SEARCH

SEARCH BY CITATION

Keywords:

  • 5-HTTLPR;
  • BDNF;
  • dorsolateral prefrontal cortex;
  • fMRI;
  • geriatric depression;
  • subgenual cingulate

Abstract

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

The brain-derived neurotrophic factor (BDNF) Val66Met allelic variation is linked to both the occurrence of mood disorders and antidepressant response. These findings are not universally observed, and the mechanism by which this variation results in increased risk for mood disorders is unclear. One possible explanation is an epistatic relationship with other neurotransmitter genes associated with depression risk, such as the serotonin-transporter-linked promotor region (5-HTTLPR). Further, it is unclear how the coexistence of the BDNF Met and 5-HTTLPR S variants affects the function of the affective and cognitive control systems. To address this question, we conducted a functional magnetic resonance imaging (fMRI) study in 38 older adults (20 healthy and 18 remitted from major depressive disorder). Subjects performed an emotional oddball task during the fMRI scan and provided blood samples for genotyping. Our analyses examined the relationship between genotypes and brain activation to sad distractors and attentional targets. We found that 5-HTTLPR S allele carriers exhibited stronger activation in the amygdala in response to sad distractors, whereas BDNF Met carriers exhibited increased activation to sad stimuli but decreased activation to attentional targets in the dorsolateral prefrontal and dorsomedial prefrontal cortices. In addition, subjects with both the S allele and Met allele genes exhibited increased activation to sad stimuli in the subgenual cingulate and posterior cingulate. Our results indicate that the Met allele alone or in combination with 5-HTTLPR S allele may increase reactivity to sad stimuli, which might represent a neural mechanism underlying increased depression vulnerability.

Depression has been hypothesized to be a failure of executive control over emotion (Disner et al. 2011; Mayberg 1997), a theory largely supported by neuroimaging studies, which find decreased function of the executive system and increased activity of the emotional system (Siegle et al. 2007; Steele et al. 2007). Genetic variants may contribute to the imbalanced executive and affective systems resulting in increased vulnerability to developing major depressive disorder (MDD). Among the best-studied genes in MDD are variants of the serotonin-transporter-linked promoter region (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) genes (Caspi et al. 2003; Gatt et al. 2009). However, it is unclear how BDNF and 5-HTTLPR variants independently and interactively influence neural systems associated with affective and executive function.

The Met variant of the BDNF Val66Met polymorphism results in decreased activity-dependent secretion of BDNF (Chen et al. 2004; Egan et al. 2003) and is associated with deficits in hippocampal function (Chen et al. 2006). Although some studies found that the Met allele is more common in geriatric depression (Taylor et al. 2007), meta-analyses concluded that Val allele was linked to anxiety and unrelated to depression (Frustaci et al. 2008; Verhagen et al. 2010). The BDNF gene also exhibits epistatic interactions with other genes (Gatt et al. 2009; Levinson 2006), including variants in 5-HTTLPR, which could partly explain the inconsistent findings in Met BDNF variant. The short (S) allele variant of 5-HTTLPR is associated with reduced transcription of 5-HTT (Lesch et al. 1996). Compared with long (L) allele homozygous individuals, healthy S allele carriers exhibit an exaggerated amygdala response to fearful and angry faces (Hariri et al. 2002, 2005). Supporting the theory of epistatic effect between BDNF and 5-HTTLPR genes, some studies reported that the combination of the S and Met alleles predicts depressive symptoms (Kaufman et al. 2006; Kim et al. 2007; Wichers et al. 2008). Others, however, suggested that the Met allele may protect against the influence of the 5-HTTLPR S allele on neural systems (Pezawas et al. 2008). Overall, little is known about the interactive effects of these genes on neural function.

Neuroimaging studies examining the BDNF Val66Met gene have predominately focused on memory-related hippocampal function (Egan et al. 2003; Hariri et al. 2003; Kanellopoulos et al. 2011; Pezawas et al. 2004) with little attention on emotional processing (Montag et al. 2008). Conversely, studies examining 5-HTTLPR neglected the executive function and only focused on emotion. Moreover, studies on emotion used mixed negative stimuli or fearful/angry stimuli (Hariri et al. 2005; Heinz et al. 2007), making it difficult to tease apart the genetic effects on depression from anxiety. Investigating neural responses to exclusively sad stimuli should be more sensitive in revealing the functional contribution of the genes specific to depressed mood.

In this study, we tested for both main and epistatic effects of the BDNF and 5-HTTLPR polymorphisms on neural activation related to sad emotion and executive function in a group of older adults. We hypothesized that epistatic interactions of the BDNF Met and 5-HTTLPR S genes exaggerate affective and executive dysfunction.

Participants and methods

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

Subjects

Eighteen individuals (11 males) with a previous DSM-IV diagnosis of unipolar MDD who were currently in full remission and 20 healthy participants (eight males) participated in the study. All subjects were Caucasians and 60 years of age or older. They were recruited from the NIMH-sponsored Conte Center for the Neuroscience of Depression in Late-Life at Duke University Medical Center. As part of the longitudinal study, all patients had a follow-up on their clinical symptoms every 2 weeks in their actively depressed state and every 3 months in their remitted state. The Montgomery–Åsberg Depression Rating Scale (MADRS) (Montgomery & Asberg 1979) was used to assess symptoms of depression in all participants on the day of functional magnetic resonance imaging (fMRI) scanning. Remission was defined as an absence of symptoms for a minimum of 6 months with a MADRS score of <8. Among the 18 remitted subjects, 14 were receiving antidepressant monotherapy [seven on selective serotonin reuptake inhibitors (SSRI), three on bupropion, three on venlafaxine and one on mirtazepine], 1 was receiving combination treatment (SSRI/bupropion) and 3 were receiving no antidepressants at the time of testing. No subjects had any other primary diagnosis of psychiatric or neurological disorders, history of head trauma or substance abuse. The study was approved by the Institutional Review Board at Duke University, and all participants provided written informed consent after the procedures had been fully explained.

