Publications by authors named "Wiepke Cahn"

142 Publications

[Anxiety and mood disorders are independent risk factors for cardiovascular diseases].

Ned Tijdschr Geneeskd 2021 Oct 28;165. Epub 2021 Oct 28.

Wilhelmina Ziekenhuis Assen, Wilhelmina Apotheek, Assen.

Objective: Psychiatric conditions are insufficiently highlighted as cardiovascular risk factors in the CVRM guideline. Objectives of this review are 1) to determine if anxiety and mood symptoms/disorders are independent cardiovascular risk factors; 2) to compare this risk to a population without these psychiatric conditions and 3) to ascertain the influence of psychiatric disease severity.

Design: Narrative systematic review METHOD: We searched for meta-analyses and systematic reviews in PubMed. Quality assessment by AMSTAR criteria.

Results: 10 reviews were included from 172 hits. (Sub)clinical depression and mood disorders are associated with an increased independent risk to develop cardiovascular diseases, coronary artery disease, myocardial infarction and cerebrovascular disease. Bipolar disorders increase the cerebrovascular risk, but not myocardial infarction. Anxiety disorders/symptoms heighten the cardiovascular, myocardial and cerebrovascular risk.

Conclusion: Anxiety and mood symptoms/disorders are independent cardiovascular risk factors. Severe anxiety and mood disorders should be included as separate risk factors in the CVRM guideline.
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October 2021

The Community Assessment of Psychic Experiences: Optimal cut-off scores for detecting individuals with a psychotic disorder.

Int J Methods Psychiatr Res 2021 Dec 31;30(4):e1893. Epub 2021 Aug 31.

Clinical Psychology and Psychotherapy, Institute of Psychology, Universität Hamburg, Hamburg, Germany.

Objectives: The need for a brief screening tool for psychosis is widely recognized. The Community Assessment of Psychic Experiences (CAPE) is a popular self-report measure of psychosis, but a cut-off score that can detect those most likely to fulfill diagnostic criteria for psychotic disorder is not established.

Methods: A case-control sample from the Genetic Risk and Outcome of Psychosis Project study (N = 1375, healthy individuals, n = 507, and individuals with a psychotic disorder, n = 868), was used to examine cut-off scores of the CAPE with receiver operating curve analyses. We examined 27 possible cut-off scores computed from a combination of scores from the frequency and distress scales of the various factors of the CAPE.

Results: The weighted severity positive symptom dimension was most optimal in detecting individuals with a psychotic disorder (>1.75 cut-off; area under the curve = 0.88; sensitivity, 75%; specificity, 88%), which correctly identified 80% of the sample as cases or controls with a diagnostic odds ratio of 22.69.

Conclusions: The CAPE can be used as a first screening tool to detect individuals who are likely to fulfill criteria for a psychotic disorder. The >1.75 cut-off of the weighted severity positive symptom dimension provides a better prediction than all alternatives tested so far.
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http://dx.doi.org/10.1002/mpr.1893DOI Listing
December 2021

Predicting Future Service Use in Dutch Mental Healthcare: A Machine Learning Approach.

Adm Policy Ment Health 2021 Aug 31. Epub 2021 Aug 31.

Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands.

A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected service use. The skewness in service use is a challenge for such models. In this study, we applied a machine learning approach to forecast expected service use, as a starting point for agreements between financiers and suppliers of mental healthcare. This study used administrative data from a large mental healthcare organization in the Netherlands. A training set was selected using records from 2017 (N = 10,911), and a test set was selected using records from 2018 (N = 10,201). A baseline model and three random forest models were created from different types of input data to predict (the remainder of) numeric individual treatment hours. A visual analysis was performed on the individual predictions. Patients consumed 62 h of mental healthcare on average in 2018. The model that best predicted service use had a mean error of 21 min at the insurance group level and an average absolute error of 28 h at the patient level. There was a systematic under prediction of service use for high service use patients. The application of machine learning techniques on mental healthcare data is useful for predicting expected service on group level. The results indicate that these models could support financiers and suppliers of healthcare in the planning and allocation of resources. Nevertheless, uncertainty in the prediction of high-cost patients remains a challenge.
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http://dx.doi.org/10.1007/s10488-021-01150-6DOI Listing
August 2021

Is change over time in psychotic symptoms related to social functioning?

Int J Soc Psychiatry 2021 Aug 13:207640211039248. Epub 2021 Aug 13.

Department of Tranzo Scientific Center for Care and Welfare, Tilburg University, The Netherlands.

Objective: In psychosis, treatment often focuses on symptom reduction whereas social functioning is also essential. In this study, we investigate positive psychotic symptoms and medication use in relation to social functioning over a 3-year time-period in 531 patients diagnosed with psychosis. Furthermore, relations of positive symptoms with needs for care and quality of life were also investigated.

