New research, presented at the European College of Neuropsychopharmacology's Virtual Congress, has shown depression can be detected by monitoring fluctuations in a person's heart rate over a 24-hour period. The small, proof-of-concept study certainly needs more verification but it promisingly points to a novel biomarker that could be easily integrated into patient monitoring systems.
A small body of recent research has identified a compelling link between depression and heart rate variability. Of course, a huge number of factors influence a person’s heart rate, so it has been challenging to home in on this novel association.
This new study set out to investigate the association by recruiting 16 subjects with treatment-resistant major depressive disorder (MDD). The small cohort was matched with 16 healthy controls and the entire group was initially tracked for four days, with a small wearable device continually recording heart rate data.
“We found that those with depression had both a higher baseline heart rate, and a lower heart rate variation, as we expected,” says Carmen Schiweck, lead researcher on the project, from Goethe University. “On average we saw that depressed patients had a heart rate which was roughly 10 to 15 beats per minute higher than in controls.”
Leveraging recent research highlighting the impressively rapid anti-depressant qualities of ketamine, the cohort was then administered either a placebo or a single ketamine treatment. Schiweck suggests this allowed the researchers to observe a nearly instant improvement in depressive symptoms and correlate this with the heart rate observations.
“After treatment, we again measured the heart rates and found that both the rate and the heart rate fluctuation of the previously depressed patients had changed to be closer to those found in the controls,” says Schiweck.
The final part of the study was to test a computerized classification system and find out whether the depressed subjects could be identified from the healthy controls solely based on heart rate data. The temporal heart rate data proved most effective in identifying those depressed subjects.
“Normally heart rates are higher during the day and lower during the night,” explains Schiweck. “Interestingly, it seems that the drop in heart rate during the night is impaired in depression. This seems to be a way of identifying patients who are at risk to develop depression or to relapse.”
Just using heart rate data records, the system could correctly identify 15 of 16 control subjects and 14 of 16 patients with depression. Higher resting heart rate also correlated with those depressed patients more likely to positively respond to ketamine treatment. This suggests the biomarker may be useful in classifying those patients with depression who would most benefit from ketamine treatment.
“Put simply, our pilot study suggests that by just measuring your heart rate for 24 hours, we can tell with 90 percent accuracy if a person is currently depressed or not,” concludes Schiweck.
The research is not yet peer-reviewed or published in a journal, and Schiweck is cautious to stress the study is preliminary and needs larger validation in diverse patient populations. However, the implications of the work are compelling.
If validated, this kind of biomarker, easily measurable through many currently available wearable devices, could be incorporated into health-monitoring apps to serve as an “early warning” sign of depression. The biomarker could also be used to monitor the efficacy of a given treatment, as well as help determine which treatments would be best for a specific patient.
The research was presented recently at the 33rd ECNP Virtual Congress.
