Measuring specific receptor binding of a PET radioligand in human brain without pharmacological blockade: The genomic plot

Emerging biomedical imaging-based companion diagnostics for precision medicine

The tumor heterogeneity, which leads to individual variations in tumor microenvironments, causes poor prognoses and limits therapeutic response. Emerging technology such as companion diagnostics (CDx) detects biomarkers and monitors therapeutic responses, allowing identification of patients who would benefit most from treatment. However, currently, most US Food and Drug Administration-approved CDx tests are designed to detect biomarkers in vitro and ex vivo, making it difficult to dynamically report variations of targets in vivo. Various medical imaging techniques offer dynamic measurement of tumor heterogeneity and treatment response, complementing CDx tests. Imaging-based companion diagnostics allow for patient stratification for targeted medicines and identification of patient populations benefiting from alternative therapeutic methods. This review summarizes recent developments in molecular imaging for predicting and assessing responses to cancer therapies, as well as the various biomarkers used in imaging-based CDx tests. We hope this review provides informative insights into imaging-based companion diagnostics and advances precision medicine.

Grey matter volume loss in Parkinson's disease psychosis and its relationship with serotonergic gene expression: A meta-analysis

BACKGROUND

Neuroanatomical alterations underlying psychosis in Parkinson's Disease (PDP) remain unclear. We carried out a meta-analysis of MRI studies investigating the neural correlates of PDP and examined its relation with dopaminergic and serotonergic receptor gene expression.

METHODS

PubMed, Web of Science and Embase were searched for MRI studies (k studies = 10) of PDP compared to PD patients without psychosis (PDnP). Seed-based d Mapping with Permutation of Subject Images and multiple linear regression analyses was used to examine the relationship between pooled estimates of grey matter volume (GMV) loss in PDP and D1/D2 and 5-HT1a/5-HT2a receptor gene expression estimates from Allen Human Brain Atlas.

RESULTS

We observed lower grey matter volume in parietal-temporo-occipital regions (PDP n = 211, PDnP, n = 298). GMV loss in PDP was associated with local expression of 5-HT1a (b = 0.109, p = 0.012) and 5-HT2a receptors (b= -0.106, p = 0.002) but not dopaminergic receptors.

CONCLUSION

Widespread GMV loss in the parieto-temporo-occipital regions may underlie PDP. Association between grey matter volume and local expression of serotonergic receptor genes may suggest a role for serotonergic receptors in PDP.

Association of CNR1 gene and cannabinoid 1 receptor protein in the human brain

We aimed to integrate genomic mapping from brain mRNA atlas with the protein expression from positron emission tomography (PET) scans of type 1 cannabinoid (CB1) receptor and to compare the predictive power of CB1 receptor with those of other neuroreceptor/transporters using a meta-analysis. Volume of distribution (V_T ) from F18-FMPEP-d2 PET scans, CNR1 gene (Cannabinoid receptor 1) expression, and H3-CP55940 binding were calculated and correlation analysis was performed. Between V_T of F18-FMPEP-d2 PET scans and CNR1 mRNA expression, moderate strength of correlation was observed (rho = .5067, p = .0337). Strong positive correlation was also found between CNR1 mRNA expression and H3-CP55940 binding (r = .6336, p = .0364), validating the finding between F18-FMPEP-d2 PET scans and CNR1 mRNA. The correlation between V_T of F18-FMPEP-d2 PET scans and H3-CP55940 binding was marginally significant (r = .5025, p = .0563). From the meta-analysis, the correlation coefficient between mRNA expression and protein expressions ranged from -.10 to .99, with a pooled effect of .76. In conclusion, we observed the moderate to strong associations between gene and protein expression for CB1 receptor in the human brain, which was validated by autoradiography. We combined the autoradiographic finding with PET of CB1 receptor, producing the density atlas map of CB1 receptor. From the meta-analysis, the moderate to strong correlation was observed between mRNA expression and protein expressions across multiple genes. Further study is needed to investigate the relationship between multiple genes and in vivo proteins to improve and accelerate drug development.

