Search

Background: Cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC) are the two major constituents of cannabis with contrasting mechanisms of action. THC is the major psychoactive, addiction-promoting, and psychotomimetic compound, while CBD may have opposite effects. The brain effects of these drugs alone and in combination are poorly understood. In particular, the striatum is implicated in the pathophysiology of several psychiatric disorders, but it is unclear how THC and CBD influence striato-cortical connectivity. Aims: To examine effects of THC, CBD, and THC + CBD on functional connectivity of striatal sub-divisions (associative, limbic and sensorimotor). Method: Resting-state functional Magnetic Resonance Imaging (fMRI) was used across two within-subjects, placebo-controlled, double-blind studies, with a unified analysis approach. Results: Study 1 ( N = 17; inhaled cannabis containing 8 mg THC, 8 mg THC + 10 mg CBD or placebo) showed strong disruptive effects of both THC and THC + CBD on connectivity in the associative and sensorimotor networks, but a specific effect of THC in the limbic striatum network which was not present in the THC + CBD condition. In Study 2 ( N = 23, oral 600 mg CBD, placebo), CBD increased connectivity in the associative network, but produced only relatively minor disruptions in the limbic and sensorimotor networks. Outcomes: THC strongly disrupts striato-cortical networks, but this effect is mitigated by co-administration of CBD in the limbic striatum network. Oral CBD administered has a more complex effect profile of relative increases and decreases in connectivity. The insula emerges as a key region affected by cannabinoid-induced changes in functional connectivity, with potential implications for understanding cannabis-related disorders, and the development of cannabinoid therapeutics.

Rationale There is growing interest in the therapeutic potential of cannabidiol (CBD) across a range of psychiatric disorders. CBD has been found to reduce anxiety during experimentally induced stress in anxious individuals and healthy controls. However, the mechanisms underlying the putative anxiolytic effects of CBD are unknown. Objectives We sought to investigate the behavioural and neural effects of a single dose of CBD vs. placebo on a range of emotion-related measures to test cognitive-mechanistic models of its effects on anxiety. Methods We conducted a randomised, double-blind, placebo-controlled, crossover, acute oral challenge of 600 mg of CBD in 24 healthy participants on emotional processing, with neuroimaging (viewing emotional faces during functional magnetic resonance imaging) and cognitive (emotional appraisal) measures as well as subjective response to experimentally induced anxiety. Results CBD did not produce effects on brain responses to emotional faces and cognitive measures of emotional processing, or modulate experimentally induced anxiety, relative to placebo. Conclusions Given the rising popularity of CBD for its putative medical benefits, these findings question whether further research is warranted to investigate the clinical potential of CBD for the treatment of anxiety disorders.

Glutamatergic excitotoxicity is hypothesised to underlie synaptic loss in schizophrenia pathogenesis, but it is unknown whether synaptic markers are related to glutamatergic function in vivo. Additionally, it has been proposed that N-acetyl aspartate (NAA) levels reflect neuronal integrity. Here, we investigated whether synaptic vesicle glycoprotein 2 A (SV2A) levels are related to glutamatergic markers and NAA in healthy volunteers (HV) and schizophrenia patients (SCZ). Forty volunteers (SCZ n = 18, HV n = 22) underwent [11C]UCB-J positron emission tomography and proton magnetic resonance spectroscopy (1H-MRS) imaging in the left hippocampus and anterior cingulate cortex (ACC) to index [11C]UCB-J distribution volume ratio (DVR), and creatine-scaled glutamate (Glu/Cr), glutamate and glutamine (Glx/Cr) and NAA (NAA/Cr). In healthy volunteers, but not patients, [11C]UCB-J DVR was significantly positively correlated with Glu/Cr, in both the hippocampus and ACC. Furthermore, in healthy volunteers, but not patients, [11C]UCB-J DVR was significantly positively correlated with Glx/Cr, in both the hippocampus and ACC. There were no significant relationships between [11C]UCB-J DVR and NAA/Cr in the hippocampus or ACC in healthy volunteers or patients. Therefore, an appreciable proportion of the brain 1H-MRS glutamatergic signal is related to synaptic density in healthy volunteers. This relationship is not seen in schizophrenia, which, taken with lower synaptic marker levels, is consistent with lower levels of glutamatergic terminals and/or a lower proportion of glutamatergic relative to GABAergic terminals in the ACC in schizophrenia.

Purpose: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. Methods: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). Results: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. Conclusion: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction.

