scholarly journals CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

2019 ◽  
Author(s):  
Shuang Li ◽  
K. Joeri van der Velde ◽  
Dick de Ridder ◽  
Aalt D.J. van Dijk ◽  
Dimitrios Soudis ◽  
...  
Keyword(s):  
Web Application ◽  
Rare Variants ◽  
Computational Prediction ◽  
Computational Method ◽  
Prediction Methods ◽  
Pathogenic Variants ◽  
Manual Classification ◽  
Short Indels ◽  
Limited Accuracy ◽  
New Machine

ABSTRACTExome sequencing is now mainstream in clinical practice, however, identification of pathogenic Mendelian variants remains time consuming, partly because limited accuracy of current computational prediction methods leaves much manual classification. Here we introduce CAPICE, a new machine-learning based method for prioritizing pathogenic variants, including SNVs and short InDels, that outperforms best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily integrated into diagnostic pipelines and is available as free and open source command-line software, file of pre-computed scores, and as a web application with web service API.

scholarly journals Prediction of post-translational modification sites using multiple kernel support vector machine

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3261 ◽  
Author(s):  
BingHua Wang ◽  
Minghui Wang ◽  
Ao Li
Keyword(s):  
Protein Function ◽  
Predictive Performance ◽  
Computational Prediction ◽  
Computational Method ◽  
Support Vector ◽  
Prediction Methods ◽  
Sequence Information ◽  
Post Translational Modification ◽  
Multiple Kernel ◽  
Local Sequence

Protein post-translational modification (PTM) is an important mechanism that is involved in the regulation of protein function. Considering the high-cost and labor-intensive of experimental identification, many computational prediction methods are currently available for the prediction of PTM sites by using protein local sequence information in the context of conserved motif. Here we proposed a novel computational method by using the combination of multiple kernel support vector machines (SVM) for predicting PTM sites including phosphorylation, O-linked glycosylation, acetylation, sulfation and nitration. To largely make use of local sequence information and site-modification relationships, we developed a local sequence kernel and Gaussian interaction profile kernel, respectively. Multiple kernels were further combined to train SVM for efficiently leveraging kernel information to boost predictive performance. We compared the proposed method with existing PTM prediction methods. The experimental results revealed that the proposed method performed comparable or better performance than the existing prediction methods, suggesting the feasibility of the developed kernels and the usefulness of the proposed method in PTM sites prediction.

scholarly journals Diagnostic exome-based preconception carrier testing in consanguineous couples: results from the first 100 couples in clinical practice

2021 ◽  
Author(s):  
Suzanne C. E. H. Sallevelt ◽  
Alexander P. A. Stegmann ◽  
Bart de Koning ◽  
Crool Velter ◽  
Anja Steyls ◽  
...  
Keyword(s):  
Autosomal Recessive ◽  
Rare Variants ◽  
Clinical Care ◽  
Carrier Testing ◽  
Carrier Status ◽  
Routine Diagnostics ◽  
Affected Offspring ◽  
Pathogenic Variants ◽  
Increased Risk ◽  
Genetics And Genomics

Abstract Purpose Consanguineous couples are at increased risk of being heterozygous for the same autosomal recessive (AR) disorder(s), with a 25% risk of affected offspring as a consequence. Until recently, comprehensive preconception carrier testing (PCT) for AR disorders was unavailable in routine diagnostics. Here we developed and implemented such a test in routine clinical care. Methods We performed exome sequencing (ES) for 100 consanguineous couples. For each couple, rare variants that could give rise to biallelic variants in offspring were selected. These variants were subsequently filtered against a gene panel consisting of ~2,000 genes associated with known AR disorders (OMIM-based). Remaining variants were classified according to American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines, after which only likely pathogenic and pathogenic (class IV/V) variants, present in both partners, were reported. Results In 28 of 100 tested consanguineous couples (28%), likely pathogenic and pathogenic variants not previously known in the couple or their family were reported conferring 25% risk of affected offspring. Conclusion ES-based PCT provides a powerful diagnostic tool to identify AR disease carrier status in consanguineous couples. Outcomes provided significant reproductive choices for a higher proportion of these couples than previous tests.

scholarly journals PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features

