Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

BACKGROUND

The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex.

RESULTS

We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02-5.61, P = 1.1E-03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status.

CONCLUSIONS

Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

AIM

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

METHODS

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

RESULTS

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and modest harmonization for CHR-P criteria. The semi-structured interview, named Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

CONCLUSIONS

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Cell-type deconvolution of bulk-blood RNA-seq reveals biological insights into neuropsychiatric disorders

Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication.

Genomic loci influence patterns of structural covariance in the human brain

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders

Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal mechanisms of the link between genetic variation and disease risk. Expression quantitative trait loci (eQTL) analysis of bulk tissue is a common approach to decipher underlying mechanisms, though this can obscure cell-type specific signals thus masking trait-relevant mechanisms. While single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell type proportions and cell type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-Seq from 1,730 samples derived from whole blood in a cohort ascertained for individuals with BP and SCZ this study estimated cell type proportions and their relation with disease status and medication. We found between 2,875 and 4,629 eGenes for each cell type, including 1,211 eGenes that are not found using bulk expression alone. We performed a colocalization test between cell type eQTLs and various traits and identified hundreds of associations between cell type eQTLs and GWAS loci that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on cell type expression regulation and found examples of genes that are differentially regulated dependent on lithium use. Our study suggests that computational methods can be applied to large bulk RNA-Seq datasets of non-brain tissue to identify disease-relevant, cell type specific biology of psychiatric disorders and psychiatric medication.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

Aim

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

Methods

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

Results

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and partial harmonization for CHR-P criteria. The semi-structured interview, named P ositive SY mptoms and Diagnostic Criteria for the C AARMS H armonized with the S IPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

Conclusion

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population

Importance

Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment.

Objective

To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations.

Design, Setting, and Participants

This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022.

Main Outcomes and Measures

The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations.

Results

Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6).

Conclusions and Relevance

This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth

Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age in youth is important because age-related brain changes in this age-group are dynamic. However, the comparative performance of the available ML algorithms has not been systematically appraised. To address this gap, the present study evaluated the accuracy (mean absolute error [MAE]) and computational efficiency of 21 machine learning algorithms using sMRI data from 2105 typically developing individuals aged 5-22 years from five cohorts. The trained models were then tested in two independent holdout datasets, one comprising 4078 individuals aged 9-10 years and another comprising 594 individuals aged 5-21 years. The algorithms encompassed parametric and nonparametric, Bayesian, linear and nonlinear, tree-based, and kernel-based models. Sensitivity analyses were performed for parcellation scheme, number of neuroimaging input features, number of cross-validation folds, number of extreme outliers, and sample size. Tree-based models and algorithms with a nonlinear kernel performed comparably well, with the latter being especially computationally efficient. Extreme Gradient Boosting (MAE of 1.49 years), Random Forest Regression (MAE of 1.58 years), and Support Vector Regression (SVR) with Radial Basis Function (RBF) Kernel (MAE of 1.64 years) emerged as the three most accurate models. Linear algorithms, with the exception of Elastic Net Regression, performed poorly. Findings of the present study could be used as a guide for optimizing methodology when quantifying brain-age in youth.

Within-family influences on dimensional neurobehavioral traits in a high-risk genetic model

BACKGROUND

Genotype-first and within-family studies can elucidate factors that contribute to psychiatric illness. Combining these approaches, we investigated the patterns of influence of parental scores, a high-impact variant, and schizophrenia on dimensional neurobehavioral phenotypes implicated in major psychiatric disorders.

METHODS

We quantitatively assessed cognitive (FSIQ, VIQ, PIQ), social, and motor functioning in 82 adult individuals with a de novo 22q11.2 deletion (22 with schizophrenia), and 148 of their unaffected parents. We calculated within-family correlations and effect sizes of the 22q11.2 deletion and schizophrenia, and used linear regressions to assess contributions to neurobehavioral measures.

RESULTS

Proband-parent intra-class correlations (ICC) were significant for cognitive measures (e.g. FSIQ ICC = 0.549, p < 0.0001), but not for social or motor measures. Compared to biparental scores, the 22q11.2 deletion conferred significant impairments for all phenotypes assessed (effect sizes -1.39 to -2.07 s.d.), strongest for PIQ. There were further decrements in those with schizophrenia. Regression models explained up to 37.7% of the variance in IQ and indicated that for proband IQ, parental IQ had larger effects than schizophrenia.

CONCLUSIONS

This study, for the first time, disentangles the impact of a high-impact variant from the modifying effects of parental scores and schizophrenia on relevant neurobehavioral phenotypes. The robust proband-parent correlations for cognitive measures, independent of the impact of the 22q11.2 deletion and of schizophrenia, suggest that, for certain phenotypes, shared genetic variation plays a significant role in expression. Molecular genetic and predictor studies are needed to elucidate shared factors and their contribution to psychiatric illness in this and other high-risk groups.

Schizophrenia Imaging Signatures and Their Associations With Cognition, Psychopathology, and Genetics in the General Population

OBJECTIVE

The prevalence and significance of schizophrenia-related phenotypes at the population level is debated in the literature. Here, the authors assessed whether two recently reported neuroanatomical signatures of schizophrenia-signature 1, with widespread reduction of gray matter volume, and signature 2, with increased striatal volume-could be replicated in an independent schizophrenia sample, and investigated whether expression of these signatures can be detected at the population level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk.

METHODS

This cross-sectional study used an independent schizophrenia-control sample (N=347; ages 16-57 years) for replication of imaging signatures, and then examined two independent population-level data sets: typically developing youths and youths with psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort (N=359; ages 16-23 years) and adults in the UK Biobank study (N=836; ages 44-50 years). The authors quantified signature expression using support-vector machine learning and compared cognition, psychopathology, and polygenic risk between signatures.

