A new role for endophenotypes in the GWAS era: functional characterization of risk variants

Dual-systems models of the genetic architecture of impulsive personality traits: neurogenetic evidence of distinct but related factors

BACKGROUND

Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted.

METHODS

Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared.

RESULTS

GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes.

CONCLUSIONS

Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.

Is auditory processing measured by the N100 an endophenotype for psychosis? A family study and a meta-analysis

BACKGROUND

The N100, an early auditory event-related potential, has been found to be altered in patients with psychosis. However, it is unclear if the N100 is a psychosis endophenotype that is also altered in the relatives of patients.

METHODS

We conducted a family study using the auditory oddball paradigm to compare the N100 amplitude and latency across 243 patients with psychosis, 86 unaffected relatives, and 194 controls. We then conducted a systematic review and a random-effects meta-analysis pooling our results and 14 previously published family studies. We compared data from a total of 999 patients, 1192 relatives, and 1253 controls in order to investigate the evidence and degree of N100 differences.

RESULTS

In our family study, patients showed reduced N100 amplitudes and prolonged N100 latencies compared to controls, but no significant differences were found between unaffected relatives and controls. The meta-analysis revealed a significant reduction of the N100 amplitude and delay of the N100 latency in both patients with psychosis (standardized mean difference [s.m.d.] = -0.48 for N100 amplitude and s.m.d. = 0.43 for N100 latency) and their relatives (s.m.d. = - 0.19 for N100 amplitude and s.m.d. = 0.33 for N100 latency). However, only the N100 latency changes in relatives remained significant when excluding studies with affected relatives.

CONCLUSIONS

N100 changes, especially prolonged N100 latencies, are present in both patients with psychosis and their relatives, making the N100 a promising endophenotype for psychosis. Such changes in the N100 may reflect changes in early auditory processing underlying the etiology of psychosis.

404-error "Disease not found": Unleashing the translational potential of -omics approaches beyond traditional disease classification in heart failure research

The emergence of personalized medicine, facilitated by the progress in -omics technologies, has initiated a new era in medical diagnostics and treatment. This review examines the potential of -omics approaches in heart failure, a condition that has not yet fully capitalized on personalized strategies compared to other medical fields like cancer therapy. Here, we argue that integrating multi-omics technology with systems medicine approaches could fundamentally transform heart failure management, moving away from the traditional paradigm of 'one size fits all'. Our review examines how omics can enhance understanding of heart failure's molecular foundations and contribute to a more comprehensive disease classification. We draw attention to the current state of medical practice that only relies on clinical evidence and a number of standard laboratory tests. At the same time, we propose a shift towards a universal approach that uses quantitative data from multi-omics to unravel complex molecular interactions. The discussion centres around the potential of the transition as a means to enhance individual risk assessment and emphasizes management within clinical settings. While the use of omics in cardiovascular research is not recent, many past studies have focused only on a single omics approach. In order to achieve a better understanding of disease mechanisms, we explore more holistic approaches using genomics, transcriptomics, epigenomics, and proteomics. This review concludes with a call to action to adopt multi-omics in clinical trials and practice to pave the way for more personalized disease management and more effective heart failure interventions.

SLCO5A1 and synaptic assembly genes contribute to impulsivity in juvenile myoclonic epilepsy

Elevated impulsivity is a key component of attention-deficit hyperactivity disorder (ADHD), bipolar disorder and juvenile myoclonic epilepsy (JME). We performed a genome-wide association, colocalization, polygenic risk score, and pathway analysis of impulsivity in JME (n = 381). Results were followed up with functional characterisation using a drosophila model. We identified genome-wide associated SNPs at 8q13.3 (P = 7.5 × 10-9) and 10p11.21 (P = 3.6 × 10-8). The 8q13.3 locus colocalizes with SLCO5A1 expression quantitative trait loci in cerebral cortex (P = 9.5 × 10-3). SLCO5A1 codes for an organic anion transporter and upregulates synapse assembly/organisation genes. Pathway analysis demonstrates 12.7-fold enrichment for presynaptic membrane assembly genes (P = 0.0005) and 14.3-fold enrichment for presynaptic organisation genes (P = 0.0005) including NLGN1 and PTPRD. RNAi knockdown of Oatp30B, the Drosophila polypeptide with the highest homology to SLCO5A1, causes over-reactive startling behaviour (P = 8.7 × 10-3) and increased seizure-like events (P = 6.8 × 10-7). Polygenic risk score for ADHD genetically correlates with impulsivity scores in JME (P = 1.60 × 10-3). SLCO5A1 loss-of-function represents an impulsivity and seizure mechanism. Synaptic assembly genes may inform the aetiology of impulsivity in health and disease.

Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors

Background

Dual-systems models provide a parsimonious framework for understanding the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychiatric disorders. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted.

Methods

Using extant IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between results of multivariate GWAS of dual-systems factors and GWAS of relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were calculated and compared.

Results

Evaluation of GenomicSEM model fit indices for dual-systems models suggested that these models highlight important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences ( r g =.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g., lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). However, no significant associations were observed for subcortical phenotypes inconsistent with hypothesized functional localization of dual-systems constructs.

Conclusions

Dual-systems models of the genetic architecture of IPTs tested here demonstrate evidence of shared and unique genetic influences and associations with relevant neuroimaging phenotypes. These findings emphasize potential advantages in utilizing dual-systems models to study genetic influences for IPTs and transdiagnostic associations with psychiatric disorders.

Genetic and Environmental Influence on the Human Functional Connectome

Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. We analyzed resting-state functional magnetic resonance imaging data from two adult twin samples (Nos = 446 and 371) to quantify genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35 000 functional connections). Nonshared environmental influence was high across the whole connectome. Approximately 14-22% of connections had nominally significant genetic influence in each sample, 4.6% were significant in both samples, and 1-2% had heritability estimates greater than 30%. Evidence of shared environmental influence was weak. Genetic influences on connections were distinct from genetic influences on a global summary measure of the connectome, network-based estimates of connectivity, and movement during the resting-state scan, as revealed by a novel connectome-wide bivariate genetic modeling procedure. The brain's genetic organization is diverse and not as one would expect based solely on structure evident in nongenetically informative data or lower resolution data. As follow-up, we make novel classifications of functional connections and examine highly localized connections with particularly strong genetic influence. This high-resolution genetic taxonomy of brain connectivity will be useful in understanding genetic influences on brain disorders.

Inclusion of endophenotypes in a standard GWAS facilitate a detailed mechanistic understanding of genetic elements that control blood lipid levels

Dyslipidemia is the primary cause of cardiovascular disease, which is a serious human health problem in large parts of the world. Therefore, it is important to understand the genetic and molecular mechanisms that regulate blood levels of cholesterol and other lipids. Discovery of genetic elements in the regulatory machinery is often based on genome wide associations studies (GWAS) focused on end-point phenotypes such as total cholesterol level or a disease diagnosis. In the present study, we add endophenotypes, such as serum levels of intermediate metabolites in the cholesterol synthesis pathways, to a GWAS analysis and use the pig as an animal model. We do this to increase statistical power and to facilitate biological interpretation of results. Although the study population was limited to ~ 300 individuals, we identify two genome-wide significant associations and ten suggestive associations. Furthermore, we identify 28 tentative associations to loci previously associated with blood lipids or dyslipidemia associated diseases. The associations with endophenotypes may inspire future studies that can dissect the biological mechanisms underlying these previously identified associations and add a new level of understanding to previously identified associations.

Genetic architecture of Alzheimer's disease

Advances in genetic and genomic technologies over the last thirty years have greatly enhanced our knowledge concerning the genetic architecture of Alzheimer's disease (AD). Several genes including APP, PSEN1, PSEN2, and APOE have been shown to exhibit large effects on disease susceptibility, with the remaining risk loci having much smaller effects on AD risk. Notably, common genetic variants impacting AD are not randomly distributed across the genome. Instead, these variants are enriched within regulatory elements active in human myeloid cells, and to a lesser extent liver cells, implicating these cell and tissue types as critical to disease etiology. Integrative approaches are emerging as highly effective for identifying the specific target genes through which AD risk variants act and will likely yield important insights related to potential therapeutic targets in the coming years. In the future, additional consideration of sex- and ethnicity-specific contributions to risk as well as the contribution of complex gene-gene and gene-environment interactions will likely be necessary to further improve our understanding of AD genetic architecture.

