Cognitive intermediate phenotype and genetic risk for psychosis

Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks

Cognitive deficits are prevalent in individuals with psychosis and are associated with neurobiological changes, potentially serving as an endophenotype for psychosis. Using the HCP-Early-Psychosis-dataset (n = 226), we aimed to investigate cognitive subtypes (deficit/intermediate/spared) through data-driven clustering in affective (AP) and non-affective psychosis patients (NAP) and controls (HC). We explored differences between three clusters in symptoms, cognition, medication, and grey matter volume. Applying principal component analysis, we selected features for clustering. Features that explained most variance were scores for intelligence, verbal recognition and comprehension, auditory attention, working memory, reasoning and executive functioning. Fuzzy K-Means clustering on those features revealed that the subgroups significantly varied in cognitive impairment, clinical symptoms, and, importantly, also in medication and grey matter volume in fronto-parietal and subcortical networks. The spared cluster (86%HC, 37%AP, 17%NAP) exhibited unimpaired cognition, lowest symptoms/medication, and grey matter comparable to controls. The deficit cluster (4%HC, 10%AP, 47%NAP) had impairments across all domains, highest symptoms scores/medication dosage, and pronounced grey matter alterations. The intermediate deficit cluster (11%HC, 54%AP, 36%NAP) showed fewer deficits than the second cluster, but similar symptoms/medication/grey matter to the spared cluster. Controlling for medication, cognitive scores correlated with grey matter changes and negative symptoms across all patients. Our findings generally emphasize the interplay between cognition, brain structure, symptoms, and medication in AP and NAP, and specifically suggest a possible mediating role of cognition, highlighting the potential of screening cognitive changes to aid tailoring treatments and interventions.

Cumulative Effect of Psychosis and Aging on Cognitive Function in Patients Diagnosed With Schizophrenia Spectrum Disorders: A Cognitive Domain Approach

BACKGROUND

Schizophrenia spectrum disorders are characterized by cognitive decline, which is evident even in the prodromal phase. Aging is a complex gradual procedure that affects, among other organs, the central nervous system, resulting in age-related cognitive decline.

OBJECTIVE

The objective of this study is to assess the cognitive function of patients diagnosed with psychotic disorders, in comparison with healthy controls, along the age spectrum.

METHODS

Sixty patients diagnosed with schizophrenia spectrum disorders in remission, 20-59 years old, and 60 healthy controls, matched by age and educational level, from the region of Thessaly in Central Greece, were evaluated, with respect to their cognitive performance, using the Greek version of the Montreal Cognitive Assessment (MoCA). Correlations between age and MoCA total and cognitive domains' scores, as well as statistical analysis of variance (ANOVA) and t-test among age groups, were performed using Statistical Product and Service Solutions (SPSS, version 23; IBM SPSS Statistics for Windows, Armonk, NY).

RESULTS

The MoCA score was negatively correlated with age, both in the patients' group (p<0.001) and in the control group (p=0.001). A significant statistical difference in mean MoCA scores between patients and healthy controls was observed, not only in the total sample (p<0.001) but also in all age groups (20-29: p=0.006, 40-49: p=0.024, 50-59: p<0.001), except for age group 30-39 (30-39: p=0.356). Statistically significant differences were also found between patients and healthy controls in the total sample, regarding specific cognitive domains, in the visuospatial and executive function domain (p=0.01), attention domain (p<0.001), language domain (p<0.001), and orientation domain (p<0.005). Interestingly, different deterioration patterns in cognitive domains were observed in each age group. Specifically, in the age group 20-29, statistically significant differences were found between patients and healthy controls in the language domain (p<0.014) and orientation domain (p<0.041). No difference was found in the age group 30-39, while statistically significant differences were found between patients and healthy controls in the age group 40-49 in the attention domain (p<0.001) and language domain (p<0.001). Finally, in the age group 50-59, such differences were found in the visuospatial and executive function domain (p=0.041), attention domain (p=0.006), and language domain (p=0.001). Statistically significant cognitive decline occurs in a shorter period in the patients' group, suggesting an accelerated cognitive decline in psychotic patients after middle age.