Genotyping

Genomic DNA was extracted by standard procedures (Puregene D-50K DNA Isolation Kit, Gentra, Minneapolis, MN, USA) from fresh or frozen samples of peripheral blood. As previously described for the BDNF Val66Met polymorphism (rs6265) (Taylor et al. 2007), DNA was amplified by polymerase chain reaction (PCR) using a Taqman by-design assay that recognizes the single nucleotide polymorphism (SNP) that defines that polymorphism. Genotyping for the 5-HTTLPR alleles initially utilized PCR amplification to generate the 484- and 528-base pair fragments corresponding to the short and long 5-HTTLPR alleles, respectively (Steffens et al. 2002). We also genotyped the A/G variant of the L allele (rs25531) by digesting the 5-HTTLPR PCR product with Hpa II, a restriction enzyme which cuts at the rs25531 site only if the G allele is present (Brummett et al. 2008). However, given the fact that the implications of the A/G variant for behavioral and neural mechanisms is unclear to date, we only conducted a subsequent explorative analysis on the A/G variant and the results was presented here. We had two sets of duplicate samples per 96-well plate and the duplicates had to match 100% or we did not accept the genotypes for any of the samples.

Experimental designfor the oddball task

Given that dysfunctions in the emotional and executive systems are key neural deficits in depression, to examine whether the genetic variants of 5-HTTLPR and BDNF are associated with increased depression vulnerability, we employed our emotional oddball task in this study. The emotional oddball task has been well validated in segregating the neural responses of the emotional and executive systems by a number of studies (Fichtenholtz et al. 2004; Pannu Hayes et al. 2009; Wang et al. 2005, 2008b; Yamasaki et al. 2002). The stimuli and design of the visual emotional oddball task were identical to those described previously (Wang et al. 2005). Briefly, there were four types of grayscale pictures: (1) attentional targets (circles of varying sizes and luminance), (2) sad distractors, (3) neutral distractors and (4) standard stimuli (phase-scrambled pictures of distractors). All of the distractors were trial unique. The presentation frequency for targets, sad distractors and neutral distractors was 3.33% each, with scrambled pictures comprising the remaining 90% of stimuli. The imaging session consisted of 10 runs, each containing 150 stimuli (stimulus duration = 1500 ms, inter-stimulus interval = 2000 ms). The interval between successive rare stimuli (targets and/or distractors) was randomized between 18 and 20 s to allow hemodynamic responses to return to the baseline.

Participants pressed a response button using their right index finger upon detection of a target oddball stimulus. Participants were asked to rate the distractors on Likert-type scales of sadness/happiness immediately after scanning (Wang et al. 2005). The analysis for the sad and neutral events was performed on pictures that had been recorded on the basis of each subject's subjective rating (Wang et al. 2005). The oddball target is a classic task that involves executive function (Huettel & McCarthy 2004; Kirino et al. 2000; McCarthy et al. 1997). The sad stimuli serving as distractors without a task requirement have evoked deactivation instead of activation in the executive system (Fichtenholtz et al. 2004; Pannu Hayes et al. 2009; Wang et al. 2008b).

Image acquisition and analysis

Functional images were acquired on a 4.0-Tesla GE scanner (Milwaukee, WI, USA) with identical acquisition parameters as described by Wang et al. (2005). Briefly, oblique spoiled gradient-recalled acquisition images (three-dimensional, whole-brain) were acquired parallel to the anterior commissure (AC) – posterior commissure (PC) plane for high-resolution T1-weighted structural images with a matrix of 256 × 256 × 68 and slice thickness of 1.9 mm. Inward spiral gradient images were acquired with the following parameters: TR = 2000 ms, TE = 31 ms, FOV = 24 cm, flip angle = 90°, matrix = 64 × 64 × 34 and slice thickness = 3.75 mm with 3.75 mm3 isotropic voxels. Image preprocessing was conducted using temporal realignment for interleaved slice acquisition and spatial realignment to adjust for motion using affine transformation routines implemented in SPM99 (Wellcome Department of Cognitive Neurology, London, UK). We used an older version of statistical parametric mapping (SPM) to be consistent with our previous studies on this task. The realigned images were coregistered to the anatomical images obtained for each participant and normalized to SPM's template image, which conforms to the Montreal Neurologic Institute's standardized brain space. The functional data were spatially smoothed with an 8-mm isotropic Gaussian kernel before statistical analysis.

Both the voxelwise and region-of-interest (ROI) analyses were conducted using custom MATLAB scripts (Dolcos & McCarthy 2006; Wang et al. 2006). Event epochs (sad, neutral and target) that were time locked to the onset of each event were extracted from 4 s before to 20 s after the presence of the stimulus. Voxelwise signal percentage change at each event time point was calculated for each subject after subtracting pre-stimulus baseline activity (from −4 s to 0 s). The voxelwise statistical t maps at each time point were computed using within-group random-effect analyses for each event thresholded at P < 0.05 (FDR-corrected) with a spatial extent of five contiguous voxels. The between-group analyses were conducted only within those voxels whose peak activation/deactivation to either of the events was significant in the within-group analyses, and their hemodynamic responses were significantly correlated with the canonical gamma hemodynamic response. Given the fact that the activations to each stimulus were peaked at 6–8 s poststimulus, averaged signal percentage changes at 6–8 s poststimulus were used for the final within- and between-group analyses and are referred to as peak mean activation in the following text.

We examined the genetic impact on brain activation to sad, neutral and target independently. We conducted voxelwise whole-brain analyses using (1) a linear regression model on 5-HTTLPR (S/S, S/L and L/L) using contrast weight (1, 0, −1) to examine the impact of S dosage effect; (2) a two-sample t test to examine the difference between BDNF Val/Val carries with BDNF Met/Val carriers (there were no subjects carrying Met/Met in our sample) and (3) S & Met allele carriers vs. non-(S & Met) carriers for the interaction effect of the two genes. To reject the alternative hypothesis, analyses on the alternative combination, S & Val/Val allele carriers vs. non-(S & Val/Val) carriers, were also conducted. All the analyses were thresholded at P < 0.001 (FDR-corrected) with a spatial extent of five contiguous voxels.

