Pathogenic Single Nucleotide Polymorphisms Research Articles

The Possible Role of Progesterone Receptors in Prostate Cancer Incidences in the Iraqi Population.

Prostate cancer (PCa) is one of the leading diseases causing mortality. It comes in the third rank of common cancer types. It is considered extremely a complicated cancer type since it occurs in highly steroid-responsive and dependent tissues. Many factors are considered to play an important role in the disease progression of PCa, with some functioning at the molecular level. After applying the exclusion criteria, 200 patients who underwent proctectomy were included in this study. Following receiving patient consent, blood samples were withdrawn from patients, DNA was extracted, and precise polymerase chain reaction (PCR) amplification was conducted using specifically designed primers. The resulting amplicons were sequenced and analyzed. The progesterone receptor B (PGRB) DNA from patients showed four distinctive single-nucleotide polymorphisms (SNPs) at sites 11:101128812, 11:101128924, 11:101128949, and 11:101128986, which altered the amino acid sequences to Y>N, A>D, T>I, and C>R, respectively, compared to control. These SNPs resided in sensitive sites that either affected the control elements or promoted alterations in the protein configuration. This DNA change diminished the PGR gene function and promoted an imbalance in the encoded PGR protein structure and expression. Many factors may play a role in PCa manifestation, with steroids and progesterone initially noted as factors. Many studies have dealt with the hormonal effect on PCa; however, few have ultimately determined the molecular impact on disease progression. The presence of pathogenic SNPs in the enhancing region of the gene may impact the expression level of PGR. High or low expression levels may negatively affect gene function, which can be considered a reliable factor in prostate tumorigenesis.

Where do obesity and male infertility collide?

The parallel rise in obesity and male infertility in modern societies necessitates the identification of susceptibility genes underlying these interconnected health issues. In our study, we conducted a comprehensive search in the OMIM database to identify genes commonly associated with male infertility and obesity. Subsequently, we performed an insilico analysis using the REVEL algorithm to detect pathogenic single nucleotide polymorphisms (SNPs) in the coding region of these candidate genes. To validate our findings in vivo, we conducted a comprehensive analysis of SNPs and gene expression of candidate genes in 200 obese infertile subjects and 240 obese fertile individuals using ARMS-PCR. Additionally, we analyzed 20 fertile and 22 infertile obese individuals using Realtime-qPCR. By removing duplicated queries, we obtained 197 obesity-related genes and 102 male infertility-related genes from the OMIM database. Interestingly, the APOB gene was found in common between the two datasets. REVEL identified the rs13306194 variant as potentially pathogenic with a calculated score of 0.524. The study identified a significant association between the AA (P value = 0.001) genotype and A allele (P value = 0.003) of the APOB rs13306194 variant and infertility in obese men. APOB expression levels were significantly lower in obese infertile men compared to obese fertile controls (p < 0.01). Moreover, the AA genotype of rs13306194 APOB was associated with a significant decrease in APOB gene expression in obese infertile men (p = 0.05). There is a significant association between the Waist-to-Hip Ratio (WHR) and LH with infertility in the obese infertile group. These results are likely to contribute to a better understanding of the causes of male infertility and its association with obesity.

Pathogenic SNPs Affect Both RNA and DNA G-Quadruplexes' Responses to Ligands.

Single nucleotide polymorphisms (SNPs) are common genetic variations that are present in over 1% of the population and can significantly modify the structures of both DNA and RNA. G-quadruplex structures (G4) are formed by the superposition of tetrads of guanines. To date, the impact of SNPs on both G4 ligands' binding efficacies and specificities has not been investigated. Here, using a bioinformatically predicted G4 and SNPs found in the α-synuclein gene as a proof-of-concept, it was demonstrated that SNPs can modulate both DNA and RNA G4s' responses to ligands. Specifically, six widely recognized ligands (Phen-DC3, PDS, 360A, RHPS4, BRACO19, and TMPyP4) were shown to differentially affect both the structure and the polymerase stalling of the different SNPs. This work highlights the importance of choosing the appropriate G4 ligand when dealing with an SNP identified in a G-rich gene.

