Determinants of accelerated metabolomic and epigenetic ageing in a UK cohort

Abstract

<jats:title>Abstract</jats:title><jats:p>Markers of biological ageing have potential utility in primary care and public health. We developed an elastic net regression model of age based on untargeted metabolic profiling across multiple platforms, including nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry in urine and serum (almost 100,000 features assayed), within a large sample (N=2,239) from the UK occupational Airwave cohort. We investigated the determinants of accelerated ageing, including genetic, lifestyle and psychological risk factors for premature mortality. The metabolomic age model was well correlated with chronological age (r=0.85 in independent test set). Increased metabolomic age acceleration (mAA) was associated (p&lt;0.0025) with overweight/obesity and depression and nominally associated (p&lt;0.05) with high alcohol use and low income. DNA methylation age acceleration (N=1,102) was nominally associated (p&lt;0.05) with high alcohol use, anxiety and post-traumatic stress disorder, but not correlated with mAA. Biological age acceleration may present an important mechanism linking psycho-social stress to age-related disease.</jats:p>

Reducing Subspace Models for Large-Scale Covariance Regression

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