Publications by authors named "Ilaria Bonoldi"

We provide here the first bottom-up review of the lived experience of mental disorders in adolescents co-designed, co-conducted and co-written by experts by experience and academics. We screened first-person accounts within and outside the medical field, and discussed them in collaborative workshops involving numerous experts by experience - representing different genders, ethnic and cultural backgrounds, and continents - and their family members and carers. Subsequently, the material was enriched by phenomenologically informed perspectives and shared with all collaborators.

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This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community.

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We provide here the first bottom-up review of the lived experience of depression, co-written by experts by experience and academics. First-person accounts within and outside the medical field were screened and discussed in collaborative workshops involving numerous individuals with lived experience of depression, family members and carers, representing a global network of organizations. The material was enriched by phenomenologically informed perspectives and shared with all collaborators in a cloud-based system.

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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 and processing parameters. 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.

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Informal caregivers of individuals affected by psychotic disorder can play a key role in the recovery process. However, little research has been conducted on the lived experiences of carers and family members. We conducted a bottom-up (from lived experience to theory) review of first-person accounts, co-written between academics and experts by experience, to identify key experiential themes.

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The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors.

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Psychosis is the most ineffable experience of mental disorder. We provide here the first co-written bottom-up review of the lived experience of psychosis, whereby experts by experience primarily selected the subjective themes, that were subsequently enriched by phenomenologically-informed perspectives. First-person accounts within and outside the medical field were screened and discussed in collaborative workshops involving numerous individuals with lived experience of psychosis as well as family members and carers, representing a global network of organizations.

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Introduction: With biomedical imaging research increasingly using large datasets, it becomes critical to find operator-free methods to quality control the data collected and the associated analysis. Attempts to use artificial intelligence (AI) to perform automated quality control (QC) for both single-site and multi-site datasets have been explored in some neuroimaging techniques (e.g.

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Importance: Estimating the current likelihood of transitioning from a clinical high risk for psychosis (CHR-P) to psychosis holds paramount importance for preventive care and applied research.

Objective: To quantitatively examine the consistency and magnitude of transition risk to psychosis in individuals at CHR-P.

Data Sources: PubMed and Web of Science databases until November 1, 2020.

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Dopaminergic dysregulation is one of the leading hypotheses for the pathoetiology underlying psychotic disorders such as schizophrenia. Molecular imaging studies have shown increased striatal dopamine synthesis capacity (DSC) in schizophrenia and people in the prodrome of psychosis. However, it is unclear if genetic risk for psychosis is associated with altered DSC.

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Background: Much is not known about the efficacy of interventions to prevent poor mental health outcomes in young people by targeting either the general population (universal prevention) or asymptomatic individuals with high risk of developing a mental disorder (selective prevention).

Methods: We conducted a PRISMA/MOOSE-compliant systematic review and meta-analysis of Web of Science to identify studies comparing post-test efficacy (effect size [ES]; Hedges' g) of universal or selective interventions for poor mental health outcomes versus control groups, in samples with mean age <35 years (PROSPERO: CRD42018102143). Measurements included random-effects models, I2 statistics, publication bias, meta-regression, sensitivity analyses, quality assessments, number needed to treat, and population impact number.

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Preclinical models propose that increased hippocampal activity drives subcortical dopaminergic dysfunction and leads to psychosis-like symptoms and behaviors. Here, we used multimodal neuroimaging to examine the relationship between hippocampal regional cerebral blood flow (rCBF) and striatal dopamine synthesis capacity in people at clinical high risk (CHR) for psychosis and investigated its association with subsequent clinical and functional outcomes. Ninety-five participants (67 CHR and 28 healthy controls) underwent arterial spin labeling MRI and F-DOPA PET imaging at baseline.

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Promotion of good mental health in young people is important. Our aim was to evaluate the consistency and magnitude of the efficacy of universal/selective interventions to promote good mental health. A systematic PRISMA/RIGHT-compliant meta-analysis (PROSPERO: CRD42018088708) search of Web of Science until 04/31/2019 identified original studies comparing the efficacy of universal/selective interventions for good mental health vs a control group, in samples with a mean age <35 years.

