Search

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Schizophrenia (SCZ) is caused by an interplay of polygenic risk and environmental factors, which may alter regulators of gene expression leading to pathogenic misexpression of SCZ risk genes. The CPEB family of RNA-binding proteins (CPEB1-4) regulates translation of target RNAs (approximately 40% of overall genes). We previously identified CPEB4 as a key dysregulated translational regulator in autism spectrum disorder (ASD) because its neuronal-specific microexon (exon 4) is mis-spliced in ASD brains, causing underexpression of numerous ASD risk genes. The genetic factors and pathogenic mechanisms shared between SCZ and ASD led us to hypothesize CPEB4 mis-splicing in SCZ leading to underexpression of multiple SCZ-related genes., Methods: We performed MAGMA-enrichment analysis on Psychiatric Genomics Consortium genome-wide association study data and analyzed RNA sequencing data from the PsychENCODE Consortium. Reverse transcriptase polymerase chain reaction and Western blot were performed on postmortem brain tissue, and the presence/absence of antipsychotics was assessed through toxicological analysis. Finally, mice with mild overexpression of exon 4-lacking CPEB4 (CPEB4Δ4) were generated and analyzed biochemically and behaviorally., Results: First, we found enrichment of SCZ-associated genes for CPEB4-binder transcripts. We also found decreased usage of CPEB4 microexon in SCZ probands, which was correlated with decreased protein levels of CPEB4-target SCZ-associated genes only in antipsychotic-free individuals. Interestingly, differentially expressed genes fit those reported for SCZ, specifically in the SCZ probands with decreased CPEB4-microexon inclusion. Finally, we demonstrated that mice with mild overexpression of CPEB4Δ4 showed decreased protein levels of CPEB4-target SCZ genes and SCZ-linked behaviors., Conclusions: We identified aberrant CPEB4 splicing and downstream misexpression of SCZ risk genes as a novel etiological mechanism in SCZ., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework., Methods: We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high., Results: After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006)., Conclusions: The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders., Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors., Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged., Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., (Copyright © 2021 Society of Biological Psychiatry. All rights reserved.)

Background: Recent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant., Methods: We aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used postmortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple prenatal and postnatal time points, with summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder, and major depressive disorder. We prioritized gene sets for overall enrichment of association with each disorder and then tested the relationship between the association of their constituent genes with their relative expression at each developmental stage., Results: We observed relationships between the expression of genes involved in voltage-gated cation channel activity during early midfetal, adolescence, and early adulthood time points and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during early midfetal development and higher expression during adolescence and early adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, while for bipolar disorder, the relationship was distributed between calcium and potassium channel activity genes., Conclusions: Our results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk for psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Cognitive impairment in schizophrenia is a major contributor to poor outcomes, yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and affect cognition in healthy populations, but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia., Methods: General cognitive ability was measured using the Measurement and Treatment Research to Improve Cognition in Schizophrenia composite z score in 875 patients with schizophrenia and in a replication sample of 519 patients with schizophrenia using Wechsler Adult Intelligence Scale Full Scale IQ. Using linear regression, we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia-enriched gene sets (loss-of-function intolerant and synaptic gene sets) were associated with cognitive impairment., Results: A total of 23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than nonschizophrenia CNV carriers in discovery (β = -0.66, 95% confidence interval [CI] = -1.31 to -0.01) and replication samples (β = -0.91, 95% CI = -1.71 to -0.11) and after meta-analysis (β = -0.76, 95% CI = -1.26 to -0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (β = -0.15, 95% CI = -0.29 to -0.001, p = .048)., Conclusions: In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5-1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss-of-function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs., (Copyright © 2021. Published by Elsevier Inc.)

Background: Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms., Methods: We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios., Results: While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10 -4 ) and NMDAR (p = 1.7 × 10 -5 ) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10 -4 )., Conclusions: In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: The UK Biobank is a unique resource for biomedical research, with extensive phenotypic and genetic data on half a million adults from the general population. We aimed to examine the effect of neurodevelopmental copy number variants (CNVs) on the cognitive performance of participants., Methods: We used Affymetrix Power Tools and PennCNV-Affy software to analyze Affymetrix microarrays of the first 152,728 genotyped individuals. We annotated a list of 93 CNVs and compared their frequencies with control datasets. We analyzed the performance on seven cognitive tests of carriers of 12 CNVs associated with schizophrenia (n = 1087) and of carriers of another 41 neurodevelopmental CNVs (n = 484)., Results: The frequencies of the 93 CNVs in the Biobank subjects were remarkably similar to those among 26,628 control subjects from other datasets. Carriers of schizophrenia-associated CNVs and of the group of 41 other neurodevelopmental CNVs had impaired performance on the cognitive tests, with nine of 14 comparisons remaining statistically significant after correction for multiple testing. They also had lower educational and occupational attainment (p values between 10 -7 and 10 -18 ). The deficits in cognitive performance were modest (Z score reductions between 0.01 and 0.51), compared with individuals with schizophrenia in the Biobank (Z score reductions between 0.35 and 0.90)., Conclusions: This is the largest study on the cognitive phenotypes of CNVs to date. Adult carriers of neurodevelopmental CNVs from the general population have significant cognitive deficits. The UK Biobank will allow unprecedented opportunities for analysis of further phenotypic consequences of CNVs., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)