Pharmacotherapy of schizophrenia: toward a metabolomic-based approach

CNS Spectrums ◽  
2018 ◽  
Vol 24 (03) ◽  
pp. 281-286 ◽  
Author(s):  
Haythum O. Tayeb ◽  
Hussam A. Murad ◽  
Misbahuddin M. Rafeeq ◽  
Frank I. Tarazi
Keyword(s):  
At Risk ◽  
Systematic Study ◽  
Psychotic Disorders ◽  
Response To Treatment ◽  
Current Standard ◽  
Biochemical Alterations ◽  
Potential Development ◽  
Novel Targets

Approximately 20%–30% of schizophrenia patients are resistant to current standard pharmacotherapies. Recent schizophrenia research aims to identify specific pathophysiological abnormalities and novel targets in the disease, with the goals of identifying at-risk individuals, facilitating diagnosis, prompting early and personalized interventions, and helping predict response to treatment. Metabolomics involves the systematic study of the profile of biochemical alterations early in the course of a given disorder. Major aspects of the schizophrenia metabolome have been characterized, uncovering potential selective biomarkers for the disease that may change how the disorder is diagnosed, and how patients are stratified and treated. This review focuses on the most common metabolomic fingerprints of the different pathways involved in the pathophysiology of schizophrenia, and the potential development of novel metabolomic-related pharmacotherapies for improved treatment of schizophrenia and other related idiopathic psychotic disorders.

Psychosis-Risk Syndromes

2016 ◽  
Vol 4 (1) ◽  
pp. 88-95
Author(s):  
Allison N. Macdonald ◽  
Katrina B. Goines ◽  
Derek M. Novacek ◽  
Elaine F. Walker
Keyword(s):  
At Risk ◽  
Medical Records ◽  
Policy Development ◽  
Predictive Power ◽  
Psychotic Disorders ◽  
Preventive Interventions ◽  
Major Focus ◽  
Psychotic Illness ◽  
Treatment Practices ◽  
Psychosis Risk

Identifying individuals at risk for psychotic disorders is now a major focus of research. The key objectives of this work are to identify mechanisms underlying the emergence of psychosis and predict impending illness, with the goal of developing preventive interventions. Despite notable progress, there is a dearth of ethically informed policies to guide disclosure, documentation, and treatment practices. The limited predictive validity of psychosis-risk criteria and stigma surrounding psychotic disorders hinder such policy development. Thus, several challenging questions remain: Does the psychosis-risk designation achieve an adequate predictive power to indicate risk for a more serious disorder? When and how should individuals learn that they are at risk for a psychotic illness, and should such information be included in medical records? What, if any, treatment recommendations should be made? This article addresses these challenges and frames the central issues confronting ethically informed policies and practices for identifying and treating psychosis-risk syndromes.

General Practice Recruitment for People at Risk of Schizophrenia: The Buckingham Experience

2000 ◽  
Vol 34 (1_suppl) ◽  
pp. A131-A136 ◽  
Author(s):  
Ian R. H. Falloon
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Primary Care ◽  
At Risk ◽  
General Practice ◽  
Early Detection ◽  
Psychotic Disorders ◽  
Community Sample ◽  
Signs And Symptoms ◽  
Psychotic Episode

Objective The process of detecting people at high risk of schizophrenia from a community sample is a major challenge for prevention of psychotic disorders. The aim of this paper is to describe early detection procedures that can be implemented in primary care settings. Methods A selected literature review is supplemented by experiences and data obtained during the Buckingham Integrated Mental Health Care Project. Results General medical practitioners have been favoured as the agents most likely to prove helpful in detecting the key risk factors that predict the onset of schizophrenic disorders, as well as in recognising the earliest signs and symptoms of these conditions. However, the practical problems of screening for multiple and subtle risk factors in general practice are substantial, and general practitioners (GPs) often have difficulty recognising the earliest signs of a psychotic episode. A range of strategies to assist GPs detect early signs of psychosis in their patients are considered. Conclusions It is feasible to implement primary care setting early detection procedures for people at risk of schizophrenia. Implementation is aided by the use of a brief screening questionnaire, training sessions and case supervision; and increased collaboration with mental health services and other community agencies.

