Serotonin-1A receptor binding is positively associated with gray matter volume — A multimodal neuroimaging study combining PET and structural MRI

NeuroImage 63 (2012) 1091–1098

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Serotonin-1A receptor binding is positively associated with gray matter volume — A multimodal neuroimaging study combining PET and structural MRI Christoph Kraus a, Andreas Hahn a, Markus Savli a, Georg S. Kranz a, Pia Baldinger a, Anna Höflich a, Christoph Spindelegger a, Johanna Ungersboeck b, Daniela Haeusler b, Markus Mitterhauser b, Christian Windischberger c, Wolfgang Wadsak b, Siegfried Kasper a, Rupert Lanzenberger a,⁎ a b c

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria Department of Nuclear Medicine, PET Center, Medical University of Vienna, Austria MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria

a r t i c l e

i n f o

Article history: Accepted 10 July 2012 Available online 23 July 2012 Keywords: Positron emission tomography Structural magnetic resonance imaging 5-HT1A receptor

a b s t r a c t Animal models revealed that the serotonin-1A (5-HT1A) receptor modulates gray matter structure. However, there is a lack of evidence showing the relationship between 5-HT1A receptor concentration and gray matter in the human brain in vivo. Here, to demonstrate an association between the 5-HT1A receptor binding potential, an index for receptor concentration, and the local gray matter volume (GMV), an index for gray matter structure, we measured 35 healthy subjects with both positron emission tomography (PET) and structural magnetic resonance imaging (MRI). We found that regional heteroreceptor binding was positively associated with GMV in distinctive brain regions such as the hippocampi and the temporal cortices in both hemispheres (R2 values ranged from 0.308 to 0.503, p b 0.05 cluster-level FDR-corrected). Furthermore, autoreceptor binding in the midbrain raphe region was positively associated with GMV in forebrain projection sites (R2 = 0.656, p = 0.001). We also observed a broad range between 5-HT1A receptor binding and GMV. Given the congruence of altered 5-HT1A receptor concentrations and GMV reduction in depression or Alzheimer's disease as reported by numerous studies, these results might provide new insights towards understanding the mechanisms behind GMV alterations observed in these brain disorders. © 2012 Elsevier Inc. All rights reserved.

Introduction Growing evidence shows distinctive neuromodulatory properties of serotonin (5-hydroxytryptamine, 5-HT) in developing and mature brain networks (Daubert and Condron, 2010; Gaspar et al., 2003). Early alterations in the 5-HT system are associated with life-long changes in cognitive and behavioral functioning and the neuronal organization in neuropsychiatric diseases (Gaspar et al., 2003). The 5-HT1A receptor, one of at least 16 receptors in the serotonergic system, is directly linked to signaling cascades mediating neuroplasticity (Azmitia, 2001). Structural neuroimaging techniques revealed increased amounts of gray matter volume (GMV) as surrogate for enhanced neuroplasticity in relation to motoric training, cognitive performance or treatment with the antidepressant fluoxetine, a selective serotonin reuptake inhibitor (Draganski et al., 2004; Kanai and Rees, 2011; Vetencourt et al., 2008). On the other side, GMV loss as measured with high-

⁎ Corresponding author at: Department of Psychiatry and Psychotherapy, Functional, Molecular and Translational Neuroimaging — PET & MRI, Medical University of Vienna, Waehringer Guertel 18‐20, 1090 Vienna, Austria. E-mail address: [email protected] (R. Lanzenberger). URL: http://www.meduniwien.ac.at/neuroimaging (R. Lanzenberger). 1053-8119/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2012.07.035

resolution structural magnetic resonance imaging (MRI), is a key feature of neuropsychiatric brain disorders, whereby the hippocampal formation was demonstrated to be especially vulnerable to volumetric alterations (Benninghoff et al., 2010; Geuze et al., 2005). Serotonin-1A autoreceptors are located presynaptically on serotonergic neurons in the raphe nuclei where they reduce tonic cell firing, thus autoinhibiting 5-HT release (Hall et al., 1997). Postsynaptically, 5-HT1A heteroreceptors are expressed on glutamatergic and GABAergic neurons and mediate an inhibitory serotonergic response (AmargósBosch et al., 2004; Hall et al., 1997; Puig et al., 2005). Neurobiological studies identified a vast number of second messenger pathways that exert neuroplastic changes (Citri and Malenka, 2008; Pittenger and Duman, 2008) triggered by 5-HT via 5-HT1A receptors (Azmitia, 2001; Tardito et al., 2006). To sum up, 5-HT1A receptors might be involved in altering GMV, thereby offering a possible explanation for gray matter atrophy observed in several brain disorders. Dysfunctional neuronal organization is an important contributor to the pathogenesis of Alzheimer's disease (Mesulam, 1999), schizophrenia (Lewis and González-Burgos, 2008) and depressive disorder (Pittenger and Duman, 2008), however the underlying molecular mechanisms, leading to gray matter loss in these disorders are complex and not fully understood. Interestingly, positron emission