2021 ◽  
Vol 22 (5) ◽  
pp. 2704
Author(s):  
Andi Nur Nilamyani ◽  
Firda Nurul Auliah ◽  
Mohammad Ali Moni ◽  
Watshara Shoombuatong ◽  
Md Mehedi Hasan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Web Application ◽  
Computational Prediction ◽  
Vital Role ◽  
Machine Learning Algorithms ◽  
Recursive Feature Elimination ◽  
Post Translational Modification ◽  
Multiple Sequence ◽  
Sequence Features

Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyrosine is a prerequisite to understanding the molecular function of nitrated proteins. Thanks to the progress of machine learning, computational prediction can play a vital role before the biological experimentation. Herein, we developed a computational predictor PredNTS by integrating multiple sequence features including K-mer, composition of k-spaced amino acid pairs (CKSAAP), AAindex, and binary encoding schemes. The important features were selected by the recursive feature elimination approach using a random forest classifier. Finally, we linearly combined the successive random forest (RF) probability scores generated by the different, single encoding-employing RF models. The resultant PredNTS predictor achieved an area under a curve (AUC) of 0.910 using five-fold cross validation. It outperformed the existing predictors on a comprehensive and independent dataset. Furthermore, we investigated several machine learning algorithms to demonstrate the superiority of the employed RF algorithm. The PredNTS is a useful computational resource for the prediction of nitrotyrosine sites. The web-application with the curated datasets of the PredNTS is publicly available.

scholarly journals BIOM-10. PREVALENCE OF NF1 MISSENSE MUTATIONS AND CANDIDATE MODIFIER GENES IN SPINAL NEUROFIBROMATOSIS PATIENTS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii3-ii3
Author(s):  
Paola Riva ◽  
Donata Bianchessi ◽  
Eleonora Mangano ◽  
Claudia Cesaretti ◽  
Paola Bettinaglio ◽  
...  
Keyword(s):  
Rare Variants ◽  
Sporadic Case ◽  
Modifier Genes ◽  
Lower Percentage ◽  
Missense Mutations ◽  
Cutaneous Manifestations ◽  
Classical Form ◽  
Ras Pathway ◽  
Pathogenic Variants ◽  
Patients At Risk

Abstract INTRODUCTION Spinal Neurofibromatosis (SNF), a distinct clinical entity of NF1, characterized by bilateral neurofibromas involving all spinal roots and a few, if any, cutaneous manifestations, entails greater morbidity than the classical form of disease. Nevertheless, there are no reliable patterns to sort out patients at risk for developing SNF. MATERIALS AND METHODS We investigated 19 NF1 families with at least one SNF member, 37 sporadic SNF patient and 100 NF1 patients with classical form of disease. We applied Targeted NGS using a panel consisting of 139 genes encoding RAS pathway effectors, neurofibromin interactors and genes mapping at 17q11.2 region. RESULTS In SNF patients we found a higher percentage of missense (21% versus 8%, p=0 0.016, OR 3.13 (95% CI 01.1 -8.2) and a lower percentage of nonsense NF1 mutations (12.5% versus 28%,, p= 0.026, OR 0.36 (95% CI 0.14–0.9) than in classical NF1 cases. Furthermore, we evaluated rare variants with damaging potential predictors in genes of the RAS pathway and in neurofibromin interactors. In more than one sporadic case possible pathogenic variants were found in LIMK2 (neurofibromin interactor), RASAL1, RASAL3, SOS1, A2ML1, MAP3K1 (RAS pathway effectors), while in more than one SNF family were detected RASAL1, RASAL3, MAP3K1 genes variations. CONCLUSIONS Our results confirm the correlation between NF1 genotype and SNF phenotype as previously reported (Ruggieri, 2015), suggesting that neurofibromin gain-of-functions mutations are associated to SNF. In some patients, the co-occurrence of potential pathogenic variants in NF1 related genes with severe phenotypes was detected supporting their role as modifier genes and promising therapeutic targets.

scholarly journals Opportunities and Challenges for Interpreting Rare Variation in Clinically Important Genes

2020 ◽  
Author(s):  
Gregory McInnes ◽  
Andrew G. Sharo ◽  
Megan L. Koleske ◽  
Julie E. H. Brown ◽  
Matthew Norstad ◽  
...  
Keyword(s):  
Healthcare System ◽  
Protein Function ◽  
Rare Variants ◽  
Clinical Importance ◽  
Computational Prediction ◽  
Ethical Challenges ◽  
Inborn Errors ◽  
Rare Variation ◽  
Learning Healthcare System ◽  
The Impact

Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, leaving a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequent frequent variants and associated mechanisms. Variants of unknown significance (VUS) in these genes are discovered at a rate that outpaces current ability to classify them using databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns, and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

Phenotype Analysis and Genetic Study of Chinese Patients With Treacher Collins Syndrome

2021 ◽  
pp. 105566562110375
Author(s):  
Meng Lu ◽  
Bin Yang ◽  
Zixiang Chen ◽  
Haiyue Jiang ◽  
Bo Pan
Keyword(s):  
Rare Variants ◽  
Clinical Care ◽  
Treacher Collins Syndrome ◽  
Chinese Patients ◽  
Pathogenic Variants ◽  
Premature Termination Codons ◽  
Whole Exome ◽  
Exome Aggregation Consortium ◽  
Phenotype Analysis ◽  
Sporadic Cases

Objective The aim of this study was to confirm the pathogenic variants, explore the genotype–phenotype correlation and characteristics of Chinese patients with Treacher Collins syndrome (TCS). Design Clinical details of 3 TCS family cases and 2 sporadic cases were collected and analyzed. Whole-exome sequencing and Sanger sequencing were conducted to detect causative variants. Setting Tertiary clinical care. Patients This study included 8 patients clinically diagnosed with TCS who were from 3 familial cases and 2 sporadic cases. Main Outcome Measures When filtering the database, variants were saved as rare variants if their frequency were less than 0.005 in the 1000 Genomes Project Database, the Exome Aggregation Consortium (ExAC) browser, and the Novogene database, or they would be removed as common ones. The pathogenic variants identified were verified by polymerase chain reaction. The sequencing results were analyzed by Chromas 2.1 software. Results Two novel pathogenic variants (NM_000356.3: c.537del and NM_000356.3: c.1965_1966dupGG) and 2 known pathogenic variants (NM_000356.3: c.1535del, NM_000356.3: c.4131_4135del) were identified within TCOF1 which are predicted to lead to premature termination codons resulting in a truncated protein. There was a known missense SNP (NM_015972.3: c.139G>A) within POLR1D. No phenotype–genotype correlation was observed. Instead, these 8 patients demonstrated the high genotypic and phenotypic heterogeneity of TCS. Conclusions This study expands on the pathogenic gene pool of Chinese patients with TCS. Besides the great variation among patients which is similar to international reports, Chinese patients have their own characteristics in clinical phenotype and pathogenesis mutations.

Whole‐Exome Sequencing of a Saudi Epilepsy Cohort Reveals Association Signals in Known and Potentially Novel Loci

2021 ◽  
Author(s):  
Amein Kadhem AlAli ◽  
Abdulrahman Al-Enazi ◽  
Ahmed Ammar ◽  
Mahmoud Hajj ◽  
Cyril Cyrus ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Rare Variants ◽  
High Rate ◽  
Variants Of Unknown Significance ◽  
Pathogenic Variants ◽  
Whole Exome ◽  
Novel Variants ◽  
Unknown Significance ◽  
Rare Genetic Variants

Abstract Background Epilepsy, a serious chronic neurological condition effecting up to 100 million people globally, has clear genetic underpinnings including common and rare variants. In Saudi Arabia the prevalence of epilepsy is high and caused mainly by perinatal and genetic factors. No whole-exome sequencing (WES) studies have been performed to date in Saudi Arabian Epilepsy cohorts. This offers a unique opportunity for the discovery of rare genetic variants impacting this disease as there is a high rate of consanguinity amongst large tribal pedigrees. Results We performed WES on 144 individuals diagnosed with epilepsy, to interrogate known Epilepsy related genes for known and functional novel variants. We also used an American College of Medical Genetics (ACMG) guideline based variant prioritization approach in an attempt to discover putative causative variants. We identified a 32 potentially causative pathogenic variants across 30 different genes in 44/144 (30%) of these Saudi Epilepsy individuals. We also identified 232 variants of unknown significance (VUS) across 101 different genes in 133/144 (92%) subjects. Strong enrichment of variants of likely pathogenicity were observed in previously described epilepsy-associated loci, and a number of putative pathogenic variants in novel loci are also observed. Conclusion Several putative pathogenic variants known to be epilepsy-related loci were identified for the first time in our population, in addition to several potential new loci have been identified which may be prioritized for further investigation.