Task-independent acute effects of delta-9-tetrahydrocannabinol on human brain function and its relationship with cannabinoid receptor gene expression: A neuroimaging meta-regression analysis

The neurobiological mechanisms underlying the effects of delta-9-tetrahydrocannabinol (THC) remain unclear. Here, we examined the spatial acute effect of THC on human regional brain activation or blood flow (hereafter called 'activation signal') in a 'core' network of brain regions from 372 participants, tested using a within-subject repeated measures design under experimental conditions. We also investigated whether the neuromodulatory effects of THC are related to the local expression of the cannabinoid-type-1 (CB1R) and type-2 (CB2R) receptors. Finally, we investigated the dose-response relationship between THC and key brain substrates. These meta-analytic findings shed new light on the localisation of the effects of THC in the human brain, suggesting that THC has neuromodulatory effects in regions central to many cognitive tasks and processes, related to dose, with greater effects in regions with higher levels of CB1R expression.

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.

First-in-human in vivo undefined imaging and quantification of monoacylglycerol lipase in the brain: a PET study with 18F-T-401

PURPOSE

Monoacylglycerol lipase (MAGL) regulates cannabinoid neurotransmission and the pro-inflammatory arachidonic acid pathway by degrading endocannabinoids. MAGL inhibitors may accordingly act as cannabinoid-potentiating and anti-inflammatory agents. Although MAGL dysfunction has been implicated in neuropsychiatric disorders, it has never been visualized in vivo in human brain. The primary objective of the current study was to visualize MAGL in the human brain using the novel PET ligand ¹⁸F-T-401.

METHODS

Seven healthy males underwent 120-min dynamic ¹⁸F-T-401-PET scans with arterial blood sampling. Six subjects also underwent a second PET scan with ¹⁸F-T-401 within 2 weeks of the first scan. For quantification of MAGL in the human brain, kinetic analyses using one- and two-tissue compartment models (1TCM and 2TCM, respectively), along with multilinear analysis (MA1) and Logan graphical analysis, were performed. Time-stability and test-retest reproducibility of ¹⁸F-T-401-PET were also evaluated.

RESULTS

¹⁸F-T-401 showed rapid uptake and gradual washout from the brain. Logan graphical analysis showed linearity in all subjects, indicating reversible radioligand kinetics. Using a metabolite-corrected arterial input function, MA1 estimated regional total distribution volume (V_T) values by best identifiability. V_T values were highest in the cerebral cortex, moderate in the thalamus and putamen, and lowest in white matter and the brainstem, which was in agreement with regional MAGL expression in the human brain. Time-stability analysis showed that MA1 estimated V_T values with a minimal bias even using truncated 60-min scan data. Test-retest reliability was also excellent with the use of MA1.

CONCLUSIONS

Here, we provide the first demonstration of in vivo visualization of MAGL in the human brain. ¹⁸F-T-401 showed excellent test-retest reliability, reversible kinetics, and stable estimation of V_T values consistent with known regional MAGL expressions. PET with ¹⁸F-T-401-PET is promising tool for measurement of central MAGL.

Integration of human whole-brain transcriptome and neuroimaging data: Practical considerations of current available methods

The Allen Human Brain Atlas (AHBA) is the first example of human brain transcriptomic mappings and detailed anatomical annotations which, for the first time, has allowed the integration of human brain transcriptomics with neuroimaging. This has been made possible because the AHBA offered an original dataset that contains mRNA expression measures for >20,000 genes covering the whole brain and, critically, in a standard stereotaxic space. In recent years many different methods have been used to integrate this data set with brain imaging data, although this endeavour has lacked harmony in terms of the workflow of data processing and subsequent analyses. In this work we discuss five main issues that experience has highlighted as in need of thorough consideration when integrating the AHBA with neuroimaging. These concerns are corroborated by comparing the performance of three different publicly available methods in correlating the same measures of serotonin receptors density with the correspondent AHBA mRNA maps. In this representative case, we were able to show how these methods can lead to discrepant results, suggesting that processing options are not neutral. We believe that the field should take into serious consideration these issues as they could undermine reproducibility and, in the end, the intrinsic value of the AHBA. We also advise on possible strategies to overcome these discrepancies. Finally, we encourage authors towards practices that will improve reproducibility such as transparency in reporting, algorithm and data sharing, collaboration.

