Abstract
Background: Sickle cell disease (SCD) is marked by wide variability in clinical phenotypes and severity due to environmental, clinical, and genetic factors. Variants in iron-regulatory genes are well described modifiers of clinical presentation in different diseases, but their role in modulating SCD phenotype has been sparsely studied in African populations. In this cross-sectional study, we investigated the role of single nucleotide polymorphisms (SNPs) in iron-regulatory genes in SCD severity and lifetime transfusion(Tx) requirement.
Methods: The study was approved by the institutional review board of Lagos University Teaching Hospital, Lagos, Nigeria. Clinical data were abstracted from medical records and patient interviews using a structured questionnaire. Participants were recruited in steady state and were stratified according to the severity score previously described by Shah et al. (Clinicoecon Outcomes Res. 2020;12:625). Biochemical analyses included serum transferrin and serum iron; transferrin saturation (TS) was calculated. Genotyping was performed using the Axiom Precision Medicine Research Array (PMRA; Thermo Fisher Scientific). Seventy-one single nucleotide polymorphisms (SNPs) in genes implicated in iron metabolism were analyzed, including SLC40A1 (ferroportin), HFE (homeostatic iron regulator), HJV (hemojuvelin), HAMP (hepcidin), and TFR2 (transferrin receptor 2). SNPs whose variants were not represented in this cohort, including HFE C282Y and H63D, were excluded. Ensembl and NCBI databases were used to describe the wild-type (WT)/variant alleles and gene consequences. Univariate and multivariate logistic regression were used to analyze binary outcomes, and age-adjusted linear regression for Tx burden. Odds ratios (OR) and regression coefficients (β) were estimated using the WT as the reference. Multiple-testing correction was performed as necessary. Statistical analyses were conducted in R version 4.4.1, with p<0.05 considered significant.
Results: We included 60 genotyped, confirmed HbSS patients; median age was 22 years (range: 18–43), 22 (37.3%) were female, 42 (70.0%) were classified as mild severity (Class I), 5 (8.0%) as Class II, and 13 (22.0%) as severe (Class III). Twenty-seven (45.0%) had never received a blood Tx, while 33 (55.0%) had received Tx, median of 2units (range: 1-10).
On univariate analysis (UVA), five SNPs (rs10218795, rs10188230, rs114250626, rs4287798, and rs634349) were significantly associated with severe phenotype; three of these remained significant on multivariable analysis (MVA). Two were associated with higher odds of severe phenotype: rs10177654 (OR = 28.9, 95% CI: 3.0–100.0, p = 0.03) and rs10218795 (OR = 15.0, 95% CI: 2.4–327.0, p<0.01), while rs10188230 was associated with lower odds (OR = 0.03, 95% CI: 0.008–0.28, p<0.01). Results remained consistent after adjusting for age.
For lifetime transfusion burden, both UVA and MVA identified two significant SNPs: rs4667289, associated with higher transfusion burden (β = 2.6, 95% CI: 0.04–5.2, p = 0.047) and rs11568344, associated with lower transfusion burden (β = –1.8, 95% CI: –3.5 to –0.36, p = 0.02).
Genotype distributions for the five significant SNPs were as follows: rs10177654 (SLC40A1, transcription factor binding site), TT(WT) 12 (20.3%), TC 30 (50.8%), CC 17 (28.8%); rs10188230 (SLC40A1, intron variant), TT (WT) 32 (54.2%), TC 22 (37.3%), CC 5 (8.5%); rs10218795 (HJV, intron variant), CC (WT) 22 (37.3%), TC 29 (49.2%), TT 8 (13.6%); rs4667289 (SLC40A1 proximal intergenic), GG (WT) 46 (78.0%), AG 10 (16.9%), AA 3 (5.1%); rs11568344 (SLC40A1 splice region variant), GG (WT) 47 (79.7%), AG 9 (15.3%), AA 3 (5.1%).
Compared with the homozygous WT, patients with rs10188230 had a lower median TS (21.65% vs. 43.3%, p = 0.04), while those with rs4667289 had a higher median TS (83% vs. 31%, p<0.01). When adjusted for age and lifetime Tx, rs4667289 remained significant (β = 47.8, 95% CI 3.6-82.8, p = 0.03). No other SNPs showed association with TS.
Conclusion: We present novel genetic data on iron-regulatory variants in African patients with sickle cell disease, identifying SNPs in SLC40A1 and HJV associated with disease severity. Most of these are yet to be fully described in the literature, and their intronic locations suggest possible regulatory roles. We hope to further validate these findings in larger cohorts and through functional studies to clarify their impact on iron metabolism and clinical significance.
