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. Author manuscript; available in PMC: 2017 Sep 30.
Published in final edited form as: Psychiatry Res. 2016 Aug 8;255:81–86. doi: 10.1016/j.pscychresns.2016.08.002

Lack of Association Between the Serotonin Transporter and Serotonin 1A Receptor: an in vivo PET Imaging Study in Healthy Adults

Michael Strupp-Levitsky a, Jeffrey M Miller a,b,*, Harry Rubin-Falcone a,b, Francesca Zanderigo a,b, Matthew S Milak a,b, Gregory Sullivan a,b, R Todd Ogden a,c, Maria A Oquendo a,b, Christine DeLorenzo d, Norman Simpson a,b, Ramin V Parsey d, J John Mann a,b
PMCID: PMC5175477  NIHMSID: NIHMS812931  PMID: 27567324

Abstract

The serotonin neurotransmitter system is modulated in part by the uptake of synaptically released serotonin (5-HT) by the serotonin transporter (5-HTT), and by specific serotonin autoreceptors such as the somatodendritic 5-HT1A receptor, which can limit serotonin neuron depolarization. However, little is known about how 5-HTT and 5-HT1A are related in vivo. To study this question, we reanalyzed positron emission tomography (PET) data obtained earlier in 40 healthy participants (21 females) using [11C]WAY-100635 for quantification of 5-HT1A binding and [11C](+)-McN-5652 for quantification of 5-HTT binding. We hypothesized negative correlations between 5-HT1A binding in the raphe nuclei (RN) and 5-HTT binding in RN terminal field regions. Controlling for sex, no significant correlations were found (all p>0.05). Similarly, an exploratory analysis correlating whole-brain voxel-wise 5-HTT binding with 5-HT1A binding in RN identified no significant clusters meeting our a priori statistical threshold. The lack of correlation between 5-HT1A and 5-HTT binding observed in the current study may be due to the different temporal responsiveness of regulatory processes controlling the somatodendritic 5-HT1A receptor and 5-HTT in response to changing availability of intrasynaptic serotonin.

Keywords: serotonin, serotonin transporter, serotonin 1A receptor, PET

1. Introduction

Serotonin neurons project throughout the brain from the brainstem raphe nuclei (RN), modulating a diverse array of functions including mood, responses to stress, sex, appetite, and memory (Hensler, 2012). Serotonin neurotransmission is modulated by the serotonin transporter (5-HTT) through uptake of synaptically released serotonin (5-HT), and by specific serotonin autoreceptors such as the somatodendritic 5-HT1A receptor, which can limit serotonin neuron depolarization (Hensler, 2012). 5-HTT is located on nerve terminals and transports serotonin from the synaptic cleft and extracellular space into the nerve terminal (Hensler, 2012). 5-HTT protein levels are regulated by intra-synaptic levels of serotonin, because the rate of internalization of the transporter is slowed when it is bound by intra-synaptic serotonin (Hensler, 2012).

Serotonin cell bodies reside in the raphe nuclei in periaqueductal brainstem and have major projections to a broad array of cortical and subcortical structures (Hensler, 2012; Hornung, 2003; Hoyer et al., 2002; Vertes and Linley, 2007). The 5-HT1A receptor subtype is widely distributed in the mammalian brain (Hensler, 2012; Hornung, 2003), serving as a somatodendritic autoreceptor on the serotonergic cell bodies and dendrites in the brainstem raphe nuclei, and as a post-synaptic heteroreceptor in the terminal field on non-serotonergic neurons as a target of 5-HT neuron projections (Garcia-Garcia et al., 2014).

The 5-HT1A receptor and 5-HTT play important roles in the serotonin signaling, the 5-HT1A autoreceptor regulating serotonin neuron resting potential (and hence propensity to generate action potentials and release serotonin at the terminal fields), and 5-HTT mediating serotonin clearance (Hensler, 2012). We therefore sought to examine the relationship between the somatodendritic 5-HT1A autoreceptor and terminal field 5-HTT in vivo in healthy volunteers. We expected that greater density of 5-HT1A autoreceptors would result in reduced firing rates of serotonin neurons, and thereby decreased 5-HT release, which in turn would reduce mean 5-HTT availability for binding due to increased 5-HTT internalization. This model would suggest an inverse relationship between 5-HT1A autoreceptor binding in raphe nuclei and 5-HTT binding in the terminal fields.

