TGF-β1Genetic Polymorphism Interactions Modulate the Risk of Sickle Cell Nephropathy in the Ghanaian Population

Abstract

Sickle cell disease (SCD) is an inherited blood disease that affects millions of people worldwide. Renal complications associated with sickle cell disease, called sickle cell nephropathy, are a major contributor to early mortality in Sub-Saharan Africa. Clinical studies have implicated some genetic variants in increasing susceptibility to sickle cell nephropathy. Transforming growth factor beta-1 (TGF-β1) is a cytokine that plays a vital role in the progression of sickle cell nephropathy (SCN). Single-nucleotide polymorphisms (SNPs) in the TGF-β1 gene have been implicated in the pathophysiology of several diseases, including diabetic nephropathy, HIV-associated nephropathy, hypertensive nephrosclerosis, and IgA nephropathy, but their association with SCN is unclear. Research on the genetic landscape of SCN is scarce, and no study has been conducted on the TGF β1 gene and SCN in Ghana. Given the strong influence of genetic variations on disease severity and mortality, investigating genetic polymorphisms in this profibrotic cytokine in Ghana offers a rational approach for early risk stratification. The study investigated the presence and possible association of two TGF-β1 SNPs (rs1800469 and rs1800470) that might predispose SCD patients in Ghana to develop sickle cell nephropathy. The participants were recruited from the sickle cell clinic of Tema General Hospital in Tema, Ghana, ensuring a well-characterised cohort. This was a nested case-control study that involved two hundred and four (204) participants with SCD, ninety-seven (97) cases with SCN, and one hundred and seven (107) controls without SCN for comparison, selected from a cohort of 2300 participants based on certain inclusion and exclusion criteria. Genomic DNA was extracted from peripheral blood samples of the selected study participants, and the TGF-β1 gene was genotyped for selected SNPs using the TaqMan SNP assay. This assay uses fluorescently labelled, allele-specific probes to hybridise with target sequences to allow precise determination of genotypes based on fluorescent signals. The association between SNPs and SCN was assessed using logistic regression analysis under different genetic models, and a p-value of < 0.05 was considered statistically significant. The major findings of this study were that rs1800469 showed a strong protective association with SCN, with the additive model yielding an odds ratio of 0.11 for heterozygote carriers and a consistent protective trend in the dominant model. Both SNPs showed a strong main effect on SCN risk under the additive model (rs1800469 OR = 3.87, p = 0.032; rs1800470 OR = 8.12, p = 0.013), with the interaction term suggesting a buffering effect between the loci. Under the recessive model, rs1800470 showed a significantly strong association with SCN risk, but the interaction term between both variants indicates a protective joint effect. Different inheritance models revealed divergent effects, highlighting that rs1800469 acts largely as a protective variant, whereas rs1800470 may confer risk in a recessive manner. In conclusion, this study showed that rs1800469 reduces the risk of SCN as compared to the reference genotype, while rs1800470 increases the risk of SCN only when there are two copies of the variant allele. This suggests that these SNPs can help guide research into high-risk and protective genotypes and are informative for clinical monitoring of SCN. The study revealed an epistatic interaction between the two SNPs, whereby their combined presence attenuates the effect that would have been exerted by each SNP independently. This calls for the need for multifactorial genetic models for research, and that risk prediction would require a polygenic risk profile instead of single-locus tests.