Projects per year
Abstract
Background: Single variant approaches have been successful in identifying DNA methylation quantitative trait loci (mQTL), although as with complex traits they lack statistical power to identify effects from rare genetic variants. We have undertaken extensive analyses to identify regions of low frequency and rare variants that are associated with DNA methylation levels.
Methods: We used repeated measurements of DNA methylation from five different life stages in human blood, taken from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Variants were collapsed across CpG islands and their flanking regions to identify variants collectively associated with methylation, where no single variant was individually responsible for the observed signal. All analyses were undertaken using the sequence kernel association test.
Results: For loci where no individual variant mQTL was observed based on a single variant analysis, we identified 95 unique regions where the combined effect of low frequency variants (MAF≤5%) provided strong evidence of association with methylation. For loci where there was previous evidence of an individual variant mQTL, a further 3 regions provided evidence of association between multiple low frequency variants and methylation levels. Effects were observed consistently across 5 different time points in the lifecourse and evidence of replication in the TwinsUK and Exeter cohorts was also identified.
Conclusion: We have demonstrated the potential of this novel approach to mQTL analysis by analysing the combined effect of multiple low frequency or rare variants. Future studies should benefit from applying this approach as a complementary follow up to single variant analyses.
Methods: We used repeated measurements of DNA methylation from five different life stages in human blood, taken from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Variants were collapsed across CpG islands and their flanking regions to identify variants collectively associated with methylation, where no single variant was individually responsible for the observed signal. All analyses were undertaken using the sequence kernel association test.
Results: For loci where no individual variant mQTL was observed based on a single variant analysis, we identified 95 unique regions where the combined effect of low frequency variants (MAF≤5%) provided strong evidence of association with methylation. For loci where there was previous evidence of an individual variant mQTL, a further 3 regions provided evidence of association between multiple low frequency variants and methylation levels. Effects were observed consistently across 5 different time points in the lifecourse and evidence of replication in the TwinsUK and Exeter cohorts was also identified.
Conclusion: We have demonstrated the potential of this novel approach to mQTL analysis by analysing the combined effect of multiple low frequency or rare variants. Future studies should benefit from applying this approach as a complementary follow up to single variant analyses.
Original language | English |
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Pages (from-to) | 4339-4349 |
Number of pages | 11 |
Journal | Human Molecular Genetics |
Volume | 25 |
Issue number | 19 |
Early online date | 15 Sept 2016 |
DOIs | |
Publication status | Published - 1 Oct 2016 |
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Dive into the research topics of 'Collapsed Methylation Quantitative Trait Loci analysis for Low Frequency and Rare variants'. Together they form a unique fingerprint.Projects
- 6 Finished
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Novel Methodology for Predicting the Functional Effects of Genetic Variation
1/06/15 → 31/05/18
Project: Research
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Equipment
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Illumina Array
Susan M Ring (Manager)
Bristol Population Health Science InstituteFacility/equipment: Facility
Profiles
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Professor Tom R Gaunt
- Bristol Medical School (PHS) - Professor of Health and Biomedical Informatics and MRC Investigator
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit - Programme lead
Person: Academic , Member
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Dr Tom G Richardson
- Bristol Medical School (PHS) - Honorary Senior Research Fellow
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit
Person: Member, Honorary and Visiting Academic