Dataset Information

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

ABSTRACT: Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, and in which variations are associated with human hyperhomocysteinemia and homocystinuria. We have created a computational challenge under the CAGI framework to evaluate how well different methods can predict the phenotypic effect(s) of CBS single amino acid substitutions using a blinded experimental data set. CAGI participants were asked to predict yeast growth based on the identity of the mutations. The performance of the methods was evaluated using several metrics. The CBS challenge highlighted the difficulty of predicting the phenotype of an ex vivo system in a model organism when classification models were trained on human disease data. We also discuss the variations in difficulty of prediction for known benign and deleterious variants, as well as identify methodological and experimental constraints with lessons to be learned for future challenges.

SUBMITTER: Kasak L

PROVIDER: S-EPMC7325732 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

Kasak Laura L Bakolitsa Constantina C Hu Zhiqiang Z Yu Changhua C Rine Jasper J Dimster-Denk Dago F DF Pandey Gaurav G De Baets Greet G Bromberg Yana Y Cao Chen C Capriotti Emidio E Casadio Rita R Van Durme Joost J Giollo Manuel M Karchin Rachel R Katsonis Panagiotis P Leonardi Emanuela E Lichtarge Olivier O Martelli Pier Luigi PL Masica David D Mooney Sean D SD Olatubosun Ayodeji A Radivojac Predrag P Rousseau Frederic F Pal Lipika R LR Savojardo Castrense C Schymkowitz Joost J Thusberg Janita J Tosatto Silvio C E SCE Vihinen Mauno M Väliaho Jouni J Repo Susanna S Moult John J Brenner Steven E SE Friedberg Iddo I

Human mutation 20190903 9

Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, an ...[more]

PMID: 31301157

Similar Datasets

Project description:Hydrogen sulfide (H2S) has been proposed to exert pro- as well as anti-inflammatory effects in various models of critical illness. In this study, we compared bacterial lipopolysaccharide (LPS)‑induced changes in inflammatory mediator production, indices of multiple organ injury and survival in wild‑type (WT) mice and in mice with reduced expression of one of the three H2S‑producing enzymes, cystathionine-γ-lyase (CSE), cystathionine-β-synthase (CBS) or 3-mercaptopyruvate sulfurtransferase (3MST). Mice were injected intraperitoneally (i.p.) with LPS (10 mg/kg). After 6 h, the animals were sacrificed, blood and organs were collected and the following parameters were evaluated: blood urea nitrogen (BUN) levels in blood, myeloperoxidase (MPO) and malondialdehyde (MDA) in the lung, cytokine levels in plasma and the expression of the three H2S‑producing enzymes (CBS, CSE and 3MST) in the spleen, lung, liver and kidney. LPS induced a tissue‑dependent upregulation of some of the H2S‑producing enzymes in WT mice (upregulation of CBS in the spleen, upregulation of 3MST in the liver and upregulation of CBS, CSE and 3MST in the lung). Moreover, LPS impaired glomerular function, as evidenced by increased BUN levels. Renal impairment was comparable in the CSE‑/‑ and Δ3MST mice after LPS challenge; however, it was attenuated in the CBS+/‑ mice. MPO levels (an index of neutrophil infiltration) and MDA levels (an index of oxidative stress) in lung homogenates were significantly increased in response to LPS; these effects were similar in the WT, CBS+/‑, CSE‑/‑ and Δ3MST mice; however, the MDA levels tended to be lower in the CBS+/‑ and CSE‑/‑ mice. LPS induced significant increases in the plasma levels of multiple cytokines [tumor necrosis factor (TNF)α, interleukin (IL)‑1β, IL‑6, IL‑10, IL‑12 and interferon (IFN)γ] in plasma; TNFα, IL‑10 and IL‑12 levels tended to be lower in all three groups of animals expressing lower levels of H2S‑producing enzymes. The survival rates after the LPS challenge did not show any significant differences between the four animal groups tested. Thus, the findings of this study indicate that a deficiency in 3MST does not significantly affect endotoxemia, while a deficiency in CBS or CSE slightly ameliorates the outcome of LPS-induced endotoxemia in vivo.

Project description:BackgroundPharmacogenetic variation is important to drug responses through diverse and complex mechanisms. Predictions of the functional impact of missense pharmacogenetic variants primarily rely on the degree of sequence conservation between species as a primary discriminator. However, idiosyncratic or off-target drug-variant interactions sometimes involve effects that are peripheral or accessory to the central systems in which a gene functions. Given the importance of sequence conservation to functional prediction tools-these idiosyncratic pharmacogenetic variants may violate the assumptions of predictive software commonly used to infer their effect.MethodsHere we exhaustively assess the effectiveness of eleven missense mutation functional inference tools on all known pharmacogenetic missense variants contained in the Pharmacogenomics Knowledgebase (PharmGKB) repository. We categorize PharmGKB entries into sub-classes to catalog likely off-target interactions, such that we may compare predictions across different variant annotations.ResultsAs previously demonstrated, functional inference tools perform variably across the complete set of PharmGKB variants, with large numbers of variants incorrectly classified as 'benign'. However, we find substantial differences amongst PharmGKB variant sub-classes, particularly in variants known to cause off-target, type B adverse drug reactions, that are largely unrelated to the main pharmacological action of the drug. Specifically, variants associated with off-target effects (hence referred to as off-target variants) were most often incorrectly classified as 'benign'. These results highlight the importance of understanding the underlying mechanism of pharmacogenetic variants and how variants associated with off-target effects will ultimately require new predictive algorithms.ConclusionIn this work we demonstrate that functional inference tools perform poorly on pharmacogenetic variants, particularly on subsets enriched for variants causing off-target, type B adverse drug reactions. We describe how to identify variants associated with off-target effects within PharmGKB in order to generate a training set of variants that is needed to develop new algorithms specifically for this class of variant. Development of such tools will lead to more accurate functional predictions and pave the way for the increased wide-spread adoption of pharmacogenetics in clinical practice.

Dataset Information

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

Publications

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets