Can We Predict Response to Antidepressants?
Can We Predict Response to Antidepressants?
A long-standing problem facing practicing psychiatrists is our limited ability to select treatments for patients based on the likelihood that a specific treatment will be effective for a particular patient. In this article, we use the example of major depressive disorder (MDD) to review research efforts to identify predictors of treatment response, both to antidepressant medications and to psychotherapy. We describe the promises and limitations of this research, with some emphasis on brain imaging studies, and then discuss how this work may be integrated into clinical practice in the future.
MDD is a significant cause of morbidity and mortality that affects 13.1 to 14.2 million American adults annually.1 Following an adequate trial of the SSRI citalopram in a recent multicenter study, only 28% of patients with MDD achieved remission.2 Remission rates with other classes of antidepressants are similar. Until clinical or biological subtypes of MDD that are more likely to respond to one treatment than to another are identified, we are left to consider other factors in selecting treatments for our patients. Common strategies include choosing medications with side-effect profiles thought to be most advantageous for a specific patient, or choosing treatments that have previously been effective for a patient's family members. While these approaches are quite rational, no empirical studies have been conducted that provide evidence to support them.
One clinical subtype of depression with good evidence of differential response to different treatments is atypical depression. Patients with atypical depression, a subtype defined in DSM-IV by reverse neurovegetative symptoms (increased sleep and appetite), rejection sensitivity, leaden paralysis, and mood reactivity,3 have higher response rates when treated with monoamine oxidase inhibitors (MAOIs) than with tricyclic antidepressants (TCAs),4 a finding replicated in at least 4 studies. While probably a valid distinction, it is of less clinical relevance today, since both these classes of medications are used less frequently because of the risks of hypertensive crisis with MAOIs and fatality in overdose with TCAs. Future studies will hopefully examine whether transdermal selegiline, an MAOI that does not carry the same dietary restrictions as orally administered MAOIs when given at dosages up to the 6 mg/24 h patch, is similarly effective in atypical depression.
An interesting body of literature has examined whether there are certain clinical variables that may predict response to treatment with psychotherapy. The NIMH Treatment of Depression Collaborative Research Program, a particularly informative study, analyzed factors predicting differential response to interpersonal psychotherapy (IPT) and to cognitive-behavioral therapy (CBT) for major depression in a 16-week, multicenter, randomized trial.5 Low levels of social dysfunction predicted a better response to IPT, and low levels of negatively biased thinking patterns as assessed by the Dysfunctional Attitudes Scale predicted a better response to CBT. IPT works to improve relationships and social functioning, and CBT works to challenge and reformulate patterns of negative thinking. This suggests that a certain level of functioning in the psychological domain that is the focus of a given psychotherapy must be present when beginning treatment in order to derive maximal benefit from that treatment. The idea that treatments that act on a certain area of functioning may work best when this area is not overly impaired has interesting analogies in the brain imaging literature.
BIOLOGICAL PREDICTORS Techniques
Positron emission tomography (PET) and single photon emission CT (SPECT) are related techniques that can be used to visualize and, when performed rigorously, quantify molecules of interest in the brain. PET can also be used to measure blood flow and glucose metabolism. Both PET and SPECT can involve the intravenous injection of a radioactively labeled molecule (a radio-ligand) that has been chemically designed to bind specifically to a protein of interest in the brain. The radioligand is then visualized using a PET or SPECT camera. These methods are very powerful in that they allow us to measure, with some assumptions, the number of available molecules of interest in vivo in the human brain. Some of the drawbacks to these approaches include cost, radiation exposure, and the occasional need for placement of a radial arterial catheter to accurately quantify proteins in the brain.
Functional MRI (fMRI) is a technique that can indirectly measure brain activity by taking advantage of the different magnetic properties of oxyhemoglobin and deoxyhemoglobin. It does not require radiation exposure and is less invasive than PET, but it yields relative, rather than absolute, information regarding brain activity and no information on location and quantity of proteins.
Pharmacogenetics identifies genetic variants, including single nucleotide polymorphisms (SNPs) that are associated with differential response to a specific treatment. These approaches are less invasive and less costly than PET or SPECT, but they are a less direct way of assessing the chemical milieu in the CNS, which arises not merely through genetics but also through gene-environment interactions.
Dysfunction in the serotonin system as a predictor of outcome
There is a large body of evidence supporting the idea that the serotonin neurotransmitter system is abnormal in patients with major depression.6 Serotonin (5-HT) acts on at least 15 different receptors and is cleared from synapses primarily by the serotonin transporter. One of these, the 5-HT1A receptor, is located on serotonin-producing neurons (in the dorsal raphe nucleus), where it provides negative feedback to communicate to these cells when to reduce the release of serotonin (Figure 1). In many regions of the brain, 5-HT1A receptors also receive the serotonin signal on postsynaptic neurons, where they mediate its effects.7 The antianxiety medication, buspirone, acts primarily on the 5-HT1A receptor. Lemonde and colleagues8 described a genetic variant of the 5-HT1A gene that is more frequently found in patients with MDD. This variant leads to elevated levels of the 5-HT1A receptor and has been associated with poor response to antidepressant treatment in many,9-11 but not all,12 studies.
In response to long-term treatment with SSRIs, the inhibitory 5-HT1A receptors on serotonin neurons are desensitized, leading to increased serotonin release, which has been proposed as the mechanism of action of SSRIs.13 The genetic variant of the 5-HT1A receptor identified by Lemonde may be incapable of down-regulation following SSRI treatment, which may limit the therapeutic effect of SSRIs in patients with this variant.
Our laboratory used PET to study the 5-HT1A receptor in patients with MDD. We found higher 5-HT1A binding potential (proportional to the total number of available receptors) in antidepressant-naive patients having a major depressive episode than in healthy controls.14 We also found a correlation between the genetic variant of 5-HT1A and the level of 5-HT1A receptor binding in the raphe nuclei, consistent with preclinical studies.
Next, we studied whether baseline 5-HT1A binding would predict outcome after 1 year of antidepressant treatment. In a sample of 22 patients who received naturalistic treatment for MDD, nonremitters had higher 5-HT1A receptor binding across all brain regions at baseline than remitters.15 Thus, both genetic and imaging assessments of the 5-HT1A receptor may be partially predictive of treatment outcome, although this imaging study is limited by nonstandardized treatment--an issue we are addressing in an NIMH-funded prospective study.
The serotonin transporter (SERT) regulates serotonin transmission by facilitating reuptake of serotonin into presynaptic neurons (Figure 1).16 We recently described lower SERT binding in the amygdala and midbrain in patients with MDD than in controls.17 A SPECT study of depressed patients found a correlation between lower SERT binding at baseline in the thalamus/hypothalamus and reduced response to SSRIs.18 This study showed a similar trend between brain stem SERT and treatment response. We also looked at SERT binding as a predictor of remission from MDD in a sample that overlaps that of the 5-HT1A receptor study. We found a trend toward a predictive effect of SERT binding on remission status at 1 year (Figure 2).