scholarly journals Circulating lipids associate with future weight gain in individuals with an at-risk mental state and in first-episode psychosis

2020 ◽  
Author(s):  
Santosh Lamichhane ◽  
Alex M. Dickens ◽  
Partho Sen ◽  
Heikki Laurikainen ◽  
Jaana Suvisaari ◽  
...  
Keyword(s):  
At Risk ◽  
Weight Gain ◽  
High Risk ◽  
Psychotic Disorders ◽  
First Episode Psychosis ◽  
Molecular Signature ◽  
First Episode ◽  
Baseline Serum ◽  
Average Life Span ◽  
Episode Psychosis

AbstractPatients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic co-morbidities. Identification of individuals with psychotic disorders with a high risk of rapid weight gain, and the associated development of metabolic complications, is an unmet need as regards public health. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 controls (CTR), 44 first-episode psychosis (FEP) patients and 22 individuals at clinical-high-risk (CHR) for psychosis, from two study centers (Turku/Finland and London/UK). Baseline serum samples were analyzed by lipidomics, while body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols with low double bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of two triacylglycerols (TG(48:0) and TG(45:0)), was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60–0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61–0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals, and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic co-morbidities.

scholarly journals Subcortical Brain Volume Abnormalities in Individuals With an At-risk Mental State

2020 ◽  
Vol 46 (4) ◽  
pp. 834-845
Author(s):  
Daiki Sasabayashi ◽  
Yoichiro Takayanagi ◽  
Tsutomu Takahashi ◽  
Naoyuki Katagiri ◽  
Atsushi Sakuma ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
At Risk ◽  
Magnetic Resonance ◽  
Globus Pallidus ◽  
Mental State ◽  
Lateral Ventricle ◽  
Psychotic Disorders ◽  
Resonance Imaging ◽  
Significant Difference ◽  
At Risk Mental State

Abstract Previous structural magnetic resonance imaging studies of psychotic disorders have demonstrated volumetric alterations in subcortical (ie, the basal ganglia, thalamus) and temporolimbic structures, which are involved in high-order cognition and emotional regulation. However, it remains unclear whether individuals at high risk for psychotic disorders with minimal confounding effects of medication exhibit volumetric changes in these regions. This multicenter magnetic resonance imaging study assessed regional volumes of the thalamus, caudate, putamen, nucleus accumbens, globus pallidus, hippocampus, and amygdala, as well as lateral ventricular volume using FreeSurfer software in 107 individuals with an at-risk mental state (ARMS) (of whom 21 [19.6%] later developed psychosis during clinical follow-up [mean = 4.9 years, SD = 2.6 years]) and 104 age- and gender-matched healthy controls recruited at 4 different sites. ARMS individuals as a whole demonstrated significantly larger volumes for the left caudate and bilateral lateral ventricles as well as a smaller volume for the right accumbens compared with controls. In male subjects only, the left globus pallidus was significantly larger in ARMS individuals. The ARMS group was also characterized by left-greater-than-right asymmetries of the lateral ventricle and caudate nucleus. There was no significant difference in the regional volumes between ARMS groups with and without later psychosis onset. The present study suggested that significant volume expansion of the lateral ventricle, caudate, and globus pallidus, as well as volume reduction of the accumbens, in ARMS subjects, which could not be explained only by medication effects, might be related to general vulnerability to psychopathology.

scholarly journals Gender differences of patients at-risk for psychosis regarding symptomatology, drug use, comorbidity and functioning – Results from the EU-GEI study

2019 ◽  
Vol 59 ◽  
pp. 52-59 ◽  
Author(s):  
Stephanie Menghini-Müller ◽  
Erich Studerus ◽  
Sarah Ittig ◽  
Ulrike Heitz ◽  
Laura Egloff ◽  
...  
Keyword(s):  
Gender Differences ◽  
At Risk ◽  
Drug Use ◽  
Anxiety Disorders ◽  
Statistical Power ◽  
Negative Symptoms ◽  
Psychotic Disorders ◽  
Cannabis Use ◽  
First Episode ◽  
Global Functioning

