Depression blood test could lead to personalised treatments

“UK scientists have developed a blood test to help doctors pick the best drug for patients with depression,” BBC News reports, somewhat prematurely.

It is currently unproven whether such a test, based on measuring inflammation, would improve treatment outcomes.

Previous research has suggested high levels of inflammation – which is not just a reaction to infection, but can also be caused by stress – may impair the beneficial effects of antidepressants.

Researchers screened blood samples from people with depression who had, and had not, responded well to antidepressant medicines in the hope of identifying molecules associated with inflammation and drug response.

They then used this information for a second group to see if they could predict who would and wouldn’t respond to treatment with antidepressants.

A significant proportion of people were correctly identified as responders and non-responders, which is a big step forward compared with current practices.

But the test also missed 39-43% of non-responders, meaning they would continue to receive antidepressant treatment that is unlikely to work for them.

One of the study’s limitations is its size. It was based on less than 200 people with depression, not nearly enough to draw any concrete conclusions about whether it works well in most people with depression.

The study also only looked at drug treatments, and did not assess talking therapies such as cognitive behavioural therapy.

This approach certainly seems to be a step in the right direction, but it needs refinement before personalised treatments for depression can be practised with confidence.

Where did the story come from?

The study was led by researchers from King’s College London in the UK.

It was funded by the Medical Research Council, South London and Maudsley NHS Foundation Trust, King’s College London, and the European Commission.

One of the study authors declared a potential conflict of interest, having received funding from Johnson & Johnson for research into depression and inflammation, as well as speaker fees for Lundbeck.

They have also received research funding from a large consortia, which included Johnson & Johnson, GSK, Pfizer and Lundbeck.

The study was published in the peer-reviewed International Journal of Neuropsychopharmacology.

The research is open access, so it is free to read online or download as a PDF.

The UK media’s coverage was generally accurate, but there was some room for improvement.

Describing current depression treatment as “trial and error” (The Daily Telegraph and BBC News) is perhaps unfair on doctors and patients, who are attempting to jointly work out the best way to treat a serious condition with the options at their disposal.

For example, doctors usually prescribe the least powerful antidepressant available that is the least likely to lead to troublesome side effects, given the person’s current and past medical history.

However, the reporting does touch on the uncertainty this treatment approach currently involves, which the new approach hopes to improve.

Also, some of the tone of the BBC’s reporting could give the impression that this blood test had led to proven successes in terms of improved outcomes, which is currently not the case.

What kind of research was this?

This laboratory study looked to develop a way of classifying people with depression into those likely or unlikely to respond to commonly used antidepressant medicines.

The research team says higher inflammation levels have been linked to poorer responses to antidepressants in several studies.

But researchers hadn’t yet developed accurate or reliable ways to predict who would benefit from antidepressants, and who wouldn’t, so they could try a different type of drug or a non-drug treatment.

Part of the problem is we don’t fully understand the biology of depression, making it difficult to know which molecules or processes to target to develop a predictive test.

What did the research involve?

Researchers screened blood samples from people with depression who had, and had not, responded well to antidepressant medicines in the hope of identifying molecules that could distinguish the two groups.

The researchers didn’t measure these molecules directly. Instead, they counted up the number of messenger RNA (mRNA) molecules in the blood – small strands of genetic material that carry instructions to build many biological molecules.

This, they said, gave a reliable and accurate measure of the levels of the immune messengers, and had the added benefit of being able to be detected accurately and reliably by a simple blood test sent to the lab.

Seventy-four people with major depression (at least moderate severity), most of whom were in their second episode of depression, had their mRNA analysed to identify potential predictive molecules, as well as cut-off points for responders and non-responders.

These people came from a randomised controlled trial comparing 12 weeks of treatment with the antidepressants escitalopram (a selective serotonin reuptake inhibitor, usually the first choice class of antidepressant) and nortriptyline (a tricyclic antidepressant, or TCA, an older class of antidepressant), so their response to these medicines was known.

