Sequence-based prediction of pathological mutations

Role of deleterious nsSNPs of klotho protein and their drug response: a computational mechanical insights

Worldwide, the burden of chronic kidney disease (CKD) has increased rapidly and is a lethal disease. The klotho protein plays a vital role in the regulatory mechanism in the progression of CKD. Particularly the decreased expression of klothoand its genetic variations might affect the potency of drugs. This study aims to identify a new drug molecule, which works equipotential in all types of klotholike wild and mutant variants. All non-synonymous SNPs were predicted by several SNP tools. Where, two missense variants were examined as vulnerable, significantly damaging, and also involved in the structural conformational changes of the protein. Based on structure-based screening, E-pharmacophore screening, binding mode analysis, binding free energy analysis, QM/MM, and molecular dynamics analysis a lead compound (Lifechemical_F2493-2038) was identified as an effective agonistic molecule hence the identified Lifechemical_F2493-2038 compound is well bound to the wild and mutant proteins which found to increase the expression of klotho.Communicated by Ramaswamy H. Sarma.

A New Set of in Silico Tools to Support the Interpretation of ATM Missense Variants Using Graphical Analysis

Establishing the pathogenic nature of variants in ATM, a gene associated with breast cancer and other hereditary cancers, is crucial for providing patients with adequate care. Unfortunately, achieving good variant classification is still difficult. To address this challenge, we extended the range of in silico tools with a series of graphical tools devised for the analysis of computational evidence by health care professionals. We propose a family of fast and easy-to-use graphical representations in which the impact of a variant is considered relative to other pathogenic and benign variants. To illustrate their value, the representations are applied to three problems in variant interpretation. The assessment of computational pathogenicity predictions showed that the graphics provide an intuitive view of prediction reliability, complementing and extending conventional numerical reliability indexes. When applied to variant of unknown significance populations, the representations shed light on the nature of these variants and can be used to prioritize variants of unknown significance for further studies. In a third application, the graphics were used to compare the two versions of the ATM-adapted American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines, obtaining valuable information on their relative virtues and weaknesses. Finally, a server [ATMision (ATM missense in silico interpretation online)] was generated for users to apply these representations in their variant interpretation problems, to check the ATM-adapted guidelines' criteria for computational evidence on their variant(s) and access different sources of information.

High-Throughput Prediction of the Impact of Genetic Variability on Drug Sensitivity and Resistance Patterns for Clinically Relevant Epidermal Growth Factor Receptor Mutations from Atomistic Simulations

Mutations in the kinase domain of the epidermal growth factor receptor (EGFR) can be drivers of cancer and also trigger drug resistance in patients receiving chemotherapy treatment based on kinase inhibitors. A priori knowledge of the impact of EGFR variants on drug sensitivity would help to optimize chemotherapy and design new drugs that are effective against resistant variants before they emerge in clinical trials. To this end, we explored a variety of in silico methods, from sequence-based to "state-of-the-art" atomistic simulations. We did not find any sequence signal that can provide clues on when a drug-related mutation appears or the impact of such mutations on drug activity. Low-level simulation methods provide limited qualitative information on regions where mutations are likely to cause alterations in drug activity, and they can predict around 70% of the impact of mutations on drug efficiency. High-level simulations based on nonequilibrium alchemical free energy calculations show predictive power. The integration of these "state-of-the-art" methods into a workflow implementing an interface for parallel distribution of the calculations allows its automatic and high-throughput use, even for researchers with moderate experience in molecular simulations.

Missense mutations involvement in COX-2 structure, and protein-substrate binding affinity: in-silico study

Cyclooxygenase-2 (COX-2) is an inducible inflammatory enzyme, which produces prostanoids from arachidonic acid. COX-2 overexpression and over-activity can cause inflammation, tumorigenesis, and angiogenesis. Prostanoids are the main reason for the inflammation, and increase of mitogenesis by COX-2. So, any change such as mutations that can lead to COX-2 over-activity could ignite the tumor situations with increase of prostanoids production is one of its ways. The aim of this study was to check the effect of 166 missense mutations of COX-2 on protein features that can affect the COX-2 activity such as protein stability, fluctuation, 2D structure, and its binding affinity with the substrate by in silico methods, network modeling, and docking calculations, by which 44 of them shown to be deleterious. Among them, the S124I and S474F mutations can increase the stability of the protein. 11.36% of deleterious nsSNPs were part of the substrate-binding region among which the M508T, H337R, and V511G have the potential to affect the protein by 2D structure alteration. V511G can improve binding affinity and H337R showed a small decrease in the deformation overall energy that can represent a decrease in the stability of COX-2. Also, L517S showed a significant decrease in the binding power of COX-2/substrate but based on the anisotropic network modeling this mutation has a dual effect on COX-2 stability. These nsSNPs/mutations have the potential causing an increase or decrease of tumorigenesis because increasing of COX-2 stability and its binding affinity can lead to altering its activity.

Structural and functional insights on vitamin D receptor and CYP24A1 deleterious single nucleotide polymorphisms: A computational and pharmacogenomics perpetual approach

The development of chronic kidney disease (CKD) drugs remains a challenge due to the variations in the genes. The vitamin D receptor (VDR) and Cytochrome 24A1 (CYP24A1) genetic variants might affect the drug potency, efficacy and pathway. Here we have to analyse and determine the deleterious single-nucleotide polymorphisms (nsSNPs) of VDR and CYP24A1 genes and their different population's drug responses in different populations to understand the key role in CKD. Among that the large scale of nsSNP, we used certain computational tools that predicted six missense variants are observed to be significantly damaging effect and SNP variability with large differences in various populations. Molecular docking studies were carried out by clinical and our screened compounds to VDR and CYP24A1. Docking results revealed all the compounds have a good binding affinity (Score). The screened compounds (TCM_2868 and UNPD_141613) show good binding affinity when compared to known compounds. The QM/MM study revealed that the compounds have electron transfer ability and act as a donor/acceptor to mutated proteins. The structural and conformational changes of protein complexes were analysed by molecular dynamics study. Hence, this study helps to identify suitable drugs through drug discovery in CKD treatment. The abovementioned compounds have more binding affinity, efficacy, and potency of both wild and mutant of VDR and CYP24A1.

Mechanistic insights on nsSNPs on binding site of renin and cytochrome P450 proteins: A computational perceptual study for pharmacogenomics evaluation

Past several decades, therapeutic investigations lead to the discovery of numerous antihypertensive drugs. Although it has been proved for their potency, altered efficacy is common norms in several conditions due to genetic variations. Cytochrome P450 plays a crucial role in drug metabolism and responsible for the pharmacokinetic and pharmacodynamic properties of the drug molecules. Here, we report the deleterious point mutations in the genes associated with the altered response of antihypertensive drug molecules and their metabolizers. Missense variants were filtered as potential nonsynonymous single nucleotide polymorphisms among the available data for the target genes (REN, CYP2D6, CYP3A4). The key objective of the work is to identify the deleterious single nucleotide polymorphisms (SNPs) responsible for the drug response and metabolism for the application of personalized medication. The molecular docking studies revealed that Aliskiren and other clinically approved drug molecules have a high binding affinity with both wild and mutant structures of renin, CYP2D6, and CYP3A4 proteins. The docking (Glide XP) score was observed to have in the range of -8.896 to -11.693 kcal/mol. The molecular dynamics simulation studies were employed to perceive the structural changes and conformational deviation through various analyses. Each studied SNPs was observed to have disparate scoring in the binding affinity to the specific drug molecules. As a prospective plan, we assume this study might be applied to identify the risky SNPs associated with hypertension from the patients to recommend the suitable drug for personalized hypertensive treatment. Further, extensive clinical pharmacogenomics studies are required to support the findings.

Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants

The present limitations in the pathogenicity prediction of BRCA1 and BRCA2 (BRCA1/2) missense variants constitute an important problem with negative consequences for the diagnosis of hereditary breast and ovarian cancer. However, it has been proposed that the use of endophenotype predictions, i.e., computational estimates of the outcomes of functional assays, can be a good option to address this bottleneck. The application of this idea to the BRCA1/2 variants in the CAGI 5-ENIGMA international challenge has shown promising results. Here, we developed this approach, exploring the predictive performances of the regression models applied to the BRCA1/2 variants for which the values of the homology-directed DNA repair and saturation genome editing assays are available. Our results first showed that we can generate endophenotype estimates using a few molecular-level properties. Second, we show that the accuracy of these estimates is enough to obtain pathogenicity predictions comparable to those of many standard tools. Third, endophenotype-based predictions are complementary to, but do not outperform, those of a Random Forest model trained using variant pathogenicity annotations instead of endophenotype values. In summary, our results confirmed the usefulness of the endophenotype approach for the pathogenicity prediction of the BRCA1/2 missense variants, suggesting different options for future improvements.

Identifying the Impact of Inframe Insertions and Deletions on Protein Function in Cancer

Inframe insertion and deletion mutations (indels) are commonly observed in cancer samples accounting for over 1% of all reported mutations. Few somatic inframe indels have been clinically documented as pathogenic and at present there are few tools to predict which indels drive cancer development. However, indels are a common feature of hereditary disease and several tools have been developed to predict the impact of inframe indels on protein function. In this study, we test whether six of the popular prediction tools can be adapted to test for cancer driver mutations and then develop a new algorithm (IndelRF) that discriminates between recurrent indels in known cancer genes and indels not associated with disease. IndelRF was developed to try and identify somatic, driver, and inframe indel mutations. Using a random forest classifier with 11 features, IndelRF achieved accuracies of 0.995 and 0.968 for insertion and deletion mutations, respectively. Finally, we use IndelRF to classify the inframe indel cancer mutations in the MOKCa database.

A Novel Homozygous Mutation in SPTBN2 Leads to Spinocerebellar Ataxia in a Consanguineous Family: Report of a New Infantile-Onset Case and Brief Review of the Literature

The objective of this study was the identification of likely genes and mutations associated with an autosomal recessive (AR) rare spinocerebellar ataxia (SCA) phenotype in two patients with infantile onset, from a consanguineous family. Using genome-wide SNP screening, autozygosity mapping, targeted Sanger sequencing and nextgen sequencing, family segregation analysis, and comprehensive neuropanel, we discovered a novel mutation in SPTBN2. Next, we utilized multiple sequence alignment of amino acids from various species as well as crystal structures provided by protein data bank (PDB# 1WYQ and 1WJM) to model the mutation site and its effect on β-III-spectrin. Finally, we used various bioinformatic classifiers to determine pathogenicity of the missense variant. A comprehensive clinical and diagnostic workup including radiological exams were performed on the patients as part of routine patient care. The homozygous missense variant (c.1572C>T; p.R414C) detected in exon 2 was fully segregated in the family and absent in a large ethnic cohort as well as publicly available data sets. Our comprehensive targeted sequencing approaches did not reveal any other likely candidate variants or mutations in both patients. The two male siblings presented with delayed motor milestones and cognitive and learning disability. Brain MRI revealed isolated cerebellar atrophy more marked in midline inferior vermis at ages of 3 and 6.5 years. Sequence alignments of the amino acids for β-III-spectrin indicated that the arginine at 414 is highly conserved among various species and located towards the end of first spectrin repeat domain. Inclusive bioinformatic analysis predicted that the variant is to be damaging and disease causing. In addition to the novel mutation, a brief literature review of the previously reported mutations as well as clinical comparison of the cases were also presented. Our study reviews the previously reported SPTBN2 mutations and cases. Moreover, the novel mutation, p.R414C, adds up to the literature for the infantile-onset form of autosomal recessive ataxia associated with SPTBN2. Previously, few SPTBN2 recessive mutations have been reported in humans. Animal models especially the β-III^-/- mouse model provided insights into early coordination and gait deficit suggestive of loss-of-function. It is expected to see more recessive SPTBN2 mutations appearing in the literature during the upcoming years.

BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene-specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.

Approaches to functionally validate candidate genetic variants involved in colorectal cancer predisposition

Most next generation sequencing (NGS) studies identified candidate genetic variants predisposing to colorectal cancer (CRC) but do not tackle its functional interpretation to unequivocally recognize a new hereditary CRC gene. Besides, germline variants in already established hereditary CRC-predisposing genes or somatic variants share the same need when trying to categorize those with relevant significance. Functional genomics approaches have an important role in identifying the causal links between genetic architecture and phenotypes, in order to decipher cellular function in health and disease. Therefore, functional interpretation of identified genetic variants by NGS platforms is now essential. Available approaches nowadays include bioinformatics, cell and molecular biology and animal models. Recent advances, such as the CRISPR-Cas9, ZFN and TALEN systems, have been already used as a powerful tool with this objective. However, the use of cell lines is of limited value due to the CRC heterogeneity and its close interaction with microenvironment. Access to tridimensional cultures or organoids and xenograft models that mimic the in vivo tissue architecture could revolutionize functional analysis. This review will focus on the application of state-of-the-art functional studies to better tackle new genes involved in germline predisposition to this neoplasm.

Genetic analysis of patients with fructose-1,6-bisphosphatase deficiency

INTRODUCTION

Fructose-1,6-bisphosphatase deficiency (FBPase deficiency) is a rare inborn error of metabolism that affects gluconeogenesis. Ketotic hypoglycemia is the main symptom and can occur at any age, usually after long periods of fasting or during illness. The diagnosis may be achieved by measurement of the enzyme activity in a liver sample, but FBP1 analysis has become the most common approach.

AIM

To characterize the genotype of Southern Brazilian FBPase-deficient patients.

METHODOLOGY

The FBP1 gene of six unrelated patients (one had consanguineous parents) with previous diagnoses of FBPase deficiency (enzymatic, pts A, B, D, E; genetic through Next-Generation Sequencing-NGS, pt F; enzymatic and Sanger sequencing, pt C) was first analyzed through NGS. Pathogenic variants found in NGS were confirmed by Sanger sequencing. The pathogenicity of novel missense variants was evaluated through in silico analysis.

