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Neuroscience Letters
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Review article
PET radioligands for the dopamine D1-receptor: Application in psychiatric disorders
Simon Cervenka
⁎Department of Clinical Neuroscience, Center for Psychiatry Research, Karolinska Institutet and Stockholm County Council, SE-171 76 Stockholm, Sweden
A R T I C L E I N F O Keywords:
PET Dopamine D1 Schizophrenia Depression Substance use disorder
A B S T R A C T
The dopamine (DA) system is considered to be centrally involved in the pathophysiology of several major psychiatric disorders. Using positron emission tomography (PET), aberrations in dopamine D2/D3-receptors (D2-R) levels and uptake of the DA precursor FDOPA have been shown for schizophrenia, substance abuse and depression. Radioligands for the dopamine D1-receptor (D1-R) have been available for more than three decades, however this receptor subtype has received much less attention in psychiatry research. Here, studies in- vestigating D1-R in psychiatric patients in comparison to healthy control subjects are summarized. Although small sample sizes, medication effects and heterogeneous methods of quantification limit the conclusions that can be drawn, the data is suggestive of higher levels of cortical D1-R in drug naïve patients with psychosis, and lower D1-R in patients with affective disorders. Data sharing and reanalysis using harmonized methodology are important next steps towards clarifying the role of D1-R in these disorders.
1. Introduction
The dopamine (DA) system is considered to be involved in most aspects of human behaviour, from motor control to cognitive and mo- tivational domains. As a corollary, DA neurotransmission has been a central focus for research on the pathophysiology and treatment of major psychiatric disorders such as schizophrenia, affective disorders and substance use disorders. Positron emission tomography (PET) is a molecular imaging technique which allows for quantification of mar- kers of brain neurotransmission in the living human brain, providing an opportunity to examine DA function in psychiatric populations. The majority of this work has focused on the dopamine D2/D3 receptor subtype (D2/D3-R) and the dopamine transporter [1–4]. In contrast, the dopamine D1-receptor (D1-R), which is the most abundant receptor subtype in the brain, has received much less attention.
D1-R belongs to the D1/D4/D5 receptor family, which shows op- posing intracellular effects compared to D2/D3-R. Whereas D2/D3-R stimulation leads to blockade of cAMP cascade, stimulation of D1/D4/
D5-R results in increased cAMP levels [5]. In the striatum, which is the most DA-rich region in the brain, these opposing effects of DA signalling are balanced by the distribution of D1-R predominantly on cells pro- viding output via the direct nigrostriatal pathway whereas D2/D3-R expressing cells project via the indirect pathway [6]. D2/D3-R are found mainly in the striatum, in contrast the D1-R is widely distributed throughout the brain [7] (Fig. 1). Finally, D2/D3-R has high affinity for
DA, and is considered sensitive to tonic DA levels, whereas the rela- tively low affinity D1-R may primarily detect phasic changes [8–10].
These differences in downstream effects, connectivity and localization suggest that D1-R may serve as a functionally distinct marker of the DA system. Indeed, a specific role for D1-R has been suggested for cognitive performance [11–14], reward signal processing [15–17] and response inhibition [18], all domains that are considered relevant for a range of psychiatric conditions [3,17,19–21].
The aim of this review is to briefly describe available radioligands for the D1-R, and their application to psychiatric populations. To fa- cilitate comparisons across clinical studies, effect sizes for each study were calculated based on reported binding values. The results obtained will be discussed in relation to radioligand characteristics and other methodological issues.
2. Radioligands for the D1-receptor
One of the first D1-R selective compounds to described was SCH 23390 [22], with in vitro KDvalues of between 0.14–0.8 nM in rats [23], and 0.35 nM in the human brain [24]. The compound was radi- olabelled with 11C in 1986 [25], shortly thereafter applied in non- human primates and humans [26,27], and has since been the most frequently used D1-R radioligand in clinical studies. One drawback with [11C]SCH 23390 is its relatively low specific binding in cortical regions, which prompted the development of new radioligands with higher
https://doi.org/10.1016/j.neulet.2018.03.007
Received 2 December 2017; Received in revised form 6 February 2018; Accepted 3 March 2018
⁎Correspondence to: Karolinska Hospital Solna, R5 171 76, Stockholm, Sweden.
