Correlation between serum ANKRD22 and SERPING1 levels and drug resistance in pulmonary tuberculosis: A retrospective cross-sectional study

Drug-resistant tuberculosis (TB) lacks rapid blood-based biomarkers. This study examined whether serum levels of ankyrin repeat domain 22 (ANKRD22) and serpin family G member 1 (SERPING1) are associated with drug resistance in TB patients. In this retrospective cross-sectional study, 170 culture-confirmed TB patients treated from January 2023 to December 2023 were classified as drug-resistant (n = 34) or drug-susceptible (n = 136) by phenotypic drug susceptibility testing. We quantified serum ANKRD22 and SERPING1 levels by enzyme-linked immunosorbent assay, used multivariate logistic regression to identify independent risk factors, and assessed diagnostic performance with receiver operating characteristic curve analysis. Both biomarkers were significantly higher in the drug-resistant group (P < .001) and positively correlated with resistance (ANKRD22 R = 0.551, SERPING1 R = 0.520). Area under the curve values were 0.898 for ANKRD22, 0.875 for SERPING1, and 0.912 for combined detection. After adjustment, elevated ANKRD22 and SERPING1 remained independent predictors, along with smoking, chronic obstructive pulmonary disease, cavitary disease, previous TB exposure, and treatment interruption. Serum ANKRD22 and SERPING1 are independently associated with TB drug resistance; their combined measurement improves diagnostic accuracy and may facilitate early detection of drug-resistant TB.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2025-10-31
DOI
https://doi.org/10.1097/md.0000000000045424
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Correlation between serum ANKRD22 and SERPING1 levels and drug resistance in pulmonary tuberculosis: A retrospective cross-sectional study

Niannian Liu, Li Zhang, Mei Zhou, Qianyun Zhou et al.
Medicine
Tuberculosis Research and Epidemiology
article

Correlation between serum ANKRD22 and SERPING1 levels and drug resistance in pulmonary tuberculosis: A retrospective cross-sectional study

Niannian Liu, Li Zhang, Mei Zhou, Qianyun Zhou, Jian Wei Xu, Xiao Lang
article en

Abstract

Drug-resistant tuberculosis (TB) lacks rapid blood-based biomarkers. This study examined whether serum levels of ankyrin repeat domain 22 (ANKRD22) and serpin family G member 1 (SERPING1) are associated with drug resistance in TB patients. In this retrospective cross-sectional study, 170 culture-confirmed TB patients treated from January 2023 to December 2023 were classified as drug-resistant (n = 34) or drug-susceptible (n = 136) by phenotypic drug susceptibility testing. We quantified serum ANKRD22 and SERPING1 levels by enzyme-linked immunosorbent assay, used multivariate logistic regression to identify independent risk factors, and assessed diagnostic performance with receiver operating characteristic curve analysis. Both biomarkers were significantly higher in the drug-resistant group (P < .001) and positively correlated with resistance (ANKRD22 R = 0.551, SERPING1 R = 0.520). Area under the curve values were 0.898 for ANKRD22, 0.875 for SERPING1, and 0.912 for combined detection. After adjustment, elevated ANKRD22 and SERPING1 remained independent predictors, along with smoking, chronic obstructive pulmonary disease, cavitary disease, previous TB exposure, and treatment interruption. Serum ANKRD22 and SERPING1 are independently associated with TB drug resistance; their combined measurement improves diagnostic accuracy and may facilitate early detection of drug-resistant TB.

MedicineVol. 104(44)
First People's Hospital of Chongqing (CN)
Openalex Percentile: Top 59%
Tuberculosis Research and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.