Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis.

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2C19/CYP2D6 genes play a role? A UK population-based study.

BACKGROUND: Dyslipidaemia is an important cardiovascular risk factor for people with severe mental illness, contributing to premature mortality. The link between antipsychotics and dyslipidaemia is well established, while evidence on antidepressants is mixed. AIMS: To investigate if antidepressant/antipsychotic use was associated with lipid parameters in UK Biobank participants and if CYP2C19 and CYP2D6 genetic variation plays a role. METHODS: Review of self-reported prescription medications identified participants taking antidepressants/antipsychotics. Total, low-, and high-density lipoprotein cholesterol (L/HDL-C) and triglycerides derived from blood samples. CYP2C19 and CYP2D6 metabolic phenotypes were assigned from genetic data. Linear regression investigated aims, adjusted for key covariates. RESULTS: Of 469,739 participants, 36,043 took antidepressants (53% female, median age 58, 17% taking cholesterol-lowering medications) and 3255 took antipsychotics (58% female, median age 57, 27% taking cholesterol-lowering medications). Significant associations were found between use of each amitriptyline, fluoxetine, citalopram/escitalopram, sertraline, paroxetine and venlafaxine with higher total cholesterol, LDL-C, and triglycerides and lower HDL-C, compared to participants not taking each medication. Venlafaxine was associated with the worst lipid profile (total cholesterol, adjusted mean difference: 0.21 mmol/L, 95% confidence interval (CI): 0.17 to 0.26, p < 0.001). Antipsychotic use was significantly associated with lower HDL-C and higher triglycerides. In participants taking sertraline, CYP2C19 intermediate metabolisers had higher HDL-C (0.05 mmol/L, 95% CI: 0.01 to 0.09, p = 0.007) and lower triglycerides (-0.17 mmol/L, 95% CI: -0.29 to -0.05, p = 0.007), compared to normal metabolisers. CONCLUSIONS: Antidepressants were significantly associated with adverse lipid profiles, potentially warranting baseline and regular monitoring. Further research should investigate the mechanistic pathways underlying the protective effects of the CYP2C19 intermediate metaboliser phenotype on HDL-C and triglycerides in people taking sertraline.

Study protocol of DIVERGE, the first genetic epidemiological study of major depressive disorder in Pakistan.

INTRODUCTION: Globally, 80% of the burdenof major depressive disorder (MDD) pertains to low- and middle-income countries. Research into genetic and environmental risk factors has the potential to uncover disease mechanisms that may contribute to better diagnosis and treatment of mental illness, yet has so far been largely limited to participants with European ancestry from high-income countries. The DIVERGE study was established to help overcome this gap and investigate genetic and environmental risk factors for MDD in Pakistan. METHODS: DIVERGE aims to enrol 9000 cases and 4000 controls in hospitals across the country. Here, we provide the rationale for DIVERGE, describe the study protocol and characterise the sample using data from the first 500 cases. Exploratory data analysis is performed to describe demographics, socioeconomic status, environmental risk factors, family history of mental illness and psychopathology. RESULTS AND DISCUSSION: Many participants had severe depression with 74% of patients who experienced multiple depressive episodes. It was a common practice to seek help for mental health struggles from faith healers and religious leaders. Socioeconomic variables reflected the local context with a large proportion of women not having access to any education and the majority of participants reporting no savings. CONCLUSION: DIVERGE is a carefully designed case-control study of MDD in Pakistan that captures diverse risk factors. As the largest genetic study in Pakistan, DIVERGE helps address the severe underrepresentation of people from South Asian countries in genetic as well as psychiatric research.

Neurophysiology in psychosis: The quest for disease biomarkers.

Psychotic disorders affect 3% of the population at some stage in life, are a leading cause of disability, and impose a great economic burden on society. Major breakthroughs in the genetics of psychosis have not yet been matched by an understanding of its neurobiology. Biomarkers of perception and cognition obtained through non-invasive neurophysiological tools, especially EEG, offer a unique opportunity to gain mechanistic insights. Techniques for measuring neurophysiological markers are inexpensive and ubiquitous, thus having the potential as an accessible tool for patient stratification towards early treatments leading to better outcomes. In this paper, we review the literature on neurophysiological markers for psychosis and their relevant disease mechanisms, mainly covering event-related potentials including P50/N100 sensory gating, mismatch negativity, and the N100 and P300 waveforms. While several neurophysiological deficits are well established in patients with psychosis, more research is needed to study neurophysiological markers in their unaffected relatives and individuals at clinical high risk. We need to harness EEG to investigate markers of disease risk as key steps to elucidate the aetiology of psychosis and facilitate earlier detection and treatment.

Adolescent Verbal Memory as a Psychosis Endophenotype: A Genome-Wide Association Study in an Ancestrally Diverse Sample.

Verbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum of 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study®, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis.

The Influence of CYP2D6 and CYP2C19 Genetic Variation on Diabetes Mellitus Risk in People Taking Antidepressants and Antipsychotics.

CYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects. We identified 31,579 individuals taking antidepressants and 2699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate, or normal metabolizers of CYP2D6, and as poor, intermediate, normal, rapid, or ultra-rapid metabolizers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. CYP2D6 poor metabolizers taking paroxetine had higher Hb1Ac than normal metabolizers (mean difference: 2.29 mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolizers had higher HbA1c levels compared to normal metabolizers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, CYP2D6 intermediate metabolizers and decreased HbA1c, compared to normal metabolizers (mean difference -7.74 mmol/mol; p = 0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication. Our results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.

Transcriptome-wide association study reveals two genes that influence mismatch negativity.