E-mail address:simon.cervenka@ki.se.
affinity. [11C]NNC 112, with a KDin rat brain of 0.18 nM [28], shows an uptake in the brain of around 4% compared to 1–2% for [11C]SCH 23390, as well as higher specific to nonspecific binding ratio [29]. A disadvantage of the higher affinity is the slower kinetics, which means that a longer scanning time is required compared to [11C]SCH 23390 [30,31].
Other candidate D1-R radioligands that have been evaluated include [11C]SCH 39166 [32,33], [11C]NNC 687 and [11C]NNC 756 [34]. Of these, [11C]SCH 39166 and [11C]NNC 687 were found to show too low binding to allow for quantification [33,35]. [11C]NNC 756 is the radi- oligand that has shown the highest specific to non-specific binding ratio, however slow kinetics (equilibrium at 50–60 min, compared to 20 min for [11C]SCH 23390) limits its usefulness in applied studies [35].
More recently, the radioligand [11C]A-69024 was shown to have ade- quate specific − to non-specific binding ratio and high selectivity [36], however this tracer does not seem to have been used in human studies.
In addition to antagonist radioligands, compounds with D1-R agonistic properties have also been developed, including [11C]SKF 75670, [11C]
SKF 82957 [37,38] and the 5-benzofuran analogue [11C]N-methyl-NNC 01-0259 [39] but thus far, none of these have been applied in clinical studies.
Autoradiography studies have shown cerebellum to be devoid of D1- R [40], confirming that this region may serve as reference for estima- tion of free and non-specifically bound radioligand concentration in tissue (= non-displaceable uptake). In initial human studies using [11C]
SCH 23390 and [11C]NNC 112, quantification of binding was per- formed by either subtracting the total measured radioactivity in the reference region from the measured activity in the target region [41], or by calculating a ratio of specific (target − reference region) and re- ference region radioligand uptake at transient equilibrium [42,43]. For [11C]SCH 23390, Chan et al. then used arterial samples as input func- tion to obtain total distribution volume (VT) and distribution volume ratios (DVR, calculated as VTdivided by non-displaceable distribution volume (VND), with VTin cerebellum as an estimate of VND). High re- liability was shown for DVR whereas reliability was low for VT[44]. In the same paper, non-displaceable binding potential (BPND, Fig. 1. Average BPNDimages of D1-R binding in 15 healthy male subjects, as measured using PET and [11C]SCH 23390. BPNDvalues were obtained using wavelet- aided parametric mapping [114,115]. Courtesy of Granville Matheson and the PET centre at Karolinska Institutet.
corresponding to ratio of specific over non-specific binding at equili- brium [45]) was estimated using a linear approach (Logan non-in- vasive) with cerebellar activity as input function, showing equal or higher reliability than plasma-input DVR [44]. Subsequently, kinetic modelling using the simplified tissue reference model (SRTM) with cerebellum as reference input was validated for [11C]SCH 23390 [31,46]. In test-retest studies, absolute variability for BPNDobtained using this approach has shown to be 4.2-8.4% for striatal regions and 7.0-11.1% for frontal cortical regions, with intraclass coefficients (ICCs) of 0.81-0.94 and 0.81-0.97 respectively [31,47].
For [11C]NNC 112, Abi-Dargham et al. performed a test-retest study using arterial input function and kinetic modelling using the 2-tissue compartment model (2TCM) [30], evaluating a range of different out- comes measures. The test-retest variability for most parameters were similar for striatal and cortical regions, which may reflect the higher specific − to nonspecific binding ratio for this radioligand compared to [11C]SCH 23390. For VTand DVR (calculated as VT/VND, using 1TCM- derived VTvalues for cerebellum as estimate for VND), mean absolute variability for all regions was 8 ± 2% (standard deviation) and 6 ± 2% respectively, with ICC values of 0.91 ± 0.06 and 0.84 ± 0.10. For BPNDcalculated using rate constants k3/k4, absolute variability values and ICC were 13 ± 5% and 0.84 ± 0.11. The out- come variable V3 (which corresponds to specific binding over free radioligand in plasma, according to current nomenclature BPF[45]), showed similar reliability as BPND, with a mean absolute variability of 14 ± 5% and a mean ICC of 0.9 ± 0.06. To date, no formal validation of kinetic models using reference tissue as input function has been performed for [11C]NNC 112.
