Mar 09 2023

Anxiety Biomarkers

Psychiatry, psychology, and all aspects of mental health are a challenging area because the clinical entities we are dealing with are complex and mostly subjective. Diagnoses are perhaps best understood as clinical constructs – a way of identifying and understanding a mental health issue, but not necessary a core neurological phenomenon. In other words, things like bipolar disorder are identified, categorized, and diagnosed based upon a list of clinical signs and symptoms. But this is a descriptive approach, and may not correlate to specific circuitry in the brain. Researchers are making progress finding the “neuroanatomical correlates” of known clinical entities, but such correlates are mostly partial and statistical. Further, there is culture, personality, and environment to deal with, which significantly influences how underlying brain circuitry manifests clinically. Also, not all mental health diagnoses are equal – some are likely to be a lot closer to discrete brain circuitry than others.

With all of these challenges, researchers are still trying to progress mental health from a purely descriptive endeavor to a more biological approach, where appropriate. There are a number of ways to do this. The most obvious is to look at the brain itself. Such imaging can be anatomical (taking a picture of the physical anatomy of the brain, such as a CT scan or MRI scan) or functional (looking at some functional aspect of the brain, like EEG or functional MRI). This kind of research is producing a steady stream of information, finding correlations with mental health disorder states, but few have progressed to the point that they are clinically useful. To be useful for research all we need is sufficient statistical significance. But to be useful clinically, to actually determine how to treat an individual person, you need sufficient accuracy (sensitivity and specificity) to guide treatment decisions. That requires much more accuracy than just basic research.

There is also another biological way of evaluating mental health states – molecular biomarkers. This approach stems from the fact that every cell in the body activates a different set of genes – so brain cells activate brain genes, while liver cells activate liver cells. Also, one type of cell will activate genes at different intensities during different functions. So when the pancreas needs to create a lot of insulin, the insulin genes become more active. We can detect the RNA that is produced when specific genes are activated, or patterns of RNA when suites of genes are activated. This can be a biomarker signature of specific functional states.

So – can this approach be applied to mental health? A recent study looks to do just that, focusing on anxiety. Anxiety is a good condition to look at because it is perhaps one of the mental health states with the best neuroanatomical correlates. We have a pretty good handle on the anxiety circuitry – “bed nucleus of the stria terminalis, the amgydala, and the hippocampus, as well as their connectivity to cortical regions such as dorsal medial and lateral prefrontal/cingulate cortex and insula…”. Also, anxiety is a pretty specific and consistent mental health phenomenon. Further still, anxiety is the most common mental health symptom. Anxiety is therefore likely the low-hanging fruit of molecular psychiatry.

The current study took a multi-step approach, which seems to me to be very logical and careful. First they looked at people with anxiety during calm and anxious states, took blood samples, and then looked for molecular correlates of anxiety. This was the “discovery” phase. I see many preliminary studies that stop here, which is fine if it is a preliminary study meant to lead to further research. But often such “discovery” results are then used to promote products or claims. I like the fact that these researchers combined multiple phases into one study – that’s the way to do it, in my opinion. The next phase was the prioritization phase, they looked at all their candidate RNA biomarkers and decided which ones make the most sense based upon what we now about the neuroscience of anxiety.

They then did a validation stage with a fresh cohort of patients. I love this – an internal control with fresh data. They looked at subjects with anxiety and tested their blood for the candidate markers during low and high anxiety states. They then did a fourth and final stage where they tested their validated markers for clinical utility – again, nice to see. Did these markers predict risk of future anxiety or hospitalization?

If nothing else, I love this study for modeling the way such research should be done. Rather than break this up into four or more studies, they included the necessary steps all in one publication. This way, if what is being studied craps out at a later stage, the overall research is published as negative. This avoids the problem of so much positive preliminary research that does not hold up under the later stages of research, but by then has already influenced practice.

In the end the researchers found molecular biomarkers that correlate with anxiety states, make sense from a basic science approach, were validated with a fresh cohort of subjects, and were found to have clinical utility in terms of predicting later risk of anxiety. Still – this is one study, and the whole approach of molecular psychiatry is very complex. Independent verification, and further exploration of clinical utility are warranted. But this is a solid step.

The effects of research like this is not just to develop a blood test for anxiety. Mental health conditions still need to be diagnosed with clinical signs and symptoms. But this can help practitioners interpret complex presentations – patients with multiple varying symptoms. What is driving their overall symptom complex? Further, the researchers propose that such tests can be used to help match patients with the medication that is most likely to help them. If you have an elevated biomarker that is targeted by drug A but not drug B, then perhaps drug A is more likely to work for you. This is the kind of application that needs to be validated with later research. The idea here is not so much to have blood tests for diagnosis, but to use biomarkers for personalized treatment.

I hope to see more research like this (and I’m confident we will) – both because of the potential of molecular biomarkers to evaluate brain function and activity (or any organ function), and because research that includes multiple steps of internal controls should become the standard.


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