Outline

• Abstract
  
• SUBJECTS AND METHODS
  
• SUBJECTS
  
• PROCEDURES
  
• BIOCHEMICAL METHODS
  
• PET SCANNING METHODS
  
• PET IMAGE PROCESSING
  
• MEASUREMENT OF ROIs
  
• DATA ANALYSIS
  
• RESULTS
  
• EFFECTS OF TRYPTOPHAN DEPLETION ON REGIONAL CEREBRAL METABOLISM
  
• ASSOCIATIONS BETWEEN VARIABLES
  
• Ham-D Scores and Brain Metabolic Response to Tryptophan Depletion
  
• Plasma Tryptophan Levels With Tryptophan Depletion, Behavior, and Regional Brain Metabolism
  
• Clinical Variables, Relapse Status, and Regional Brain Metabolism
  
• COMMENT
  
• REFERENCES
  

Graphics

• Table 1
  
• Figure 1
  
• Figure 2
  
• Figure 3
  
• Figure 4
  
• Figure 5
  
• Figure 6
  
• Table 2
  
• Table 3
  

Background: Short-term depletion of plasma tryptophan has been shown to result in depressive relapse in patients with remission of major depression. Positron emission tomography and single photon emission computed tomography studies implicated the dorsolateral prefrontal cortex, orbitofrontal cortex, thalamus, and caudate nucleus in the pathogenesis of depression. The purpose of this study was to measure cerebral metabolic correlates of tryptophan depletion-induced depressive relapse.

Methods: Patients diagnosed as having major depression (N=21) who clinically improved with serotonin reuptake inhibitors underwent 2 test days involving tryptophan depletion or placebo, followed 6 hours later by positron emission tomography scanning with fludeoxyglucose F18. Brain metabolism was compared in patients with (n=7) and without (n=14) a tryptophan depletion-induced depressive relapse.

Results: Tryptophan depletion resulted in a decrease in brain metabolism in the middle frontal gyrus (dorsolateral prefrontal cortex), thalamus, and orbitofrontal cortex in patients with a depletion-induced depressive relapse (but not in patients without depletion-induced relapse). Decreased brain metabolism in these regions correlated with increased depressive symptoms. Baseline metabolism was increased in prefrontal and limbic regions in relapse-prone patients.

Conclusion: Specific brain regions, including the middle frontal gyrus, thalamus, and orbitofrontal cortex, may mediate the symptoms of patients with major depression.

Arch Gen Psychiatry. 1997;54:364-374

Studies using positron emission tomography (PET) and single photon emission computed tomography have implicated specific brain regions in the pathogenesis of depression. [39-66] Some PET and SPECT studies, [41-44] but not others, [45,61] showed decreased global brain metabolism and blood flow in untreated unipolar depressives at baseline. Multiple PET and SPECT studies found decreased metabolism or blood flow, or both, in left [41,45,48,57] and bilateral [46,47,53,56,60] dorsolateral prefrontal cortex. Other PET and SPECT studies in patients with unipolar depression showed decreased metabolism or blood flow, or both, in caudate, [44,47,50,53,54] thalamus, [47] temporal, [47,50,53,55] cingulate, [48,53] parietal cortex, [47,50,60] and left putamen regions, [47] but orbitofrontal metabolism was increased [60] or unchanged. [66] Positron emission tomography studies in patients with Huntington [40] or Parkinson disease [49,65] and comorbid depression also showed decreased metabolism or blood flow, or both, in the prefrontal cortex, [40,49,65] orbitofrontal cortex, [40,49] and anterior cingulate region. [65] Treatment of depression was associated with a reversal of these metabolism and blood flow deficits. [64] Antidepressants increased metabolism or blood flow, or both, in the left prefrontal cortex in some studies, [41,45] but not in others, [50,56] and increased blood flow in anterior cingulate, right putamen, and right thalamus regions. [59] Sleep deprivation-induced improvement in depression was associated with increased baseline metabolism or blood flow, or both, in anterior cingulate, [61] amygdala, [57,61,63] orbitofrontal, [57,63] hippocampus, [57,63] and infratemporal regions, [57,63] but sleep deprivation in sleep responders resulted in a decrease in cingulate metabolism. [61] Treatment response to electroconvulsive therapy also was correlated with blood flow changes in cingulate cortex [58] and anterior frontal cortex. [62]

These findings led to the hypothesis that dysfunction of a circuit involving these regions mediates the symptoms of depression. [39,50] One PET study, however, found increased blood flow in unipolar depressives in left prefrontal cortex, left amygdala, and bilateral thalamus. [50] The authors hypothesized that rumination on depressive themes may have contributed to the increased blood flow. Consistent with this idea, active rumination on depressive themes in healthy subjects was associated with increased blood flow in prefrontal [51,52] and orbitofrontal cortex, caudate nucleus, putamen, and thalamus. [51] The use of a within-subjects design, in which subjects undergo scanning at baseline and after the experimental induction of depression with a technique such as tryptophan depletion, would help resolve some of these state-related questions in a way that is impossible by scanning only at baseline.