AbstractBackground:Gender differences in symptomatology in chronic schizophrenia and first episode psychosis patients have often been reported. However, little is known about gender differences in those at risk of psychotic disorders. This study investigated gender differences in symptomatology, drug use, comorbidity (i.e. substance use, affective and anxiety disorders) and global functioning in patients with an at-risk mental state (ARMS) for psychosis.Methods:The sample consisted of 336 ARMS patients (159 women) from the prodromal work package of the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI; 11 centers). Clinical symptoms, drug use, comorbidity and functioning were assessed at first presentation to an early detection center using structured interviews.Results:In unadjusted analyses, men were found to have significantly higher rates of negative symptoms and current cannabis use while women showed higher rates of general psychopathology and more often displayed comorbid affective and anxiety disorders. No gender differences were found for global functioning. The results generally did not change when corrected for possible cofounders (e.g. cannabis use). However, most differences did not withstand correction for multiple testing.Conclusions:Findings indicate that gender differences in symptomatology and comorbidity in ARMS are similar to those seen in overt psychosis and in healthy controls. However, observed differences are small and would only be reliably detected in studies with high statistical power. Moreover, such small effects would likely not be clinically meaningful.

The Australian National Survey of Psychotic Disorders: profile of psychosocial disability and its risk factors

2002 ◽  
Vol 32 (4) ◽  
pp. 639-647 ◽  
Author(s):  
O. GUREJE ◽  
H. HERRMAN ◽  
C. HARVEY ◽  
V. MORGAN ◽  
A. JABLENSKY
Keyword(s):  
Risk Factors ◽  
Social Adjustment ◽  
Urban Areas ◽  
Psychotic Disorders ◽  
Structured Interview ◽  
Service Planning ◽  
Response To Treatment ◽  
Epidemiological Surveys ◽  
Psychosocial Disability ◽  
The Impact

Background. Knowledge of the level of psychosocial impairment associated with psychosis is important in evaluating the impact of the illness on those affected. When such knowledge is derived from community-based epidemiological surveys, it can help in providing a public health perspective for service planning with information derived from representative samples of patients.Methods. A two-phase epidemiological survey of persons with psychosis in four predominantly urban areas of Australia. First phase screening for psychosis (N = 5710) was followed by a semi-structured interview of a stratified random sample (N = 980) to assess psychopathology (lifetime and current) and psychosocial disability.Results. Most of the interviewees were unemployed and had never married. There was widespread impairment in sexual and social relationships and in the performance of activities of daily living. Over half expressed dissatisfaction with life in general. Persons with affective psychoses were often as disabled as those with schizophrenia and diagnostic categorizations were not important in the conferment of risk for disability. Rather, poor pre-morbid work or social adjustment and poor course of illness were potent risk factors for diverse forms of disability in persons with psychosis.Conclusion. A large proportion of persons with experience of psychosis living in the community suffers from significant levels of psychosocial disability. Disablement seems to reflect, in part, a diathesis of poor pre-morbid functioning and less than optimal response to treatment of the disorder.

Relapse After First-Episode Psychosis: A 3-Year Follow-Up

2017 ◽  
Vol 41 (S1) ◽  
pp. S276-S276
Author(s):  
E. Pereira ◽  
M. Mota Oliveira ◽  
R. Guedes ◽  
M.J. Peixoto ◽  
I. Ferraz ◽  
...  
Keyword(s):  
Psychotic Disorders ◽  
Statistical Significance ◽  
First Episode Psychosis ◽  
Response To Treatment ◽  
First Episode ◽  
Final Sample ◽  
Episode Psychosis ◽  
Competing Interest ◽  
Relapse Rates