To further illustrate the voxelwise findings, an ROI analysis was conducted using independent clusters that showed a significant group effect in the whole-brain analyses. Activation strength to sad and target stimuli in each ROI was computed, and group comparisons were conducted using two-sample t tests to confirm the results of whole-brain analyses. The significance level was threshold at P < 0.05.

Results

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

Clinical profiles and genotyping

The distribution of the 5-HTTLPR genotypes for all subjects [S/S (23%), S/L (52.6%) and L/L (26.3%)] did not deviate from Hardy Weinberg proportions (χ2 = 0.12, df = 2, P = 0.94). Among the 38 subjects, 4 subjects did not have BDNF genetic data; therefore, there were 34 subjects who had both 5-HTTLPR and BDNF measures. Among them, 12 subjects had Met/Val (38%) and 22 had Val/Val (62%), with no Met/Met homozygotes (0%) in this sample, which did not deviate from Hardy Weinberg proportions (χ2 = 1.56, df = 2, P = 0.46). The demographic profiles of the participants are shown in Table 1. There were no significant differences in demographic parameters between the remitted MDD and healthy control groups in either age, gender, education, race or distribution of either the 5-HTTLPR genotypes or the BDNF genotypes, except a trend of higher MADRS score as the increase of numbers of 5-HTTLPR L alleles (F2,35 = 3.11, P = 0.06). Given that we previously have reported group differences between control and remitted MDD on neural response during this emotional oddball task, in this study, we combined the two groups when we examine the genetic impact.

Table 1.  Profile of participants by genetic variants
 5-HTTLPR (n = 38)BDNF (n = 34)*
S/S (n = 8)L/S (n = 20)L/L (n = 10) χ 2 or anovaMet/Val (n = 12)Val/Val (n = 22) χ 2 or two-sample t test
  1. anova, analysis of variance.

  2. *Four subjects did not have BDNF genotyping, therefore, there were 34 subjects who had both 5-HTTLPR and BDNF genetic data.

Gender (female/male)5/38/126/4 χ 2 = 1.70, df = 26/612/10 χ 2 = 0.06, df = 1
     P = 0.43   P = 0.80
No. of remitted/control4/48/126/4 χ 2 = 1.10, df = 27/58/14 χ 2 = 1.52, df = 1
     P = 0.58   P = 0.22
Age in years (SD)73.4 (4.0)72.3 (5.1)71.1 (6.8) F 2,35 = 0.5170.7 (3.7)70.8 (13.5) t 32 = 0.04
     P = 0.60   P = 0.97
Education in years (SD)16.8 (2.2)17.2 (1.9)15.9 (2.0) F 2,35 = 0.9416.9 (1.9)16.1 (4.0) t 32 = 0.68
     P = 0.40   P = 0.50
No. of subjects with antidepressants/ non-antidepressant2/68/126/4 χ 2 = 2.31, df = 25/78/14 χ 2 = 0.09, df = 1
     P = 0.32   P = 0.76
MADRS (SD)1.3 (1.6)2.1 (1.9)4.4 (4.7) F 2,35 = 3.113.2 (4.0)2.2 (2.7) t 32 = 0.91
     P = 0.06   P = 0.37

fMRI results

Replicating our previous studies (Wang et al. 2008a,b), sad distractors evoked the emotional system including the amygdala, fusiform gyrus, visual cortex and occipito-temporal conjunction area, the ventrolateral prefrontal cortex (vlPFC), the orbital frontal cortex (OFC), the anterior medial prefrontal cortex (mPFC) and the superior temporal cortex. The target stimuli evoked the executive system including bilateral dorsolateral prefrontal cortex (dlPFC), dorsal anterior cingulate cortex (dACC), anterior portion of the posterior cingulate cortex (aPCC), supramarginal gyrus, insula, thalamus, and cerebellum.

The group differences on the neural response to sad and attentional targets between remitted and healthy groups were reported earlier (Wang et al. 2008a). Briefly, there was no significant difference in brain responses to sad stimuli between remitted and healthy control subjects. However, the remitted group showed significantly reduced activation in response to attentional targets in the dACC, aPCC and supramarginal gyrus area (Wang et al. 2008a). While we addressed the genetic effect by combining all subjects in the analyses below, we acknowledged the potential group impact in the discussion.

Impact of 5-HTTLPR S allele on brain activation to sad stimuli

The linear regression analysis comparing activation among 5-HTTLPR genotypes (S/S, S/L and L/L) revealed that only the left amygdala showed a linear change of activation to sad stimuli (Fig. 1, upper left image). Extracting the significant cluster in the left amygdala as a ROI, the general linear model analysis confirmed that amygdala activation to sad stimuli increased with increasing numbers of S alleles (Fig. 1, upper bar graph, F2,35 = 5.21, P = 0.01, post hoc Bonferroni t test revealed a significant difference among the three groups with P < 0.05 for each comparison). There were no significant differences in any region of the brain in response to targets among the S/S, S/L and L/L genotypes.

image

Figure 1. Main effect of 5-HTTLPR S allele and BDNF Met allele. Upper left, whole-brain voxelwise analysis revealed a linear increase in activation in the left amygdala to sad distractors in 5-HTTLPR L/L and S/L to S/S allele carriers. The upper right bar is the ROI analysis in the left amygdala. *Indicates significant differences of the ROI analyses (P < 0.05 in both the general linear model analyses across the groups and post hoc Bonferroni test analyses between groups). Lower left, whole brain voxelwise two-sample t-test analysis revealed significantly increased activation to sad distractors in bilateral dorsolateral prefrontal cortex (dlPFC) and dorsomedial prefrontal cortex (dmPFC) in the BDNF Met/Val allele carriers compared to the Val/Val carriers. The lower right bar graphs illustrate the ROI analysis results in the right dlPFC. The BDNF Met/Val allele carriers demonstrated increased activation to sad and decreased activation to target stimuli in this region. *Indicates significant differences between the two groups (P < 0.05 for two-sample t test between groups).