RESULTS

Five patients (pt A, B, D, E, F) had their genotype identified by NGS, all of them being homozygous. In Pt C, NGS detected only one pathogenic variant. Among the 11 alleles analyzed, only three variants were found, two being novel: c.958G > A and c.986T > C. In silico analysis indicated the pathogenicity of both variants. Interestingly, the three variants seem to be linked to specific haplotypes, indicating that an endogamy effect may be acting on these alleles in the population of Southern Brazil.

CONCLUSIONS

Our data suggest that NGS is a good tool for the diagnosis of FBPase deficiency. Variants c.958G > A and c.986T > C are the most prevalent variants in the country.

Novel mutation in Teneurin 3 found to co-segregate in all affecteds in a multi-generation family with developmental dysplasia of the hip

DDH is a debilitating condition characterized by incomplete formation of the acetabulum leading to dislocation of the hip, suboptimal joint function and accelerated wear of the articular cartilage resulting in early onset crippling arthritis of the hip in 20-40 year olds. Current diagnostic tests in newborns using physical manipulation of the femur or ultrasound either under or over-diagnose this condition. Developing an accurate, cost effective diagnostic test is a goal of this study. To better understand the biologic pathways involved in acetabular development, DNA from severely affected individuals in a four generation family that showed inter-generational transmission of the disorder was isolated and whole exome sequenced. A novel A to C transversion at position 183721398 on human chromosome four was found to co-segregate with the affected phenotype in this family. This mutation encodes a glutamine to proline change at position 2665 in the Teneurin 3 (TENM3) gene and was judged damaging by four prediction programs. Eight week old knock-in mutant mice show delayed development of the left acetabulum and the left glenoid fossa as shown by the presence of more Alcian blue staining on the socket rims of both the hip and the shoulder. We hypothesize that mutated TENM3 will slow chondrogenesis. MMP13 has been shown to impair extracellular matrix remodeling and suppress differentiation. Bone marrow cells from the knock-in mouse were found to overexpress MMP13 with or without BMP2 stimulation. This variant may elucidate pathways responsible for normal hip development and become part of an accurate test for DDH. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

The clinical spectrum of CASQ1-related myopathy

OBJECTIVE

To identify and characterize patients with calsequestrin 1 (CASQ1)-related myopathy.

METHODS

Patients selected according to histopathologic features underwent CASQ1 genetic screening. CASQ1-mutated patients were clinically evaluated and underwent muscle MRI. Vacuole morphology and vacuolated fiber type were characterized.

RESULTS

Twenty-two CASQ1-mutated patients (12 families) were identified, 21 sharing the previously described founder mutation (p.Asp244Gly) and 1 with the p.Gly103Asp mutation. Patients usually presented in the sixth decade with exercise intolerance and myalgias and later developed mild to moderate, slowly progressive proximal weakness with quadriceps atrophy and scapular winging. Muscle MRI (n = 11) showed a recurrent fibrofatty substitution pattern. Three patients presented subclinical cardiac abnormalities. Muscle histopathology in patients with p.Asp244Gly showed vacuoles in type II fibers appearing empty in hematoxylin-eosin, Gomori, and nicotinamide adenine dinucleotide (NADH) tetrazolium reductase stains but strongly positive for sarcoplasmic reticulum proteins. The muscle histopathology of p.Gly103Asp mutation was different, showing also NADH-positive accumulation consistent with tubular aggregates.

CONCLUSIONS

We report the clinical and molecular details of the largest cohort of CASQ1-mutated patients. A possible heart involvement is presented, further expanding the phenotype of the disease. One mutation is common due to a founder effect, but other mutations are possible. Because of a paucity of symptoms, it is likely that CASQ1 mutations may remain undiagnosed if a muscle biopsy is not performed.

Fabry disease in the Spanish population: observational study with detection of 77 patients

Background

Fabry disease is a multisystemic lysosomal storage disorder caused by the impairment of α-galactosidase A. The incidence of this rare disease is underestimated due to delayed diagnosis. Moreover, the management of the identified subjects is often complicated by the detection of variants of unclear diagnostic interpretation, usually identified in screening studies. We performed an observational study based on biochemical and genetic analysis of 805 dried blood spot samples from patients with clinical symptoms or family history of this pathology, which were collected from 109 Spanish hospitals, all over the country.

Results

We identified 77 new diagnosed patients with mutations related to classical Fabry disease, as well as 2 subjects with c.374A > T; p.His125Leu, a possible new mutation that need to be confirmed. Additionally, we detected 8 subjects carrying genetic variants possibly linked to late onset Fabry disease (p.Arg118Cys and p.Ala143Thr), 4 cases with polymorphism p.Asp313Tyr and 36 individuals with single nucleotide polymorphisms in intronic regions of GLA. Five of the identified mutations (c.431delG; c.1182delA; c.374A > T; c.932 T > C; c.125 T > A; c.778G > A), which were associated with a classical phenotype have not been previously described. Moreover 3 subjects presenting complex haplotypes made up by the association of intronic variants presented impaired levels of GLA transcripts and Gb3 deposits in skin biopsy.

Conclusions

Enzymatic screening for Fabry Disease in risk population (2 or more clinical manifestations or family history of the disease) helped to identify undiagnosed patients and unravel the impairment of GLA expression in some subjects with complex haplotypes.

Electronic supplementary material

The online version of this article (10.1186/s13023-018-0792-8) contains supplementary material, which is available to authorized users.

Two microcephaly-associated novel missense mutations in CASK specifically disrupt the CASK-neurexin interaction

Deletion and truncation mutations in the X-linked gene CASK are associated with severe intellectual disability (ID), microcephaly and pontine and cerebellar hypoplasia in girls (MICPCH). The molecular origin of CASK-linked MICPCH is presumed to be due to disruption of the CASK-Tbr-1 interaction. This hypothesis, however, has not been directly tested. Missense variants in CASK are typically asymptomatic in girls. We report three severely affected girls with heterozygous CASK missense mutations (M519T (2), G659D (1)) who exhibit ID, microcephaly, and hindbrain hypoplasia. The mutation M519T results in the replacement of an evolutionarily invariant methionine located in the PDZ signaling domain known to be critical for the CASK-neurexin interaction. CASK^M519T is incapable of binding to neurexin, suggesting a critically important role for the CASK-neurexin interaction. The mutation G659D is in the SH3 (Src homology 3) domain of CASK, replacing a semi-conserved glycine with aspartate. We demonstrate that the CASK^G659D mutation affects the CASK protein in two independent ways: (1) it increases the protein's propensity to aggregate; and (2) it disrupts the interface between CASK's PDZ (PSD95, Dlg, ZO-1) and SH3 domains, inhibiting the CASK-neurexin interaction despite residing outside of the domain deemed critical for neurexin interaction. Since heterozygosity of other aggregation-inducing mutations (e.g., CASK^W919R) does not produce MICPCH, we suggest that the G659D mutation produces microcephaly by disrupting the CASK-neurexin interaction. Our results suggest that disruption of the CASK-neurexin interaction, not the CASK-Tbr-1 interaction, produces microcephaly and cerebellar hypoplasia. These findings underscore the importance of functional validation for variant classification.

