Kieran J. O’Donnell

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Across 15 cohorts (birth to 24 years), 20 epigenetic clocks and eight brain age models predicted chronological age modestly, stabilizing by middle childhood; their age residuals were weakly associated.

slideimp: Efficient Imputation for DNA Methylation Data

slideimp provides efficient imputation methods for DNA methylation data, achieving faster runtime and lower memory usage while maintaining accuracy.

Childhood adversity in mothers is associated with accelerated epigenetic aging in pregnancy and in male newborns

This study finds that maternal childhood adversity is linked to accelerated epigenetic aging in male newborns but not females, using multiple epigenetic clocks.

A Sparse Additive Model for High-Dimensional Interactions with an Exposure Variable

The paper introduces a method called sail to detect non-linear interactions between a key exposure variable and high-dimensional data, showing it outperforms existing methods in prediction and support recovery.

Internalizing Symptoms Associate with the Pace of Epigenetic Aging in Childhood

This study finds that internalizing symptoms in early childhood predict higher epigenetic age acceleration at age 6, which is linked to later internalizing symptoms.

Variably methylated regions in the newborn epigenome: environmental, genetic and combined influences

The paper examines how genetic and environmental factors influence DNA methylation at variably methylated regions in neonatal blood, finding that combined effects best explain methylation variability.

A biologically-informed polygenic score identifiesendophenotypes and clinical conditions associated with the insulinreceptor function on specific brain regions

The paper introduces a biologically informed polygenic score for insulin receptor-related genes in mesocorticolimbic regions and shows it better predicts childhood impulsivity and early addiction risk than conventional scores.

PRS-on-Spark: a novel, efficient and flexible approach for generating polygenic risk scores

PRS-on-Spark generates polygenic risk scores efficiently, supporting diverse data inputs and improving variance explained for major depression.