GABA-A receptor differences in schizophrenia: a positron emission tomography study using [11C]Ro154513

A loss of GABA signaling is a prevailing hypothesis for the pathogenesis of schizophrenia. Preclinical studies indicate that blockade of the α5 subtype of the GABA receptor (α5-GABA_ARs) leads to behavioral phenotypes associated with schizophrenia, and postmortem evidence indicates lower hippocampal α5-GABA_ARs protein and mRNA levels in schizophrenia. However, it is unclear if α5-GABA_ARs are altered in vivo or related to symptoms. We investigated α5-GABA_ARs availability in antipsychotic-free schizophrenia patients and antipsychotic-medicated schizophrenia patients using [¹¹C]Ro15-4513 PET imaging in a cross-sectional, case-control study design. Thirty-one schizophrenia patients (n = 10 antipsychotic free) and twenty-nine matched healthy controls underwent a [¹¹C]Ro15-4513 PET scan and MRI. The α5 subtype GABA-A receptor availability was indexed using [¹¹C]Ro15-4513 PET imaging. Dynamic PET data were analyzed using the two-tissue compartment model with an arterial plasma input function and total volume of distribution (V_T) as the outcome measure. Symptom severity was assessed using the PANSS scale. There was significantly lower [11C]Ro15-4513 V_T in the hippocampus of antipsychotic-free patients, but not in medicated patients (p = 0.64), relative to healthy controls (p < 0.05; effect size = 1.4). There was also a significant positive correlation between [¹¹C]Ro15-4513 V_T and total PANSS score in antipsychotic-free patients (r = 0.72; p = 0.044). The results suggest that antipsychotic-free patients with schizophrenia have lower α5-GABAARs levels in the hippocampus, consistent with the hypothesis that GABA hypofunction underlies the pathophysiology of the disorder.

Association of dopamine D2/3 receptor binding potential measured using PET and [11C]-(+)-PHNO with post-mortem DRD2/3 gene expression in the human brain

Open access post-mortem transcriptome atlases such as the Allen Human Brain Atlas (AHBA) can inform us about mRNA expression of numerous proteins of interest across the whole brain, while in vivo protein binding in the human brain can be quantified by means of neuroreceptor positron emission tomography (PET). By combining both modalities, the association between regional gene expression and receptor distribution in the living brain can be approximated. Here, we compare the characteristics of D2 and D3 dopamine receptor distribution by applying the dopamine D2/3 receptor agonist radioligand [11C]-(+)-PHNO and human gene expression data. Since [11C]-(+)-PHNO has a higher affinity for D3 compared to D2 receptors, we hypothesized that there is a stronger relationship between D2/3 non-displaceable binding potentials (BPND) and D3 mRNA expression. To investigate the relationship between D2/3 BPND and mRNA expression of DRD2 and DRD3 we performed [11C]-(+)-PHNO PET scans in 27 healthy subjects (12 females) and extracted gene expression data from the AHBA. We also calculated D2/D3 mRNA expression ratios to imitate the mixed D2/3 signal of [11C]-(+)-PHNO. In accordance with our a priori hypothesis, a strong correlation between [11C]-(+)-PHNO and DRD3 expression was found. However, there was no significant correlation with DRD2 expression. Calculated D2/D3 mRNA expression ratios also showed a positive correlation with [11C]-(+)-PHNO binding, reflecting the mixed D2/3 signal of the radioligand. Our study supports the usefulness of combining gene expression data from open access brain atlases with in vivo imaging data in order to gain more detailed knowledge on neurotransmitter signaling.

