I measured my lipids every hour for 15 hours: here’s what I saw.

-Azure Grant

Now this is just preliminary data — we’ll be collecting similar timeseries for others in our test group — but it has me very excited about what we have the opportunity to learn.

Hourly timeseries of lipid data under normal living conditions are very hard to find. Most research articles take a few measurements over the course of an intervention (Say, a baseline fasting measurement, a midpoint measurement, and and endpoint measurement in a dietary adjustment experiment). Then, the results are averaged over the study population, and reported — often with error bars larger than the size of a small but statistically significant effect.

Access to what happens on an individual-by-individual basis is slim, and using high temporal resolution measurements to really look at what’s going on across a day or more seems to be a low priority.

So why did I do this? First, it’s downright cool. Not only did my lipids change a lot during the day (50 mg/dL- enough to take me into a different CVD risk category), but they didn’t change randomly. They responded to the meals I ate, and seemed to have an ~ 3 h oscillation over the course of the day. And the timing of the gradual rise of both metrics across the day matched the timing expected for circadian variability in lipids, as measured by one of the only studies to examine this in humans(Singh et al., 2016).

But…Why tho?

Yes, I have a pet interest in biological rhythms. I studied them in undergraduate and will continue to do so in grad school. BUT, it has taught me to see periodic temporal structure in biological outputs as hugely informative about the health and stability of internal systems.There is value in periodic biological time series for predicting onset of illness, identifying pregnancy within hours of conception, monitoring mental health and much more. The power of high temporal resolution data has not yet been applied to one of the foremost diagnostic metrics of cardiovascular health: the lipid panel.

So exploring the power of high temporal resolution data in blood lipids seems a logical extension of the fact that our biological outputs vary periodically — and that therefore any measurement makes much more sense in context of the (rough) sine wave it sits on.

More examples to come soon.