Method: Using repeated measures analysis, changes were measured over time. Hereafter, mixed model analyses were performed to determine the associations of social functioning, needs for care, and quality of life with psychotic symptoms and patient characteristics. Finally, we assessed differences in symptoms and medication dose between those with an increase and those with a decrease in social functioning.

Results: Patients significantly improved in social functioning, while psychotic symptoms increased. Improvement in social functioning was associated with younger age, higher IQ, and lower social functioning at T1, but not with positive symptoms. Also, improvement in social functioning was found to be related to a decrease in the dose of clozapine. Improvement in social functioning occurs despite worsening of positive symptoms.

Conclusions: The findings suggest the need to further explore the relation between symptomatology, social functioning, and medication use. In the treatment of psychotic disorders, one should reconsider the strong focus on reducing psychotic symptoms. The current focus needs to shift much more toward improving functional outcome, especially when the patient expresses a desire for change in this respect.
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http://dx.doi.org/10.1177/00207640211039248DOI Listing
August 2021

The relation between psychological distress and medication adherence in lung transplant candidates and recipients: A cross-sectional study.

J Clin Nurs 2021 Jul 2. Epub 2021 Jul 2.

Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.

Aims And Objectives: To explore the prevalence of psychological distress such as anxiety, depression and post-traumatic stress disorder and its associations with medication adherence in lung transplant patients.

Background: Psychological distress after lung transplantation may impact clinical outcomes by associated behaviours such as non-adherence to medication. Evidence about the relation between psychological distress and medication adherence in lung transplant patients is limited and not well explained.

Design And Methods: We conducted a single-centre study with a cross-sectional design in 73 lung transplant candidates and 116 recipients. Questionnaires were the Brief Symptom Inventory, Impact of Event Scale and Basel Assessment of Adherence to Immunosuppressive Medications Scale. The STROBE checklist was monitored.

Results: In candidates, 39.7% reported (sub)clinical symptoms of depression, in recipients this was 21.6%. We observed suicidal ideation in recipients (8.6%), and candidates (5.5%). The prevalence of (sub)clinical symptoms of anxiety was 38.3% in candidates and 33.7% in recipients. After lung transplantation, 12% of the recipients reported clinical symptoms of PTSD related to the transplantation. Symptoms of anxiety and medication adherence were significantly and positively related in transplant recipients. We found no association between depressive or post-traumatic stress symptoms, and medication adherence.

Conclusions: In lung transplant patients, we found a high prevalence of symptoms of depression and anxiety. Recipients had high levels of post-traumatic stress symptoms related to the transplantation. The prevalence of suicidal ideation was unexpectedly high in recipients. After lung transplantation, higher levels of anxiety were related to better medication adherence. We propose that LTX recipients are very anxious to develop dyspnoea and therefore take their medication more conscientiously.

Relevance To Clinical Practice: The clinical nurse specialist can play a key role in identifying and addressing psychological and behavioural problems. More prospective research on the role of anxiety and dyspnoea in lung transplant recipients is recommended.
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http://dx.doi.org/10.1111/jocn.15931DOI Listing
July 2021

Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach.

NPJ Schizophr 2021 Jul 2;7(1):34. Epub 2021 Jul 2.

Department of Psychiatry, University Medical Center Utrecht, UMC Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.

Schizophrenia and related disorders have heterogeneous outcomes. Individualized prediction of long-term outcomes may be helpful in improving treatment decisions. Utilizing extensive baseline data of 523 patients with a psychotic disorder and variable illness duration, we predicted symptomatic and global outcomes at 3-year and 6-year follow-ups. We classified outcomes as (1) symptomatic: in remission or not in remission, and (2) global outcome, using the Global Assessment of Functioning (GAF) scale, divided into good (GAF ≥ 65) and poor (GAF < 65). Aiming for a robust and interpretable prediction model, we employed a linear support vector machine and recursive feature elimination within a nested cross-validation design to obtain a lean set of predictors. Generalization to out-of-study samples was estimated using leave-one-site-out cross-validation. Prediction accuracies were above chance and ranged from 62.2% to 64.7% (symptomatic outcome), and 63.5-67.6% (global outcome). Leave-one-site-out cross-validation demonstrated the robustness of our models, with a minor drop in predictive accuracies of 2.3% on average. Important predictors included GAF scores, psychotic symptoms, quality of life, antipsychotics use, psychosocial needs, and depressive symptoms. These robust, albeit modestly accurate, long-term prognostic predictions based on lean predictor sets indicate the potential of machine learning models complementing clinical judgment and decision-making. Future model development may benefit from studies scoping patient's and clinicians' needs in prognostication.
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http://dx.doi.org/10.1038/s41537-021-00162-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253813PMC
July 2021

Sex Differences in Lifespan Trajectories and Variability of Human Sulcal and Gyral Morphology.

Cereb Cortex 2021 Oct;31(11):5107-5120

Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.