IntroductionRelapse after first-episode psychosis (FEP) is a frequent problem, which can lead to patients’ poorer functioning and response to treatment. Its prevention is one of the most important and challenging targets in the treatment of psychotic disorders.ObjectivesTo characterize and evaluate relapse rates after FEP, during the course of 3 years, of a group of patients admitted at a psychiatry department.MethodsA retrospective observational study was conducted. Patients with a FEP between ages 18 to 40, admitted at the Clinic of Psychiatry and Mental Health at São João Hospital Centre between January 1, 2007 and September 30, 2013. Only patients with, at least, 3 years of follow-up at the clinic were included.ResultsFinal sample of 58 patients, 39 of which were male (mean age = 26.4 years). Forty patients were excluded by not completing the 3 years follow-up at our department. The cumulative relapse rates were 32.8% at 12 months, 53.4% at 24 months and 63.8% at 36 months. Patients with at least one relapse were younger (25.78 years vs. 27.52 years) and had shorter periods of first hospitalization (19.25 days vs. 23.52 days). These data did not reach statistical significance. Non-adherence to prescribed medication was described in 73.0% (n = 27) of patients at the time of relapse. Eight of them (21.6%) presented with cannabis use.ConclusionsAlthough no statistical significance was reached, our findings are consistent with other studies. A future study with a bigger sample would be important in achieving statistical significant results.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals T21. DEVELOPMENT OF PROTEOMIC PREDICTION MODELS FOR OUTCOMES IN THE CLINICAL HIGH RISK STATE AND PSYCHOTIC EXPERIENCES IN ADOLESCENCE: MACHINE LEARNING ANALYSES IN TWO NESTED CASE-CONTROL STUDIES

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S238-S239
Author(s):  
David Mongan ◽  
Melanie Föcking ◽  
Colm Healy ◽  
Subash Raj Susai ◽  
Gerard Cagney ◽  
...  
Keyword(s):  
Body Mass Index ◽  
At Risk ◽  
Psychotic Disorders ◽  
Case Control ◽  
Plasma Samples ◽  
Clinical High Risk ◽  
Psychotic Experiences ◽  
Case Control Studies ◽  
False Discovery ◽  
Nested Case Control

Abstract Background Individuals at clinical high risk (CHR) of psychosis have an approximately 20% probability of developing psychosis within 2 years, as well as an associated risk of non-psychotic disorders and functional impairment. People with subclinical psychotic experiences (PEs) are also at risk of future psychotic and non-psychotic disorders and decreased functioning. It is difficult to accurately predict outcomes in individuals at risk of psychosis on the basis of symptoms alone. Biomarkers for accurate prediction of outcomes could inform the clinical management of this group. Methods We conducted two nested case-control studies. We employed discovery-based proteomic methods to analyse protein expression in baseline plasma samples in EU-GEI and age 12 plasma samples in ALSPAC using liquid chromatography mass spectrometry. Differential expression of quantified proteomic markers was determined by analyses of covariance (with false discovery rate of 5%) comparing expression levels for each marker between those who did not and did not develop psychosis in Study 1 (adjusting for age, gender, body mass index and years in education), and between those who did and did not develop PEs in Study 2 (adjusting for gender, body mass index and maternal social class). Support vector machine algorithms were used to develop models for prediction of transition vs. non-transition (as determined by the Comprehensive Assessment of At Risk Mental States) and poor vs. good functional outcome at 2 years in Study 1 (General Assessment of Functioning: Disability subscale score </=60 vs. >60). Similar algorithms were used to develop a model for prediction of PEs vs. no PEs at age 18 in Study 2 (as determined by the Psychosis Like Symptoms Interview). Results In Study 1, 35 of 166 quantified proteins were significantly differentially expressed between CHR participants who did and did not develop psychosis. Functional enrichment analysis provided evidence for particular implication of the complement and coagulation cascade (false discovery rate-adjusted Fisher’s exact test p=2.23E-21). Using 65 clinical and 166 proteomic features a model demonstrated excellent performance for prediction of transition status (area under the receiver-operating curve [AUC] 0.96, positive predictive value [PPV] 83.0%, negative predictive value [NPV] 93.8%). A model based on the ten most predictive proteins accurately predicted transition status in training (AUC 0.96, PPV 87.5%, NPV 95.8%) and withheld data (AUC 0.92, PPV 88.9%, NPV 91.4%). A model using the same 65 clinical and 166 proteomic features predicted 2-year functional outcome with AUC 0.72 (PPV 67.6%, NPV 47.6%). In Study 2, 5 of 265 quantified proteins were significantly differentially expressed between participants who did and did not report PEs at age 18. A model using 265 proteomic features predicted PEs at age 18 with AUC 0.76 (PPV 69.1%, NPV 74.2%). Discussion With external validation, models incorporating proteomic data may contribute to improved prediction of clinical outcomes in individuals at risk of psychosis.