CONCLUSIONS

Age-related cognitive decline in psychotic patients occurs at an accelerated rate in relation to the control sample, with age-specific cognitive domain decline patterns, due to the cumulative effect of aging and psychosis on cognition. Further, larger, multicenter research should focus on establishing these results and designing relevant procognitive interventions.

Dissecting Schizotypy and Its Association With Cognition and Polygenic Risk for Schizophrenia in a Nonclinical Sample

Schizotypy is a multidimensional construct that captures a continuum of risk for developing schizophrenia-spectrum psychopathology. Existing 3-factor models of schizotypy, consisting of positive, negative, and disorganized dimensions have yielded mixed evidence of genetic continuity with schizophrenia using polygenic risk scores. Here, we propose an approach that involves splitting positive and negative schizotypy into more specific subdimensions that are phenotypically continuous with distinct positive symptoms and negative symptoms recognized in clinical schizophrenia. We used item response theory to derive high-precision estimates of psychometric schizotypy using 251 self-report items obtained from a non-clinical sample of 727 (424 females) adults. These subdimensions were organized hierarchically using structural equation modeling into 3 empirically independent higher-order dimensions enabling associations with polygenic risk for schizophrenia to be examined at different levels of phenotypic generality and specificity. Results revealed that polygenic risk for schizophrenia was associated with variance specific to delusional experiences (γ = 0.093, P = .001) and reduced social interest and engagement (γ = 0.076, P = .020), and these effects were not mediated via the higher-order general, positive, or negative schizotypy factors. We further fractionated general intellectual functioning into fluid and crystallized intelligence in 446 (246 females) participants that underwent onsite cognitive assessment. Polygenic risk scores explained 3.6% of the variance in crystallized intelligence. Our precision phenotyping approach could be used to enhance the etiologic signal in future genetic association studies and improve the detection and prevention of schizophrenia-spectrum psychopathology.

Analysis of polyunsaturated fatty acids in antipsychotic-free individuals with at-risk mental state and patients with first-episode schizophrenia

Introduction

Abnormalities in membrane phospholipids are considered one of the pathophysiological backgrounds for schizophrenia. This study, explores the fatty acid composition of erythrocyte membranes and its association with clinical characteristics in two groups: individuals with an at-risk mental state (ARMS) and patients experiencing their first-episode of schizophrenia (FES).

Materials and methods

This study measured erythrocyte membrane fatty acids in 72 antipsychotic-free individuals with ARMS, 18 antipsychotic-free patients with FES, and 39 healthy volunteers. Clinical symptoms and cognitive and social functions were assessed using the Positive and Negative Syndrome Scale (PANSS), Brief Assessment of Cognition in Schizophrenia (BACS), Schizophrenia Cognition Rating Scale (SCoRS), and Social and Occupational Functioning Assessment Scale (SOFAS).

Results

Eicosapentaenoic and docosapentaenoic acid levels were lower in the ARMS and FES groups than in the healthy control group. In contrast, nervonic acid (NA) levels were markedly higher in the ARMS and FES groups than in the controls, while only the FES group showed higher levels of arachidonic acid. Oleic acid and NA levels were significantly associated with PANSS scores in both the FES and ARMS groups, particularly for the negative and general subscores. However, the patient groups had no significant associations between the fatty acid composition and the BACS, SCoRS, and SOFAS scores. Furthermore, the baseline fatty acid composition did not differ between the ARMS individuals who later developed psychosis (N = 6) and those who were followed for more than 2 years without developing psychosis onset (N = 30).

Discussion

The findings suggest that abnormal fatty acid compositions may be shared in the early stages of schizophrenia and the clinical high-risk state for psychosis and may serve as vulnerability markers of psychopathology.

