effects and nutritional values. They contain bioactive compounds which display a wide spectrum of therapeutic effects. Gaucher's disease (GD) is a rare autosomal recessively inherited metabolic disorder caused due to the defect in Glucosylceramidase beta gene coding for the enzyme acid-β-glucosidase in humans. We revealed the profound binding efficiency of five selected bioactive compounds from different plants against the main enzyme acid-β-glucosidase responsible for GD through molecular docking. An in silico approach along with the ADMET profiles of phytocompounds was done using the Schrodinger software. The preventive measure of GD leads to side effects, inaccessible and unaffordable which put forth the emergence of phytocompounds which have fewer toxic effects, and one such compound is β-D-Glucopyranose with the best docking score (-10.28 kcal/mol) and an excellent binding affinity than other ligands, which could be further analyzed for stability using molecular dynamics study and in vitro. Being a dietary supplement, these compounds could be prepared in any form of formulation as a drug.

BRCA1/2 variants of unknown significance in hereditary breast and ovarian cancer (HBOC) syndrome: looking for the hidden meaning

Hereditary breast and ovarian cancer syndrome is caused by germline mutations in BRCA1/2 genes. These genes are very large and their mutations are heterogeneous and scattered throughout the coding sequence. In addition to the above-mentioned mutations, variants of uncertain/unknown significance (VUSs) have been identified in BRCA genes, which make more difficult the clinical management of the patient and risk assessment. In the last decades, several laboratories have developed different databases that contain more than 2000 variants for the two genes and integrated strategies which include multifactorial prediction models based on direct and indirect genetic evidence, to classify the VUS and attribute them a clinical significance associated with a deleterious, high-low or neutral risk. This review provides a comprehensive overview of literature studies concerning the VUSs, in order to assess their impact on the population and provide new insight for the appropriate patient management in clinical practice.

Identification of a novel HEXB Mutation in an Iranian Family with suspected patient to GM2-gangliosidoses

Sandhoff disease is one of the GM2-gangliosidoses which is caused by a mutation in the HEXB preventing the breakdown of GM2-ganglioside. We report a novel HEXB variant in a family with a history of a dead girl with Sandhoff disease which was not found in controls.

Determining the pathogenicity of CFTR missense variants: Multiple comparisons of in silico predictors and variant annotation databases

Pathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR) are responsible for cystic fibrosis (CF), the commonest monogenic autosomal recessive disease, and CFTR-related disorders in infants and youth. Diagnosis of such diseases relies on clinical, functional, and molecular studies. To date, over 2,000 variants have been described on CFTR (~40% missense). Since few of them have confirmed pathogenicity, in silico analysis could help molecular diagnosis and genetic counseling. Here, the pathogenicity of 779 CFTR missense variants was predicted by consensus predictor PredictSNP and compared to annotations on CFTR2 and ClinVar. Sensitivity and specificity analysis was divided into modeling and validation phases using just variants annotated on CFTR2 and/or ClinVar that were not in the validation datasets of the analyzed predictors. After validation phase, MAPP and PhDSNP achieved maximum specificity but low sensitivity. Otherwise, SNAP had maximum sensitivity but null specificity. PredictSNP, PolyPhen-1, PolyPhen-2, SIFT, nsSNPAnalyzer had either low sensitivity or specificity, or both. Results showed that most predictors were not reliable when analyzing CFTR missense variants, ratifying the importance of clinical information when asserting the pathogenicity of CFTR missense variants. Our results should contribute to clarify decision making when classifying the pathogenicity of CFTR missense variants.

Computational modelling approaches as a potential platform to understand the molecular genetics association between Parkinson's and Gaucher diseases

