PET Imaging of the Serotonin 1A Receptor in Major Depressive Disorder: Hierarchical Multivariate Analysis of [11C]WAY100635 Overcomes Outcome Measure Discrepancies.

The serotonin 1A receptor has been linked to both the pathophysiology of major depressive disorder (MDD) and the antidepressant action of serotonin reuptake inhibitors. Most PET studies of the serotonin 1A receptor in MDD used the receptor antagonist radioligand, [carbonyl-11C]WAY100635; however the interpretation of the combined results has been contentious owing to reports of higher or lower binding in MDD with different outcome measures. The reasons for these divergent results originate from several sources, including properties of the radiotracer itself, which complicate its quantification and interpretation; as well as from previously reported differences between MDD and healthy volunteers in both reference tissue binding and plasma free fraction, which are typically assumed not to differ. Recently, we have developed two novel hierarchical multivariate methods which we validated for the quantification and analysis of [11C]WAY100635, which show better accuracy and inferential efficiency compared to standard analysis approaches. Importantly, these new methods should theoretically be more resilient to many of the factors thought to have caused the discrepancies observed in previous studies. We sought to apply these methods in the largest [11C]WAY100635 sample to date, consisting of 160 individuals, including 103 MDD patients, of whom 50 were not-recently-medicated and 53 were antidepressant-exposed, as well as 57 healthy volunteers. While the outcome measure discrepancies were substantial using conventional univariate analysis, our multivariate analysis techniques instead yielded highly consistent results across PET outcome measures and across pharmacokinetic models, with all approaches showing higher serotonin 1A autoreceptor binding potential in the raphe nuclei of not-recently-medicated MDD patients relative to both healthy volunteers and antidepressant-exposed MDD patients. Moreover, with the additional precision of estimates afforded by this approach, we can show that while binding is also higher in projection areas in this group, these group differences are approximately half of those in the raphe nuclei, which are statistically distinguishable from one another. These results are consistent with the biological role of the serotonin 1A autoreceptor in the raphe nuclei in regulating serotonin neuron firing and release, and with preclinical and clinical evidence of deficient serotonin activity in MDD due to over expression of autoreceptors resulting from genetic and/or epigenetic effects. These results are also consistent with downregulation of autoreceptors as a mechanism of action of selective serotonin reuptake inhibitors. In summary, the results using multivariate analysis approaches therefore demonstrate both face and convergent validity, and may serve to provide a resolution and consensus interpretation for the disparate results of previous studies examining the serotonin 1A receptor in MDD.

Nonlinear Mixed-Effects Modeling Approach for Simplified Reference Tissue Model.

OBJECTIVE: The conventional approach to the analysis of dynamic PET data can be described as a two-stage approach. In Stage 1, each individual's kinetic parameter estimates are obtained by modeling their PET data. Then in Stage 2, those parameter estimates are treated as though they are the observed data and compared across subjects and groups using standard statistical analyses. In this context, we explore the application of nonlinear mixed-effects (NLME) model under the assumptions of simplified reference tissue model. METHODS: In the NLME framework, all subject's PET data are modeled simultaneously and the estimation of kinetic parameters and statistical inference across subjects are performed jointly. RESULTS: In simulated [ 11C]WAY100635 data, this NLME approach shows improved power (6-27% increase) for detecting group differences and greater consistency of population (1.13-1.44 times greater) and individual-level parameter estimation compared to the two-stage approach applying simplified reference tissue model for pharmacokinetic modeling of PET data. We applied our NLME approach to clinical PET data and observed shrinkage of individual-level parameters that is inherent in this modeling structure. CONCLUSION: The proposed approach is more powerful and accurate than the two-stage approach under the assumptions of simplified reference tissue model in PET data. SIGNIFICANCE: The stability of the NLME approach not only improves the efficiency of collected data, but also comes with no additional financial cost and negligible computation cost.

Parametric and non-parametric Poisson regression for modelling of the arterial input function in positron emission tomography.