Empirical studies investigating the relationship between 5-HT1A and 5-HTT report divergent findings. A postmortem study of brain samples from suicide victims found a negative correlation between 5-HT1A and 5-HTT binding within prefrontal cortex (Arango et al., 1995), consistent with the theoretical mechanism described above. A PET imaging genetics study found no relationship between a functional polymorphism in the 5-HT1A receptor gene promoter region [(−1018) C>G] (shown to be involved in regulating the transcription of 5-HT1A) and 5-HT1A binding, but observed lower 5-HT1A binding potential in all regions examined in short allele carriers of the a 5-HTT gene polymorphism (5-HTTLPR) (David et al., 2005), suggesting complex interactions between the genetic variation and protein expression across these two loci.

Animal studies have investigated 5-HTT/5-HT1A relationships using transgenic approaches. Monoamine oxidase-A (MAO-A) knockout mice, which have increased levels of extracellular 5-HT, exhibit downregulation of 5-HTT and a concurrent desensitization of 5-HT1A autoreceptors (Evrard et al., 2002). Studies of 5-HTT knockout mice have variably observed decreased 5-HT1A receptor mRNA levels and protein density in the dorsal raphe nuclei and hypothalamus; increased levels in the hippocampus, and no differences in other high-density projection areas (Alexandre et al., 2006; Fabre et al., 2000; Li et al., 1999). These studies suggest that the absence of 5-HTT may cause a complex pattern of differential responses in different subpopulations of 5-HT1A receptors.

In vivo human brain imaging studies examining the relationship between 5-HTT and 5-HT1A are also inconclusive. One study (Lundberg et al., 2007) used [11C]WAY-100635 for quantification of the 5-HT1A receptor and [11C]MADAM for quantification of 5-HTT and found a positive correlation between 5-HT1A and 5-HTT BPND in the raphe nuclei and the hippocampus but not in frontal cortical areas. Another study (Jovanovic et al., 2008) found 5-HT1A and 5-HTT BPND to be positively correlated only in hippocampus and only in women using [11C]WAY-100635 and [11C]MADAM. In contrast, a study of seventeen healthy male subjects found negative correlations between 5-HTT and 5-HT1A BPND within multiple brain regions (cingulate, insula, frontal, temporal and parietal cortices) using [11C]WAY-100635 and [11C]DASB (Takano et al., 2011). Another study (Bose et al., 2011) used [11C]WAY-100635 and [11C]DASB and found no intra-regional correlations after controlling for relevant covariates, but a positive correlation between [11C]WAY-100635 BPND in the raphe and [11C]DASB BPND in the superior temporal gyrus and insula. In summary, these studies observed positive, negative, and no correlations between in vivo 5-HTT and 5-HT1A binding using PET. Our model predicts a negative correlation.

In this manuscript, we have examined the relationship between 5-HT1A and 5-HTT binding in a large sample of forty healthy volunteers who underwent PET using [11C]WAY-100635 and [11C](+)-McN-5652 in a secondary analysis of previously published data (Parsey et al., 2006a; Parsey et al., 2006c). Based on our previous post-mortem findings and the theoretical model described above, we expected to find negative correlations between 5-HT1A in the raphe nuclei (RN) and 5-HTT in serotonergic projection areas: thalamus, hippocampus, caudate, amygdala, temporal lobe and insula. Prefrontal cortical regions were not included in this analysis, despite being serotonin projection areas, because quantification of transporter binding in these regions with [11C](+)-McN-5652 is not reliable due to inadequate signal-to-noise ratio.”. We also performed an exploratory voxel-wise whole-brain analysis to examine the relationship between 5-HT1A autoreceptor binding in the RN and 5-HTT binding throughout the brain.

