The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review

Understanding polygenic models, their development and the potential application of polygenic scores in healthcare

The use of genomic information to better understand and prevent common complex diseases has been an ongoing goal of genetic research. Over the past few years, research in this area has proliferated with several proposed methods of generating polygenic scores. This has been driven by the availability of larger data sets, primarily from genome-wide association studies and concomitant developments in statistical methodologies. Here we provide an overview of the methodological aspects of polygenic model construction. In addition, we consider the state of the field and implications for potential applications of polygenic scores for risk estimation within healthcare.

Update on the genetic architecture of schizophrenia

A long-established hypothesis is that schizophrenia has a strong genetic component. In the early 1990s, the first genetic variant that substantially increases risk for psychosis was identified. Since this initial reporting of deletions in the chromosomal region 22q11.2, nearly two decades passed until substantial insights into schizophrenia’s genetic architecture were gained. Schizophrenia is a polygenic disorder and genetic risk is conferred by both common and rare alleles distributed across the genome. A small number of rare, deleterious copy number variants (CNVs) are associated with moderate to substantial increases in individual risk to schizophrenia. These deletions and duplications are also associated with a range of neurodevelopmental disorders. The diagnostic investigation of CNVs in patients with schizophrenia is likely to represent one of the first examples of genetic testing in clinical psychiatry. The prerequisites for this are currently being defined.

Derivation of poly-methylomic profile scores for schizophrenia

Schizophrenia and bipolar disorder share biological features and environmental risk factors that may be associated with altered DNA methylation. In this study we sought to: 1) construct a novel 'Poly-Methylomic Profile Score (PMPS)' by transforming schizophrenia-associated epigenome-wide methylation from a previously published epigenome-wide association study (EWAS) into a single quantitative metric; and 2) examine associations between the PMPS and clinical status in an independent sample of 57 schizophrenia (SZ) cases, 59 bipolar disorder (BD) cases and 55 healthy controls (HC) for whom blood-derived DNA methylation was quantified using the Illumina 450 K methylation beadchip. We constructed five PMPSs at different p-value thresholds by summing methylation beta-values weighted by individual-CpG effect sizes from the meta-analysis of a previously published schizophrenia EWAS (comprising three separate cohorts with 675 [353 SZ and 322 HC] discovery cohort participants, 847 [414 SZ and 433 HC] replication cohort participants, and 96 monozygotic twin-pairs discordant for SZ). All SZ PMPSs were elevated in SZ participants relative to HCs, with the score calculated at a p-value threshold of 1 × 10^-5 accounting for the greatest amount of variance. All PMPSs were elevated in SZ relative to BD and none of the PMPSs were increased in BD, or in a combined cohort of BD and SZ cases, relative to HCs. PMPSs were also not associated with positive or negative symptom severity. That this SZ-derived PMPSs was elevated in SZ, but not BD, suggests that epigenome-wide methylation patterns may represent distinct pathophysiology that is yet to be elucidated.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

Polygenic liability for schizophrenia and childhood adversity influences daily-life emotion dysregulation and psychosis proneness

OBJECTIVE

To test whether polygenic risk score for schizophrenia (PRS-S) interacts with childhood adversity and daily-life stressors to influence momentary mental state domains (negative affect, positive affect, and subtle psychosis expression) and stress-sensitivity measures.

METHODS

The data were retrieved from a general population twin cohort including 593 adolescents and young adults. Childhood adversity was assessed using the Childhood Trauma Questionnaire. Daily-life stressors and momentary mental state domains were measured using ecological momentary assessment. PRS-S was trained on the latest Psychiatric Genetics Consortium schizophrenia meta-analysis. The analyses were conducted using multilevel mixed-effects tobit regression models.

RESULTS

Both childhood adversity and daily-life stressors were associated with increased negative affect, decreased positive affect, and increased subtle psychosis expression, while PRS-S was only associated with increased positive affect. No gene-environment correlation was detected. There is novel evidence for interaction effects between PRS-S and childhood adversity to influence momentary mental states [negative affect (b = 0.07, P = 0.013), positive affect (b = -0.05, P = 0.043), and subtle psychosis expression (b = 0.11, P = 0.007)] and stress-sensitivity measures.

CONCLUSION

Exposure to childhood adversities, particularly in individuals with high PRS-S, is pleiotropically associated with emotion dysregulation and psychosis proneness.

Associations between schizophrenia polygenic risk and apathy in schizophrenia spectrum disorders and healthy controls

OBJECTIVE

Apathy is a central predictor of a poor functional outcome in schizophrenia. Schizophrenia polygenic risk scores (PRSs) are used to detect genetic associations to key clinical phenotypes in schizophrenia. We explored the associations between schizophrenia PRS and apathy levels in schizophrenia spectrum disorders (n = 281) and matched healthy controls (n = 298), and further how schizophrenia PRS contributed in predicting apathy when added to premorbid and clinical factors in the patient sample.

METHOD

Schizophrenia PRSs were computed for each participant. Apathy was assessed with the Apathy Evaluation Scale. Bivariate correlation analyses were used to investigate associations between schizophrenia PRS and apathy, and between apathy and premorbid and clinical factors. Multiple hierarchical regression analyses were employed to evaluate the contributions of clinical variables and schizophrenia PRS to apathy levels.

RESULTS

We found no significant associations between schizophrenia PRS and apathy in patients and healthy controls. Several premorbid and clinical characteristics significantly predicted apathy in patients, but schizophrenia PRS did not.

CONCLUSION

Since the PRSs are based on common genetic variants, our results do not preclude associations to other types of genetic factors. The results could also indicate that environmentally based biological or psychological factors contribute to apathy levels in schizophrenia.

Profiling haplotype specific CpG and CpH methylation within a schizophrenia GWAS locus on chromosome 14 in schizophrenia and healthy subjects

Interrogating DNA methylation within schizophrenia risk loci holds promise to identify mechanisms by which genes influence the disease. Based on the hypothesis that allele specific methylation (ASM) of a single CpG, or perhaps CpH, might mediate or mark the effects of genetic variants on disease risk and phenotypes, we explored haplotype specific methylation levels of individual cytosines within a genomic region harbouring the BAG5, APOPT1 and KLC1 genes in peripheral blood of schizophrenia patients and healthy controls. Three DNA fragments located in promoter, intronic and intergenic areas were studied by single-molecule real-time bisulfite sequencing enabling the analysis of long reads of DNA with base-pair resolution and the determination of haplotypes directly from sequencing data. Among 1,012 cytosines studied, we did not find any site where methylation correlated with the disease or cognitive deficits after correction for multiple testing. At the same time, we determined the methylation profile associated with the schizophrenia risk haplotype within the KLC1 fourth intron and confirmed ASM for cytosines located in the vicinity of rs67899457. These genetically associated DNA methylation variations may be related to the pathophysiological mechanism differentiating the risk and non-risk haplotypes and merit further investigation.

Genome-wide association studies in schizophrenia: Recent advances, challenges and future perspective

Genome-wide association studies (GWAS) have proved to be a powerful approach for gene discovery in schizophrenia; their findings have important implications not just for our understanding of the genetic architecture of the disorder, but for the potential applications of personalised medicine through improved classification and targeted interventions. In this article we review the current status of the GWAS literature in schizophrenia including functional annotation methods and polygenic risk scoring, as well as the directions and challenges of future research. We consider recent findings in East Asian populations and the advancements from trans-ancestry analysis, as well as the insights gained from research looking across psychiatric disorders.

Characteristics of youth with reported family history of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort

Little is known about the impact of family history of psychosis on youth from community samples. To fill this gap, we compared youth with a first-degree relative with psychosis spectrum symptoms (i.e. family history of psychosis spectrum symptoms, FHPS) to youth without FHPS in a cross-sectional analysis of the Philadelphia Neurodevelopmental Cohort (PNC). The PNC is a racially diverse community sample of 9498 youth ages 8-21 years old, of whom 8928 completed the Family Interview for Genetic Studies to determine FHPS status. Polygenic risk score for schizophrenia (PRSS) was available for a subsample of 4433 European Americans. FHPS youth (n = 489) constituted 5.5% of the analytic sample. After adjusting for environmental risk factors (sociodemographic variables and traumatic stressful events), FHPS youth had lower functioning on the Children's Global Assessment Scale and elevated psychosis spectrum, mood, externalizing, and fear symptoms compared to non-FHPS youth (all p < .001). In the European-American subsample, FHPS status was associated with poorer functioning and greater symptom burden in all four psychopathology domains (all p < .001), even after covarying for PRSS. Thus, ascertaining FHPS is important because it is uniquely associated with symptoms and functional impairment in community youth beyond PRS-S and the environmental risk factors we investigated. Future research identifying environmental causes of FHPS-associated impairment could inform the development of interventions for the broad array of symptoms observed in FHPS youth.