Full quantification of Positron Emission Tomography (PET) requires an arterial input function (AIF) for measurement of certain targets, or using particular radiotracers, or for the quantification of specific outcome measures. The AIF represents the measurement of radiotracer concentrations in the arterial blood plasma over the course of the PET examination. Measurement of the AIF is prone to error as it is a composite measure created from the combination of multiple measurements of different samples with different equipment, each of which can be sources of measurement error. Moreover, its measurement requires a high degree of temporal granularity for early time points, which necessitates a compromise between quality and quantity of recorded samples. For these reasons, it is often desirable to fit models to this data in order to improve its quality before using it for quantification of radiotracer binding in the tissue. The raw observations of radioactivity in arterial blood and plasma samples are derived from radioactive decay, which is measured as a number of recorded counts. Count data have several specific properties, including the fact that they cannot be negative as well as a particular mean-variance relationship. Poisson regression is the most principled modelling strategy for working with count data, as it both incorporates and exploits these properties. However, no previous studies to our knowledge have taken this approach, despite the advantages of greater efficiency and accuracy which result from using the appropriate distributional assumptions. Here, we implement a Poisson regression modelling approach for the AIF as proof-of-concept of its application. We applied both parametric and non-parametric models for the input function curve. We show that a negative binomial distribution is a more appropriate error distribution for handling overdispersion. Furthermore, we extend this approach to a hierarchical non-parametric model which is shown to be highly resilient to missing data. We thus demonstrate that Poisson regression is both feasible and effective when applied to AIF data, and propose that this is a promising strategy for modelling blood count data for PET in future.

Multivariate analysis of PET pharmacokinetic parameters improves inferential efficiency.

PURPOSE: In positron emission tomography quantification, multiple pharmacokinetic parameters are typically estimated from each time activity curve. Conventionally all but the parameter of interest are discarded before performing subsequent statistical analysis. However, we assert that these discarded parameters also contain relevant information which can be exploited to improve the precision and power of statistical analyses on the parameter of interest. Properly taking this into account can thereby draw more informative conclusions without collecting more data. METHODS: By applying a hierarchical multifactor multivariate Bayesian approach, all estimated parameters from all regions can be analysed at once. We refer to this method as Parameters undergoing Multivariate Bayesian Analysis (PuMBA). We simulated patient-control studies with different radioligands, varying sample sizes and measurement error to explore its performance, comparing the precision, statistical power, false positive rate and bias of estimated group differences relative to univariate analysis methods. RESULTS: We show that PuMBA improves the statistical power for all examined applications relative to univariate methods without increasing the false positive rate. PuMBA improves the precision of effect size estimation, and reduces the variation of these estimates between simulated samples. Furthermore, we show that PuMBA yields performance improvements even in the presence of substantial measurement error. Remarkably, owing to its ability to leverage information shared between pharmacokinetic parameters, PuMBA even shows greater power than conventional univariate analysis of the true binding values from which the parameters were simulated. Across all applications, PuMBA exhibited a small degree of bias in the estimated outcomes; however, this was small relative to the variation in estimated outcomes between simulated datasets. CONCLUSION: PuMBA improves the precision and power of statistical analysis of PET data without requiring the collection of additional measurements. This makes it possible to study new research questions in both new and previously collected data. PuMBA therefore holds great promise for the field of PET imaging.

Experimental Sleep Deprivation Results in Diminished Perceptual Stability Independently of Psychosis Proneness.

Psychotic disorders as well as psychosis proneness in the general population have been associated with perceptual instability, suggesting weakened predictive processing. Sleep disturbances play a prominent role in psychosis and schizophrenia, but it is unclear whether perceptual stability diminishes with sleep deprivation, and whether the effects of sleep deprivation differ as a function of psychosis proneness. In the current study, we aimed to clarify this matter. In this preregistered study, 146 participants successfully completed an intermittent version of the random dot kinematogram (RDK) task and the 21-item Peters Delusion Inventory (PDI-21) to assess perceptual stability and psychosis proneness, respectively. Participants were randomized to sleep either as normal (8 to 9 h in bed) (n = 72; Mage = 24.7, SD = 6.2, 41 women) or to stay awake through the night (n = 74; Mage = 24.8, SD = 5.1, 44 women). Sleep deprivation resulted in diminished perceptual stability, as well as in decreases in perceptual stability over the course of the task. However, we did not observe any association between perceptual stability and PDI-21 scores, nor a tendency for individuals with higher PDI-21 scores to be more vulnerable to sleep-deprivation-induced decreases in perceptual stability. The present study suggests a compromised predictive processing system in the brain after sleep deprivation, but variation in psychosis trait is not related to greater vulnerability to sleep deprivation in our dataset. Further studies in risk groups and patients with psychosis are needed to evaluate whether sleep loss plays a role in the occurrence of objectively measured perceptual-related clinical symptoms.

Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden.

BACKGROUND: Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data. METHODS: We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CLLi) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CLLi,age/sex), were used as the dependent variable in a GWAS. FINDINGS: 2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R2]: R2cohort1=0·41 and R2cohort2=0·31; both p<0·0001), sex (R2cohort1=0·0063 [p=0·045] and R2cohort2=0·026 [p<0·0001]), eGFR (R2cohort1=0·38 and R2cohort2=0·20; both p<0·0001), comedication with diuretics (R2cohort1=0·0058 [p=0·014] and R2cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R2cohort1=0·028 and R2cohort2=0·015; both p<0·0001) were clinical predictors of CLLi. Notably, an association between CLLi and serum lithium was observed, with a lower CLLi being associated with higher serum lithium (R2cohort1=0·13 and R2cohort2=0·15; both p<0·0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; ß=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CLLi in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components. INTERPRETATION: Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CLLi introduces the opportunity of individualised medicine in lithium treatment. FUNDING: Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.

Simultaneous multifactor Bayesian analysis (SiMBA) of PET time activity curve data.

Positron emission tomography (PET) is an in vivo imaging method essential for studying the neurochemical pathophysiology of psychiatric and neurological disease. However, its high cost and exposure of participants to radiation make it unfeasible to employ large sample sizes. The major shortcoming of PET imaging is therefore its lack of power for studying clinically-relevant research questions. Here, we introduce a new method for performing PET quantification and analysis called SiMBA, which helps to alleviate these issues by improving the efficiency of PET analysis by exploiting similarities between both individuals and regions within individuals. In simulated [11C]WAY100635 data, SiMBA greatly improves both statistical power and the consistency of effect size estimation without affecting the false positive rate. This approach makes use of hierarchical, multifactor, multivariate Bayesian modelling to effectively borrow strength across the whole dataset to improve stability and robustness to measurement error. In so doing, parameter identifiability and estimation are improved, without sacrificing model interpretability. This comes at the cost of increased computational overhead, however this is practically negligible relative to the time taken to collect PET data. This method has the potential to make it possible to test clinically-relevant hypotheses which could never be studied before given the practical constraints. Furthermore, because this method does not require any additional information over and above that required for traditional analysis, it makes it possible to re-examine data which has already previously been collected at great expense. In the absence of dramatic advancements in PET image data quality, radiotracer development, or data sharing, PET imaging has been fundamentally limited in the scope of research hypotheses which could be studied. This method, especially combined with the recent steps taken by the PET imaging community to embrace data sharing, will make it possible to greatly improve the research possibilities and clinical relevance of PET neuroimaging.

Thalamic dopamine D2-receptor availability in schizophrenia: a study on antipsychotic-naive patients with first-episode psychosis and a meta-analysis.

Pharmacological and genetic evidence support a role for an involvement of the dopamine D2-receptor (D2-R) in the pathophysiology of schizophrenia. Previous molecular imaging studies have suggested lower levels of D2-R in thalamus, but results are inconclusive. The objective of the present study was to use improved methodology to compare D2-R density in whole thalamus and thalamic subregions between first-episode psychosis patients and healthy controls. Differences in thalamocortical connectivity was explored based on the D2-R results. 19 antipsychotic-naive first-episode psychosis patients and 19 age- and sex-matched healthy controls were examined using high-resolution Positron Emission Tomography (PET) and the high-affinity D2-R radioligand [11C]FLB457. The main outcome was D2-R binding potential (BPND) in thalamus, and it was predicted that patients would have lower binding. Diffusion tensor imaging (DTI) was performed in a subgroup of 11 patients and 15 controls. D2-R binding in whole thalamus was lower in patients compared with controls (Cohen's dz = -0.479, p = 0.026, Bayes Factor (BF) > 4). Among subregions, lower BPND was observed in the ROI representing thalamic connectivity to the frontal cortex (Cohen's dz = -0.527, p = 0.017, BF > 6). A meta-analysis, including the sample of this study, confirmed significantly lower thalamic D2-R availability in patients. Exploratory analyses suggested that patients had lower fractional anisotropy values compared with controls (Cohen's d = -0.692, p = 0.036) in the inferior thalamic radiation. The findings support the hypothesis of a dysregulation of thalamic dopaminergic neurotransmission in schizophrenia, and it is hypothesized that this could underlie a disturbance of thalamocortical connectivity.

