Publications
700 results found
Selvaggi P, Osugo M, Dipasquale O, et al., 2023, Effects of Sustained D2 Receptors Blockade on Brain Structure and Function in Healthy Volunteers, Publisher: ELSEVIER SCIENCE INC, Pages: S95-S96, ISSN: 0006-3223
Merritt K, McCutcheon RA, Aleman A, et al., 2023, Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis., Mol Psychiatry, Vol: 28, Pages: 2039-2048
Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = -0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = -0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data
Pillinger T, McCutcheon RA, Howes OD, 2023, Variability of glucose, insulin, and lipid disturbances in first-episode psychosis: a meta-analysis, PSYCHOLOGICAL MEDICINE, Vol: 53, Pages: 3150-3156, ISSN: 0033-2917
Howes OD, Onwordi EC, 2023, The synaptic hypothesis of schizophrenia version III: a master mechanism, MOLECULAR PSYCHIATRY, ISSN: 1359-4184
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- Citations: 1
Sathyanarayanan A, Mueller TT, Ali Moni M, et al., 2023, Multi-omics data integration methods and their applications in psychiatric disorders., Eur Neuropsychopharmacol, Vol: 69, Pages: 26-46
To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.
Oliver D, Davies C, Zelaya F, et al., 2023, Parsing neurobiological heterogeneity of the clinical high-risk state for psychosis: A pseudo-continuous arterial spin labelling study, FRONTIERS IN PSYCHIATRY, Vol: 14, ISSN: 1664-0640
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- Citations: 1
Pillinger T, Osimo EF, de Marvao A, et al., 2023, Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study, The Lancet Psychiatry, Vol: 10, Pages: 98-107, ISSN: 2215-0366
BACKGROUND: Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. METHODS: For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. FINDINGS: Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk
Howes OD, Baxter L, 2023, The drug treatment deadlock in psychiatry and the route forward, WORLD PSYCHIATRY, Vol: 22, Pages: 2-3, ISSN: 1723-8617
Egerton A, Griffiths K, Casetta C, et al., 2023, Anterior cingulate glutamate metabolites as a predictor of antipsychotic response in first episode psychosis: data from the STRATA collaboration., Neuropsychopharmacology, Vol: 48, Pages: 567-575
Elevated brain glutamate has been implicated in non-response to antipsychotic medication in schizophrenia. Biomarkers that can accurately predict antipsychotic non-response from the first episode of psychosis (FEP) could allow stratification of patients; for example, patients predicted not to respond to standard antipsychotics could be fast-tracked to clozapine. Using proton magnetic resonance spectroscopy (1H-MRS), we examined the ability of glutamate and Glx (glutamate plus glutamine) in the anterior cingulate cortex (ACC) and caudate to predict response to antipsychotic treatment. A total of 89 minimally medicated patients with FEP not meeting symptomatic criteria for remission were recruited across two study sites. 1H-MRS and clinical data were acquired at baseline, 2 and 6 weeks. Response was defined as >20% reduction in Positive and Negative Syndrome Scale (PANSS) Total score from baseline to 6 weeks. In the ACC, baseline glutamate and Glx were higher in Non-Responders and significantly predicted response (P < 0.02; n = 42). Overall accuracy was greatest for ACC Glx (69%) and increased to 75% when symptom severity at baseline was included in the model. Glutamate metabolites in the caudate were not associated with response, and there was no significant change in glutamate metabolites over time in either region. These results add to the evidence linking elevations in ACC glutamate metabolites to a poor antipsychotic response. They indicate that glutamate may have utility in predicting response during early treatment of first episode psychosis. Improvements in accuracy may be made by combining glutamate measures with other response biomarkers.