Conceptualization of Heterogeneity of Chronic Diseases and Atherosclerosis as a Pathway to Precision Medicine: Endophenotype, Endotype, and Residual Cardiovascular Risk

The article discusses modern approaches to the conceptualization of pathogenetic heterogeneity in various branches of medical science. The concepts of endophenotype, endotype, and residual cardiovascular risk and the scope of their application in internal medicine and cardiology are considered. Based on the latest results of studies of the genetic architecture of atherosclerosis, five endotypes of atherosclerosis have been proposed. Each of the presented endotypes represents one or another pathophysiological mechanism of atherogenesis, having an established genetic substrate, a characteristic panel of biomarkers, and a number of clinical features. Clinical implications and perspectives for the study of endotypes of atherosclerosis are briefly reviewed.

Depression genetic risk score is associated with anhedonia-related markers across units of analysis

Investigations of pathophysiological mechanisms implicated in vulnerability to depression have been negatively impacted by the significant heterogeneity characteristic of psychiatric syndromes. Such challenges are also reflected in numerous null findings emerging from genome-wide association studies (GWAS) of depression. Bolstered by increasing sample sizes, recent GWAS studies have identified genetics variants linked to MDD. Among them, Okbay and colleagues (Nat. Genet. 2016 Jun;48(6):624-33) identified genetic variants associated with three well-validated depression-related phenotypes: subjective well-being, depressive symptoms, and neuroticism. Despite this progress, little is known about psychopathological and neurobiological mechanisms underlying such risk. To fill this gap, a genetic risk score (GRS) was computed from the Okbay's study for a sample of 88 psychiatrically healthy females. Across two sessions, participants underwent two well-validated psychosocial stressors, and performed two separate tasks probing reward learning both before and after stress. Analyses tested whether GRS scores predicted anhedonia-related phenotypes across three units of analyses: self-report (Snaith Hamilton Pleasure Scale), behavior (stress-induced changes in reward learning), and circuits (stress-induced changes in striatal reward prediction error; striatal volume). GRS scores were negatively associated with anhedonia-related phenotypes across all units of analyses but only circuit-level variables were significant. In addition, the amount of explained variance was systematically larger as variables were putatively closer to the effects of genes (self-report < behavior < neural circuitry). Collectively, findings implicate anhedonia-related phenotypes and neurobiological mechanisms in increased depression vulnerability, and highlight the value of focusing on fundamental dimensions of functioning across different units of analyses.

Longitudinal trajectory of early functional recovery in patients with first episode psychosis

BACKGROUND

There is a large variability in the recovery trajectory and outcome of first episode of psychosis [FEP] patients. To date, individuals' outcome trajectories at early stage of illness and potential risk factors associated with a poor outcome trajectory are largely unknown. This study aims to apply three separate predictors (positive symptoms, negative symptoms, and soft neurological signs) to identify homogeneous function outcome trajectories in patients with FEP using objective data-driven methods, and to explore the potential risk /protective factors associated with each trajectory.

METHODS

A total of 369 first episode patients (93% antipsychotic naive) were included in the baseline assessments and followed-up at 4-8 weeks, 6 months, and 1 year. K means cluster modeling for longitudinal data (kml3d) was used to identify distinct, homogeneous clusters of functional outcome trajectories. Patients with at least 3 assessments were included in the trajectory analyses (N = 129). The Scale for the Assessment of Negative Symptoms (SANS), Scale for the Assessment of Positive Symptoms (SAPS), and Neurological examination abnormalities (NEA) were used as predictors against Global Assessment of Functioning Scale (GAF).

RESULTS

In each of the three predictor models, four distinct functional outcome trajectories emerged: "Poor", "Intermediate", High" and "Catch-up". Individuals with male gender; ethnic minority status; low premorbid adjustment; low executive function/IQ, low SES, personality disorder, substance use history may be risk factors for poor recovery.

CONCLUSIONS

Functioning recovery in individuals with FEP is heterogeneous, although distinct recovery profiles are apparent. Data-driven trajectory analysis can facilitate better characterization of individual longitudinal patterns of functioning recovery.