[Brain imaging in schizophrenia : A review of current trends and developments]

Imaging methods have become the main approach for identifying dysfunctional neuronal networks in schizophrenia. This review article presents recent results of disorders of neuronal networks at structural and functional levels and summarizes the current developments. Large multicenter analyses have further established patterns of regional brain alterations, while novel methods in magnetic resonance (MR) morphometry have contributed to differentiating early from delayed brain structural changes. The use of machine learning approaches has not only enabled the establishment of classification models using biological data for future differential diagnostic use, it has also facilitated multivariate models for outcome prediction following therapeutic interventions. Novel methods, such as BrainAGE, a surrogate marker of accelerated brain aging processes, have added to longitudinal studies to gain insights into the brain structural dynamics from early brain developmental alterations to progressive structural brain changes after disease onset.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

Looking at Intergenerational Risk Factors in Schizophrenia Spectrum Disorders: New Frontiers for Early Vulnerability Identification?

Offspring of individuals with serious mental illness (SMI) constitute a special population with a higher risk of developing psychiatric disorders, which is also highly prevalent among referrals to child and adolescent mental health services (CAMHS). They often exhibit more or less subclinical conditions of vulnerability, fueled by mutually potentiating combinations of risk factors, such as presumed genetic risk, poor or inadequate affective and cognitive parenting, and low socio-economic status. Despite this evidence, neither specific preventive programs for offspring of parents with SMI are usually implemented in CAMHS, nor dedicated supportive programs for parenting are generally available in adult mental health services (AMHS). Needless to say, while both service systems tend to focus on individual recovery and clinical management (rather than on the whole family system), these blind spots add up to frequent gaps in communication and continuity of care between CAMHS and AMHS. This is particularly problematic in an age-range in which an offspring's vulnerabilities encounter the highest epidemiological peak of incident risk of SMI. This paper offers a clinical-conceptual perspective aimed to disentangle the complex intertwine of intergenerational risk factors that contribute to the risk of developing SMI in offspring, taking schizophrenia spectrum disorders as a paradigmatic example.

Maternal environmental risk factors and the development of internalizing and externalizing problems in childhood: The complex role of genetic factors

The development of problem behavior in children is associated with exposure to environmental factors, including the maternal environment. Both are influenced by genetic factors, which may also be correlated, that is, environmental risk and problem behavior in children might be influenced by partly the same genetic factors. In addition, environmental and genetic factors could interact with each other increasing the risk of problem behavior in children. To date, limited research investigated these mechanisms in a genome-wide approach. Therefore, the goal of this study was to investigate the association between genetic risk for psychiatric and related traits, as indicated by polygenetic risk scores (PRSs), exposure to previously identified maternal risk factors, and problem behavior in a sample of 1,154 children from the Amsterdam Born Children and their Development study at ages 5-6 and 11-12 years old. The PRSs were derived from genome-wide association studies (GWASs) on schizophrenia, major depressive disorder, neuroticism, and wellbeing. Regression analysis showed that the PRSs were associated with exposure to multiple environmental risk factors, suggesting passive gene-environment correlation. In addition, the PRS based on the schizophrenia GWAS was associated with externalizing behavior problems in children at age 5-6. We did not find any association with problem behavior for the other PRSs. Our results indicate that genetic predispositions for psychiatric disorders and wellbeing are associated with early environmental risk factors for children's problem behavior.

Investigating genetic links between grapheme-colour synaesthesia and neuropsychiatric traits

Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme-colour synaesthesia (n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R2 = 0.00092, empirical p = 0.54) or body mass index (R2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'.

SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies

Background

Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses.

Methods

We used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs.

Results

We found that SNPs reported as eQTLs were more significant in GWAS (higher -log₁₀p) regardless of the tissue specificity of the eQTL. Pan-tissue eQTLs (those reported as eQTLs in multiple tissues) tended to be more significant in the GWAS compared to those reported as eQTL in only one tissue type. eQTL density in the ±5 kb adjacent region of a given SNP was also positively associated with the level of GWAS statistical significance regardless of the eQTL status of the SNP. We found that SNPs located in the regions of high eQTL density were more likely to be located in regulatory elements (transcription factor or miRNA binding sites).

When SNPs were stratified by the level of statistical significance, the proportion of eQTLs was positively associated with the mean level of statistical significance in the group. The association curve reaches a plateau around -log₁₀p ≈ 5. The observed associations suggest that quasi-significant SNPs (10^− 5 < p < 5 × 10^− 8) and SNPs at the genome wide level of statistical significance (p < 5 × 10^− 8) may have a similar proportions of risk associated SNPs.

Conclusions

The results of this study indicate that the SNP’s eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS.

Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems

OBJECTIVE

Individuals at high risk for schizophrenia may benefit from early intervention, but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts. The authors sought to test the utility of this approach in clinical settings and to evaluate the broader health consequences of high genetic risk for schizophrenia.

METHODS

The authors used electronic health records for 106,160 patients from four health care systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1,359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.

RESULTS

PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS, 1.55; 95% CI=1.4, 1.7), and patients in the highest risk decile of the PRS distribution had up to 4.6-fold higher odds of schizophrenia compared with those in the bottom decile (95% CI=2.9, 7.3). PRSs were also positively associated with other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.

CONCLUSIONS

The study demonstrates that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in health care settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. The results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in health care systems.

The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders

Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.

Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk

Importance

Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature.

Objectives

To compare brain structural variability between individuals with schizophrenia and healthy controls and to test whether respective variability reflects the polygenic risk score (PRS) for schizophrenia in an independent sample of healthy controls.

Design, Setting, and Participants

This case-control and polygenic risk analysis compared MRI-derived cortical thickness and subcortical volumes between healthy controls and patients with schizophrenia across 16 cohorts and tested for associations between PRS and MRI features in a control cohort from the UK Biobank. Data were collected from October 27, 2004, through April 12, 2018, and analyzed from December 3, 2017, through August 1, 2018.

Main Outcomes and Measures

Mean and dispersion parameters were estimated using double generalized linear models. Vertex-wise analysis was used to assess cortical thickness, and regions-of-interest analyses were used to assess total cortical volume, total surface area, and white matter, subcortical, and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, test of robustness of the PRS threshold, population covariates, outlier removal, and control for image quality.

Results

A comparison of 1151 patients with schizophrenia (mean [SD] age, 33.8 [10.6] years; 68.6% male [n = 790] and 31.4% female [n = 361]) with 2010 healthy controls (mean [SD] age, 32.6 [10.4] years; 56.0% male [n = 1126] and 44.0% female [n = 884]) revealed higher heterogeneity in schizophrenia for cortical thickness and area (t = 3.34), cortical (t = 3.24) and ventricle (t range, 3.15-5.78) volumes, and hippocampal subfields (t range, 2.32-3.55). In the UK Biobank sample of 12 490 participants (mean [SD] age, 55.9 [7.5] years; 48.2% male [n = 6025] and 51.8% female [n = 6465]), higher PRS was associated with thinner frontal and temporal cortices and smaller left CA2/3 (t = -3.00) but was not significantly associated with dispersion.

Conclusions and Relevance

This study suggests that schizophrenia is associated with substantial brain structural heterogeneity beyond the mean differences. These findings may reflect higher sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of schizophrenia. A higher PRS was associated with thinner frontotemporal cortices and smaller hippocampal subfield volume, but not heterogeneity. This finding suggests that brain variability in schizophrenia results from interactions between environmental and genetic factors that are not captured by the PRS. Factors contributing to heterogeneity in frontotemporal cortices and hippocampus are key to furthering our understanding of how genetic and environmental factors shape brain biology in schizophrenia.

Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients

BACKGROUND

Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia.

METHODS

We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]).

RESULTS

The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05).

CONCLUSIONS

In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.

Examining the independent and joint effects of molecular genetic liability and environmental exposures in schizophrenia: results from the EUGEI study

Schizophrenia is a heritable complex phenotype associated with a background risk involving multiple common genetic variants of small effect and a multitude of environmental exposures. Early twin and family studies using proxy-genetic liability measures suggest gene-environment interaction in the etiology of schizophrenia spectrum disorders, but the molecular evidence is scarce. Here, by analyzing the main and joint associations of polygenic risk score for schizophrenia (PRS-SCZ) and environmental exposures in 1,699 patients with a diagnosis of schizophrenia spectrum disorders and 1,542 unrelated controls with no lifetime history of a diagnosis of those disorders, we provide further evidence for gene-environment interaction in schizophrenia. Evidence was found for additive interaction of molecular genetic risk state for schizophrenia (binary mode of PRS-SCZ above 75% of the control distribution) with the presence of lifetime regular cannabis use and exposure to early-life adversities (sexual abuse, emotional abuse, emotional neglect, and bullying), but not with the presence of hearing impairment, season of birth (winter birth), and exposure to physical abuse or physical neglect in childhood. The sensitivity analyses replacing the a priori PRS-SCZ at 75% with alternative cut-points (50% and 25%) confirmed the additive interaction. Our results suggest that the etiopathogenesis of schizophrenia involves genetic underpinnings that act by making individuals more sensitive to the effects of some environmental exposures.

Progress in Polygenic Composite Scores in Alzheimer's and Other Complex Diseases

Advances in high-throughput genotyping and next-generation sequencing (NGS) coupled with larger sample sizes brings the realization of precision medicine closer than ever. Polygenic approaches incorporating the aggregate influence of multiple genetic variants can contribute to a better understanding of the genetic architecture of many complex diseases and facilitate patient stratification. This review addresses polygenic concepts, methodological developments, hypotheses, and key issues in study design. Polygenic risk scores (PRSs) have been applied to many complex diseases and here we focus on Alzheimer's disease (AD) as a primary exemplar. This review was designed to serve as a starting point for investigators wishing to use PRSs in their research and those interested in enhancing clinical study designs through enrichment strategies.

Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.

Polygenic risk for schizophrenia and associated brain structural changes: A systematic review

BACKGROUND

Genome wide association studies (GWAS) of schizophrenia allow the generation of Polygenic Risk Scores (PRS). PRS can be used to determine the contribution to altered brain structures in this disorder, which have been well described. However, findings from studies using PRS to predict brain structural changes in schizophrenia have been inconsistent. We therefore performed a systematic review to determine the association between schizophrenia PRS and brain structure.

METHODS

Following PRISMA systematic review guidelines, databases were searched for literature using key search terms. Inclusion criteria for the discovery sample required case-control schizophrenia GWAS summary statistics from European populations. The target sample was required to be of European ancestry, and have brain structure and genotype information. Quality assessment of the publications was conducted using the Mixed Methods Appraisal Tool for quantitative non-randomised studies.

MAIN FINDINGS

A total of seven studies were found to be eligible for review. Five studies found no significant association and two studies found a significant association of schizophrenia PRS with total brain, reduced white matter volume, and globus pallidus volume. However, the latter studies were conducted using smaller discovery (n_cases = 9394 n_controls = 12,462) and target samples compared to the studies with substantially larger discovery (n_cases = 33,636 n_controls = 43,008) and target samples where no association was observed. Taken together, the results suggest that schizophrenia PRS are not significantly associated with brain structural changes in this disorder.

CONCLUSIONS

The lack of significant association between schizophrenia PRS and brain structural changes may indicate that intermediate phenotypes other than brain structure should be the focus of future work. Alternatively, however, the lack of association found here may point to limitations of the current evidence-base, and so point to the need for future better powered studies.

