The Progress and Pitfalls of Pharmacogenetics-Based Precision Medicine in Schizophrenia Spectrum Disorders:A Systematic Review and Meta-Analysis

The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010–2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of CYP2D9, and 3 of CYP2C19. We observed weak unadjusted nominal significant (p &lt; 0.05) additive effects of PGx variants of DRD1, DRD2, DRD3, HTR1A, HTR2A, HTR3A, and COMT (10 variants) on antipsychotic response; DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25 (14 variants) on weight gain; HTR2C (one variant) on metabolic syndrome; DRD2 (one variant) on prolactin levels; COMT and BDNF (two variants) on TD; HLA-DRB1 (one variant) on CLA; CYP2D6 (four phenotypes) and CYP2C19 (two phenotypes) on antipsychotics plasma levels. In the future, well-designed longitudinal naturalistic multi-center PGx studies are needed to validate the effectiveness of PGx variants in antipsychotic outcomes before establishing any reproducible PGx passport in clinical practice.</p

Abnormal connectivity between attentional, language and auditory networks in schizophrenia

Brain circuits involved in language processing have been suggested to be compromised in patients with schizophrenia. This does not only include regions subserving language production and perception, but also auditory processing and attention. We investigated resting state network connectivity of auditory, language and attention networks of patients with schizophrenia and hypothesized that patients would show reduced connectivity. Patients with schizophrenia (n=45) and healthy controls (n=30) underwent a resting state fMRI scan. Independent components analysis was used to identify networks of the auditory cortex, left inferior frontal language regions and the anterior cingulate region, associated with attention. The time courses of the components where correlated with each other, the correlations were transformed by a Fisher's Z transformation, and compared between groups. In patients with schizophrenia, we observed decreased connectivity between the auditory and language networks. Conversely, patients showed increased connectivity between the attention and language network compared to controls. There was no relationship with severity of symptoms such as auditory hallucinations. The decreased connectivity between auditory and language processing areas observed in schizophrenia patients is consistent with earlier research and may underlie language processing difficulties. Altered anterior cingulate connectivity in patients may be a correlate of habitual suppression of unintended speech, or of excessive attention to internally generated speech. This altered connectivity pattern appears to be present independent of symptom severity, and may be suggestive of a trait, rather than a state characteristic. (C) 2011 Elsevier B.V. All rights reserved

Polygenic risk score for schizophrenia was not associated with glycemic level (HbA1c) in patients with non-affective psychosis:Genetic Risk and Outcome of Psychosis (GROUP) cohort study

Introduction: Type 2 diabetes (T2D) is a common comorbidity in patients with schizophrenia (SCZ). The underlying pathophysiologic mechanisms are yet to be fully elucidated, although it can be argued that shared genes, environmental factors or their interaction effect are involved. This study investigated the association between polygenic risk score of SCZ (PRSSCZ) and glycated haemoglobin (HbA1c) while adjusting for polygenic risk score of T2D (PRST2D), and clinical and demographic covariables. Methods: Genotype, clinical and demographic data of 1129 patients with non-affective psychosis were extracted from Genetic Risk and Outcome of Psychosis (GROUP) cohort study. The glycated haemoglobin (HbA1c) was the outcome. PRS was calculated using standard methods. Univariable and multivariable linear regression analyses were applied to estimate associations. Additionally, sensitivity analysis based on multiple imputation was done. After correction for multiple testing, a two-sided p-value ≤.003 was considered to discover evidence for an association. Results: Of 1129 patients, 75.8% were male with median age of 29 years. The mean (standard deviation) HbA1c level was 35.1 (5.9) mmol/mol. There was no evidence for an association between high HbA1c level and increased PRSSCZ (adjusted regression coefficient (aβ) = 0.69, standard error (SE) = 0.77, p-value =.37). On the other hand, there was evidence for an association between high HbA1c level and increased PRST2D (aβ = 0.93, SE = 0.32, p-value =.004), body mass index (aβ = 0.20, SE = 0.08, p-value =.01), diastolic blood pressure (aβ = 0.08, SE = 0.04, p-value =.03), late age of first psychosis onset (aβ = 0.19, SE = 0.05, p-value =.0004) and male gender (aβ = 1.58, SE = 0.81, p-value =.05). After multiple testing correction, there was evidence for an association between high HbA1c level and late age of first psychosis onset. Evidence for interaction effect between PRSscz and antipsychotics was not observed. The multiple imputation-based sensitivity analysis provided consistent results with complete case analysis. Conclusions: Glycemic dysregulation in patients with SCZ was not associated with PRSSCZ. This suggests that the mechanisms of hyperglycemia or diabetes are at least partly independent from genetic predisposition to SCZ. Our findings show that the change in HbA1c level can be caused by at least in part due to PRST2D, late age of illness onset, male gender, and increased body mass index and diastolic blood pressure