Associations between parental broader autism phenotype and child autism spectrum disorder phenotype in the Study to Explore Early Development

The autism spectrum disorder phenotype varies by social and communication ability and co-occurring developmental, behavioral, and medical conditions. Etiology is also diverse, with myriad potential genetic origins and environmental risk factors. Examining the influence of parental broader autism phenotype-a set of sub-clinical characteristics of autism spectrum disorder-on child autism spectrum disorder phenotypes may help reduce heterogeneity in potential genetic predisposition for autism spectrum disorder. We assessed the associations between parental broader autism phenotype and child phenotype among children of age 30-68 months enrolled in the Study to Explore Early Development (N = 707). Child autism spectrum disorder phenotype was defined by a replication of latent classes derived from multiple developmental and behavioral measures: Mild Language Delay with Cognitive Rigidity, Mild Language and Motor Delay with Dysregulation (e.g. anxiety/depression), General Developmental Delay, and Significant Developmental Delay with Repetitive Motor Behaviors. Scores on the Social Responsiveness Scale-Adult measured parent broader autism phenotype. Broader autism phenotype in at least one parent was associated with a child having increased odds of being classified as mild language and motor delay with dysregulation compared to significant developmental delay with repetitive motor behaviors (odds ratio: 2.44; 95% confidence interval: 1.16, 5.09). Children of parents with broader autism phenotype were more likely to have a phenotype qualitatively similar to broader autism phenotype presentation; this may have implications for etiologic research.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition

Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) - a measure of the overall genetic risk an individual carries for a disorder - to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, pFDR = 0.03; MSE = 4.20 × 10-5, pFDR = 0.02). For the schizophrenia PRS, the MSE was significant (MSE = 1.30 × 10-5, pFDR = 0.02) although the correlation was not (r = 0.15, pFDR = 0.06). These results lend support to the hypothesis that polygenic liability for autism and schizophrenia is associated with widespread changes in grey matter concentrations. These associations were seen in individuals not affected by these disorders, indicating that this is not driven by the expression of the disease, but by the genetic risk captured by the PRSs.

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

Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.

Phenotypic Features of Central Sensitization

PURPOSE

The current manuscript reviews approaches for phenotyping central sensitization (CS).

METHODS

The manuscript covers the concept of diagnostic phenotyping, use of endophenotypes, biomarkers, and symptom clusters. Specifically, the components of CS that include general sensory sensitivity (assessed by quantitative sensory testing) and a symptom cluster denoting sleep difficulties, pain, affect, cognitive difficulties, and low energy (S.P.A.C.E.).

RESULTS

Each of the assessment domains are described with reference to CS and their presence in chronic overlapping pain conditions (COPCs) - conditions likely influenced by CS.

CONCLUSIONS

COPCs likely represent clinical diagnostic phenotypes of CS. Components of CS can also be assessed using QST or self-report instruments designed to assess single elements of CS or more general composite indices.

Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

BACKGROUND

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

METHODS

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

RESULTS

The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

CONCLUSIONS

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains

This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.

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

Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms

Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10^-08, β=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10^-03, β=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10^-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10^-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.

Abnormal frontoparietal synaptic gain mediating the P300 in patients with psychotic disorder and their unaffected relatives

The "dysconnection hypothesis" of psychosis suggests that a disruption of functional integration underlies cognitive deficits and clinical symptoms. Impairments in the P300 potential are well documented in psychosis. Intrinsic (self-)connectivity in a frontoparietal cortical hierarchy during a P300 experiment was investigated. Dynamic Causal Modeling was used to estimate how evoked activity results from the dynamics of coupled neural populations and how neural coupling changes with the experimental factors. Twenty-four patients with psychotic disorder, twenty-four unaffected relatives, and twenty-five controls underwent EEG recordings during an auditory oddball paradigm. Sixteen frontoparietal network models (including primary auditory, superior parietal, and superior frontal sources) were analyzed and an optimal model of neural coupling, explaining diagnosis and genetic risk effects, as well as their interactions with task condition were identified. The winning model included changes in connectivity at all three hierarchical levels. Patients showed decreased self-inhibition-that is, increased cortical excitability-in left superior frontal gyrus across task conditions, compared with unaffected participants. Relatives had similar increases in excitability in left superior frontal and right superior parietal sources, and a reversal of the normal synaptic gain changes in response to targets relative to standard tones. It was confirmed that both subjects with psychotic disorder and their relatives show a context-independent loss of synaptic gain control at the highest hierarchy levels. The relatives also showed abnormal gain modulation responses to task-relevant stimuli. These may be caused by NMDA-receptor and/or GABAergic pathologies that change the excitability of superficial pyramidal cells and may be a potential biological marker for psychosis. Hum Brain Mapp 38:3262-3276, 2017. © 2017 Wiley Periodicals, Inc.

