scholarly journals Predicting functional consequences of mutations using molecular interaction network features

2021 ◽  
Author(s):  
Kivilcim Ozturk ◽  
Hannah Carter

AbstractVariant interpretation remains a central challenge for precision medicine. Missense variants are particularly difficult to understand as they change only a single amino acid in a protein sequence yet can have large and varied effects on protein activity. Numerous tools have been developed to identify missense variants with putative disease consequences from protein sequence and structure. However, biological function arises through higher order interactions among proteins and molecules within cells. We therefore sought to capture information about the potential of missense mutations to perturb protein interaction networks by integrating protein structure and interaction data. We developed 16 network-based annotations for missense mutations that provide orthogonal information to features classically used to prioritize variants. We then evaluated them in the context of a proven machine-learning framework for variant effect prediction across multiple benchmark datasets to demonstrate their potential to improve variant classification. Interestingly, network features resulted in larger performance gains for classifying somatic mutations than for germline variants, possibly due to different constraints on what mutations are tolerated at the cellular versus organismal level. Our results suggest that modeling variant potential to perturb context-specific interactome networks is a fruitful strategy to advance in silico variant effect prediction.

2021 ◽  
Author(s):  
Kivilcim Ozturk ◽  
Hannah Carter

AbstractVariant interpretation remains a central challenge for precision medicine. Missense variants are particularly difficult to understand as they change only a single amino acid in protein sequence yet can have large and varied effects on protein activity. Numerous tools have been developed to identify missense variants with putative disease consequences from protein sequence and structure. However, biological function arises through higher order interactions among proteins and molecules within cells. We therefore sought to capture information about the potential of missense mutations to perturb protein interaction networks by integrating protein structure and interaction data. We developed 16 network-based annotations for missense mutations that provide orthogonal information to features classically used to prioritize variants. We then evaluated them in the context of a proven machine-learning framework for variant effect prediction across multiple benchmark datasets to demonstrate their potential to improve variant classification. Interestingly, network features resulted in larger performance gains for classifying somatic mutations than for germline variants, possibly due to different constraints on what mutations are tolerated at the cellular versus organismal level. Our results suggest that modeling variant potential to perturb context-specific interactome networks is a fruitful strategy to advance in silico variant effect prediction.


Science ◽  
2019 ◽  
Vol 365 (6453) ◽  
pp. 599-604 ◽  
Author(s):  
Steffen Boettcher ◽  
Peter G. Miller ◽  
Rohan Sharma ◽  
Marie McConkey ◽  
Matthew Leventhal ◽  
...  

TP53, which encodes the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, are enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We used CRISPR-Cas9 to generate isogenic human leukemia cell lines of the most common TP53 missense mutations. Functional, DNA-binding, and transcriptional analyses revealed loss of function but no GOF effects. Comprehensive mutational scanning of p53 single–amino acid variants demonstrated that missense variants in the DNA-binding domain exert a dominant-negative effect (DNE). In mice, the DNE of p53 missense variants confers a selective advantage to hematopoietic cells on DNA damage. Analysis of clinical outcomes in patients with acute myeloid leukemia showed no evidence of GOF for TP53 missense mutations. Thus, a DNE is the primary unit of selection for TP53 missense mutations in myeloid malignancies.


2021 ◽  
Author(s):  
Alistair Dunham ◽  
Gwendolyn M Jang ◽  
Monita Muralidharan ◽  
Danielle Swaney ◽  
Pedro Beltrao

AbstractThe COVID19 pandemic is a global crisis severely impacting many people across the world. An important part of the response is monitoring viral variants and determining the impact they have on viral properties, such as infectivity, disease severity and interactions with drugs and vaccines. In this work we generate and make available computational variant effect predictions for all possible single amino-acid substitutions to SARS-CoV-2 in order to complement and facilitate experiments and expert analysis. The resulting dataset contains predictions from evolutionary conservation and protein and complex structural models, combined with viral phosphosites, experimental results and variant frequencies. We demonstrate predictions’ effectiveness by comparing them with expectations from variant frequency and prior experiments. We then identify higher frequency variants with significant predicted effects as well as finding variants measured to impact antibody binding that are least likely to impact other viral functions. A web portal is available at sars.mutfunc.com, where the dataset can be searched and downloaded.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1039.1-1039
Author(s):  
A. Barinotti ◽  
M. Radin ◽  
I. Cecchi ◽  
S. G. Foddai ◽  
E. Rubini ◽  
...  

