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Biology subjects

Gormley, I. C.

Publications and source records attributed to Gormley, I. C..

3 recordsLinked to original sources

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

Bovine tuberculosis (bTB) remains recalcitrant to eradication in many endemic countries where current diagnostics are suboptimal. Mycobacterium bovis causes bTB and is closely related to Mycobacterium tuberculosis, which causes human tuberculosis (hTB). Although blood-based mRNA biomarkers identified through machine learning can discriminate hTB-positive from hTB-negative individuals, similar approaches have not been explored for bTB. Here, we use RNA-seq and machine learning to investigate the utility of blood mRNA as a host-response biomarker for bTB. We identify a 30-gene signature and a 273-gene elastic net classifier that differentiate bTB-positive from bTB-negative cattle, achieving area under the curve (AUC) values of 0.986/0.900 for the former and 0.968/0.938 for the latter in training and testing, respectively. Additionally, we show that these classifiers distinguish bTB-positive cattle from cattle infected with other microbial pathogens (AUC [≥] 0.819). These mRNA-based classifiers represent a promising tool for augmenting current diagnostics to advance global bTB eradication efforts.

genomics↗

Genetic control of the transcriptional response to active tuberculosis disease and treatment

Understanding the functional impact of genomic sequence variants is critical for evaluating the role of genetic variation in the host response during tuberculosis (TB) disease and anti-TB treatment (ATT). Hitherto, there have been no genome-wide in vivo response expression quantitative trait loci (reQTL) studies conducted for active TB and ATT. Here, using longitudinal peripheral blood RNA-seq data from n = 48 patients with active TB who underwent ATT, we call sequence variants directly from these transcriptomes and impute them with a multi-ancestry reference panel. Associating our variants with the expression of nearby genes, we characterise thousands of cis-eQTL and hundreds of reQTL. We further show significant changes in cell type proportions during ATT through deconvolution of the bulk RNA-seq data and identify the putative cell type specific nature of cis-eQTL. Our work sheds light on the immunogenetics of TB disease and treatment, while providing a framework for studies using only RNA-seq data.

genetics↗

Integrative genomics sheds light on the immunobiology of tuberculosis in cattle

Mycobacterium bovis causes bovine tuberculosis (bTB), an infectious disease of cattle that poses a zoonotic threat to humans. Research has shown that bTB susceptibility is a heritable trait, and that the peripheral blood (PB) transcriptome is perturbed during bTB disease. Hitherto, no study has integrated PB transcriptomic, genomic and GWAS data to study bTB disease, and little is known about the genomic architecture underpinning the PB transcriptional response to M. bovis infection. Here, we perform transcriptome profiling of PB from 63 control and 60 confirmed M. bovis infected animals and detect 2,592 differently expressed genes that perturb multiple immune response pathways. Leveraging imputed genome-wide SNP data, we characterise thousands of cis- and trans-expression quantitative trait loci (eQTLs) and show that the PB transcriptome is substantially impacted by intrapopulation genomic variation. We integrate our gene expression data with summary statistics from multiple GWAS data sets for bTB susceptibility and perform the first transcriptome-wide association study (TWAS) in the context of tuberculosis disease. From this TWAS, we identify 136 functionally relevant genes (including RGS10, GBP4, TREML2, and RELT) and provide important new omics data for understanding the host response to mycobacterial infections that cause tuberculosis in mammals.

genomics↗