Background:Cannabidiol (CBD) is being investigated as a potential treatment for several medical indications, many of which are characterised by altered memory processing. However, the mechanisms underlying these effects are unclear.Aims:Our primary aim was to investigate how CBD influences cerebral blood flow (CBF) in regions involved in memory processing. Our secondary aim was to determine if the effects of CBD on CBF were associated with differences in working and episodic memory task performance.Methods:We used a randomised, crossover, double-blind design in which 15 healthy participants were administered 600 mg oral CBD or placebo on separate days. We measured regional CBF at rest using arterial spin labelling 3 h after drug ingestion. We assessed working memory with the digit span (forward, backward) and n-back (0-back, 1-back, 2-back) tasks, and we used a prose recall task (immediate and delayed) to assess episodic memory.Results:CBD increased CBF in the hippocampus (mean (95% confidence intervals) = 15.00 (5.78–24.21) mL/100 g/min, t14= 3.489, Cohen’s d = 0.75, p = 0.004). There were no differences in memory task performance, but there was a significant correlation whereby greater CBD-induced increases in orbitofrontal CBF were associated with reduced reaction time on the 2-back working memory task ( r= −0.73, p = 0.005).Conclusions:These findings suggest that CBD increases CBF to key regions involved in memory processing, particularly the hippocampus. These results identify potential mechanisms of CBD for a range of conditions associated with altered memory processing, including Alzheimer’s disease, schizophrenia, post-traumatic stress disorder and cannabis-use disorders.

Background: Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population. Objectives: The goal of this study was to compare lifetime outcomes and cardiovascular phenotypes according to the presence of rare variants in sarcomere-encoding genes among middle-aged adults. Methods: This study analyzed whole exome sequencing and cardiac magnetic resonance imaging in UK Biobank participants stratified according to sarcomere-encoding variant status. Results: The prevalence of rare variants (allele frequency

There is growing interest in the therapeutic potential of cannabidiol (CBD) across a range of psychiatric disorders. CBD has been found to reduce anxiety during experimentally induced stress in anxious individuals and healthy controls. However, the mechanisms underlying the putative anxiolytic effects of CBD are unknown.We sought to investigate the behavioural and neural effects of a single dose of CBD vs. placebo on a range of emotion-related measures to test cognitive-mechanistic models of its effects on anxiety.We conducted a randomised, double-blind, placebo-controlled, crossover, acute oral challenge of 600 mg of CBD in 24 healthy participants on emotional processing, with neuroimaging (viewing emotional faces during functional magnetic resonance imaging) and cognitive (emotional appraisal) measures as well as subjective response to experimentally induced anxiety.CBD did not produce effects on brain responses to emotional faces and cognitive measures of emotional processing, or modulate experimentally induced anxiety, relative to placebo.Given the rising popularity of CBD for its putative medical benefits, these findings question whether further research is warranted to investigate the clinical potential of CBD for the treatment of anxiety disorders.

Cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC) are two major constituents of cannabis with contrasting mechanisms of action. THC is the major psychoactive, addiction-promoting, and psychotomimetic compound, while CBD may have somewhat opposite effects. The brain effects of these drugs alone and in combination are poorly understood. In particular the striatum is implicated in the pathophysiology of several psychiatric disorders, but it is unclear how THC and CBD influence striato-cortical connectivity. Across two placebo-controlled, double-blind studies, we examine the effects of THC, CBD, and THC+CBD on the functional connectivity of striatal sub-divisions (associative, limbic, and sensorimotor) using resting-state functional Magnetic Resonance Imaging (fMRI) and seed-based functional connectivity analyses. Study 1 (N=17; inhaled 8mg THC, 8mg THC+10mg CBD, placebo) showed strong disruptive effects of both THC and THC+CBD conditions on connectivity in the associative and sensorimotor networks, but a specific effect of THC in the limbic striatum, which was alleviated in the THC+CBD condition such that it did not differ from placebo. In Study 2 (N=23, oral 600mg CBD, placebo) CBD increased connectivity in the associative network, but relatively minor decreases/disruptions were found in the limbic and sensorimotor. In conclusion, THC strongly disrupts striato-cortical networks, and this effect is selectively mitigated in the limbic striatum when co-administered with CBD. When administered alone, 600mg oral CBD has a more complex effect profile of relative increases and decreases in connectivity. The insula emerges as a key region affected by cannabinoid-induced changes in functional connectivity, with potential implications for understanding cannabis related disorders, and the development of cannabinoid therapeutics.

