Polymorphisms in Inflammatory Genes Modulate Clinical Complications in Patients With Sickle Cell Disease

Sickle cell disease (SCD), the most common monogenic disease worldwide, is marked by a phenotypic variability that is, to date, only partially understood. Because inflammation plays a major role in SCD pathophysiology, we hypothesized that single nucleotide polymorphisms (SNP) in genes encoding functionally important inflammatory proteins might modulate the occurrence of SCD complications. We assessed the association between 20 SNPs in genes encoding Toll-like receptors (TLR), NK cell receptors (NKG), histocompatibility leukocyte antigens (HLA), major histocompatibility complex class I polypeptide-related sequence A (MICA) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), and the occurrence of six SCD clinical complications (stroke, acute chest syndrome (ACS), leg ulcers, cholelithiasis, osteonecrosis, or retinopathy). This study was performed in a cohort of 500 patients. We found that the TLR2 rs4696480 TA, TLR2 rs3804099 CC, and HLA-G, rs9380142 AA genotypes were more frequent in patients who had fewer complications. Also, in logistic regression, the HLA-G rs9380142 G allele increased the risk of cholelithiasis (AG vs. AA, OR 1.57, 95%CI 1.16–2.15; GG vs. AA, OR 2.47, 95%CI 1.34–4.64; P = 0.02). For SNPs located in the NKG2D loci, in logistic regression, the A allele in three SNPs was associated with a lower frequency of retinopathy, namely, rs2246809 (AA vs. GG: OR 0.22, 95%CI 0.09–0.50; AG vs. GG: OR 0.47, 95%CI 0.31–0.71; P = 0.004, for patients of same origin), rs2617160 (AT vs. TT: OR 0.67, 95%CI 0.48–0.92; AA vs. TT: OR 0.45, 95%CI 0.23–0.84; P = 0.04), and rs2617169 (AA vs. TT: OR 0.33, 95%CI 0.13–0.82; AT vs. TT: OR 0.58, 95%CI 0.36–0.91, P = 0.049, in patients of same SCD genotype). These results, by uncovering susceptibility to, or protection against SCD complications, might contribute to a better understanding of the inflammatory pathways involved in SCD manifestations and to pave the way for the discovery of biomarkers that predict disease severity, which would improve SCD management.