RESULTS

Two neuroanatomical signatures of schizophrenia were replicated. Signature 1 but not signature 2 was significantly more common in youths with psychosis spectrum symptoms than in typically developing youths, whereas signature 2 frequency was similar in the two groups. In both youths and adults, signature 1 was associated with worse cognitive performance than signature 2. Compared with adults with neither signature, adults expressing signature 1 had elevated schizophrenia polygenic risk scores, but this was not seen for signature 2.

CONCLUSIONS

The authors successfully replicated two neuroanatomical signatures of schizophrenia and describe their prevalence in population-based samples of youths and adults. They further demonstrated distinct relationships of these signatures with psychosis symptoms, cognition, and genetic risk, potentially reflecting underlying neurobiological vulnerability.

Comparing psychotic experiences in low-and-middle-income-countries and high-income-countries with a focus on measurement invariance

BACKGROUND

The prevalence of psychotic experiences (PEs) is higher in low-and-middle-income-countries (LAMIC) than in high-income countries (HIC). Here, we examine whether this effect is explicable by measurement bias.

METHODS

A community sample from 13 countries (N = 7141) was used to examine the measurement invariance (MI) of a frequently used self-report measure of PEs, the Community Assessment of Psychic Experiences (CAPE), in LAMIC (n = 2472) and HIC (n = 4669). The CAPE measures positive (e.g. hallucinations), negative (e.g. avolition) and depressive symptoms. MI analyses were conducted with multiple-group confirmatory factor analyses.

RESULTS

MI analyses showed similarities in the structure and understanding of the CAPE factors between LAMIC and HIC. Partial scalar invariance was found, allowing for latent score comparisons. Residual invariance was not found, indicating that sum score comparisons are biased. A comparison of latent scores before and after MI adjustment showed both overestimation (e.g. avolition, d = 0.03 into d = -0.42) and underestimation (e.g. magical thinking, d = -0.03 into d = 0.33) of PE in LAMIC relative to HIC. After adjusting the CAPE for MI, participants from LAMIC reported significantly higher levels on most CAPE factors but a significantly lower level of avolition.

CONCLUSION

Previous studies using sum scores to compare differences across countries are likely to be biased. The direction of the bias involves both over- and underestimation of PEs in LAMIC compared to HIC. Nevertheless, the study confirms the basic finding that PEs are more frequent in LAMIC than in HIC.

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes

Disease heterogeneity is a significant obstacle to understanding pathological processes and delivering precision diagnostics and treatment. Clustering methods have gained popularity for stratifying patients into subpopulations (i.e., subtypes) of brain diseases using imaging data. However, unsupervised clustering approaches are often confounded by anatomical and functional variations not related to a disease or pathology of interest. Semi-supervised clustering techniques have been proposed to overcome this and, therefore, capture disease-specific patterns more effectively. An additional limitation of both unsupervised and semi-supervised conventional machine learning methods is that they typically model, learn and infer from data using a basis of feature sets pre-defined at a fixed anatomical or functional scale (e.g., atlas-based regions of interest). Herein we propose a novel method, "Multi-scAle heteroGeneity analysIs and Clustering" (MAGIC), to depict the multi-scale presentation of disease heterogeneity, which builds on a previously proposed semi-supervised clustering method, HYDRA. It derives multi-scale and clinically interpretable feature representations and exploits a double-cyclic optimization procedure to effectively drive identification of inter-scale-consistent disease subtypes. More importantly, to understand the conditions under which the clustering model can estimate true heterogeneity related to diseases, we conducted extensive and systematic semi-simulated experiments to evaluate the proposed method on a sizeable healthy control sample from the UK Biobank (N = 4403). We then applied MAGIC to imaging data from Alzheimer's disease (ADNI, N = 1728) and schizophrenia (PHENOM, N = 1166) patients to demonstrate its potential and challenges in dissecting the neuroanatomical heterogeneity of common brain diseases. Taken together, we aim to provide guidance regarding when such analyses can succeed or should be taken with caution. The code of the proposed method is publicly available at https://github.com/anbai106/MAGIC.

Characterisation of age and polarity at onset in bipolar disorder

BACKGROUND

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

AIMS

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

METHOD

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

RESULTS

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

CONCLUSIONS

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

The Community Assessment of Psychic Experiences: Optimal cut-off scores for detecting individuals with a psychotic disorder

OBJECTIVES

The need for a brief screening tool for psychosis is widely recognized. The Community Assessment of Psychic Experiences (CAPE) is a popular self-report measure of psychosis, but a cut-off score that can detect those most likely to fulfill diagnostic criteria for psychotic disorder is not established.

METHODS

A case-control sample from the Genetic Risk and Outcome of Psychosis Project study (N = 1375, healthy individuals, n = 507, and individuals with a psychotic disorder, n = 868), was used to examine cut-off scores of the CAPE with receiver operating curve analyses. We examined 27 possible cut-off scores computed from a combination of scores from the frequency and distress scales of the various factors of the CAPE.

RESULTS

The weighted severity positive symptom dimension was most optimal in detecting individuals with a psychotic disorder (>1.75 cut-off; area under the curve = 0.88; sensitivity, 75%; specificity, 88%), which correctly identified 80% of the sample as cases or controls with a diagnostic odds ratio of 22.69.

CONCLUSIONS

The CAPE can be used as a first screening tool to detect individuals who are likely to fulfill criteria for a psychotic disorder. The >1.75 cut-off of the weighted severity positive symptom dimension provides a better prediction than all alternatives tested so far.

Structural brain volumes of individuals at clinical high risk for psychosis: a meta-analysis

Background

Structural magnetic resonance imaging studies in individuals at clinical high risk (CHR) for psychosis have yielded conflicting results.