Osimo E, Perry BI, Mallikarjun P, et al., 2023, Predicting treatment-resistance from first-episode psychosis using routinely collected clinical information, Nature Mental Health, Vol: 1, Pages: 25-35, ISSN: 2731-6076
Around a quarter of people who experience a first episode of psychosis (FEP) will develop treatment-resistant schizophrenia (TRS), but there are currently no established clinically useful methods to predict this from baseline. We aimed to explore the predictive potential for clozapine use as a proxy for TRS of routinely collected, objective biomedical predictors at FEP onset, and to externally validate the model in a separate clinical sample of people with FEP. We developed and externally validated a forced-entry logistic regression risk prediction Model fOr cloZApine tReaTment, or MOZART, to predict up to 8-year risk of clozapine use from FEP using routinely recorded information including age, sex, ethnicity, triglycerides, alkaline phosphatase levels, and lymphocyte counts. We also produced a least-absolute shrinkage and selection operator (LASSO) based model, additionally including neutrophil count, smoking status, body mass index, and random glucose levels. The models were developed using data from two UK psychosis early intervention services (EIS) and externally validated in another UK EIS. Model performance was assessed via discrimination and calibration. We developed the models in 785 patients, and validated externally in 1,110 patients. Both models predicted clozapine use well at internal validation (MOZART: C 0.70; 95%CI 0.63,0.76; LASSO: 0.69; 95%CI 0.63,0.77). At external validation, discrimination performance reduced (MOZART: 0.63; 0.58,0.69; LASSO: 0.64; 0.58,0.69) but recovered after re-estimation of the lymphocyte predictor (C: 0.67; 0.62,0.73). Calibration plots showed good agreement between observed and predicted risk in the forced-entry model. We also present a decision-curve analysis and an online data visualisation tool. The use of routinely collected clinical information including blood-based biomarkers taken at FEP onset can help to predict the individual risk of clozapine use, and should be considered equally alongside other potentially useful
Kaar SJ, Nottage JF, Angelescu I, et al., 2023, Gamma Oscillations and Potassium Channel Modulation in Schizophrenia: Targeting GABAergic Dysfunction, CLINICAL EEG AND NEUROSCIENCE, ISSN: 1550-0594
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- Citations: 2
Nordio G, Easmin R, Giacomel A, et al., 2023, Automated quantification of FDOPA PET using XNAT
In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. We found good reproducibility of the data analysis by the automated pipeline (for the controls ICC=0.71, for the psychotic patients ICC=0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F=10.7, p<0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid recourse for standardized and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.
Severino M, Selvaggi P, Osugo M, et al., 2023, Modelling cerebral blood flow and neuroreceptor occupancy in dopamine blocking studies
As a result of neuro-vascular coupling, the functional effects of antipsychotics in human brain have been investigated using hemodynamic markers such as Cerebral Blood Flow (CBF) and Cerebral Blood Volume (CBV). However, the relationship between observed hemodynamic effects and the pharmacological action of antipsychotics has not been fully established. Here we wanted to investigate the relationship between the administered repeated dose of amisulpride, an atypical antipsychotic, and the changes in cerebral blood flow in the striatum. To investigate this relationship, we linked the plasma concentration to PET receptor occupancy and ultimately to the Arterial Spin Labelling's (ASL) CBF data from a placebo-controlled study in healthy volunteers, who received a repeated dose of amisulpride. To link the data, we developed a PK/PD framework which, starting from the dose administered, was able to predict the plasma drug concentration after a repeated dose, to predict the receptor occupancy (RO) in the targeted regions of the brain, and finally to link it with changes in cerebral blood flow in the striatum. The results showed a statistically significant monotonically increasing relationship between changes in relative to global CBF and receptor occupancies in the putamen (p-value < 0.001) and caudate regions of the brain (p-value < 0.01). These findings suggest that antipsychotics increase striatal perfusion, with a mechanism possibly mediated by D2 receptors and represent further evidence supporting the hypothesized PK/PD model of antipsychotic effects on CBF measures founded on macaques by 'Sander et al, 2013'.
Giacomel A, Martins D, Nordio G, et al., 2023, Assessing Multisite PET Neuroimaging Harmonisation for Normative Modelling
Although normative modelling has been recently widely adopted by the neuroimaging community to estimate deviation of cohorts or single subjects, from a reference population's trajectory, it has never been applied on molecular neuroimaging datasets. This is because the typical sample size of molecular imaging datasets of single studies is not adequate for a reliable estimation of population models. Here, we pooled scans from different datasets and compared the performance of common neuroimaging harmonisation techniques when used on molecular neuroimaging data, by measuring the effect of the harmonisation on the deviation scores of the normative model. As harmonisation methods we employed a 3D Gaussian filter and a Bayesian scale and shift estimation method (Combat). By statistically testing the parameters of the deviation-score distribution and inspecting the explained variance map of the model, we selected Combat, trading-off between the two parameters' performance, as the most suitable way to harmonise multi-site/multi-scanner molecular neuroimaging datasets.