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8-21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18-35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development.

Impaired prefrontal synaptic gain in people with psychosis and their relatives during the mismatch negativity

The mismatch negativity (MMN) evoked potential, a preattentive brain response to a discriminable change in auditory stimulation, is significantly reduced in psychosis. Glutamatergic theories of psychosis propose that hypofunction of NMDA receptors (on pyramidal cells and inhibitory interneurons) causes a loss of synaptic gain control. We measured changes in neuronal effective connectivity underlying the MMN using dynamic causal modeling (DCM), where the gain (excitability) of superficial pyramidal cells is explicitly parameterised. EEG data were obtained during a MMN task—for 24 patients with psychosis, 25 of their first‐degree unaffected relatives, and 35 controls—and DCM was used to estimate the excitability (modeled as self‐inhibition) of (source‐specific) superficial pyramidal populations. The MMN sources, based on previous research, included primary and secondary auditory cortices, and the right inferior frontal gyrus. Both patients with psychosis and unaffected relatives (to a lesser degree) showed increased excitability in right inferior frontal gyrus across task conditions, compared to controls. Furthermore, in the same region, both patients and their relatives showed a reversal of the normal response to deviant stimuli; that is, a decrease in excitability in comparison to standard conditions. Our results suggest that psychosis and genetic risk for the illness are associated with both context‐dependent (condition‐specific) and context‐independent abnormalities of the excitability of superficial pyramidal cell populations in the MMN paradigm. These abnormalities could relate to NMDA receptor hypofunction on both pyramidal cells and inhibitory interneurons, and appear to be linked to the genetic aetiology of the illness, thereby constituting potential endophenotypes for psychosis. Hum Brain Mapp 37:351–365, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Heritability and molecular-genetic basis of the P3 event-related brain potential: a genome-wide association study

P3 amplitude is a candidate endophenotype for disinhibitory psychopathology, psychosis, and other disorders. The present study is a comprehensive analysis of the behavioral- and molecular-genetic basis of P3 amplitude and a P3 genetic factor score in a large community sample (N = 4,211) of adolescent twins and their parents, genotyped for 527,829 single nucleotide polymorphisms (SNPs). Biometric models indicated that as much as 65% of the variance in each measure was due to additive genes. All SNPs in aggregate accounted for approximately 40% to 50% of the heritable variance. However, analyses of individual SNPs did not yield any significant associations. Analyses of individual genes did not confirm previous associations between P3 amplitude and candidate genes but did yield a novel association with myelin expression factor 2 (MYEF2). Main effects of individual variants may be too small to be detected by GWAS without larger samples.

The genetics of early-onset bipolar disorder: A systematic review

BACKGROUND

Early-onset bipolar disorder has been associated with a significantly worse prognosis than late-onset BD and has been hypothesized to be a genetically homogenous subset of BD. A sizeable number of studies have investigated early-onset BD through linkage-analyses, candidate-gene association studies, genome-wide association studies (GWAS), and analyses of copy number variants (CNVs), but this literature has not yet been reviewed.

METHODS

A systematic review was conducted using the PubMed database on articles published online before January 15, 2015 and after 1990. Separate searches were made for linkage studies, candidate gene-association studies, GWAS, and studies on CNVs.

RESULTS

Seventy-three studies were included in our review. There is a lack of robust positive findings on the genetics of early-onset BD in any major molecular genetics method.

LIMITATIONS

Early-onset populations were quite small in some studies. Variance in study methods hindered efforts to interpret results or conduct meta-analysis.