Download figure to PowerPoint

Impact of Met allele on brain activation to sad and target stimuli

Compared with BDNF Val/Val carriers, Met/Val carriers had significantly increased activation to sad stimuli in bilateral dlPFC, bilateral dorsomedial prefrontal cortex (dmPFC), left orbitofrontal/insula, bilateral posterior cingulate (PCC), right supramarginal gyrus, left inferior and middle temporal cortex, and right globus pallidus regions. Some of these regions such as dlPFC and supramarginal gyrus typically showed activation to target stimuli and deactivation to emotional distractors in healthy subjects in our previous studies (Wang et al. 2005, 2008b). The ROI analysis on these regions revealed that the Met/Val allele carriers showed greater activation to sad stimuli instead of deactivation (Fig. 1, low right bar graph, two-sample t test, t32 = 2.40, P = 0.02).

Compared with the BDNF Val/Val carriers, the Met/Val carriers had significantly decreased activation to target stimuli in the left dlPFC, left inferior parietal cortex, right hippocampus/parahippocampus and right insula areas (Table 2). The ROI analysis on these regions confirmed decreased activation in the Met/Val allele carriers relative to the Val/Val carriers. Although not found in the voxelwise analysis, the ROI analysis on the right dlPFC exhibited significantly decreased activation to targets in the Met/Val allele carriers relative to the Val/Val carriers (Fig. 2, bar graph on the right side, two-sample t test, t32 = 2.14, P = 0.046). The right dlPFC ROI was the significant cluster, which showed increased activation to sad stimuli in the Met/Val carrier relative to Val/Val allele carriers.

Table 2.  Regions that revealed significant difference in brain activation to sad and target stimuli among participants carrying different genetic variants
Group contrasts categorized by genetic variantsStimuliRegionsBrodmann areaPeak t valuePeak voxel
XMNIYMNIZMNI
  1. anova, analysis of variance.

5-HTTLRP
S/S > L/S > L/L (anova)SadLeft amygdala  F = 13.3−24−4−23
BDNF
Met/Val > Val/Val (two-sample t test)SadLeft dorsolateral prefrontalBA96.3−421439
  Right dorsolateral prefrontalBA95.8353528
  Left dorsomedial prefrontalBA65.0−72842
  Right dorsomedial prefrontalBA65.242849
  Left orbitofrontal/insulaBA135.9−421111
  Left posterior cingulateBA316.5−7−1846
  Right mid-posterior cingulateBA245.811−1435
  Right supramarginal cortexBA404.935−4239
  Left inferior temporalBA208.0−60−28−21
  Left middle temporalBA216.6−63−25−7
  Right globus pallidus 4.821−11−7
Met/Val < Val/Val (two-sample t test)TargetLeft dorsolateral prefrontalBA86.4−422845
  Left inferior parietalBA407.3−56−4152
  Right hippocampus/parahippocampus 6.027−14−11
  Right insula 6.232−118
Interaction effect
(S & Met) > non-(S & Met) (two-sample t test)SadLeft dorsolateral prefrontalBA93.8−461135
  Right dorsolateral prefrontalBA93.2353228
  Left orbitofrontal/insulaBA474.2−2514−14
  Left subgenual cingulateBA253.2−1121−14
  Right posterior cingulateBA314.011−1846
  Left posterior cingulateBA313.6−11−2846
  Right supramarginal gyrusBA403.746−3942
image

Figure 2. The effect of carrying both 5-HTTLPR S allele and BDNF Met allele on brain activation in response to sad stimuli. The brain image shows increased activation to sad stimuli in the left subgenual cingulate (sgACC, upper left) and posterior cingulate (PCC, lower left) in the (S & Met) combination group compared with the non-(S & Met) group. The right bar graphs illustrate the results from the ROI analyses on these regions. *Indicates significant differences between groups (P < 0.05 for two-sample t test between groups).

Download figure to PowerPoint

Examination of potential epistatic effects

In initial tests for epistasis, we first combined those who had at least one S allele of the 5-HTTLPR gene and one Met allele of the BDNF gene, the S & Met group (n = 8, 4 remitted and 4 healthy subjects), and compared them to the remainder of subjects, the non-(S & Met) group (n = 26, 8 remitted and 14 healthy subjects) in their brain activation to sad stimuli and attentional targets. Compared with the non-(S & Met) group, the S & Met group showed significantly greater activation to sad stimuli in the subgenual cingulate (sgACC), the PCC, right lingual gyrus and the left cerebellum (Fig. 2) and the results were confirmed by ROI analyses to sad stimuli (two-sample t test, sgACC, t32 = 2.20, P = 0.04; PCC, t32 = 2.63, P = 0.01). There was no significant difference in activation in response to targets between the non-(S & Met) and the S & Met groups.

We also performed the same analyses combining those who had at least one S allele of the 5-HTTLPR gene and the homozygous Val/Val allele of the BDNF genes, the S & Val/Val group (n = 17, 6 remitted and 12 healthy subjects), and compared them to the other subjects, the non-(S & Val/Val) group (n = 17, 9 remitted and 8 healthy subjects). We did not find significant differences between the alternative two pairings in brain activation in response to either sad or target stimuli.

Discussion

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

We found that the 5-HTTLPR S allele carriers had exaggerated amygdala activation to sad stimuli without alteration in neural responses during target detection. Met allele carriers showed increased activation when processing sad information and decreased activation during target detection in the dlPFC and dmPFC, regions typically associated with cognitive processing (Wang et al. 2005). Furthermore, those carrying both the S allele of the 5-HTTLPR gene and Met allele of the BDNF gene had stronger activation to sad stimuli in the PCC and the subgenual cingulate than those who did not carry both genetic variants. On the other hand, there was no significant group difference in the S & Val/Val allele carriers compared with non-(S & Val/Val) carriers. Taken together, the results indicate that the Met allele of the BDNF gene rather than the Val allele is associated with affective and executive dysfunction, which might increase vulnerability to depression.

