This PhD proposal aims to look at a gene, the HMOX1 gene, that is critical for managing the breakdown of haemoglobin in humans. Previous studies have shown that this gene is critical for management of infection. In animal studies, loss of function of this gene is associated with much worse outcomes in infection (more likely to die). In humans, there is much more uncertainty about the role of this gene and its importance. It has previously been shown that a small region of DNA in this gene is comprised of a dinucleotide repeat, where the two bases guanine and thymine are repeated. This is called a “GT” repeat. In this region, the DNA code is of variable length between patients, with an average of 31 repeats across the whole population, although some people have as little as 20 repeats, and some as high as 45. In previous small studies, the length of this repeat has altered the amount the gene is switched on and off (gene expression), and some studies have shown this has important impacts on lots of diseases, including in infection. Previous studies have shown those with longer repeats are more likely to be diagnosed with Type 2 diabetes, for example. Importantly, multiple studies in malaria have shown that carriage of the longer repeats is associated with much better outcomes, with a large reduction in severe malaria. However, all of the previous studies (in all clinical diseases) have been performed in small cohorts. In this proposal, we aim to measure this repeat using bioinformatic tools in ALSPAC using whole genome sequencing data. We also then plan to measure this repeat using another methodology, by imputing it from array data. These two methods will be compared to test the accuracy of repeat calling from array data. This will also be used to allow confidence in the imputation method so this can be used in other databases (e.g. UK Biobank). Subsequently, we will then look at the relationship between the repeat length and various clinical and bioinformatic measurements. In particular, we will focus on whether repeat length relates to immunological function (e.g. antibody levels, T-cell function (where measured)), clinical outcomes (both self-reported and healthcare linked), and metabolomic outcomes. Finally, we will also look at the impact of this repeat on the transcriptome, to see if gene expression truly changes with the repeat length. Further work will compare results from ALSPAC with other cohorts e.g. UK Biobank. All participants who have genetic data will be included.