Interrelationships between depressive symptoms and positive and negative symptoms of recent onset schizophrenia spectrum disorders:A network analytical approach

Objective: There is a need to better understand the interrelationships between positive and negative symptoms of recent-onset schizophrenia spectrum disorders (SSD) and co-occurring depressive symptoms. Aims were to determine: (1) whether depressive symptoms are best conceptualised as distinct from, or intrinsic to, positive and negative symptoms; and (2) bridging symptoms. Methods: Network analysis was applied to data from 198 individuals with depressive and psychotic symptoms in SSD from the Psychosis Recent Onset GRoningen Survey (PROGR-S). Measures were: Montgomery-Asberg Depression Rating Scale and Positive and Negative Syndrome Scale. Results: Positive symptoms were just as likely to be associated with depressive and negative symptoms, and had more strong associations with depressive than negative symptoms. Negative symptoms were more likely to be associated with depressive than positive symptoms, and had more strong associations with depressive than positive symptoms. Suspiciousness and stereotyped thinking bridged between positive and depressive symptoms, and apparent sadness and lassitude between negative and depressive symptoms. Conclusions: Depressive symptoms might be best conceptualised as intrinsic to positive and negative symptoms pertaining to deficits in motivation and interest in the psychotic phase of SSD. Treatments targeting bridges between depressive and positive symptoms, and depressive and such negative symptoms, might prevent or improve co-occurring depressive symptoms, or vice-versa, in the psychotic phase of SSD

The development and evaluation of a computerized decision aid for the treatment of psychotic disorders

Abstract Background Routinely monitoring of symptoms and medical needs can improve the diagnostics and treatment of medical problems, including psychiatric. However, several studies show that few clinicians use Routine Outcome Monitoring (ROM) in their daily work. We describe the development and first evaluation of a ROM based computerized clinical decision aid, Treatment-E-Assist (TREAT) for the treatment of psychotic disorders. The goal is to generate personalized treatment recommendations, based on international guidelines combined with outcomes of mental and physical health acquired through ROM. We present a pilot study aimed to assess the feasibility of this computerized clinical decision aid in daily clinical practice by evaluating clinicians’ experiences with the system. Methods Clinical decision algorithms were developed based on international schizophrenia treatment guidelines and the input of multidisciplinary expert panels from multiple psychiatric institutes. Yearly obtained diagnostic (ROM) information of patients was presented to treating clinicians combined with treatment suggestions generated by the algorithms of TREAT. In this pilot study 6 clinicians and 16 patients of Lentis Psychiatric Institute used the application. Clinicians were interviewed and asked to fill out self-report questionnaires evaluating their opinions about ROM and the effectiveness of TREAT. Results Six clinicians and 16 patients with psychotic disorders participated in the pilot study. The clinicians were psychiatrists, physicians and nurse-practitioners which all worked at least 8 years in mental health care of which at least 3 years treating patients with psychotic illnesses. All Clinicians found TREAT easy to use and would like to continue using the application. They reported that TREAT offered support in using diagnostic ROM information when drafting the treatment plans, by creating more awareness of current treatment options. Conclusion This article presents a pilot study on the implementation of a computerized clinical decision aid linking routine outcome monitoring to clinical guidelines in order to generate personalized treatment advice. TREAT was found to be feasible for daily clinical practice and effective based on this first evaluation by clinicians. However, adjustments have to be made to the system and algorithms of the application. The ultimate goal is to provide appropriate evidence based care for patients with severe mental illnesses

A systematic review and narrative synthesis of data-driven studies in schizophrenia symptoms and cognitive deficits

To tackle the phenotypic heterogeneity of schizophrenia, data-driven methods are often applied to identify subtypes of its symptoms and cognitive deficits. However, a systematic review on this topic is lacking. The objective of this review was to summarize the evidence obtained from longitudinal and cross-sectional data-driven studies in positive and negative symptoms and cognitive deficits in patients with schizophrenia spectrum disorders, their unaffected siblings and healthy controls or individuals from general population. Additionally, we aimed to highlight methodological gaps across studies and point out future directions to optimize the translatability of evidence from data-driven studies. A systematic review was performed through searching PsycINFO, PubMed, PsycTESTS, PsycARTICLES, SCOPUS, EMBASE and Web of Science electronic databases. Both longitudinal and cross-sectional studies published from 2008 to 2019, which reported at least two statistically derived clusters or trajectories were included. Two reviewers independently screened and extracted the data. In this review, 53 studies (19 longitudinal and 34 cross-sectional) that conducted among 17,822 patients, 8729 unaffected siblings and 5520 controls or general population were included. Most longitudinal studies found four trajectories that characterized by stability, progressive deterioration, relapsing and progressive amelioration of symptoms and cognitive function. Cross-sectional studies commonly identified three clusters with low, intermediate (mixed) and high psychotic symptoms and cognitive profiles. Moreover, identified subgroups were predicted by numerous genetic, sociodemographic and clinical factors. Our findings indicate that schizophrenia symptoms and cognitive deficits are heterogeneous, although methodological limitations across studies are observed. Identified clusters and trajectories along with their predictors may be used to base the implementation of personalized treatment and develop a risk prediction model for high-risk individuals with prodromal symptoms

