Circulating epigenetic signatures classifying brain insulin resistance in humans.

Abstract

Brain insulin action plays an important role in metabolic and cognitive health, but there is no biomarker available to assess brain insulin resistance in humans. Here, we developed a machine learning framework based on blood DNA methylation profiles of participants who did not have type 2 diabetes with and without brain insulin resistance and detailed metabolic phenotyping. We identified 540 DNA methylation sites (CpGs) as classifiers of brain insulin resistance in a discovery cohort (<i>n</i> = 167), results that were validated in two replication cohorts (<i>n</i> = 33 and 24) with high accuracy (83 to 94%). All 540 CpGs were differentially methylated and annotated to 445 genes mapping to neuronal development and axonogenesis processes. Methylation patterns of 98 of 540 CpGs exhibited a strong and significant (<i>P</i> < 0.05) blood-brain correlation, indicating that blood cells are a reliable proxy to capture brain-specific DNA methylation changes. These blood-based epigenetic signatures could potentially serve in the future for the early detection of individuals with brain insulin resistance in a broad clinical setting.