Tuesday, 13 April 2010

The Hunt for the Prozac Gene

One of the difficulties doctors face when prescribing antidepressants is that they're unpredictable.

One person might do well on a certain drug, but the next person might get no benefit from the exact same pills. Finding the right drug for each patient is often a matter of trying different ones until one works.

So a genetic test to work out whether a certain drug will help a particular person would be really useful. Not to mention really profitable for whoever patented it. Three recent papers, published in three major journals, all claim to have found genes that predict antidepressant response. Great! The problem is, they were different genes.

First up, American team Binder et al looked at about 200 variants in 10 genes involved in the corticosteroid stress response pathway. They found one, in a gene called CRHBP, that was significantly associated with poor response to the popular SSRI antidepressant citalopram (Celexa), using the large STAR*D project data set. But this was only true of African-Americans and Latinos, not whites.

Garriock et al used the exact same dataset, but they did a genome-wide association study (GWAS), which looks at variants across the whole genome, unlike Binder et al who focussed on a small number of specific candidate genes. Sadly no variants were statistically significantly correlated with response to citalopram, although in a GWAS, the threshold for genome-wide significance is very high due to multiple comparisons correction. Some were close to being significant, but they weren't obviously related to CRHBP, and most weren't anything to do with the brain.

Uher et al did another GWAS of response to escitalopram and nortriptyline in a different sample, the European GENDEP study. Escitalopram is extremely similar to citalopram, the drug in the STAR*D studies; nortriptyline however is very different. They found one genome-wide significant hit. A variant in a gene called UST was associated with response to nortriptyline, but not escitalopram. No variants were associated with response to escitalopram, although one in the gene IL11 was close. There were some other nearly-significant results, but they didn't overlap with either of the STAR*D studies.

Finally, one of the STAR*D studies found a variant significantly linked to tolerability (side effects) of citalopram. GENDEP didn't look at this.

*

The UST link to nortriptyline finding is the strongest thing here, but for citalopram / escitalopram, no consistent pharmacogenetic results emerged at all. What does this mean? Well, it's possible that there just aren't any genes for citalopram response, but that seems unlikely. Even if you believe that antidepressants only work as placebos, you'd expect there would be genes that alter placebo responses, or at the very least, that affect side-effects and hence the active placebo improvement.

The thing is that the "antidepressant response" in these studies isn't really that: it's a mix of many factors. We know that a lot of the improvement would have happened even with placebo pills, so much of it isn't a pharmacological effect. There are probably genes associated with placebo improvement, but they might not be the same ones that are associated with drug improvement and a gene might even have opposite effects that cancel out (better drug effect, worse placebo effect). Some of the recorded improvement won't even be real improvement at all, just people saying they feel better because they know they're expected to.

If I were looking for the genes for SSRI response, not that I plan to, here's what I'd do. To stack the odds in my favour, I'd forget people with an moderate or partial response, and focus on those who either do really well, or those who get no benefit at all, with a certain drug. I'd also want to exclude people who respond really well, but not due to the specific effects of the drug.

That would be hard but one angle would be to only include people whose improvement is specifically reversed by acute tryptophan depletion, which reduces serotonin levels thus counteracting SSRIs. This would be a hard study to do, though not impossible. (In fact there are dozens of patients on record who meet my criteria, and their blood samples are probably still sitting in freezers in labs around the world... maybe someone should dig them out).

Still, even if you did find some genes that way, would they be useful? We'd have had to go to such lengths to find them, that they're not going to help doctors decide what to do with the average patient who comes through the door with depression. That's true, but they might just help us to work out who will respond to SSRIs, as opposed to other drugs.

ResearchBlogging.orgBinder EB, Owens MJ, Liu W, Deveau TC, Rush AJ, Trivedi MH, Fava M, Bradley B, Ressler KJ, & Nemeroff CB (2010). Association of polymorphisms in genes regulating the corticotropin-releasing factor system with antidepressant treatment response. Archives of general psychiatry, 67 (4), 369-79 PMID: 20368512

Uher, R., Perroud, N., Ng, M., Hauser, J., Henigsberg, N., Maier, W., Mors, O., Placentino, A., Rietschel, M., Souery, D., Zagar, T., Czerski, P., Jerman, B., Larsen, E., Schulze, T., Zobel, A., Cohen-Woods, S., Pirlo, K., Butler, A., Muglia, P., Barnes, M., Lathrop, M., Farmer, A., Breen, G., Aitchison, K., Craig, I., Lewis, C., & McGuffin, P. (2010). Genome-Wide Pharmacogenetics of Antidepressant Response in the GENDEP Project American Journal of Psychiatry DOI: 10.1176/appi.ajp.2009.09070932

Garriock, H., Kraft, J., Shyn, S., Peters, E., Yokoyama, J., Jenkins, G., Reinalda, M., Slager, S., McGrath, P., & Hamilton, S. (2010). A Genomewide Association Study of Citalopram Response in Major Depressive Disorder Biological Psychiatry, 67 (2), 133-138 DOI: 10.1016/j.biopsych.2009.08.029

10 comments:

Unknown said...