Gaucher's disease (GD) is a genetic disorder in which glucocerebroside accumulates in cells and specific organs. It is broadly classified into type I, type II and type III. Patients with GD are at high risk of Parkinson's disease (PD), and the clinical and pathological presentation of GD patients with PD is almost identical to idiopathic PD. Several experimental models like cell culture, animal models, and transgenic mice models were used to understand the molecular mechanism behind GD and PD association; however, such mechanism remains unclear. In this context, based on literature reports, we identified the most common mutations K198T, E326K, T369M, N370S, V394L, D409H, L444P, and R496H, in the Glucosylceramidase (GBA) protein that are known to cause GD1, and represent a risk of developing PD. However, to date, no computational analyses have designed to elucidate the potential functional role of GD mutations with increased risk of PD. The present computational pipeline allows us to understand the structural and functional significance of these GBA mutations with PD. Based on the published data, the most common and severe mutations were E326K, N370S, and L444P, which further selected for our computational analysis. PredictSNP and iStable servers predicted L444P mutant to be the most deleterious and responsible for the protein destabilization, followed by the N370S mutation. Further, we used the structural analysis and molecular dynamics approach to compare the most frequent deleterious mutations (N370S and L444P) with the mild mutation E326K. The structural analysis demonstrated that the location of E326K and N370S in the alpha helix region of the protein whereas the mutant L444P was in the starting region of the beta sheet, which might explain the predicted pathogenicity level and destabilization effect of the L444P mutant. Finally, Molecular Dynamics (MD) at 50 ns showed the highest deviation and fluctuation pattern in the L444P mutant compared to the two mutants E326K and N370S and the native protein. This was consistent with more loss of intramolecular hydrogen bonds and less compaction of the radius of gyration in the L444P mutant. The proposed study is anticipated to serve as a potential platform to understand the mechanism of the association between GD and PD, and might facilitate the process of drug discovery against both GD and PD.

A novel p.L216I mutation in the glucocerebrosidase gene is associated with Parkinson's disease in Han Chinese patients

OBJECTIVES

Pathogenic mutations in the glucocerebrosidase (GBA) gene are associated with Parkinson's disease (PD), of which L444P and N370S are the most frequently observed in patients with PD. The aim of this study was to systematically explore variations in the coding regions of GBA in Han Chinese patients with PD, as well as to expand the GBA mutation spectrum.

MATERIAL AND METHODS

A total of 213 Han Chinese patients with PD and 348 controls were enrolled in the study. Whole coding regions of GBA were captured and sequenced by target region sequencing. Sanger sequencing was also used to confirm the identified variants.

RESULTS

We identified a novel variant (c. C646A; p.L216I; NM_001171811.1) of GBA in two unrelated patients, which was not observed in the controls. Both patients had early-onset PD and neither exhibited any motor-related symptoms. However, we did not find an L444P or N370S mutations in our patients.

CONCLUSIONS

The p.L216I mutation is a novel GBA mutation, which we identified in two Han Chinese patients with PD. The patients exhibited similar characteristics, which differed from those seen in patients with other GBA mutations. Future work is needed to investigate this mutation further, as well as larger cohort studies to explore other GBA mutations associated with PD in the Han Chinese and in other populations.

Genetic analysis of CLDN14 in the Chinese population affected with non-syndromic hearing loss

OBJECTIVE

The CLDN14 gene, encoding the tight junction protein Claudin-14, has been proposed as a candidate causative gene affecting autosomal recessive non-syndromic hearing loss (ARNSHL). Genetic analysis of nonsynonymous single-nucleotide variations (nsSNVs) in CLDN14 has been performed in different populations. The role of CLDN14 nsSNVs in contributing to hearing loss in Chinese populations would be investigated in this study.

METHODS

Target screening for CLDN14 variations were conducted in 500 unrelated patients diagnosed with non-syndromic hearing loss (NSHL).

RESULTS

No reported pathogenic CLDN14 nsSNVs in heterozygote or homozygote were detected in this study, however, we identified 4 heterozygous nsSNVs [c.11C > T, p.(Thr4Met); c.16G > A, p.(Val6Met); c.68T > C, p.(Ile23Thr); c.367A > C, p.(Thr123Pro)] in CLDN14. The 4 nsSNVs are located at claudin-14 transmembrane domains, but assessed to be poorly conservative and non-pathogenic via multiple in silico algorithms. The structure-based analysis also suggested that the 4 nsSNVs had less structural and functional impact on claudin-14.

CONCLUSION

Our findings indicated that CLDN14 might not be a major causative gene for NSHL in Chinese populations, which would contribute to fully understanding the genetic cause of NSHL in the East Asian populations.

KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment

BACKGROUND

Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the Kir6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic β cell KATP channel respectively with a critical role in insulin secretion and glucose homeostasis. TCF7L2 encodes a transcription factor expressed in pancreatic β cells that regulates insulin production and processing. Because mutations of these genes could affect insulin secretion stimulated by sulfonylureas, the aim of this study is to assess associations between molecular variants of KCNJ11, ABCC8 and TCF7L2 genes and response to sulfonylurea treatment and to predict their potential functional effects.