Response was defined as a greater than 50% reduction in score on a standard depression rating scale (the Montgomery-Åsberg Depression Rating Scale, MADRS).

To make sure these initial test cut-offs were accurate, the researchers tested them in a second validation sample of 68 people with depression using the same methods to detect responders.

This group had only recently started to take antidepressants and took a wider range, including:

• escitalopram (SSRI)
• paroxetine (SSRI)
• duloxetine (serotonin and noradrenaline reuptake inhibitors, SNRI)
• venlafaxine (SNRI)
• amitriptyline (TCA)
• desipramine (a TCA not licensed in the UK)

Patients were excluded from this part of the investigation if they were taking antipsychotics or mood stabilising medication.

The main analysis quantified the accuracy of the newly developed test to identify responders and non-responders to antidepressant medicines.

This included taking into account background differences in mRNA expression, which varies naturally from person to person.

What were the basic results?

Across the two studies, between 66% and 69% of patients responded to antidepressants.

Researchers identified mRNA linked to macrophage migration inhibitory factor and interleukin-1ß as the most useful to identify responders and non-responders.

Using their first group of patients, the test found:

• 100% of those classified as non-responders were true non-responders (positive predictive value 100%, 14 of 14) – in other words a positive test result is 100% accurate
• 100% of responders were correctly identified as being responders (specificity 100%, 51 of 51), meaning nobody on effective treatment would be unnecessarily “stepped up” to more advanced treatment
• about 22% of the group were identified as “intermediates”, meaning they weren’t responders or non-responders – they fell in the middle
• the test missed 39% of non-responders, falsely categorising them as responders (negative predictive value 85%) – a negative test result is only 85% accurate; this group would continue to receive standard antidepressant treatment that is unlikely to work for them

Results were very similar in the second group. The top two measures remained at 100% and the test missed 43% of non-responders, falsely categorising them as responders (negative predictive value 82%). Around 38% were classified as intermediates.

The researchers found background levels of mRNA made little difference to the test accuracy. All that mattered was the absolute amount of mRNA for macrophage migration inhibitory factor and interleukin-1ß.

How did the researchers interpret the results?

The researchers concluded that, “The absolute numbers of MIF [macrophage migration inhibitory factor] and IL-1β [interleukin-1ß] mRNA molecules are both accurate and reliable predictors of antidepressant response, identifying, for the first time, an mRNA-based biomarker approach that is independent from local experimental settings and does not require ‘relative’ quantification using housekeeping genes.”

Conclusion

This study shows how a new blood test in development can help identify people with depression who are most and least likely to benefit from antidepressants.

While promising, the test is far from perfect. For example, it missed 39-43% of non-responders, meaning these people would continue to receive standard antidepressant treatment that is unlikely to work for them.

A large proportion of patients (22-38%) also fell into the “intermediate” group who were neither responders nor non-responders, so the test wasn’t too useful here.

This means there is a significant proportion of people with depression who would not necessarily benefit from this test.

However, we shouldn’t be overly negative. A significant proportion of people were identified correctly as responders and non-responders, which is a big step forward on what happens today.

The study was based on less than 200 people with depression, far too few to conclude whether it works well in most people with depression.

Larger studies involving many hundreds, perhaps thousands, of people will be needed to establish this, and is the natural next step for this research.  

Links To The Headlines

New blood test targets depression. BBC News, June 7 2016

Blood test could identify people who will respond to antidepressants. The Guardian, June 7 2016

Simple blood test could stop doctors using ‘trial and error’ to prescribe antidepressants, scientists claim. The Daily Telegraph, June 7 2016

Depression patients ‘could get personalised treatment thanks to new blood test’. Mail Online, June 7 2016

Links To Science

Cattaneo A, Ferrari C, Uher R, et al. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients. International Journal of Neuropsychopharmacology. Published online May 11 2016