Graph Analysis of Functional Brain Networks in Patients with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is one of the most common neurological disorders worldwide. Posttraumatic complaints are frequently reported, interfering with outcome. However, a consistent neural substrate has not yet been found. We used graph analysis to further unravel the complex interactions between functional brain networks, complaints, anxiety and depression in the sub-acute stage after mTBI. This study included 54 patients with uncomplicated mTBI and 20 matched healthy controls. Posttraumatic complaints, anxiety and depression were measured at two weeks post-injury. Patients were selected based on presence (n = 34) or absence (n = 20) of complaints. Resting-state fMRI scans were made approximately four weeks post-injury. High order independent component analysis resulted in 89 neural components that were included in subsequent graph analyses. No differences in graph measures were found between patients with mTBI and healthy controls. Regarding the two patient subgroups, degree, strength, local efficiency and eigenvector centrality of the bilateral posterior cingulate/precuneus and bilateral parahippocampal gyrus were higher, and eigenvector centrality of the frontal pole/bilateral middle & superior frontal gyrus was lower in patients with complaints compared to patients without complaints. In patients with mTBI, higher degree, strength and eigenvector centrality of default mode network components were related to higher depression scores, and higher degree and eigenvector centrality of executive network components were related to lower depression scores. In patients without complaints, one extra module was found compared to patients with complaints and healthy controls, consisting of the cingulate areas. In conclusion, this research extends the knowledge of functional network connectivity after mTBI. Specifically, our results suggest that an imbalance in the function of the default mode-and executive network plays a central role in the interaction between emotion regulation and the persistence of posttraumatic complaints

Intrinsic mesocorticolimbic connectivity is negatively associated with social amotivation in people with schizophrenia

Background: Social amotivation is a core element of the negative symptoms of schizophrenia. However, it is still largely unknown which neural substrates underpin social amotivation in people with schizophrenia, though deficiencies in the mesocorticolimbic dopamine system have been proposed. Methods: We examined the association between social amotivation and substantia nigra/ventral tegmental area-seeded intrinsic connectivity in 84 people with schizophrenia using resting state functional magnetic resonance imaging. Results: Spontaneous fluctuations of midbrain dopaminergic regions were positively associated with striatal and prefrontal fluctuations in people with schizophrenia. Most importantly, social amotivation was negatively associated with functional connectivity between the midbrain's substantia nigra/ventral tegmental area and medial-and lateral prefrontal cortex, the temporoparietal junction, and dorsal and ventral striatum. These associations were observed independently of depressive and positive symptoms. Conclusions: Our findings suggest that social amotivation in people with schizophrenia is associated with altered intrinsic connectivity of mesocorticolimbic pathways linked to cognitive control and reward processing. Dysconnectivity of dopaminergic neuronal ensembles that are fundamental to approach behavior and motivation may help explain the lack of initiative social behavior in people with social amotivation. (C) 2019 Elsevier B.V. All rights reserved

Understanding the relationship between apathy, cognition and functional outcome in schizophrenia: The significance of an ecological assessment

In recent years there has been an increasing interest in understanding the role apathy plays in mediating the relationship between cognitive impairment and functional outcome. In general, most studies measure cognition with traditional cognitive tests that give explicit instructions and guide the participants toward generating a response. However, given that apathy is defined by a decrease in self-initiated behavior, it is crucial to evaluate cognition with ecological tasks that do not explicitly direct the patient´s motivation to generate behaviors to assess the actual effect. This study investigated whether an ecological cognitive assessment (the Jansari Executive Function Assessment, JEF©) would uniquely contribute to the relationship between cognition, apathy, and functional outcome in schizophrenia. The Apathy Evaluation Scale (AES), neuropsychological tests and the JEF© were administered to 20 patients with schizophrenia. Hierarchical multiple regression and mediation analysis were performed to test the associations between the variables of interest. Results showed that JEF© explained a significant portion of the variance in AES (25%). In addition, apathy explained 36% of the variance in functional outcome. However, AES did not mediate between cognition and functional outcome. Our results highlight the importance of assessing cognition with tasks that require integration of cognitive functions needed for real life demands