Using both [11C]SCH 23390 and [11C]NNC 112, D1-R binding has in cross-sectional studies shown to decline by around 7–8% per decade in striatum and 8–14% in cortex [48–50]. In adolescents a similar rate of decrease was found for dorsal striatum (8%), whereas frontal cortical receptor levels showed a more rapid decline corresponding to around 26% per decade [51]. Hence, age is an important confounder in clinical studies, in particular when examining cortical regions in younger samples. Moreover, for both these radioligands part of the binding in cortical regions is explained by 5HT2a receptor binding, despite showing more than 100-fold higher affinity for D1-R in vitro [23]. In a study on non-human primates, where blocking was performed using the selective 5HT2a antagonist MDL 100907, both radioligands showed a 25% reduction in binding [23]. For [11C]NNC 112, this was subse- quently confirmed in a human blocking study, showing that specific binding in cortical regions was reduced by 20–30%, whereas striatum showed no change [52].
3. Application of D1-receptor PET in psychiatric disorders 3.1. Schizophrenia
Aberrations in DA neurotransmission has long been considered a key disease mechanism in schizophrenia, based on observations since several decades of an antipsychotic effect by drugs with D2-R antago- nist properties [42,53,54]. Compared to D2-R, D1-R is not a major target for antipsychotic drug action. Whereas most antipsychotics show a 70–85% D2-R occupancy at clinically effective doses [42], D1-R oc- cupancy has generally been much lower, ranging from 0 to 20% for typical antipsychotics [42,55] to 33–59% for the atypic antipsychotic drug clozapine [42,56,57]. Moreover, drugs specifically targeting the D1-R have shown limited efficacy and in some cases even a deteriora- tion in patients [58].
With regard to examining alterations in DA-R in patients, a series of studies on D2/D3-R have been performed dating back to the 80′s, mainly in schizophrenia. A metaanalysis showed a small-to-medium increase in striatal receptor levels in schizophrenia patients [1], al- though this effect was not significant when including only studies in antipsychotic-naïve patients. For extrastriatal regions such as thalamus,
decreases have also been shown [59,60]. The main rationale for in- vestigating D1-R in schizophrenia has been that frontal cortex is con- sidered a key region in cognitive neuroscience models of the disorder [61,62], and that cognitive domains involving D1-R function in this region show clear deficits in patients [11–14,19].
In the following review of PET D1-R studies in psychiatric disorders, effect sizes for comparisons between patients and control subjects were calculated using the formula for Cohens d:
− n − D + n − D n +n −
Meanpat mean / ((ctrl 1 1)S 12 (2 1)S )/(22 1 2 2) (SD = standard deviation). Notably, since individual-participant data was not available for any of the studies, the influence of confounders could not be taken into account, and the calculated values are therefore to be viewed as rough estimates of the magnitude of difference.
In the first PET study evaluating D1-R in schizophrenia, [11C]SCH 23390 was used to examine 18 patients and 17 healthy controls [63]. 10 of the patients were naive to antipsychotic drugs (DN), and the re- maining 7 were drug free (DF) for a minimum of 2 weeks. BPNDwas calculated as a ratio between the rate constants k3/k4as derived from 2TCM with metabolite-corrected arterial plasma as input function. A statistically significant decrease was found in prefrontal cortex (d = −1.0 for DN, −1.39 for DF, uncorrected for age), and binding in this region showed a negative association to negative symptoms and cognitive function as assessed using Wisconsin Card sorting. No sig- nificant difference was observed in the striatum (Table 1). In order to exclude that the differences were due to 5HT2a-R binding, in a sub- sequent study [11C]N-methylspiperone was used to examine 5HT2-R binding in the same cohort of patients. A trend-level reduction was ob- served in DF patients, but no difference in the DN subgroup was found, indicating that the reported decrease in [11C]SCH 23390 at least in the latter group was not explained by the contribution of 5HT2a [64].
Subsequently, Abi-Dargham et al. used [11C]NNC 112 in 16 drug free patients with schizophrenia, of which 7 were drug naïve, and 16 control subjects [65]. The outcome measure used for D1-R binding was specific binding over total plasma concentration (BPP[45]), calculated as VT-VND, with VTin target region estimated using 2TCM, and 1TCM cerebellum VTas VND. Binding was shown to be higher in cortical re- gions, reaching statistical significance for prefrontal cortex (d = 0.87) however no correction for multiple comparisons was applied (13 re- gions were tested). No difference was found in striatum (average effect size 0.06). Moreover, D1-R binding in prefrontal cortex showed nega- tive correlations to working memory task (n-back).