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tomography (PET) studies demonstrated alterations of 5-HT1A receptors in patients suffering from these disorders (Kasper et al., 2002; Kepe et al., 2006; Lanzenberger et al., 2007; Mamo et al., 2007; Savitz et al., 2009). This congruence and a lack of data in human brains in vivo lead us to investigate the relationship between 5-HT1A receptor concentration and GMV with a multimodal neuroimaging approach. Material and methods Participants We examined 35 healthy adults, 18 males and 17 females (age range = 21–52, mean = 26.6 ± 6.8 years, Table 1), with at least general qualification for university entrance as lowest educational level. All subjects were recruited via advertisement at the Medical University of Vienna, Austria and underwent a general physical and neurological examination at the screening visit including medical history, electrocardiogram and routine laboratory tests. Inclusion criteria were age between 18 and 60, ability to perform study procedures and absence of any acute or chronic disease. Exclusion criteria comprised any history of severe disease, any psychiatric or neurologic disorder, previous drug abuse, pregnancy as assessed by urine pregnancy tests and any continuous medication for three months prior to the study. All participants provided written informed consent after written and oral presentation of a general intelligible information form and received reimbursement after participation. The institutional review board of the Medical University of Vienna, Austria, gave approval to all study procedures. The pooled study sample consisted of subjects who were part of PET and MRI studies previously published by our group (Hahn et al., 2010; Spindelegger et al., 2009). Magnetic resonance imaging and image preprocessing Structural magnetic resonance imaging was performed at the MR Center of Excellence at the Medical University of Vienna, Austria, with a 3 Tesla whole-body MEDSPEC S300 MR-scanner (Bruker BioSpin, Ettlingen, Germany) using a magnetization-prepared rapid gradient echo (MPRAGE, T1-weighted) sequence (128 slices, 256 × 256 matrix, slice thickness 1.56 mm, voxel size 0.78 × 0.86 mm). To optimize image-preprocessing quality we used the DARTEL (Diffeomorphic Anatomical Registration using Exponentiated Lie algebra) algorithm (Ashburner, 2007), which ranked top in a comparison of 14 image registration algorithms (Klein et al., 2009). The major advantage of the DARTEL algorithm is an increase in the accuracy of inter-subject alignment by a high number of parameters derived from deformation fields. T1-weighted images of all 35 subjects in our study were manually re-oriented and segmented using the New Segment option in SPM8 (2009, Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom, http://www.fil. ion.ucl.ac.uk/spm/software/spm8/) to generate rigid-body aligned gray matter, white matter and CSF-images. After segmentation all

Table 1 Demographic and radiochemical variables of study subjects.

n Age Weight (kg) GMV (cm3) Injected dose (MBq) RCP (%)

All subjects

Males

Females

p

35 26.6 ± 6.8 71.3 ± 14.6 731.5 ± 73.8 385 ± 36 97.7 ± 1.4

17 29.6 ± 8.4 79.7 ± 11.7 777.5 ± 53.9 396.9 ± 45.8 98 ± 1.4

18 24.4 ± 2.5 62.5 ± 12.2 682.8 ± 58.5 372.3 ± 14.4 97.4 ± 1.3

0.026+ b0.001 b0.001 0.002+ 0.320

Data are given as means ± standard deviation. GMV = total gray matter volume, MBq = megabecquerel, RCP = radiochemical purity, p compares males and females with independent sample t-test or Mann–Whitney U test (+) where normal distribution was not obtained by Levene's test.