2. Materials and methods

2.1. Subjects

Forty healthy volunteers (21 females; 19 males) who had no history of an Axis I or Axis II psychiatric disorder (including absence of current or past alcohol or substance abuse or dependence), no family history of a mood disorder or schizophrenia, no significant medical illness, free of all medications that may affect the brain or specifically the serotonin system, and aged 18–69 years (mean = 39 +/− 15) were included in this analysis. The Structured Clinical Interview for DSM-IV Axis I Disorders (non-patient version- SCID NP) (First et al., 2012), physical examination, routine blood tests, pregnancy test, urine toxicology, and electrocardiogram were used to evaluate study eligibility. Other exclusion criteria included lack of capacity to provide informed consent and pregnancy. The Institutional Review Board of the New York State Psychiatric Institute approved the protocol, and all subjects provided informed consent after an explanation of the study protocol and associated risks.

2.2. Radiochemistry and input function measurement

All subjects were scanned with both [11C]WAY-100635 (for quantification of 5-HT1A) and [11C](+)-McN-5652 (for quantification of 5-HTT) on the same day. For details of radiotracer preparation see (Parsey et al., 2000b) for [11C]WAY-100635 and (Frankle et al., 2004) for [11C](+)-McN-5652. A metabolite corrected arterial input function was obtained for both tracers (Parsey et al., 2000b). Plasma free fraction (fP) of [11C]-WAY-100635 was assayed in triplicate (Parsey et al., 2006b).

2.3. Image acquisition and analysis

All subjects underwent a T1-weighted magnetic resonance image (MRI) scan for identification of regions of interest (ROIs) and tissue segmentation into gray and white matter. T1 images were acquired with either a 1.5-T Signa Advantage or a 3-T Signa HDx (General Electric Medical Systems, Milwaukee, Wisconsin), at a resolution of 1.5 × .9 × 1.0 mm or 1.0 mm × 1.0 mm × 1.0 mm, respectively. PET images were acquired from an ECAT EXACT HR+ scanner (Siemens/CTI, Knoxville, Tennessee) as previously described (Parsey et al., 2000b). A 15-minute transmission scan was obtained, and injection of [11C]-WAY-100635 was followed by an emission scan of 110 minutes with 20 frames of increasing duration (3 × 20 s, 3 × 1 min, 3 × 2 min, 2 × 5 min, 9 × 10 min). After a break (mean break duration = 67 minutes, range = 28 to 129 minutes), subjects returned to the PET scanner and received a bolus injection of [11C](+)-McN-5652 followed by a 130-minute emission scan also using frames of increasing duration (3 × 20 s, 3 × 1 min, 3 × 2 min, 2 × 5 min, 11 × 10 min). One participant underwent [11C](+)-McN-5652 scanning prior [11C]-WAY-100635 scanning for logistical reasons, with a break of 91 minutes between scans. To correct for subject motion, PET frames were registered to the eighth frame using the FMRIB linear image registration tool (FLIRT), version 5.0 (FMRIB Image Analysis Group, Oxford, UK). An automated algorithm identified ROIs (amygdala, dorsal caudate, hippocampus, insula, thalamus, temporal cortex) as well as reference regions of cerebellar gray matter (CGM) for [11C](+)-McN-5652 and cerebellar white matter (CWM) for [11C]-WAY-100635 on individuals’ T1-weighted MRIs (Milak et al., 2010). The raphe nuclei ROI cannot be reliably identified on MRI images, so this region was labeled using a mask of the average location of the RN in 52 healthy subjects, which was created using [11C]-WAY-100635 voxel binding maps warped into standard space (Delorenzo et al., 2013). Each subject’s MRI was transformed into standard space using Advanced Normalization Tools (Avants et al., 2014), and the reverse transform was applied to the RN mask to bring it into MRI space. RN masks were then applied to the PET through the PET-to-MRI coregistration.

Each subject’s mean PET image was co-registered to their MRI using FLIRT, optimized as previously described (DeLorenzo et al., 2009). ROI maps superimposed on MRI and PET images for a sample subject are shown in supplemental figure 1. Time activity curves were generated as the average activity measured across the voxels within each ROI over the time course of the acquisition.