Karlsson et al. then used [11C]SCH 23390 to examine 10 DN first episode patients with schizophrenia and 10 healthy control subjects [66]. Two examinations were performed, one with high and one with low specific radioactivity, allowing for estimation of receptor density (Bmax) and apparent affinity (KD) separately by use of a Scatchard plot.
BPFwas calculated directly as Bmax/KD[67]. No statistically significant differences were found for any region, with an average effect size of BP in striatal regions of −0.35, and for cortical regions 0.32. No statisti- cally significant difference between groups was found for Bmaxor KD.
In a Finnish twin study, [11C]SCH 23390 was used to estimate D1-R in 9 patients with chronic schizophrenia compared to that of 11 healthy co-twins of patients, as well as 13 healthy control twins (independent twin pairs) [68]. BPNDwas quantified using the SRTM, for striatum as well as a range of cortical regions. For the main analysis, statistically lower BPNDin patients compared to healthy co-twins was reported for striatal (mean d = −1.13 (DZ); −1.48 (MZ) as well as most cortical regions (mean d for significant regions = −1.24 (DZ), −1.60 (MZ)).
Although statistical tests for the comparison between patients and control twins were not reported in the paper, D1-R binding appeared to be lower in patients, with average effect sizes of −1.18 for striatal regions and −0.58 for cortical regions.
Given that these somewhat conflicting results in schizophrenia pa- tients were obtained using different radioligands, Kosaka et al. in- vestigated a group of six patients in residual phase and 12 age-matched
Table1 PETstudiescomparingD1-Rbindinginpsychiatricpatientstothatofhealthycontrolsubjects. PublicationPopulationPatientage(mean (SD))HCage(mean (SD))MedicationRadioligandOutcome measureKineticmodelStatisticallysignificant differencesAverageESstriatal (d)AverageEScortical (d) Okuboetal.[63]17SCZ18HC27.4(5.9)27.7(5.6)10DN,7DFSCHBPND2TCMk3/k4PFC↓−0.06(DN);−0.52 (DF)−0.58(DN);−1.02 (DF) Abi-Darghametal. [65]16SCZ16HC33(12)34(10)7DN,9DFNNCBPP2TCM(VT−VND)DLPFC↑0.060.62 Karlssonetal.[64]10SCZ10HC24.5(2.3)26.3(3.6)DNSCHBPFBmax/KDn.d.−0.350.32 Hirvonenetal.[68]9SCZ11HC*49.9(3.8)MZ49.9(3.8)MedicatedSCHBPNDSRTMcaudate,putamen,cortical regions↓−1.31−1.24 DZ52.8(5.3) Kosakaetal.[69]6SCZ12HC46.5(8.2)42.8(8.5)Medicated**SCH,NNCBPNDSRTMfrontalcx,ACC,temporalcx, striatum↓−2.22(SCH), −2.09(NNC)−2.31(SCH),−2.36 (NNC) Abi-Darghametal. [71]25SCZ48HCDF30.6(10.2)DF30.3(9.8)13DF,12DNNNCBPP2TCM(VT−VND)DLPFC,MPFC,OFC↑(DN)0.60(DN);−0.09 (DF)0.93(DN);−0.25 (DF) DN25.4(4.8)DN25.4(4.7)BPND2TCM((VT−VND)/ VND)n.d.N/AN/A Suharaetal.[77]10BD21HC41.8(9.7)HC39.5 (15.9)***DFSCHBPND2TCMk3/k4****frontalcx↓−0.39−2.00 Doughertyetal.[78]10MDD+A10HC43.1(7.1)41.6(6.4)noinformationSCHBPNDSRTMrightandleftstriatum↓−0.95N/A Cannonetal.[79]18MDD19HC31.(8.5)31(11)DFNNCBPNDMRTMleftmiddlecaudate↓−0.29−0.03 Olveretal.[80,81]7OCD7HC40.0(13.9)40.3(12.3)2DN,5DFSCHBPNDN/AN/A*****N/A*****N/A***** Narendranetal.[84]14KetamineCU14 HC25(4)26(5)–NNCBPP2TCM(VT−VND)DLPFC↑0.20.52 BPND2TCM((VT−VND)/ VND)DLPFC↑0.540.47 Martinezetal.[85]24CD23HC40(4)38(4)–NNCBPP2TCM(VT−VND)n.d.0.11−0.10 BPND2TCM((VT−VND)/ VND)n.d.−0.26−0.49 SD=standarddeviation;ES=effectsize(Cohen'sd);SCZ=schizophreniapatients;HC=healthycontrolsubjects;BD=bipolardisorder;MDD+A=majordepressionwithangerattacks;DN=drugnaïve;DF=drug free;OCD=obsessivecompulsivedisorder;CD=cocainedependence;CU=chronicusers;NNC=[11C]NNC112;SCH=[11C]SCH23390;2TCM=twotissuecompartmentmodel;BPND=bindingpotential(specific overnon-displaceablebinding);BPP=bindingpotential(specificbindingovertotalplasma);MRTM=multilinearreference-tissuemodel;PFC=prefrontalcortex;DLPFC=dorsolateralprefrontalcortex; ACC=anteriorcingulatecortex;MFC=medialfrontalcortex;OFC=orbitofrontalcortex;n.s.=nonsignificant;*HCformainanalysisconsistedofunaffectedco-twinsofpatients.Effectsizesreportedasaveragesfor mono-anddizogytictwins.**Allpatients’medicationwerechangedtosulpiride;***DataextractedfromFig.1;SRTM=simplifiedreferencetissuemodel;****k3/k4wasestimatedbyfittingtargetandreferencetime activitycurvestoaconvolutionequation;*****reportedbindingdataandeffectsizesconsideredunrealistic.
