Identification and application of plasmatic microRNA expression quantitative trait loci (miR-QTL) at first trimester of pregnancy

Abstract

BackgroundMicroRNAs (miRNAs) are a class of small non-coding RNAs regulating gene expression. They are involved in many biological processes, including adaptation to pregnancy. The identification of genetic variants associated with gene expression, known as expression quantitative trait loci (eQTL), helps to understand the underlying molecular mechanisms and determinants of complex diseases. Using data from the prospective pre-birth Gen3G cohort, we investigated associations between maternal genotypes and plasmatic miRNA levels measured during the first trimester of pregnancy of 369 women. ResultsAssessing the associations between about 2 million SNPs and miRNA proximal pairs using best practices from the GTEx consortium, a total of 22,140 significant eQTLs involving 147 unique miRNAs were identified. Elastic-net regressions were applied to select the most relevant SNPs to build genetic risk scores (GRS) for each of these 147 miRNAs. For about half of the circulating miRNAs, the GRS captured >10% of the variance abundance. As a demonstration of the usefulness of the identified eQTLs and derived GRS, we used the GRSs as instrumental variables to test for association between the circulating levels of miRNAs quantified before the 16th week of pregnancy and the development of pregnancy complications (gestational diabetes [GDM] or pre-eclampsia [PE]) developing more than three months later on average. Using predicted miRNA levels derived from instrumental variables, we found 18 significant associations of miRNAs with potential support of causal inference for GDM or PE. ConclusionsOur results represent a valuable resource to understand miRNA regulation and highlight the potential of genetic instruments in predicting circulating miRNA levels and their possible contribution in disease development.