images were visually checked for major artifacts. The DARTEL algorithm consecutively generates six individual templates based on deformation fields calculated during segmentation, where the last template produced (number 6) was used for normalization. Each individual's segmented gray matter image together with each deformation field and the template was normalized to standard Montreal Neurological Institute (MNI) space at a voxel size of 1.5 × 1.5 × 1.5 mm. To correct for nonlinear spatial normalization, images were modulated by multiplication with the Jacobian determinants of the deformation fields in order to preserve the actual amount of gray matter within each structure before normalization. Based on this, the modulated images are further referred to as gray matter volume (GMV). The resultant values represent a quantitative measure of gray matter tissue volume per unit volume of the spatially normalized images (Ashburner and Friston, 2009). Finally, GMV images were smoothed with an 8-mm full-width at half-maximum Gaussian kernel. Such smoothing is considered sufficient to increase the stability of segmented images with respect to small registration errors. Radiochemistry The 5-HT1A receptor specific radioligand [carbonyl- 11C]WAY100635 was prepared at the Cyclotron Unit of the PET center at the Department of Nuclear Medicine of the Medical University of Vienna, Austria according to the optimized synthesis instruction proposed by Wadsak et al. (2007). [Carbonyl- 11C]WAY-100635 was prepared in a multistep radiosynthesis starting from cyclotron-produced [ 11C]CO2 and purified by high-performance liquid chromatography and solidphase extraction. [carbonyl- 11C]WAY-100635 was dissolved in a phosphate-buffered saline solution and injected at a target dose of 5.4 MBq/kg bodyweight, further details of radiochemical variables are given in Table 1. Positron emission tomography (PET) measurements PET was performed at the Department of Nuclear Medicine of the Medical University of Vienna, Austria with a GE advance full-ring scanner (General Electric Medical Systems, Milwaukee, WI). Each subject's head was placed in the scanner parallel to the orbitomeatal line guided by a laser beam system to ensure full coverage of the neocortex and the cerebellum in the field of view (FOV). A polyurethane cushion and head straps kept the head in position to minimize head movement and to guarantee a soft head rest during the whole scanning period. Initially, a 5-minute transmission scan in twodimensional mode was conducted to correct for tissue attenuation with a retractable 68Ge ring source. Dynamic PET scans started simultaneously with the intravenous bolus injection of the radioligand [Carbonyl- 11C]WAY-100635. PET scans lasted for 90 min per subject and were acquired in a three-dimensional mode. The overall dynamic scan time was divided in 30 successive time frames (15 × 1 min, 15× 5 min). The emission data were scatter- and attenuation corrected based on the data from the transmission scans and reconstructed using an iterative filtered back-projection algorithm (FORE + ITER). The final spatial resolution of the reconstructed volume was 4.36 mm fullwidth at half maximum at the center of the FOV. We did not perform realignment for head movement upon visual inspection of PET-data quality. All 30 dynamic PET image frames were summed (PETADD) for co-registration to the MRI. Quantification of 5-HT1A receptor binding potential We assessed in vivo receptor density as indexed by 5-HT1A receptor binding potential (BPND), the ratio at equilibrium of specifically bound radioligand to that of nondisplaceable radioligand in tissue (Innis et al., 2007). Binding was computed using the voxel-wise modeling tool in the PMOD software package (v3.1, 2009, for Linux,

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PMOD Technologies, Zurich, Switzerland, http://www.pmod.com) and applying the two-parameter linearized reference tissue model (MRTM2) (Ichise et al., 2003). Compared to other models such as the simplified reference tissue model (SRTM), MRTM2 leads to lower BPND bias and hence a better signal-to-noise-ratio, especially for whole-brain voxel-by-voxel analysis. We modeled 5-HT1A BPND as previously described by our group using the insula and the cerebellum taken from an automated anatomical labeling-based (AAL) region of interest (ROI) (Tzourio-Mazoyer et al., 2002) atlas, as receptor-rich region and receptor-poor region, respectively. The cerebellum excluding cerebellar vermis served as reference region. This was done for the voxel-by-voxel analysis as well as the ROI-based multimodal analysis. Image co-registration for multimodal data analysis We combined the advantages of PET in quantifying receptors at the molecular level with structural MRI, which provides data on brain structure such as cortical folding, regional cortical thickness and volume or gray/white matter contrast. This was achieved by co-registration of each individual's PET image to the corresponding structural MRI image. We used SPM8 to apply the transformation matrix of the structural scans obtained during normalization to the PETADD images. As the structural scans were already normalized to standard MNI space, this step also brought the PET data to MNI space resulting in whole-brain dynamic [carbonyl-11C]WAY-100635 maps co-registered to the structural MRI images. Quantification of 5-HT1A receptor binding potential in anatomical regions of interest With this post-hoc analysis we aimed to investigate the area-specific relationship between 5-HT1A and GMV to further confirm our primary voxel-by-voxel results using a different approach. The ROI-based analysis also served to test, whether there exists a network association between 5-HT1A receptors and gray matter in the projection areas of the one of the main raphe nuclei, the dorsal raphe nucleus (DRN). For the ROIbased network analysis the DRN was manually delineated on an averaged PETADD image in PMOD 3.1 (Kranz et al., 2012). Our DRN ROI consisted of a sphere, 4 mm in diameter, comprising three slices on the averaged PETADD image. Each individual's 5-HT1A BPND value in the DRN was then obtained from individual time–activity curves averaged across subjects (again using cerebellar gray matter as reference). For further post-hoc analysis we quantified 5-HT1A receptor BPND values and GMV values in MNI standard space in 48 ROIs, taken from the automatic anatomical labeling (AAL) atlas covering a broad range of brain regions as previously shown (Stein et al., 2008). A ratio between GMV and rescaled 5-HT1A BPND values was calculated by dividing the first through the latter.