Methods

The aims of this study were to compare intracranial and structural brain volumes and variability of CHR individuals with those of healthy control (HC) subjects and to investigate brain volume differences and variability in CHR subjects with and without transition to psychosis. The PubMed and Embase databases were searched for relevant studies published before June 1, 2020.

Results

A total of 34 studies were deemed eligible, which included baseline data of 2111 CHR and 1472 HC participants. In addition, data were included for 401 CHR subjects who subsequently transitioned to psychosis and 1023 nontransitioned CHR participants. Whole-brain and left, right, and bilateral hippocampal volume were significantly smaller in CHR subjects than in HC subjects. Cerebrospinal fluid and lateral ventricle volumes were significantly larger in CHR subjects than in HC subjects. Variability was not significantly different in CHR subjects compared with HC subjects. CHR individuals with and without subsequent transition to psychosis did not show significant differences in any of the volumetric assessments or in variability.

Conclusions

This meta-analysis demonstrates reduced whole-brain and hippocampal volumes and increased cerebrospinal fluid and lateral ventricle volumes in CHR individuals. However, no significant differences were observed in any of the volumetric assessments between CHR individuals with and without subsequent transition to psychosis. These findings suggest that although structural brain alterations are present before the onset of the disorder, they may not significantly contribute to the identification of CHR individuals at the highest risk for the development of psychosis.

Cognitive functioning throughout adulthood and illness stages in individuals with psychotic disorders and their unaffected siblings

Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271), compared to controls (n = 3301). An abbreviated WAIS-III measured verbal knowledge, working memory, visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = -0.45 to -0.73, p < 0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = -0.14 to -0.33, p < 0.001). Magnitude of impairment was not associated with participant age, such that the size of impairment in older and younger patients did not significantly differ. However, first-episode patients performed worse than prodromal patients (ES range = -0.88 to -0.60, p < 0.001). Adjusting for cannabis use, symptom severity, and global functioning attenuated impairments in siblings, while deficits in patients remained statistically significant, albeit reduced by half (ES range = -0.13 to -0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = -0.21 to -0.43, p < 0.01). Deficits in verbal knowledge, and working memory may specifically index familial, i.e., shared genetic and/or shared environmental, liability for psychotic disorders. Nevertheless, potentially modifiable illness-related factors account for a significant portion of the cognitive impairment in psychotic disorders.

Relationship Between Serum NMDA Receptor Antibodies and Response to Antipsychotic Treatment in First-Episode Psychosis

BACKGROUND

When psychosis develops in NMDA receptor (NMDAR) antibody encephalitis, it usually has an acute or subacute onset, and antipsychotic treatment may be ineffective and associated with adverse effects. Serum NMDAR antibodies have been reported in a minority of patients with first-episode psychosis (FEP), but their role in psychosis onset and response to antipsychotic treatment is unclear.

METHODS

Sera from 387 patients with FEP (duration of psychosis <2 years, minimally or never treated with antipsychotics) undergoing initial treatment with amisulpride as part of the OPTiMiSE (Optimization of Treatment and Management of Schizophrenia in Europe) trial (ClinicalTrials.gov number NCT01248195) were tested for NMDAR IgG antibodies using a live cell-based assay. Symptom severity was assessed using the Positive and Negative Syndrome Scale and the Clinical Global Impressions Scale at baseline and again after 4 weeks of treatment with amisulpride.

RESULTS

At baseline, 15 patients were seropositive for NMDAR antibodies and 372 were seronegative. The seropositive patients had similar symptom profiles and demographic features to seronegative patients but a shorter duration of psychosis (median 1.5 vs. 4.0 months; p = .031). Eleven seropositive and 284 seronegative patients completed 4 weeks of amisulpride treatment: after treatment, there was no between-groups difference in improvement in Positive and Negative Syndrome Scale scores or in the frequency of adverse medication effects.

CONCLUSIONS

These data suggest that in FEP, NMDAR antibody seropositivity alone is not an indication for using immunotherapy instead of antipsychotic medications. Further studies are required to establish what proportion of patients with FEP who are NMDAR antibody seropositive have coexisting cerebrospinal fluid inflammatory changes or other paraclinical evidence suggestive of a likely benefit from immunotherapy.

Brain age prediction in schizophrenia: Does the choice of machine learning algorithm matter?

Brain-predicted age difference (brainPAD) has been used in schizophrenia to assess individual-level deviation in the biological age of the patients' brain (i.e., brain-age) from normative reference brain structural datasets. There is marked inter-study variation in brainPAD in schizophrenia which is commonly attributed to sample heterogeneity. However, the potential contribution of the different machine learning algorithms used for brain-age estimation has not been systematically evaluated. Here, we aimed to assess variation in brain-age estimated by six commonly used algorithms [ordinary least squares regression, ridge regression, least absolute shrinkage and selection operator regression, elastic-net regression, linear support vector regression, and relevance vector regression] when applied to the same brain structural features from the same sample. To assess reproducibility we used data from two publically available samples of healthy individuals (n = 1092 and n = 492) and two further samples, from the Icahn School of Medicine at Mount Sinai (ISMMS) and the Center of Biomedical Research Excellence (COBRE), comprising both patients with schizophrenia (n = 90 and n = 76) and healthy individuals (n = 200 and n = 87). Performance similarity across algorithms was compared within each sample using correlation analyses and hierarchical clustering. Across all samples ordinary least squares regression, the only algorithm without a penalty term, performed markedly worse. All other algorithms showed comparable performance but they still yielded variable brain-age estimates despite being applied to the same data. Although brainPAD was consistently higher in patients with schizophrenia, it varied by algorithm from 3.8 to 5.2 years in the ISMMS sample and from to 4.5 to 11.7 years in the COBRE sample. Algorithm choice introduces variations in brain-age and may confound inter-study comparisons when assessing brainPAD in schizophrenia.

