A BBC report of a new study by sleep researchers suggests that night shift workers have higher risk of various health problems than do we daytime doodlers; heart attacks, cancers and type 2 diabetes. This is because the expression patterns of many genes are based on the day-night cycle, and the 'chrono-chaos' of night work upsets lots of body functions, the story says.
The study, published in the Proceedings of the National Academy of Sciences, found that mistimed sleep caused gene expression to fall significantly. Genes affected included those having to do with circadian rhythms, or the maintenance of our sleep/wake cycles.
One can't be totally surprised, although one might expect that the graveyarders would get used to their diurnal cycle and do just fine. One has to wonder if there are other things about who chooses to do night work, or doesn't have options, so that nightshifting is a consequence rather than cause. In that case, nightshifting would be a confounder relative to the health implications rather than their cause.
The point here is rather just a brief one, that we and many others have repeatedly made. If these types of variables are not known or taken into account, or there isn't enough of this risk factor detectable in the study sample, then attributions of causation of what is measured will be inaccurate of misleading. This is one of the challenges of epidemiological research, including the search for reliable risk factors in the genome.
Then there is the question, related to an earlier point above, whether any genetic risk factors lead the bearer to look for nightwork and hence appear to be associated with some health result only indirectly. What about variants in the chrono-genes? Many such questions come to mind.
Maybe, therefore, the chrono-chaos is a different form of informational and inferential disorder. A disorder of incorrectly done studies. As we know, many results of association studies, genetic or otherwise, are not confirmed by attempts to replicate them (and here we're not referring to the notorious failure to report negative results, which exacerbates the problem). We don't know if the 'fault' is in the study design, the claimed finding of the first study, other biases, or just bad statistical luck.
A piece in Monday's New York Times laments the high fraction of scientific results that are not replicable. This topic has not gone unnoticed; we've written about different reasons for nonreplicability over the years ourselves. The degree of
confidence in each report as it comes out is thus surprising, unless one
thinks in terms of careerism, a 24/7 news cycle and so on.