Ancient genome of the Chinese Emperor Wu of Northern Zhou

Emperor Wu (, Wudi) of the Xianbei-led Northern Zhou dynasty, named Yuwen Yong (, 543-578 CE), was a highly influential emperor who reformed the system of regional troops, pacified the Turks, and unified the northern part of the country. His genetic profile and physical characteristics, including his appearance and potential diseases, have garnered significant interest from the academic community and the public.In this study, we have successfully generated a 0.343×-coverage genome of Wudi with 1,011,419 single-nucleotide polymorphisms (SNPs) on the 1240k panel. By analyzing pigmentation-relevant SNPs and conducting cranial CT-based facial reconstruction, we have determined that Wudi possessed a typical East or Northeast Asian appearance. Furthermore, pathogenic SNPs suggest Wudi faced an increased susceptibility to certain diseases, such as stroke. Wudi shared the closest genetic relationship with ancient Khitan and Heishui Mohe samples and modern Daur and Mongolian populations but also showed additional affinity with Yellow River (YR) farmers. We estimated that Wudi derived 61% of his ancestry from ancientNortheast Asians (ANAs) and nearly one-third from YR farmer-related groups. This can likely be attributed to continuous intermarriage between Xianbei royal families, and local Han aristocrats.1,2 Furthermore, our study has revealed genetic diversities among available ancient Xianbei individuals from different regions, suggesting that the formation of the Xianbei was a dynamic process influenced by admixture with surrounding populations.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Investigating pathogenic SNP of PKCι in HCV-induced hepatocellular carcinoma

Hepatocellular carcinoma is a leading cause of cancer-related deaths due to its complexity in diagnosis, chemo-resistance, and aggressive nature. Identifying pathogenic single nucleotide polymorphism (SNP) in protein kinase C iota (PKCι) can be a potential biomarker in the prognosis and treatment of HCC. This study investigated the association between a SNP in PRKCI and the Pakistani population's hepatocellular carcinoma (HCC) risk. Obtained samples were first evaluated for ALT measurements and viral load quantification through reverse transcriptase-PCR. The PKCι nsSNP rs1199520604 was evaluated computationally by multiple consensus bioinformatics tools for predicting its potential deleterious effects. Its association with hepatitis C virus- (HCV) mediated HCC was then investigated through ARMS-PCR (Amplification Refractory Mutation System Polymerase Chain Reaction). SNP analysis of rs1199520604 was performed in 100 cases and 100 controls. Variant rs1199520604’s homozygous T genotype is a risk factor allele for the HCV-induced HCC (odds ratio: 4.13, relative risk: 2.01, P-value < 0.0001). The heterozygous genotype is determined to protect HCV patients from HCC development (P < 0.001). The study highlighted the disease association of variant rs1199520604 with HCV-induced HCC in the Pakistani populations. This variant, after further validation through high-throughput investigation on a larger cohort, has the potential to be translated at the clinical level.

WHOLE EXOME SEQUENCING OF A MULTIPLEX CROHN’S DISEASE FAMILY IDENTIFIES RARE ALTERATIONS IN PYGB ANDXRN2 AS POTENTIALLY HIGH IMPACT RISK VARIANTS OF DISEASE