Simvastatin Augmentation for Patients With Early-Phase Schizophrenia-Spectrum Disorders: A Double-Blind, Randomized Placebo-Controlled Trial

Schizophrenia-spectrum disorders (SSD) are associated with increased inflammatory markers, both in brain and periphery. Augmentation with drugs that lower this pro-inflammatory status may improve clinical presentation. Simvastatin crosses the blood-brain barrier, has anti- inflammatory and neuroprotective effects and reduces metabolic syndrome. In this study, we investigated if 12 months of simvastatin augmentation can improve symptoms and cognition in patients with early SSD. This double-blind placebo-controlled trial included 127 SSD patients across the Netherlands, <3 years after their diagnosis. From these, 119 were randomly assigned 1:1 to simvastatin 40 mg (n = 61) or placebo (n = 58), stratified for sex and study site. Primary outcomes were symptom severity and cognition after 12 months of treatment. Depression, symptom subscores, general functioning, metabolic syndrome, movement disorders, and safety were secondary outcomes. Intention to treat analyses were performed using linear mixed models and ANCOVA. No main effect of simvastatin treatment was found on total symptom severity after 12 months of treatment as compared to placebo (X2(1) = 0.01, P = .90). Group differences varied over time (treatment*time X2(4) = 11.2; P = .025), with significantly lower symptom severity in the simvastatin group after 6 months (mean difference = -4.8; P = .021; 95% CI: -8.8 to -0.7) and at 24 months follow-up (mean difference = -4.7; P = .040; 95% CI: -9.3 to -0.2). No main treatment effect was found for cognition (F(1,0.1) = 0.37, P = .55) or secondary outcomes. SAEs occurred more frequently with placebo (19%) than with simvastatin (6.6%). This negative finding corroborates other large scale studies on aspirin, minocycline, and celecoxib that could not replicate positive findings of smaller studies, and suggests that anti-inflammatory augmentation does not improve the clinical presentation of SSD.

Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect

BACKGROUND

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.

METHODS

We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.

RESULTS

While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.

CONCLUSIONS

These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study

Individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, that may be particularly prominent, already at illness onset, in those more likely to have poorer symptom remission following treatment with the first antipsychotic. The identification of strong neuroanatomical markers of symptom remission could thus facilitate stratification and individualized treatment of patients with schizophrenia. We used magnetic resonance imaging at baseline to examine brain regional and network correlates of subsequent symptomatic remission in 167 medication-naïve or minimally treated patients with first-episode schizophrenia, schizophreniform disorder, or schizoaffective disorder entering a three-phase trial, at seven sites. Patients in remission at the end of each phase were randomized to treatment as usual, with or without an adjunctive psycho-social intervention for medication adherence. The final follow-up visit was at 74 weeks. A total of 108 patients (70%) were in remission at Week 4, 85 (55%) at Week 22, and 97 (63%) at Week 74. We found no baseline regional differences in volumes, cortical thickness, surface area, or local gyrification between patients who did or did not achieved remission at any time point. However, patients not in remission at Week 74, at baseline showed reduced structural connectivity across frontal, anterior cingulate, and insular cortices. A similar pattern was evident in patients not in remission at Week 4 and Week 22, although not significantly. Lack of symptom remission in first-episode psychosis is not associated with regional brain alterations at illness onset. Instead, when the illness becomes a stable entity, its association with the altered organization of cortical gyrification becomes more defined.

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.

Vitamin D concentration and psychotic disorder: associations with disease status, clinical variables and urbanicity

BACKGROUND

The association between schizophrenia and decreased vitamin D levels is well documented. Low maternal and postnatal vitamin D levels suggest a possible etiological mechanism. Alternatively, vitamin D deficiency in patients with schizophrenia is presumably (also) the result of disease-related factors or demographic risk factors such as urbanicity.

METHODS

In a study population of 347 patients with psychotic disorder and 282 controls, group differences in vitamin D concentration were examined. Within the patient group, associations between vitamin D, symptom levels and clinical variables were analyzed. Group × urbanicity interactions in the model of vitamin D concentration were examined. Both current urbanicity and urbanicity at birth were assessed.

RESULTS

Vitamin D concentrations were significantly lower in patients (B = -8.05; 95% confidence interval (CI) -13.68 to -2.42; p = 0.005). In patients, higher vitamin D concentration was associated with lower positive (B = -0.02; 95% CI -0.04 to 0.00; p = 0.049) and negative symptom levels (B = -0.03; 95% CI -0.05 to -0.01; p = 0.008). Group differences were moderated by urbanicity at birth (χ2 = 6.76 and p = 0.001), but not by current urbanicity (χ2 = 1.50 and p = 0.224). Urbanicity at birth was negatively associated with vitamin D concentration in patients (B = -5.11; 95% CI -9.41 to -0.81; p = 0.020), but not in controls (B = 0.72; 95% CI -4.02 to 5.46; p = 0.765).

CONCLUSIONS

Lower vitamin D levels in patients with psychotic disorder may in part reflect the effect of psychosis risk mediated by early environmental adversity. The data also suggest that lower vitamin D and psychopathology may be related through direct or indirect mechanisms.

No association between anti-thyroidperoxidase antibodies and bipolar disorder: a study in the Dutch Bipolar Cohort and a meta-analysis

BACKGROUND

Thyroid autoimmunity has been associated with bipolar disorder (BD). However, results from previous studies on the seroprevalence of anti-thyroid peroxidase antibodies (TPO-abs) in BD are inconsistent.