Howes OD, Cummings C, Chapman GE, et al., 2023, Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes, NEUROPSYCHOPHARMACOLOGY, Vol: 48, Pages: 151-167, ISSN: 0893-133X
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- Citations: 11
Halff EF, Rutigliano G, Garcia-Hidalgo A, et al., 2023, Trace amine-associated receptor 1 (TAAR1) agonism as a new treatment strategy for schizophrenia and related disorders, TRENDS IN NEUROSCIENCES, Vol: 46, Pages: 60-74, ISSN: 0166-2236
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- Citations: 7
Petty A, Howes O, Eyles D, 2023, Animal Models of Relevance to the Schizophrenia, BIOLOGICAL PSYCHIATRY: GLOBAL OPEN SCIENCE, Vol: 3, Pages: 22-32, ISSN: 2667-1743
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- Citations: 4
Shatalina E, Ashok AH, Wall MB, et al., 2023, Reward processing in schizophrenia and its relation to Mu opioid receptor availability and negative symptoms: A [11C]-carfentanil PET and fMRI study, NEUROIMAGE-CLINICAL, Vol: 39, ISSN: 2213-1582
Onwordi E, Whitehurst T, Shatalina E, et al., 2022, The Relationship Between Synaptic and Cognitive Markers in Schizophrenia: A Positron Emission Tomography Study Using [11 C]UCB-J, 61st Annual Meeting of the American-College-of-Neuropsychopharmacology (ACNP), Publisher: SPRINGERNATURE, Pages: 341-341, ISSN: 0893-133X
Howes OD, Barnes TRE, Lennox BR, et al., 2022, Time to re-evaluate the risks and benefits of valproate and a call for action, BRITISH JOURNAL OF PSYCHIATRY, Vol: 221, Pages: 711-713, ISSN: 0007-1250
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- Citations: 1
Butler E, Pillinger T, Brown K, et al., 2022, Real-world clinical and cost-effectiveness of community clozapine initiation: mirror cohort study, BRITISH JOURNAL OF PSYCHIATRY, Vol: 221, Pages: 740-747, ISSN: 0007-1250
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- Citations: 4
D'Souza DC, DiForti M, Ganesh S, et al., 2022, Consensus paper of the WFSBP task force on cannabis, cannabinoids and psychosis, WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY, Vol: 23, Pages: 719-742, ISSN: 1562-2975
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- Citations: 15
Chesters RA, Pepper F, Morgan C, et al., 2022, Brain volume in chronic ketamine users - relationship to sub-threshold psychotic symptoms and relevance to schizophrenia, PSYCHOPHARMACOLOGY, Vol: 239, Pages: 3421-3429, ISSN: 0033-3158
Marques TR, Natesan S, Rabiner EA, et al., 2022, Adenosine A<sub>2A</sub> receptor in schizophrenia: an in vivo brain PET imaging study, PSYCHOPHARMACOLOGY, Vol: 239, Pages: 3439-3445, ISSN: 0033-3158
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- Citations: 2
Millgate E, Griffiths K, Egerton A, et al., 2022, Cognitive function and treatment response trajectories in first-episode schizophrenia: evidence from a prospective cohort study, BMJ OPEN, Vol: 12, ISSN: 2044-6055
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- Citations: 1
Nohr AK, Forsingdal A, Moltke I, et al., 2022, Polygenic heterogeneity in antidepressant treatment and placebo response, TRANSLATIONAL PSYCHIATRY, Vol: 12, ISSN: 2158-3188
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- Citations: 1
Halff EF, Natesan S, Bonsall DR, et al., 2022, Evaluation of Intraperitoneal [<SUP>18</SUP>F]-FDOPA Administration for Micro-PET Imaging in Mice and Assessment of the Effect of Subchronic Ketamine Dosing on Dopamine Synthesis Capacity, MOLECULAR IMAGING, Vol: 2022
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- Citations: 1
Kane JM, Kinon BJ, Forray C, et al., 2022, Efficacy and safety of Lu AF35700 in treatment-resistant schizophrenia: A randomized, active-controlled trial with open-label extension, SCHIZOPHRENIA RESEARCH, Vol: 248, Pages: 271-278, ISSN: 0920-9964
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- Citations: 2
Kaar SJ, Angelescu I, Nour MM, et al., 2022, The effects of AUT00206, a novel Kv3.1/3.2 potassium channel modulator, on task-based reward system activation: a test of mechanism in schizophrenia, PSYCHOPHARMACOLOGY, Vol: 239, Pages: 3313-3323, ISSN: 0033-3158
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- Citations: 1
Chen KC, Yang YK, Howes OD, et al., 2022, Striatal dopamine D<sub>2/3</sub> receptors in medication-naive schizophrenia: an [<SUP>123</SUP>I] IBZM SPECT study, PSYCHOLOGICAL MEDICINE, Vol: 52, Pages: 3251-3259, ISSN: 0033-2917
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- Citations: 23
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