control subjects using both [11C]NNC 112 and [11C]SCH 23390 [69]. In all patients, previously used antipsychotics were discontinued and changed to sulpiride, which is a selective D2/D3-R antagonist with low affinity for D1-R [70]. For both tracers, BPNDwas calculated using the SRTM, with cerebellum as reference region. The correlation between D1-R binding for the two tracers was R2= 0.74. Significantly lower binding values in patients were found in all cortical and striatal brain regions examined, with effect sizes in striatum of −2.22 for [11C]SCH 23390 and −2.09 for [11C]NCC 112. For extrastriatal regions the cor- responding values were −2.67 and −2.80 for frontal cortex, −1.59 and −1.66 for anterior cingulate and −2.66 and −2.63 for temporal cortex.
Finally, Abi-Dargham and colleagues used PET and [11C]NCC 112 to examine a new cohort of schizophrenia patients, all of whom were drug-free, and 12 drug-naïve [71]. Data was quantified using 2TCM for target regions and 1TCM for cerebellum, using distribution volumes to derive BPPas described above, as well as BPND((VT− VND)/VND). A significant increase was found in all cortical regions in drug naïve pa- tients when using BPPas outcome measure (d = 1.03 for dorsolateral prefrontal cortex, 0.74 for medial frontal cortex, 1.03 for orbitofrontal cortex), but not for drug-free patients (mean d = −0.25). No differ- ences in either group were observed when employing BPND, a dis- crepancy that according to the authors could have been explained by trend-level group differences in VND. In a subsequent publication, tracer-specific effects were explored by using [11C]SCH 23390 and [11C]NNC 112 in a subgroup of 8 patients and 12 healthy control subjects from the same cohort, showing no tracer by diagnosis inter- actions [72].
Of all studies on D1-R in schizophrenia, the two reports showing higher levels included only drug-free patients, with a substantial part of the patients being drug-naïve [65,71]. In the only study on drug-free and drug-naive patients showing decreases [63], binding potential was ob- tained using 2TCM with plasma as input function, a method that has shown low reliability for [11C]SCH 23390 [44] . Moreover, in studies where both drug-free and drug naïve patients were included, subgroup analyses showed that patients with previous antipsychotic treatment had numerically lower binding compared to patients without such exposure [71,63]. Although these comparison were post-hoc (i.e. DN and DF pa- tient were not matched) and therefore should be interpreted cautiously, the data is suggestive of a reduction in D1-R being caused by anti- psychotic medication. This is in line with experimental post-mortem studies in non-human primates, showing a clear downregulation of D1-R density after treatment with classical D2-antagonists as well as cloza- pine, as assessed using both quantitative autoradiography and mRNA levels [73,74]. Further support comes from the large decreases in D1-R binding observed in treated patients compared to healthy monozygotic co-twins [68]. Although a direct occupancy effect by the medication cannot be fully excluded, the reported effect sizes are striking con- sidering the high ICC values reported between healthy control MZ twins (0.71-0.8 for striatum) [68], paralleling data for D2/D3 that together suggest a largely genetic regulation of DA-R [75].