The purpose of the present study was to examine brain metabolic correlates of tryptophan depletion-induced depressive relapse in patients with major depression who were in remission and receiving antidepressants. Studies in animals showed that electrical stimulation of the serotonergic system (rostral raphe nuclei) results in an increase in brain metabolism in thalamus, [67] the extrapyramidal system, [67,68] and other regions, [68] but PET fludeoxyglucose F18 studies showed increased brain metabolism with fenfluramine in prefrontal cortex in healthy human subjects. [69] Based on these findings and those already discussed, we hypothesized that tryptophan depletion-induced depressive relapse would be associated with decreases in metabolism in middle frontal gyrus (dorsolateral prefrontal cortex), orbitofrontal cortex, thalamus, and caudate nucleus regions. We also hypothesized that changes in regional brain metabolism would distinguish patients with depletion-induced depressive relapse from patients without depletion-induced depressive relapse.

SUBJECTS AND METHODS^
SUBJECTS^
The patient group comprised 21 patients between the ages of 18 and 65 years with clinically improved major depression who gave informed consent for participation. Patients were recruited by newspaper advertisement or clinician referral and were receiving treatment with outpatient clinicians at the time of the study. Nineteen of the patients were treated with fluoxetine hydrochloride and 2 with paroxetine. Patients were included who met the criteria for major depression based on the Structured Clinical Interview for DSM-III-R. [70] Patients were excluded if they had a history of meningitis, traumatic brain injury, loss of consciousness for more than 10 minutes, neurologic disorder, current alcohol or substance abuse or dependence, or schizophrenia based on the Structured Clinical Interview for DSM-III-R. Patients had not received benzodiazepines or sedatives for at least 4 weeks before the study. None of the patients had a history of loss of consciousness within the last year. Patients also were excluded if they had a history of foreign bodies that would preclude magnetic resonance imaging (MRI) scanning. Patients with risk factors for human immunodeficiency virus (HIV) infection were screened for HIV; HIV-positive patients were excluded. The patients (10 women and 11 men) had a mean+/-SD age of 40+/-7 years. Patients had been in remission and receiving a serotonin reuptake inhibitor from 1 to 335 weeks, with a mean+/-SD of 44.8+/-47.9 weeks of remission before participation in the study. Previous depressive events ranged from 0 to more than 10, with a mean+/-SD of 1.86+/-1.31 events. Eighteen of 21 patients had at least 1 previous episode of depression. Inpatient hospitalizations for depression ranged from 0 to 10 (mean+/-SD, 1.86+/-2.38).

Patients were evaluated with the Structured Clinical Interview for DSM-III-R for comorbid psychiatric diagnoses. All patients met criteria for a lifetime history of major depression. Eighteen (86%) of 21 patients had recurrent depression. Four (19%) of 21 patients met criteria for a lifetime history of panic disorder without agoraphobia, 1 (5%) for social phobia, 1 (5%) for simple phobia, 1 (5%) for anorexia, and 1 (5%) for bulimia. No patients had lifetime or current posttraumatic stress, generalized anxiety, obsessive-compulsive, bipolar, somatization, somatic pain, or undifferentiated somatization disorders; schizophrenia; dysthymia; or hypochondriasis. Three (14%) of 21 patients met criteria for a lifetime history of alcohol abuse, 4 (19%) of 21 for a lifetime history of alcohol dependence, 3 (14%) of 21 for polysubstance abuse, and 1 (5%) of 21 for polysubstance dependence. None of the patients met criteria for current alcohol or substance abuse, or for lifetime or current cannabis, sedative, hypnotic, anxiolytic, stimulant, opiate, cocaine, hallucinogen, or phencyclidine hydrochloride dependence or abuse.

