Department of Donor Medicine Research - Donor Studies, Sanquin Research, Amsterdam, The Netherlands.
Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Vox Sang. 2021 Aug;116(7):755-765. doi: 10.1111/vox.13066. Epub 2021 Jan 25.
Blood donors might develop iron deficiency as approximately 250 mg of iron is lost with every donation. Susceptibility to iron deficiency and low haemoglobin levels differs between individuals, which might be due to genetic variation. Therefore, the aim of this study was to investigate associations between single nucleotide polymorphisms (SNPs) and haemoglobin trajectories, haemoglobin levels and ferritin levels in blood donors.
In 2655 donors participating in the observational cohort study Donor InSight-III (2015-2017), haemoglobin and ferritin levels were measured in venous EDTA whole blood and plasma samples, respectively. Haemoglobin trajectories (stable/declining) were determined by fitting growth-mixture models on repeated pre-donation capillary haemoglobin measurements. Genotyping was done using the UK Biobank - version 2 Axiom Array. Single SNP analyses adopting an additive genetic model on imputed genetic variants were performed for haemoglobin trajectories, haemoglobin levels and ferritin levels. Conditional analyses identified independent SNPs.
Twelve, twenty and twenty-four independent SNPs were associated with haemoglobin trajectories, haemoglobin levels and ferritin levels respectively (P < 1 x 10 ). Rs112016443 reached genome-wide significance for ferritin levels, which influences WDSUB1 expression.
Rs112016443 was genome-wide significantly associated with ferritin levels in Dutch donors. Further validation studies are needed, as well as studies towards underlying mechanisms and predicting iron deficiency using SNPs.
由于每次献血会损失约 250 毫克的铁,献血者可能会出现缺铁。个体对缺铁和低血红蛋白水平的易感性存在差异,这可能与遗传变异有关。因此,本研究旨在探讨单核苷酸多态性(SNP)与献血者血红蛋白轨迹、血红蛋白水平和铁蛋白水平之间的关系。
在参加观察性队列研究 Donor InSight-III(2015-2017 年)的 2655 名献血者中,分别测量静脉 EDTA 全血和血浆样本中的血红蛋白和铁蛋白水平。通过对重复的预捐毛细血管血红蛋白测量值进行生长混合模型拟合,确定血红蛋白轨迹(稳定/下降)。使用 UK Biobank-版本 2 Axiom 阵列进行基因分型。采用加性遗传模型对推断的遗传变异进行单 SNP 分析,以研究血红蛋白轨迹、血红蛋白水平和铁蛋白水平。条件分析确定了独立的 SNP。
12、20 和 24 个独立的 SNP 分别与血红蛋白轨迹、血红蛋白水平和铁蛋白水平相关(P<1×10)。Rs112016443 与铁蛋白水平达到全基因组显著相关,影响 WDSUB1 的表达。
Rs112016443 与荷兰献血者的铁蛋白水平存在全基因组显著关联。需要进一步的验证研究,以及研究 SNP 预测铁缺乏的潜在机制。