When it comes to diagnosing physical illnesses, there are a myriad of different biological tests that can be done to correctly diagnose the condition. Take for example, hypertension (otherwise known as high blood pressure), after carrying out some simple biological tests such as a blood pressure reading, it is possible to diagnose the patient and provide the correct treatment.
These measurable medical signs that provide an objective way to indicate an illness or condition are also known as biomarkers. There has been a huge focus in recent years to find an equivalent measure, or biomarker, for diagnosing and monitoring mental health disorders with the hope of preventing, improving diagnosis and monitoring mental illness.
The problem? There is a lack of reliable and broadly accessible biological measures to accurately diagnose mental illness.
Introducing… heart rate variability
Heart rate variability is the small variations in the amount of time between each heartbeat. This measure, which can be obtained through an electrocardiogram otherwise known as an ECG (a simple test that can be used to check your heart’s rhythm and electrical activity), has been put forward as a promising and exciting candidate for helping to diagnose and monitor symptoms of common mental health conditions such as depression and anxiety.
I am a Researcher at King’s College London and as part of my work I have been investigating how heart rate variability could be a useful tool in mental healthcare practices. In this blog, I will give you an overview of what heart rate variability is and share some of the evidence which suggests heart rate variability might be a promising candidate as a biomarker for psychiatric illnesses such as depression and anxiety.
What is Heart Rate Variability?
Heart rate variability or, HRV, is the fluctuation in time intervals between each consecutive heartbeat. These variations are controlled by the autonomic nervous system, an important component of the body’s nervous system, in charge of regulating involuntary processes like heart rate, blood pressure, breathing, digestion, and emotional response.
The autonomic nervous system is made up of two components, the sympathetic branch which prepares the body for stressful or emergency situations — ‘fight or flight’, and the parasympathetic branch which controls bodily processes and dominates during quiet, resting conditions — ‘rest and digest’.
High HRV reflects the autonomic nervous system’s ability efficiently adapt to the demands of the environment by effectively switching between the sympathetic ‘fight and flight’ and the parasympathetic ‘rest and digest’ modes. Insufficient or low HRV, on the other hand, suggests a reduced ability to switch between these two modes and respond effectively to environmental and psychological stress.
Given the importance of the autonomic nervous system in regulating emotion, it is not surprising that dysregulation of this important biological system measured through HRV, is associated with reduced emotional wellbeing and mental health problems such as depression.
So, is there a link between HRV and depression?
So far, strong evidence has emerged for a link between depression and HRV. Findings from a meta-analysis (a method through which the results from many studies are pooled together) which compared 2250 patients with depression with 1982 healthy controls (i.e., those without depression), demonstrated that in comparison to those without, those with depression had significantly lower HRV.
In another meta-analysis, results were taken from 18 different studies which looked at whether the severity of depressive symptoms were relative to the degree of HRV reduction. In total 673 depressed participants and 407 healthy controls were included and found that overall, the more severe patient’s symptoms were the lower their HRV was found to be.
Further studies have shown evidence that HRV could even be used to help predict later development of depression. One study investigated whether HRV measured at an earlier time point was associated with later depressive symptoms. Participant’s HRV and depressive symptoms were measured at visit one and then seven years later at visit two. It was found that lower HRV at visit one was associated with increased depressive symptoms at visit two, seven years later.
The findings from this study were particularly interesting as they allow us to understand more about the direction of the relationship between HRV and depression. In other words, it shed some light on whether reduced HRV came before or after the development of depression. Overall, there was stronger evidence that reduced HRV was present before the onset of depression, rather than occuring as a consequence of having depression.
So, could HRV be useful in real world settings for depression?
There are many promising ways HRV could be used in real world clinical settings for depression. One of the key ways that HRV could be used is to help identify those who are at risk of developing depression. Several studies have suggested that reduced HRV is a risk factor for the development of depression. If we can clearly understand the HRV patterns that are associated with the development of depression, it may be possible to identify those at risk at an earlier stage and prevent the onset of depression by providing treatment and intervening earlier.
Encouraging evidence suggests HRV could also be used in clinical settings to decide the best treatment option for patients with depression. One study found that measures of pre-treatment HRV (i.e., HRV before patients received any treatment) could predict whether patient’s symptoms improved after taking antidepressant medication when considering the type of symptoms patients were experiencing. Often patients will have to try several types of treatments before they find the one that works for them. Excitingly, these findings suggest HRV could be used to find the correct treatment more quickly without patients having to go through a long and often frustrating trial and error process.
However, although findings so far are promising, the number of participants included in previous studies have been relatively small. Further studies require larger sample sizes and more representative samples (for example, participants from wider age ranges and different ethnicities) in order for the conclusions to be applied to the general population. In addition, there is a limited number of prospective studies which follow participants from before they develop depression to illness onset. These types of longitudinal studies are important to understand whether HRV and more specifcally, what HRV patterns are an indication of risk for depression onset.
Despite the need for more research on HRV and depression, and how HRV could be utilised in clinical settings for depression, the evidence so far, which clearly demonstrates the importance of HRV in depression, is exciting for future clinical care.
Who knows, just as some of us use blood pressure monitors routinely to check our blood pressure, we may find ourselves routinely checking our HRV for helping to monitor our mental health.