Exploration of deleterious single nucleotide polymorphisms in late-onset Alzheimer disease susceptibility genes

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed in-silico methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein. We have discovered a total of 50 nsSNPs, of which 23 were located in the exon region of the HRAS gene and denoting that they were expected to cause harm or be deleterious. Out of these 23, 10 nsSNPs ([G60V], [G60D], [R123P], [D38H], [I46T], [G115R], [R123G], [P11OL], [A59L], and [G13R]) were identified as having the most delterious effect based on results of SIFT analysis and PolyPhen2 scores ranging from 0.53 to 69. The DDG values -3.21 kcal/mol to 0.87 kcal/mol represent the free energy change associated with protein stability upon mutation. Interestingly, we identified that the three mutations (Y4C, T58I, and Y12E) were found to improve the structural stability of the protein. We performed molecular dynamics (MD) simulations to investigate the structural and dynamic effects of HRAS mutations. Our results showed that the stable model of HRAS had a significantly lower energy value of -18756 kj/mol compared to the initial model of -108915 kj/mol. The RMSD value for the wild-type complex was 4.40 Å, and the binding energies for the G60V, G60D, and D38H mutants were -107.09 kcal/mol, -109.42 kcal/mol, and -107.18 kcal/mol, respectively as compared to wild-type HRAS protein had -105.85 kcal/mol. The result of our investigation presents convincing corroboration for the potential functional significance of nsSNPs in augmenting HRAS expression and adding to the activation of malignant oncogenic signalling pathways.

A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR-Alu (SVA) elements, a class of great ape-specific transposable elements with gene-regulatory roles, which represents a major source of structural variability in the human population. We highlight the presence of structurally variable SVAs (SV-SVAs) in neurological disease-associated loci, and we further associate SV-SVAs to disease-associated SNPs and differential gene expression using luciferase assays and expression quantitative trait loci data. Finally, we genetically deleted SV-SVAs in the BIN1 and CD2AP Alzheimer's disease-associated risk loci and in the BCKDK Parkinson's disease-associated risk locus and assessed multiple aspects of their gene-regulatory influence in a human neuronal context. Together, this study reveals a novel layer of genetic variation in transposable elements that may contribute to identification of the structural variants that are the actual drivers of disease associations of GWAS loci.

Effects of Phenylethanoid Glycosides Extracted from Herba Cistanches on the Learning and Memory of the APP/PSI Transgenic Mice with Alzheimer's Disease

Background

To investigate the effects of phenylethanoid glycosides (PhGs) extracted from Herba Cistanches on the behavioral and cognition capacity of the APP/PSI transgenic mice with Alzheimer's disease (AD).

Methods

AD mice were randomly divided into the control group, model group, donepezil group, PhG groups, and verbascose group, respectively. Three weeks later, the animals were subject to behavioral and cognition evaluation by the nesting test, Morris water maze test, and step-down test.

Results

The cognition capacity in these groups showed a significant increase compared with that in the model group. The step-down test indicated that the errors induced by the memory decrease in the PhG groups and verbascose group showed a significant decrease compared with those in the model group (P < 0.05).

Conclusions

PhGs attenuated the cognitive dysfunction features of the APP/PSI transgenic gene. Besides, PhGs were the active components for the anti-AD activity of H. Cistanches.

In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review

Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

CYP2R1 and CYP27A1 genes: An in silico approach to identify the deleterious mutations, impact on structure and their differential expression in disease conditions

Mutations in CYP2R1 and CYP27A1 involved in the conversion of Cholecalciferol into Calcidiol were associated with the impaired 25-hydroxylase activity therefore affecting the Vitamin D metabolism. Hence, this study attempted to understand the influence of genetic variations at the sequence and structural level via computational approach. The non-synonymous mutations retrieved from dbSNP database were assessed for their pathogenicity, stability as well as conservancy using various computational tools. The above analysis predicted 11/260 and 35/489 non-synonymous mutations to be deleterious in CYP2R1 and CYP27A1 genes respectively. Native and mutant forms of the corresponding proteins were modeled. Further, interacting native and mutant proteins with cholecalciferol showed difference in hydrogen bonds, hydrophobic bonds and their binding affinities suggesting the possible influence of these mutations in their function. Also, expression of these genes in various disease conditions was investigated using GEO datasets which predicted that there is a differential expression in cancer and arthritis.