Multiple Property Tolerance Analysis for the Evaluation of Missense Mutations

Computational prediction of the impact of a mutation on protein function is still not accurate enough for clinical diagnostics without additional human expert analysis. Sequence alignment-based methods have been extensively used but their results highly depend on the quality of the input alignments and the choice of sequences. Incorporating the structural information with alignments improves prediction accuracy. Here, we present a conservation of amino acid properties method for mutation prediction, Multiple Properties Tolerance Analysis (MuTA), and a new strategy, MuTA/S, to incorporate the solvent accessible surface (SAS) property into MuTA. Instead of combining multiple features by machine learning or mathematical methods, an intuitive strategy is used to divide the residues of a protein into different groups, and in each group the properties used is adjusted.

The results for LacI, lysozyme, and HIV protease show that MuTA performs as well as the widely used SIFT algorithm while MuTA/S outperforms SIFT and MuTA by 2%–25% in terms of prediction accuracy. By incorporating the SAS term alone, the alignment dependency of overall prediction accuracy is significantly reduced. MuTA/S also defines a new way to incorporate any structural features and knowledge and may lead to more accurate predictions.

Development of pathogenicity predictors specific for variants that do not comply with clinical guidelines for the use of computational evidence

Background

Strict guidelines delimit the use of computational information in the clinical setting, due to the still moderate accuracy of in silico tools. These guidelines indicate that several tools should always be used and that full coincidence between them is required if we want to consider their results as supporting evidence in medical decision processes. Application of this simple rule certainly decreases the error rate of in silico pathogenicity assignments. However, when predictors disagree this rule results in the rejection of potentially valuable information for a number of variants. In this work, we focus on these variants of the protein sequence and develop specific predictors to help improve the success rate of their annotation.

Results

We have used a set of 59,442 protein sequence variants (15,723 pathological and 43,719 neutral) from 228 proteins to identify those cases for which pathogenicity predictors disagree. We have repeated this process for all the possible combinations of five known methods (SIFT, PolyPhen-2, PON-P2, CADD and MutationTaster2). For each resulting subset we have trained a specific pathogenicity predictor. We find that these specific predictors are able to discriminate between neutral and pathogenic variants, with a success rate different from random. They tend to outperform the constitutive methods but this trend decreases as the performance of the constitutive predictor improves (e.g. with PON-P2 and PolyPhen-2). We also find that specific methods outperform standard consensus methods (Condel and CAROL).

Conclusion

Focusing development efforts on the case of variants for which known methods disagree we may obtain pathogenicity predictors with improved performances. Although we have not yet reached the success rate that allows the use of this computational evidence in a clinical setting, the simplicity of the approach indicates that more advanced methods may reach this goal in a close future.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3914-0) contains supplementary material, which is available to authorized users.

Molecular and functional characterization of the BMPR2 gene in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension is a progressive disease that causes the obstruction of precapillary pulmonary arteries and a sustained increase in pulmonary vascular resistance. The aim was to analyze functionally the variants found in the BMPR2 gene and to establish a genotype-phenotype correlation. mRNA expression studies were performed using pSPL3 vector, studies of subcellular localization were performed using pEGFP-N1 vector and luciferase assays were performed using pGL3-Basic vector. We have identified 30 variants in the BMPR2 gene in 27 of 55 patients. In 16 patients we detected pathogenic mutations. Minigene assays revealed that 6 variants (synonymous, missense) result in splicing defect. By immunofluorescence assay, we observed that 4 mutations affect the protein localization. Finally, 4 mutations located in the 5'UTR region showed a decreased transcriptional activity in luciferase assays. Genotype-phenotype correlation, revealed that patients with pathogenic mutations have a more severe phenotype (sPaP p = 0.042, 6MWT p = 0.041), a lower age at diagnosis (p = 0.040) and seemed to have worse response to phosphodiesterase-5-inhibitors (p = 0.010). Our study confirms that in vitro expression analysis is a suitable approach in order to investigate the phenotypic consequences of the nucleotide variants, especially in cases where the involved genes have a pattern of expression in tissues of difficult access.

Mitochondrial DNA Mutations in Grade II and III Glioma Cell Lines Are Associated with Significant Mitochondrial Dysfunction and Higher Oxidative Stress

The role of mitochondria in tumorigenesis has regained much attention as it could dysregulate cellular energetics, oxidative stress and apoptosis. However, the role of mitochondria in different grade gliomasis still unknown. This study aimed to identify mitochondrial DNA (mtDNA) sequence variations that could possibly affect the mitochondrial functions and also the oxidative stress status. Three different grades of human glioma cell lines and a normal human astrocyte cell line were cultured in-vitro and tested for oxidative stress biomarkers. Relative oxidative stress level, mitochondria activity, and mitochondrial mass were determined by live cell imaging with confocal laser scanning microscope using CM-H₂DCFDA, MitoTracker Green, and MitoTracker Orange stains. The entire mitochondrial genome was sequenced using the AffymetrixGeneChip Human Mitochondrial Resequencing Array 2.0. The mitochondrial sequence variations were subjected to phylogenetic haplogroup assessment and pathogenicity of the mutations were predicted using pMUT and PolyPhen2. The Grade II astrocytoma cells showed increased oxidative stress wherea high level of 8-OHdG and oxidative stress indicator were observed. Simultaneously, Grade II and III glioma cells showed relatively poor mitochondria functions and increased number of mutations in the coding region of the mtDNA which could be due to high levels of oxidative stress in these cells. These non-synonymous mtDNA sequence variations were predicted to be pathogenic and could possibly lead to protein dysfunction, leading to oxidative phosphorylation (OXPHOS) impairment, mitochondria dysfunction and could create a vicious cycle of oxidative stress. The Grade IV cells had no missense mutation but preserved intact mitochondria and excellent antioxidant defense mechanisms thus ensuring better survival. In conclusion, Grade II and III glioma cells demonstrated coding region mtDNA mutations, leading to mitochondrial dysfunction and higher oxidative stress.

A novel MTTT mutation m.15933G > A revealed in analysis of mitochondrial DNA in patients with suspected mitochondrial disease

Background

Mitochondrial diseases present with variable multi-organ symptoms. Common disease-causing mutations in mitochondrial DNA (mtDNA) are regularly screened in diagnostic work-up, but novel mutations may remain unnoticed.

Methods

Patients (N = 66) with a clinical suspicion of mitochondrial disease were screened for their mtDNA coding region using conformation sensitive gel electrophoresis and sequencing. Long-PCR was used to detect deletions followed by POLG1 sequencing in patients with multiple deletions.

Results

We discovered three novel mtDNA variants that included m.8743G > C, m.11322A > G and m.15933G > A. The novel MTTT variant m.15933G > A is suggested to be pathogenic. Analysis revealed also multiple mtDNA deletions in two patients and five nonsynonymous variants that were putatively pathogenic according to in-silico prediction algorithms. In addition, a rare haplogroup H associated m.7585_7586insT variant was discovered.

Conclusions

Among patients with a suspected mitochondrial disease, a novel MTTT variant m.15933G > A was discovered and is suggested to be pathogenic. In addition, several putatively pathogenic nonsynonymous variants and rare variants were found. These findings highlight the importance of coding region mtDNA screening among patients with clinical features suggesting a mitochondrial disease, but who lack the common mitochondrial disease mutations.