Sex differences in the development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, gyral span, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants 2 scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. Although hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and lower variability for sulcal width. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.
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http://dx.doi.org/10.1093/cercor/bhab145DOI Listing
October 2021

Sex Differences in Lifespan Trajectories and Variability of Human Sulcal and Gyral Morphology.

Cereb Cortex 2021 Oct;31(11):5107-5120

Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.

Sex differences in the development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, gyral span, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants 2 scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. Although hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and lower variability for sulcal width. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.
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http://dx.doi.org/10.1093/cercor/bhab145DOI Listing
October 2021

Clinical, Biochemical and Genetic Variables Associated With Metabolic Syndrome in Patients With Schizophrenia Spectrum Disorders Using Second-Generation Antipsychotics: A Systematic Review.

Front Psychiatry 2021 29;12:625935. Epub 2021 Mar 29.

Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

Individuals with severe mental illness experience increased morbidity and mortality compared to the general population. Adverse effects of antipsychotics, including weight gain, may contribute to the development of metabolic syndrome (MetS), which is associated with increased risks of all-cause and cardiovascular disease mortality. We aim to provide a comprehensive overview of clinical, biochemical and genetic factors associated with MetS among patients with schizophrenia spectrum disorders using second-generation antipsychotics (SGA). A literature search was performed in Pubmed and Embase to identify all cohort studies, cross-sectional studies and clinical trials investigating associations with MetS in patients with schizophrenia spectrum disorders using SGAs. We extracted and enumerated clinical, biochemical and genetic factors reported to be associated with MetS. We defined factors associated with MetS as factors being reported as associated with MetS in two or more studies. 58 studies were included in this review ( = 12,123). In total, 62 factors were found to be associated with increased risk of MetS. Thirty one out of 58 studies investigated factors that were reported as associated with MetS in two or more studies. With regard to clinical factors, we found gender, higher age, concomitant use of mood stabilizers, higher baseline and current BMI, earlier SGA exposure, higher dose, longer duration of treatment, psychosis and tobacco smoking to be significantly associated with MetS. Furthermore, the biochemical factors hypo-adiponectinemia, elevated levels of C-reactive protein (CRP) and higher white blood cell (WBC) count were identified as factors associated with MetS. Among pharmacogenetic factors, the rs1414334 C-allele of the HTR2C-gene was associated with MetS in patients using SGA. In this systematic review investigating clinical, biochemical and genetic factors associated with MetS in patients using SGAs we found that higher age, higher baseline BMI, higher current BMI and male as well as female gender were positively associated with MetS across all antipsychotics. This study may set the stage for the application of clinical, biochemical and genetic factors to predict the risk of developing MetS in patients using SGAs. Future research is needed to determine which patients using SGAs are at risk to develop MetS in clinical practice.
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http://dx.doi.org/10.3389/fpsyt.2021.625935DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044798PMC
March 2021

Author Correction: Functional connectome differences in individuals with hallucinations across the psychosis continuum.

Sci Rep 2021 Apr 14;11(1):8540. Epub 2021 Apr 14.

Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Neuroimaging Center, PO Box 196, 9700 AD, Groningen, The Netherlands.

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http://dx.doi.org/10.1038/s41598-021-87849-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046756PMC
April 2021

Reduced resting state functional connectivity in the hippocampus-midbrain-striatum network of schizophrenia patients.

J Psychiatr Res 2021 06 26;138:83-88. Epub 2021 Mar 26.

Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands. Electronic address:

Contemporary preclinical models suggest that abnormal functioning of a brain network consisting of the hippocampus, midbrain and striatum plays a critical role in the pathophysiology of schizophrenia. Previous neuroimaging studies examined individual aspects of this model in schizophrenia patients and individuals at clinical high risk for psychosis. However, this exact preclinical brain network has not been translated to human neuroimaging studies with schizophrenia patients and therefore it is currently unknown how functioning of this network is altered in patients. Here we investigated resting state functional connectivity in the hippocampus-midbrain-striatum network of schizophrenia patients, using functional Magnetic Resonance Imaging. Based on preclinical models, a network of functionally validated brain regions comprising the anterior subiculum (SUB), limbic striatum (LS), ventral tegmental area (VTA) and associative striatum (AS) was examined in 47 schizophrenia patients and 51 healthy controls. Schizophrenia patients demonstrated significantly lower functional connectivity in this hippocampus-midbrain-striatum network compared with healthy controls (p = 0.036). Particular reductions in connectivity were found between the SUB and LS (0.002 ± 0.315 and 0.116 ± 0.224, p = 0.040) and between the VTA and AS (0.230 ± 0.268 and 0.356 ± 0.285, p = 0.026). In patients, functional connectivity was not significantly associated with positive, negative or general symptom scores. Reduced connectivity is consistent with the concept of functional brain dysconnectivity as a key feature of the disorder. Our results support the notion that functioning of the hippocampus-midbrain-striatum network is significantly altered in the pathophysiology of schizophrenia.
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http://dx.doi.org/10.1016/j.jpsychires.2021.03.041DOI Listing
June 2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Transl Psychiatry 2021 03 22;11(1):182. Epub 2021 Mar 22.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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http://dx.doi.org/10.1038/s41398-021-01213-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985307PMC
March 2021

Functional connectome differences in individuals with hallucinations across the psychosis continuum.