A systematic review of genome-wide research on psychotic experiences and negative symptom traits: new revelations and implications for psychiatry

We present a systematic review of genome-wide research on psychotic experience and negative symptom (PENS) traits in the community. We integrate these new findings, most of which have emerged over the last four years, with more established behaviour genetic and epidemiological research. The review includes the first genome-wide association studies of PENS, including a recent meta-analysis, and the first SNP heritability estimates. Sample sizes of <10 000 participants mean that no genome-wide significant variants have yet been replicated. Importantly, however, in the most recent and well-powered studies, polygenic risk score prediction and linkage disequilibrium (LD) score regression analyses show that all types of PENS share genetic influences with diagnosed schizophrenia and that negative symptom traits also share genetic influences with major depression. These genetic findings corroborate other evidence in supporting a link between PENS in the community and psychiatric conditions. Beyond the systematic review, we highlight recent work on gene-environment correlation, which appears to be a relevant process for psychotic experiences. Genes that influence risk factors such as tobacco use and stressful life events are likely to be harbouring 'hits' that also influence PENS. We argue for the acceptance of PENS within the mainstream, as heritable traits in the same vein as other sub-clinical psychopathology and personality styles such as neuroticism. While acknowledging some mixed findings, new evidence shows genetic overlap between PENS and psychiatric conditions. In sum, normal variations in adolescent and adult thinking styles, such as feeling paranoid, are heritable and show genetic associations with schizophrenia and major depression.

Mini-review: Update on the genetics of schizophrenia

A number of important findings have recently emerged relevant to identifying genetic risk factors for schizophrenia. Findings using common variants point towards gene sets of interest and also demonstrate an overlap with other psychiatric and nonpsychiatric disorders. Imputation of variants of the gene for complement component 4 (C4) from GWAS data has shown that the predicted expression of the C4A product is associated with schizophrenia risk. Very rare variants disrupting SETD1A, RBM12 or NRXN1 have a large effect on risk. Other rare, damaging variants are enriched in genes that are loss of function intolerant and/or whose products localise to the synapse. These and particular copy number variants can result in increased risk of schizophrenia but also of other neurodevelopmental disorders. The findings for C4 and NRXN1 may be especially helpful for elucidating the biological mechanisms that can lead to disease.

Recent Advances in the Genetics of Schizophrenia

The last decade brought tremendous progress in the field of schizophrenia genetics. As a result of extensive collaborations and multiple technological advances, we now recognize many types of genetic variants that increase the risk. These include large copy number variants, rare coding inherited and de novο variants, and over 100 loci harboring common risk variants. While the type and contribution to the risk vary among genetic variants, there is concordance in the functions of genes they implicate, such as those whose RNA binds the fragile X-related protein FMRP and members of the activity-regulated cytoskeletal complex involved in learning and memory. Gene expression studies add important information on the biology of the disease and recapitulate the same functional gene groups. Studies of alternative phenotypes help us widen our understanding of the genetic architecture of mental function and dysfunction, how diseases overlap not only with each other but also with non-disease phenotypes. The challenge is to apply this new knowledge to prevention and treatment and help patients. The data generated so far and emerging technologies, including new methods in cell engineering, offer significant promise that in the next decade we will unlock the translational potential of these significant discoveries.

Polygenic risk for psychiatric disorders correlates with executive function in typical development

Executive functions are a diverse and critical suite of cognitive abilities that are often disrupted in individuals with psychiatric disorders. Despite their moderate to high heritability, little is known about the molecular genetic factors that contribute to variability in executive functions and how these factors may be related to those that predispose to psychiatric disorders. We examined the relationship between polygenic risk scores built from large genome-wide association studies of psychiatric disorders and executive functioning in typically developing children. In our discovery sample (N = 417), consistent with previous reports on general cognitive abilities, polygenic risk for autism spectrum disorder was associated with better performance on the Dimensional Change Card Sort test from the NIH Cognition Toolbox, with the largest effect in the youngest children. Polygenic risk for major depressive disorder was associated with poorer performance on the Flanker test in the same sample. This second association replicated for performance on the Penn Conditional Exclusion Test in an independent cohort (N = 3681). Our results suggest that the molecular genetic factors contributing to variability in executive function during typical development are at least partially overlapping with those associated with psychiatric disorders, although larger studies and further replication are needed.

Genomic and Imaging Biomarkers in Schizophrenia

Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.