PROCEDURES^
Patients underwent 2 PET scanning days separated by 1 week, 1 following tryptophan depletion and the other following placebo. Tryptophan depletion and placebo were administered in a double-blind, placebo-controlled fashion, with randomized order of assignment. The tryptophan depletion day consisted of a 24-hour, 160 mg/d tryptophan diet (day 1) with blue placebo capsules taken 3 times daily, followed the next morning by a tryptophan-free, 15-amino acid drink (day 2). The amino acids consumed were L-alanine, 5.5 g; L-arginine, 4.9 g; L-cysteine, 2.7 g; L-glycine, 3.2 g; L-histidine, 3.2 g; L-isoleucine, 8.0 g; L-leucine, 13.5 g; L-lysine monohydrochloride, 11.0 g; L-methionine, 3.0 g; L-phenylalanine, 5.7 g; L-proline, 12.2 g; L-serine, 6.9 g; L-threonine, 6.9 g; L-tyrosine, 6.9 g; and L-valine, 8.9 g. Control testing consisted of a 24-hour, 160-mg/d tryptophan diet supplemented with blue capsules containing 500 mg of L-tryptophan taken 3 times daily, followed the next morning by a 16-amino acid drink containing L-tryptophan, 2.3 g, in addition to the aforementioned 15 amino acids. [71]

Patients underwent behavioral ratings, and plasma for free and total tryptophan levels was obtained at 9 AM before starting the diet (test day 1), 15 minutes before, and 5 and 7 hours after the drink (test day 2). Ratings were obtained again between 11 AM and 1 PM after each amino acid drink (the day after testing). Ratings were obtained by 1 of us (R.M.S.) or by a trained nurse-clinician. Raters had established reliability on the rating instruments used (interrater reliability for Hamilton Depression Scale (Ham-D) ranged from 88% to 95%) and were blinded to the sequence of placebo or active tryptophan supplementation.

Behavioral rating scales consisted of the Ham-D, the Hamilton Anxiety Scale, and the Symptom Checklist. A depressive relapse was defined as a 50% and a 9-point increase from baseline on the Ham-D. Seven patients met criteria for a depressive relapse with depletion, and 14 patients did not meet criteria. One patient had a depressive relapse with placebo.

BIOCHEMICAL METHODS^
Total plasma tryptophan concentration was assayed by high-performance liquid chromatography with fluorometric detection as previously described. [21] Free plasma tryptophan concentration was assayed by obtaining the ultrafiltrate of plasma through a commercially available anisotropic, hydrophilic ultrafiltration membrane system (Amicon Inc, Beverly, Mass.) centrifuged (1000g) at room temperature and subjecting the ultrafiltrate to the high-performance liquid chromatography with fluorometric detection method. Plasma tryptophan levels were unavailable in 4 patients (1 with a tryptophan depletion-induced depressive relapse, and 3 without).

PET SCANNING METHODS^
All subjects underwent 2 days of testing as described. The PET scans took place 6 hours after administration of the tryptophan-depleting low amino acid drink or placebo. Subjects were placed in the positron camera (Posicam 6.5, Positron Corp, Houston, Tex, at the Yale Veterans Affairs Positron Emission Tomography Center, West Haven, Conn), with the head positioned along the canthomeatal line and immobilized with head and chin straps. The Posicam 6.5 is a 21-slice camera with 5.125-mm interslice distance. The inherent resolution of the camera in-plane is 5.8 mm and 11.9 mm in the z-axis. [72] After application of the Butterworth filter, the in-plane resolution of the camera, measured as full-width half-maximum, is 7.5 mm. The sensitivity of the camera, measured in a 20-cm diameter cylinder phantom, can be expressed as the system sensitivity (165 kcounts/s per microcurie per cubic centimeter); slice sensitivity (9.5 kcounts/s per microcurie per cubic centimeter); or the sensitivity/axial cm (8.0 kcounts/microCi per cubic centimeter per axial centimeter). [72]

An intravenous line was inserted in the hand and warmed with heating pads for measurement of arterialized venous blood samples. This method has been shown to yield equivalent values of metabolism to arterial line placement. [73] A 10-minute⁶⁷ Ga/⁶⁸ Ge rod transmission scan was performed for attenuation correction. Subjects then received an injection of 185 MBq of fludeoxyglucose F18 in a single intravenous bolus and were scanned for 60 minutes with eyes open in a dimly lit room. Arterialized venous blood samples were obtained at 23 time points after injection and spun down for measurement of radioactivity in plasma, which was used in the measurement of the plasma time-activity curve. A PET image was reconstructed 30 to 50 minutes after injection to determine brain tissue activity. Brain and tissue time-activity curves were then combined for measurement of cerebral glucose metabolic rate in milligrams per minute per 100 mL using the fixed rate constant approach of Sokoloff et al. [74] Separate kinetic rate constants were used for gray and white matter. [75]

