E
DITORIALS
Antidepressant Selection in the Postgenomic Era
The term selective serotonin reuptake inhibitors (SSRIs) implies a common mechanism of action for these agents; hence, the assumption by pharmacy managers and health care planners that they are all clinically equivalent. Exten-sive clinical case report data belie this assumption, how-ever, as individuals may have differing responses to the different SSRIs, and the average profile of response in terms of symptoms and side effects may differ between agents; however, there are little empirical data bearing on this issue, as few studies have directly contrasted SSRIs in empirical clinical trials.
In this issue, Stahl and colleagues compare sertraline and citalopram in a well-designed, double-blind, con-trolled trial. They employed a range of assessment instru-ments including the Hamilton Depression Rating Scale, the Montgomery–Asberg Depression Rating Scale, and the Clinical Global Impressions Scale. They noted a signifi-cant improvement with sertraline at week 12, whereas improvement with citalopram began at weeks 2 to 4. Also, a significant anxiolytic effect of the citalopram, but not the sertraline, was demonstrated in comparison to a placebo. As investigators note, there have been quite variable results in previous comparisons of SSRIs. In a previous double-blind, multicenter study comparing sertraline and citalopram with 308 patient completers, but without a placebo trial, there were no statistically significant differ-ences in rate of side effects between the two agents, although there was an absolute increase in citalopram-induced sexual dysfunctional symptoms that did not reach statistical significance. In this study, the patients in the sertraline groups used significantly more sedatives and hypnotics than those in the citalopram group, whereas there was a slight but nonsignificant increase in response in the citalopram group as well as a higher dosage of citalopram employed (Ekselius et al 1997). In a compari-son of citalopram and fluoxetine, citalopram also showed a significantly better response at 2 weeks, demonstrating an earlier onset of recovery (Patris et al 1996), whereas another report from this group suggested greater reduction of anxiety symptoms with citalopram, as compared to fluoxetine (Bougerol et al 1997).
Given the discrepant or variable results between differ-ent multicdiffer-enter trials regarding comparisons between SSRIs, the investigators interpret these results in the context of different populations responding differentially to one SSRI as compared with another. A number of studies suggest that patients who were intolerant of (Brown and Harrison 1995; Thase et al 1997; Zarate et al 1996) or failed to respond to (Joffe et al 1996; Thase et al 1997) an initial SSRI trial may respond to a second trial
with a different SSRI. Thus, the investigators are probably right in stating that these results support a differential response to SSRIs in different populations rather than the conclusion that one SSRI is clearly superior to another in a generalizable fashion.
This conclusion, although not directly inferable from this study, has important practical and research implica-tions. A trend for pharmacies or health care organizations to restrict SSRIs to one or two agents, under the assump-tion that they are all equivalently efficacious, may not be valid and would prevent access of patients to medications that might be effective for them when the SSRI chosen by the pharmacy is not. When cost control issues become paramount in clinical care, definitive empirical data that can correct these assumptions of equal efficacy for the SSRIs in all populations are clearly called for.
There are many reasons, of course, why antidepressants may differ in their efficacy. Differences in pharmacoki-netics, including drug metabolism; differences in pharma-cologic effects; and differences in nontarget pharmaco-logic mechanisms that contribute to side effects and tolerability can contribute to differential responses. Thus, for example, agents that enhance dopaminergic activities, such as buproprion, would be expected to have a different profile of efficacy than the SSRIs. Similarly, mixed noradrenergic/serotonergic reuptake blockers such as ven-lafaxine would be expected to have some properties of the SSRIs with additional effects that more nearly mimic the actions of the tricyclics at higher doses, where noradren-ergic effects are more prominent. A better understanding of differential efficacy of the antidepressants and the populations that are best served by the individual agents could have important implications for treatment interventions.
If this conclusion is true, however, it remains elusive as to how to define population differences that are relevant for treatment response. Up until now, demographic or clinical characteristic approaches to defining homoge-neous populations that will respond to one rather than another antidepressant have been largely disappointing. But with the advent of new techniques of mapping the genotype permitting the identification of single nucleotide pairs that vary between individuals, the door is opened to identifying genetic differences in individuals that are relevant for medication responses. Indeed, this has re-sulted in a new field of “pharmacogenomics.” By identi-fying genetic differences between populations of respond-ers to a particular medication and those who are nonresponders, the possibility of identifying those who would most benefit from a particular medication and those
who are most at risk for potentially deleterious side effects becomes potentially realizable.