Rare CNVs and phenome-wide profiling highlight brain structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleiotropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts. It remains unknown, for example, how distinct CNVs escalate vulnerability for the same developmental and psychiatric disorders. Here we quantitatively dissect the associations between brain organization and behavioural differentiation across 8 key CNVs. In 534 CNV carriers, we explored CNV-specific brain morphology patterns. CNVs were characteristic of disparate morphological changes involving multiple large-scale networks. We extensively annotated these CNV-associated patterns with ~1,000 lifestyle indicators through the UK Biobank resource. The resulting phenotypic profiles largely overlap and have body-wide implications, including the cardiovascular, endocrine, skeletal and nervous systems. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

Cognitive Dysfunction as a Risk Factor for Psychosis

The current chapter summarizes recent evidence for cognition as a risk factor for the development of psychosis, including the range of cognitive impairments that exist across the spectrum of psychosis risk symptoms. The chapter examines several possible theories linking cognitive deficits with the development of psychotic symptoms, including evidence that cognitive deficits may be an intermediate risk factor linking genetic and/or neural metrics to psychosis spectrum symptoms. Although there is not strong evidence for unique cognitive markers associated specifically with psychosis compared to other forms of psychopathology, psychotic disorders are generally associated with the greatest severity of cognitive deficits. Cognitive deficits precede the development of psychotic symptoms and may be detectable as early as childhood. Across the psychosis spectrum, both the presence and severity of psychotic symptoms are associated with mild to moderate impairments across cognitive domains, perhaps most consistently for language, cognitive control, and working memory domains. Research generally indicates the size of these cognitive impairments worsens as psychosis symptom severity increases. The chapter points out areas of unclarity and unanswered questions in each of these areas, including regarding the mechanisms contributing to the association between cognition and psychosis, the timing of deficits, and whether any cognitive systems can be identified that function as specific predictors of psychosis risk symptoms.

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

Sex-Related Differences in White Matter Asymmetry and Its Implications for Verbal Working Memory in Psychosis High-Risk State

Objective: Sexual dimorphism has been investigated in schizophrenia, although sex-specific differences among individuals who are at clinical high-risk (CHR) for developing psychosis have been inconclusive. This study aims to characterize sexual dimorphism of language areas in the brain by investigating the asymmetry of four white matter tracts relevant to verbal working memory in CHR patients compared to healthy controls (HC). HC typically show a leftward asymmetry of these tracts. Moreover, structural abnormalities in asymmetry and verbal working memory dysfunctions have been associated with neurodevelopmental abnormalities and are considered core features of schizophrenia. Methods: Twenty-nine subjects with CHR (17 female/12 male) for developing psychosis and twenty-one HC (11 female/10 male) matched for age, sex, and education were included in the study. Two-tensor unscented Kalman filter tractography, followed by an automated, atlas-guided fiber clustering approach, were used to identify four fiber tracts related to verbal working memory: the superior longitudinal fasciculi (SLF) I, II and III, and the superior occipitofrontal fasciculus (SOFF). Using fractional anisotropy (FA) of tissue as the primary measure, we calculated the laterality index for each tract. Results: There was a significantly greater right>left asymmetry of the SLF-III in CHR females compared to HC females, but no hemispheric difference between CHR vs. HC males. Moreover, the laterality index of SLF-III for CHR females correlated negatively with Backward Digit Span performance, suggesting a greater rightward asymmetry was associated with poorer working memory functioning. Conclusion: This study suggests increased rightward asymmetry of the SLF-III in CHR females. This finding of sexual dimorphism in white matter asymmetry in a language-related area of the brain in CHR highlights the need for a deeper understanding of the role of sex in the high-risk state. Future work investigating early sex-specific pathophysiological mechanisms, may lead to the development of novel personalized treatment strategies aimed at preventing transition to a more chronic and difficult-to-treat disorder.

A systematic review of research on neuropsychological measures in psychotic disorders from low and middle-income countries: The question of clinical utility

INTRODUCTION

Several studies of neuropsychological measures have been undertaken in patients with psychotic disorders from low- and middle-income countries (LMICs). It is, however, unclear if the measures used in these studies are appropriate for cognitive screening in clinical settings. We undertook a systematic review to determine if measures investigated in research on psychotic disorders in LMICs meet the clinical utility criteria proposed by The Working Group on Screening and Assessment.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses were employed. We determined if tests had been validated against a comprehensive test battery, the duration and scope of the tests, the personnel administering the tests, and the means of administration.

