Controlling for baseline telomere length biases estimates of the rate of telomere attrition.

Preprint, Supplementary Material, associated R script and dataset.

Abstract

Background

Longitudinal studies have an important role in telomere epidemiology. In analysing effects of exposures on change in leukocyte telomere length (LTL), it is common to control for baseline LTL. However, collider bias arising from measurement error could cause overestimation of the difference in LTL attrition between groups with different exposures. We evaluated this using smoking as a test case.

Methods

We simulated LTL data to ask whether controlling for baseline LTL biases estimates of the difference in LTL attrition between smokers and non-smokers. We tested predictions from our simulation in a meta-analysis of previously-published longitudinal cohorts.

Results

Our simulations show that if baseline LTL is shorter in smokers and LTL measurement error is non-zero, then controlling for baseline LTL overestimates the difference in LTL attrition between smokers and non-smokers. The size of this bias increases synergistically with increasing baseline difference and increasing LTL measurement error. Supporting these simulation results, the estimated difference in LTL attrition between smokers and non-smokers in empirical data is greater when models control for baseline LTL and the size of this discrepancy is positively correlated with LTL measurement error.

Conclusions

The false-positive error rate for reports of effects of smoking on telomere attrition is likely to exceed 5%. The bias responsible is not specific to smoking and will affect all exposures for which baseline differences in LTL exist. To avoid bias, models of LTL attrition should not control for baseline LTL. Many claims of accelerated LTL attrition in individuals exposed to adversity need to be re-assessed.