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We thus calculated a multiple linear regression model with 5-HT1A receptor BPND values as independent variables and GMV values as dependent variables for every voxel in the entire gray matter. In this regression model age, sex and total GMV served as controlling variables. This was done to adjust for age related gray matter alteration, varying brain sizes, and sex differences (as outlined in Table 1). In two further models, we also considered the two radiochemical variables specific activity (SA) and injected dose (ID) as factors. However, given that the number of control variables should not exceed n/10 and the results (data not shown) were virtually identical with the primary model, we did not include SA and ID in our further analyses. The voxel-by-voxel regression model was set up in the Biological Parametric Mapping (BPM) toolbox for SPM8 (Casanova et al., 2007), which is designed to calculate voxel-by-voxel statistics for multiple imaging modalities. More precisely, multiple regression was calculated in each voxel (average voxel number across all subjects = 216,741.2) with one value for GMV and one for 5-HT1A BPND (in arbitrary units). We used 0.1 as absolute threshold and a level of statistical significance of α = 0.001. Due to multiple comparisons and the concomitant high chance of false positives the obtained results were corrected with the cluster-level false discovery rate (FDR) at a significance level of α = 0.05. Correlation coefficients were calculated with cluster-wise means (in arbitrary units) in Matlab (v. r2010b, The MathWorks, Inc., Natick, United States of America). For the analysis of serotonergic projections from the DRN, we calculated a regression model in SPM8 using 5-HT1A BPND values of the DRN ROI as independent variable and whole brain GMV as dependent variable. Sex, age and total GMV were control variables for the reasons mentioned above. Further, GMV of the DRN was added in the regression model to eliminate potential confounding effects of DRN gray matter and whole brain gray matter interactions. GMV values were obtained from the DRN ROI overlaid on the MRI images. We excluded voxels exhibiting BPND or GMV voxel values below 0.1. The level of statistical significance was set at α = 0.001 and only results with a cluster size over 100 voxels are reported. For the analysis of smoking status on BPND a regression analysis was set up in SPM8 using 5-HT1A BPND values as independent variables and smoking status or number of smoked cigarettes as dependent variable, respectively, controlling for sex, age and GMV. Age effects on GMV were calculated with a regression analysis using GMV as independent variable and age as dependent variable controlling for sex and GMV. In both analyses an uncorrected α = 0.001 was accepted as level of significance. Results 5-HT1A receptor binding positively correlated with gray matter volumes within distinctive brain regions

Statistical analyses Demographics Sex differences in biological, demographical and radiochemical variables were calculated to assess study sample characteristics with either independent sample t-tests or Mann–Whitney U tests where appropriate, using IBM SPSS Statistics (v19.0, 2010, SPSS, Inc., an IBM Company, Chicago, United States of America) assuming a significance level of α = 0.05. Multimodal analysis Multimodal image analysis was divided into two parts: we calculated regional voxel-by-voxel associations between 5-HT1A receptor distribution and gray matter in the whole-brain. Second, we assessed the associations between 5-HT1A receptor binding in a single area, the DRN, and GMV in projection sites of the DRN. The DRN was chosen because of its central role in the regulation of serotonergic firing and neurotransmission.