PET IMAGE PROCESSING^
Images were attenuation-corrected based on the transmission scan and reconstructed using a spatially varying convolution scatter subtraction technique and a Butterworth filter. A 20-cm cylindrical, fluid-filled phantom was scanned on the same day as each study to obtain a calibration factor for each of the 21 slices obtained with the PET camera for conversion of radioactivity in the PET image into units of microcuries per milliliter.

Magnetic resonance imaging scans were obtained in all subjects for coregistration with PET and determination of regions of interest (ROIs) from MRI scans subsequently resliced to correspond to the PET. The head was positioned with the canthomeatal line aligned with the laser light for reproducibility of data acquisition and to create MRI scans in the same plane as the PET images. Magnetic resonance imaging scans of 3-mm contiguous slices were obtained with a 1.5-T scanner (Signa, General Electric, Milwaukee, Wis). Axial images were acquired with a spoiled gradient recall acquisition in the steady state sequence with repetition time=25 milliseconds, echo time=5 milliseconds, number of excitations=2, matrix 256x256, and field of view=24 cm. The PET and MRI scans were transferred using a computer network to a SUN Sparc10 Workstation (SUN Microsystems, Mountain View, Calif). A surface-matching algorithm running under Analyze [76] was used for coregistration of PET and MRI scans. In this method, the surface of the brain is first identified in the PET image and in the corresponding MRI scan. A distance transform is calculated from the MRI scan using a Chamfer algorithm. The distance transform of an image is an image in which the value at each pixel is equal to the distance to the nearest surface point in the original image. The distance image values can then be summed at each point on the other transformed surface (or set of points) to give the total distance between the surfaces. The best transformation is then determined by minimizing the total distance using local gradient descent. [77] The MRI was then resliced to obtain 21 MRI slices, each of which corresponded to 1 of the 21 PET slices. Studies from our group using this surface-matching method and brain phantom data have had a registration error of 2.2 pixels (2.86 mm). [78]

MEASUREMENT OF ROIs^
Measurements of ROIs on MRI were performed using specific criteria developed in conjunction with a neuroradiologist (R.A.B.). These criteria were developed for reproducibility of measurements between observers and to have criteria based on an anatomical atlas that allows for the use of a common terminology and that is available to general access. [79] The criteria for ROIs use anatomical landmarks located on the individual subject's MRI to allow for decision-making in the measurement of ROIs that follow specific guidelines and are therefore reproducible. Regions of interest were drawn on the resliced MRI using a mouse-driven cursor by an operator blinded to subject identity and diagnosis. Templates for ROIs drawn on the MRI were transferred to the PET. Multiple brain regions were selected for analysis (Table 1). When a specific region was present in multiple slices as determined by these criteria, the mean of activity measured in each of these slices was determined. Global brain metabolism was calculated by obtaining the mean of brain tissue activity in all slices of the brain. Brain tissue activity determined from the coregistered scan was used in the determination of regional cerebral glucose metabolic rate. Normalization for global metabolic rate was performed by dividing metabolism in an individual region by global metabolism. We have recently tested these ROI criteria with 3 raters performing measurements on 11 fludeoxyglucose F18 scans coregistered with MRI. There was a high level of agreement between raters, with intraclass correlation coefficients ranging from 0.63 to 0.98. Intraclass correlation values for 3 of the hypothesized regions in this study were middle frontal gyrus (r=0.95), thalamus (r=0.85), and orbital cortex (r=0.78) (J.D.B., Gabriel De Erasquin, MD, Eric Vermetten, MD, et al, unpublished data, January 10, 1996, available on request).

Data were analyzed for regional brain metabolic rates following administration of placebo or tryptophan depletion using a repeated measures analysis of variance (ANOVA) with depletion (tryptophan depletion vs placebo) as the repeated factor, and relapse status (patients with a relapse on the depletion day vs patients without a relapse on the depletion day) and hemisphere (left vs right) as factors in the analysis. Bonferroni corrections (dividing P value of.05 by the number of repeated measures comparisons, in this case P=.05/20=.003) were used to correct for multiple comparisons. Spearman rank order correlations were used to examine the relation between score on the Ham-D and brain metabolic response to tryptophan depletion. Normalization of regional metabolism for global metabolism was obtained by dividing regional metabolism by global metabolism.

