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Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler.
Johnson, W Evan; Odom, Aubrey; Cintron, Chelsie; Muthaiah, Mutharaj; Knudsen, Selby; Joseph, Noyal; Babu, Senbagavalli; Lakshminarayanan, Subitha; Jenkins, David F; Zhao, Yue; Nankya, Ethel; Horsburgh, C Robert; Roy, Gautam; Ellner, Jerrold; Sarkar, Sonali; Salgame, Padmini; Hochberg, Natasha S.
Afiliação
  • Johnson WE; Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.
  • Odom A; Bioinformatics Program, Boston University, Boston, MA, USA. wej@bu.edu.
  • Cintron C; Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA. wej@bu.edu.
  • Muthaiah M; Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
  • Knudsen S; Bioinformatics Program, Boston University, Boston, MA, USA.
  • Joseph N; Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA.
  • Babu S; Boston Medical Center, Boston, MA, USA.
  • Lakshminarayanan S; Government Hospital for Chest Diseases, Puducherry, India.
  • Jenkins DF; Boston Medical Center, Boston, MA, USA.
  • Zhao Y; Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
  • Nankya E; Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
  • Horsburgh CR; Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
  • Roy G; Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
  • Ellner J; Bioinformatics Program, Boston University, Boston, MA, USA.
  • Sarkar S; Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA.
  • Salgame P; Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
  • Hochberg NS; Bioinformatics Program, Boston University, Boston, MA, USA.
BMC Infect Dis ; 21(1): 106, 2021 Jan 22.
Article em En | MEDLINE | ID: mdl-33482742
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Software / Perfilação da Expressão Gênica / Desnutrição Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Child / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Infect Dis Assunto da revista: DOENCAS TRANSMISSIVEIS Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Software / Perfilação da Expressão Gênica / Desnutrição Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Child / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Infect Dis Assunto da revista: DOENCAS TRANSMISSIVEIS Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos