P021
Piloting Precision: Implementation of targeted next generation sequencing for antibiotic resistance testing into the diagnostic algorithm of Tuberculosis in Kyrgyzstan
C Utpatel(1,2) A Iskakova(3) H Hoffmann(4,5) M Sydykova(3) A Kadyrov(6) S Niemann(1,2) G Kalmambetova(6)
1:Research Center Borstel; 2:German Center for Infection Research; 3:Republican Tuberculosis Reference Laboratory; 4:IML red GmbH; 5:SYNLAB Gauting; 6:Republican Tuberculosis Center
Targeted next-generation sequencing (tNGS) is an increasingly valuable tool in tuberculosis diagnostics, offering rapid, comprehensive detection of drug resistance mutations directly from clinical specimens or cultures. Its ability to guide individualized treatment and improve diagnostics makes it particularly beneficial in high-burden settings like Kyrgyzstan, where DR-TB poses major challenges to public health.
Here we report on the first successful implementation of tNGS at the Republican Tuberculosis Reference Laboratory. Using the now WHO-endorsed Deeplex® Myc-TB assay, we conducted a pilot study on sputum samples collected from 2020 to 2022 from 281 people living with TB.
Overall, 266 samples were eligible for tNGS. 238 (89%) yielded full resistance profiles covering 15 drugs. 143/238 (60%) were rifampicin (RIF) resistant. 108 (76%) were MDR, 22 (15%) pre-XDR and 6 (4%) XDR. Bedaquiline resistance was detected in 11/143 (8%) samples which were recovered only from new cases. No resistance to linezolid was detected. Deeplex success rate correlated with smear positivity.
The concordance to phenotypic drug susceptibility testing was 90% for RIF. Noteworthy, 15/19 (79%) of the samples tested phenotypically susceptible towards RIF actually carried low level resistance mutations.
On average, the final tNGS results were available after 53h from the start of DNA extracts.
DR-TB remains a challenge in Kyrgyzstan, particularly due to high numbers of fluoroquinolone and bedaquiline resistance. Our findings support the integration of tNGS into the national diagnostic algorithm as a complementary test to the existing diagnostic methods to improve precise diagnosis of DR-TB.