PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Inferring a measure of physiological age from multiple ageing related phenotypes
David Knowles, Leopold Parts, Daniel Glass and John Winn
In: NIPS 2011 Workshop: From Statistical Genetics to Predictive Models in Personalized Medicine(2011).

Abstract

What is ageing? One definition is simultaneous degradation of multiple organ systems. Can an individual be said to be "old" or "young" for their (chronological) age in a scientifically meaningful way? We investigate these questions using ageing related phenotypes measured on the 12,000 female twins in the Twins UK study. We propose a simple linear model of ageing, which allows a latent adjustment to be made to an individual's chronological age to give her "physiological age", shared across the observed phenotypes. We note problems with the analysis resulting from the linearity assumption and show how to alleviate these issues using a non-linear extension. We find more gene expression probes are significantly associated with our measurement of physiological age than to chronological age.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:8460
Deposited By:David Knowles
Deposited On:19 January 2012