CONCLUSIONS

The field is still at an early phase for research on early-onset BD. The largely null findings mirror the results of most genetics research on BD. Although most studies were underpowered, the null findings could mean that early-onset BD may not be as genetically homogenous as has been hypothesized or even that early-onset BD does not differ genetically from adult-onset BD. Nevertheless, clinically the probabilistic developmental risk trajectories associated with early-onset that may not be primarily genetically determined continued to warrant scrutiny. Future research should dramatically expand sample sizes, use atheoretical research methods like GWAS, and standardize methods.

5-HTTLPR Genotype Moderates the Effects of Past Ecstasy Use on Verbal Memory Performance in Adolescent and Emerging Adults: A Pilot Study

OBJECTIVE

Ecstasy use is associated with memory deficits. Serotonin transporter gene (5-HTTLPR) polymorphisms have been linked with memory function in healthy samples. The present pilot study investigated the influence of 5-HTTLPR polymorphisms on memory performance in ecstasy users, marijuana-using controls, and non-drug-using controls, after a minimum of 7 days of abstinence.

METHOD

Data were collected from 116 young adults (18-25 years-old), including 45 controls, 42 marijuana users, and 29 ecstasy users, and were balanced for 5-HTTLPR genotype. Participants were abstinent seven days prior to completing memory testing. Three MANCOVAs and one ANCOVA were run to examine whether drug group, 5-HTTLPR genotype, and their interactions predicted verbal and visual memory after controlling for gender, past year alcohol use, other drug use, and nicotine cotinine levels.

RESULTS

MANCOVA and ANCOVA analysis revealed a significant interaction between drug group and genotype (p = .03) such that ecstasy users with the L/L genotype performed significantly worse on CVLT-2 total recall (p = .05), short (p = .008) and long delay free recall (p = .01), and recognition (p = .006), with the reverse pattern found in controls. Ecstasy did not significantly predict visual memory. 5-HTTLPR genotype significantly predicted memory for faces (p = .02); short allele carriers performed better than those with L/L genotype.

CONCLUSIONS

5-HTTLPR genotype moderated the effects of ecstasy on verbal memory, with L/L carriers performing worse compared to controls. Future research should continue to examine individual differences in ecstasy's impact on neurocognitive performance as well as relationships with neuronal structure. Additional screening and prevention efforts focused on adolescents and emerging adults are necessary to prevent ecstasy consumption.

Complexin2 modulates working memory-related neural activity in patients with schizophrenia

The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 (CPLX2) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. We examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as 'neural inefficiency,' these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.

Intra-Individual Response Variability Assessed by Ex-Gaussian Analysis may be a New Endophenotype for Attention-Deficit/Hyperactivity Disorder

Intra-individual variability of response times (RTisv) is considered as potential endophenotype for attentional deficit/hyperactivity disorder (ADHD). Traditional methods for estimating RTisv lose information regarding response times (RTs) distribution along the task, with eventual effects on statistical power. Ex-Gaussian analysis captures the dynamic nature of RTisv, estimating normal and exponential components for RT distribution, with specific phenomenological correlates. Here, we applied ex-Gaussian analysis to explore whether intra-individual variability of RTs agrees with criteria proposed by Gottesman and Gould for endophenotypes. Specifically, we evaluated if normal and/or exponential components of RTs may (a) present the stair-like distribution expected for endophenotypes (ADHD > siblings > typically developing children (TD) without familiar history of ADHD) and (b) represent a phenotypic correlate for previously described genetic risk variants. This is a pilot study including 55 subjects (20 ADHD-discordant sibling-pairs and 15 TD children), all aged between 8 and 13 years. Participants resolved a visual Go/Nogo with 10% Nogo probability. Ex-Gaussian distributions were fitted to individual RT data and compared among the three samples. In order to test whether intra-individual variability may represent a correlate for previously described genetic risk variants, VNTRs at DRD4 and SLC6A3 were identified in all sibling-pairs following standard protocols. Groups were compared adjusting independent general linear models for the exponential and normal components from the ex-Gaussian analysis. Identified trends were confirmed by the non-parametric Jonckheere-Terpstra test. Stair-like distributions were observed for μ (p = 0.036) and σ (p = 0.009). An additional "DRD4-genotype" × "clinical status" interaction was present for τ (p = 0.014) reflecting a possible severity factor. Thus, normal and exponential RTisv components are suitable as ADHD endophenotypes.