A positron emission tomography study of the serotonin1B receptor effect of electroconvulsive therapy for severe major depressive episodes.

BACKGROUND: Electroconvulsive therapy (ECT) is an effective treatment for depressive disorders, although its molecular mechanism of action is unknown. The serotonin 1B (5-HT1B) receptor is a potential target for treatment of depression and low 5-HT1B receptor binding in limbic regions has been reported in previous positron emission tomography (PET) studies of depression. METHODS: The objective of this longitudinal PET study was to examine the effect of ECT for depression on 5-HT1B receptor binding. Fifteen hospitalized patients with major depressive episodes were examined with PET and the 5-HT1B receptor selective radioligand [11C]AZ10419369, before and after ECT. Fifteen controls matched for age and sex were examined. Limbic regions with previously reported low 5-HT1B receptor binding in depression and a dorsal brain stem region were selected. RESULTS: Thirteen patients completed the study according to protocol. Eleven out of thirteen patients responded to ECT. 5-HT1B receptor binding in hippocampus increased with 30 % after ECT (p=0.021). Using linear mixed effects modelling, we observed increases in 5-HT1B receptor binding following ECT with a moderate to large effect size, which did not differ significantly between regions. In an exploratory analysis, strong correlations between changes in 5-HT1B receptor binding and agitation scores on the Hamilton Depression Rating Scale after ECT were observed. LIMITATIONS: Albeit representative of a PET study, the sample size is still small and there are potential confounding effects of medication. CONCLUSIONS: Increased 5-HT1B receptor binding was observed following ECT for depression, corresponding to previous findings of increased 5-HT1B receptor binding in hippocampus after rapid acting ketamine for treatment resistant depression.

Test-Retest Reliability and Consistency of HVPG and Impact on Trial Design: A Study in 289 Patients from 20 Randomized Controlled Trials.

BACKGROUND AND AIMS: Portal hypertension (PH) is a major driver for cirrhosis complications. Portal pressure is estimated in practice by the HVPG. The assessment of HVPG changes has been used for drug development in PH. This study aimed at quantifying the test-retest reliability and consistency of HVPG in the specific context of randomized controlled trials (RCTs) for the treatment of PH in cirrhosis and its impact on power calculations for trial design. APPROACH AND RESULTS: We conducted a search of published RCTs in patients with cirrhosis reporting individual patient-level data of HVPG at baseline and after an intervention, which included a placebo or an untreated control arm. Baseline and follow-up HVPGs in the control groups were extracted after digitizing the plots. We assessed reliability and consistency and the potential impact of study characteristics. We retrieved a total of 289 before and after HVPG measurements in the placebo/untreated groups from 20 RCTs. The time span between the two HVPG measurements ranged between 20 minutes and 730 days. Pre-/post-HVPG variability was lower in studies including only compensated patients; therefore, modeled sample size calculations for trials in compensated cirrhosis were lower than for decompensated cirrhosis. A higher proportion of alcohol-associated cirrhosis and unicentric trials was associated with lower differences between baseline and follow-up measurements. The smallest detectable difference in an individual was 26% and 30% in compensated and decompensated patients, respectively. CONCLUSIONS: The test-retest reliability of HVPG is overall excellent. Within-individual variance was higher in studies including higher proportions of decompensated patients. These findings should be taken into account when performing power analysis for trials based on the effects on HVPG or when considering HVPG as a tool to guide therapy of PH.

Low convergent validity of [11C]raclopride binding in extrastriatal brain regions: A PET study of within-subject correlations with [11C]FLB 457.