Abstract BACKGROUND The study of multiplex Crohn’s disease (CD) families has played a critical role in our understanding of the disease, including the identification of the first recognized CD risk variants in NOD2, which remain among the highest impact genetic predispositions known. Since then, genome wide association studies have revealed over 200 additional inflammatory bowel disease (IBD) risk alleles. However, such technologies may miss low prevalence, high impact variants. We therefore have been studying multiplex CD families to identify additional novel variants of disease. METHODS A 3 generation family, including 5 CD subjects, 12 relatives, and 5 controls (spouses) underwent whole exome sequencing on the Illumina platform. Single nucleotide polymorphisms (SNPs) were identified, whose minor allele frequencies were &amp;lt;0.1% in all gnomAD subpopulations and were also predicted to be damaging, deleterious, or disease-causing by at least one of the pathogenicity prediction tools (PhyloP, SIFT, PolyPhen2, MutationTaster, LRT, and CADD). We selected the 5 CD diagnosed individuals, as well as a first degree relative of all 5 individuals (but who did not have CD) as the putative variant-carrying group. SNPs that were carried in this group, but were not found in the controls, were identified. Subjects for whom we did not have sufficient DNA to complete whole exome sequencing were excluded from analysis (Figure 1). RESULTS We found 32 rare, pathogenic SNPs shared among the variant-carrying group. After removing those that were also found in any of the 5 controls, we were left with 4 variants as described in Table 1. Of these, rs145974526 was also found in 3 non-CD relatives (1 adult and 2 children). rs369261067 was also identified in 3 non-CD relatives (2 adults and 1 child). The remaining two variants (rs150582502 and rs149199982) were present in only 1 additional relative, the adult offspring of a CD-affected subject. Both SNPs are found on chromosome 20, and these risk alleles are located in the PYGB and XRN2 genes, respectively. Of note, NOD2 variants were not identified in this family. DISCUSSION Based on our analysis, we identify SNPs rs150582502 and rs149199982 as possible private, rare, high impact variants for Crohn’s disease. PYGB (glycogen phosphorylase B) has been shown to promote cellular proliferation in multiple tumor types by regulation of the Wnt/β-Catenin pathway. XRN2 encodes 5'-3' exoribonuclease 2, which is involved in transcription termination. Studies of XRN2 have demonstrated its involvement in DNA repair, and alterations in the gene have been identified in various cancers. Additional functional work will be performed to further validate the role of these mutations. We are also in the process of analyzing additional multiplex IBD families and datasets for these SNPs, as well as for other potential novel variants of disease.

Structural impact of pathogenic SNPs on β-tubulin using molecular dynamics study

Single nucleotide polymorphisms (SNPs) in the TUBB1 (β-tubulin) gene have been implicated as the primary cause of macro thrombocytopenia. Therefore it is essential to identify the potential SNPs which are harmful to cause diseases such as macro thrombocytopenia. The impact caused by these variants on β-tubulin is twofold, both structural and functional. Multiple in-silico tools were used to scrutinise the most deleterious nsSNPs (non-synonymous SNPs) via sequence and structure-based approaches. Further, the β-tubulin protein model incorporating identified mutants was subjected to MD (molecular dynamic) simulations to analyse the impact on protein structure. A total of 2974 SNPs of TUBB1 were retrieved from various sources, and 32 nsSNPs were identified. By screening through sequence-based technique, 13 variants were detected as deleterious and further structure-based filtration was carried out to find thermally destabilising variants. Finally, three variants have been detected as highly destabilising by the mCSM server and chosen for the MD study. All three variants are present in the N-terminal, Intermediate, and C-terminal regions, breaking the spatial arrangement required for microtubule assembly. The spatial arrangement of these variants is in deviation with respect to WT (wild type) β-tubulin. The protein model was subjected to a simulation period of 100 ns. The FEL analysis revealed multiple clusters with minor populations indicating the unstable conformation adapted by the β-tubulin. The normal mode vector analysis exhibited high-intensity flexible motions at the C-terminal end, responsible for binding with MAPs (microtubule-associated proteins), an essential region in microtubule assembly. All these results reveal that the SNP’s predicted eventually influence the spatial arrangement of β-tubulin, which would disturb the stacking arrangement of αβ tubulin dimer in microtubule assembly. The present study may set a path to cure the diseases like macro thrombocytopenia. Communicated by Ramaswamy H. Sarma

Small-molecule activators specific to adenine base editors through blocking the canonical TGF-β pathway.

Adenine base editors (ABEs) catalyze A-to-G conversions, offering therapeutic options to treat the major class of human pathogenic single nucleotide polymorphisms (SNPs). However, robust and precise editing at diverse genome loci remains challenging. Here, using high-throughput chemical screening, we identified and validated SB505124, a selective ALK5 inhibitor, as an ABE activator. Treating cells with SB505124 enhanced on-target editing at multiple genome loci, including epigenetically refractory regions, and showed little effect on off-target conversion on the genome. Furthermore, SB505124 facilitated the editing of disease-associated genes in vitro and in vivo. Intriguingly, SB505124 served as a specific activator by selectively promoting ABE activity. Mechanistically, SB505124 promotes ABE editing, at least in part, by enhancing ABE expression and modulating DNA repair-associated genes. Our findings reveal the role of the canonical transforming growth factor-β pathway in gene editing and equip ABEs with precise chemical control.