2.3.1 Outcome measure estimation

Distribution volumes (VT) of [11C]WAY-100635 were estimated for each ROI using kinetic analysis with an arterial input function and a two tissue compartment constrained (2TCC) model (for more details, see (Parsey et al., 2000b)). Time activity curves were fit with a 2TCC model in which the K1/k2 ratio was constrained to that of the reference region (CWM). For [11C]WAY-100635, BPF was calculated as (VT(ROI) − VT(REF))/fP. Derivation of [11C](+)-McN-5652 regional VT was performed using likelihood estimation in graphical approach (LEGA) (Ogden, 2003; Ogden et al., 2002; Parsey et al., 2003). As fP cannot be reliably measured for [11C](+)-McN-5652, the outcome measure BPP was estimated as (VT(ROI) − VT(REF)), with CGM as the reference region. For both tracers, for comparison with other published studies, we also calculated BPND as (VT(ROI) − VT(REF))/ VT(REF).

2.3.2 Voxel-level image generation

For [11C](+)-McN-5652, BPP was also estimated at the voxel-level for each participant, to generate parametric maps of 5-HTT binding. Briefly, VT parametric images were obtained by applying empirical Bayesian estimation in graphical analysis (EBEGA) (Zanderigo et al., 2010), a fully automatic approach that incorporates LEGA (Ogden, 2003) estimation of VT in a Bayesian framework. Once the VT parametric images were obtained for each subject using EBEGA, the corresponding BPP images were generated by subtracting the mean reference region voxel value (VT(REF)) from each target voxel (Parsey et al., 2000a).

2.4. Statistics

The associations between 5-HT1A binding measures in the raphe and 5-HTT binding in the regions of interest (thalamus, hippocampus, caudate, amygdala, temporal lobe, and insula; selected because of high 5-HTT binding) were examined using a linear mixed effects model with subject as the random effect and region and sex as fixed effects. To correct for some slight skewness in the data, to stabilize the variance across regions, and to allow for a proportional effect across regions, the analysis was performed on log-transformed estimates of 5-HTT binding. The observations were weighted according to standard errors that take into account variation in PET data, plasma data, and metabolite data (Ogden and Tarpey, 2006).

[11C](+)-McN-5652 BPP voxel images were analyzed using Statistical Parametric Mapping software (SPM8; Institute of Neurology, University College of London, London, England) implemented in Matlab2009b (The Mathworks Inc, Natick, Mass). Voxel images were transformed into standard space as described under image acquisition and analysis. A standard space gray matter mask from the FSL toolbox was applied to consider only gray matter voxels, and the images were smoothed using a Gaussian filter with a kernel of 5 mm. A two-tailed voxel-by-voxel t-test was performed using [11C]WAY-100635 BPF within the RN as a regressor and sex as a covariate, looking for correlations with 5-HTT BPp. A statistical threshold was set to p < 0.01 a priori, and extent threshold was set to p < 0.05 after correction for multiple comparisons.

3. Results

3.1. Correlations between [11C]WAY-100635 BPF and [11C](+)-McN-5652 BPP

No significant effect of [11C]-WAY-100635 was found on [11C](+)-McN-5652 binding across the a priori ROIs after accounting for sex (F=0.00; df=1, 37; p=0.99). Figure one shows the relationship between [11C]-WAY-100635 BPF in raphe nuclei and [11C](+)-McN-5652 BPP in a representative region (thalamus).

To test whether there was a heterogenous relationship between WAY raphe binding and McN binding across the a priori regions, we considered an interaction term with region, which was also not significant (F = 0.44; df = 7, 226; p = 0.88). Similarly, post-hoc testing for relationships between WAY raphe binding and McN binding in each individual ROI were also not significant (all p>0.54).

3.2 Voxel-level Results

At the voxel level, there were no clusters of 5-HTT BPP that correlated with raphe 5-HT1A BPF at our a priori statistical threshold (p>.01 for all clusters, uncorrected).

3.3. Other analytic approaches

In order to accurately replicate approaches from past literature and because of controversy in the field regarding optimal outcome measures for these radiotracers (Parsey et al., 2010), data was re-analyzed comparing 5-HT1A BPND vs. 5-HTT BPND and then again comparing 5-HT1A BPP vs. 5-HTT BPP. Consistent with our primary findings, no significant effect of raphe 5-HT1A binding on 5-HTT binding in the selected regions was observed (F=1.50; df=1, 37; p=0.23 for BPP and F=0.33; df=1, 37; p=0.57 for BPND).

Although we have not previously found an effect of age on [11C]WAY-100635 or [11C](+)-McN-5652 binding (Parsey et al., 2002), other groups have found such an effect (Tauscher et al., 2001). Including age as a co-variate in the current analyses did not affect the significance of the results reported across all outcome measures.