This approach has been used with varying results to predict responses of individuals to atypical antipsychotics, particularly clozapine, but has not been widely applied to the SSRIs, with several exceptions. A polymorphism for the serotonin transporter gene promoter site has been identified, with the long (l) form resulting in more trans-porter being expressed than the short (s) form, which is associated with greater psychopathology (Lesch et al 1994). In one study of 102 inpatients with major depres-sive disorder with psychotic features, patients homozy-gous for the s allele (s/s) demonstrated a worse antidepres-sant response to fluvoxamine than either those heterozygous (l/s) or homozygous (l/l) for the l allele (Smeraldi et al 1998). In another study of 51 patients treated with paroxetine, patients homozygous for the l allele responded with more improvement from week 2 to week 6 then those with l/s or s/s genotypes, although at 12 weeks there were no differences in response between groups (Pollock et al, in press). Another study also showed a worse response to paroxetine in depressed patients with the s/s homozygote of the transporter (Zanardi et al, in press). Transporter polymorphisms have been related to response to fluoxetine as well as platelet serotonin trans-porter affinity (Rausch et al 2000). The promoter poly-morphism and an intronic polypoly-morphism in the transporter gene were also associated with treatment response to fluoxetine or paroxetine in a Korean population (Kim et al 2000). This polymorphism has also been associated with response to sleep deprivation (Benedetti et al 1999). Although there have been inconsistencies between these initial studies, which require replication in larger series, these results suggest that a functional polymorphism at the promoter site of the serotonin transporter might influence timing or magnitude of antidepressant response to SSRIs. It seems quite possible that the presence, magnitude, and direction of this association may vary in differ genetic populations.
Animal models using knockout gene strategies have also been used to evaluate genetic differences in relation to antidepressant effects. For example, mutant mice lacking the serotonin 1B (5-HT1B) receptor showed increased or potentiated effects of paroxetine in increasing extracellular serotonin levels in the ventral hippocampus but not in the frontal cortex (Trillat et al 1998), and the knockout mice did not demonstrate the decreased mobility following SSRIs that has been found in wild type mice, suggesting that activation of 5-HT1B receptors may play a role in mediation of the antidepressant effects of SSRIs. Thus, it would be logical to investigate allelic variations of 5-HT1B receptors, which have been demonstrated in human beings (Lappalainen et al 1995), in relation to treatment response
to SSRIs. Other genetic sites in the serotonin system may differ between individuals and have an impact on the pharmacologic effect of the SSRIs. The 5-HT2Areceptor has allelic variance that may be related to behavioral traits such as the propensity to alcoholism or impulsivity, but has not been investigated with relation to the response to SSRIs (Lappalainen et al 1998). Other genes with the allelic variation include the 5-HT1Areceptor, which may influence both postsynaptic response and presynaptic se-rotonergic activity. With the advent of DNA chip technol-ogy, it may be possible to evaluate a panel of related serotonergic genes to determine those profiles that are associated with optimal drug response for any particular agent, pointing the way to a rational basis for pharmaco-logic selection.
Strain differences in animal models of antidepressant response (West and Weiss 1998) to antidepressants with differing mechanisms of action may enable a better un-derstanding of the factors that confer differential response to antidepressants. It is not clear whether some of the pharmacologic effects of antidepressant administration such as downregulation of the serotonin transporter may differ in different genetic strains. These differences are not likely to be due to differences in transporter gene expres-sion, but may be attributable to genes affecting regulation of the transporter (Benmansour et al 1999).
Individual differences in the cytochrome P-450 system may also play a role in differential response to SSRIs. Although the pharmacogenetic differences and oxidation of the SSRIs themselves may not be of clear clinical relevance, the differential inhibition of the various cyto-chrome P-450 isozymes will alter the interactions with other drugs that patients may be taking that are metabo-lized by these isozymes, thus influencing their differential response (Brosen 1993).
Environmental variables such as diet or stress may also influence response to SSRIs. For example, patients with anorexia nervosa may not be responsive to SSRIs when ill as a consequence of inadequate supply of nutrients that are essential for normal serotonin synthesis and function (Kaye et al 1998). Conceivably, then, factors including nutritional status, stress, and even social milieu (Raleigh et al 1994) can affect responses to SSRIs. Trauma may influence responses of the serotonergic system and its relation to hypothalamic–pituitary–adrenal axis activity (Siever et al 1998), and such differences might conceiv-ably affect the response of antidepressant medication.
Whereas perhaps the choice of antidepressant type in a clinical situation will always be partially an art, there are clearly a lot of questions that could empirically be an-swered to bring more science into the process. There are few head-on-head studies to evaluate differential re-sponses, even differing mechanisms of action, between
876 BIOL PSYCHIATRY Editorial
antidepressants, much less the more similar SSRIs. We know little of the potential genetic and environmental factors that might influence individual responses to spe-cific antidepressants. The new science of pharmacog-enomics can help us understand the genetic determinants of drug response, whereas the role of other environmental factors such as diet or social context needs to be more systematically studied. As the genome has now been largely mapped, these strategies then may afford us the prospect for a more rational pharmacotherapy in the next 100 years.
Larry J. Siever
Mount Sinai School of Medicine 1 Gustave L. Levy Place, Box 1230 New York NY 10029
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Editorial BIOL PSYCHIATRY 877