Sci Rep 2021 01 13;11(1):1108. Epub 2021 Jan 13.

Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Neuroimaging Center, PO Box 196, 9700 AD, Groningen, The Netherlands.

Hallucinations may arise from an imbalance between sensory and higher cognitive brain regions, reflected by alterations in functional connectivity. It is unknown whether hallucinations across the psychosis continuum exhibit similar alterations in functional connectivity, suggesting a common neural mechanism, or whether different mechanisms link to hallucinations across phenotypes. We acquired resting-state functional MRI scans of 483 participants, including 40 non-clinical individuals with hallucinations, 99 schizophrenia patients with hallucinations, 74 bipolar-I disorder patients with hallucinations, 42 bipolar-I disorder patients without hallucinations, and 228 healthy controls. The weighted connectivity matrices were compared using network-based statistics. Non-clinical individuals with hallucinations and schizophrenia patients with hallucinations exhibited increased connectivity, mainly among fronto-temporal and fronto-insula/cingulate areas compared to controls (P < 0.001 adjusted). Differential effects were observed for bipolar-I disorder patients with hallucinations versus controls, mainly characterized by decreased connectivity between fronto-temporal and fronto-striatal areas (P = 0.012 adjusted). No connectivity alterations were found between bipolar-I disorder patients without hallucinations and controls. Our results support the notion that hallucinations in non-clinical individuals and schizophrenia patients are related to altered interactions between sensory and higher-order cognitive brain regions. However, a different dysconnectivity pattern was observed for bipolar-I disorder patients with hallucinations, which implies a different neural mechanism across the psychosis continuum.
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http://dx.doi.org/10.1038/s41598-020-80657-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806763PMC
January 2021

Cognitive functioning throughout adulthood and illness stages in individuals with psychotic disorders and their unaffected siblings.

Mol Psychiatry 2021 Aug 7;26(8):4529-4543. Epub 2021 Jan 7.

Department of Psychiatry, Dokuz Eylül University, School of Medicine, Izmir, Turkey.

Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271), compared to controls (n = 3301). An abbreviated WAIS-III measured verbal knowledge, working memory, visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = -0.45 to -0.73, p < 0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = -0.14 to -0.33, p < 0.001). Magnitude of impairment was not associated with participant age, such that the size of impairment in older and younger patients did not significantly differ. However, first-episode patients performed worse than prodromal patients (ES range = -0.88 to -0.60, p < 0.001). Adjusting for cannabis use, symptom severity, and global functioning attenuated impairments in siblings, while deficits in patients remained statistically significant, albeit reduced by half (ES range = -0.13 to -0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = -0.21 to -0.43, p < 0.01). Deficits in verbal knowledge, and working memory may specifically index familial, i.e., shared genetic and/or shared environmental, liability for psychotic disorders. Nevertheless, potentially modifiable illness-related factors account for a significant portion of the cognitive impairment in psychotic disorders.
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http://dx.doi.org/10.1038/s41380-020-00969-zDOI Listing
August 2021

Study protocol of a randomized, double-blind, placebo-controlled, multi-center trial to treat antipsychotic-induced weight gain: the Metformin-Lifestyle in antipsychotic users (MELIA) trial.

BMC Psychiatry 2021 01 5;21(1). Epub 2021 Jan 5.

Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, HP A01.126, P.O. Box 85500, 3508, Utrecht, GA, The Netherlands.

Background: Antipsychotic-induced Weight Gain (AiWG) is a debilitating and common adverse effect of antipsychotics. AiWG negatively impacts life expectancy, quality of life, treatment adherence, likelihood of developing type-2 diabetes and readmission. Treatment of AiWG is currently challenging, and there is no consensus on the optimal management strategy. In this study, we aim to evaluate the use of metformin for the treatment of AiWG by comparing metformin with placebo in those receiving treatment as usual, which includes a lifestyle intervention.