4. Discussion

In this reanalysis of this large dataset of 40 healthy volunteers who underwent quantification of 5-HT1A and 5-HTT binding, we did not observe an association between regional 5-HT1A in RN and 5-HTT binding in a priori terminal field ROIs. We also did not find an association between 5-HT1A binding in the RN and 5-HTT binding in the rest of the brain in an exploratory voxel-wise whole-brain analysis. These data do not support our hypothesis of inverse intra- and inter-regional 5-HT1A – 5-HTT binding relationships. These findings were not affected by removing variance attributable to sex and age differences or by the use of alternative PET outcome measures.

In contrast to our results, several studies have found correlations between 5-HT1A and 5-HTT, some positive (Bose et al., 2011; Jovanovic et al., 2008), and others negative (Takano et al., 2011). In contrast to our previously described model of responses positing a negative correlation, a positive correlation between 5-HTT and 5-HT1A binding might be expected if 5-HTT genetic variation is primary: for example, lower 5-HTT expression and protein and would lead to increased intrasynaptic 5-HT, with resultant downregulation of the 5-HT1A autoreceptor.

Lundberg et al., who also found significant positive correlations within the RN in an all male sample, built on the explanation of Bose et al. in saying that subtle, temporally synchronized covariation in expression of 5-HTT and 5-HT1A autoreceptors on neurons in the raphe is feasible because both proteins exist on the same neuron in this region (Bose et al., 2011; Hensler, 2012; Lundberg et al., 2007). However, the 5-HT1A receptors and 5-HTT proteins are expressed by different neuron types in the prefrontal cortex and other target brain regions, with the 5-HT1A in these regions existing as post-synaptic heteroreceptors on and around the axon hillock of glutamatergic pyramidal neurons or the dendrites of GABAergic interneurons and the 5-HTT located pre-synaptically on axon terminals of serotonin neurons whose cell bodies reside in RN.

One possible interpretation for the lack of an observed correlation between in vivo 5-HT1A and 5-HTT binding is that regulatory responses of these proteins may occur according to different time scales. 5-HTT appears to be rapidly regulated to appropriately match extracellular levels of serotonin, and up-or down-regulates within hours as a function of available 5-HT, as demonstrated by a tryptophan depletion experiment (Milak et al., 2005). In that study, baboons underwent [11C]DASB PET scans at baseline and after acute tryptophan depletion. 5-HTT binding decreased as a function of tryptophan and subsequent serotonin depletion (which occurred within 6 hours of scanning), demonstrating both the high sensitivity of SERT to serotonin levels and the rapidity of internalization. This is consistent with in vitro work demonstrating that 5-HT stabilizes 5-HTT at the cell membrane, preventing phosphorylation and internalization (Ramamoorthy and Blakely, 1999; Whitworth et al., 2002). Some conflicting evidence does exist from human imaging studies of tryptophan depletion, however (Praschak-Rieder et al., 2005). In contrast to the animal and in vitro work suggesting rapid responsiveness of 5-HTT to 5-HT, 5-HT1A receptors appear to have a slower time-course of response to serotonin levels as evidenced by the delayed action of SSRI antidepressants, which take weeks to produce desensitization of the autoreceptors (Blier and de Montigny, 1999; Gardier et al., 1996). Consistent with those animal findings, human PET studies have demonstrated that 5-HT1A binding is down-regulated by several weeks of SSRI treatment (Gray et al., 2013), but is not affected by acute SSRI administration (Pinborg et al., 2012). The lack of correlation between 5-HTT and 5-HT1A binding at both the ROI and voxel-level in the current analysis may therefore reflect different time courses of response to changes in 5-HT levels, leading to a de-coupling of 5-HTT and 5-HT1A protein levels.