OBJECTIVES

The aim of the present study is to investigate whether the seroprevalence and titer levels of TPO-abs are related to BD.

METHOD

TPO-abs were measured in plasma samples of 760 patients with bipolar disorder, 261 first-degree relatives and 363 controls by enzyme-linked immunosorbent assay (ELISA). To address methodological limitations of previous studies, we assessed clinical characteristics with several (self-reported) questionnaires to investigate whether TPO-abs positivity is related to particular clinical subgroups of BD patients. We performed an additional meta-analysis of seroprevalences of TPO-abs in BD patients including data from present and previous studies.

RESULTS

Seroprevalence or titer levels of TPO-abs did not significantly differ between patients with BD, their first-degree relatives, and controls. In BD patients, the prevalence of TPO-abs was unrelated to specific clinical factors, including lithium use. Our meta-analysis of twelve studies showed an overall odds ratio of 1.3 (CI 95 %: 0.7-2.3; p = 0.30), reaffirming the absence of an association of BD with TPO-abs.

CONCLUSIONS

In the largest study of TPO-abs in BD to date, our findings indicate that TPO-abs are not associated with (the risk for) bipolar disorder.

Brain structure, IQ, and psychopathology in young offspring of patients with schizophrenia or bipolar disorder

BACKGROUND

Studying offspring of schizophrenia (SZo) and bipolar disorder patients (BDo) provides important information on the putative neurodevelopmental trajectories underlying development toward severe mental illnesses. We compared intracranial volume (ICV), as a marker for neurodevelopment, and global and local brain measures between SZo or BDo and control offspring (Co) in relation to IQ and psychopathology.

METHODS

T1-weighted magnetic resonance imaging (MRI) brain scans were obtained from 146 participants (8-19 years; 40 SZo, 66 BDo, 40 Co). Linear mixed models were applied to compare ICV, global, and local brain measures between groups. To investigate the effect of ICV, IQ (four subtests Wechsler Intelligence Scale for Children/Wechsler Adult Intelligence Scale-III) or presence of psychopathology these variables were each added to the model.

RESULTS

SZo and BDo had significantly lower IQ and more often met criteria for a lifetime psychiatric disorder than Co. ICV was significantly smaller in SZo than in BDo (d = -0.56) and Co (d = -0.59), which was largely independent of IQ (respectively, d = -0.54 and d = -0.35). After ICV correction, the cortex was significantly thinner in SZo than in BDo (d = -0.42) and Co (d = -0.75) and lateral ventricles were larger in BDo than in Co (d = 0.55). Correction for IQ or lifetime psychiatric diagnosis did not change these findings.

CONCLUSIONS

Despite sharing a lower IQ and a higher prevalence of psychiatric disorders, brain abnormalities in BDo appear less pronounced (but are not absent) than in SZo. Lower ICV in SZo implies that familial risk for schizophrenia has a stronger association with stunted early brain development than familial risk for bipolar disorder.

Demographic and clinical features as predictors of clozapine response in patients with schizophrenia spectrum disorders: A systematic review and meta-analysis

OBJECTIVES

Clozapine (CLZ) is prescribed to (relatively) treatment-resistant patients with schizophrenia spectrum disorders. Currently, it is unknown what factors predict response to CLZ. Therefore, we performed meta-analyses to identify predictors of CLZ response, hence aiming to facilitate timely and efficient prescribing of CLZ.

METHODS

A systematic search was performed in 'Pubmed' and 'Embase' until 1 January 2019. Articles were eligible if they provided data on predictors of CLZ response measured demographic and clinical factors at baseline or biochemical factors at follow-up in schizophrenia spectrum disorder patients.

RESULTS

A total of 34 articles, total number of participants = 9386; N unique = 2094, were eligible. Factors significantly associated with better CLZ response were: lower age, lower PANSS negative score and paranoid schizophrenia subtype.

CONCLUSION

The results of our meta-analyses suggest that three baseline demographic and clinical features are associated with better clozapine response, i.e. relatively young age, few negative symptoms and paranoid schizophrenia subtype. These variables may be taken into account by clinicians who consider treating a specific patient with CLZ.

Family interventions and prevention of suicide in first-episode schizophrenia

Suicide is one of the leading causes of premature death among individuals with schizophrenia and psychotic spectrum disorders (1). Suicide and suicide attempts occur at a significantly greater rate in schizophrenia than in the general population. Common estimates are that 10% of people with schizophrenia will eventually have a completed suicide, and that attempts are made at two to five times that rate. This article is protected by copyright. All rights reserved.

Neurocognition and adaptive functioning in a genetic high risk model of schizophrenia

BACKGROUND

Identifying factors that influence the functional outcome is an important goal in schizophrenia research. The 22q11.2 deletion syndrome (22q11DS) is a unique genetic model with high risk (20-25%) for schizophrenia. This study aimed to identify potentially targetable domains of neurocognitive functioning associated with functional outcome in adults with 22q11DS.

METHODS

We used comprehensive neurocognitive test data available for 99 adults with 22q11DS (n = 43 with schizophrenia) and principal component analysis to derive four domains of neurocognition (Verbal Memory, Visual and Logical Memory, Motor Performance, and Executive Performance). We then investigated the association of these neurocognitive domains with adaptive functioning using Vineland Adaptive Behavior Scales data and a linear regression model that accounted for the effects of schizophrenia status and overall intellectual level.

RESULTS

The regression model explained 46.8% of the variance in functional outcome (p &lt; 0.0001). Executive Performance was significantly associated with functional outcome (p = 0.048). Age and schizophrenia were also significant factors. The effects of Executive Performance on functioning did not significantly differ between those with and without psychotic illness.

