December 24, 2024 • Brooke Siem
Genetic Testing and the CYP450 Pathway, Part II: An analysis of my personal GeneSight results
In the 100th issue of Happiness Is A Skill, I revealed that I underwent genetic testing through GeneSight in order to get an insight into how my body metabolizes psychiatric drugs. My results are in, and we’re going to take a look at them together in order to better understand this technology, while also examining some of the limitations and concerns around this type of testing.
I recommend reading through issue 100 before diving in here.
Please note that I have no affiliation with GeneSight, and this is in no way an advertisement or medical advice.
Interpreting GeneSight Results
The GeneSight report focuses on three different aspects of psychiatric drug metabolism: psychotropic, which indicates how a person is likely to metabolize a wide variety of psychiatric drugs; genotype and phenotype, which is the organism’s genetic information and its observable traits; and a gene-drug interaction chart.
In theory, this information aims to optimize medication choices by reducing trial-and-error prescribing. Given that I’m not in the business of taking psychiatric drugs ever again, I’m more interested in the insight this gives me into my own body, and what it might mean for psychiatric drug withdrawal. Big emphasis on might. I won’t be running any double blind, placebo controlled trials on the hypothesis any time soon, but seeing this information and understanding what it means does make me think twice about blindly taking prescription drugs. Personally, I think that’s the power of a test like this. It shows the layperson that pharmaceutical intervention is extremely complicated, while also increasing the patient’s medical literacy. Given that on average, doctors only spend 17 minutes with each patient—and 4.5 hours per day on electronic medical records—it behooves the patient to have some basic medical literacy before walking into an appointment.
My Psychotropic Results
Genesight gives psychotropic results for five drug categories: antidepressants, anxiolytics and hypnotics (anti-anxiety and sedatives), antipsychotics, mood stabilizers, stimulants & non stimulants.
The results are coded in green (use as directed), yellow (moderate gene-drug interaction), and red (significant gene-drug interaction.)
Intuitively, you can gather that green medications are not associated with any known genetic issues that would be expected to change patient medication outcomes; yellow medications may require dose adjustments in order to have the desired effect and may be less likely to work/may cause side effects; and red mediations are likely to require significant dose adjustments in order to have the desired effect, or they not work at all, and may cause side effects.
The number to the right indicates the rationale for the reason why a drug is in the yellow or red column. This is where things get interesting when viewed through the lens of my personal history.
Before my child psychiatrist landed on a combination of Wellbutrin XL and Effexor XR, he gave me at least two other drug that created obvious, immediate side effects. I don’t remember which drugs they were and the medical records have long been destroyed, but given the antidepressant market in 2001/2002, it was likely to be Prozac, Celexa, or Zoloft—all of which exist in my yellow column.
Effexor, too, is on my yellow list. While I know I didn’t have immediate side effects from my 37.5mg dose, Effexor withdrawal was pure hell. While there aren’t any clinical studies looking at the relationship between the CYP450 system and psychiatric drug withdrawal, it doesn’t seem like a radical leap to assume that someone’s ability to metabolize a drug also affects the body’s ability to get the drug out of the system. Anecdotally, this hypothesis is further bolstered by my relative ease when it came to getting off the Wellbutrin, a drug in my green column. I know this isn’t the whole story, but it seems unlikely that it’s not somehow related.
Another reason why I find this test valuable is because of the information buried in the anxiolytics and hypnotics results. Many of these drug are commonly prescribed as part of surgical procedures in hospitals. If I ever needed major surgery, I’d want my anesthesiologist to have these results. Whether or not they’d take them into consideration is another matter, but I’ve given a copy to my emergency contact, just in case.
Genotypes and Phenotypes
The genotype and phenotype type results show specific variants for each gene. These results explain why drugs end up in the green/yellow/red column.
It is broken down into two categories: Pharmacodynamic and pharmacokinetic.
Pharmacodynamic Genes
Pharmacodynamic genes provide insights into how medications interact with the body. Variations in these genes can impact the likelihood of response or the risk of side effects with certain medications.