RESULTS

A total of 31 articles were included in the review, of which 11 were from Africa. The studies included 3254 participants with psychosis and 1331 controls. 3 studies reported on the validation of the test against a comprehensive cognitive battery. Assessments took 1 h or less to administer in 6/31 studies. The average number of cognitive domains assessed was four. Nonspecialized staff were used in only 3/31 studies, and most studies used pen and paper tests (17/31).

CONCLUSION

Neuropsychological measures used in research on psychotic disorders in LMICs typically do not meet the Working Group on Screening and Assessment clinical utility criteria for cognitive screening. Measures that have been validated in high-income countries but not in LMICs that do meet these criteria, such as the Brief Assessment of Cognition in Schizophrenia, therefore deserve further study in LMIC settings.

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects

BACKGROUND

Evidence suggests that the AKT1 gene may modulate the degree to which cannabis use induces cognitive alterations in patients with a psychotic disorder.

AIM

To examine the interplay between AKT1 and cannabis use in terms of the cognitive performance of the general population.

METHODS

Our sample consisted of 389 Spanish university students. Sustained attention was measured via the Continuous Performance Test-Identical Pairs, immediate and delayed verbal memory with the Logical Memory subtest of the Wechsler Memory Scale, and working memory with the Wisconsin Card Sorting Test. Lifetime cannabis use frequency was assessed and individuals were classified as cannabis users or non-users. Two single nucleotide polymorphisms of the AKT1 gene were genotyped and, according to previous studies, each subject was defined as a carrier of two, one or no copies of the haplotype (rs2494732(C)-rs1130233(A)). Multiple linear regressions were conducted to test the effect of the genetic variability and cannabis use (and their interaction) on cognitive performance.

RESULTS

An effect of the AKT1 haplotype was found on attention scores: individuals with two copies of the haplotype performed better (β=0.18, p<0.001 (adjusted for false discovery rate)), while neither cannabis nor the AKT1-cannabis interaction was associated with attention. No effect of AKT1, cannabis or the AKT1-cannabis interaction was found on verbal memory or working memory.

CONCLUSIONS

Our study provides additional evidence that AKT1 modulates cognitive performance. However, in our non-clinical sample, the previously reported interaction between cannabis use and the AKT1 gene was not replicated.

A Pattern of Cognitive Deficits Stratified for Genetic and Environmental Risk Reliably Classifies Patients With Schizophrenia From Healthy Control Subjects

BACKGROUND

Schizophrenia risk is associated with both genetic and environmental risk factors. Furthermore, cognitive abnormalities are established core characteristics of schizophrenia. We aim to assess whether a classification approach encompassing risk factors, cognition, and their associations can discriminate patients with schizophrenia (SCZs) from healthy control subjects (HCs). We hypothesized that cognition would demonstrate greater HC-SCZ classification accuracy and that combined gene-environment stratification would improve the discrimination performance of cognition.

METHODS

Genome-wide association study-based genetic, environmental, and neurocognitive classifiers were trained to separate 337 HCs from 103 SCZs using support vector classification and repeated nested cross-validation. We validated classifiers on independent datasets using within-diagnostic (SCZ) and cross-diagnostic (clinically isolated syndrome for multiple sclerosis, another condition with cognitive abnormalities) approaches. Then, we tested whether gene-environment multivariate stratification modulated the discrimination performance of the cognitive classifier in iterative subsamples.

RESULTS

The cognitive classifier discriminated SCZs from HCs with a balanced accuracy (BAC) of 88.7%, followed by environmental (BAC = 65.1%) and genetic (BAC = 55.5%) classifiers. Similar classification performance was measured in the within-diagnosis validation sample (HC-SCZ BACs, cognition = 70.5%; environment = 65.8%; genetics = 49.9%). The cognitive classifier was relatively specific to schizophrenia (HC-clinically isolated syndrome for multiple sclerosis BAC = 56.7%). Combined gene-environment stratification allowed cognitive features to classify HCs from SCZs with 89.4% BAC.