Human Positron Emission Tomography Neuroimaging

Neuroimaging with positron emission tomography (PET) is the most powerful tool for understanding pharmacology, neurochemistry, and pathology in the living human brain. This technology combines high-resolution scanners to measure radioactivity throughout the human body with specific, targeted radioactive molecules, which allow measurements of a myriad of biological processes in vivo. While PET brain imaging has been active for almost 40 years, the pace of development for neuroimaging tools, known as radiotracers, and for quantitative analytical techniques has increased dramatically over the past decade. Accordingly, the fundamental questions that can be addressed with PET have expanded in basic neurobiology, psychiatry, neurology, and related therapeutic development. In this review, we introduce the field of human PET neuroimaging, some of its conceptual underpinnings, and motivating questions. We highlight some of the more recent advances in radiotracer development, quantitative modeling, and applications of PET to the study of the human brain.

A practical guide to linking brain-wide gene expression and neuroimaging data

The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl-¹¹C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level.

Comparison of two PET radioligands, [11C]FPEB and [11C]SP203, for quantification of metabotropic glutamate receptor 5 in human brain

Of the two ¹⁸F-labeled PET ligands currently available to image metabotropic glutamate receptor 5 (mGluR5), [¹⁸F]FPEB is reportedly superior because [¹⁸F]SP203 undergoes glutathionlyation, generating [¹⁸F]-fluoride ion that accumulates in brain and skull. To allow multiple PET studies on the same day with lower radiation exposure, we prepared [¹¹C]FPEB and [¹¹C]SP203 from [¹¹C]hydrogen cyanide and compared their abilities to accurately quantify mGluR5 in human brain, especially as regards radiometabolite accumulation. Genomic plot was used to estimate the ratio of specific-to-nondisplaceable uptake ( BP_ND) without using a receptor blocking drug. Both tracers quantified mGluR5; however [¹¹C]SP203, like [¹⁸F]SP203, had radiometabolite accumulation in brain, as evidenced by increased distribution volume ( V_T) over the scan period. Absolute V_T values were ∼30% lower for ¹¹C-labeled compared with ¹⁸F-labeled radioligands, likely caused by the lower specific activities (and high receptor occupancies) of the ¹¹C radioligands. The genomic plot indicated ∼60% specific binding in cerebellum, which makes it inappropriate as a reference region. Whole-body scans performed in healthy subjects demonstrated a low radiation burden typical for ¹¹C-ligands. Thus, the evidence suggests that [¹¹C]FPEB is superior to [¹¹C]SP203. If prepared in higher specific activity, [¹¹C]FPEB would presumably be as effective as [¹⁸F]FPEB for quantifying mGluR5 in human brain.

Test-retest reproducibility of quantitative binding measures of [11C]Ro15-4513, a PET ligand for GABAA receptors containing alpha5 subunits

INTRODUCTION

Alteration of γ-aminobutyric acid "A" (GABAA) receptor-mediated neurotransmission has been associated with various neurological and psychiatric disorders. [11C]Ro15-4513 is a PET ligand with high affinity for α5-subunit-containing GABAA receptors, which are highly expressed in limbic regions of the human brain (Sur et al., 1998). We quantified the test-retest reproducibility of measures of [11C]Ro15-4513 binding derived from six different quantification methods (12 variants).