Association analysis of genes in serotonin pathway with attention and executive function in patients with bipolar affective disorder

BACKGROUND

The reason why it is difficult to identify susceptibility genes attributed to bipolar disorder (BPD) is the phenotypic heterogeneity. The use of endophenotypes has been advocated as one possible strategy to discovery cause variants of BPD.

METHODS

A total of 164 patients with BPD and 164 matched controls were employed in the present research. Fifty-two single nucleotide polymorphisms (SNPs) within the genes in serotonin pathway were selected for genotyping using the GoldenGate genotyping assay. All participants completed three neurocognitive tests including the tower of Hanoi (TOH), the Wisconsin card sorting test (WCST) and Trail making tests (TMTA and TMTB-M).

RESULTS

Patients with BPD demonstrated a wide range of deficits in mental activities of attention and speed of information processing, and executive function. Significant interactions between rs2760347 in 5HTR2A gene and diagnosis were found for the executive time of TOH, with β=11.82 and P=0.002 (adjusted P=0.03 after Bonferroni correction).

CONCLUSIONS

Cognitive impairments existing in BPD may be particularly notable in certain domains of attention and executive function, and 5HTR2A gene may be involved in modulating executive function of BP-I patients.

MB-COMT promoter DNA methylation is associated with working-memory processing in schizophrenia patients and healthy controls

Many genetic studies report mixed results both for the associations between COMT polymorphisms and schizophrenia and for the effects of COMT variants on common intermediate phenotypes of the disorder. Reasons for this may include small genetic effect sizes and the modulation of environmental influences. To improve our understanding of the role of COMT in the disease etiology, we investigated the effect of DNA methylation in the MB-COMT promoter on neural activity in the dorsolateral prefrontal cortex during working memory processing as measured by fMRI - an intermediate phenotype for schizophrenia. Imaging and epigenetic data were measured in 102 healthy controls and 82 schizophrenia patients of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia. Neural activity during the Sternberg Item Recognition Paradigm was acquired with either a 3T Siemens Trio or 1.5T Siemens Sonata and analyzed using the FMRIB Software Library (FSL). DNA methylation measurements were derived from cryo-conserved blood samples. We found a positive association between MB-COMT promoter methylation and neural activity in the left dorsolateral prefrontal cortex in a model using a region-of-interest approach and could confirm this finding in a whole-brain model. This effect was independent of disease status. Analyzing the effect of MB-COMT promoter DNA methylation on a neuroimaging phenotype can provide further evidence for the importance of COMT and epigenetic risk mechanisms in schizophrenia. The latter may represent trans-regulatory or environmental risk factors that can be measured using brain-based intermediate phenotypes.

Explaining additional genetic variation in complex traits

Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those that influence phenotype, because there are likely to be many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping, including recording of nongenetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power.

In search of biomarkers in psychiatry: EEG-based measures of brain function

Current clinical parameters used for diagnosis and phenotypic definitions of psychopathology are both highly variable and subjective. Intensive research efforts for specific and sensitive biological markers, or biomarkers, for psychopathology as objective alternatives to the current paradigm are ongoing. While biomarker research in psychiatry has focused largely on functional neuroimaging methods for identifying the neural functions that associate with psychopathology, scalp electroencephalography (EEG) has been viewed, historically, as offering little specific brain source information, as scalp appearance is only loosely correlated to its brain source dynamics. However, ongoing advances in signal processing of EEG data can now deliver functional EEG brain-imaging with distinctly improved spatial, as well as fine temporal, resolution. One computational approach proving particularly useful for EEG cortical brain imaging is independent component analysis (ICA). ICA decomposition can be used to identify distinct cortical source activities that are sensitive and specific to the pathophysiology of psychiatric disorders. Given its practical research advantages, relatively low cost, and ease of use, EEG-imaging is now both feasible and attractive, in particular for studies involving the large samples required by genetically informative designs to characterize causal pathways to psychopathology. The completely non-invasive nature of EEG data acquisition, coupled with ongoing advances in dry, wireless, and wearable EEG technology, makes EEG-imaging increasingly attractive and appropriate for psychiatric research, including the study of developmentally young samples. Applied to large genetically and developmentally informative samples, EEG imaging can advance the search for robust diagnostic biomarkers and phenotypes in psychiatry.

