Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis

Elvis Ndukong Ndzi; Celine Nguefeu Nkenfou; Eric Walter Yone Pefura; Linda Chapdeleine Mouafo Mekue; Elise Guiedem; Carine Nkenfou Nguefeu; Marie Nicole Ngoufack; Elise Elong; Laeticia Grace Yatchou; Alexis Ndjolo; Jules-Roger Kuiate

doi:10.1016/j.heliyon.2019.e02559

Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis

Heliyon. 2019 Oct 18;5(10):e02559. doi: 10.1016/j.heliyon.2019.e02559. eCollection 2019 Oct.

Authors

Elvis Ndukong Ndzi^{1

2}, Celine Nguefeu Nkenfou^{1

3}, Eric Walter Yone Pefura^{4

5}, Linda Chapdeleine Mouafo Mekue^{1

2}, Elise Guiedem^{6

7}, Carine Nkenfou Nguefeu⁷, Marie Nicole Ngoufack^{1

7}, Elise Elong¹, Laeticia Grace Yatchou¹, Alexis Ndjolo^{1

5}, Jules-Roger Kuiate²

Affiliations

¹ Chantal Biya International Reference Centre for Research on HIV/AIDS Prevention and Management (CBIRC), Yaounde, Cameroon.
² University of Dschang, Faculty of Sciences, Departement of Biochemistry, Dschang, Cameroon.
³ University of Yaounde I, Higher Teachers' Training College, Department of Biology, Yaounde, Cameroon.
⁴ Pneumological Service, Yaoundé Jamot Hospital, Yaounde, Cameroon.
⁵ University of Yaounde I, Faculty of Medicine and Biomedical Sciences, Yaounde, Cameroon.
⁶ Center for the Study and Control of Communicable Diseases (CSCCD), Yaounde, Cameroon.
⁷ University of Yaounde I, Faculty of Sciences, Departement of Biochemistry, Yaounde, Cameroon.

Abstract

Diagnosis of tuberculosis still faces a lot of challenges and is one of the priorities in the field of tuberculosis management. Deciphering the complex tuberculosis pathogenicity network could provide biomarkers for diagnosis. We discussed the distribution of HLA-B17, -DQB and -DRB together with QuantiFERON test results in tuberculosis infection. A case control study was done during which a total of 337 subjects were enrolled comprising 227 active tuberculosis (ATB), 46 latent tuberculosis infection (LTBI) and 64 healthy controls (HC). Sequence-specific primer polymerase chain reaction and immune epitope database were used to genotype samples and determine the epitope binding ability of the over-represented alleles respectively. QuantiFERON test was done according to manufacturer's instructions. The peptides HLA-B*5801 and HLA-DRB1*12 and the peptides HLA-B*5802 and HLA-DQB1*03 were found to be associated with latent tuberculosis while the haplotypes DRB1*10-DQB1*02 and DRB1*13-DQB1*06 were found to be associated with active tuberculosis (All p-values≤0.05). The association of HLA-B*5801 and HLA-B*5802 with latent tuberculosis was linked to their ability to bind or not mycobacterial antigens. DRB1*10-DQB1*02 haplotype was found to be over-represented in LTBI compared to ATB (p-value = 0.0015) while DRB1*13-DQB1*06 was found to be under-represented in LTBI compared to ATB (p-value = 0.0335). The DRB1*10-DQB1*02 haplotype was only found in the LTBI when compared with the ATB group. The present study suggests the following algorithm to discriminate LTBI from ATB: QuantiFERON+ and DRB1*10-DQB1*02 haplotype + may indicate LTBI; QuantiFERON+ and DRB1*10-DQB1*02 haplotype - may indicate ATB.

Keywords: Active TB; Algorithm; Clinical genetics; Diagnosis; Epitope; Genetics; HLA-Haplotypes; Immunology; Infectious disease; Latency; Microbiology; Tuberculosis; quantiFERON.