CONCLUSION

The findings provide the impetus for further studies to examine the potential of directed (early) interventions targeting Executive Performance to improve long-term adaptive functional outcome in individuals with, or at high risk for, schizophrenia. Moreover, the neurocognitive test profiles may benefit caregivers and clinicians by providing insight into the relative strengths and weaknesses of individuals with 22q11DS, with and without psychotic illness.

Schizophrenia Polygenic Risk Score as a Predictor of Antipsychotic Efficacy in First-Episode Psychosis

OBJECTIVE

Pharmacogenomic studies of antipsychotics have typically examined effects of individual polymorphisms. By contrast, polygenic risk scores (PRSs) derived from genome-wide association studies (GWAS) can quantify the influence of thousands of common alleles of small effect in a single measure. The authors examined whether PRSs for schizophrenia were predictive of antipsychotic efficacy in four independent cohorts of patients with first-episode psychosis (total N=510).

METHOD

All study subjects received initial treatment with antipsychotic medication for first-episode psychosis, and all were genotyped on standard single-nucleotide polymorphism (SNP) arrays imputed to the 1000 Genomes Project reference panel. PRS was computed based on the results of the large-scale schizophrenia GWAS reported by the Psychiatric Genomics Consortium. Symptoms were measured by using total symptom rating scales at baseline and at week 12 or at the last follow-up visit before dropout.

RESULTS

In the discovery cohort, higher PRS significantly predicted higher symptom scores at the 12-week follow-up (controlling for baseline symptoms, sex, age, and ethnicity). The PRS threshold set at a p value <0.01 gave the strongest result in the discovery cohort and was used to replicate the findings in the other three cohorts. Higher PRS significantly predicted greater posttreatment symptoms in the combined replication analysis and was individually significant in two of the three replication cohorts. Across the four cohorts, PRS was significantly predictive of adjusted 12-week symptom scores (pooled partial r=0.18; 3.24% of variance explained). Patients with low PRS were more likely to be treatment responders than patients with high PRS (odds ratio=1.91 in the two Caucasian samples).

CONCLUSIONS

Patients with higher PRS for schizophrenia tended to have less improvement with antipsychotic drug treatment. PRS burden may have potential utility as a prognostic biomarker.

Patterns of obsessive-compulsive symptoms and social functioning in schizophrenia; a replication study

Research has found that Obsessive Compulsive Symptoms (OCS) in schizophrenia are associated with either more or less negative symptoms and either better or poorer cognitive functioning. In order to explain these contradictory results, (Lysaker et al., 2004), performed a cluster analysis resulting in 2 OCS positive (OCSpos) clusters, one with higher functioning (HF) and one with poorer functioning (PF) compared to 2 OCS negative (OCSneg) clusters. The OCSpos/HF cluster had less negative symptoms compared to all other clusters, while the OCSpos/PF cluster showed poorer executive functioning. We performed a replication study, in an almost 10 times larger, representative sample, using both a longitudinal and cross-sectional design. Similar to Lysaker et al., we found a group with mild OCS and HF (OCSmild/HF) showing less negative symptoms compared to the PF groups. We also found an OCSmild/PF group, which did not significantly differ in executive functioning from the other groups. Moreover, we did not find evidence for a better prognosis in the OCSmild/HF group, and thus found no support for the assumption that for some patients OCS might be an effective coping mechanism.

Reward-related brain structures are smaller in patients with schizophrenia and comorbid metabolic syndrome

OBJECTIVE

Metabolic syndrome (MS) is highly prevalent in schizophrenia and often a consequence of unhealthy behaviour. Reward-related brain areas might be associated with MS, since they play a major role in regulating health behaviour. This study examined the relationship between MS and brain volumes related to the reward system in schizophrenia.

METHOD

We included patients with schizophrenia, with MS (MS+; n = 23), patients with schizophrenia, without MS (MS-; n = 48), and healthy controls (n = 54). Global brain volumes and volumes of (sub)cortical areas, part of the reward circuit, were compared between patients and controls. In case of a significant brain volume difference between patients and controls, the impact of MS in schizophrenia was examined.

RESULTS

Patients had smaller total brain (TB; P = 0.001), GM (P = 0.010), larger ventricles (P = 0.026), and smaller reward circuit volume (P < 0.001) than controls. MS+ had smaller TB (P = 0.017), GM (P = 0.008), larger ventricles (P = 0.015), and smaller reward circuit volume (P = 0.002) than MS-. MS+ had smaller orbitofrontal cortex (OFC; P = 0.002) and insula volumes (P = 0.005) and smaller OFC (P = 0.008) and insula cortical surface area (P = 0.025) compared to MS-.

CONCLUSION

In schizophrenia, structural brain volume reductions in areas of the reward circuitry appear to be related to comorbid MS.

Association Between Smoking Behavior and Cognitive Functioning in Patients With Psychosis, Siblings, and Healthy Control Subjects: Results From a Prospective 6-Year Follow-Up Study

OBJECTIVE

The high prevalence of smoking and cognitive deficits in schizophrenia patients is well known, but findings regarding the association between the two are contradictory, and longitudinal studies are lacking. The authors sought to examine the multi-cross-sectional association between smoking behavior and performance in specific cognitive domains and the longitudinal association between change in smoking behavior and change in cognitive functioning in a large prospective study.

METHOD

The authors conducted a cohort study of patients with nonaffective psychosis (N=1,094), their siblings (N=1,047), and healthy control subjects (N=579). At baseline and at 3- and 6-year follow-ups, smoking behavior was assessed with the Composite International Diagnostic Interview and cognitive functioning with a test battery. Multivariate linear mixed-effects regression analyses were conducted to assess associations between smoking and cognitive domains while adjusting for variation in demographic factors, psychopathology, medication, and substance use. Bonferroni correction for multiple testing was applied.