In this pooled study sample, male study subjects significantly differed from females in GMV, weight and total injected radiotracer dose (Table 1). In line with previous results of our group, 5-HT1A BPND, an index for receptor density, peaked in the parahippocampal gyri, the temporal poles and the insula (Figs. 1A and 3, Table S1 and Stein et al., 2008). Serotonin-1A BPND strongly correlated with GMV in the hippocampus (the cluster in the right hippocampus spread from the posterior hippocampus to the parahippocampus), the posterior medial temporal cortex, the posterior inferior temporal cortex, the medial occipital cortex and the pericalcarine region in each hemisphere (R 2 values ranged from 0.308 to 0.503, p b 0.05 cluster-level false discovery rate [FDR] corrected, see Figs. 1B, C and Table 2). In other words, 5-HT1A heteroreceptor binding strongly correlated with relative volumes of gray matter in these specific regions. Negative correlations between 5-HT1A BPND and GMV were restricted to two regions in the cerebellum (Table 2).

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Fig. 1. Serotonin-1A (5-HT1A) receptor binding is positively associated with regional gray matter. (A) 5-HT1A receptor distribution in vivo measured with positron emission tomography displayed with the surface-rendering algorithm used by the visualization program MRIcro (http://www.cabiatl.com/mricro/mricro/mricro.html). (B) T maps showing that 5-HT1A binding potential (BPND) strongly correlates with gray matter volume (GMV). Significant positive correlations were superimposed on MR images (pb 0.05, FDR cluster-level corrected, see Table 2), coordinates correspond to the standard Montreal Neurological Institute (MNI) stereotactic system. (C) Regression graphs between GMV and 5-HT1A BPND (multiple regression analysis controlled for sex, age and total GMV, adjusted values in arbitrary units) correspond to cluster means of each subject (in red circles (B), N=35).

5-HT1A receptor binding in the raphe region positively correlated with gray matter volume in the anterior cingulate cortex Previous data show that presynaptic 5-HT1A autoreceptors in the DRN regulate tonic serotonergic firing, serotonin release and the

postsynaptic density of 5-HT1A heteroreceptors and 5-HT transporters (Bose et al., 2011). Hypothesizing that the influence of the DRN autoregulation extends to gray matter, we investigated associations between 5-HT1A autoreceptor binding in the DRN and whole brain GMV at projection sites. We observed a positive correlation

Table 2 Statistical results as obtained by Statistical Parametric Mapping (SPM8). Region

Peak

Cluster

x

y

z

t

Positive correlation Right posterior medial temporal Right hippocampus/parahippocampus Right medial occipital Right inferior orbitofrontal Right posterior inferior temporal Left posterior medial temporal Right superior parietal Left posterior inferior temporal Left medial occipital Left pericalcarine Left precentral Right pericalcarine Right inferior occipital Left hippocampus

42 29 38 51 59 −44 24 −53 −21 −27 −33 30 38 −24

−32 −39 −92 20 −32 −26 −53 −42 −101 −57 5 −57 −65 −27

0 0 −5 −8 −15 −6 48 −14 9 5 41 8 −11 −14

6.7 6.2 4.9 4.9 5.4 6.7 6.0 5.1 4.9 6.1 5.7 7.2 5.5 5.3

Negative correlation Left posterior lobe of cerebellum Left cerebellar crus

−26 −50

−57 −69

−23 −23

−6 −5.4

R2

p–FWE

p–FDR

Voxels

5.2 4.9 4.1 4.2 4.5 5.2 4.8 4.3 4.2 4.9 4.7 5.4 4.5 4.4

0.487 0.503 0.308 0.403 0.436 0.386 0.449 0.302 0.217 0.424 0.183 0.489 0.308 0.428

b0.001 b0.001 b0.001 0.002 0.002 0.003 0.004 0.004 0.006 0.009 0.031 0.043 0.089 0.127

b0.001 b0.001 b0.001 0.001 0.002 0.002 0.002 0.002 0.002 0.003 0.01 0.013 0.026 0.035

952 850 541 434 416 400 381 374 349 323 253 234 195 176

−4.83 −4.48

0.422 0.461

0.102 0.349

0.176 0.35

363 235

z

Voxel‐wise regression analysis results between whole‐brain 5‐HT1A binding potential (BPND) and whole‐brain gray matter volume (GMV). Stereotactical coordinates (x,y,z) represent cluster peaks in standard Montreal Institute of Neurology (MNI) space. FWE = family wise error. FDR = false discovery rate. Note that R2 values were calculated cluster‐wise between 5‐HT1A BPND and GMV and therefore do not correspond to peak t‐ or z‐values.

