Minimum redundancy maximal relevance gene selection of apoptosis pathway genes in peripheral blood mononuclear cells of HIV-infected patients with antiretroviral therapy-associated mitochondrial toxicity

Eliezer Bose,Musie Ghebremichael,Elijah Paintsil

doi:10.1186/s12920-021-01136-1

Abstract

BackgroundWe previously identified differentially expressed genes on the basis of false discovery rate adjusted P value using empirical Bayes moderated tests. However, that approach yielded a subset of differentially expressed genes without accounting for redundancy between the selected genes.MethodsThis study is a secondary analysis of a case–control study of the effect of antiretroviral therapy on apoptosis pathway genes comprising of 16 cases (HIV infected with mitochondrial toxicity) and 16 controls (uninfected). We applied the maximum relevance minimum redundancy (mRMR) algorithm on the genes that were differentially expressed between the cases and controls. The mRMR algorithm iteratively selects features (genes) that are maximally relevant for class prediction and minimally redundant. We implemented several machine learning classifiers and tested the prediction accuracy of the two mRMR genes. We next used network analysis to estimate and visualize the association among the differentially expressed genes. We employed Markov Random Field or undirected network models to identify gene networks related to mitochondrial toxicity. The Spinglass model was used to identify clusters of gene communities.ResultsThe mRMR algorithm ranked DFFA and TNFRSF1A, two of the upregulated proapoptotic genes, on the top. The overall prediction accuracy was 86%, the two mRMR genes correctly classified 86% of the participants into their respective groups. The estimated network models showed different patterns of gene networks. In the network of the cases, FASLG was the most central gene. However, instead of FASLG, ABL1 and LTBR had the highest centrality in controls.ConclusionThe mRMR algorithm and network analysis revealed a new correlation of genes associated with mitochondrial toxicity.

Highlights

We previously identified differentially expressed genes on the basis of false discovery rate adjusted P value using empirical Bayes moderated tests
Nucleoside reverse transcriptase inhibitors (NRTIs), the first class to show anti-Human Immunodeficiency Virus (HIV) activity, are associated with toxicities such as skeletal muscle myopathy, lactic acidosis, lipodystrophy, peripheral neuropathies, cardiomyopathies, and pancytopenia [9,10,11,12]. These toxicities are due to NRTIinduced mitochondrial dysfunction through the inhibition of mitochondrial DNA polymerase gamma (Pol-γ) [13]
To assess the discriminatory power of DFFA and TNFRSF1A, we tested several classifier models to classify study participants based on these two selected genes into groups

Summary

Introduction

We previously identified differentially expressed genes on the basis of false discovery rate adjusted P value using empirical Bayes moderated tests. Nucleoside reverse transcriptase inhibitors (NRTIs), the first class to show anti-HIV activity, are associated with toxicities such as skeletal muscle myopathy, lactic acidosis, lipodystrophy, peripheral neuropathies, cardiomyopathies, and pancytopenia [9,10,11,12]. These toxicities are due to NRTIinduced mitochondrial dysfunction through the inhibition of mitochondrial DNA (mtDNA) polymerase gamma (Pol-γ) [13]. We recently reported that in a case–control study (HIV + with mitochondrial toxicity vs HIV uninfected controls), a total of 26 of 84 genes of the apoptosis pathway were differentially expressed [21]

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Conclusion