Our finding that the 5-HTTLPR S allele carriers had hyperactivity to sad stimuli in the amygdala, a key structure of the ‘emotional system’, is consistent with majority of studies in the literature (Bertolino et al. 2005; Hariri et al. 2002, 2005; Munafo et al. 2008). Some studies argued that the strong amgydala activation in the S allele carriers was because of reduced activation to neutral stimuli rather than increased activation to negative stimuli (Canli et al. 2005a; Heinz et al. 2007). Heinz and colleagues (2007) found increased amygdala activation to fixation vs. neutral contrast in the S allele carriers and they emphasized that a passively resting baseline might increase anxiety as an aversive stimuli to the S allele carriers. In this study, the baseline was phase-scrambled pictures. Relative to this baseline, we did not find decreased activation to neutral stimuli in the S allele carriers (Fig. 1, the bar graph), and the increased amygdala activation was specific to sad stimuli. Previous studies used threatening pictures (Bertolino et al. 2005), mixed emotional pictures (Hariri et al. 2002) or negative words (Canli et al. 2005b) as emotional stimuli. Our study extended these previous findings to sad emotion in older subjects with S allele polymorphism.

Literature examining the association between 5-HTTLPR genetic variants and neural function was primarily focused on responses to negative stimuli. The predominant findings of studies are increased amygdala activation and amygdala-vmPFC (ventromedial prefrontal cortex) connectivity (Pezawas et al. 2005), along with increased perfusion in the amygdala and vmPFC during resting state in one study (Rao et al. 2007). Studies of S allele carriers in MDD also found increased amygdala activation when perceiving masked (Dannlowski et al. 2008) or non-masked emotional pictures (Dannlowski et al. 2007; Gillihan et al. 2011). Studies examining whether the 5-HTTLPR genetic variants affect the executive system are rare. In this study, we investigated the modulation effect of 5-HTTLPR genetic variants on neural responses during both emotional and executive processing. We found that the S/S, S/L and L/L genotypes were not different in response to attentional targets. These results suggest that S-allele-associated genetic vulnerability predominantly influences the affective system rather than the executive system.

Consistent with studies reporting decreased hippocampal volume and function, we found decreased activation of targets in the Met allele carriers in the right hippocampus/parahippocampus region. The studies on emotional processing in BDNF Met allele carriers reported increased activation in the amygdala during an affective startle reflex paradigm (Montag et al. 2008); increased activation in the anterior cingulate, brainstem and insula during fear processing (Mukherjee et al. 2011); and decreased activation in the orbitofrontal cortex, striatum and amygdala to negative stimuli (Gasic et al. 2009). Similarly, we found an increased response to sad distractors but a decreased response to targets in the dlPFC and dmPFC in Met allele carriers relative to the Val homozygous carriers. The dlPFC typically shows deactivation during a ‘passive viewing’ task (Wang et al. 2005, 2008b; Yamasaki et al. 2002). Activation, instead of deactivation, to sad stimuli in the dlPFC and dmPFC in the Met allele carriers suggests increased cognitive processing rather than passively processing sad emotional information. The dmPFC has been related to self-referential processing or an implicit cognitive aspect of emotional processing such as judgment of emotion (Northoff & Bermpohl 2004) or attentional modulation of emotion (Bermpohl et al. 2006; Northoff et al. 2006). Therefore, the Met allele carriers might have initiated a cognitive coping strategy to actively deal with sad distractors, which might have been more distracting to them compared to the Val/Val carriers, while passively viewing sad stimuli. The altered activation to both sad and target stimuli suggest that the Met allele can alter neural function in both emotional and executive systems, which predisposes individuals to MDD.

While 5-HTTLPR S alleles increased activation to sad stimuli in the amygdala, a combination of the BDNF Met with 5-HTTLPR S alleles increased activation in broader regions including the sgACC and PCC, regions that are critically associated with depression (Drevets 2001; Mayberg 2009). The result is not surprising because BDNF Met may exacerbate monoamine deficiencies at the genetic level (Ren-Patterson et al. 2005) and enhance hyperactivity in the emotional system because of executive dysfunction at the neural level when 5-HTTLPR S allele is present. This is consistent with the genome-wide association (GWA) study, which revealed that individuals carrying 5-HTTLPR S/S and the BDNF Met variants scored high on neuroticism (Terracciano et al. 2010). It is also consistent with the findings that individuals carrying the S/S and BDNF Met genes had the highest depression scores (Kaufman et al. 2006; Kim et al. 2007; Wichers et al. 2008) and high rumination in life stress (Clasen et al. 2011). Therefore, our results support the hypothesis that the combination of the BDNF Met with 5-HTTLPR S genes increases one's risk for depression, which opposes the alternative explanation that it has a protective effect on depression (Martinowich & Lu 2008; Pezawas et al. 2008).

One counterintuitive finding in our study was the trend of greater degree of residual symptoms (high MADRS score) as the increase in numbers of 5-HTTLPR L alleles, although importantly this trend did not achieve statistical significance. Notably, all our subjects were in a fully remitted state; thus, our results do not reflect the degree of antidepressant response but could be related to residual symptoms. One potential explanation for this trend is that remitted L/L allele carriers may be at increased risk for residual depressive symptoms than are S/S allele carriers. However, to our knowledge there is no evidence from the literature supporting this theory. Carefully designed studies are needed to further address this issue.

The significant limitation of this study is the sample size, which does not allow us to separate our study sample into remitted and control groups in order to further investigate an interaction or mediation effect between the BDNF Val66Met and 5-HTTLPR genetic variants. Given that the significant differences between the remitted and control groups in our previous study (i.e. decreased activation in the remitted group in the dACC and aPCC to attentional targets (Wang et al. 2008a) were not overlapping the findings of the genetic variants reported here, it is less likely that our results were dominantly affected by depression history. Another limitation of this study is mixed medication in some remitted subjects. We did not find significant medication difference neither (Table 1) among the S/S, S/L and L/L genotype groups nor between the BDNF Met/Val and Val/Val carrier groups, which can partially cancel out the medication effect on brain activation. Although not always found, generally speaking antidepressants reduce activation in the amygdala and increase activation in the dlPFC (Robertson et al. 2007; Siegle et al. 2007). Therefore, one might expect stronger results if all subjects were not medicated with antidepressants. Nevertheless, future studies are needed in large samples free of medication.

