Collapsed methylation quantitative trait loci analysis for low frequency and rare variants

Area of Science:

• Genetics
• Epigenetics
• Bioinformatics

Background:

• Single variant analyses successfully identify DNA methylation quantitative trait loci (mQTLs).
• However, these methods lack the statistical power to detect associations involving rare genetic variants.
• This study addresses the need to identify effects from low-frequency and rare variants on DNA methylation.

Purpose of the Study:

• To develop and apply a novel approach for identifying regions of low-frequency and rare variants associated with DNA methylation levels.
• To overcome the limitations of single-variant mQTL analyses.

Main Methods:

• Utilized repeated DNA methylation measurements across five life stages from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.
• Collapsed variants across CpG islands and flanking regions for collective association analysis.
• Employed the sequence kernel association test (SKAT) for all analyses.

Main Results:

• Identified 95 unique regions with associations between combined low-frequency variants (MAF ≤ 5%) and methylation, where single-variant analysis failed.
• Found 3 additional regions with associations involving multiple low-frequency variants in loci with prior single-variant mQTL evidence.
• Observed consistent effects across five life stages and replicated findings in the TwinsUK and Exeter cohorts.

Conclusions:

• Demonstrated the potential of a novel multi-variant approach for mQTL analysis.
• This method effectively identifies associations involving multiple low-frequency or rare variants.
• Recommends this approach as a complementary follow-up to single-variant analyses in future studies.