BackgroundLeft ventricular non-compaction (LVNC) is a condition characterised by trabeculations in the myocardial wall and is the subject of considerable conjecture as to whether it represents a distinct pathology or a secondary phenotype associated with other cardiac diseases, particularly cardiomyopathies. We sought to investigate the genetic architecture of LVNC by identifying genes and variant classes robustly associated with disease and comparing these to other genetically characterised cardiomyopathies.MethodsWe performed rare variant association analysis using six different LVNC cohorts comprising 840 cases together with 125,748 gnomAD population controls and compared results to similar analyses with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) cases.ResultsWe observed substantial overlap in genes and variant classes enriched in LVNC and DCM/HCM, indicating that in many cases LVNC belongs to a spectrum of more established cardiomyopathies, with non-compaction representing a phenotypic variation in patients with DCM- or HCM-causing variants. In contrast, five variant classes were uniquely enriched in LVNC cases, of which truncating variants inMYH7, ACTN2andPRDM16may represent a distinct LVNC aetiology.MYH7truncating variants are generally considered as non-pathogenic but were detected in 2% of LVNC cases compared to 0.1% of controls, including a cluster of variants around a single splice region. Individuals withMYH7truncating variants identified in the UK Biobank and cohorts of healthy volunteers also displayed significantly greater non-compaction compared to matched controls, with 50% meeting the diagnostic criteria for LVNC. Additionally, structural variants (exon deletions) inRYR2and missense variants in the transmembrane region ofHCN4were enriched in LVNC cases, confirming prior reports regarding the association of these variant classes with combined LVNC and arrhythmia phenotypes.ConclusionsWe demonstrated that genetic association analysis can clarify the relationship between LVNC and established cardiomyopathies, highlighted substantial overlap with DCM/HCM but also identified variant classes associated with distinct LVNC and with joint LVNC/arrhythmia phenotypes. These results underline the complex genetic landscape of LVNC and inform how genetic testing in LVNC cases should be pursued and interpreted.

BackgroundHeart disease is the leading cause of death in schizophrenia. However, there has been little research directly examining cardiac function in schizophrenia.AimsTo investigate cardiac structure and function in individuals with schizophrenia using cardiac magnetic resonance imaging (CMR) after excluding medical and metabolic comorbidity.MethodIn total, 80 participants underwent CMR to determine biventricular volumes and function and measures of blood pressure, physical activity and glycated haemoglobin levels. Individuals with schizophrenia (‘patients’) and controls were matched for age, gender, ethnicity and body surface area.ResultsPatients had significantly smaller indexed left ventricular (LV) end-diastolic volume (effect size d = −0.82, P = 0.001), LV end-systolic volume (d = −0.58, P = 0.02), LV stroke volume (d = −0.85, P = 0.001), right ventricular (RV) end-diastolic volume (d = −0.79, P = 0.002), RV end-systolic volume (d = −0.58, P = 0.02), and RV stroke volume (d = −0.87, P = 0.001) but unaltered ejection fractions relative to controls. LV concentricity (d = 0.73, P = 0.003) and septal thickness (d = 1.13, P < 0.001) were significantly larger in the patients. Mean concentricity in patients was above the reference range. The findings were largely unchanged after adjusting for smoking and/or exercise levels and were independent of medication dose and duration.ConclusionsIndividuals with schizophrenia show evidence of concentric cardiac remodelling compared with healthy controls of a similar age, gender, ethnicity, body surface area and blood pressure, and independent of smoking and activity levels. This could be contributing to the excess cardiovascular mortality observed in schizophrenia. Future studies should investigate the contribution of antipsychotic medication to these changes.

Background The relationship between structural pathology and electrophysiological substrate in cardiac amyloidosis is unclear. Differences between light‐chain ( AL ) and transthyretin ( ATTR ) cardiac amyloidosis may have prognostic implications. Methods and Results ECG imaging and cardiac magnetic resonance studies were conducted in 21 cardiac amyloidosis patients (11 AL and 10 ATTR ). Healthy volunteers were included as controls. With respect to ATTR , AL patients had lower amyloid volume (51.0/37.7 versus 73.7/16.4 mL, P =0.04), lower myocardial cell volume (42.6/19.1 versus 58.5/17.2 mL, P =0.021), and higher T1 (1172/64 versus 1109/80 ms, P =0.022) and T2 (53.4/2.9 versus 50.0/3.1 ms, P =0.003). ECG imaging revealed differences between cardiac amyloidosis and control patients in virtually all conduction‐repolarization parameters. With respect to ATTR , AL patients had lower epicardial signal amplitude (1.07/0.46 versus 1.83/1.26 mV, P =0.026), greater epicardial signal fractionation ( P =0.019), and slightly higher dispersion of repolarization (187.6/65 versus 158.3/40 ms, P =0.062). No significant difference between AL and ATTR patients was found using the standard 12‐lead ECG . T1 correlated with epicardial signal amplitude (cc=−0.78), and extracellular volume with epicardial signal fractionation (cc=0.48) and repolarization time (cc=0.43). Univariate models based on single features from both cardiac magnetic resonance and ECG imaging classified AL and ATTR patients with an accuracy of 70% to 80%. Conclusions In this exploratory study cardiac amyloidosis was associated with ventricular conduction and repolarization abnormalities, which were more pronounced in AL than in ATTR . Combined ECG imaging–cardiac magnetic resonance analysis supports the hypothesis that additional mechanisms beyond infiltration may contribute to myocardial damage in AL amyloidosis. Further studies are needed to assess the clinical impact of this approach.