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between the dorsal raphe 5-HT1A BPND and GMV in the right perigenual anterior cingulate cortex (R2 =0.656, p=0.001, uncorrected, Figs. 2A, B).

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observed in the hippocampus (r = 0.41, p = 0.02) but not in the insula (r = −0.03, p = 0.87). No effects of age or smoking status

Post-hoc ROI analysis revealed regional differences in the relation between 5-HT1A receptor binding and GMV An intuitive caveat to the results might be that these associations could be merely based on primary larger numbers of neuronal or glial cells expressing 5-HT1A receptors and thus a priori higher GMV values. Therefore, we investigated if the resulting clusters were exclusively situated in regions with high regional GMV and quantified the BPND and GMV values of 48 ROIs covering the whole brain. We found several regions, such as the cingulate cortex or the amygdala, which despite high regional GMV and 5-HT1A BPND values did not exhibit significant positive associations in the voxel-by-voxel analysis (Fig. 3). Furthermore, we calculated ratios between GMV and BPND values to assess regional proportions between 5-HT1A receptor binding and gray matter in the whole brain. These GMV/BPND ratios ranged from 0.54 in the temporal pole to 4.8 in the caudate region, suggesting high regional variability within the ratio of regional GMV and 5-HT1A BPND (Fig. 3). Following that, to confirm the associations between 5-HT1A BPND and GMV obtained by voxel-by-voxel analysis, we repeated the regression analysis within two ROIs. The ROIs should have similar GMV and 5-HT1A BPND values, one exhibiting and one lacking the associations as obtained by voxel-by-voxel analysis. Out of the 48 quantified ROIs, the hippocampus and the insula were the only two regions meeting the selection criteria (GMV/BPND: insula= 0.63, hippocampus= 0.64, GMV: insula and hippocampus= 0.53, BPND: insula= 0.84, hippocampus= 0.83, see Fig. 3 and Table S1). In the voxel-by-voxel analysis, the hippocampus exhibited significant positive associations between 5-HT1A receptor BPND and GMV, but in the insula, despite similar values, 5-HT1A BPND did not correlate with GMV. Congruent to the voxel-by-voxel analysis, in the post-hoc ROI analysis a significant positive correlation was

Fig. 2. Network analysis. 5-HT1A receptor binding of the dorsal raphe nucleus (DRN) is positively associated with gray matter volume of the anterior cingulate cortex (ACC). (A) Significant cluster superimposed on a sagittal MRI slice (regression analysis, R2 = 0.656, pb 0.001, uncorrected, cluster peak: t = 5, MNI: x = 6, y = 35, z = 3). (B) Data points represent cluster means (adjusted values in arbitrary units) of each subject (N = 35) as adjusted by regression analysis controlled for sex, age total GMV and GMV of the DRN.