scholarly journals Diagnostic exome sequencing in non-acquired focal epilepsies highlights a major role of GATOR1 complex genes

2020 ◽  
Vol 57 (9) ◽  
pp. 624-633 ◽  
Author(s):  
Martin Krenn ◽  
Matias Wagner ◽  
Christoph Hotzy ◽  
Elisabeth Graf ◽  
Sandrina Weber ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Rare Variants ◽  
Focal Epilepsy ◽  
Diagnostic Yield ◽  
Mammalian Target Of Rapamycin ◽  
High Rate ◽  
Molecular Heterogeneity ◽  
Pathogenic Variants ◽  
Uncertain Significance

BackgroundThe genetic architecture of non-acquired focal epilepsies (NAFEs) becomes increasingly unravelled using genome-wide sequencing datasets. However, it remains to be determined how this emerging knowledge can be translated into a diagnostic setting. To bridge this gap, we assessed the diagnostic outcomes of exome sequencing (ES) in NAFE.Methods112 deeply phenotyped patients with NAFE were included in the study. Diagnostic ES was performed, followed by a screen to detect variants of uncertain significance (VUSs) in 15 well-established focal epilepsy genes. Explorative gene prioritisation was used to identify possible novel candidate aetiologies with so far limited evidence for NAFE.ResultsES identified pathogenic or likely pathogenic (ie, diagnostic) variants in 13/112 patients (12%) in the genes DEPDC5, NPRL3, GABRG2, SCN1A, PCDH19 and STX1B. Two pathogenic variants were microdeletions involving NPRL3 and PCDH19. Nine of the 13 diagnostic variants (69%) were found in genes of the GATOR1 complex, a potentially druggable target involved in the mammalian target of rapamycin (mTOR) signalling pathway. In addition, 17 VUSs in focal epilepsy genes and 6 rare variants in candidate genes (MTOR, KCNA2, RBFOX1 and SCN3A) were detected. Five patients with reported variants had double hits in different genes, suggesting a possible (oligogenic) role of multiple rare variants.ConclusionThis study underscores the molecular heterogeneity of NAFE with GATOR1 complex genes representing the by far most relevant genetic aetiology known to date. Although the diagnostic yield is lower compared with severe early-onset epilepsies, the high rate of VUSs and candidate variants suggests a further increase in future years.

scholarly journals Assessing Lysosomal Disorders in the NGS Era: Identification of Novel Rare Variants

2020 ◽  
Vol 21 (17) ◽  
pp. 6355
Author(s):  
Marisa Encarnação ◽  
Maria Francisca Coutinho ◽  
Lisbeth Silva ◽  
Diogo Ribeiro ◽  
Souad Ouesleti ◽  
...  
Keyword(s):  
Rare Variants ◽  
Health Care Systems ◽  
Genetic Disorders ◽  
Case Series ◽  
In Silico Analysis ◽  
Analysis Data ◽  
Lysosomal Storage ◽  
Pathogenic Variants ◽  
Number Of Patients

Lysosomal storage diseases (LSDs) are a heterogeneous group of genetic disorders with variable degrees of severity and a broad phenotypic spectrum, which may overlap with a number of other conditions. While individually rare, as a group LSDs affect a significant number of patients, placing an important burden on affected individuals and their families but also on national health care systems worldwide. Here, we present our results on the use of an in-house customized next-generation sequencing (NGS) panel of genes related to lysosome function as a first-line molecular test for the diagnosis of LSDs. Ultimately, our goal is to provide a fast and effective tool to screen for virtually all LSDs in a single run, thus contributing to decrease the diagnostic odyssey, accelerating the time to diagnosis. Our study enrolled a group of 23 patients with variable degrees of clinical and/or biochemical suspicion of LSD. Briefly, NGS analysis data workflow, followed by segregation analysis allowed the characterization of approximately 41% of the analyzed patients and the identification of 10 different pathogenic variants, underlying nine LSDs. Importantly, four of those variants were novel, and, when applicable, their effect over protein structure was evaluated through in silico analysis. One of the novel pathogenic variants was identified in the GM2A gene, which is associated with an ultra-rare (or misdiagnosed) LSD, the AB variant of GM2 Gangliosidosis. Overall, this case series highlights not only the major advantages of NGS-based diagnostic approaches but also, to some extent, its limitations ultimately promoting a reflection on the role of targeted panels as a primary tool for the prompt characterization of LSD patients.

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