Mismatch negativity (MMN) is a differential electrophysiological response measuring cortical adaptability to unpredictable stimuli. MMN is consistently attenuated in patients with psychosis. However, the genetics of MMN are uncharted, limiting the validation of MMN as a psychosis endophenotype. Here, we perform a transcriptome-wide association study of 728 individuals, which reveals 2 genes (FAM89A and ENGASE) whose expression in cortical tissues is associated with MMN. Enrichment analyses of neurodevelopmental expression signatures show that genes associated with MMN tend to be overexpressed in the frontal cortex during prenatal development but are significantly downregulated in adulthood. Endophenotype ranking value calculations comparing MMN and three other candidate psychosis endophenotypes (lateral ventricular volume and two auditory-verbal learning measures) find MMN to be considerably superior. These results yield promising insights into sensory processing in the cortex and endorse the notion of MMN as a psychosis endophenotype.

CYP2D6 Genetic Variation and Antipsychotic-Induced Weight Gain: A Systematic Review and Meta-Analysis.

BACKGROUND: Antipsychotic-induced weight gain is a contributing factor in the reduced life expectancy reported amongst people with psychotic disorders. CYP2D6 is a liver enzyme involved in the metabolism of many commonly used antipsychotic medications. We investigated if CYP2D6 genetic variation influenced weight or BMI among people taking antipsychotic treatment. METHODS: We conducted a systematic review and a random effects meta-analysis of publications in Pubmed, Embase, PsychInfo, and CENTRAAL that had BMI and/or weight measurements of patients on long-term antipsychotics by their CYP2D6-defined metabolic groups (poor, intermediate, normal/extensive, and ultra-rapid metabolizers, UMs). RESULTS: Twelve studies were included in the systematic review. All cohort studies suggested that the presence of reduced-function or non-functional alleles for CYP2D6 was associated with greater antipsychotic-induced weight gain, whereas most cross-sectional studies did not find any significant associations. Seventeen studies were included in the meta-analysis with clinical data of 2,041 patients, including 93 poor metabolizers (PMs), 633 intermediate metabolizers (IMs), 1,272 normal metabolizers (NMs), and 30 UMs. Overall, we did not find associations in any of the comparisons made. The estimated pooled standardized differences for the following comparisons were (i) PM versus NM; weight = -0.07 (95%CI: -0.49 to 0.35, p = 0.74), BMI = 0.40 (95%CI: -0.19 to 0.99, p = 0.19). (ii) IM versus NM; weight = 0.09 (95% CI: -0.04 to 0.22, p = 0.16) and BMI = 0.09 (95% CI: -0.24 to 0.41, p = 0.60). (iii) UM versus EM; weight = 0.01 (95% CI: -0.37 to 0.40, p = 0.94) and BMI = -0.08 (95%CI: -0.57 to 0.42, p = 0.77). CONCLUSION: Our systematic review of cohort studies suggested that CYP2D6 poor metabolizers have higher BMI than normal metabolizers, but the data of cross-sectional studies and the meta-analysis did not show this association. Although our review and meta-analysis constitutes one of the largest studies with comprehensively genotyped samples, the literature is still limited by small numbers of participants with genetic variants resulting in poor or UMs status. We need further studies with larger numbers of extreme metabolizers to establish its clinical utility in antipsychotic treatment. CYP2D6 is a key gene for personalized prescribing in mental health.

The effect of CYP2D6 variation on antipsychotic-induced hyperprolactinaemia: a systematic review and meta-analysis.

Hyperprolactinemia is a known adverse drug reaction to antipsychotic treatment. Antipsychotic blood levels are influenced by cytochrome P450 enzymes, primarily CYP2D6. Variation in CYP450 genes may affect the risk of antipsychotic-induced hyperprolactinemia. We undertook a systematic review and meta-analysis to assess whether CYP2D6 functional genetic variants are associated with antipsychotic-induced hyperprolactinemia. The systematic review identified 16 relevant papers, seven of which were suitable for the meta-analysis (n = 303 participants including 134 extreme metabolisers). Participants were classified into four phenotype groups as poor, intermediate, extensive, and ultra-rapid metabolisers. A random effects meta-analysis was used and Cohen's d calculated as the effect size for each primary study. We found no significant differences in prolactin levels between CYP2D6 metabolic groups. Current evidence does not support using CYP2D6 genotyping to reduce risk of antipsychotic-induced hyperprolactinemia. However, statistical power is limited. Future studies with larger samples and including a range of prolactin-elevating drugs are needed.

Endophenotypes of executive functions in obsessive compulsive disorder? A meta-analysis in unaffected relatives.

Endophenotypes are mediator traits between genetic influences and clinical phenotypes. Meta-analyses have consistently shown modest impairments of executive functioning in obsessive compulsive disorder (OCD) patients compared to healthy controls. Similar deficits have also been reported in unaffected relatives of OCD patients, but have not been quantified. We conducted the first meta-analysis combining all studies investigating executive functioning in unaffected relatives of individuals with OCD to quantify any deficits. A search of Pubmed, Medline and PsychInfo databases identified 21 suitable papers comprising 707 unaffected relatives of OCD patients and 842 healthy controls. Effect sizes were calculated using random effects models. Unaffected relatives displayed a significant impairment in global executive functioning. Analyses of specific executive functioning subdomains revealed impairments in: planning, visuospatial working memory and verbal fluency. Deficits in executive functioning are promising endophenotypes for OCD. To identify further biomarkers of disease risk/resilience in OCD, we suggest examining specific executive functioning domains.

Use of schizophrenia and bipolar disorder polygenic risk scores to identify psychotic disorders.

BACKGROUND: There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.AimsTo investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls. METHOD: Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls. RESULTS: Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest. CONCLUSIONS: Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.Declaration of interestR.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.