Another form of interaction between elements in the serotonin neurotransmitter system are gene-protein relationships, eg. between functional polymorphisms in genes within the serotonergic system and protein binding potential of proteins within the serotonin system as assessed by PET. For example, a recent study demonstrated an interaction effect of the 5-HTTLPR polymorphism in the SERT gene with a polymorphism at the rs6296 locus in the serotonin 1B receptor gene on 5-HT1A BPND measured by [11C]WAY-100635 (Baldinger et al., 2015). As genotyping at these loci was available in this sample, we performed an exploratory analysis, examining relationships between genotype at these loci and [11C](+)-McN-5652 or [11C]WAY-100635 binding in the a priori ROIs in this study; no significant relationships were observed (all p>0.05, uncorrected for multiple comparisons). In addition, including genotype at these loci as covariates in the primary analyses of the paper (examining the relationship between [11C](+)-McN-5652 and [11C]WAY-100635 binding) did not affect the significance of reported results.

One potential limitation of the present design relates to the radiotracers used. [11C]WAY-100635 is antagonist tracer that binds to both the high and low affinity states of the 5-HT1A receptor, as opposed to an agonist that binds specifically to the subset of high affinity, active receptors (Kumar et al., 2012). [11C](+)-McN-5652 has suboptimal imaging characteristics, including low specific-to-nonspecific binding ratios and an extended acquisition time required to obtain stable binding estimates (Parsey et al., 2000a), but it was used in this study because it was the tracer for which the largest sample of data for healthy volunteers was available. A second limitation of [11C](+)-McN-5652 is that it has too little specific binding to prefrontal cortices or anterior cingulate to permit reliable quantification of protein density in those brain regions, although specific prefrontal cortical binding is also low with other 5-HTT radiotracers, including [11C]DASB. Alternative methods for quantification of 5-HTT also could have been considered, such as quantification of the ratio of 5-HTT binding in the terminal field region of interest to that in the raphe nuclei (Savli et al., 2012).

A third limitation was the scanner resolution. In this analysis we looked at the RN as one region, but it might have been preferable to look at the dorsal and medial raphe nuclei separately. These two regions have different terminal regions, projecting parallel and overlapping fibers, with their axonal fibers displaying distinct traits (Hornung, 2003). Axons of the dorsal raphe do not form true chemical synapses, but rather release serotonin in a paracrine manner, whereas serotonergic projections from the median raphe form abundant, closely spaced synapses at the terminal fields (Hornung, 2003). Serotonergic neurons originating from the dorsal raphe project primarily to prefrontal, parietal, occipital and temporal cortex, hippocampus, amygdala and striatum (Hensler, 2012; Hornung, 2003). In contrast, median raphe axonal fibers are largely restricted to midline subcortical structures (e.g. dentate gyrus, hippocampus), with only sparse projections to cortex (Hensler, 2012). The small size of these structures in comparison to the spatial resolution of PET, and the associated challenges of partial volume effects and signal-to-noise limitations, makes distinguishing between regions as small as the median and dorsal raphe a technical challenge; we therefore examined binding within a larger ROI encompassing both dorsal and median raphe nuclei. Partial volume effects and signal-to-noise limitations may also have impacted the reliability of our quantification within the entire raphe nuclei ROI employed here, possibly contributing to the lack of observed correlations. Future studies with improved PET resolution may allow dissection of the raphe nuclei into their functionally distinct components.

The large age range in the sample was an additional limitation; however, repeating our analyses with age in the model did not impact any of the reported findings. Finally, with the sample size employed in this study (n=40), we had 80% power to detect a correlation of r=0.43. We were therefore underpowered to detect correlations of smaller magnitudes than this, raising the possibility of Type II error.

5. Conclusions

We do not observe a systematic relationship between in vivo 5-HT1A and 5-HTT binding in a large sample of healthy volunteers. The relationship between these components of the serotonin neurotransmitter system is more complex and may not be measureable with the current cross-sectional design. We suspect this complexity is related to the temporal de-coupling of 5-HT1A and 5-HTT due to different regulatory mechanisms.

Supplementary Material

Figure 1.

Figure 1

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Scatter plot showing relationship between raphe 5-HT1A binding ([11C]WAY-100635) and 5-HTT binding in a representative terminal field region (thalamus). No significant correlation is observed (see results).

Highlights.

  • Brain serotonin transporter (5-HTT) and serotonin 1A receptor were quantified via PET.

  • Serotonin 1A receptor and 5-HTT binding are not correlated in a priori regions.

  • This suggests different regulatory control for these proteins in the serotonin system.

Acknowledgments

This research was funded by National Institutes of Mental Health grants MH040695 and MH062185.

Footnotes

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