Isn't the other potential predictor patterns in brain activity? Whilst I'm not sure of the modern consensus on the findings, it's been known for a long time that brain activity can be a predictor of response to anti-depressants (specificity, activity in the rostral anterior cingulate, as in Mayberg et al (1999)-http://journals.lww.com/neuroreport/Abstract/1997/03030/Cingulate_function_in_depression__a_potential.48.

Doesn't this suggest another way to effectively target treatments?

Bernard Carroll said...

Going after genetic predictors of response in samples like STAR*D is a waste of time and money. It illustrates the maxim that the name of the game is just to keep the game going. The sample is so heterogeneous that any genetic signal will be lost in the clinical noise. And that is even before one factors in the absence of placebo controls.

The appearance of this report in Archives of General Psychiatry says a lot about how low standards have gone.

Anonymous said...

I hope that Dr. Carroll has a longevity gene. Because his continued insightful postings is the only way psychiatry can survive as as an academic discipline. And I mean that most sincerely.

Neuroskeptic said...

Maaku: That's another line that's promising in theory but has yet to produce practical fruit.

Depression research has a long history of predictors that didn't work out in the end. My suspicion though is that some of the oldest ones are most likely to lead to insights because the reason they were discovered a long time ago is that they're pretty big.

For example, a fair % of people with severe depression show cortisol/"stress axis" abnormalities.

These aren't specific to depression, they occur in other conditions, but I don't see that as a fatal flaw: some people with depression have them and some don't. There's got to be a biological reason for that, and if so, it's likely to have treatment implications.

Anonymous said...

Neuroskeptic:
Of course people who are depressed have "stress axis abnormalities." But what is the significance of that finding? I mean is it any more explanatory than saying that "depressed people have poor stress or coping resources?" Or, using the old psychoanalytic jargon, "depressed people have ego deficits?" Using biological terms like "cortisol", while looking more "scientific" because the term is "biological," in the end, explains nothing more than the psychological phrasings of such issues.

Bernard Carroll said...

Speaking as one who began clinical research in the Jurassic era of cortisol studies in depression, I can say there was actually a time when high cortisol was interpreted in psychoanalytic terms. Ed Sachar thought it signified ego disintegration. He changed his mind after seeing evidence of persistent high cortisol throughout sleep in severe depression. Lately, studies of the cortisol system in depression have been confounded by the same problem that invalidates attempts to find genes associated with response to treatments, namely, heterogeneity of the clinical samples. The average person who receives a prescription for Prozac and its cousins for DSM-IV-defined major depression does not have high cortisol levels.

Now, if you’re talking about melancholia, that’s a different matter.

Bernard Carroll said...

Neuroskeptic said “Depression research has a long history of predictors that didn't work out in the end. My suspicion though is that some of the oldest ones are most likely to lead to insights because the reason they were discovered a long time ago is that they're pretty big.

For example, a fair % of people with severe depression show cortisol/"stress axis" abnormalities.

These aren't specific to depression, they occur in other conditions, but I don't see that as a fatal flaw: some people with depression have them and some don't. There's got to be a biological reason for that, and if so, it's likely to have treatment implications.”


As a matter of fact they do have treatment implications. Here is a quick summary of one such biomarker, the dexamethasone suppression test (DST), which dates from the late 1960s.

1. It is a state variable, i.e., episode related.
2. Normalization precedes remission.
3. Failure to normalize predicts relapse
4. DST switch precedes clinical switch to depression in rapid cycling bipolar cases (Greden)
5. Not abnormal in adjustment disorder, atypical depression or bereavement (Clayton)
6. Risk factor for switch to bipolar (Coryell). Relative risk is ~ 8.
7. Risk factor for completed suicide (Coryell). Relative risk is ~ 8.
8. Risk factor for poor long term course (Unden)
9. Predicts diagnostic change to depression from other diagnoses such as adjustment disorder and schizophrenia (Evans, Arato, Coryell)
10. Low response to cognitive behavioral therapy (CBT) in major depression (Thase).
11. Low response to placebo in major depression (9% when DST positive but 37% when DST negative) (Ribeiro).
12. High specific response to tricyclic antidepressants in major depression
- high drug-placebo difference
- Number Needed to Treat is ~ 2 when DST positive but ~ 4 when DST negative.

It is a sign of the times that there are essentially no data on this question for the weaker SSRI antidepressant drugs. Overall, the NNT for these drugs in depression is ~ 9-10.

Neuroskeptic said...

On that note a paper's just out finding that dexamethasone non-suppression is correlated with response to ECT, in MDD and PTSD patients. but it was small (n=32).

Dr. Deb said...

Such a great post.

Bernard Carroll said...

Thanks, NS. Your comment underscores the view that the research literature contains a few big facts with enduring influence. The DST in melancholia is one such big fact. In terms of impact, it is the most highly cited primary research report of a biological marker for psychiatric disorder in Archives of General Psychiatry, and the second highest in British Journal of Psychiatry (where #1 is Martin Roth’s 1968 report of cortical atrophy in dementia – another big fact).