Cardiovascular disease (CVD) is a major cause of excess mortality in schizophrenia. Preclinical evidence shows antipsychotics can cause myocardial fibrosis and myocardial inflammation in murine models, but it is not known if this is the case in patients. We therefore set out to determine if there is evidence of cardiac fibrosis and/or inflammation using cardiac MRI in medicated patients with schizophrenia compared with matched healthy controls. 31 participants (14 patients and 17 controls) underwent cardiac MRI assessing myocardial markers of fibrosis/inflammation, indexed by native myocardial T1 time, and cardiac structure (left ventricular (LV) mass) and function (left/right ventricular end-diastolic and end-systolic volumes, stroke volumes, and ejection fractions). Participants were physically fit, and matched for age, gender, smoking, blood pressure, BMI, HbA1c, ethnicity, and physical activity. Compared with controls, native myocardial T1 was significantly longer in patients with schizophrenia (effect size, d=0.89; p=0.02). Patients had significantly lower LV mass, and lower left/right ventricular end-diastolic and stroke volumes (effect sizes, d=0.86-1.08; all p-values 0.05). These results suggest an early diffuse fibro-inflammatory myocardial process in patients that is independent of established CVD-risk factors and could contribute to the excess cardiovascular mortality associated with schizophrenia. Future studies are required to determine if this is due to antipsychotic treatment or is intrinsic to schizophrenia.

In this work, we propose a deep learning approach for parallel magnetic resonance imaging (MRI) reconstruction, termed a variable splitting network (VS-Net), for an efficient, high-quality reconstruction of undersampled multi-coil MR data. We formulate the generalized parallel compressed sensing reconstruction as an energy minimization problem, for which a variable splitting optimization method is derived. Based on this formulation we propose a novel, end-to-end trainable deep neural network architecture by unrolling the resulting iterative process of such variable splitting scheme. VS-Net is evaluated on complex valued multi-coil knee images for 4-fold and 6-fold acceleration factors. We show that VS-Net outperforms state-of-the-art deep learning reconstruction algorithms, in terms of reconstruction accuracy and perceptual quality. Our code is publicly available at https://github.com/j-duan/VS-Net.

Introduction Hypertrophic cardiomyopathy (HCM) is characterised by great phenotypic diversity and broad spectrum of clinical courses. The genetic, environmental and phenotypic determinants of outcome remain poorly understood. We integrated machine-learning analysis of cardiovascular magnetic resonance (CMR) with computational modelling to define the effects of genetic variation on the heart in both HCM patients and heathy volunteers. Methods Healthy volunteers were recruited at Imperial College London (n=1367) and National Health Centre Singapore (n=754). Patients with HCM were enrolled at the Royal Brompton Hospital (n=622) and National Heart Centre Singapore (n=211). Participants underwent conventional CMR at 1.5 T. Using cardiac atlas and machine learning techniques, CMRs were segmented and co-registered providing statistical models of phenotypic variation. Subjects were sequenced with comprehensive gene panels and using stringent criteria identified as genotype positive (G+), negative (G-) or as carriers of variants of unknown significance (VUS). Results In healthy volunteers, sarcomeric G+variants were associated with increased septal and apical LV wall thickness. In HCM, sarcomeric thin filament G+displayed the mildest global hypertrophy. Sarcomeric thick filament G+variants were associated with asymmetric septal hypertrophy, when compared to G-, VUS and other G+. Conclusion We show that in a healthy population, rare variants in sarcomeric genes are penetrant and associated with increased wall thickness. This has potential clinical implications to the ~0.5% of the population that are carriers. In HCM, distinct patterns of hypertrophy were associated with specific genotypes. We demonstrate that machine-learning analysis of CMRs offers unparalleled insights into the earliest manifestations of cardiomyopathy and mutation-specific pathophysiology.