Background:Antiphospholipid Syndrome (APS) is an autoimmune disease whose precise aetiology is still unknown, but the high heterogeneity of its manifestations and clinical course is presumably due to the occurrence of different mechanisms and alterations at different levels and pathways [1]. The first genetic studies in APS focused primarily on the human leukocytes antigen system region, but more recent data highlighted a role of other genes in APS susceptibility, primarily those involved in the immune response and in the haemostatic process.Objectives:We aimed to deepen the investigation of APS genetic background starting from a case of familial APS, analysing two siblings with thrombotic APS (Table 1), both triple positive for antiphospholipid antibodies (aPL).Table 1.Main clinical and laboratory characteristics of the patients included in the study.PatientAgeaPL ProfileRelevant Clinical History1 (F)51Triple positive (LA, aCL IgG, aβ2GPI IgG)Two episodes of ischemic stroke, one episode of CAPS (renal thrombotic microangiopathy, visual impairment, ischemic stroke)2 (M)47Triple positive (LA, aCL IgG, aβ2GPI IgG)Three episodes of deep vein thrombosis, regardless ongoing well conducted therapy vitamin k antagonist and additional retinal vein thrombosisLA: lupus anticoagulant; aCL: anti-cardiolipin antibodies; aβ2GPI: anti- β2 glycoprotein I antibodies; CAPS: catastrophic APS.Methods:Genomic DNA was extracted from peripheral blood and the samples underwent Whole Exome Sequencing (WES). Sequencing was done on a 100X coverage, and reads have been aligned to the human reference genome (GRCh37/hg19 assembly) using the Burrows–Wheeler Alignment tool (BWA). The mean sequencing depth on target regions was 170X for patient 1, 205X for patient 2, moreover, 99.50% of the targeted bases had at least 10X coverage for all the three donors. The resulting single nucleotide polymorphisms (SNPs) have been analysed through a step-by-step process based on their frequency population (using Genome Aggregation Database), their predicted effects on the protein (using VarSome) and a literature research about the genes carrying them. Moreover, genes previously associated with a pro-thrombotic tendency and with APS have been analysed in the two patients.Results:Starting from more than 120000 SNPs for each patients, the analysis led to reduce the list of SNPs of interest to 27 missense mutations. The complete literature research regarding the genes carrying these mutations allowed to further reduce the number of selected genes, focusing on those that exert a role potentially involved in APS pathogenesis and development. In particular, these genes (PLA2G6, HSPG2, BCL3, ZFAT, ATP2B2, CRTC3 and ADCY3) take part in the immune response and the vascular homeostasis. The list of the DNA missense variants of interest found in our cases of familial APS is resumed in Figure 2.Figure 2.List of DNA missense variants of interest found in patient 1 and 2. Genes potentially involved in APS pathogenesis and development are highlighted in bold.No mutations on genes known to be associated with a pro-thrombotic state (F5, F2, MTHFR, F13A1, PROC, PROS1, FGB and SERPINE1), or on genes previously associated with APS (B2GPI, PF4V1, SELP, TLR2, TLR4, GP Ia, GP1BA, F2R, F2RL1, TFPI, F3, VEGFA, FLT1, and TNF) have been found in the WES analysis.Conclusion:To some extent, this can be seen as a proof of concept of the complexity of APS. Efforts to interpret the genetic risk factors involved in the heterogeneous clinical features of the syndrome, for instance, the integration of WES and network-based approaches might help to identify and stratify patients at risk of developing APS.References:[1]Iuliano A, Galeazzi M, Sebastiani GD. Antiphospholipid syndrome’s genetic and epigenetic aspects. Autoimmun Rev. 2019;18(9).Disclosure of Interests:None declared


2021 ◽  
Author(s):  
Asieh Amousoltani Arani ◽  
Mohammadreza Sehhati ◽  
Mohammad Amin Tabatabaiefar

A new feature space, which can discriminate deleterious variants, was constructed by the integration of various input data using the proposed supervised nonnegative matrix tri-factorization (sNMTF) algorithm.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Philipp Rentzsch ◽  
Max Schubach ◽  
Jay Shendure ◽  
Martin Kircher

Abstract Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond those occurring at donor and acceptor dinucleotides. To address this, various methods aim to predict variant effects on splicing. Recently, deep neural networks (DNNs) have been shown to achieve better results in predicting splice variants than other strategies. Methods It has been unclear how best to integrate such process-specific scores into genome-wide variant effect predictors. Here, we use a recently published experimental data set to compare several machine learning methods that score variant effects on splicing. We integrate the best of those approaches into general variant effect prediction models and observe the effect on classification of known pathogenic variants. Results We integrate two specialized splicing scores into CADD (Combined Annotation Dependent Depletion; cadd.gs.washington.edu), a widely used tool for genome-wide variant effect prediction that we previously developed to weight and integrate diverse collections of genomic annotations. With this new model, CADD-Splice, we show that inclusion of splicing DNN effect scores substantially improves predictions across multiple variant categories, without compromising overall performance. Conclusions While splice effect scores show superior performance on splice variants, specialized predictors cannot compete with other variant scores in general variant interpretation, as the latter account for nonsense and missense effects that do not alter splicing. Although only shown here for splice scores, we believe that the applied approach will generalize to other specific molecular processes, providing a path for the further improvement of genome-wide variant effect prediction.


Author(s):  
Minxian Wang ◽  
Vivian S. Lee-Kim ◽  
Deepak S. Atri ◽  
Nadine H. Elowe ◽  
John Yu ◽  
...  