While it is important to note that many genes—including ones not tested by GeneSight—are involved in the process of metabolizing psychiatric drugs, GeneSight has identified a handful of issues known to come with specific gene variants. SLC6A4, for example, encodes for the serotonin transporter, which is the main site of action for SSRIs. People have either a long allele (variation) or short allele of SLC6A4. According to GeneSight, “Studies have shown that the short [SLC6A4] allele results in less serotonin transporters than the long allele. Individuals who have the short allele may be less likely to respond to certain SSRIs based on this genotype.” Thus, my short SLC6A4 allele contributes to the reason why SSRIs like Celexa, Paxil, and Zoloft are on my yellow list.
The same goes for pharmacokinetic genes, which provide information about how the body processes medications.
What stands out here is my CYP2D6 and CYP1A2. CYP2D6 is involved in a wide range of drug metabolism, psychiatric and otherwise. My intermediate metabolizer status indicates that I metabolize these drugs more slowly than normal. This is important because it means that while I may not have immediate adverse reactions, I am more likely to encounter them long term as the drug slowly builds up in my system.
On the other end of the spectrum, I am an ultra rapid metabolizer for CYP1A2. CYP1A2 is involved in the metabolism of a not only some antipsychotics, but also melatonin and caffeine. This explains two things I’ve known to be true about myself: I can drink caffeinated coffee or tea late in the day without it affecting my sleep, and melatonin has little to no effect on me. This makes sense—thanks to my quick CYP1A2, both caffeine and melatonin rush right through my system.
Additionally, vegetables like cabbages, cauliflower and broccoli are known to increase levels of CYP1A2, whereas spices like turmeric and cumin inhibit CYP1A2. So much so that a Sydney based researcher concluded that the “different diets and lifestyles of South Asians compared to Europeans could lead to the two groups requiring very different doses of medicines commonly used to treat illnesses such as depression and psychosis.”
Said another way: diet affects drug metabolism.
Of course, most of us aren’t thinking about how that chai tea affects the efficacy of our Rx cocktail. For the majority of people, it’s this particular quirk probably irrelevant. But for others—say, someone living in a Sri Lankan household who is struggling with a particular prescription drug—the knowledge might be more akin to low hanging fruit.
Furthermore, it speaks to the nuance of drug prescription that is all but ignored. Now, I know that any drug or supplement I take should be crossed checked to see if it’s metabolized by CYP1A2 or CYP2D6. If so, maybe I need to stay away from Indian food while I take it or consider a change in dose.
Gene-Drug Interaction
The last chunk of the GeneSight test is a handy chart outlining gene-drug interaction. The chart is supplementary, and only tells you which genes are involved in metabolizing each drug.
The real limitation here is that the second multiple drug are involved, all of this goes out the window.
You now know that a drug-gene interaction occurs when a person’s genetic makeup affects how their body metabolizes or responds to a medication. A drug-drug-gene interaction occurs when the effects of two or more medications are altered by a person’s genetic makeup.
For example, someone who is an intermediate metabolizer for CYP3A4—one of the enzymes involved in Zoloft (sertraline) metabolizatoin—may have no issue with the Zoloft alone, even as an intermediate metabolizer. But serotonin toxicity, also know n as serotonin syndrome, becomes a real risk if they start taking the antibiotic erythromycin. Erythromycin uses the CYP3A4 pathway and therefore inhibits the metabolism of Zoloft, leading increased and potentially toxic Zoloft levels in the body.
While the Zoloft or the erythromycin individually may not create an issue, combine them together with an intermediate or slow metabolizer, and you’ve got a problem.
GeneSight isn’t of any help when it comes to drug-drug-gene interaction, a giant limitation given how many people are on multiple drugs. But again, it gives us more information than we had before, which I think is a net positive.
GeneSight Conclusions
In general, I went down the GeneSight rabbit hole for no reason other than pure curiosity. I have no plans to take psychiatric drugs in the future, nor do I know how my trajectory might have been different had I had this information back when I was medicated in 2001.
There is plenty of debate about the use of genetic testing in the world of mental health, most of it focusing on questions about privacy, accuracy, over interpretation of the results, lack of FDA approval, and cost.
From my perspective, there’s not enough compelling evidence to convince me that people shouldn’t take it into consideration. We do all sorts of things that aren’t approved by the FDA—drinking wine and taking multivitamins, for example—so that argument is moot. Privacy concerns are ubiquitous these days, but I personally don’t care what they do with my results. Some think that the results could inhibit people from getting insurance to pay for psychiatric care down the line, but again, I haven’t seen direct evidence of this.
Like anything, it’s up to the individual to decide what’s best for them.
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