RESULTS

At baseline, 66.6% of the patients smoked, compared with 38.3% of the siblings and 25.2% of the control subjects. Significant multi-cross-sectional associations were found between smoking and lower processing speed in the patient and control groups compared with the nonsmoking patient group (estimate=-2.38, SE=0.84) and the nonsmoking control group (estimate=-3.13, SE=1.06). In siblings, smoking was significantly associated with lower performance in working memory and reasoning and problem solving compared with nonsmoking. Also, the number of cigarettes smoked per day was negatively associated with these domains. Patients, but not siblings and control subjects, who quit smoking showed a significant improvement in processing speed (estimate=4.90, SE=1.73).

CONCLUSIONS

The study findings indicate that smoking is associated with poorer cognitive performance in patients, their siblings, and healthy control subjects compared with nonsmoking. Smoking cessation may improve processing speed in patients.

Genetic vulnerability to DUSP22 promoter hypermethylation is involved in the relation between in utero famine exposure and schizophrenia

Epigenetic changes may account for the doubled risk to develop schizophrenia in individuals exposed to famine in utero. We therefore investigated DNA methylation in a unique sample of patients and healthy individuals conceived during the great famine in China. Subsequently, we examined two case-control samples without famine exposure in whole blood and brain tissue. To shed light on the causality of the relation between famine exposure and DNA methylation, we exposed human fibroblasts to nutritional deprivation. In the famine-exposed schizophrenia patients, we found significant hypermethylation of the dual specificity phosphatase 22 (DUSP22) gene promoter (Chr6:291687-293285) (N = 153, p = 0.01). In this sample, DUSP22 methylation was also significantly higher in patients independent of famine exposure (p = 0.025), suggesting that hypermethylation of DUSP22 is also more generally involved in schizophrenia risk. Similarly, DUSP22 methylation was also higher in two separate case-control samples not exposed to famine using DNA from whole blood (N = 64, p = 0.03) and postmortem brains (N = 214, p = 0.007). DUSP22 methylation showed strong genetic regulation across chromosomes by a region on chromosome 16 which was consistent with new 3D genome interaction data. The presence of a direct link between famine and DUSP22 transcription was supported by data from cultured human fibroblasts that showed increased methylation (p = 0.048) and expression (p = 0.019) in response to nutritional deprivation (N = 10). These results highlight an epigenetic locus that is genetically regulated across chromosomes and that is involved in the response to early-life exposure to famine and that is relevant for a major psychiatric disorder.

At-risk individuals display altered brain activity following stress

Stress is a major risk factor for almost all psychiatric disorders, however, the underlying neurobiological mechanisms remain largely elusive. In healthy individuals, a successful stress response involves an adequate neuronal adaptation to a changing environment. This adaptive response may be dysfunctional in vulnerable individuals, potentially contributing to the development of psychopathology. In the current study, we investigated brain responses to emotional stimuli following stress in healthy controls and at-risk individuals. An fMRI study was conducted in healthy male controls (N = 39) and unaffected healthy male siblings of schizophrenia patients (N = 39) who are at increased risk for the development of a broad range of psychiatric disorders. Brain responses to pictures from the International Affective Picture System (IAPS) were measured 33 min after exposure to stress induced by the validated trier social stress test (TSST) or a control condition. Stress-induced levels of cortisol, alpha-amylase, and subjective stress were comparable in both groups. Yet, stress differentially affected brain responses of schizophrenia siblings versus controls. Specifically, control subjects, but not schizophrenia siblings, showed reduced brain activity in key nodes of the default mode network (PCC/precuneus and mPFC) and salience network (anterior insula) as well as the STG, MTG, MCC, vlPFC, precentral gyrus, and cerebellar vermis in response to all pictures following stress. These results indicate that even in the absence of a psychiatric disorder, at-risk individuals display abnormal functional activation following stress, which in turn may increase their vulnerability and risk for adverse outcomes.

Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10^-21), left fusiform gyrus (d=-0.288; P=8.25 × 10^-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10^-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

The role of cognitive functioning in the relationship between childhood trauma and a mixed phenotype of affective-anxious-psychotic symptoms in psychotic disorders

Cognitive impairments in patients with psychotic disorder have been associated with poor functioning and increased symptom severity. Furthermore, childhood trauma (CT) exposure has been associated with worse cognitive functioning as well as co-occurrence of affective-anxious-psychosis symptoms or a 'mixed phenotype of psychopathology' (MP), which in turn is associated with greater symptom severity, and poor functioning. This study aims to evaluate if cognition could be associated with CT/MP. 532 patients with non-affective psychotic patients were assessed on CT, symptom profile, cognition, functioning, and symptom severity at baseline and 3 and 6-year follow-up. Four subgroups were made according to trauma exposure (CT- or CT+) and presence of a mixed phenotype (MP- or MP+): CT-/MP (n=272), CT-/MP+ (n=157), CT+/MP- (n=49), and CT+/MP+ (n=54). Mixed-effects multilevel regression, linear regression, and Tobit analyses were performed. Patients with both CT and MP showed lower verbal learning and memory than CT-/MP+ individuals (p<0.001). No other significant differences were found among the 4 subgroups. No cognitive decline was found at follow-up, neither in the CT+/MP- nor in CT-/MP- group. Lower cognition was not associated with increased symptom severity or poor functioning at follow-up, neither in the CT+/MP- nor in CT-/MP- group. Although cognitive impairments and CT may be related to clinical or functional features of psychotic disorder, and cognitive functioning could be affected by CT exposure, cognition does not discriminate subgroups of patients stratified by CT exposure and MP.

