Malaria Journal (Nov 2022)
HMOX1 STR polymorphism and malaria: an analysis of a large clinical dataset
Abstract
Abstract Background Inducible expression of heme oxygenase-1 (encoded by the gene HMOX1) may determine protection from heme released during malaria infections. A variable length, short tandem GT(n) repeat (STR) in HMOX1 that may influence gene expression has been associated with outcomes of human malaria in some studies. In this study, an analysis of the association between variation at the STR in HMOX1 on severe malaria and severe malaria subtypes is presented in a large, prospectively collected dataset (MalariaGEN). Methods The HMOX1 STR was imputed using a recently developed reference haplotype panel designed for STRs. The STR was classified by total length and split into three alleles based on an observed trimodal distribution of repeat lengths. Logistic regression was used to assess the association between this repeat on cases of severe malaria and severe malaria subtypes (cerebral malaria and severe malarial anaemia). Individual analyses were performed for each MalariaGEN collection site and combined for meta-analysis. One site (Kenya), had detailed clinical metadata, allowing the assessment of the effect of the STR on clinical variables (e.g. parasite count, platelet count) and regression analyses were performed to investigate whether the STR interacted with any clinical variables. Results Data from 17,960 participants across 11 collection sites were analysed. In logistic regression, there was no strong evidence of association between STR length and severe malaria (Odds Ratio, OR: 0.96, 95% confidence intervals 0.91–1.02 per ten GT(n) repeats), although there did appear to be an association at some sites (e.g., Kenya, OR 0.90, 95% CI 0.82–0.99). There was no evidence of an interaction with any clinical variables. Conclusions Meta-analysis suggested that increasing HMOX1 STR length is unlikely to be reliably associated with severe malaria. It cannot be ruled out that repeat length may alter risk in specific populations, although whether this is due to chance variation, or true variation due to underlying biology (e.g., gene vs environment interaction) remains unanswered.