In addition to studying drug-naïve patients, another approach to circumvent the confounding effects of medication is to investigate re- latives to patients, or conditions showing a genetic overlap with schi- zophrenia, with the assumption that the shared genetic liability would translate to similarities in brain biochemical markers. In the twin study by Hirvonen et al., unaffected co-twins to schizophrenia patients showed higher cortical D1-R levels compared to healthy twins without an af- fected sibling [68]. The effect was tested statistically for monozygotic twins (n = 6 vs n = 13), reaching significance for some cortical regions (average d for cortical regions = 0.66) whereas no significant difference was found for striatum (d = 0.33). Additional evidence in favour of a role of increased D1-R in psychosis comes from a study in schizotypal personality disorder, a condition sharing genetic risk with schizophrenia, where higher prefrontal D1-R availability as assessed using BPFand BPP
was associated with poorer working performance [76].
3.2. Affective disorders
In patients with affective disorders, PET studies on the DA system have mainly focused on D2-R, showing inconclusive results [4]. In contrast, studies on D1-R have been more scarce. Suhara and colleagues used PET and [11C]SCH 23390 in 21 healthy control subjects and 10 bipolar patients, of which 3 experienced a depressive episode, one a mild manic episode, and 6 were euthymic [77]. BPND values were calculated by fitting the difference between the ROI curve and the re- ference tissue curve to a convolution equation (ROI − reference tissue = reference tissue convolved with k3exp(-k4t)). Patients showed lower D1-R binding in frontal cortex, whereas no difference in BPND
was found in the striatum. Summary statistics were not provided, but by extracting BPNDvalues from the graphs, the effect size for frontal cortex was estimated to be d = −2.0. Using the same radioligand, Dougherty et al., studied 10 patients with major depressive disorder with anger attacks and 10 control subjects [78]. SRTM was used to calculate D1-R BPNDin striatal regions, finding lower D1-R levels bilaterally (mean d = −0.95). Finally, Cannon et al. used [11C]NNC 112 to examine 18 patients with major depression (MDD) and 19 healthy controls [79].
Binding was quantified using a multilinear reference-tissue model (MRTM) to obtain parametric BPNDimages. 5 striatal regions with right and left side analysed separately were chosen for the primary analysis, whereas amygdala, insula and anterior cingulate cortex were included as a post-hoc exploratory analysis. A statistically significant lower binding in left middle caudate was reported (d = −0.74). No correc- tion for multiple comparisons was employed. Effect sizes for the other regions included in the analysis ranged from −0.49 to 0.04.
3.3. Obsessive-compulsive disorder
There are two published papers on D1-R in obsessive-compulsive disorder (OCD), based on the same sample of 7 drug free OCD patients and 7 healthy control subjects investigated using [11C]SCH 23390. In the first report, caudate and putamen were used as primary regions of interest [80], and in a subsequent publication the analysis was extended to include the anterior cingulate cortex (ACC) [81]. When describing the method of quantification, the authors state that cerebellum was used as a reference region, citing Lammertsma et al. (1996) [46] which describes the SRTM, but then Logan graphical analysis is given as the method used to obtain distribution volume ratios. However, this ap- proach requires an arterial input function [82] and there is no in- formation given on collection of arterial samples. Moreover, if a linear method was indeed used, it is not clear if the analysis was restricted to a range after the equilibrium time, and if so which t* was used. The re- ported BP values (0.52 − 1.14 for striatum, 0.13 − 0.29 for ACC) as well as the coefficient of variance COV (3 − 8% for the healthy control subjects) are much lower than what is typically observed for [11C]SCH 23390 BPND(mean COV for all ROIs reported in healthy controls in the present review is around 15%). Statistically significant reductions were reported in patients with effect sizes of −4.83 and −4.17 for caudate and putamen, and −4.71 and −5.14 for right and left ACC respec- tively. Notably, a Cohens d of 5 corresponds to only a 1.24% overlap between groups, a magnitude of difference which is extreme compared to what is normally obtained in biomedical research [83]. Given these uncertainties, the results from this study should be interpreted with caution.
