Specific Cytokines Analysis Incorporating Latency-Associated Antigens Differentiates

Mycobacterium tuberculosis active tuberculosis cytokine latency-associated antigen latent tuberculosis infection virulence factor

Journal

Infection and drug resistance
ISSN: 1178-6973
Titre abrégé: Infect Drug Resist
Pays: New Zealand
ID NLM: 101550216

Informations de publication

Date de publication:
2024
Historique:
received: 27 03 2024
accepted: 29 07 2024
medline: 12 8 2024
pubmed: 12 8 2024
entrez: 12 8 2024
Statut: epublish

Résumé

Current immunologic methods cannot distinguish ATB patients (20), LTBI healthcare workers (25), fever patients (11), and healthy controls (10) were enrolled. Cytokine levels (IFN-γ, TNF-α, IL-2, IL-6, IP-10, IL-1Ra, CXCL-1, and MCP-1) were measured using Luminex with/without MTB-specific virulence factor and latency-associated antigens stimulation. Without antigen stimulation, IL-6, IP-10, MCP-1, and IL-1Ra were higher in the ATB group than in the LTBI group (p<0.05), but no significant differences between the ATB group and the fever group. Stimulated with the four antigens, respectively, the cytokines, including IP-10 Latency-associated antigens enhance multiple cytokine discriminatory ability, particularly TH1-type cytokines, for differentiating Mtb infection statuses.

Identifiants

pubmed: 39131518
doi: 10.2147/IDR.S470963
pii: 470963
pmc: PMC11317045
doi:

Types de publication

Journal Article

Langues

eng

Pagination

3385-3393

Informations de copyright

© 2024 Li et al.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Yuanchun Li (Y)

Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Zhengrong Yang (Z)

Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Qiping Ge (Q)

Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People's Republic of China.

Yueqiu Zhang (Y)

Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Mengqiu Gao (M)

Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People's Republic of China.

Xiaoqing Liu (X)

Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Clinical Epidemiology Unit, Peking Union Medical College, International Clinical Epidemiology Network, Beijing, People's Republic of China.
Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Lifan Zhang (L)

Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Clinical Epidemiology Unit, Peking Union Medical College, International Clinical Epidemiology Network, Beijing, People's Republic of China.
Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Classifications MeSH