Complex inheritance in Pulmonary Arterial Hypertension patients with several mutations

Pulmonary Arterial Hypertension (PAH) is a rare and progressive disease with low incidence and prevalence, and elevated mortality. PAH is characterized by increased mean pulmonary artery pressure. The aim of this study was to analyse patients with combined mutations in BMPR2, ACVRL1, ENG and KCNA5 genes and to establish a genotype-phenotype correlation. Major genes were analysed by polymerase chain reaction (PCR) and direct sequencing. Genotype-phenotype correlation was performed. Fifty-seven (28 idiopathic PAH, 29 associated PAH group I) were included. Several mutations in different genes, classified as pathogenic by in silico analysis, were present in 26% of PAH patients. The most commonly involved gene was BMPR2 (12 patients) followed by ENG gene (9 patients). ACVRL1 and KCNA5 genes showed very low incidence of mutations (5 and 1 patients, respectively). Genotype-phenotype correlation showed statistically significant differences for gender (p = 0.045), age at diagnosis (p = 0.035), pulmonary vascular resistance (p = 0.030), cardiac index (p = 0.035) and absence of response to treatment (p = 0.011). PAH is consequence of a heterogeneous constellation of genetic arrangements. Patients with several pathogenic mutations seem to display a more severe phenotype.

Mutational and clinical analysis of the ENG gene in patients with pulmonary arterial hypertension

Background

Pulmonary arterial hypertension (PAH) is a rare vascular disorder characterized by a capillary wedge pressure ≤ 15 mmHg and a mean pulmonary arterial pressure ≥ 25 mmHg at rest. PAH can be idiopathic, heritable or associated with other conditions. The aim of this study was to analyze the Endoglin (ENG) gene and assess the influence of the c.572G > A (p.G191D) mutation in patients with idiopathic or associated PAH. The correlation between the pathogenic mutations and clinical and functional parameters was further analyzed.

Results

Sixteen different changes in the ENG gene were found in 44 out of 57 patients. After in silico analysis, we classified eight mutations as pathogenic in 16 of patients. The c.572G>A (p.G191D) variation was observed in ten patients, and the analysis for the splicing process using hybrid minigenes, with pSPL3 vector to assess splicing alterations, do not generate a new transcript. Age at diagnosis (p = 0.049) and the 6-min walking test (p = 0.041) exhibited statistically significant differences between carriers and non-carriers of pathogenic mutations. Patients with pathogenic mutations exhibited disease symptoms 8 years before non-carriers. Five patients with pathogenic mutations were carriers of another mutation in the BMPR2 or ACVRL1 genes.

Conclusions

We present a series of PAH patients with mutations in the ENG gene, some of them not previously described, exhibiting clinical and hemodynamic alterations suggesting that the presence of these mutations may be associated with the severity of the disease. Moreover, genetic analysis in patients with PAH may be of clinical relevance and indicates the complexity of the genetic background.

Comparison of pathogenicity prediction tools on missense variants in RYR1 and CACNA1S associated with malignant hyperthermia

BACKGROUND

Malignant hyperthermia (MH) is a pharmacogenetic disorder that has been linked to the skeletal muscle calcium release channel (RYR1) and the α1S subunit of the voltage-dependent L-type calcium channel (CACNA1S). Genomic DNA capture and next generation sequencing are becoming the preferred method to identify mutations in these genes. Bioinformatic pathogenicity prediction of identified variants may help to determine if these variants are in fact disease causing.

METHODS

Eight pathogenicity prediction programmes freely available on the web were used to determine their ability to correctly predict the impact of a missense variant on RyR1 or dihydropyridine receptor (DHPR) protein function. We tested MH-causative variants, variants that had been shown to alter calcium release in cells, and common sequence variants in RYR1 and CACNA1S.

RESULTS

None of the prediction programmes was able to identify all of the variants tested correctly as either 'damaging' (MH-causative variants, variants that had been shown to alter calcium release in cells) or as 'benign' (common sequence variants). The overall sensitivity of predictions ranged from 84% to 100% depending on the programme used, with specificity from 25% to 83%.

CONCLUSIONS

In this study we determined the sensitivity and specificity of bioinformatic pathogenicity prediction tools for RYR1 and CACNA1S. We suggest that the prediction results should be treated with caution, as none of the programmes tested predicted all the variants correctly and should only be used in combination with other available data (functional assays, segregation analysis).

Genomic screening of ABCA4 and array CGH analysis underline the genetic variability of Greek patients with inherited retinal diseases

Background

Retinal dystrophies are a clinically and genetically heterogeneous group of disorders which affect more than two million people worldwide. The present study focused on the role of the ABCA4 gene in the pathogenesis of hereditary retinal dystrophies (autosomal recessive Stargardt disease, autosomal recessive cone-rod dystrophy, and autosomal recessive retinitis pigmentosa) in patients of Greek origin.

Materials and methods

Our cohort included 26 unrelated patients and their first degree healthy relatives. The ABCA4 mutation screening involved Sanger sequencing of all exons and flanking regions. Evaluation of novel variants included sequencing of control samples, family segregation analysis and characterization by in silico prediction tools. Twenty five patients were also screened for copy number variations by array-comparative genomic hybridization.

Results

Excluding known disease-causing mutations and polymorphisms, two novel variants were identified in coding and non-coding regions of ABCA4. Array-CGH analysis revealed two partial deletions of USH2A and MYO3A in two patients with nonsyndromic autosomal recessive retinitis pigmentosa.

Conclusions

The ABCA4 mutation spectrum in Greek patients differs from other populations. Bioinformatic tools, segregation analysis along with clinical data from the patients seemed to be crucial for the evaluation of genetic variants and particularly for the discrimination between causative and non-causative variants.

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Sixteen known pathological genetic variants were identified in ABCA4 gene in Greek patients with retinal dystrophies.

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Two novel variants were found in patients with Stargardt’s disease and cone-rod dystrophy respectively.

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Two reported mutations in Stargardt's patients were identified in retinitis pigmentosa and cone-rod dystrophy patients.

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The mutations p.Gly1961Glu and p.Ala1038Val, which are common in other populations, where also found in our cohort consisted of 26 Greek patients.

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Array-comparative genome hybridization revealed large deletions in two out of the 25 cases studied.

Analysis of Genes Involved in Body Weight Regulation by Targeted Re-Sequencing

Introduction

Genes involved in body weight regulation that were previously investigated in genome-wide association studies (GWAS) and in animal models were target-enriched followed by massive parallel next generation sequencing.

Methods

We enriched and re-sequenced continuous genomic regions comprising FTO, MC4R, TMEM18, SDCCAG8, TKNS, MSRA and TBC1D1 in a screening sample of 196 extremely obese children and adolescents with age and sex specific body mass index (BMI) ≥ 99^th percentile and 176 lean adults (BMI ≤ 15^th percentile). 22 variants were confirmed by Sanger sequencing. Genotyping was performed in up to 705 independent obesity trios (extremely obese child and both parents), 243 extremely obese cases and 261 lean adults.