From bugs to bedside: functional annotation of human genetic variation for neurological disorders using invertebrate models.

The exponential accumulation of DNA sequencing data has opened new avenues for discovering the causative roles of single-nucleotide polymorphisms (SNPs) in neurological diseases. The opportunities emerging from this are staggering, yet only as good as our abilities to glean insights from this surplus of information. Whereas computational biology continues to improve with respect to predictions and molecular modeling, the differences between in silico and in vivo analysis remain substantial. Invertebrate in vivo model systems represent technically advanced, experimentally mature, high-throughput, efficient and cost-effective resources for investigating a disease. With a decades-long track record of enabling investigators to discern function from DNA, fly (Drosophila) and worm (Caenorhabditis elegans) models have never been better poised to serve as living engines of discovery. Both of these animals have already proven useful in the classification of genetic variants as either pathogenic or benign across a range of neurodevelopmental and neurodegenerative disorders-including autism spectrum disorders, ciliopathies, amyotrophic lateral sclerosis, Alzheimer's and Parkinson's disease. Pathogenic SNPs typically display distinctive phenotypes in functional assays when compared with null alleles and frequently lead to protein products with gain-of-function or partial loss-of-function properties that contribute to neurological disease pathogenesis. The utility of invertebrates is logically limited by overt differences in anatomical and physiological characteristics, and also the evolutionary distance in genome structure. Nevertheless, functional annotation of disease-SNPs using invertebrate models can expedite the process of assigning cellular and organismal consequences to mutations, ascertain insights into mechanisms of action, and accelerate therapeutic target discovery and drug development for neurological conditions.

IKBKE and BANK1 Polymorphisms and Clinical Characteristics in Chinese Women with Systemic Lupus Erythematosus

ABSTRACT Background Defects in apoptotic cell clearance is a pathogenic factor in systemic lupus erythematosus (SLE). This study screened potential pathogenic single nucleotide polymorphisms (SNPs) related to anti-apoptosis from an SLE family and explored their contribution to SLE susceptibility in Chinese women. Methods Four SNPs (IKBKE rs15672, BANK1 rs12640056, BANK1 rs6842661, and NFKBIA rs1957106) with potential SLE susceptibility were analyzed for clinical characteristics between 567 patients with SLE and 345 healthy control subjects. Results IKBKE rs15672 G/A and BANK1 rs12640056C/T polymorphisms were associated with SLE susceptibility (rs15672 A vs G, P = 0.028, OR = 1.25, 95% CI = 1.02–1.52; rs12640056 T vs C, P = 0.015, OR = 0.78, 95% CI = 0.64–0.95, respectively). In addition, patients with AA+GA genotypes of IKBKE rs15672 had higher positive rates of anti-SSB antibodies (q = 0.008) and lower positive rates of anti-RIB antibodies (q = 0.024) than those with the GG genotype. There were no significant differences in BANK1 rs12640056 between different genotypes and clinical characteristics. Conclusion IKBKE rs15672 G/A and BANK1 rs12640056C/T polymorphisms are associated with susceptibility to SLE in Chinese women. This highlights the important role of these two SNPs in this disease and suggests that multiple genes from these pathways are candidates for functional studies and therapeutic targets.