CONCLUSIONS

Consistent with cognitive deficits being core features of the phenotype of SCZs, our results suggest that cognitive features alone bear the greatest amount of information for classification of SCZs. Consistent with genes and environment being risk factors, gene-environment stratification modulates HC-SCZ classification performance of cognition, perhaps providing another target for refining early identification and intervention strategies.

Developmental Genes and Regulatory Proteins, Domains of Cognitive Impairment in Schizophrenia Spectrum Psychosis and Implications for Antipsychotic Drug Discovery: The Example of Dysbindin-1 Isoforms and Beyond

Alongside positive and negative symptomatology, deficits in working memory, attention, selective learning processes, and executive function have been widely documented in schizophrenia spectrum psychosis. These cognitive abnormalities are strongly associated with impairment across multiple function domains and are generally treatment-resistant. The DTNBP1 (dystrobrevin-binding protein-1) gene, encoding dysbindin, is considered a risk factor for schizophrenia and is associated with variation in cognitive function in both clinical and nonclinical samples. Downregulation of DTNBP1 expression in dorsolateral prefrontal cortex and hippocampal formation of patients with schizophrenia has been suggested to serve as a primary pathophysiological process. Described as a "hub," dysbindin is an important regulatory protein that is linked with multiple complexes in the brain and is involved in a wide variety of functions implicated in neurodevelopment and neuroplasticity. The expression pattern of the various dysbindin isoforms (-1A, -1B, -1C) changes depending upon stage of brain development, tissue areas and subcellular localizations, and can involve interaction with different protein partners. We review evidence describing how sequence variation in DTNBP1 isoforms has been differentially associated with schizophrenia-associated symptoms. We discuss results linking these isoform proteins, and their interacting molecular partners, with cognitive dysfunction in schizophrenia, including evidence from drosophila through to genetic mouse models of dysbindin function. Finally, we discuss preclinical evidence investigating the antipsychotic potential of molecules that influence dysbindin expression and functionality. These studies, and other recent work that has extended this approach to other developmental regulators, may facilitate identification of novel molecular pathways leading to improved antipsychotic treatments.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Comparison of cognitive functions between first-episode schizophrenia patients, their unaffected siblings and individuals at clinical high-risk for psychosis

BACKGROUND

Cognitive impairment is a core feature of schizophrenia and has been observed in both familial (FHR) and clinical high-risk (CHR) samples. Nonetheless, there is a paucity of research directly contrasting cognitive profiles in these two high-risk states and first-episode schizophrenia. This study aimed to compare cognitive functions in patients with first-episode schizophrenia-spectrum disorder (FES), their unaffected siblings (FHR), CHR individuals and healthy controls.

METHOD

A standardized battery of cognitive assessments was administered to 69 FES patients, 71 help-seeking CHR individuals without family history of psychotic disorder, 50 FHR participants and 68 controls. FES and CHR participants were recruited from territory-wide early intervention service for psychosis in Hong Kong. CHR status was ascertained using Comprehensive Assessment of At-Risk Mental State.

RESULTS

Among four groups, FES patients displayed the largest global cognitive impairment and had medium-to-large deficits across all cognitive tests relative to controls. CHR and FHR participants significantly underperformed in most cognitive tests than controls. Among various cognitive tests, digit symbol coding demonstrated the greatest magnitude of impairment in FES and CHR groups compared with controls. No significant difference between two high-risk groups was observed in global cognition and all individual cognitive tests except digit symbol coding which showed greater deficits in CHR than in FHR participants.

CONCLUSION

Clinical and familial risk groups experienced largely comparable cognitive impairment that was intermediate between FES and controls. Digit symbol coding may have the greatest discriminant capacity in distinguishing FES and CHR from healthy controls, and between two high-risk samples.

Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia

Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity within schizophrenia. This has primarily been done using risk score profiling, which aggregates effects across all variants into a single predictor. While effective, this method lacks flexibility in certain domains: risk scores cannot capture nonlinear effects and do not employ any variable selection. We used random forest, an algorithm with this flexibility designed to maximize predictive power, to predict 6 cognitive endophenotypes in a combined sample of psychiatric patients and controls (N = 739) using 77 genetic variants strongly associated with schizophrenia. Tenfold cross-validation was applied to the discovery sample and models were externally validated in an independent sample of similar ancestry (N = 336). Linear approaches, including linear regression and task-specific polygenic risk scores, were employed for comparison. Random forest models for processing speed (P = .019) and visual memory (P = .036) and risk scores developed for verbal (P = .042) and working memory (P = .037) successfully generalized to an independent sample with similar predictive strength and error. As such, we suggest that both methods may be useful for mapping a limited set of predetermined, disease-associated SNPs to related phenotypes. Incorporating random forest and other more flexible algorithms into genotype-phenotype mapping inquiries could contribute to parsing heterogeneity within schizophrenia; such algorithms can perform as well as standard methods and can capture a more comprehensive set of potential relationships.

Cognitive genomics: Searching for the genetic roots of neuropsychological functioning

OBJECTIVE

Human cognition has long been known to be under substantial genetic control. With the complete mapping of the human genome, genome-wide association studies for many complex traits have proliferated; however, the highly polygenic nature of intelligence has made the identification of the precise genes that influence both global and specific cognitive abilities more difficult than anticipated.

METHOD

Here, we review the latest developments in the genomics of cognition, including a discussion of methodological advances in the genetic analysis of complex traits, and shared genetic contributions to cognitive abilities and neuropsychiatric disorders.

RESULTS

A wealth of twin and family studies have provided compelling evidence for a strong heritable component of both global and specific cognitive abilities, and for the existence of "generalist genes" responsible for a large portion of the variance in diverse cognitive abilities. Increasingly sophisticated analytic tools and ever-larger sample sizes are now facilitating the identification of specific genetic and molecular underpinnings of cognitive abilities, leading to optimism regarding possibilities for novel treatments for illnesses related to cognitive function.

CONCLUSIONS

We conclude with a set of future directions for the field, which will further accelerate discoveries regarding the biological pathways relevant to cognitive abilities. These, in turn, may be further interrogated in order to link biological mechanisms to behavior. (PsycINFO Database Record

Evidence that polygenic risk for psychotic disorder is expressed in the domain of neurodevelopment, emotion regulation and attribution of salience

BACKGROUND

The liability-threshold model of psychosis risk predicts stronger phenotypic manifestation of the polygenic risk score (PRS) in the healthy relatives of patients, as compared with healthy comparison subjects.

METHODS

First-degree relatives of patients with psychotic disorder (871 siblings and 812 parents) and healthy comparison subjects (n = 523) were interviewed three times in 6 years. Repeated measures of two psychosis phenotypes, the Community Assessment of Psychic Experiences (CAPE; self-report - subscales of positive, negative and depressive symptoms) and the Structured Interview for Schizotypy - Revised (SIS-R; clinical interview - subscales of positive and negative schizotypy), were examined for association with PRS. Interview-based lifetime rate of depressive and manic episodes were also examined, as was association with repeated measures of intelligence quotient (IQ).

RESULTS

In the relatives, PRS was associated with CAPE/SIS-R total score (respectively, B = 0.12, 95% CI 0.02-0.22 and B = 0.11, 95% CI 0.02-0.20), the SIS-R positive subscale (B = 0.16, 95% CI 0.04-0.28), the CAPE depression subscale (B = 0.21, 95% CI 0.07-0.34), any lifetime affective episode (OR 3.1, 95% CI 1.04-9.3), but not with IQ (B = -1.8, 95% CI -8.0 to 4.4). In the controls, similar associations were apparent between PRS on the one hand and SIS-R total score, SIS-R positive, SIS-R negative, any lifetime affective episode and, in contrast, lower IQ (B = -8.5, 95% CI -15.5 to -1.6).