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The ability to identify biomarkers of psychosis risk is essential in defining effective preventive measures to potentially circumvent the transition to psychosis. Using samples of people at clinical high risk for psychosis (CHR) and Healthy controls (HC) who were administered a task fMRI paradigm, we used a framework for labelling time windows of fMRI scans as 'integrated' FC networks to provide a granular representation of functional connectivity (FC). Periods of integration were defined using the 'cartographic profile' of time windows and k-means clustering, and sub-network discovery was carried out using Network Based Statistics (NBS).

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Background: The clinical high-risk state for psychosis (CHR-P) paradigm has facilitated the implementation of psychosis prevention into clinical practice; however, advancements in adolescent CHR-P populations are less established.

Methods: We performed a PRISMA/MOOSE-compliant systematic review of the Web of Science database, from inception until 7 October 2019, to identify original studies conducted in CHR-P children and adolescents (mean age <18 years). Findings were systematically appraised around core themes: detection, prognosis and intervention.

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Psychosis has been proposed to develop from dysfunction in a hippocampal-striatal-midbrain circuit, leading to aberrant salience processing. Here, we used functional magnetic resonance imaging (fMRI) during novelty salience processing to investigate this model in people at clinical high risk (CHR) for psychosis according to their subsequent clinical outcomes. Seventy-six CHR participants as defined using the Comprehensive Assessment of At-Risk Mental States (CAARMS) and 31 healthy controls (HC) were studied while performing a novelty salience fMRI task that engaged an a priori hippocampal-striatal-midbrain circuit of interest.

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In children and adolescents, schizophrenia is one of the ten main causes of disability-adjusted life years. The identification of people at Clinical High Risk of developing Psychosis (CHR-P) is one of the most promising strategies to improve outcomes. However, in children and adolescents research on the CHR-P state is still in its infancy and the clinical validity of at-risk criteria appears understudied in this population.

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A leading hypothesis for schizophrenia and related psychotic disorders proposes that cortical brain disruption leads to subcortical dopaminergic dysfunction, which underlies psychosis in the majority of patients who respond to treatment. Although supported by preclinical findings that prefrontal cortical lesions lead to striatal dopamine dysregulation, the relationship between prefrontal structural volume and striatal dopamine function has not been tested in people with psychosis. We therefore investigated the in vivo relationship between striatal dopamine synthesis capacity and prefrontal grey matter volume in treatment-responsive patients with psychosis, and compared them to treatment non-responsive patients, where dopaminergic mechanisms are not thought to be central.

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Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predictors automatically. To date, there is no empirical research comparing the prognostic accuracy of these two methods for the prediction of psychosis onset. In a first experiment, no improved performance was observed when machine-learning methods (LASSO and RIDGE) were applied-using the same predictors-to an individualised, transdiagnostic, clinically based, risk calculator previously developed on the basis of clinical-learning (predictors: age, gender, age by gender, ethnicity, ICD-10 diagnostic spectrum), and externally validated twice.

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Preclinical models of psychosis propose that hippocampal glutamatergic neuron hyperactivity drives increased striatal dopaminergic activity, which underlies the development of psychotic symptoms. The aim of this study was to examine the relationship between hippocampal glutamate and subcortical dopaminergic function in people at clinical high risk for psychosis, and to assess the association with the development of psychotic symptoms. H-MRS was used to measure hippocampal glutamate concentrations, and F-DOPA PET was used to measure dopamine synthesis capacity in 70 subjects (51 people at clinical high risk for psychosis and 19 healthy controls).

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One of the most statistically significant loci to result from large-scale GWAS of schizophrenia is 10q24.32. However, it is still unclear how this locus is involved in the pathoaetiology of schizophrenia.

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The first rate-limiting step for primary indicated prevention of psychosis is the detection of young people who may be at risk. The ability of specialized clinics to detect individuals at risk for psychosis is limited. A clinically based, individualized, transdiagnostic risk calculator has been developed and externally validated to improve the detection of individuals at risk in secondary mental health care.

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Alterations of the "pre-reflective" sense of first-person perspective (e.g., of the "basic self") are characteristic features of schizophrenic spectrum disorders and are significantly present in the prodromal phase of psychosis and in subjects at ultra-high risk for psychosis (UHR).

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