It is also noteworthy that we did not find any difference in task performance among genetic variants during conducting the emotional oddball task. Also, we could not prove that the changes in the emotional and executive systems increased susceptibility to depression from our study. The increased susceptibility to depression that we discussed above was only based on changes in neural activation, and those with risk genes had changed activation in the same direction as those with depression. Future studies using more mental challenging tasks to evoke executive dysfunction and longitudinally following up on risk-gene carriers are needed to confirm whether activation changes in the emotional and executive systems confers increased vulnerability to depression.

In summary, results from our current study suggest that the Met allele rather than Val allele is possibly a risk gene for depression. Furthermore, our results also indicate that a combination of the S allele of the 5-HTTLPR gene and Met allele of the BDNF genotypes may have increased depression vulnerability supported by exaggerated activation in the PCC and the subgenual cingulate in response to sad stimuli. Future studies comparing sad and fearful or anger stimuli might further elucidate the genetic impact on neural function related to depression vs. anxiety disorders.

References

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  • Bermpohl, F., Pascual-Leone, A., Amedi, A., Merabet, L.B., Fregni, F., Gaab, N., Alsop, D., Schlaug, G. & Northoff, G. (2006) Attentional modulation of emotional stimulus processing: an fMRI study using emotional expectancy. Hum Brain Map 27, 662677.
  • Bertolino, A., Arciero, G., Rubino, V., Latorre, V., De Candia, M., Mazzola, V., Blasi, G., Caforio, G., Hariri, A., Kolachana, B., Nardini, M., Weinberger, D.R. & Scarabino, T. (2005) Variation of human amygdala response during threatening stimuli as a function of 5’HTTLPR genotype and personality style. Biol Psychiatry 57, 15171525.
  • Brummett, B.H., Muller, C.L., Collins, A.L., Boyle, S.H., Kuhn, C.M., Siegler, I.C., Williams, R.B. & Ashley-Koch, A. (2008) 5-HTTLPR and gender moderate changes in negative affect responses to tryptophan infusion. Behav Genet 38, 476483.
  • Canli, T., Cooney, R.E., Goldin, P., Shah, M., Sivers, H., Thomason, M.E., Whitfield-Gabrieli, S., Gabrieli, J.D. & Gotlib, I.H. (2005a) Amygdala reactivity to emotional faces predicts improvement in major depression. Neuroreport 16, 12671270.
  • Canli, T., Omura, K., Haas, B.W., Fallgatter, A., Constable, R.T. & Lesch, K.P. (2005b) Beyond affect: a role for genetic variation of the serotonin transporter in neural activation during a cognitive attention task. Proc Natl Acad Sci U S A 102, 1222412229.
  • Caspi, A., Sugden, K., Moffitt, T.E., Taylor, A., Craig, I.W., Harrington, H., Mcclay, J., Mill, J., Martin, J., Braithwaite, A. & Poulton, R. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301, 386389.
  • Chen, Z.Y., Patel, P.D., Sant, G., Meng, C.X., Teng, K.K., Hempstead, B.L. & Lee, F.S. (2004) Variant brain-derived neurotrophic factor (BDNF) (Met66) alters the intracellular trafficking and activity-dependent secretion of wild-type BDNF in neurosecretory cells and cortical neurons. J Neurosci 24, 44014411.
  • Chen, Z.Y., Jing, D., Bath, K.G., Ieraci, A., Khan, T., Siao, C.J., Herrera, D.G., Toth, M., Yang, C., Mcewen, B.S., Hempstead, B.L. & Lee, F.S. (2006) Genetic variant BDNF (Val66Met) polymorphism alters anxiety-related behavior. Science 314, 140143.
  • Clasen, P.C., Wells, T.T., Knopik, V.S., Mcgeary, J.E. & Beevers, C.G. (2011) 5-HTTLPR and BDNF Val66Met polymorphisms moderate effects of stress on rumination. Genes Brain Behav 10, 740746.
  • Dannlowski, U., Ohrmann, P., Bauer, J., Kugel, H., Baune, B.T., Hohoff, C., Kersting, A., Arolt, V., Heindel, W., Deckert, J. & Suslow, T. (2007) Serotonergic genes modulate amygdala activity in major depression. Genes Brain Behav 6, 672676.
  • Dannlowski, U., Ohrmann, P., Bauer, J., Deckert, J., Hohoff, C., Kugel, H., Arolt, V., Heindel, W., Kersting, A., Baune, B.T. & Suslow, T. (2008) 5-HTTLPR biases amygdala activity in response to masked facial expressions in major depression. Neuropsychopharmacology 33, 418424.
  • Disner, S.G., Beevers, C.G., Haigh, E.A. & Beck, A.T. (2011) Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci 12, 467477.
  • Dolcos, F. & McCarthy, G. (2006) Brain systems mediating cognitive interference by emotional distraction. J Neurosci 26, 20722079.
  • Drevets, W.C. (2001) Neuroimaging and neuropathological studies of depression: implications for the cognitive-emotional features of mood disorders. Curr Opin Neurobiol 11, 240249.
  • Egan, M.F., Kojima, M., Callicott, J.H., Goldberg, T.E., Kolachana, B.S., Bertolino, A., Zaitsev, E., Gold, B., Goldman, D., Dean, M., Lu, B. & Weinberger, D.R. (2003) The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 112, 257269.
  • Fichtenholtz, H.M., Dean, H.L., Dillon, D.G., Yamasaki, H., McCarthy, G. & Labar, K.S. (2004) Emotion-attention network interactions during a visual oddball task. Brain Res Cogn Brain Res 20, 6780.