Results and Conclusion

We detected 20 different non-synonymous variants, one frame shift and one nonsense mutation in the 7 continuous genomic regions in study groups of different weight extremes. For SNP Arg695Cys (rs58983546) in TBC1D1 we detected nominal association with obesity (p_TDT = 0.03 in 705 trios). Eleven of the variants were rare, thus were only detected heterozygously in up to ten individual(s) of the complete screening sample of 372 individuals. Two of them (in FTO and MSRA) were found in lean individuals, nine in extremely obese. In silico analyses of the 11 variants did not reveal functional implications for the mutations. Concordant with our hypothesis we detected a rare variant that potentially leads to loss of FTO function in a lean individual. For TBC1D1, in contrary to our hypothesis, the loss of function variant (Arg443Stop) was found in an obese individual. Functional in vitro studies are warranted.

Computational analysis of prolyl hydroxylase domain-containing protein 2 (PHD2) mutations promoting polycythemia insurgence in humans

Idiopathic erythrocytosis is a rare disease characterized by an increase in red blood cell mass due to mutations in proteins of the oxygen-sensing pathway, such as prolyl hydroxylase 2 (PHD2). Here, we present a bioinformatics investigation of the pathological effect of twelve PHD2 mutations related to polycythemia insurgence. We show that few mutations impair the PHD2 catalytic site, while most localize to non-enzymatic regions. We also found that most mutations do not overlap the substrate recognition site, suggesting a novel PHD2 binding interface. After a structural analysis of both binding partners, we suggest that this novel interface is responsible for PHD2 interaction with the LIMD1 tumor suppressor.

Performance of In Silico Tools for the Evaluation of UGT1A1 Missense Variants

Variations in the gene encoding uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) are particularly important because they have been associated with hyperbilirubinemia in Gilbert's and Crigler-Najjar syndromes as well as with changes in drug metabolism. Several variants associated with these phenotypes are nonsynonymous single-nucleotide polymorphisms (nsSNPs). Bioinformatics approaches have gained increasing importance in predicting the functional significance of these variants. This study was focused on the predictive ability of bioinformatics approaches to determine the pathogenicity of human UGT1A1 nsSNPs, which were previously characterized at the protein level by in vivo and in vitro studies. Using 16 Web algorithms, we evaluated 48 nsSNPs described in the literature and databases. Eight of these algorithms reached or exceeded 90% sensitivity and six presented a Matthews correlation coefficient above 0.46. The best-performing method was MutPred, followed by Sorting Intolerant from Tolerant (SIFT). The prediction measures varied significantly when predictors such us SIFT, polyphen-2, and Prediction of Pathological Mutations on Proteins were run with their native alignment generated by the tool, or with an input alignment that was strictly built with UGT1A1 orthologs and manually curated. Our results showed that the prediction performance of some methods based on sequence conservation analysis can be negatively affected when nsSNPs are positioned at the hypervariable or constant regions of UGT1A1 ortholog sequences.

Insights into the proline hydroxylase (PHD) family, molecular evolution and its impact on human health

PHDs (proline hydroxylases) are a small protein family found in all organisms, considered the central regulator of the molecular hypoxia response due to PHDs being completely inactivated under low oxygen concentration. At physiological oxygen concentration, PHDs drive the degradation of the HIF-1α (hypoxia-inducible factor 1-α), which is responsible for upregulating the expression of genes involved in the cellular response to hypoxia. Hypoxia is a common feature of most tumors, in particular during metastasis development. Indeed, cancer reacts by activating pathways promoting new blood vessel formation and activating strategies aimed to improve survival. In this scenario, the PHD family regulates the activation of HIF-1α and cell-cycle regulation. Several PHD mutations were found in cancer patients, underlining their importance for human health. Here, we propose a Bayesian model able to predict the pathological effect of human PHD mutations and their correlation with cancer outcome. The model was developed through an integrative in silico approach, where data collected from the literature has been coupled with sequence evolution and structural analysis. The model was used to assess 135 human PHD variants. Finally, bioinformatics characterization was used to demonstrate how few amino acid changes are able to explain the functional specialization of PHD family members and their physiological role in human health.

Biophysics of protein evolution and evolutionary protein biophysics

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

Fine Mapping of a GWAS-Derived Obesity Candidate Region on Chromosome 16p11.2

INTRODUCTION

Large-scale genome-wide association studies (GWASs) have identified 97 chromosomal loci associated with increased body mass index in population-based studies on adults. One of these SNPs, rs7359397, tags a large region (approx. 1MB) with high linkage disequilibrium (r2>0.7), which comprises five genes (SH2B1, APOBR, sulfotransferases: SULT1A1 and SULT1A2, TUFM). We had previously described a rare mutation in SH2B1 solely identified in extremely obese individuals but not in lean controls.

METHODS

The coding regions of the genes APOBR, SULT1A1, SULT1A2, and TUFM were screened for mutations (dHPLC, SSCP, Sanger re-sequencing) in 95 extremely obese children and adolescents. Detected non-synonymous variants were genotyped (TaqMan SNP Genotyping, MALDI TOF, PCR-RFLP) in independent large study groups (up to 3,210 extremely obese/overweight cases, 485 lean controls and 615 obesity trios). In silico tools were used for the prediction of potential functional effects of detected variants.

RESULTS

Except for TUFM we detected non-synonymous variants in all screened genes. Two polymorphisms rs180743 (APOBR p.Pro428Ala) and rs3833080 (APOBR p.Gly369_Asp370del9) showed nominal association to (extreme) obesity (uncorrected p = 0.003 and p = 0.002, respectively). In silico analyses predicted a functional implication for rs180743 (APOBR p.Pro428Ala). Both APOBR variants are located in the repetitive region with unknown function.

CONCLUSION

Variants in APOBR contributed as strongly as variants in SH2B1 to the association with extreme obesity in the chromosomal region chr16p11.2. In silico analyses implied no functional effect of several of the detected variants. Further in vitro or in vivo analyses on the functional implications of the obesity associated variants are warranted.

Mutation update for GNE gene variants associated with GNE myopathy

The GNE gene encodes the rate-limiting, bifunctional enzyme of sialic acid biosynthesis, uridine diphosphate-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE). Biallelic GNE mutations underlie GNE myopathy, an adult-onset progressive myopathy. GNE myopathy-associated GNE mutations are predominantly missense, resulting in reduced, but not absent, GNE enzyme activities. The exact pathomechanism of GNE myopathy remains unknown, but likely involves aberrant (muscle) sialylation. Here, we summarize 154 reported and novel GNE variants associated with GNE myopathy, including 122 missense, 11 nonsense, 14 insertion/deletions, and seven intronic variants. All variants were deposited in the online GNE variation database (http://www.dmd.nl/nmdb2/home.php?select_db=GNE). We report the predicted effects on protein function of all variants well as the predicted effects on epimerase and/or kinase enzymatic activities of selected variants. By analyzing exome sequence databases, we identified three frequently occurring, unreported GNE missense variants/polymorphisms, important for future sequence interpretations. Based on allele frequencies, we estimate the world-wide prevalence of GNE myopathy to be ∼4-21/1,000,000. This previously unrecognized high prevalence confirms suspicions that many patients may escape diagnosis. Awareness among physicians for GNE myopathy is essential for the identification of new patients, which is required for better understanding of the disorder's pathomechanism and for the success of ongoing treatment trials.