Systematic Exploration of Optimized Base Editing gRNA Design and Pleiotropic Effects with BExplorer

Base editing technology is being increasingly applied in genome engineering, but the current strategy for designing guide RNAs (gRNAs) relies substantially on empirical experience rather than a dependable and efficient in silico design. Furthermore, the pleiotropic effect of base editing on disease treatment remains unexplored, which prevents its further clinical usage. Here, we presented BExplorer, an integrated and comprehensive computational pipeline to optimize the design of gRNAs for 26 existing types of base editors in silico. Using BExplorer, we described its results for two types of mainstream base editors, BE3 and ABE7.10, and evaluated the pleiotropic effects of the corresponding base editing loci. BExplorer revealed 524 and 900 editable pathogenic single nucleotide polymorphism (SNP) loci in the human genome together with the selected optimized gRNAs for BE3 and ABE7.10, respectively. In addition, the impact of 707 edited pathogenic SNP loci following base editing on 131 diseases was systematically explored by revealing their pleiotropic effects, indicating that base editing should be carefully utilized given the potential pleiotropic effects. Collectively, the systematic exploration of optimized base editing gRNA design and the corresponding pleiotropic effects with BExplorer provides a computational basis for applying base editing in disease treatment.

Impact of deleterious missense PRKCI variants on structural and functional dynamics of protein

Protein kinase C iota (PKCɩ) is a novel protein containing 596 amino acids and is also a member of atypical kinase family. The role of PKCɩ has been explored in neurodegenerative diseases, neuroblastoma, ovarian and pancreatic cancers. Single nucleotide polymorphisms (SNPs) have not been studied in PKCɩ till date. The purpose of the current study is to scrutinize the deleterious missense variants in PKCɩ and determine the effect of these variants on stability and dynamics of the protein. The structure of protein PKCɩ was predicted for the first time and post translational modifications were determined. Genetic variants of PKCɩ were retrieved from ENSEMBL and only missense variants were further analyzed because of its linkage with diseases. The pathogenicity of missense variants, effect on structure and function of protein, association with cancer and conservancy of the protein residues were determined through computational approaches. It is observed that C1 and the pseudo substrate region has the highest number of pathogenic SNPs. Variations in the kinase domain of the protein are predicted to alter overall phosphorylation of the protein. Molecular dynamic simulations predicted noteworthy change in structural and functional dynamics of the protein because of these variants. The study revealed that nine deleterious variants can possibly contribute to malfunctioning of the protein and can be associated with diseases. This can be useful in diagnostics and developing therapeutics for diseases related to these polymorphisms.

Analysis of Functional Polymorphisms in Meningioma associated Genes

Meningioma is the most common benign intracranial tumour that develops in the meningeal protective covering of the central nervous system (CNS). Globally, every nine individuals out of 100,000 are diagnosed with this cancer. Basic risk factors of meningioma comprise ionizing radiation, hormonal imbalance, and genetic aberrations. In this study, various bioinformatics tools, specialized for consensus-based identification, sequence-homology, and supervised learning, were employed to analyze and screen the deleterious mutational landscape of commonly associated genes of meningioma/genes commonly associated with meningioma. This study employed an in-silico approach aimed to utilize thirteen different tools to benchmark pathogenic single nucleotide polymorphisms (SNPs) in SMARCB1, AKT1, SMO, SUFU, NF2 and MTHFR genes related to meningioma. We identified six highly pathogenic SNPs related to meningioma: SMARCB1 (rs387906812, rs387906811, rs267607072), AKT1 (rs121434592), SMO (rs121918347), and SUFU (rs202247756). Additionally, several deleterious missense variants of NF2 and MTHFR genes were also identified. Hence, this study is a gateway for research on SNPs since they can be utilized to conduct a type-based diagnosis of meningioma for its early prognosis. They can also be utilized as genomic targets for a targeted therapy by developing inhibitors against mutated proteins. For this purpose, further wet-lab experiments and genome-wide association studies are required to genotype these SNPs in a large number of samples, collected from different populations belonging to various ethnicities, for the development of SNP(s) gene panels.

Replacing the SpCas9 HNH domain by deaminases generates compact base editors with an alternative targeting scope

Base editors are RNA-guided deaminases that enable site-specific nucleotide transitions. The targeting scope of these Cas-deaminase fusion proteins critically depends on the availability of a protospacer adjacent motif (PAM) at the target locus and is limited to a window within the CRISPR-Cas R-loop, where single-stranded DNA (ssDNA) is accessible to the deaminase. Here, we reason that the Cas9-HNH nuclease domain sterically constrains ssDNA accessibility and demonstrate that omission of this domain expands the editing window. By exchanging the HNH nuclease domain with a monomeric or heterodimeric adenosine deaminase, we furthermore engineer adenine base editor variants (HNHx-ABEs) with PAM-proximally shifted editing windows. This work expands the targeting scope of base editors and provides base editor variants that are substantially smaller. It moreover informs of potential future directions in Cas9 protein engineering, where the HNH domain could be replaced by other enzymes that act on ssDNA.

