Miina Ollikainen

The paper introduces the Proteomic Sex Index (PSI), a continuous measure of plasma proteome alignment with chromosomal sex, showing its association with health and disease traits.

This study identifies conserved ageing-associated genes in King penguins using methylome data and shows their relevance to human epigenetic age prediction.

The paper develops BEAC, an epigenetic clock for birds, validated across multiple species and showing strong predictive performance for chronological age.

This study examines how NR supplementation and HIIT affect skeletal muscle epigenetic aging, finding opposing effects on epigenetic age acceleration across different clocks.

This study conducts an epigenome-wide association study (EWAS) meta-analysis of wellbeing using DNA methylation data, finding no significant methylation sites but suggesting the need for larger studies.

This study explores proteomic and epigenetic aging clocks as biomarkers for Alzheimer's disease phenotypes, finding proteomic clocks improve explained variance in cognitive and biomarker measures by up to 18%.

The paper creates a DNA methylation aging atlas across 17 human tissues, identifying conserved and tissue-specific aging signatures and potential therapeutic targets.

The paper develops a proteomic signature (HPS) to predict healthspan, showing it predicts mortality and age-related diseases better than other biological age measures.

The paper estimates heritability for 2,321 plasma proteins using twin data and finds that SNP-based heritability accounts for only half of the total genetic effects.

The paper identifies a locus, SH3BP4, where DNA methylation correlates with mtDNAq and obesity-related traits in adipose tissue, suggesting potential causal relationships.

The paper identifies 40 multi-omic factors associated with epigenetic age acceleration in young twins, with six remaining significant after accounting for genetic effects, and finds some associations persist across generations in older twins.

The paper compares transcriptomic and metabolomic data from monozygotic and dizygotic twins to identify molecular biomarkers of twinning, finding no replicable transcript-level differences but highlighting potential pathways.

The paper identifies DNA methylation markers associated with breast cancer risk in twin pairs, showing most are independent of genetic effects and linked to environmental factors.

This study shows that sedentary life in zoo-housed King penguins accelerates epigenetic ageing, similar to humans, linked to methylation changes in metabolic and heart-related pathways.

This study finds that early childbearing, numerous pregnancies, and nulliparity are associated with accelerated aging and increased mortality risk in Finnish twin women.

This study integrates multi-OMIC data from 12 cohorts to identify exercise-specific molecular signatures and gene regulatory patterns in human skeletal muscle.

This study identifies DNA methylation sites associated with pubertal timing and development in young adults using twin data and examines their genetic and environmental influences.

This study shows exercise training reduces epigenetic and transcriptomic aging in human skeletal muscle, while muscle disuse accelerates transcriptomic aging.

The paper investigates the effects of alcohol exposure on placental DNA methylation and identifies DPPA4 as a candidate gene for alcohol-induced developmental disorders.

The paper examines nc886 methylation across populations and tissues, finding stable levels except in specific tissues and some discordance in dizygotic twins.

The paper examines the association between BMI and epigenetic aging in twin pairs, finding BMI increases are linked to accelerated epigenetic age using GrimAge.

The paper identifies genetic variants influencing DNA methylation in blood and shows their associations with complex traits and diseases, but finds limited direct causality.

This paper identifies DNA methylation sites associated with aggression through a meta-analysis of epigenome-wide studies across different age groups and tissues.

This study identifies 137 genome-wide significant loci associated with DNA methylation biomarkers of ageing using DNAm and SNP data from over 41,000 individuals.

The paper identifies DNA methylation differences in peripheral blood of Alzheimer’s disease discordant twin pairs, linking these to brain gene expression and neuronal functions.

The paper develops a machine learning classifier, EpiSmokEr, to predict smoking status from DNA methylation data, showing robust performance across multiple datasets and tissues.

This study identifies smoking-associated DNA methylation and gene expression changes in adipose tissue and links some to cardio-metabolic health outcomes.

This study investigates the association between CpG methylation and educational attainment, finding limited significant associations that may be influenced by confounding factors.