Methods: In this randomized, double-blind, multicenter, placebo-controlled, pragmatic trial with a follow-up of 52 weeks, we aim to include 256 overweight participants (Body Mass Index (BMI) > 25 kg/m) of at least 16 years of age. Patients are eligible if they have been diagnosed with schizophrenia spectrum disorder and if they have been using an antipsychotic for at least three months. Participants will be randomized with a 1:1 allocation to placebo or metformin, and will be treated for a total of 26 weeks. Metformin will be started at 500 mg b.i.d. and escalated to 1000 mg b.i.d. 2 weeks thereafter (up to a maximum of 2000 mg daily). In addition, all participants will undergo a lifestyle intervention as part of the usual treatment consisting of a combination of an exercise program and dietary consultations. The primary outcome measure is difference in body weight as a continuous trait between the two arms from treatment inception until 26 weeks of treatment, compared to baseline. Secondary outcome measures include: 1) Any element of metabolic syndrome (MetS); 2) Response, defined as ≥5% body weight loss at 26 weeks relative to treatment inception; 3) Quality of life; 4) General mental and physical health; and 5) Cost-effectiveness. Finally, we aim to assess whether genetic liability to BMI and MetS may help estimate the amount of weight reduction following initiation of metformin treatment.

Discussion: The pragmatic design of the current trial allows for a comparison of the efficacy and safety of metformin in combination with a lifestyle intervention in the treatment of AiWG, facilitating the development of guidelines on the interventions for this major health problem.

Trial Registration: This trial was registered in the Netherlands Trial Register (NTR) at  https://www.trialregister.nl/trial/8440 as NTR NL8840 on March 8, 2020.
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http://dx.doi.org/10.1186/s12888-020-02992-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783702PMC
January 2021

Diffusion MRI derived free-water imaging measures in patients with schizophrenia and their non-psychotic siblings.

Prog Neuropsychopharmacol Biol Psychiatry 2021 07 2;109:110238. Epub 2021 Jan 2.

Department of Psychiatry, University Medical Center Utrecht (UMCU), UMCU Brain Center, Utrecht, the Netherlands; Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, USA; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Boston, USA.

Free-water imaging is a diffusion MRI technique that separately models water diffusion hindered by fiber tissue and water that disperses freely in the extracellular space. Studies using this technique have shown that schizophrenia is characterized by a lower level of fractional anisotropy of the tissue compartment (FA) and higher free-water fractional volume (FW). It is unknown, however, whether such abnormalities are an expression of pre-existing (genetic) risk for schizophrenia or a manifestation of the illness. To investigate the contribution of familial risk factors to white matter abnormalities, we used the free-water imaging technique to assess FA and FW in a large cohort of 471 participants including 161 patients with schizophrenia, 182 non-psychotic siblings, and 128 healthy controls. In this sample, patients did not show significant differences in FA as compared to controls, but did exhibit a higher level of FW relative to both controls and siblings in the left uncinate fasciculus, superior corona radiata and fornix / stria terminalis. This increase in FW was found to be related to, though not solely explained by, ventricular enlargement. Siblings did not show significant FW abnormalities. However, siblings did show a higher level of FA as compared to controls and patients, in line with results of a previous study on the same data using conventional DTI. Taken together, our findings suggest that extracellular free-water accumulation in patients is likely a manifestation of established disease rather than an expression of familial risk for schizophrenia and that super-normal levels of FA in unaffected siblings may reflect a compensatory process.
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http://dx.doi.org/10.1016/j.pnpbp.2020.110238DOI Listing
July 2021

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Hum Brain Mapp 2020 Oct 7. Epub 2020 Oct 7.

Neuroscience Research Australia, Sydney, Australia.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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http://dx.doi.org/10.1002/hbm.25206DOI Listing
October 2020

Comparing psychotic experiences in low-and-middle-income-countries and high-income-countries with a focus on measurement invariance.

Psychol Med 2020 Oct 7:1-8. Epub 2020 Oct 7.

Clinical Psychology and Psychotherapy, Institute of Psychology, Universität Hamburg, Hamburg, Germany.

Background: The prevalence of psychotic experiences (PEs) is higher in low-and-middle-income-countries (LAMIC) than in high-income countries (HIC). Here, we examine whether this effect is explicable by measurement bias.

Methods: A community sample from 13 countries (N = 7141) was used to examine the measurement invariance (MI) of a frequently used self-report measure of PEs, the Community Assessment of Psychic Experiences (CAPE), in LAMIC (n = 2472) and HIC (n = 4669). The CAPE measures positive (e.g. hallucinations), negative (e.g. avolition) and depressive symptoms. MI analyses were conducted with multiple-group confirmatory factor analyses.

Results: MI analyses showed similarities in the structure and understanding of the CAPE factors between LAMIC and HIC. Partial scalar invariance was found, allowing for latent score comparisons. Residual invariance was not found, indicating that sum score comparisons are biased. A comparison of latent scores before and after MI adjustment showed both overestimation (e.g. avolition, d = 0.03 into d = -0.42) and underestimation (e.g. magical thinking, d = -0.03 into d = 0.33) of PE in LAMIC relative to HIC. After adjusting the CAPE for MI, participants from LAMIC reported significantly higher levels on most CAPE factors but a significantly lower level of avolition.