RESULTS^
EFFECTS OF TRYPTOPHAN DEPLETION ON REGIONAL CEREBRAL METABOLISM^
Metabolism was decreased or unchanged with tryptophan depletion in all 7 of the patients with depletion-induced relapse (but not in patients without depletion-induced relapse) in thalamus (Figure 1) and middle frontal gyrus (Figure 2). Tryptophan depletion also reduced orbitofrontal cortex metabolism in the patients who experienced relapse (Table 1). Repeated measures ANOVA showed a significant interaction after correction for multiple comparisons between depletion status (depletion vs placebo) and relapse status (relapsers vs nonrelapsers) in these regions for absolute (Figure 1) and (Figure 2) and globally normalized (Figure 3) and (Figure 4) metabolism (P<.003). A significant correlation was seen between decrease in absolute and normalized metabolism and increase in depressive symptoms in these regions (Figure 5) and (Figure 6).

An unexpected finding was an increase in baseline metabolism (placebo day) in patients with depletion-induced relapse compared with patients without a depletion-induced relapse. This finding was significant for absolute metabolism in middle frontal gyrus, orbitofrontal cortex, hippocampus, and pons, and for globally normalized metabolism in amygdala, parahippocampal gyrus, anteromedial frontal cortex, and midbrain (P<.003).

ASSOCIATIONS BETWEEN VARIABLES^
Ham-D Scores and Brain Metabolic Response to Tryptophan Depletion^
Hamilton Depression Scale scores for patients with and without depletion-induced relapse are given in (Table 2). Change in Ham-D score with tryptophan depletion was associated with changes in brain metabolism. We examined the relation between change from baseline in Ham-D score on the depletion day (minus the change from baseline on the placebo day) and placebo-subtracted metabolism on the depletion day. Increased baseline-subtracted scores on the Ham-D on the depletion day relative to the placebo day were associated with decreased brain metabolism on the depletion day relative to the placebo day in thalamus (r=-0.66, df=20; P=.001) (Figure 5), middle frontal gyrus (r=-0.53, df=20; P=.01) (Figure 6), and orbitofrontal cortex (r=-0.55, df=20; P=.01). Significant correlations were seen for these brain regions for left and right sides. Correlations between Ham-D scores and regional metabolism normalized for whole brain metabolism were found for thalamus (r=-0.75, df=20; P<.001), middle frontal gyrus (r=-0.58, df =20; P=.006), and orbitofrontal cortex (r=-0.48, df=20; P=.02), but not for any of the other regions measured in this study.

COMMENT^
Tryptophan depletion was associated with a decrease in absolute and globally normalized brain metabolism in thalamus, middle frontal gyrus, and orbitofrontal cortex in patients with a tryptophan depletion-induced depressive relapse, but not in patients without a tryptophan depletion-induced depressive relapse. These regions were hypothesized to change based on previous studies. Tryptophan depletion had a tendency to decrease metabolism in several regions in the patients who experienced relapse, but the only nonhypothesized region in which this reached statistical significance was for putamen. Decreases in normalized brain metabolism were correlated with increases in Ham-D score for thalamus, middle frontal gyrus, and orbitofrontal cortex (but not putamen or other regions). In addition, increased baseline metabolism was seen in patients prone to depletion-induced relapse, which made a substantial contribution to the difference between patients who experienced relapse and those who did not. The variation in metabolism in these regions on the placebo day vs the tryptophan depletion day (33%) was greater in magnitude than the normal variation found in test-retest within subjects for PET fludeoxyglucose F18 (7%). [80,81]