Variability in pathogenicity prediction programs: impact on clinical diagnostics

Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb-girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss-of-function and gain-of-function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies.

Computational pipeline to identify and characterize functional mutations in ornithine transcarbamylase deficiency

Ornithine transcarbamylase (OTC) (E.C. 2.1.3.3) is one of the enzymes in the urea cycle, which involves in a sequence of reactions in the liver cells. During protein assimilation in our body surplus nitrogen is made, this open nitrogen is altered into urea and expelled out of the body by kidneys, in this cycle OTC helps in the conversion of free toxic nitrogen into urea. Ornithine transcarbamylase deficiency (OTCD: OMIM#311250) is triggered by mutation in this OTC gene. To date more than 200 mutations have been noted. Mutation in OTC gene indicates alteration in enzyme production, which upsets the ability to carry out the chemical reaction. The computational analysis was initiated to identify the deleterious nsSNPs in OTC gene in causing OTCD using five different computational tools such as SIFT, PolyPhen 2, I-Mutant 3, SNPs&Go, and PhD-SNP. Studies on the molecular basis of OTC gene and OTCD have been done partially till date. Hence, in silico categorization of functional SNPs in OTC gene can provide valuable insight in near future in the diagnosis and treatment of OTCD.

Molecular damage in Fabry disease: characterization and prediction of alpha-galactosidase A pathological mutations

Loss-of-function mutations of the enzyme alpha-galactosidase A (GLA) causes Fabry disease (FD), that is a rare and potentially fatal disease. Identification of these pathological mutations by sequencing is important because it allows an early treatment of the disease. However, before taking any treatment decision, if the mutation identified is unknown, we first need to establish if it is pathological or not. General bioinformatic tools (PolyPhen-2, SIFT, Condel, etc.) can be used for this purpose, but their performance is still limited. Here we present a new tool, specifically derived for the assessment of GLA mutations. We first compared mutations of this enzyme known to cause FD with neutral sequence variants, using several structure and sequence properties. Then, we used these properties to develop a family of prediction methods adapted to different quality requirements. Trained and tested on a set of known Fabry mutations, our methods have a performance (Matthews correlation: 0.56-0.72) comparable or better than that of the more complex method, Polyphen-2 (Matthews correlation: 0.61), and better than those of SIFT (Matthews correl.: 0.54) and Condel (Matthews correl.: 0.51). This result is validated in an independent set of 65 pathological mutations, for which our method displayed the best success rate (91.0%, 87.7%, and 73.8%, for our method, PolyPhen-2 and SIFT, respectively). These data confirmed that our specific approach can effectively contribute to the identification of pathological mutations in GLA, and therefore enhance the use of sequence information in the identification of undiagnosed Fabry patients.

Congenital hypogonadotropic hypogonadism with split hand/foot malformation: a clinical entity with a high frequency of FGFR1 mutations

PURPOSE

Congenital hypogonadotropic hypogonadism (CHH) and split hand/foot malformation (SHFM) are two rare genetic conditions. Here we report a clinical entity comprising the two.

METHODS

We identified patients with CHH and SHFM through international collaboration. Probands and available family members underwent phenotyping and screening for FGFR1 mutations. The impact of identified mutations was assessed by sequence- and structure-based predictions and/or functional assays.

RESULTS

We identified eight probands with CHH with (n = 3; Kallmann syndrome) or without anosmia (n = 5) and SHFM, seven of whom (88%) harbor FGFR1 mutations. Of these seven, one individual is homozygous for p.V429E and six individuals are heterozygous for p.G348R, p.G485R, p.Q594*, p.E670A, p.V688L, or p.L712P. All mutations were predicted by in silico analysis to cause loss of function. Probands with FGFR1 mutations have severe gonadotropin-releasing hormone deficiency (absent puberty and/or cryptorchidism and/or micropenis). SHFM in both hands and feet was observed only in the patient with the homozygous p.V429E mutation; V429 maps to the fibroblast growth factor receptor substrate 2α binding domain of FGFR1, and functional studies of the p.V429E mutation demonstrated that it decreased recruitment and phosphorylation of fibroblast growth factor receptor substrate 2α to FGFR1, thereby resulting in reduced mitogen-activated protein kinase signaling.

CONCLUSION

FGFR1 should be prioritized for genetic testing in patients with CHH and SHFM because the likelihood of a mutation increases from 10% in the general CHH population to 88% in these patients.

A comprehensive evaluation of collapsing methods using simulated and real data: excellent annotation of functionality and large sample sizes required

The advent of next generation sequencing (NGS) technologies enabled the investigation of the rare variant-common disease hypothesis in unrelated individuals, even on the genome-wide level. Analysis of this hypothesis requires tailored statistical methods as single marker tests fail on rare variants. An entire class of statistical methods collapses rare variants from a genomic region of interest (ROI), thereby aggregating rare variants. In an extensive simulation study using data from the Genetic Analysis Workshop 17 we compared the performance of 15 collapsing methods by means of a variety of pre-defined ROIs regarding minor allele frequency thresholds and functionality. Findings of the simulation study were additionally confirmed by a real data set investigating the association between methotrexate clearance and the SLCO1B1 gene in patients with acute lymphoblastic leukemia. Our analyses showed substantially inflated type I error levels for many of the proposed collapsing methods. Only four approaches yielded valid type I errors in all considered scenarios. None of the statistical tests was able to detect true associations over a substantial proportion of replicates in the simulated data. Detailed annotation of functionality of variants is crucial to detect true associations. These findings were confirmed in the analysis of the real data. Recent theoretical work showed that large power is achieved in gene-based analyses only if large sample sizes are available and a substantial proportion of causing rare variants is present in the gene-based analysis. Many of the investigated statistical approaches use permutation requiring high computational cost. There is a clear need for valid, powerful and fast to calculate test statistics for studies investigating rare variants.

BTNL2 gene SNPs as a contributing factor to sarcoidosis pathogenesis in a cohort of Greek patients

Sarcoidosis is a multisystemic granulomatous disease of unknown etiology that primarily affects adults between the ages of 20 and 40 years old. It is characterized by the activation of Th1 lymphocytes resulting in the production of inflammatory cytokines and the formation of noncaseating epithelioid cell granulomas in affected tissues. The lungs and lymphatic system are the ones most frequently affected. The disease usually presents spontaneous remission in the first two years and, in a few patients, the disease progresses to pulmonary fibrosis or other fatal complications depending on the affected organ. The pathogenesis of sarcoidosis is still not clearly defined, and is considered an interaction between the environment and risk alleles in many genes.

The present case control study consisted of 146 Greek patients with sarcoidosis and 90 healthy volunteers from the same ethnic group. The coding and neighboring intronic regions of the BTNL2 gene were sequenced and risk alleles were compared amongst the two groups. Thirty-seven different variants were detected from which 12 were synonymous substitutions and 25 non-synonymous. With the help of in silico tools (SIFT, PolyPhen, PROVEAN, PMut and EX_SKIP), 13 variants were classified as possible pathological risk variants including 4 novel ones. The most common risk variants contributing to phenotypic modulation of sarcoidosis were p.S360G and p.S334L, with the latter contributing to a more severe disease stage with extra-pulmonary manifestations such as skin granulomas and relapses being more common.

