PT - JOURNAL ARTICLE AU - Gabriel Cuellar Partida AU - Charles Laurin AU - Susan M. Ring AU - Tom R. Gaunt AU - Caroline L. Relton AU - George Davey Smith AU - David M. Evans TI - Imprinted loci may be more widespread in humans than previously appreciated and enable limited assignment of parental allelic transmissions in unrelated individuals AID - 10.1101/161471 DP - 2017 Jan 01 TA - bioRxiv PG - 161471 4099 - http://biorxiv.org/content/early/2017/07/10/161471.short 4100 - http://biorxiv.org/content/early/2017/07/10/161471.full AB - Genomic imprinting is an epigenetic mechanism leading to parent-of-origin dependent gene expression. So far, the precise number of imprinted genes in humans is uncertain. In this study, we leveraged genome-wide DNA methylation in whole blood measured longitudinally at 3 time points (birth, childhood and adolescence) and GWAS data in 740 Mother-Child duos from the Avon Longitudinal Study of Parents and Children (ALSPAC) to systematically identify imprinted loci. We reasoned that cis-meQTLs at genomic regions that were imprinted would show strong evidence of parent-of-origin associations with DNA methylation, enabling the detection of imprinted regions. Using this approach, we identified genome-wide significant cis-meQTLs that exhibited parent-of-origin effects (POEs) at 35 novel and 50 known imprinted regions (10−10< P <10−300). Among the novel loci, we observed signals near genes implicated in cardiovascular disease (PCSK9), and Alzheimer’s disease (CR1), amongst others. Most of the significant regions exhibited imprinting patterns consistent with uniparental expression, with the exception of twelve loci (including the IGF2, IGF1R, and IGF2R genes), where we observed a bipolar-dominance pattern. POEs were remarkably consistent across time points and were so strong at some loci that methylation levels enabled good discrimination of parental transmissions at these and surrounding genomic regions. The implication is that parental allelic transmissions could be modelled at many imprinted (and linked) loci and hence POEs detected in GWAS of unrelated individuals given a combination of genetic and methylation data. Our results indicate that modelling POEs on DNA methylation is effective to identify loci that may be affected by imprinting.