Brain morphology in antipsychotic-naïve schizophrenia: A study of multiple brain structures

Background

Although brain volume changes are found in schizophrenia, only a limited number of structural magnetic resonance imaging studies have exclusively examined antipsychotic-naïve patients.

Aims

To comprehensively investigate multiple brain structures in a single sample of patients who were antipsychotic-naïve.

Method

Twenty antipsychotic-naïve patients with first-episode schizophrenia and 20 healthy comparison subjects were included. Intracranial, total brain, frontal lobe, grey and white matter, cerebellar, hippocampal, parahippocampal, thalamic, caudate nucleus and lateral and third ventricular volumes were measured. Repeated-measures analyses of (co)variance were conducted with intracranial volume as covariate.

Results

Third ventricle volume enlargement was found in patients compared with the healthy subjects. No differences were found in other brain regions.

Conclusions

These findings suggest that some brain abnormalities are present in the early stages of schizophrenia. Moreover, it suggests that brain abnormalities reported in patients with chronic schizophrenia develop in a later stage of the disease and/or are medication induced.

Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium

BACKGROUND

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.

METHODS

This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).

RESULTS

Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.

CONCLUSIONS

Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Autism Spectrum and psychosis risk in the 22q11.2 deletion syndrome. Findings from a prospective longitudinal study

BACKGROUND

Individuals with 22q11.2 deletion syndrome (22q11DS) have a 25% risk for schizophrenia and related psychotic disorders. Some have hypothesized that Autism Spectrum Disorders (ASDs) diagnosed in children with 22q11DS may actually represent the social-communicative defects often observed during the early developmental stages of schizophrenia.

METHODS

We prospectively studied 89 children with 22q11DS to test this hypothesis. At baseline, the Autism Diagnostic Interview was used to assess ASD, evaluating both current and early childhood behaviors. At follow-up, the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS) was used to determine development of a psychotic disorder or psychotic symptoms.

RESULTS

The average age (±SD) at first and last assessments was 14.3±1.9 and 19.0±3.0years, respectively. Nineteen (21.3%) children developed a psychotic disorder. Contrary to our hypothesis, there was no significant difference in the proportion that developed a psychotic disorder, comparing those with (n=9, 17.3%) and those without ASD at baseline (n=10, 27%; OR=0.500, 95% CI=0.160-1.569, p=0.235). Similar results were obtained using autistic symptom severity as quantitative predicting variable, psychotic symptoms as the outcome, and when correcting for age, gender and full scale IQ.

CONCLUSION

Results indicate that in children with 22q11DS, early childhood autistic features are not associated with an increased risk for subsequent development of psychotic disorders or symptoms, replicating previous retrospective findings in adults with 22q11DS. These results indicate that ASD and psychotic disorders can emerge independently, as pleiotropic phenotypes in the context of 22q11DS.

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.

Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10-7) and PKP4 (P=8.67 × 10-7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10-3]), SCZ (rg=0.34 [P=4.37 × 10-5]) and MDD (rg=0.57 [P=1.04 × 10-3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.

Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA Schizophrenia consortium

OBJECTIVE

Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia.

METHOD

This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness.

RESULTS

Positive symptom severity was negatively related to STG thickness in both hemispheres (left: β_std = -0.052; P = 0.021; right: β_std = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness.

CONCLUSION

Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

More than 25 years of genetic studies of clozapine-induced agranulocytosis

Clozapine is one of the most effective atypical antipsychotic drugs prescribed to patients with treatment-resistant schizophrenia. Approximately 1% of patients experience potential life-threatening adverse effects in the form of agranulocytosis, greatly hindering its applicability in clinical practice. The etiology of clozapine-induced agranulocytosis (CIA) remains unclear, but is thought to be a heritable trait. We reviewed the genetic studies of CIA published thus far. One recurrent finding from early candidate gene study to more recent genome-wide analysis is that of the involvement of human leukocyte antigen locus. We conclude that CIA is most likely a complex, polygenic trait, which may hamper efforts to the development of a genetic predictor test with clinical relevance. To decipher the genetic architecture of CIA, it is necessary to apply more rigorous standards of phenotyping and study much larger sample sizes.

Educational achievement in psychiatric patients and their siblings: a register-based study in 30 000 individuals in The Netherlands

BACKGROUND

Poor educational achievement is associated with a range of psychiatric disorders. Several studies suggest that this underperformance is due to cognitive deficits that commence before disease onset and reflect a genetic risk for this disorder. However, the specificity and the familial contribution of this cognitive deficit are not clear. We analysed lifetime educational achievement of psychiatric patients diagnosed with schizophrenia, bipolar or depressive disorder and their unaffected siblings.

METHOD

In a register-based case-control study, 1561 patients with schizophrenia, 813 patients with bipolar disorder, 8112 patients with depression, and their siblings were each matched with eight population controls. Patients, siblings and controls were compared on the highest educational stream they completed.

RESULTS

Lower educational achievement was present in schizophrenia patients from primary school onwards [completing primary school: odds ratio (OR) 0.69; completing secondary school: OR 0.69; completing academic education: OR 0.46], compared to patients with bipolar disorder or depression. Siblings of schizophrenia, bipolar or depressed patients showed no underachievement at primary or secondary school, but siblings of schizophrenia patients as well as siblings of depressed patients were less successful in their educational achievement after secondary school (completing academic education, schizophrenia siblings: OR 0.90; depressive disorder siblings: OR 0.91).

CONCLUSIONS

Educational underachievement from primary school onwards is specifically related to schizophrenia and not to bipolar disorder or depression. Moreover, it appears to be a harbinger of the illness, since it is not found in their siblings. These results add to evidence that early cognitive deficits are a distinct feature of the schizophrenia phenotype.