  • Frustaci, A., Pozzi, G., Gianfagna, F., Manzoli, L. & Boccia, S. (2008) Meta-analysis of the brain-derived neurotrophic factor gene (BDNF) Val66Met polymorphism in anxiety disorders and anxiety-related personality traits. Neuropsychobiology 58, 163170.
  • Gasic, G.P., Smoller, J.W., Perlis, R.H., Sun, M., Lee, S., Kim, B.W., Lee, M.J., Holt, D.J., Blood, A.J., Makris, N., Kennedy, D.K., Hoge, R.D., Calhoun, J., Fava, M., Gusella, J.F. & Breiter, H.C. (2009) BDNF, relative preference, and reward circuitry responses to emotional communication. Am J Med Genet B Neuropsychiatr Genet 150B, 762781.
  • Gatt, J.M., Nemeroff, C.B., Dobson-Stone, C., Paul, R.H., Bryant, R.A., Schofield, P.R., Gordon, E., Kemp, A.H. & Williams, L.M. (2009) Interactions between BDNF Val66Met polymorphism and early life stress predict brain and arousal pathways to syndromal depression and anxiety. Mol Psychiatry 14, 681695.
  • Gillihan, S.J., Rao, H., Brennan, L., Wang, D.J., Detre, J.A., Sankoorikal, G.M., Brodkin, E.S. & Farah, M.J. (2011) Serotonin transporter genotype modulates the association between depressive symptoms and amygdala activity among psychiatrically healthy adults. Psychiatry Res 193, 161167.
  • Hariri, A.R., Mattay, V.S., Tessitore, A., Kolachana, B., Fera, F., Goldman, D., Egan, M.F. & Weinberger, D.R. (2002) Serotonin transporter genetic variation and the response of the human amygdala. Science 297, 400403.
  • Hariri, A.R., Goldberg, T.E., Mattay, V.S., Kolachana, B.S., Callicott, J.H., Egan, M.F. & Weinberger, D.R. (2003) Brain-derived neurotrophic factor val66met polymorphism affects human memory-related hippocampal activity and predicts memory performance. J Neurosci 23, 66906694.
  • Hariri, A.R., Drabant, E.M., Munoz, K.E., Kolachana, B.S., Mattay, V.S., Egan, M.F. & Weinberger, D.R. (2005) A susceptibility gene for affective disorders and the response of the human amygdala. Arch Gen Psychiatry 62, 146152.
  • Heinz, A., Smolka, M.N., Braus, D.F., Wrase, J., Beck, A., Flor, H., Mann, K., Schumann, G., Buchel, C., Hariri, A.R. & Weinberger, D.R. (2007) Serotonin transporter genotype (5-HTTLPR): effects of neutral and undefined conditions on amygdala activation. Biol Psychiatry 61, 10111014.
  • Huettel, S.A. & McCarthy, G. (2004) What is odd in the oddball task? Prefrontal cortex is activated by dynamic changes in response strategy. Neuropsychologia 42, 379386.
  • Kanellopoulos, D., Gunning, F.M., Morimoto, S.S., Hoptman, M.J., Murphy, C.F., Kelly, R.E., Glatt, C., Lim, K.O. & Alexopoulos, G.S. (2011) Hippocampal volumes and the brain-derived neurotrophic factor val66met polymorphism in geriatric major depression. Am J Geriatr Psychiatry 19, 1322.
  • Kaufman, J., Yang, B.Z., Douglas-Palumberi, H., Grasso, D., Lipschitz, D., Houshyar, S., Krystal, J.H. & Gelernter, J. (2006) Brain-derived neurotrophic factor-5-HTTLPR gene interactions and environmental modifiers of depression in children. Biol Psychiatry 59, 673680.
  • Kim, J.M., Stewart, R., Kim, S.W., Yang, S.J., Shin, I.S., Kim, Y.H. & Yoon, J.S. (2007) Interactions between life stressors and susceptibility genes (5-HTTLPR and BDNF) on depression in Korean elders. Biol Psychiatry 62, 423428.
  • Kirino, E., Belger, A., Goldman-Rakic, P. & McCarthy, G. (2000) Prefrontal activation evoked by infrequent target and novel stimuli in a visual target detection task: an event-related functional magnetic resonance imaging study. J Neurosci 20, 66126618.
  • Lesch, K.P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg, B.D., Petri, S., Benjamin, J., Muller, C.R., Hamer, D.H. & Murphy, D.L. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274, 15271531.
  • Levinson, D.F. (2006) The genetics of depression: a review. Biol Psychiatry 60, 8492.
  • Martinowich, K. & Lu, B. (2008) Interaction between BDNF and serotonin: role in mood disorders. Neuropsychopharmacology 33, 7383.
  • Mayberg, H.S. (1997) Limbic-cortical dysregulation: a proposed model of depression. J Neuropsychiatry Clin Neurosci 9, 471481.
  • Mayberg, H.S. (2009) Targeted electrode-based modulation of neural circuits for depression. J Clin Invest 119, 717725.
  • Mccarthy, G., Luby, M., Gore, J. & Goldman-Rakic, P. (1997) Infrequent events transiently activate human prefrontal and parietal cortex as measured by functional MRI. J Neurophysiol 77, 16301634.
  • Montag, C., Reuter, M., Newport, B., Elger, C. & Weber, B. (2008) The BDNF Val66Met polymorphism affects amygdala activity in response to emotional stimuli: evidence from a genetic imaging study. Neuroimage 42, 15541559.
  • Montgomery, S.A. & Asberg, M. (1979) A new depression scale designed to be sensitive to change. Br J Psychiatry 134, 382389.
  • Mukherjee, P., Whalley, H.C., Mckirdy, J.W., Mcintosh, A.M., Johnstone, E.C., Lawrie, S.M. & Hall, J. (2011) Effects of the BDNF Val66Met polymorphism on neural responses to facial emotion. Psychiatry Res 191, 182188.
  • Munafo, M.R., Brown, S.M. & Hariri, A.R. (2008) Serotonin transporter (5-HTTLPR) genotype and amygdala activation: a meta-analysis. Biol Psychiatry 63, 852857.
  • Northoff, G. & Bermpohl, F. (2004) Cortical midline structures and the self. Trends Cogn Sci 8, 102107.
  • Northoff, G., Grimm, S., Boeker, H., Schmidt, C., Bermpohl, F., Heinzel, A., Hell, D. & Boesiger, P. (2006) Affective judgment and beneficial decision making: ventromedial prefrontal activity correlates with performance in the Iowa Gambling Task. Hum Brain Mapp 27, 572587.