Background: Corin is a protease expressed in cardiomyocytes that plays a key role in salt handling and intravascular volume homeostasis via activation of natriuretic peptides. It is unknown if Corin loss-of-function (LOF) is causally associated with risk of coronary artery disease (CAD). Methods: We analyzed all coding CORIN variants in an Italian case-control study of CAD. We functionally tested all 64 rare missense mutations in Western Blot and Mass Spectroscopy assays for proatrial natriuretic peptide cleavage. An expanded rare variant association analysis for Corin LOF mutations was conducted in whole exome sequencing data from 37 799 CAD cases and 212 184 controls. Results: We observed LOF variants in CORIN in 8 of 1803 (0.4%) CAD cases versus 0 of 1725 controls ( P , 0.007). Of 64 rare missense variants profiled, 21 (33%) demonstrated <30% of wild-type activity and were deemed damaging in the 2 functional assays for Corin activity. In a rare variant association study that aggregated rare LOF and functionally validated damaging missense variants from the Italian study, we observed no association with CAD—21 of 1803 CAD cases versus 12 of 1725 controls with adjusted odds ratio of 1.61 ([95% CI, 0.79–3.29]; P =0.17). In the expanded sequencing dataset, there was no relationship between rare LOF variants with CAD was also observed (odds ratio, 1.15 [95% CI, 0.89–1.49]; P =0.30). Consistent with the genetic analysis, we observed no relationship between circulating Corin concentrations with incident CAD events among 4744 participants of a prospective cohort study—sex-stratified hazard ratio per SD increment of 0.96 ([95% CI, 0.87–1.07], P =0.48). Conclusions: Functional testing of missense mutations improved the accuracy of rare variant association analysis. Despite compelling pathophysiology and a preliminary observation suggesting association, we observed no relationship between rare damaging variants in CORIN or circulating Corin concentrations with risk of CAD.


2020 ◽  
Vol 7 (6) ◽  
pp. 3835-3842
Author(s):  
Sandya Menon Prabhakaran Menon ◽  
Asita Elengoe

Introduction: cancer is one of the top three most commonly occurring cancer worldwide with more than 1.8 million cases in 2018. In Malaysia, cancer is the most common cancer in males and the second most common cancer in females. Albeit being the second most common form of cancer in Malaysia, there is a lack of informal or structured national cancer screening program in Malaysia and it remains a low priority in healthcare planning and expenditure. The risk of developing colon cancer is greatly influenced by factors such as lifestyle habits, genetic inheritance, diet, weight, and exercise. KRAS, the most frequently mutated oncogene in cancer, occurs in about 50 percent of cancers. This study maps the KRAS gene involved in colon cancer pathway using applications such as STRING version 11.0 and version 3.7.0 to provide a clear visualization of all the related and involved proteins and genes that interact with KRAS gene in the pathway. Methods: Using KRAS as a seed, a protein-protein interaction network was constructed with 3391 interactions which were retrieved from the STRING version 11.0 database. The protein network interaction was further grouped into 6 clusters using the MCODE application. Molecular function and biological processes of the genes involved in the KRAS protein network were determined using Biological Networks Gene Ontology (BiNGO). Results: According to the resulting protein-protein network interaction map, it revealed that KRAS mechanism and co-expressed genes interconnected with protein or enzyme binding, receptor signaling protein activity and vascular endothelial growth factor (VEGF) receptor 2 binding. Conclusion: Understanding these protein-protein interactions provide insight into cellular activities and thus aid in the understanding of the cause of disease.  


Development ◽  
1998 ◽  
Vol 125 (18) ◽  
pp. 3599-3606 ◽  
Author(s):  
D. Levitan ◽  
I. Greenwald

Presenilins have been implicated in the development of Alzheimer's disease and in facilitating LIN-12/Notch activity. Here, we use genetic methods to explore the relationship between C. elegans LIN-12 and SEL-12 presenilin. Reducing sel-12 activity can suppress the effects of elevated lin-12 activity when LIN-12 is activated by missense mutations but not when LIN-12 is activated by removal of the extracellular and transmembrane domains. These results suggest that SEL-12 does not function downstream of activated LIN-12. An active SEL-12::GFP hybrid protein accumulates in the perinuclear region of the vulval precursor cells (VPCs) of living hermaphrodites, consistent with a localization in endoplasmic reticulum/Golgi membranes; when sel-12 activity is reduced, less LIN-12 protein accumulates in the plasma membranes of the VPCs. Together with the genetic interactions between lin-12 and sel-12, these observations suggest a role for SEL-12 in LIN-12 processing or trafficking. However, SEL-12 does not appear to be a general factor that influences membrane protein activity, since reducing sel-12 activity does not suppress or enhance hypomorphic mutations in other genes encoding membrane proteins. We discuss potential parallels for the role of SEL-12/presenilin in facilitating LIN-12/Notch activity and in amyloid precursor protein (APP) processing.


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