To rule out cortical atrophy due to aging was somehow related to the results, we analyzed our dataset for age-related effects. Multiple regression analysis in SPM8 revealed a negative correlation for GMV and age in the left medial occipital cortex (t= 4.24, p b 0.001, uncorrected, x = −27, y= −81, z = 26) near the angular gyrus. BPND was negatively correlated with age in a cluster around the left postcentral gyrus (t= 3.82, p b 0.001, uncorrected; x =−22, y =−27, z = 62). These results indicate that an effect of aging in our data occurred in different brain areas than the main results. Smoking status was available for 34 participants, out of which 14 were smokers (6 female, mean cigarettes per day = 7.1 ± 4.8). Multiple regression analysis revealed that neither smoking status nor number of smoked cigarettes was associated with 5-HT1A BPND (all p > 0.001). Discussion Our results demonstrate positive associations between 5-HT1A receptor binding and gray matter. In distinctive regions of both hemispheres, as in the hippocampi and in temporal cortices, 5-HT1A receptor binding was strongly correlated with gray matter. These results were not just based on a priori higher regional values of gray matter, because we demonstrated that in regions such as the insula, in contrast to the hippocampus, there were no significant positive associations, although having comparable gray matter and 5-HT1A receptor binding. We observed a large variability between 5-HT1A binding and gray matter in the whole brain. We also found that 5-HT1A autoreceptor binding in the DRN was positively associated with gray matter in the anterior cingulate cortex. The results were not affected by cortical atrophy due to aging or smoking status. A large number of previous findings in animal models (Daubert and Condron, 2010; Gaspar et al., 2003) show direct links between serotonergic receptors like the 5-HT1A receptor and neuroplasticity. Furthermore, there is evidence that allows direct inference from MRI-based measurements to changes of the underlying neuronal structures (la Fougère et al., 2011). Therefore, we propose that the discovered associations provide valuable insights into the relationship between 5-HT1A receptor binding and gray matter cytoarchitecture in adult human brains in vivo. Serotonin is highly active in shaping neurons during embryonic development and early postnatal neuronal maturation, and this neuroplastic role is partially conserved in specific brain regions throughout adulthood (Gould, 1999). Downstream cytosolic signaling kinases from membrane-bound small G proteins (Ye and Carew, 2010), that activate transcription factors (McClung and Nestler, 2008) and epigenetic mechanisms (Borrelli et al., 2008) were suggested to effect neuronal reconfigurations. Serotonergic-1A receptors are able to modulate the activity of these pathways (Cowen, 2007; Polter and Li, 2010). Recently a study using hippocampal cell cultures could show that 5-HT1A receptors are essential for normal synaptogenesis (Mogha et al., 2012). Blockade of astrocytic 5-HT1A receptors leads to a reduction of synaptic connections between neurons (Wilson et al., 1998) and fits well to findings demonstrating that the 5-HT1A receptor is required for behavioral and neurogenic effects of the selective serotonin reuptake inhibitors (Santarelli et al., 2003). From a neurobiological perspective, we suggest that neuroplastic effects of 5-HT1A receptors might contribute to the observed association between 5-HT1A binding and alterations of regional gray matter. Nevertheless, this interpretation must be considered with caution, because one voxel in high-resolution structural MRI contains too many neuronal cells to reliably link our results with mechanisms observed in cell cultures or animal models (for review see May, 2011).

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Fig. 3. Area-specific differences in the relation between 5-HT1A receptor binding and gray matter volume. Gray matter volume (GMV, red) and 5-HT1A binding potential (BPND, blue), in arbitrary units, quantified in 48 brain regions of interest (ROI) covering the whole brain. This demonstrates high variabilities between 5-HT1A receptor densities and regional volumes of gray matter (also see Table S1).

To better pin down how 5-HT1A receptor-mediated neuroplasticity might affect gray matter in the living brain, further longitudinal investigations are needed. A possible alternative explanation to our results could simply be, that regional 5-HT1A binding was elevated through primary higher regional amounts of gray matter. However, considering results from animal models, we have several arguments against this. Firstly, we predominately found positive associations. In a similar study using structural MRI, PET and the D2/D3 receptor ligand [ 18F] fallypride, Woodward et al. (2009) previously pointed out that negative associations are unexpected. Hypothetically, the density of 5-HT1A receptors should vary with the amount of gray matter within a region, in other words the more gray matter, the more receptors it can support and vice versa. A recent study, however, nicely demonstrates divergent values between 5-HT1A binding and neuronal densities in humans as measured by stereology and autoradiography (Underwood et al., 2012). This result is congruent to the broad variability in the range between 5-HT1A binding and GMV shown in our study. The predominantly positive associations in our study go well along with the finding, that astrocytic 5-HT1A receptors (via S-100ß)

are necessary for maintaining the neuronal integrity (WhitakerAzmitia, 2001). In the absence of S-100ß a mature neuron can regress its major processes and even enter apoptosis (Whitaker-Azmitia, 2001). Secondly, the associations between 5-HT1A binding and gray matter were obtained symmetrically in both hemispheres, which indicate validity. The distinctive regional pattern could be explained by varying strengths of 5-HT1A mediated neuroplastic effects (Cowen, 2007). Thirdly, the insula, even with similar 5-HT1A and GMV values as the hippocampus, did not exhibit significant associations. This further suggests a region-specific mechanism and might indicate that the observed associations were not based on higher numbers of regional neuronal and glial cells, both associated with GMV. According to the current state of knowledge 5-HT1A mediated neuroplasticity is more active in the hippocampus than in the insula (Santarelli et al., 2003). In the hippocampus 5-HT1A receptors were demonstrated to stimulate neurogenesis and dendritic maturation (Yan et al., 1997). Finally, we demonstrated an association between 5-HT1A receptors in one of the major serotonergic nuclei, the DRN, and gray matter at serotonergic axon terminals in the anterior cingulate cortex. Hypothetically, interregional correlation between 5-HT1A auto- and heteroreceptors