METHODS

Based on a comprehensive literature search, we found 13 pharmacogenetic studies showing that single nucleotide polymorphisms (SNPs) located in KCNJ11: rs5219 (E23K), ABCC8: rs757110 (A1369S), rs1799854 (intron 15, exon 16 -3C/T), rs1799859 (R1273R), and TCF7L2: rs7903146 (intron 4) were significantly associated with responses to sulfonylureas. For in silico bioinformatics analysis, SIFT, PolyPhen-2, PANTHER, MutPred, and SNPs3D were applied for functional predictions of 36 coding (KCNJ11: 10, ABCC8: 24, and TCF7L2: 2; all are missense), and HaploReg v4.1, RegulomeDB, and Ensembl's VEP were used to predict functions of 7 non-coding (KCNJ11: 1, ABCC8: 1, and TCF7L2: 5) SNPs, respectively.

RESULTS

Based on various in silico tools, 8 KCNJ11 missense SNPs, 23 ABCC8 missense SNPs, and 2 TCF7L2 missense SNPs could affect protein functions. Of them, previous studies showed that mutant alleles of 4 KCNJ11 missense SNPs and 5 ABCC8 missense SNPs can be successfully rescued by sulfonylurea treatments. Further, 3 TCF7L2 non-coding SNPs (rs7903146, rs11196205 and rs12255372), can change motif(s) based on HaploReg v4.1 and are predicted as risk factors by Ensembl's VEP.

CONCLUSIONS

Our study indicates that a personalized medicine approach by tailoring sulfonylurea therapy of T2D patients according to their genotypes of KCNJ11, ABCC8, and TCF7L2 could attain an optimal treatment efficacy.

In silico analysis of deleterious single nucleotide polymorphisms in human BUB1 mitotic checkpoint serine/threonine kinase B gene

One of the major challenges in the analysis of human genetic variation is to distinguish mutations that are functionally neutral from those that contribute to disease. BubR1 is a key protein mediating spindle-checkpoint activation that plays a role in the inhibition of the anaphase-promoting complex/cyclosome (APC/C), delaying the onset of anaphase and ensuring proper chromosome segregation. Owing to the importance of BUB1B gene in mitotic checkpoint a functional analysis using different in silico approaches was undertaken to explore the possible associations between genetic mutations and phenotypic variation. In this work we found that 3 nsSNPs I82N, P334L and R814H have a functional effect on protein function and stability. A literature search revealed that R814H was already implicated in human diseases. Additionally, 2 SNPs in the 5' UTR region was predicted to exhibit a pattern change in the internal ribosome entry site (IRES), and eight MicroRNA binding sites were found to be highly affected due to 3' UTR SNPs. These in silico predictions will provide useful information in selecting the target SNPs that are likely to have functional impact on the BUB1B gene.

Why individual thermo sensation and pain perception varies? Clue of disruptive mutations in TRPVs from 2504 human genome data

Every individual varies in character and so do their sensory functions and perceptions. The molecular mechanism and the molecular candidates involved in these processes are assumed to be similar if not same. So far several molecular factors have been identified which are fairly conserved across the phylogenetic tree and are involved in these complex sensory functions. Among all, members belonging to Transient Receptor Potential (TRP) channels have been widely characterized for their involvement in thermo-sensation. These include TRPV1 to TRPV4 channels which reveal complex thermo-gating behavior in response to changes in temperature. The molecular evolution of these channels is highly correlative with the thermal response of different species. However, recent 2504 human genome data suggest that these thermo-sensitive TRPV channels are highly variable and carry possible deleterious mutations in human population. These unexpected findings may explain the individual differences in terms of complex sensory functions.

Value of predictive bioinformatics in inherited metabolic diseases

Typically, inherited metabolic diseases arise from point mutations in genes encoding metabolic enzymes. Although some of these mutations directly affect amino acid residues in the active sites of these enzymes, the majority do not. It is now well accepted that the majority of these disease-associated mutations exert their effects through alteration of protein stability, which causes a reduction in enzymatic activity. This finding suggests a way to predict the severity of newly discovered mutations. In silico prediction of the effects of amino acid sequence alterations on protein stability often correlates with disease severity. However, no stability prediction tool is perfect and, in general, better results are obtained if the predictions from a variety of tools are combined and then interpreted. In addition to predicted alterations to stability, the degree of conservation of a particular residue can also be a factor which needs to be taken into account: alterations to highly conserved residues are more likely to be associated with severe forms of the disease. The approach has been successfully applied in a variety of inherited metabolic diseases, but further improvements are necessary to enable robust translation into clinically useful tools.