Previous studies showed alterations in function as measured by brain metabolism and blood flow primarily in middle frontal gyrus (dorsolateral prefrontal cortex), [39,82] but also in limbic (orbitofrontal cortex, cingulate, thalamus, and amygdala) and striatal (caudate and putamen) regions. Normal subjects showed an activation during states of sadness, although most studies showed that depressed patients have decreased function in these regions when they are actively depressed, and our current findings show a reduction with depletion-induced relapse compared with baseline. This discrepancy may be explainable by the hypothesis that essential differences exist in brain function between normal subjects and patients with depression. Prefrontal cortex-limbic-striatal regions [83,84] comprise a functional circuit that may mediate normal dysphoria. This circuit may function abnormally in patients with depression (as previously hypothesized [39,50]), and this dysfunction may play a role in the pathogenesis of depression. Fundamental differences also may exist between induced sadness in normal subjects, which involves active rumination on sad themes, and symptoms of depression in the pathological states, which is essentially a passive process. In the single study of depressed patients that showed an increase in blood flow in prefrontal and limbic regions, the authors speculated that active rumination on depressive themes in their patients may have accounted for their discrepant findings. [50] A fundamental difference in base line brain function between normal subjects and patients with depression also may explain increased metabolism at baseline in prefrontal and limbic regions in certain subgroups of patients with depression, including patients who have improvement in symptoms with sleep deprivation and patients vulnerable to tryptophan depletion-induced depressive relapse. In the case of the tryptophan-depletion findings, patients with depression who are in the "compensated" nonsymptomatic state have increased function, indicating that although they are not actively depressed, their brain function is different from normal, perhaps due to adaptive changes. Challenge to the system with tryptophan depletion leads to a decompensation, with a reduction in metabolism toward the level seen in patients with baseline depression, and an associated increase in depressive symptoms. Patients who respond to sleep deprivation have increased baseline function in orbitofrontal cortex, cingulate, and other limbic regions, with a reduction in cingulate function as their symptoms improve. These discrepant findings do not support the idea that all states of sadness or depression are associated with reduced prefrontal and limbic function from baseline. Rather, diversions from the normal pattern in these regions at baseline and during affective changes seem to be characteristic of patients with depression, even in the compensated nonsymptomatic state for at least a subgroup of patients.

Our study has several limitations. Our rates of depressive relapse were lower than those previously reported. Our method of normalization for global metabolism involved whole brain slice measurements, which include areas such as the ventricles, which have no functional brain tissue. The use of a conservative Bonferroni correction for multiple comparisons creates the possibility that regions that showed true changes after correction for global changes may not have been identified as statistically significant. This limits our ability to conclude that depletion-induced relapse results in specific decreases in thalamus, middle frontal gyrus, and orbitofrontal cortex. In fact, several nonhypothesized regions showed substantial reductions with depletion.

We did not find a relation between free or total L-tryptophan levels in the plasma and brain metabolism. In addition, plasma free and total L-tryptophan levels were reduced to an equal extent in patients with and without a depletion-induced depressive relapse. We did not, however, measure CAAs, which compete with L-tryptophan for uptake into the brain, or proteins such as albumin, which affect L-tryptophan binding. In addition, loading with CAAs and lowering L-tryptophan levels will induce changes in hormones such as insulin and glucagon (not measured in the present study) that will affect L-tryptophan uptake and possibly have behavioral or metabolic effects of their own. These factors limit the formation of definite conclusions about the relation among plasma L-tryptophan level, depressed mood, and brain metabolism. If plasma free L-tryptophan is related to brain serotonin in the current study, however, and if our findings are not confounded by the aforementioned factors, this suggests that decreased brain metabolism (with associated depressed mood) in the patients who experience relapse is not a function of brain serotonin levels, but rather is related to a postsynaptic effect of serotonin on brain function. According to this model, instead of a deficiency in serotonin, a dysfunction of specific brain regions that are vulnerable to a reduction below critical levels in various modulators, including serotonin and norepinephrine, taking the form of a change in postsynaptic receptor binding or affinity or other postreceptor mechanisms, leads to depressive relapse. This raises the question of why some brain regions are more vulnerable than others to the effect of a decrease in brain serotonin levels. Finding the answer to this question may help us to understand the pathogenesis of depression.

Accepted for publication August 20, 1996.

This work was supported by a Veterans Administration Career Development Award (Dr Bremner) and a Veterans Administration Merit Review Grant (Dr Charney).

We thank Melissa Giunti, Cathy Colonese, RN, Pat Barry, RN, and Angie Genovese, RN, for indispensable assistance in execution of the scanning studies; Hedy Sarofin, for acquisition of magnetic resonance images; Samuel M. Mazza, PhD, for preparation of fludeoxyglucose F18; and George Aghajanian, MD, and Helen Mayberg, MD, for useful and interesting discussions.

Reprints: J. Douglas Bremner, MD, West Haven Veterans Affairs Medical Center (116a), 950 Campbell Ave, West Haven, CT 06516.

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Depressive Disorder; Positron-Emission Tomography; Recurrence; Relapse; Tomography, Emission-Computed; Tryptophan