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(Hahn et al., 2010) could foster the observed association between 5-HT1A receptors and GMV in this study. The autoregulatory influence of the DRN on serotonergic heteroreceptors at axon terminals in the forebrain, by neuroplastic properties of 5-HT1A receptors, might thus extend to GMV. Patients suffering from mood disorders exhibit both significantly reduced GMV of the anterior cingulate cortex and altered 5-HT1A receptor density in the raphe nucleus (Salvadore et al., 2011; Savitz and Drevets, 2009; van Tol et al., 2010). We could speculate here, that a disturbance in this association might contribute to the reduction of GMV in the anterior cingulate cortex. In summary, the associations between 5-HT1A binding and GMV could theoretically result from a priori higher regional amounts of gray matter or other unknown mechanisms. But given the high amount of clear evidence, we suggest that neuroplastic actions of 5-HT1A receptors should be taken into account as explanatory model for this dataset. The 5-HT1A receptor, in addition, could prove to be an interesting target in clinical studies on altered neuroplasticity in brain disorders, due to well known behavioral functions such as mediating mood (Savitz et al., 2009), anxiety (Akimova et al., 2009) or cognition (Ogren et al., 2008).

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surrogate markers to predict and monitor treatment response were demanded (Cramer et al., 2011). With combinations of structural and molecular neuroimaging, as performed in this multimodal study, dysfunctional neuroregulatory processes leading to loss of gray matter might be investigated at early stages in clinical populations. This could lead to a more comprehensive understanding of neurodegenerative diseases such as Alzheimer's disease, schizophrenia and mood disorders and ultimately to a better diagnostic assessment and therapeutic evaluation of patients with these highly life impairing disorders. Acknowledgments This research was partly supported by grants from the Austrian Science Fund, and the Austrian National Bank (P 11468) to R. L. A. Hahn is recipient of a DOC-fellowship of the Austrian Academy of Sciences at the Department of Psychiatry and Psychotherapy. We are grateful to the technical and medical teams of the PET and High-Field MRI Centre, Medical University of Vienna, especially to K. Kletter, R. Dudczak, E. Moser, L.-K. Mien, and F. Gerstl. Furthermore, we would like to thank U. Moser, M. Fink, and P. Stein for medical support and A. Saulin for help with the manuscript.

Limitations This dataset does not imply that the observed associations can be causally attributed to neuroplastic actions of 5-HT1A receptors. For such a deduction a longitudinal, interventional and translational approach in a future study would be more favorable, for which this dataset provides excellent justification. Furthermore, as previously pointed out (Tost et al., 2010) the neurobiological correlates of changes in brain morphology measured by structural neuroimaging are not sufficiently resolved, for an excellent recent review see Zatorre et al. (2012). Even at high-resolution MRI, there are still ten thousands of interconnected neuronal and glial cells packed in one single voxel. Thus, more translational cell studies on neuroplasticity are necessary to exactly determine what cellular processes are mediated by serotonin and the 5-HT1A receptor that could gain effects, large enough to be detectable by structural MRI (May, 2011). Finally, we did not use correction for partial volume effects (PVC) of the PET data. Although this may be an obvious issue, PVC is typically carried out by using the corresponding segmented MRI, namely, the gray and white matter probability maps. More precisely, the GM values represent the denominator of the PVC algorithm (MullerGartner et al., 1992). This implies that the PET activity concentrations are adjusted for individual differences in the GM volume. However, the current study particularly aims to investigate the association between individual differences in 5-HT1A binding and GM volume. Hence, MRI-based PVC would include the effect of interest as nuisance variable, which in turn cancels the association. Accordingly, no PVC was carried out in the similar investigation of Woodward et al. (2009). Conclusions Our results demonstrate that 5-HT1A receptor binding is positively associated with gray matter in specific regions such as the hippocampus and the temporal cortices in both hemispheres. Furthermore 5-HT1A autoreceptor binding in the midbrain is positively associated with gray matter in the anterior cingulate cortex. Currently, it is hard to pin down the molecular mechanisms underlying our results, mostly because, there are no exact models which cellular compounds correspond to the signal strength in a single voxel. To increase the validity of neuroimaging studies, this issue must be an objective of further studies. With regard to translational neuroscience, assessments of processes underlying networking and reorganization of neurons as well as early

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