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Thirteen pathological risk variants were discovered in BTNL2 gene in sarcoidosis patients.

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The common risk variant p.S360G was found in cases (37.67%) and controls (30%).

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The 2nd most common variant p.S334L was found in cases (16.43%) and controls (12.22%).

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Six novel variants were detected with 4 deemed pathological.

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Coinheritance of common and novel variants affected the final clinical phenotype.

Point mutation frequency in the FMR1 gene as revealed by fragile X syndrome screening

Fragile X syndrome (FXS) is a common cause of intellectual disability, developmental delay and autism spectrum disorders. This syndrome is due to a functional loss of the FMR1 gene product FMRP, and, in most cases, it is caused by CGG repeat expansion in the FMR1 promoter. Yet, also other FMR1 mutations may cause a FXS-like phenotype. Since standard molecular testing does not include the analysis of the FMR1 coding region, the prevalence of point mutations causing FXS is not well known. Here, high resolution melting (HRM) was used to screen for FMR1 gene mutations in 508 males with clinical signs of mental retardation and developmental delay, but without CGG and GCC repeat expansions in the FMR1 gene and AFF2 genes, respectively. Sequence variations were identified by HRM analysis and verified by direct DNA sequencing. Two novel missense mutations (p.Gly482Ser in one patient and p.Arg534His in two unrelated patients), one intronic and two 3'-untranslated region (UTR) variations were identified in the FMR1 gene. Missense mutations in the FMR1 gene might account for a considerable proportion of cases in male patients with FXS-related symptoms, such as those linked to mental retardation and developmental delay.

Computational analysis of functional single nucleotide polymorphisms associated with the CYP11B2 gene

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans and play a major role in the genetics of human phenotype variation and the genetic basis of human complex diseases. Recently, there is considerable interest in understanding the possible role of the CYP11B2 gene with corticosterone methyl oxidase deficiency, primary aldosteronism, and cardio-cerebro-vascular diseases. Hence, the elucidation of the function and molecular dynamic behavior of CYP11B2 mutations is crucial in current genomics. In this study, we investigated the pathogenic effect of 51 nsSNPs and 26 UTR SNPs in the CYP11B2 gene through computational platforms. Using a combination of SIFT, PolyPhen, I-Mutant Suite, and ConSurf server, four nsSNPs (F487V, V129M, T498A, and V403E) were identified to potentially affect the structure, function, and activity of the CYP11B2 protein. Furthermore, molecular dynamics simulation and structure analyses also confirmed the impact of these nsSNPs on the stability and secondary properties of the CYP11B2 protein. Additionally, utilizing the UTRscan, MirSNP, PolymiRTS and miRNASNP, three SNPs in the 3'UTR region were predicted to exhibit a pattern change in the upstream open reading frames (uORF), and eight microRNA binding sites were found to be highly affected due to 3'UTR SNPs. This cataloguing of deleterious SNPs is essential for narrowing down the number of CYP11B2 mutations to be screened in genetic association studies and for a better understanding of the functional and structural aspects of the CYP11B2 protein.

MutaCYP: Classification of missense mutations in human cytochromes P450

BACKGROUND

Cytochrome P450 monooxygenases (CYPs) represent a large and diverse family of enzymes involved in various biological processes in humans. Individual genome sequencing has revealed multiple mutations in human CYPs, and many missense mutations have been associated with variety of diseases. Since 3D structures are not resolved for most human CYPs, there is a need for a reliable sequence-based prediction that discriminates benign and disease causing mutations.

METHODS

A new prediction method (MutaCYP) has been developed for scoring de novo missense mutations to have a deleterious effect. The method utilizes only five features, all of which are sequence-based: predicted relative solvent accessibility (RSA), variance of predicted RSA among the residues in close sequence proximity, Z-score of Shannon entropy for a given position, difference in similarity scores and weighted difference in size between wild type and new amino acids. The method is based on a single neural network.

RESULTS

MutaCYP achieves MCC = 0.70, Q2 = 88.52%, Recall = 93.40% with Precision = 91.09%, and AUC = 0.909. Comparative evaluation with other existing methods indicates that MutaCYP outperforms SIFT and PolyPhen-2. Predictions by MutaCYP appear to be orthogonal to predictions by the evaluated methods. Potential issues on reliability of annotations of mutations in the existing databases are discussed.

CONCLUSIONS

A new accurate method, MutaCYP, for classification of missense mutations in human CYPs is presented. The prediction model consists of only five sequence-based features, including a real-valued predicted relative solvent accessibility. The method is publicly available at http://research.cchmc.org/MutaSense/.

Novel mutations in BMPR2, ACVRL1 and KCNA5 genes and hemodynamic parameters in patients with pulmonary arterial hypertension

Background

Pulmonary arterial hypertension (PAH) is a rare and progressive vascular disorder characterized by increased pulmonary vascular resistance and right heart failure. The aim of this study was to analyze the Bone Morphogenetic Protein Receptor 2 (BMPR2), Activin A type II receptor like kinase 1 (ALK1/ACVRL1) and potassium voltage-gated channel, shakerrelated subfamily, member 5 (KCNA5) genes in patients with idiopathic and associated PAH. Correlation among pathogenic mutations and clinical and functional parameters was further analyzed.

Methods and Results

Forty one patients and fifty controls were included in this study. Analysis of BMPR2, ACVRL1 and KCNA5 genes was performed by polymerase chain reaction (PCR) and direct sequencing. Fifty one nucleotide changes were detected in these genes in 40 of the 41 patients; only 22 of these changes, which were classified as pathogenic, have been detected in 21 patients (51.2%). Ten patients (62.5%) with idiopathic PAH and 10 (40%) with associated PAH showed pathogenic mutations in some of the three genes. Several clinical and hemodynamics parameters showed significant differences between carriers and non-carriers of mutations, being more severe in carriers: mean pulmonary artery pressure (p = 0.043), pulmonary vascular resistence (p = 0.043), cardiac index (p = 0.04) and 6 minute walking test (p = 0.02). This differences remained unchanged after adjusting for PAH type (idiopathic vs non idiopathic).

Conclusions

Pathogenic mutations in BMPR2 gene are frequent in patients with idiopathic and associated PAH group I. Mutations in ACVRL1 and KCNA5 are less frequent. The presence of these mutations seems to increase the severity of the disease.

Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics

DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules.

Functional implications of the p.Cys680Arg mutation in the MLH1 mismatch repair protein

In clinical genetic diagnostics, it is difficult to predict whether genetic mutations that do not greatly alter the primary sequence of the encoded protein causing unknown functional effects on cognate proteins lead to development of disease. Here, we report the clinical identification of c.2038 T>C missense mutation in exon 18 of the human MLH1 gene and biochemically characterization of the p.Cys680Arg mutant MLH1 protein to implicate it in the pathogenicity of the Lynch syndrome (LS). We show that the mutation is deficient in DNA mismatch repair and, therefore, contributing to LS in the carriers.