3.4. Substance abuse disorders
The DA system has long been of central interest in research on drug addiction. PET research has focused primarily on the D2/D3-R, and to date only two studies have investigated D1-R. In a study by Narendran et al. (2005), 14 individuals with chronic ketamine use and 14 healthy control subjects were examined using [11C]NNC 112 [84]. Data were analysed using 2TCM and 1TCM, with BPPand BPNDcalculated using
distribution volumes as described above. Dorsolateral prefrontal cortex was the ROI used for primary analysis, and a total of 13 additional cortical, limbic and striatal regions were examined for exploratory purposes. A statistically significant increase in patients compared to healthy controls was observed in the primary ROI (d = 0.88 (BPP), 0.87 (BPND)), with no other regions showing any differences.
In psychostimulant abuse, a series of PET studies have showed lower D2/D3-R binding in striatum in patients compared to control subjects, as well as blunted DA release [2,20]. Following experimental data suggesting a role also for the D1-R, Martinez et al. (2009) investigated 24 patients with cocaine addiction and 23 healthy control subjects using [11C]NNC 112 [85]. Regions included in the primary analysis were functional subregions of the striatum as well as a range of cortical regions, and quantification was performed as in [84]. No statistically significant difference was observed between patients and control sub- jects, in striatum (d = 0.11 (BPP) and −0.26 (BPND)), or cortical re- gions (d=−0.1 and −0.49). A significant correlation was observed between D1-R BPNDin ventral striatum and the choice for cocaine at the 6 mg level, but no relationship was found for any other subregion, when using BPPas outcome measure, or when analysing behavioural data for higher doses.
4. Discussion
Compared to other markers of the DA system, only a limited number of studies have investigated D1-R in psychiatric disorders. In schizo- phrenia, which is the most studied condition with a total of 83 identi- fied unique patients, results have been somewhat discrepant. Although studies were not designed to specifically investigate the effect of anti- psychotic medication, the data strongly suggests that antipsychotic drugs cause a decrease in D1-R, an observation which is in line with non-human experimental data [73,74]. When taking this confounder into account, the overall evidence is arguably in favour of higher levels of D1-R in frontal cortical regions in patients suffering from psychosis symptoms. Differences in quantification methods and small sample sizes limit the conclusions that can be drawn, but if replicated, the re- sults may indicate a specific role of D1-R in psychosis, alternatively they may reflect an upregulation in response to a reduction in cortical DA release [86,87]. For affective disorders, a lower striatal D1-R levels is suggested in depression, as well as reductions in cortical D1-R in bipolar patients. However, the total sample size for these conditions is con- siderably smaller than for schizophrenia and the results should be viewed as preliminary. Similarly, the higher D1-R levels shown in frontal cortex for chronic ketamine users is in need for replication.
A number of factors have to be considered when interpreting the data. With existing PET radioligands, it is not possible to obtain a fully unbiased measure of cortical D1-R. 5HT2a-R receptor binding may account for around 25% of the cortical binding for both [11C]SCH 23390 and [11C]NCC 112 [23,52], which reflects that 5HT2a-R shows about two-fold density compared to D1 in cortical regions in nonhuman primates [88] and has shown to be abundant also in human cortex [89].
5HT2a-R has shown to be implicated in both schizophrenia and de- pression based on genetic associations and gene expression data [90–92], and both established and more recently developed anti- psychotics show an affinity for 5HT2a [93,94]. In schizophrenia, the follow-up study by Okubo et al. showed trend-level lower 5HT2 binding as measured using PET and [11C]NMSP in neuroleptic-treated patients, which could have contributed to the observed decreases in [11C]SCH 23390 binding, whereas no difference was found in drug-naïve patients [64,63]. Subsequently, lower binding of the 5HT2-R radioligand [18F]
altanserin was shown in a sample of 30 drug-naïve patients compared to control subjects [95]. Hence, it cannot be excluded that differences in 5HT2a-R density may have influenced the results for cortical regions in schizophrenia. In contrast, striatal 5HT2a-R density is 2–3 fold lower than striatal D1-R [40,96] and blocking of 5HT2a-R did not affect binding of either [11C]SCH 23390 or [11C]NCC 112 in striatal regions
[52], confirming that the influence of 5HT2a-R in this region should be negligible.
For D2/D3-R antagonist radioligands such as [11C]raclopride, sen- sitivity of binding to endogenous DA levels is well-documented [97,98].