METHODS

Five healthy males (median age 40 years, range 38-49 years) had a 90-min PET scan on two occasions (median interval 12 days, range 11-30 days), after injection of a median dose of 441 MegaBequerels of [11C]Ro15-4513. Metabolite-corrected arterial plasma input functions (parent plasma input functions, ppIFs) were generated for all scans. We quantified regional binding using six methods (12 variants), some of which were region-based (applied to the average time-activity curve within a region) and others were voxel-based: 1) Models requiring arterial ppIFs - regional reversible compartmental models with one and two tissue compartments (2kbv and 4kbv); 2) Regional and voxelwise Logan's graphical analyses (Logan et al., 1990), which required arterial ppIFs; 3) Model-free regional and voxelwise (exponential) spectral analyses (SA; (Cunningham and Jones, 1993)), which also required arterial ppIFs; 4) methods not requiring arterial ppIFs - voxelwise standardised uptake values (Kenney et al., 1941), and regional and voxelwise simplified reference tissue models (SRTM/SRTM2) using brainstem or alternatively cerebellum as pseudo-reference regions (Lammertsma and Hume, 1996; Gunn et al., 1997). To compare the variants, we sampled the mean values of the outcome parameters within six bilateral, non-reference grey matter regions-of-interest. Reliability was quantified in terms of median absolute percentage test-retest differences (MA-TDs; preferentially low) and between-subject coefficient of variation (BS-CV, preferentially high), both compounded by the intraclass correlation coefficient (ICC). These measures were compared between variants, with particular interest in the hippocampus.

RESULTS

Two of the six methods (5/12 variants) yielded reproducible data (i.e. MA-TD <10%): regional SRTMs and voxelwise SRTM2s, both using either the brainstem or the cerebellum; and voxelwise SA. However, the SRTMs using the brainstem yielded a lower median BS-CV (7% for regional, 7% voxelwise) than the other variants (8-11%), resulting in lower ICCs. The median ICCs across six regions were 0.89 (interquartile range 0.75-0.90) for voxelwise SA, 0.71 (0.64-0.84) for regional SRTM-cerebellum and 0.83 (0.70-0.86) for voxelwise SRTM-cerebellum. The ICCs for the hippocampus were 0.89 for voxelwise SA, 0.95 for regional SRTM-cerebellum and 0.93 for voxelwise SRTM-cerebellum.

CONCLUSION

Quantification of [11C]Ro15-4513 binding shows very good to excellent reproducibility with SRTM and with voxelwise SA which, however, requires an arterial ppIF. Quantification in the α5 subunit-rich hippocampus is particularly reliable. The very low expression of the α5 in the cerebellum (Fritschy and Mohler, 1995; Veronese et al., 2016) and the substantial α1 subunit density in this region may hamper the application of reference tissue methods.

Brain transcriptome atlases: a computational perspective

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

BACKGROUND AND AIM

Estimation of a PET tracer's non-displaceable distribution volume (VND) is required for quantification of specific binding to its target of interest. VND is generally assumed to be comparable brain-wide and is determined either from a reference region devoid of the target, often not available for many tracers and targets, or by imaging each subject before and after blocking the target with another molecule that has high affinity for the target, which is cumbersome and involves additional radiation exposure. Here we propose, and validate for the tracers [11C]DASB and [11C]CUMI-101, a new data-driven hybrid deconvolution approach (HYDECA) that determines VND at the individual level without requiring either a reference region or a blocking study.

METHODS

HYDECA requires the tracer metabolite-corrected concentration curve in blood plasma and uses a singular value decomposition to estimate the impulse response function across several brain regions from measured time activity curves. HYDECA decomposes each region's impulse response function into the sum of a parametric non-displaceable component, which is a function of VND, assumed common across regions, and a nonparametric specific component. These two components differentially contribute to each impulse response function. Different regions show different contributions of the two components, and HYDECA examines data across regions to find a suitable common VND. HYDECA implementation requires determination of two tuning parameters, and we propose two strategies for objectively selecting these parameters for a given tracer: using data from blocking studies, and realistic simulations of the tracer. Using available test-retest data, we compare HYDECA estimates of VND and binding potentials to those obtained based on VND estimated using a purported reference region.

RESULTS

For [11C]DASB and [11C]CUMI-101, we find that regardless of the strategy used to optimize the tuning parameters, HYDECA provides considerably less biased estimates of VND than those obtained, as is commonly done, using a non-ideal reference region. HYDECA test-retest reproducibility is comparable to that obtained using a VND determined from a non-ideal reference region, when considering the binding potentials BPP and BPND.

CONCLUSIONS

HYDECA can provide subject-specific estimates of VND without requiring a blocking study for tracers and targets for which a valid reference region does not exist.