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Susceptibility to leishmaniasis is affected by host SLC11A1 gene polymorphisms: a systematic review and meta-analysis

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Leishmaniases are cutaneous, mucocutaneous, and visceral diseases affecting humans and domesticated animals mostly in the tropical and subtropical areas of the planet. Host genetics have been widely investigated for their role in developing various infectious diseases. The SLC11A1 gene has been reported to play a role in neutrophil function and is associated with susceptibility to infectious and inflammatory diseases such as tuberculosis or rheumatoid arthritis. In the present meta-analysis, we investigate the genetic association of SLC11A1 polymorphisms with susceptibility to leishmaniasis. Genotypes and other risk-related data were collected from 13 case-control and family-based studies (after literature search). Conventional random-effects meta-analysis was performed using STATA 13. To pool case-control and family-based data, the weighted Stouffer’s method was also applied. Eight polymorphisms were investigated: rs2276631, rs3731865, rs3731864, rs17221959, rs201565523, rs2279015, rs17235409, and rs17235416. We found that rs17235409 (D543N) and rs17235416 (1729 + 55del4) are significantly associated with a risk for cutaneous leishmaniasis (CL), whereas rs17221959, rs2279015, and rs17235409 are associated with visceral leishmaniasis (VL). Our results suggest that polymorphisms in SLC11A1 affect susceptibility to CL and VL. These findings open new pathways in understanding macrophage response to Leishmania infection and the genetic factors predisposing to symptomatic CL or VL that can lead to the usage of predictive biomarkers in populations at risk.

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Correspondence to Georgia G. Braliou or Pantelis G. Bagos.

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Braliou, G.G., Kontou, P.I., Boleti, H. et al. Susceptibility to leishmaniasis is affected by host SLC11A1 gene polymorphisms: a systematic review and meta-analysis. Parasitol Res 118, 2329–2342 (2019). https://doi.org/10.1007/s00436-019-06374-y

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  • Leishmaniasis
  • SLC11A1
  • Meta-analysis
  • Genetic association
  • Predictive biomarkers
  • Genetic risk