For D1-R radioligands, ex vivo studies in rodents have shown no effect on [11C]SCH 23390 binding by amphetamine-induced DA release or DA depletion [99] whereas other studies found an increase in [11C]NNC 112 binding, and a paradoxical decrease of [11C]SCH 23390 binding in response to DA depletion [100,101]. In non-human primate in vivo studies neither [11C]SCH 23390 nor [11C]NNC 112 binding was shown to be affected by acute increases or decreases in endogenous DA caused by amphetamine and reserpine respectively [102,103]. Similar results of no change in response to amphetamine was observed for [11C]NNC 756 in baboons [103]. Dopamine depletion in human subjects using alpha-methyl-para-tyrosine did not change [11C]SCH 23390 binding, despite a clear increase in D2/D3-R binding as measured using [11C]
raclopride [104]. For the D2/D3-R, agonist radioligands have shown increased sensitivity to endogenous DA levels compared to antagonist radioligands [105]. One potential explanation is that D2/D3-R may exist in an active (G-protein-coupled state) and an inactive state, and that agonist radioligands only bind to the active state resulting in a larger degree of displacement by endogenous ligands. With regard to the D1-R, the agonist radioligand [11C]N-methyl-NNC 01–0259 failed to show any differences in response to amphetamine-induced DA re- lease [39]. Taken together, the available evidence does not support endogenous DA as a confounding factor in D1-R PET studies. Possible explanations for this lack of sensitivity to endogenous DA is the lower affinity for DA [10], a large degree of extra-synaptic receptor location [106,107] or that only a small fraction of dopamine D1-like receptors exist in the high-affinity state [108].
An important question is to what extent any differences in radi- oligand characteristics may have contributed to discrepancies between studies. Two studies on schizophrenia addressed this question directly by using [11C]SCH 23390 and [11C]NCC 112 in the same individuals, not finding any differences between the tracers with regard to group differences between patients and control subjects [72,69]. This lack of difference is in line with in vivo data showing similar contributions from 5HT2a-R, as well as lack of sensitivity to endogenous DA, as reviewed above. Another possible source of bias could be the use of different methods of quantification. For instance, some of the early studies with [11C]SCH 23390 used 2TCM-derived rate constants to estimate BPND
[63,77], an approach which has shown to be unsuitable for most radioligands [109,110]. For [11C]SCH 23390 in particular, binding parameters derived using 2TCM have shown low reliability and accu- racy [44], which may be due to the rapid metabolism of this tracer in plasma [111]. For three studies using [11C]NCC 112, results were re- ported using both BPPand BPND. In the study on schizophrenia by Abi- Dargham et al. (2012), statistically significant increases in patients compared to control subjects were found only for BPP, however com- parison of effect sizes between outcome measures was not possible since BPNDvalues were not reported. Notably, BPPrelies on the assumption of no differences in protein binding of the radioligand [45], which was trend-level different between groups. In the two remaining studies employing both BPP and BPND, both in substance use disorders, the outcome measures gave slightly different effect sizes [84,85] (Table 1).
A potential explanation for these differences could be that even minor group differences in VNDwould cause a relatively larger impact on BPND
compared to BPP, since it is included in the denominator [71].
One important general caveat that needs to be considered in the reviewed studies are the small sample sizes used. In 6 out of the 11 studies, only 10 or fewer patients were included. Given the difference in sample sizes, effect sizes were calculated to allow for an informal synthesis of the data, instead of comparing p-values. However, since the analysis was based on summary statistics, confounding variables were not possible to take into account in this analysis.
Low power is a problem in neuroscience research in general, and for
neuroimaging in particular, and can lead to both false negative and false positives [112]. Since PET is an expensive method and also in- volves radiation exposure, an important way forward for D1-R research in psychiatric populations would be to share data [113]. This can be done at the level of outcome measures to allow for an individual par- ticipant data meta-analysis, which makes it possible to take con- founders such as age and medication into account in a more formal way [116]. Alternatively, if raw data is shared this would also solve some of the methodological confounders by allowing for a harmonized re-ana- lysis. Arguably, data sharing may be particularly important in research on the pathophysiology of psychiatric disorders, where disease het- erogeneity is often considered to be high.
In summary, PET studies using radioligands for the D1-R has shown some promise as a means of investigating the DA system in psychiatric disorders. Additional work in larger sample sizes, ideally with more selective radioligands, are needed to evaluate D1-R as a candidate disease biomarker that could eventually be used to inform treatment.
Conflicts of interest
SC has received grant support from AstraZeneca as a co-investigator, and has served as a one-off speaker for Otsuka-Lundbeck.
Acknowledgements
Granville J. Matheson for providing figure and help with proof reading. S.C. is supported by a grant from the Swedish Research Council (523-2014-3467).
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