  • Pannu Hayes, J., Labar, K.S., Petty, C.M., McCarthy, G. & Morey, R.A. (2009) Alterations in the neural circuitry for emotion and attention associated with posttraumatic stress symptomatology. Psychiatry Res 172, 715.
  • Pezawas, L., Verchinski, B.A., Mattay, V.S., Callicott, J.H., Kolachana, B.S., Straub, R.E., Egan, M.F., Meyer-Lindenberg, A. & Weinberger, D.R. (2004) The brain-derived neurotrophic factor val66met polymorphism and variation in human cortical morphology. J Neurosci 24, 1009910102.
  • Pezawas, L., Meyer-Lindenberg, A., Drabant, E.M., Verchinski, B.A., Munoz, K.E., Kolachana, B.S., Egan, M.F., Mattay, V.S., Hariri, A.R. & Weinberger, D.R. (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nat Neurosci 8, 828834.
  • Pezawas, L., Meyer-Lindenberg, A., Goldman, A.L., Verchinski, B.A., Chen, G., Kolachana, B.S., Egan, M.F., Mattay, V.S., Hariri, A.R. & Weinberger, D.R. (2008) Evidence of biologic epistasis between BDNF and SLC6A4 and implications for depression. Mol Psychiatry 13, 709716.
  • Rao, H., Gillihan, S.J., Wang, J., Korczykowski, M., Sankoorikal, G.M., Kaercher, K.A., Brodkin, E.S., Detre, J.A. & Farah, M.J. (2007) Genetic variation in serotonin transporter alters resting brain function in healthy individuals. Biol Psychiatry 62, 600606.
  • Ren-Patterson, R.F., Cochran, L.W., Holmes, A., Sherrill, S., Huang, S.J., Tolliver, T., Lesch, K.P., Lu, B. & Murphy, D.L. (2005) Loss of brain-derived neurotrophic factor gene allele exacerbates brain monoamine deficiencies and increases stress abnormalities of serotonin transporter knockout mice. J Neurosci Res 79, 756771.
  • Robertson, B., Wang, L., Diaz, M.T., Aiello, M., Gersing, K., Beyer, J., Mukundan, S. Jr., McCarthy, G. & Doraiswamy, P.M. (2007) Effect of bupropion extended release on negative emotion processing in major depressive disorder: a pilot functional magnetic resonance imaging study. J Clin Psychiatry 68, 261267.
  • Siegle, G.J., Thompson, W., Carter, C.S., Steinhauer, S.R. & Thase, M.E. (2007) Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: related and independent features. Biol Psychiatry 61, 198209.
  • Steele, J.D., Currie, J., Lawrie, S.M. & Reid, I. (2007) Prefrontal cortical functional abnormality in major depressive disorder: a stereotactic meta-analysis. J Affect Disord 101, 111.
  • Steffens, D.C., Svenson, I., Marchuk, D.A., Levy, R.M., Hays, J.C., Flint, E.P., Krishnan, K.R. & Siegler, I.C. (2002) Allelic differences in the serotonin transporter-linked polymorphic region in geriatric depression. Am J Geriatr Psychiatry 10, 185191.
  • Taylor, W.D., Zuchner, S., Mcquoid, D.R., Steffens, D.C., Speer, M.C. & Krishnan, K.R. (2007) Allelic differences in the brain-derived neurotrophic factor Val66Met polymorphism in late-life depression. Am J Geriatr Psychiatry 15, 850857.
  • Terracciano, A., Tanaka, T., Sutin, A.R., Deiana, B., Balaci, L., Sanna, S., Olla, N., Maschio, A., Uda, M., Ferrucci, L., Schlessinger, D. & Costa, P.T. Jr. (2010) BDNF Val66Met is associated with introversion and interacts with 5-HTTLPR to influence neuroticism. Neuropsychopharmacology 35, 10831089.
  • Verhagen, M., Van Der Meij, A., Van Deurzen, P.A., Janzing, J.G., Arias-Vasquez, A., Buitelaar, J.K. & Franke, B. (2010) Meta-analysis of the BDNF Val66Met polymorphism in major depressive disorder: effects of gender and ethnicity. Mol Psychiatry 15, 260271.
  • Wang, L., McCarthy, G., Song, A.W. & Labar, K.S. (2005) Amygdala activation to sad pictures during high-field (4 tesla) functional magnetic resonance imaging. Emotion 5, 1222.
  • Wang, L., Labar, K.S. & McCarthy, G. (2006) Mood alters amygdala activation to sad distractors during an attentional task. Biol Psychiatry 60, 11391146.
  • Wang, L., Krishnan, K.R., Steffens, D.C., Potter, G.G., Dolcos, F. & McCarthy, G. (2008a) Depressive state- and disease-related alterations in neural responses to affective and executive challenges in geriatric depression. Am J Psychiatry 165, 863871.
  • Wang, L., Labar, K.S., Smoski, M., Rosenthal, M.Z., Dolcos, F., Lynch, T.R., Krishnan, R.R. & McCarthy, G. (2008b) Prefrontal mechanisms for executive control over emotional distraction are altered in major depression. Psychiatry Res 163, 143155.
  • Wichers, M., Kenis, G., Jacobs, N., Mengelers, R., Derom, C., Vlietinck, R. & Van Os, J. (2008) The BDNF Val(66)Met x 5-HTTLPR x child adversity interaction and depressive symptoms: An attempt at replication. Am J Med Genet B Neuropsychiatr Genet 147B, 120123.
  • Yamasaki, H., Labar, K.S. & McCarthy, G. (2002) Dissociable prefrontal brain systems for attention and emotion. Proc Natl Acad Sci U S A 99, 1144711451.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Participants and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

This research was supported by the NIMH-sponsored Duke Silvio O. Conte Center for the Neuroscience of Depression (P50-MH60451) and NIMH grant R01 MH077745. L.W. is supported by the Paul B. Beeson Career Developmental Awards (K23-AG028982).

The authors declare no conflict of interests that appear to have any relevance to the topic covered in the submission.