CONCLUSIONS

In non-ill people, polygenic risk for psychotic disorder is expressed pleiotropically in the domain of neurodevelopment, emotion regulation and attribution of salience. In subjects at elevated genetic risk, emerging expression of neurodevelopmental alterations may create floor effects, obscuring genetic associations.

IQ, the Urban Environment, and Their Impact on Future Schizophrenia Risk in Men

Exposure to an urban environment during early life and low IQ are 2 well-established risk factors for schizophrenia. It is not known, however, how these factors might relate to one another. Data were pooled from the North Jutland regional draft board IQ assessments and the Danish Conscription Registry for men born between 1955 and 1993. Excluding those who were followed up for less than 1 year after the assessment yielded a final cohort of 153170 men of whom 578 later developed a schizophrenia spectrum disorder. We found significant effects of having an urban birth, and also experiencing an increase in urbanicity before the age of 10 years, on adult schizophrenia risk. The effect of urban birth was independent of IQ. However, there was a significant interaction between childhood changes in urbanization in the first 10 years and IQ level on the future adult schizophrenia risk. In short, those subjects who moved to more or less urban areas before their 10th birthday lost the protective effect of IQ. When thinking about adult schizophrenia risk, the critical time window of childhood sensitivity to changes in urbanization seems to be linked to IQ. Given the prediction that by 2050, over 80% of the developed world's population will live in an urban environment, this represents a major future public health issue.

Working Memory in Unaffected Relatives of Patients With Schizophrenia: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies

Working memory deficits, a core cognitive feature of schizophrenia may arise from dysfunction in the frontal and parietal cortices. Numerous studies have also found abnormal neural activation during working memory tasks in patients' unaffected relatives. The aim of this study was to systematically identify and anatomically localize the evidence for those activation differences across all eligible studies. Fifteen functional magnetic resonance imaging (fMRI) manuscripts, containing 16 samples of 289 unaffected relatives of patients with schizophrenia, and 358 healthy controls were identified that met our inclusion criteria: (1) used a working memory task; and (2) reported standard space coordinates. Activation likelihood estimation (ALE) identified convergence across studies. Compared to healthy controls, patients' unaffected relatives showed decreases in neural activation in the right middle frontal gyrus (BA9), as well as right inferior frontal gyrus (BA44). Increased activation was seen in relatives in the right frontopolar (BA10), left inferior parietal lobe (BA40), and thalamus bilaterally. These results suggest that the familial risk of schizophrenia is expressed in changes in neural activation in the unaffected relatives in the cortical-subcortical working memory network that includes, but is not restricted to the middle prefrontal cortex.

Working memory circuit as a function of increasing age in healthy adolescence: A systematic review and meta-analyses

Working memory ability matures through puberty and early adulthood. Deficits in working memory are linked to the risk of onset of neurodevelopmental disorders such as schizophrenia, and there is a significant temporal overlap between the peak of first episode psychosis risk and working memory maturation. In order to characterize the normal working memory functional maturation process through this critical phase of cognitive development we conducted a systematic review and coordinate based meta-analyses of all the available primary functional magnetic resonance imaging studies (n = 382) that mapped WM function in healthy adolescents (10–17 years) and young adults (18–30 years). Activation Likelihood Estimation analyses across all WM tasks revealed increased activation with increasing subject age in the middle frontal gyrus (BA6) bilaterally, the left middle frontal gyrus (BA10), the left precuneus and left inferior parietal gyri (BA7; 40). Decreased activation with increasing age was found in the right superior frontal (BA8), left junction of postcentral and inferior parietal (BA3/40), and left limbic cingulate gyrus (BA31). These results suggest that brain activation during adolescence increased with age principally in higher order cortices, part of the core working memory network, while reductions were detected in more diffuse and potentially more immature neural networks. Understanding the process by which the brain and its cognitive functions mature through healthy adulthood may provide us with new clues to understanding the vulnerability to neurodevelopmental disorders.

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Healthy working memory functional maturation process in adolescence

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Brain activation increased with age in higher order cortices.

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Activation decreased in more diffuse and potentially more immature networks.

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Provide new clues to understanding vulnerability to neurodevelopmental disorders