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Rayane Rafei, Rayane AL Iaali, Marwan Osman, Fouad Dabboussi, Monzer Hamze
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A global snapshot on the prevalent macrolide-resistant emm types of Group A Streptococcus worldwide, their phenotypes and their resistance marker genotypes during the last two decades: A systematic review
Watchful epidemiological surveillance of macrolide-resistant Group A Streptococcus (MRGAS) clones is important owing to the evolutionary and epidemiological dynamic of GAS. Meanwhile, data on the global distribution of MRGAS emm types according to macrolide resistance phenotypes and genotypes are scant and need to be updated. For this, the present systematic review analyses a global set of extensively characterized MRGAS isolates from patients of diverse ages and clinical presentations over approximately two decades (2000 to 2020) and recaps the peculiar epidemiological features of the dominant MRGAS clones. Based on the inclusion and exclusion criteria, 53 articles (3593 macrolide-resistant and 15,951 susceptible isolates) distributed over 23 countries were dissected with a predominance of high-income countries over low-income ones. Although macrolide resistance in GAS is highly variable in different countries, its within-GAS distribution seems not to be random. emm pattern E, 13 major emm types (emm12, 4, 28, 77, 75, 11, 22, 92, 58, 60, 94, 63, 114) and 4 emm clusters (A-C4, E1, E6, and E2) were significantly associated with macrolide resistance. emm patterns A-C and D, 14 major emm types (emm89, 3, 6, 2, 44, 82, 87, 118, 5, 49, 81, 59, 227, 78) and 3 well-defined emm clusters (AC5, E3, and D4) were significantly associated with macrolide susceptibility. Scrutinizing the tendency of each MRGAS emm type to be significantly associated with specific macrolide resistance phenotype or genotype, interesting vignettes are also unveiled. The 30-valent vaccine covers ~95% of MRGAS isolates. The presented data urge the importance of comprehensive nationwide sustained surveillance of MRGAS circulating clones particularly in Low and Middle income countries where sampling bias is high and GAS epidemiology is obfuscated and needs to be demystified.