Conclusion: Previous studies using sum scores to compare differences across countries are likely to be biased. The direction of the bias involves both over- and underestimation of PEs in LAMIC compared to HIC. Nevertheless, the study confirms the basic finding that PEs are more frequent in LAMIC than in HIC.
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http://dx.doi.org/10.1017/S0033291720003323DOI Listing
October 2020

Dissimilarity in Sulcal Width Patterns in the Cortex can be Used to Identify Patients With Schizophrenia With Extreme Deficits in Cognitive Performance.

Schizophr Bull 2021 03;47(2):552-561

Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.

Schizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in the severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The person-based similarity index (PBSI) of brain morphology indexes an individual's morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes the morphometric similarity of an independent individual (eg, a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual's degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients and 164 healthy controls; 656 magnetic resonance imaging scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in the severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.
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http://dx.doi.org/10.1093/schbul/sbaa131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965061PMC
March 2021

Functional brain networks in the schizophrenia spectrum and bipolar disorder with psychosis.

NPJ Schizophr 2020 Sep 2;6(1):22. Epub 2020 Sep 2.

University of Groningen, Department of Neuroscience, University Medical Center Groningen, Groningen, The Netherlands.

Psychotic experiences have been proposed to lie on a spectrum, ranging from subclinical experiences to treatment-resistant schizophrenia. We aimed to characterize functional connectivity and brain network characteristics in relation to the schizophrenia spectrum and bipolar disorder with psychosis to disentangle neural correlates to psychosis. Additionally, we studied antipsychotic medication and lithium effects on network characteristics. We analyzed functional connectivity strength and network topology in 487 resting-state functional MRI scans of individuals with schizophrenia spectrum disorder (SCZ), bipolar disorder with a history of psychotic experiences (BD), treatment-naïve subclinical psychosis (SCP), and healthy controls (HC). Since differences in connectivity strength may confound group comparisons of brain network topology, we analyzed characteristics of the minimum spanning tree (MST), a relatively unbiased backbone of the network. SCZ and SCP subjects had a lower connectivity strength than BD and HC individuals but showed no differences in network topology. In contrast, BD patients showed a less integrated network topology but no disturbances in connectivity strength. No differences in outcome measures were found between SCP and SCZ, or between BD patients that used antipsychotic medication or lithium and those that did not. We conclude that functional networks in patients prone to psychosis have different signatures for chronic SCZ patients and SCP compared to euthymic BD patients, with a limited role for medication. Connectivity strength effects may have confounded previous studies, as no functional network alterations were found in SCZ after strict correction for connectivity strength.
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http://dx.doi.org/10.1038/s41537-020-00111-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468123PMC
September 2020

Neutrophil fluorescence in clozapine users is attributable to a 14kDa secretable protein.

Pharmacol Res Perspect 2020 10;8(5):e00627

Department of Respiratory Medicine, Laboratory of Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.

Clozapine is the only antipsychotic agent with demonstrated efficacy in refractory schizophrenia. However, use of clozapine is hampered by its adverse effects, including potentially fatal agranulocytosis. Recently, we showed an association between neutrophil autofluorescence and clozapine use. In this study, we evaluated the subcellular localization of clozapine-associated fluorescence and tried to elucidate its source. Neutrophils of clozapine users were analyzed with fluorescence microscopy to determine the emission spectrum and localization of the fluorescence signal. Next, these neutrophils were stimulated with different degranulation agents to determine the localization of fluorescence. Lastly, isolated neutrophil lysates of clozapine users were separated by SDS-PAGE and evaluated. Clozapine-associated fluorescence ranged from 420 nm to 720 nm, peaking at 500-550 nm. Fluorescence was localized in a large number of small loci, suggesting granular localization of the signal. Neutrophil degranulation induced by Cytochalasin B/fMLF reduced fluorescence, whereas platelet-activating factor (PAF)/fMLF induced degranulation did not, indicating that the fluorescence originates from a secretable substance in azurophilic granules. SDS-PAGE of isolated neutrophil lysates revealed a fluorescent 14kDa band, suggesting that neutrophil fluorescence is likely to be originated from a 14kDa protein/peptide fragment. We conclude that clozapine-associated fluorescence in neutrophils is originating from a 14kDa soluble protein (fragment) present in azurophilic granules of neutrophils. This protein could be an autofluorescent protein already present in the cell and upregulated by clozapine, or a protein altered by clozapine to express fluorescence. Future studies should further explore the identity of this protein and its potential role in the pathophysiology of clozapine-induced agranulocytosis.
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http://dx.doi.org/10.1002/prp2.627DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437349PMC
October 2020

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study.

Mol Psychiatry 2021 Sep 27;26(9):5307-5319. Epub 2020 Jul 27.

The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland.

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.
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http://dx.doi.org/10.1038/s41380-020-0820-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589646PMC
September 2021

Intoxicated persons showing challenging behavior demand complexity interventions: a pilot study at the interface of the ER and the complexity intervention unit.