Dopamine D2 receptors (D2-R) in extrastriatal brain regions are of high interest for research in a wide range of psychiatric and neurologic disorders. Pharmacological competition studies and test-retest experiments have shown high validity and reliability of the positron emission tomography (PET) radioligand [11C]FLB 457 for D2-R quantification in extrastriatal brain regions. However, this radioligand is not available at most research centers. Instead, the medium affinity radioligand [11C]raclopride, which has been extensively validated for quantification of D2-R in the high-density region striatum, has been applied also in studies on extrastriatal D2-R. Recently, the validity of this approach has been questioned by observations of low occupancy of [11C]raclopride in extrastriatal regions in a pharmacological competition study with quetiapine. Here, we utilise a data set of 16 healthy control subjects examined with both [11C]raclopride and [11C]FLB 457 to assess the correlation in binding potential (BPND) in extrastriatal brain regions. BPND was quantified using the simplified reference tissue model with cerebellum as reference region. The rank order of mean regional BPND values were similar for both radioligands, and corresponded to previously reported data, both post-mortem and using PET. Nevertheless, weak to moderate within-subject correlations were observed between [11C]raclopride and [11C]FLB 457 BPND extrastriatally (Pearson's R: 0.30-0.56), in contrast to very strong correlations between repeated [11C]FLB 457 measurements (Pearson's R: 0.82-0.98). In comparison, correlations between repeated [11C]raclopride measurements were low to moderate (Pearson's R: 0.28-0.75). These results are likely related to low signal to noise ratio of [11C]raclopride in extrastriatal brain regions, and further strengthen the recommendation that extrastriatal D2-R measures obtained with [11C]raclopride should be interpreted with caution.

Reliability of dopamine transporter PET measurements with [18F]FE-PE2I in patients with Parkinson's disease.

BACKGROUND: Reliable quantification of dopamine transporter (DAT), a biomarker for Parkinson's disease (PD), is essential for diagnostic purposes as well as for evaluation of potential disease-modifying treatment. Due to degeneration of dopaminergic neurons and thus lower expected radioligand binding to DAT, higher measurement variability in PD patients might be expected than earlier reproducibility results in healthy controls. Therefore, we aimed to examine the test-retest properties of [18F]FE-PE2I-PET in PD patients. METHODS: Nine patients with PD (Hoehn and Yahr stage < 3) were included (men/women 6/3; mean age 65.2 ± 6.8 years). Each patient underwent two [18F]FE-PE2I-PET measurements within 7-28 days. The outcome measure was non-displaceable binding potential generated using wavelet-aided parametric imaging with cerebellum as reference region. We assessed test-retest performance using estimates of reliability and repeatability. Regions for primary analysis were caudate, putamen, ventral striatum, and substantia nigra. Exploratory analysis was performed for functional subdivisions of the striatum. We also compared the more vs. less affected side. RESULTS: [18F]FE-PE2I showed absolute variability estimates of 5.3-7.6% in striatal regions and 11% in substantia nigra and ICCs of 0.74-0.97 (median 0.91). The absolute variability for functional striatal subdivisions was 6.0-9.6% and ICCs of 0.76-0.91 (median 0.91). The less affected substantia nigra exhibited greater consistency than the more affected side. According to power calculations based on the current sample size, DAT changes of 5-11% in the striatum and 28% in the substantia nigra can be detected with a power of 0.8 (p < 0.0125). CONCLUSION: DAT-PET measurements with [18F]FE-PE2I in PD patients showed good repeatability and reliability. The slightly lower reliability in the substantia nigra in patients may be explained by lower DAT density and smaller anatomical size. Power calculations suggest that [18F]FE-PE2I PET is a suitable marker for longitudinal DAT decline in PD. TRIAL REGISTRATION: EudraCT 2017-003327-29.

Dopamine D1 receptor availability is not associated with delusional ideation measures of psychosis proneness.

The dopamine D1 receptor (D1R) is thought to play a role in psychosis and schizophrenia, however positron emission tomography studies comparing patients and controls have been inconsistent. To circumvent some of the limitations of clinical studies, such as antipsychotic exposure, an alternative approach is to examine subclinical psychotic symptoms within the general population, i.e. psychosis proneness traits. In this study, we investigated whether D1R availability is associated with delusional ideation in healthy controls, in four experiments, using [11C]SCH23390 PET (n = 76) and psychometric questionnaires (n = 217). We performed exploratory analyses, direct self-replication, and confirmatory analyses using Bayesian statistical modelling. Collectively, we found strong evidence that there is little to no linear association between delusional ideation and D1R. If hypothesised changes in D1R in drug-naive psychosis patients can be confirmed, our results suggest that they may either occur at disease onset, or that they are associated with specific aspects of psychosis other than delusional ideation.