Childhood trauma and functional disability in psychosis, bipolar disorder and borderline personality disorder: a review of the literature

2014 ◽  
Vol 32 (1) ◽  
pp. 21-30 ◽  
Author(s):  
J. Cotter ◽  
M. Kaess ◽  
A. R. Yung
Keyword(s):  
Bipolar Disorder ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Childhood Trauma ◽  
Psychotic Disorders ◽  
Functional Disability ◽  
Clinical Work ◽  
Borderline Personality ◽  
Response To Treatment ◽  
Neurocognitive Deficits

ObjectivesWe aimed to examine the association between childhood trauma and functional impairment in psychotic disorders, bipolar disorder and borderline personality disorder, to speculate on possible mechanisms that underlie this association and discuss the implications for clinical work.MethodsNarrative review of the peer-reviewed English language literature in the area.ResultsHigh rates of childhood trauma in psychotic disorders, bipolar disorder and borderline personality disorder were identified. This was associated with impaired social and occupational functioning in both the premorbid and established phases of each of these psychiatric disorders over and above the deficits typically observed in these populations. Possible mechanisms mediating this relationship include neurocognitive deficits, insecure attachment, higher rates of comorbidities and problems with adherence and response to treatment.ConclusionsRoutine clinical inquiry about childhood maltreatment should be adopted within mental health settings. This has potentially important treatment implications for identifying those individuals at elevated risk of functional disability. While there is no clear guidance currently available on how to target childhood trauma in the treatment of psychotic disorders, bipolar disorder or borderline personality disorder, there are several promising lines of enquiry and further research is warranted.

BDNF and S100B in psychotic disorders: evidence for an association with treatment responsiveness

2013 ◽  
Vol 26 (4) ◽  
pp. 223-229 ◽  
Author(s):  
Noortje W.A. van de Kerkhof ◽  
Durk Fekkes ◽  
Frank M.M.A. van der Heijden ◽  
Willem M.A. Verhoeven
Keyword(s):  
Negative Symptoms ◽  
Psychotic Disorders ◽  
Brain Plasticity ◽  
Control Sample ◽  
Serum Levels ◽  
Response To Treatment ◽  
Antipsychotic Treatment ◽  
Specific Symptom ◽  
Symptom Dimensions ◽  
Symptom Profile

ObjectiveBrain-derived neurotrophic factor (BDNF) and S100B are involved in brain plasticity processes and their serum levels have been demonstrated to be altered in patients with psychoses. This study aimed to identify subgroups of patients with psychotic disorders across diagnostic boundaries that show a specific symptom profile or response to treatment with antipsychotics, by measuring serum levels of BDNF and S100B.MethodsThe study sample consisted of 58 patients with DSM-IV psychotic disorders. Comprehensive Assessment of Symptoms and History (CASH), Positive and Negative Syndrome Scale (PANSS) and Clinical Global Impression scale for severity and improvement (CGI-S/CGI-I) were applied at baseline and after 6 weeks of antipsychotic treatment. At both time points, serum levels of BDNF and S100B were measured and compared with a matched control sample.ResultsBaseline BDNF and S100B levels were significantly lower in patients as compared with controls and did not change significantly during treatment. Dividing the patient sample according to baseline biochemical parameters (low and high 25% and middle 50%), no differences in symptom profiles or outcome were found with respect to BDNF. However, the subgroups with low and high S100B levels had higher PANSS scores than the middle subgroup. In addition, the high subgroup still showed significantly more negative symptoms after treatment, whereas the low subgroup showed more positive symptoms compared with the other subgroups.ConclusionSerum levels of BDNF and S100B are lowered in patients with psychotic disorders across diagnostic boundaries. The differences between high and low S100B subgroups suggest a relationship between S100B, symptom dimensions and treatment response, irrespective of diagnostic categories.

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