Pathogenic nsSNPs that increase the risks of cancers among the Orang Asli and Malays

Single-nucleotide polymorphisms (SNPs) are the most common genetic variations for various complex human diseases, including cancers. Genome-wide association studies (GWAS) have identified numerous SNPs that increase cancer risks, such as breast cancer, colorectal cancer, and leukemia. These SNPs were cataloged for scientific use. However, GWAS are often conducted on certain populations in which the Orang Asli and Malays were not included. Therefore, we have developed a bioinformatic pipeline to mine the whole-genome sequence databases of the Orang Asli and Malays to determine the presence of pathogenic SNPs that might increase the risks of cancers among them. Five different in silico tools, SIFT, PROVEAN, Poly-Phen-2, Condel, and PANTHER, were used to predict and assess the functional impacts of the SNPs. Out of the 80 cancer-related nsSNPs from the GWAS dataset, 52 nsSNPs were found among the Orang Asli and Malays. They were further analyzed using the bioinformatic pipeline to identify the pathogenic variants. Three nsSNPs; rs1126809 (TYR), rs10936600 (LRRC34), and rs757978 (FARP2), were found as the most damaging cancer pathogenic variants. These mutations alter the protein interface and change the allosteric sites of the respective proteins. As TYR, LRRC34, and FARP2 genes play important roles in numerous cellular processes such as cell proliferation, differentiation, growth, and cell survival; therefore, any impairment on the protein function could be involved in the development of cancer. rs1126809, rs10936600, and rs757978 are the important pathogenic variants that increase the risks of cancers among the Orang Asli and Malays. The roles and impacts of these variants in cancers will require further investigations using in vitro cancer models.

In-silico study to identify the pathogenic single nucleotide polymorphisms in the coding region of CDKN2A gene

Background: CDKN2A, encoding two important tumor suppressor proteins p16 and p14, is a tumor suppressor gene. Mutations in this gene and subsequently the defect in p16 and p14 proteins lead to the downregulation of RB1/p53 and cancer malignancy. To identify the structural and functional effects of mutations, various powerful bioinformatics tools are available. The aim of this study is the identification of high-risk non-synonymous single nucleotide variants in the CDKN2A gene via bioinformatics tools. Materials and Methods: Among the identified polymorphisms in this gene, 353 missense variants are retrieved from the national center for biotechnology information/single nucleotide polymorphism database (NCBI/dbSNP). Then, the pathogenicity of missense variants are considered using different bioinformatics tools. The stability of these mutant proteins, conservation of amino acids and the secondary and tertiary structural changes are analyzed by bioinformatics tools. After the identification of high-risk mutations, the changes in the hydrophobicity of high-risk amino acid substitutions are considered. Results: Deleterious single nucleotide polymorphisms (SNPs) were screened step by step using the bioinformatics tools. The results obtained from the set of bioinformatics tools identify high-risk mutations in CDKN2A gene. Conclusion: 18 high-risk mutations including L16R/Q, G23D/R/S, L32P, N42K, G55D, G67D/R, P81R, H83R, G89D/S, A102E, G101R, G122R, and V126D were identified. According to the previous experimental studies, the association of L16R, G23D/R/S, L32P, G67R, H83R, G89D, G101R, and V126D amino acid substitutions with various cancers has been confirmed.

