May 30, 2013

A probabilistic model of biological ageing of the lungs for analyzing the effects of smoking, asthma and COPD

Open Access
Research

A probabilistic model of biological ageing of the lungs for analyzing the effects of smoking, asthma and COPD

Silvia ChiappaJohn WinnAna VinuelaHannah Tipney and Timothy David Spector
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Respiratory Research 2013, 14:60 doi:10.1186/1465-9921-14-60
Published: 30 May 2013

Abstract (provisional)

Background

Although a large body of literature is available that describes the effects of factors such as smoking, asthma and COPD on lung function, characterizations over the entire adulthood and analysis of co-occurrence of factors are still rare due to the high number of measurements required for reliable estimation in current approaches. Such a fragmentation, together with the way the effects are expressed, makes it also often difficult to compare results from multiple studies. Furthermore, current approaches consider one type of measurement only or several types separately.

Methods

We propose a probabilistic model that expresses effects on lung function as number of years added to chronological age or, in other words, that estimates the biological age of the lungs. Using biological age as a measure of the effects has the advantage of facilitating the understanding of their severity and comparison of results. In our model, chronological age and other factors affecting the health status of the lungs generate biological age, which in turn generates lung function measurements. This structure enables the use of multiple types of measurement to obtain a more precise estimate of the effects and parameter sharing for characterization over large age ranges and of co-occurrence of factors with little data. We treat the parameters that model smoking habits and lung diseases as random variables to obtain uncertainty in the estimated effects.

Results

We use the model to investigate the effects of smoking, asthma and COPD on the TwinsUK Registry. We find that combination of smoking with lung disease(s) has higher effect than smoking or lung disease(s) alone. Furthermore, in smokers, co-occurence of asthma and COPD is more detrimental than asthma or COPD alone.

Conclusions

The proposed model or other models based on a similar approach could be of help in improving the understanding of factors affecting lung function by enabling characterizations over large age ranges and of co-occurrence of factors with little data and the use of multiple types of measurement. The software implementing the model can be downloaded at the first author's webpage.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.


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