Genes-in-Action - Hepcidin Regulation of Iron Supplementation

Anaemia is a recalcitrant problem in global health, affecting particularly children and childbearing women in sub-Saharan Africa. Anaemia causes impaired growth and cognitive development in children, poor pregnancy outcomes including both maternal and perinatal mortality. Also, it is associated with poor economic growth due to its impact on physical activity.

Mass iron supplementation and food fortification are commonly used to combat anaemia in low- and middle-income countries. This due to the fact that the main driver of anaemia is thought to be nutritional iron deficiency. However, these programs have had little impact in sub-Saharan Africa and new strategies are desperately needed.

Low-cost oral iron tablets and micronutrient powders are routinely given to treat and prevent anaemia in both children and pregnant women. However, often these interventions are frequently ineffective, never very effective, and may even cause harm by increasing susceptibility to infections. Both the aetiology of anaemia and the efficacy of iron absorption are complex processes influenced by multiple factors, including nutritional status, infection and host genetics.

Hepcidin, a 25-amino acid liver-produced hormone is the master regulator of body iron status. Hepcidin controls plasma iron influx through its interaction with ferroportin - the only known cellular iron channel. Hepcidin's binding to ferroportin leads to the degradation and internalisation of the latter, thereby blocking iron traffic from macrophages, hepatocytes and duodenal enterocytes, into the plasma. Hepcidin secretion is dampened by hypoxia, erythroid drive and iron deficiency, to enable iron absorption, whereas, iron sufficiency/overload and infection enhances hepcidin transcription.

Hepcidin transcription is regulated by a number of signals and pathways. At the molecular level, the regulation of hepcidin expression is complex, but one of the key regulators is TMPRSS6 (transmembrane protease serine 6). TMPRSS6 (also called matriptase-2) is a type II transmembrane serine protease principally expressed in the liver. TMPRSS6 indirectly regulates hepcidin transcription, by interfering with the bone morphogenetic protein (BMP), hemojuvelin (HJV), and son of mothers against decapentaplegic homolog (SMAD) signalling pathway. TMPRSS6 decreases hepcidin transcription by cleaving hemojuvelin (HJV), thus, reducing BMP-SMAD signalling. Cleavage of membrane-bound HJV, the BMP receptor, by TMPRSS6 leads to BMP reduction, thereby decreasing BMP, resulting in hepcidin repression as BMP-HJV signalling is required for hepcidin transcription. TMPRSS6 is the main negative regulator of hepcidin expression and functional variants leas to iron-refractory iron deficiency anaemia (IRIDA).

Due to its central role in iron homeostasis, most inherited iron pathologies arise from genetic defects in genes encoding proteins that regulate hepcidin or in the hepcidin gene (HAMP) itself. Genetic variations that inactivate HAMP expression result in hepcidin deficiency, which has been implicated inherited iron-loading diseases such as hereditary hemochromatosis (HH). In contrast, genetic alteration that lead to elevated ristrictis iron availability. For instance, genetic defects that curtail the expression of TMPRSS6 results in elevated hepcidin, thereby causing anaemia that is resistant to oral iron supplementation, IRIDA.

This project aims to investigate the impact of functional single nucleotide polymorphisms (SNPs) in the genes within the hepcidin regulatory pathways that are known or proposed to predispose to low iron status. To begin with, the focus will be on three common SNPs within the TMPRSS6 gene, rs855791, rs4820268 and rs2235321, with minor allele frequencies (MAF) at 7, 27 and 44% in the study population. These SNPs were selected with reference to previous association and genome-wide association (GWA) studies. All three SNPs have been significantly associated with fall in plasma iron status biomarkers, including serum iron, haemoglobin concentrations, transferrin saturation, and a rise in hepcidin levels, as well as iron deficiency anaemia in both association and GWA studies.

The hypothesis is that risk alleles will cause a baseline increase in serum hepcidin levels and that individuals with these SNPs will absorb iron less effectively than those with the wild-type alleles. Subsequently, more functional or putative functional SNPs within the TMPRSS6 gene and other hepcidin/iron-related genes such as TF, SLC11A2, TFR2 will be investigated.

Several GWAS have to identified dozens of SNPs association associated with low iron status. Although these studies can detect phenotype-genotype associations, they fail to reveal functional and mechanism underlying genotype-phenotyoe relationships. For instance, this approach may be misleading due influence of variations in interim phenotypes, especially in relation to genetic predictors of infections. Thus, in order to overcome this limitation, the investigators will employ a recall-by-genotype paradigm the investigators termed 'Genes-in-Action' (GiA) to understand genotype-phenotype relationships and identify causal relationships. The GiA study design will use pre-determine genetic variants of interest to investigate the effect of genotype on phenotypic outcomes (genotype-biomarker-phenotype). Furthermore, the GiA study design will require a large and traceable pre-genotype population. Participant selection using pre-determined genetic variants improves statistical power by eliminating recruitment of non-informative participants, thus providing major ethical benefits.

The existing resource of the MRC-Gambia Keneba Biobank will be used as the basis for study participant selection. This resource allows individuals from rural Gambia to be recalled from an area, where a recent survey reported that anaemia affects 60% and 73% of child-bearing women and children respectively. Participants will be selected from a database comprising of data on >3000 Gambians, with Illumina HumanExome array data on 80K directly genotyped putative functional variants as well as imputation data on 20M variants.