Insights into association between urolithiasis and prostate cancer

Background and objective: Urolithiasis or renal stones form a major urinary tract infection with formation of calcifications in the bladder and uterus. With the lifestyle diseases burgeoning, the renal stones have become a common cause with an approximate 1 in 1000 people affected all over the world with a risk ratio of 3 : 1 in men and women. On the other hand, prostate or genitourinary cancers are well documented to be associated with urolithiasis. Methods: A gene list was prepared from the published NCBI dataset, comprising all the genes related to urolithiasis primarily with mutations (both pathogenic and likely pathogenic Single nucleotide polymorphisms, SNP's) for every particular gene screened later from the published datasets. To see the interactions among all the potential genetic factors, PPI based tools were used and an interaction map was prepared. For the characterization of mutations, we have used gnomAD for verifying all the SNPs whether they are synonymous or nonsynonymous mutations. Results: We outlined the list of genes and discussed the systems bioinformatics integrated approach associated with it. Conclusion: We found a large number of genes common to them and their association is subtly known for immunomodulatory response.

In silico characterization of coding and non-coding SNPs of the androgen receptor gene

The Androgen Receptor (AR), an important ligand-dependent nuclear transcription factor, encoded by the AR gene, functions in regulating the cell proliferation, migration, invasion, and apoptosis pathways. Single nucleotide polymorphisms (SNPs) of AR have been implicated in playing a role in several diseases. This study sought to explore the molecular consequences of the disease susceptible germ-line missense and non-coding SNPs of AR gene, by using different computational methods. 586 Missense SNPs were retrieved from dbSNP, DisGeNET, ClinVar, and LitVar databases, and then analyzed using nine different functionality prediction servers such as SIFT, PolyPhen-2, PROVEAN, PhD-SNP, etc. These sieved the most deleterious SNPs, which was then followed by the analysis of conservation, surface exposure, post-translational modification, stability, secondary structure, protein-ligand docking and molecular dynamics simulation. Among the missense SNPs, 21 SNPs were identified as most deleterious by all nine filtration tools. These high-risk disease-causing mutations mostly belong to highly conserved regions (buried or exposed) and affect protein stability and post-translational modifications. Based on the phenotypic effect predicted by ModPred and HOPE, and integrating the result with modeled mutated structures, two variants S866P and P893Q were considered to have the most severe functional consequences on protein 3D structure. Furthermore, based on the structural variations in mutant structure modeling, 98 noncoding pathogenic SNPs were identified as having an effect on the transcription factors’ binding and gene expression regulation. In contrast, 39 AR-SNPs were investigated using the PolymiRTS database. It was found that they affect miRNA target sites as well as destroying or creating miRNA target seeds. Significantly, these SNPs, distributed in random coil, alpha helix, extended sheet, and beta-turn, are most likely to affect the phenotypic characteristics of AR by altering hydrophobicity, flexibility, charges, H-bonds, salt bridges, and spatial structure. This current study is a comprehensive analysis, using an integrated in-silico approach on AR gene variants. It may provide a platform to conduct large-scale experiments involving AR polymorphism.

Screening of SLE-susceptible SNPs in One Chinese Family with Systemic Lupus Erythematosus

Background: Systemic lupus erythematosus (SLE) is a complex autoimmune disease, which mainly affects childbearing-aged women. Although its pathogenesis is not fully clear yet, studies have shown that genetic factors are vital in exploring SLE pathogenic mechanisms. Objective: The purpose of this study is to predict and screen potential pathogenic single nucleotide polymorphisms (SNPs). By comparing the genomes of members of a family with SLE and performing functional analysis on mutation loci, possible pathogenic polymorphisms are screened. These analyses lay the foundation for further research mechanisms. Method: Genomic alignment, variant calling and functional annotation were performed and then ~92,778 original SNPs were obtained for each specimen. We found that the patient/healthyspecific SNPs show different conservative score distribution. Many patient-specific SNPs were detected in SLE-related pathways. We therefore investigated the patient-specific SNPs from four diverse perspectives, including nonsynonymous variations in exon regions, expression quantitative trait loci (eQTLs), RNA binding sites and RNA-binding protein (RBP) binding sites. Results: 18 potential pathogenic SNPs were identified in SLE risk genes, which were associated with functional loci. Systematic literature study was then performed to verify these potential pathogenic SNPs. Conclusion: This study could help to better explain possible genetic mechanisms of SLE from the perspective of variation. It could provide effective strategy for the accurate diagnosis and personalized treatment of SLE patients.