Guidelines for the content and format of PET brain data in publications and archives: A consensus paper.

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

AKT1 and genetic vulnerability to bipolar disorder.

AKT1 encodes a serine/threonine kinase that has as one of its best-known substrates glycogen synthase kinase-3 (GSK3), a primary target for lithium. AKT1 has been previously been implicated as a vulnerability gene for bipolar disorder (BD). We aimed to associate genetic variants in the AKT1 gene with subgroups of BD. BD patients from a Swedish cohort (N = 831) were phenotyped in regards to their psychotic episodes according to mood-congruence in depression and manias, and compared to controls (N = 1,496). All participants were genotyped for SNPs in AKT1 previously implicated to have a role: rs3730358, rs1130214 and rs3803300. None of the effects reported in earlier studies were statistically significant, including the association between rs3803300 and BD without any psychotic symptoms, rs3803300 and mood-congruent psychosis, rs3803300 and the combined groups, as well as the association between the haplotypes formed by rs3730358 and rs1130214 and risk for BD. In a Bayesian analysis, all Bayes' Factors using default priors supported the null hypothesis in the replication set by a factor of between 5 and 1300 times. Analysis of genome wide association data did not reveal any association between BD and the AKT1 region. We conclude AKT1 is less likely to be a vulnerability gene in BD.

We need to talk about reliability: making better use of test-retest studies for study design and interpretation.

Neuroimaging, in addition to many other fields of clinical research, is both time-consuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is exacerbated by the use of outcome measures whose accuracy is sometimes insufficient to answer the scientific questions posed. Reliability is usually assessed in validation studies using healthy participants, however these results are often not easily applicable to clinical studies examining different populations. I present a new method and tools for using summary statistics from previously published test-retest studies to approximate the reliability of outcomes in new samples. In this way, the feasibility of a new study can be assessed during planning stages, and before collecting any new data. An R package called relfeas also accompanies this article for performing these calculations. In summary, these methods and tools will allow researchers to avoid performing costly studies which are, by virtue of their design, unlikely to yield informative conclusions.

D1-Dopamine Receptor Availability in First-Episode Neuroleptic Naive Psychosis Patients.

BACKGROUND: Positron emission tomography studies examining differences in D1-dopamine receptor binding between control subjects and patients with schizophrenia have been inconsistent, reporting higher, lower, and no difference in the frontal cortex. Exposure to antipsychotic medication has been suggested to be a likely source of this heterogeneity, and thus there is a need for studies of patients at early stages of the disorder who have not been exposed to such drugs. METHODS: Here, we compared 17 healthy control subjects and 18 first-episode neuroleptic naive patients with schizophrenia or schizophreniform psychosis using positron emission tomography and the D1-dopamine receptor radioligand [11C]SCH23390. RESULTS: We observed a statistically significant difference in the dorsolateral prefrontal cortex. Contrary to our expectations, patients had less D1-dopamine receptor availability with a moderate effect size. In a Bayesian analysis, we show that the data are over 50 times more likely to have occurred under the decrease as opposed to the increase hypothesis. This effect was not global, as our analysis showed that the null hypothesis was preferred over either hypothesis in the striatum. CONCLUSIONS: This investigation represents the largest single sample of neuroleptic-naive patients examined for D1-dopamine receptor availability using PET and suggests a reduction of prefrontal D1-dopamine receptor density in the pathophysiology of schizophrenia. However, further work will be required to reach a consensus.

Serotonin 5-HT1A receptor binding and self-transcendence in healthy control subjects-a replication study using Bayesian hypothesis testing.

OBJECTIVE: A putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis. METHODS: Regional 5-HT1A receptor binding potential (BPND) was examined in 50 healthy male subjects using PET with the radioligand [11C]WAY100635. 5-HT1Aavailability was calculated using the simplified reference tissue model (SRTM) yielding regional BPND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT1ABPND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs. RESULTS: There were no significant correlations between 5-HT1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT1A availability and ST/SA, while the remaining BF provided only weak evidence. CONCLUSION: We could not replicate our previous findings of an association between 5-HT1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.