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. 2024 Oct 11;16(10):1597.
doi: 10.3390/v16101597.

Frequency of Major Transmitted Integrase Resistance in Poland Remains Low Despite Change in Subtype Variability

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Frequency of Major Transmitted Integrase Resistance in Poland Remains Low Despite Change in Subtype Variability

Kaja Mielczak et al. Viruses. .

Abstract

With the widespread use of integrase inhibitors and the expanding use of long-acting cabotegravir in both pre-exposure prophylaxis and antiretroviral treatment, molecular surveillance on the transmission of integrase resistance has regained clinical significance. This study aimed to determine the frequency of INSTI-transmitted drug resistance mutations (DRMs) among treatment-naïve individuals in Poland from 2016 to 2023. INSTI resistance was analyzed in 882 antiretroviral treatment-naïve individuals using Sanger sequencing. Integrase DRMs were defined based on the Stanford HIV drug resistance database scores. Phylogeny was used to investigate subtyping and clustering. For the analysis of time-trends, logistic regression was used. Major (E138K and R263K) integrase mutations were detected in 0.45% of cases with minor resistance observed in 14.85%, most commonly (13.95%) E157Q. Overall, no major clusters of transmitted drug resistance were identified, and the transmission of E157Q showed a decreasing trend (p < 0.001). While the frequency of sub-subtype A6 increased, it was predominantly found among migrants and associated with L74 mutations. The frequency of major integrase-transmitted DRMs remains low, despite the changes in subtype variability. Surveillance of changing HIV molecular variation patterns is vital from the perspective of the optimal use of integrase inhibitors, especially due to expanding long-acting cabotegravir implementation.

Keywords: HIV; clustering; integrase strand transfer inhibitors; resistance mutations; transmitted drug resistance.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Logistic regression estimates for time trends between 2016 and 2023 are shown for major (red, dashed line) and minor (blue, solid line) DRMs. Dots represent the percentage per year, with vertical bars indicating 95% confidence intervals. The logistic regression trend lines are shown vertically, with shaded areas representing 95% confidence intervals for the regression estimate.
Figure 2
Figure 2
(a) Prevalence of minor DRMs over time among subtype B sequences. (b) Prevalence of minor DRMs over time among sub-subtype A6 sequences.
Figure 2
Figure 2
(a) Prevalence of minor DRMs over time among subtype B sequences. (b) Prevalence of minor DRMs over time among sub-subtype A6 sequences.
Figure 3
Figure 3
(a) Time trend in the prevalence of subtype B. (b) Time trend in the prevalence of sub-subtype A6.
Figure 3
Figure 3
(a) Time trend in the prevalence of subtype B. (b) Time trend in the prevalence of sub-subtype A6.
Figure 4
Figure 4
(a) Phylogenetic tree for subtype B. Sequences with DRMs are marked with dots. Clustering sequences are highlighted with different colors based on the number of sequences in the cluster, as indicated in the legend. Bootstrap values > 70% are shown at the branch nodes. (b) Phylogenetic tree for sub-subtype A6.
Figure 4
Figure 4
(a) Phylogenetic tree for subtype B. Sequences with DRMs are marked with dots. Clustering sequences are highlighted with different colors based on the number of sequences in the cluster, as indicated in the legend. Bootstrap values > 70% are shown at the branch nodes. (b) Phylogenetic tree for sub-subtype A6.

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