Cytokine polymorphisms in patients with autoimmune hemolytic anemia.
Front Immunol 2023;
14:1221582. [PMID:
38022547 PMCID:
PMC10667680 DOI:
10.3389/fimmu.2023.1221582]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Autoimmune hemolytic anemia (AIHA) is due to autoantibodies with or without complement activation and involves cellular and cytokine dysregulation. Here, we investigated cytokine single-nucleotide polymorphisms (SNPs) of TNF-α, TGF-β1, IL-10, IL-6, and IFN-γ, along with their serum levels. The former were related to hematological parameters, therapy, and clinical outcome. The study included 123 consecutive patients with primary AIHA [77 warm AIHA and 46 cold agglutinin disease (CAD)], followed up for a median of 49 months. Results show that the allelic frequency of TNF-α -308 G/A polymorphisms was significantly lower in patients versus controls. Moreover, the genotypic frequency of TNF-α -308G/A and TGF-β gene codon 25 G/C genotypes was significantly lower in patients versus controls. Considering cytokine SNP genotypes associated with different gene expression levels, TNF-α high gene expression was significantly more frequent in patients, TGF-β and IL-10 high gene expression was higher in patients with more severe anemia, and TGF-β high gene expression was higher in patients with active disease. Considering treatment, TNF-α and TGF-β high gene expression was more frequent in multitreated patients and particularly in CAD. It may be speculated that this genetic predisposition to a stronger inflammatory response may result in a greater immune dysregulation and in a relapsed/refractory disease. Regarding cytokine serum levels, TNF-α and TGF-β were significantly lower, and IL-10 and IL-6 were significantly higher in patients versus controls, underlying the complex interplay between genetic background and disease features.
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