Morgan E. Levine

This paper investigates how APOEe4 influences molecular changes in Alzheimer's disease through proteomic, epigenetic, and genetic analyses of post-mortem brain samples, identifying key proteins and epigenetic markers associated with risk and resilience.

The paper develops 11 system-specific methylation clocks from blood samples to quantify aging heterogeneity across physiological systems and identifies aging subtypes with distinct disease patterns.

The paper identifies and characterizes age-invariant genes across multiple tissues in mice, finding they are stable across the lifespan and have distinct molecular features.

The paper analyzes DNA methylation patterns across aging, (de)differentiation, and reprogramming to identify shared and distinct signals.

This study improves the reliability of stochastic epigenetic mutations (SEMs) by filtering technical noise and identifies their associations with cardiovascular disease and aging.

The paper introduces the EN-TEx resource, which provides personal epigenomes and variant-impact models across multiple tissues, revealing allele-specific loci and their associations with GWAS loci.

The paper develops PCBrainAge, an epigenetic age predictor for brain tissue, showing it better captures aging heterogeneity and links to Alzheimer's disease features than existing methods.

This paper introduces a computational method to improve the reliability of epigenetic clocks by using principal component analysis, showing reduced technical noise and better performance in longitudinal studies.

methylCIPHER is a local R package providing standardized epigenetic clock calculation, clock-selection helpers, and missing-CpG imputation assessment, showing that many clocks produce highly correlated outputs despite non-overlapping CpGs.

Clustering 5,717 clock CpGs into twelve modules shows that different epigenetic clocks mix those modules in different proportions, and that reprogramming rejuvenates only some of them.

This study identifies genetic associations for two biological age measures, revealing distinct aging phenotypes linked to different pathways and APOE variants.

This study compares 11 epigenetic aging clocks using DNA methylation data from human tissues and cells, finding differences in CpG characteristics, tissue specificity, and gene network associations.

This paper develops a rat epigenetic clock (DNAmAge) that correlates with age and phenotypic aging, and identifies histone modifications linked to its signal.

This paper develops a DNA methylation biomarker, DNAmSen, to measure cellular senescence and shows its correlation with age and age-related diseases.

This study identifies genetic variants associated with epigenetic age acceleration and shows TERT's role in regulating the DNA methylation clock.