An Overview of Experimental and Clinical Spinal Cord Findings in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that occurs mainly in the elderly and presenile life stages. It is estimated that by the year 2050, 135 million people will be affected by AD worldwide, representing a huge burden to society. The pathological hallmarks of AD mainly include intracellular neurofibrillary tangles (NFTs) caused by hyperphosphorylation of tau protein, formation of extracellular amyloid plaques, and massive neural cell death in the affected nervous system. The pathogenesis of AD is very complicated, and recent scientific research on AD is mainly concentrated on the cortex and hippocampus. Although the spinal cord is a pivotal part of the central nervous system, there are a limited number of studies focusing on the spinal cord. As an extension of the brain, the spinal cord functions as the bridge between the brain and various parts of the body. However, pathological changes in the spinal cord in AD have not been comprehensively and systematically studied at present. We here review the existing progress on the pathological features of AD in the spinal cord.

Computational Screening and Exploration of Disease-Associated Genes in Alzheimer's Disease

Alzheimer's is a neurodegenerative disease affecting large populations worldwide characterized mainly by progressive loss of memory along with various other symptoms. The foremost cause of the disease is still unclear, however various mechanisms have been proposed to cause the disease that include amyloid hypothesis, tau hypothesis, and cholinergic hypothesis in addition to genetic factors. Various genes have been known to be involved which are APOE, PSEN1, PSEN2, and APP among others. In the present study, we have used computational methods to examine the pathogenic effects of non-synonymous single nucleotide polymorphisms (SNPs) associated with ABCA7, CR1, MS4A6A, CD2AP, PSEN1, PSEN2, and APP genes. The SNPs were obtained from dbSNP database followed by identification of deleterious SNPs and prediction of their functional impact. Prediction of disease-associated mutations was performed and the impact of the mutations on the stability of the protein was carried out. To study the structural significance of the computationally prioritized mutations on the proteins, molecular dynamics simulation studies were carried out. On analysis, the SNPs with IDs rs76282929 ABCA7; CR1 rs55962594; MS4A6A rs601172; CD2AP rs61747098; PSEN1 rs63750231, rs63750265, rs63750526, rs63750577, rs63750687, rs63750815, rs63750900, rs63751037, rs63751163, rs63751399; PSEN2 rs63749851; and APP rs63749964, rs63750066, rs63750734, and rs63751039 were predicted to be deleterious and disease-associated having significant structural impact on the proteins. The current study proposes a precise computational methodology for the identification of disease-associated SNPs. J. Cell. Biochem. 118: 1471-1479, 2017. © 2016 Wiley Periodicals, Inc.

In silico approach to identify non-synonymous SNPs in human obesity related gene, MC3R (melanocortin-3-receptor)

The melanocortin-3-receptor (MC3R) is a novel gene candidate for human obesity, which involved in controlling the energy homeostasis and food intake behavior. The main aim behind this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in obesity related gene MC3R by using six computational tools viz., PolyPhen, I-Mutant, PROVEAN, SIFT, PANTHER and PhD-SNP. In our study, we predicted eight nsSNPs i.e., rs74315393 (Ile146Asn), rs368205448 (Asp121Tyr), rs143321797 (Phe45Ser), rs17847261 (Cys274Ser), rs144166442 (Pro257His), rs370533946 (Leu224Pro), rs371354428 (Pro72Leu) and rs373708098 (Gly249Ser) found to be potentially deleterious. The functional impact of three nsSNPs i.e., rs74315393, rs368205448 and rs143321797 have already been validated experimentally in the context of human obesity. Moreover, Homology modeling and structural analysis were carried out for already experimentally validated nsSNPs i.e., rs74315393, rs368205448 and rs143321797 to check the stability of predicted models. The mutant models showed higher energy and RMSD (Root mean square deviation) values. In addition, FTSite server predicted one nsSNP i.e., rs368205448 (Asp121Tyr) out of eight identified nsSNPs found in the MC3R protein binding site. Thus, the present computational study may suggest that predicted nsSNPs possibly be a better drug target and contribute to the treatment and better understanding of human obesity.

