Case Study 5: Eight Years of Antidepressant Failure — Until the Treatment Strategy Changed

Reason to come to PPI: The medications were being processed normally, but the patient’s brain chemistry told a different story.

A patient came to Personalized Prescribing after struggling with depression for approximately eight years.

During that time, the patient had tried several antidepressants, including SSRIs and SNRIs.

The medications were taken appropriately, but the patient experienced little meaningful improvement.

After years of unsuccessful treatment, the patient wanted to understand: Why were so many antidepressants failing?

PPI First Looked at Medication Metabolism

Many pharmacogenomic tests focus mainly on liver enzymes such as:

• CYP2D6
• CYP2C19 and other enzymes that determine how quickly antidepressants are processed.

PPI testing showed that the patient’s relevant liver enzymes were functioning as expected.

In simple terms:

1. The medications were reaching the body
2. The body was processing them normally
3. There was no major metabolism problem to explain eight years of antidepressant failure.

If the patient had received a pharmacogenomic test that looked mainly at liver enzymes, the result might simply have shown: “Normal metabolism.”

But that did not explain the patient’s experience.

PPI Looked at the Brain Pathways the Medications Were Trying to Affect

PPI’s assessment also examined genes involved in:

• Serotonin production and regulation
• Serotonin transport
• Serotonin breakdown
• Dopamine regulation
• Norepinephrine regulation Several findings stood out.

HTR1A — A Strong Serotonin “Brake”

The patient had a genetic pattern associated with higher activity of the serotonin 5-HT1A autoreceptor. The autoreceptor acts partly like a feedback brake. When serotonin begins to rise:

1. Serotonin activates the autoreceptor
2. The autoreceptor signals the nerve cell to reduce further serotonin release
3. Serotonin output is restrained

For this patient, the stronger autoreceptor signal suggested that increasing serotonin through a conventional SSRI mechanism might not produce the same effect as it would in someone with weaker feedback inhibition.

SLC6A4 — Lower Serotonin Transporter Activity

The patient also had a genetic pattern associated with lower activity of the serotonin transporter, produced by the SLC6A4 gene. This was important because the serotonin transporter is the main target of SSRIs. SSRIs work primarily by blocking this transporter.

A simplified picture is:

1. SSRI
2. Blocks serotonin transporter
3. More serotonin remains available between brain cells

But if the transporter system is already functioning differently, blocking it may produce a different biological effect.

The combination of: strong autoreceptor regulation and lower transporter activity suggested that a traditional serotonin-reuptake strategy might be a less favorable fit for this patient.

MAOA — Serotonin and Norepinephrine Were Being Broken Down More Quickly

Another important finding involved MAOA**.** MAO-A is an enzyme that helps break down:

• Serotonin
• Norepinephrine
• Dopamine (lesser extend) The patient’s genetic profile suggested higher MAO-A activity.

A simple way to think about it is:

1. Brain chemicals are produced
2. MAO-A helps break them down
3. Higher MAO-A activity may increase breakdown
4. Less neurotransmitter signaling may remain available

This suggested that the patient’s inherited biology might favour lower functional availability of serotonin and norepinephrine.

COMT — Another Clue About Dopamine and Norepinephrine

The patient also had a genetic pattern associated with higher COMT activity. COMT is another enzyme involved in breaking down catecholamines, particularly:

• Dopamine
• Norepinephrine In the prefrontal cortex, COMT is especially important for controlling dopamine availability.

Higher COMT activity may therefore contribute to relatively lower dopamine signaling in areas involved in:

• Motivation
• Energy
• Concentration
• Planning
• Mental effort

The Whole Pattern Was More Important Than Any One Gene

None of these findings alone could explain eight years of treatment failure. But taken together, they suggested a broader pattern. The patient appeared to have:

• Strong serotonin autoreceptor braking
• Lower serotonin transporter activity
• Higher MAO-A activity
• Higher COMT activity A possible inherited tendency toward lower monoamine pathway capacity In other words, the patient’s biology suggested that simply preventing serotonin or norepinephrine from being taken back up might not be enough.

The problem might also involve how much neurotransmitter was available in the first place

and: how quickly it was being broken down.

Why SSRIs and SNRIs May Have Been Insufficient

SSRIs and SNRIs mainly work by preventing serotonin and/or norepinephrine from being recycled too quickly.

They do not directly create serotonin, dopamine or norepinephrine.

A simple way to think about this patient’s situation is:

• Relatively limited neurotransmitter availability
• Faster enzymatic breakdown
• Strong serotonin feedback inhibition Reuptake inhibition alone may have been insufficient This provided a possible explanation for why several SSRIs and SNRIs had produced little benefit despite normal liver metabolism.

A Different Treatment Strategy

The PPI pharmacist recommended discussing Moclobemide with the patient’s treating clinician.

Moclobemide works very differently from an SSRI or SNRI. It is a Reversible inhibitor of monoamine oxidase A — RIMA

Instead of mainly blocking the reuptake of neurotransmitters, moclobemide temporarily reduces the activity of MAO-A, the enzyme that breaks down serotonin, norepinephrine and dopamine.

The treatment strategy therefore shifted from: “Keep serotonin in the synapse longer” to:

“Reduce the breakdown of several important neurotransmitters.”

For this patient’s genetic and clinical pattern, that represented a very different mechanism.

What Happened?

The treating clinician implemented the medication change. PPI followed up with the patient approximately four months late.

The patient reported that the medication was working.

They experienced:

• Meaningful symptom relief
• Improved overall wellbeing
• A significant improvement compared with their previous antidepressant treatments After approximately eight years of unsuccessful medication trials, the patient finally reported that treatment was helping.

Why This Case Matters

This case demonstrates an important limitation of pharmacogenomic testing that focuses only on: “Can the liver process the medication?”

For this patient, the answer was: Yes.

But normal metabolism did not mean the medication mechanism was necessarily the best biological fit.

PPI also considered:

• Medication metabolism
• Serotonin transport
• Serotonin autoreceptor regulation
• Neurotransmitter breakdown
• Dopamine and norepinephrine pathways
• Eight years of treatment history A different treatment strategy emerged

The Bigger Lesson

A patient can have perfectly normal:

• CYP2D6
• CYP2C19 and still experience repeated antidepressant failure.

Why?

Because medication response involves more than getting the correct amount of drug into the bloodstream.

The medication must also act on a biological system capable of responding to its mechanism.

The Takeaway

For this patient: Normal liver metabolism did not mean normal antidepressant response.

The broader genetic pattern suggested possible vulnerabilities affecting:

• Serotonin
• Dopamine
• Norepinephrine rather than a problem with drug metabolism itself.

That information helped the pharmacist consider a medication with a different and broader mechanism of action, rather than continuing to repeat similar SSRI or SNRI strategies.

Important Note

This individual case does not mean that HTR1A, SLC6A4, MAOA or COMT results can independently predict antidepressant failure, nor does it mean moclobemide is appropriate for everyone with similar genetic findings.

PPI does not directly measure a person’s serotonin, dopamine or norepinephrine levels. These genetic findings are better described as inherited tendencies that may influence neurotransmitter pathways.

Evidence for many pharmacodynamic genes is still developing. PPI therefore considers multiple genes together with symptoms, previous medication response, pharmacokinetics and clinical judgment rather than using any single genetic result as a stand-alone prescribing rule.