Eur Arch Psychiatry Clin Neurosci 2021 Aug 12;271(5):903-913. Epub 2020 Jul 12.

Department of Psychiatry, Rijnstate Hospital, Arnhem, The Netherlands.

Intoxicated persons showing challenging behavior (IPCBs) under influence of alcohol and/or drugs frequently have trouble finding appropriate acute care. Often IPCBs are stigmatized being unwilling or unable to accept help. Separated physical and mental healthcare systems hamper integrated acute care for IPCBs. This pilot aimed to substantiate the physical, psychiatric, and social health needs of IPCBs visiting the emergency room (ER) during a 3-month period. All ER visits were screened. After triage by the ER physician, indicated IPCBs were additionally assessed by the consultation-liaison-psychiatry physician. If needed, IPCBs were admitted to a complexity intervention unit for further examinations to provide integrated treatments and appropriate follow-up care. The INTERMED and Health of the Nation Outcome Scale (HoNOS) questionnaires were used to substantiate the complexity and needs. Field-relevant stakeholders were interviewed about this approach for acute integrated care. Alongside substance abuse, almost half of identified IPCBs suffered from comorbid psychiatric disturbances and one third showed substantial physical conditions requiring immediate medical intervention. Almost all IPCBs (96%) accepted the acute medical care voluntarily. IPCBs showed high mean initial scores of INTERMED (27.8 ± 10.0) and HoNOS (20.8 ± 6.9). At discharge from the complexity intervention unit, the mean HoNOS score decreased significantly (13.4 ± 8.6; P < 0.001). Field-relevant stakeholders strongly supported the interdisciplinary approach and ER-facility for IPCBs and acknowledged their unmet health needs. A biopsychosocial assessment at the ER, followed by a short admission if necessary, is effective in IPCBs. This approach helps to merge separated healthcare systems and may reduce stigmatization of IPCBs needing help.
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http://dx.doi.org/10.1007/s00406-020-01162-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236043PMC
August 2021

Insight, personality, and symptoms among individuals with psychosis: Cross-sectional and longitudinal relationships.

Schizophr Res 2020 08 8;222:243-250. Epub 2020 Jun 8.

Department of Clinical Psychology, University of Amsterdam, Amsterdam, the Netherlands.

Background: Reports on the relationship between clinical insight and psychotic symptoms have shown inconsistent results, and the association between clinical insight and personality has rarely been addressed. The aim of this study was to examine whether personality is correlated cross-sectionally with insight level, and longitudinally with change in insight, beyond symptoms.

Methods: Participants were a sub-sample of the Dutch Genetic Risk and Outcome of Psychosis (GROUP) project. Two hundred and eleven participants diagnosed with non-affective psychotic disorders took part in the cross-sectional part of the study, of whom 136 took part in the three-year follow-up assessment. They were administered with self-report Birchwood insight scale and NEO-Five Factor Inventory, and clinicians assessed them according to PANSS and CDS symptoms scales.

Results: Cross-sectional analysis showed baseline self-report insight was positively related to neuroticism and agreeableness and negatively related to extraversion. Longitudinal analysis showed change in level of self-reported insight was predicted by baseline-insight and change in symptoms of disorganization. Personality factors did not predict insight change (as measured either by self-report or by clinician assessment).

Discussion: The cross-sectional findings showed self-report insight (as opposed to clinician-rated) is associated with personality traits, suggesting negative affect is related to higher level of insight and that having insight may be influenced by the wish to comply with views of professionals, or a tendency to cover up problems. The longitudinal findings imply that not personality but change in severity of symptoms of disorganization, and possibly other variables, predicts change in insight.
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http://dx.doi.org/10.1016/j.schres.2020.05.042DOI Listing
August 2020

Bariatric surgery in patients with psychiatric comorbidity: Significant weight loss and improvement of physical quality of life.

Clin Obes 2020 Aug 18;10(4):e12373. Epub 2020 May 18.

Nederlandse Obesitas Kliniek, Huis ter Heide, The Netherlands.

Background: Patients that have psychiatric comorbidity are thought to lose less weight than the general bariatric population and are therefore sometimes denied surgery. However, there is no scientific evidence for this assumption. The aim of this study is to evaluate the weight loss and health-related quality of life (HRQoL) in patients with psychiatric disorders who undergo bariatric surgery and compare these patients with a general bariatric population.

Method: Patients who underwent bariatric surgery in 2015 were included. Patients who received individual counselling and had a current DSM IV axis 1 or 2 diagnosis were included in the psychiatric group (n = 163), all other patients in the generic group (n = 2362).Weight and HRQoL were assessed before and 12-, 24-, 36- and 48-months after surgery. Data was analysed using regression analyses.

