Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler

BMC Infectious Diseases

Selby Knudsen¹  Natasha S. Hochberg¹  Chelsie Cintron¹  C. Robert Horsburgh²  Padmini Salgame³  Jerrold Ellner³  Aubrey Odom⁴  David F. Jenkins⁴  W. Evan Johnson⁴  Ethel Nankya⁴  Yue Zhao⁴  Mutharaj Muthaiah⁵  Sonali Sarkar⁶  Senbagavalli Babu⁶  Noyal Joseph⁶  Subitha Lakshminarayanan⁶  Gautam Roy⁶ 

[1] Boston Medical Center;Department of Epidemiology, Boston University School of Public Health;Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School;Division of Computational Biomedicine, Boston University School of Medicine;Government Hospital for Chest Diseases;Jawaharlal Institute of Postgraduate Medical Education and Research;

关键词: Tuberculosis;    RNA-sequencing;    Gene sets;    Signatures;    Biomarkers;    Latent tuberculosis infection;   

DOI  :  10.1186/s12879-020-05598-z

来源: DOAJ

【 摘 要 】

Abstract Background Gene expression signatures have been used as biomarkers of tuberculosis (TB) risk and outcomes. Platforms are needed to simplify access to these signatures and determine their validity in the setting of comorbidities. We developed a computational profiling platform of TB signature gene sets and characterized the diagnostic ability of existing signature gene sets to differentiate active TB from LTBI in the setting of malnutrition. Methods We curated 45 existing TB-related signature gene sets and developed our TBSignatureProfiler software toolkit that estimates gene set activity using multiple enrichment methods and allows visualization of single- and multi-pathway results. The TBSignatureProfiler software is available through Bioconductor and on GitHub. For evaluation in malnutrition, we used whole blood gene expression profiling from 23 severely malnourished Indian individuals with TB and 15 severely malnourished household contacts with latent TB infection (LTBI). Severe malnutrition was defined as body mass index (BMI) < 16 kg/m2 in adults and based on weight-for-height Z scores in children < 18 years. Gene expression was measured using RNA-sequencing. Results The comparison and visualization functions from the TBSignatureProfiler showed that TB gene sets performed well in malnourished individuals; 40 gene sets had statistically significant discriminative power for differentiating TB from LTBI, with area under the curve ranging from 0.662–0.989. Three gene sets were not significantly predictive. Conclusion Our TBSignatureProfiler is a highly effective and user-friendly platform for applying and comparing published TB signature gene sets. Using this platform, we found that existing gene sets for TB function effectively in the setting of malnutrition, although differences in gene set applicability exist. RNA-sequencing gene sets should consider comorbidities and potential effects on diagnostic performance.

【 授权许可】

Unknown