A Comprehensive In Silico Analysis on the Structural and Functional Impact of SNPs in the Congenital Heart Defects Associated with NKX2-5 Gene-A Molecular Dynamic Simulation Approach

Congenital heart defects (CHD) presented as structural defects in the heart and blood vessels during birth contribute an important cause of childhood morbidity and mortality worldwide. Many Single nucletotide polymorphisms (SNPs) in different genes have been associated with various types of congenital heart defects. NKX 2–5 gene is one among them, which encodes a homeobox-containing transcription factor that plays a crucial role during the initial phases of heart formation and development. Mutations in this gene could cause different types of congenital heart defects, including Atrial septal defect (ASD), Atrial ventricular block (AVB), Tetralogy of fallot and ventricular septal defect. This highlights the importance of studying the impact of different SNPs found within this gene that might cause structural and functional modification of its encoded protein. In this study, we retrieved SNPs from the database (dbSNP), followed by identification of potentially deleterious Non-synonymous single nucleotide polymorphisms (nsSNPs) and prediction of their effect on proteins by computational screening using SIFT and Polyphen. Furthermore, we have carried out molecular dynamic simulation (MDS) in order to uncover the SNPs that would cause the most structural damage to the protein altering its biological function. The most important SNP that was found using our approach was rs137852685 R161P, which was predicted to cause the most damage to the structural features of the protein. Mapping nsSNPs in genes such as NKX 2–5 would provide valuable information about individuals carrying these polymorphisms, where such variations could be used as diagnostic markers.

Genetic Factors Affecting Late-Onset Alzheimer's Disease Susceptibility

Alzheimer's disease is considered a progressive brain disease in the older population. Late-onset Alzheimer's disease (LOAD) as a multifactorial dementia has a polygenic inheritance. Age, environment, and lifestyle along with a growing number of genetic factors have been reported as risk factors for LOAD. Our aim was to present results of LOAD association studies that have been done in northwestern Iran, and we also explored possible interactions with apolipoprotein E (APOE) status. We re-evaluated the association of these markers in dominant, recessive, and additive models. In all, 160 LOAD and 163 healthy control subjects of Azeri Turkish ethnicity were studied. The Chi-square test with Yates' correction and Fisher's exact test were used for statistical analysis. A Bonferroni-corrected p value, based on the number of statistical tests, was considered significant. Our results confirmed that chemokine receptor type 2 (CCR2), estrogen receptor 1 (ESR1), toll-like receptor 2 (TLR2), tumor necrosis factor alpha (TNF α), APOE, bridging integrator 1 (BIN1), and phosphatidylinositol-binding clathrin assembly protein (PICALM) are LOAD susceptibility loci in Azeri Turk ancestry populations. Among them, variants of CCR2, ESR1, TNF α, and APOE revealed associations in three different genetic models. After adjusting for APOE, the association (both allelic and genotypic) with CCR2, BIN1, and ESRα (PvuII) was evident only among subjects without the APOE ε4, whereas the association with CCR5, without Bonferroni correction, was significant only among subjects carrying the APOE ε4 allele. This result is an evidence of a synergistic and antagonistic effect of APOE on variant associations with LOAD.

Genetics of Alzheimer's disease

Alzheimer's disease (AD) represents the main form of dementia, and is a major public health problem. Despite intensive research efforts, current treatments have only marginal symptomatic benefits and there are no effective disease-modifying or preventive interventions. AD has a strong genetic component, so much research in AD has focused on identifying genetic causes and risk factors. This chapter will cover genetic discoveries in AD and their consequences in terms of improved knowledge regarding the disease and the identification of biomarkers and drug targets. First, we will discuss the study of the rare early-onset, autosomal dominant forms of AD that led to the discovery of mutations in three major genes, APP, PSEN1, and PSEN2. These discoveries have shaped our current understanding of the pathophysiology and natural history of AD as well as the development of therapeutic targets and the design of clinical trials. Then, we will explore linkage analysis and candidate gene approaches, which identified variants in Apolipoprotein E (APOE) as the major genetic risk factor for late-onset, "sporadic" forms of AD (LOAD), but failed to robustly identify other genetic risk factors, with the exception of variants in SORL1. The main focus of this chapter will be on recent genome-wide association studies that have successfully identified common genetic variations at over 20 loci associated with LOAD outside of the APOE locus. These loci are in or near-novel AD genes including BIN1, CR1, CLU, phosphatidylinositol-binding clathrin assembly protein (PICALM), CD33, EPHA1, MS4A4/MS4A6, ABCA7, CD2AP, SORL1, HLA-DRB5/DRB1, PTK2B, SLC24A4-RIN3, INPP5D, MEF2C, NME8, ZCWPW1, CELF1, FERMT2, CASS4, and TRIP4 and each has small effects on risk of AD (relative risks of 1.1-1.3). Finally, we will touch upon the ongoing effort to identify less frequent and rare variants through whole exome and whole genome sequencing. This effort has identified two novel genes, TREM2 and PLD3, and shown a role for APP in LOAD. The identification of these recently identified genes has implicated previously unsuspected biological pathways in the pathophysiology of AD.

Computational SNP analysis: current approaches and future prospects

The computational approaches in determining disease-associated Non-synonymous single nucleotide polymorphisms (nsSNPs) have evolved very rapidly. Large number of deleterious and disease-associated nsSNP detection tools have been developed in last decade showing high prediction reliability. Despite of all these highly efficient tools, we still lack the accuracy level in determining the genotype-phenotype association of predicted nsSNPs. Furthermore, there are enormous questions that are yet to be computationally compiled before we might talk about the prediction accuracy. Earlier we have incorporated molecular dynamics simulation approaches to foster the accuracy level of computational nsSNP analysis roadmap, which further helped us to determine the changes in the protein phenotype associated with the computationally predicted disease-associated mutation. Here we have discussed on the present scenario of computational nsSNP characterization technique and some of the questions that are crucial for the proper understanding of pathogenicity level for any disease associated mutations.

Genetic evidence for the involvement of variants at APOE, BIN1, CR1, and PICALM loci in risk of late-onset Alzheimer's disease and evaluation for interactions with APOE genotypes

Alzheimer's disease (AD) is the most common form of dementia in older population. Growing evidence of genetic background that predisposes individuals to AD has been reported as the risk factors in recent years. The Department of Medical Genetics and the Immunology Research Centre investigated the distribution of 11 polymorphisms in 160 patients with late onset AD (LOAD) and in 163 healthy controls, using the sequencing technique. All participants were of Turkish Azeri ethnicity. We compared allele and genotype frequencies between the LOAD patients and control subjects using a chi-square or Fisher's exact test. Alleles and genotypes of APOE, PICALM rs3851179 and rs541458, and the BIN1 gene rs744373 polymorphism were significantly different between LOAD and control groups. The frequencies of the other investigated alleles were similar in the two groups. We also analyzed the association of BIN1, CR1 and PICALM SNPs with LOAD in subgroups stratified by the presence or absence of the APOE ε4 allele. After adjusting for APOE, statistical analysis revealed that the association with PICALM rs541458 and BIN1 rs744373 were only significant among subjects without the APOE ε4 allele.

Bridging integrator 1 (BIN1): form, function, and Alzheimer's disease

The bridging integrator 1 (BIN1) gene, also known as amphiphysin 2, has recently been identified as the most important risk locus for late onset Alzheimer's disease (LOAD), after apolipoprotein E (APOE). Here, we summarize the known functions of BIN1 and discuss the polymorphisms associated with LOAD, as well as their possible physiological effects. Emerging data suggest that BIN1 affects AD risk primarily by modulating tau pathology, but other affected cellular functions are discussed, including endocytosis/trafficking, inflammation, calcium homeostasis, and apoptosis. Epigenetic modifications are important for AD pathogenesis, and we review data that suggests the possible DNA methylation of the BIN1 promoter. Finally, given the potential contributions of BIN1 to AD pathogenesis, targeting BIN1 might present novel opportunities for AD therapy.

Alzheimer's disease drug development: translational neuroscience strategies

Alzheimer's disease (AD) is an urgent public health challenge that is rapidly approaching epidemic proportions. New therapies that defer or prevent the onset, delay the decline, or improve the symptoms are urgently needed. All phase 3 drug development programs for disease-modifying agents have failed thus far. New approaches to drug development are needed. Translational neuroscience focuses on the linkages between basic neuroscience and the development of new diagnostic and therapeutic products that will improve the lives of patients or prevent the occurrence of brain disorders. Translational neuroscience includes new preclinical models that may better predict human efficacy and safety, improved clinical trial designs and outcomes that will accelerate drug development, and the use of biomarkers to more rapidly provide information regarding the effects of drugs on the underlying disease biology. Early translational research is complemented by later stage translational approaches regarding how best to use evidence to impact clinical practice and to assess the influence of new treatments on the public health. Funding of translational research is evolving with an increased emphasis on academic and NIH involvement in drug development. Translational neuroscience provides a framework for advancing development of new therapies for AD patients.