Results: The maximum total weight loss (TWL) was 27.4% in the psychiatric group vs 31.0% in the generic group. Difference in %TWL between the psychiatric and generic group was significant from baseline to all follow-up moments (P < .001). Improvement of PHS was significantly higher in the generic group from baseline to 12-month (P = .002), 24-month (P = .0018), 36-month (P = .025) and 48-monthfollow-up (P = .003). Change in mental HRQoL was only different comparing baseline to 48-monthfollow-up (P = .014).

Conclusion: Although weight loss and change in physical HRQoL was lower in patients with pre-operative psychiatric disorders, results of this group were still excellent. Thus, patients with psychiatric diagnoses benefit greatly from bariatric surgery and these patients should not be denied weight loss surgery.
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http://dx.doi.org/10.1111/cob.12373DOI Listing
August 2020

Changes in the intracranial volume from early adulthood to the sixth decade of life: A longitudinal study.

Neuroimage 2020 10 24;220:116842. Epub 2020 Apr 24.

UMC Utrecht Brain Center, Department of Psychiatry, University Medical Center Utrecht, the Netherlands. Electronic address:

Normal brain-aging occurs at all structural levels. Excessive pathophysiological changes in the brain, beyond the normal one, are implicated in the etiology of brain disorders such as severe forms of the schizophrenia spectrum and dementia. To account for brain-aging in health and disease, it is critical to study the age-dependent trajectories of brain biomarkers at various levels and among different age groups. The intracranial volume (ICV) is a key biological marker, and changes in the ICV during the lifespan can teach us about the biology of development, aging, and gene X environment interactions. However, whether ICV changes with age in adulthood is not resolved. Applying a semi-automatic in-house-built algorithm for ICV extraction on T1w MR brain scans in the Dutch longitudinal cohort (GROUP), we measured ICV changes. Individuals between the ages of 16 and 55 years were scanned up to three consecutive times with 3.32±0.32 years between consecutive scans (N = 482, 359, 302). Using the extracted ICVs, we calculated ICV longitudinal aging-trajectories based on three analysis methods; direct calculation of ICV differences between the first and the last scan, fitting all ICV measurements of individuals to a straight line, and applying a global linear mixed model fitting. We report statistically significant increase in the ICV in adulthood until the fourth decade of life (average change +0.03%/y, or about 0.5 ml/y, at age 20), and decrease in the ICV afterward (-0.09%/y, or about -1.2 ml/y, at age 55). To account for previous cross-sectional reports of ICV changes, we analyzed the same data using a cross-sectional approach. Our cross-sectional analysis detected ICV changes consistent with the previously reported cross-sectional effect. However, the reported amount of cross-sectional changes within this age range was significantly larger than the longitudinal changes. We attribute the cross-sectional results to a generational effect. In conclusion, the human intracranial volume does not stay constant during adulthood but instead shows a small increase during young adulthood and a decrease thereafter from the fourth decade of life. The age-related changes in the longitudinalmeasure are smaller than those reported using cross-sectional approaches and unlikely to affect structural brain imaging studies correcting for intracranial volume considerably. As to the possible mechanisms involved, this awaits further study, although thickening of the meninges and skull bones have been proposed, as well as a smaller amount of brain fluids addition above the overall loss of brain tissue.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116842DOI Listing
October 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Using machine learning to predict mental healthcare consumption in non-affective psychosis.

Schizophr Res 2020 04 5;218:166-172. Epub 2020 Mar 5.

Tilburg University, Department of Tranzo Scientific Center for Care and Welfare, The Netherlands; Erasmus University Rotterdam, Department of Health Care Governance.

Objective: The main goal of the study was to predict individual patients' future mental healthcare consumption, and thereby enhancing the design of an efficient demand-oriented mental healthcare system by focusing on a patient population associated with intensive mental healthcare consumption. Factors that affect the mental healthcare consumption of service users with non-affective psychosis were identified, and subsequently used in a prognostic model to predict future healthcare consumption.

Method: This study was a secondary analysis of an existing dataset from the GROUP study. Based on mental healthcare consumption, patients with non-affective psychosis were divided into two groups: low (N = 579) and high (N = 488) intensive mental healthcare consumers. Three different techniques from the field of machine learning were applied on crosssectional data to identify risk factors: logistic regression, classification tree and a random forest. Subsequently, the same techniques were applied longitudinally in order to predict future healthcare consumption.

Results: Identified variables that affected healthcare consumption were the number of psychotic episodes, paid employment, engagement in social activities, previous healthcare consumption, and met needs. Analyses showed that the random forest method is best suited to model risk factors, and that these relations predict future healthcare consumption (AUC 0.71, PPV 0.65).

Conclusions: Machine learning techniques provide valuable information for identifying risk factors in psychosis. They may thus help clinicians optimize allocation of mental healthcare resources by predicting future healthcare consumption.
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http://dx.doi.org/10.1016/j.schres.2020.01.008DOI Listing
April 2020
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