Resting EEG in psychosis and at-risk populations--a possible endophenotype?

BACKGROUND

Finding reliable endophenotypes for psychosis could lead to an improved understanding of aetiology, and provide useful alternative phenotypes for genetic association studies. Resting quantitative electroencephalography (QEEG) activity has been shown to be heritable and reliable over time. However, QEEG research in patients with psychosis has shown inconsistent and even contradictory findings, and studies of at-risk populations are scarce. Hence, this study aimed to investigate whether resting QEEG activity represents a candidate endophenotype for psychosis.

METHOD

QEEG activity at rest was compared in four frequency bands (delta, theta, alpha, and beta), between chronic patients with psychosis (N=48), first episode patients (N=46), at-risk populations ("at risk mental state", N=33; healthy relatives of patients, N=45), and healthy controls (N=107).

RESULTS

Results showed that chronic patients had significantly increased resting QEEG amplitudes in delta and theta frequencies compared to healthy controls. However, first episode patients and at-risk populations did not differ from controls in these frequency bands. There were no group differences in alpha or beta frequency bands.

CONCLUSION

Since no abnormalities were found in first episode patients, ARMS, or healthy relatives, resting QEEG activity in the frequency bands examined is unlikely to be related to genetic predisposition to psychosis. Rather than endophenotypes, the low frequency abnormalities observed in chronic patients are probably related to illness progression and/or to the long-term effects of treatments.

Neurophysiologic effect of GWAS derived schizophrenia and bipolar risk variants

Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) as disease associated variants for schizophrenia (SCZ), bipolar disorder (BPD), or both. Although these results are statistically robust, the functional effects of these variants and their role in the pathophysiology of SCZ or BPD remain unclear. Dissecting the effects of risk genes on distinct domains of brain function can provide important biological insights into the mechanisms by which these genes may confer illness risk. This study used quantitative event related potentials to characterize the neurophysiological effects of well-documented GWAS-derived SCZ/BPD susceptibility variants in order to map gene effects onto important domains of brain function. We genotyped 199 patients with DSM-IV diagnoses of SCZ or BPD and 74 healthy control subjects for 19 risk SNPs derived from previous GWAS findings and tested their association with five neurophysiologic traits (P3 amplitude, P3 latency, N1 amplitude, P2 amplitude, and P50 sensory gating responses) known to be abnormal in psychosis. The TCF4 SNP rs17512836 risk allele showed a significant association with reduced auditory P3 amplitude (P = 0.00016) after correction for multiple testing. The same allele was also associated with delayed P3 latency (P = 0.005). Our results suggest that a SCZ risk variant in TCF4 is associated with neurophysiologic traits thought to index attention and working memory abnormalities in psychotic disorders. These findings suggest a mechanism by which TCF4 may contribute to the neurobiological basis of psychotic illness.

The impact of genome-wide supported schizophrenia risk variants in the neurogranin gene on brain structure and function

The neural mechanisms underlying genetic risk for schizophrenia, a highly heritable psychiatric condition, are still under investigation. New schizophrenia risk genes discovered through genome-wide association studies (GWAS), such as neurogranin (NRGN), can be used to identify these mechanisms. In this study we examined the association of two common NRGN risk single nucleotide polymorphisms (SNPs) with functional and structural brain-based intermediate phenotypes for schizophrenia. We obtained structural, functional MRI and genotype data of 92 schizophrenia patients and 114 healthy volunteers from the multisite Mind Clinical Imaging Consortium study. Two schizophrenia-associated NRGN SNPs (rs12807809 and rs12541) were tested for association with working memory-elicited dorsolateral prefrontal cortex (DLPFC) activity and surface-wide cortical thickness. NRGN rs12541 risk allele homozygotes (TT) displayed increased working memory-related activity in several brain regions, including the left DLPFC, left insula, left somatosensory cortex and the cingulate cortex, when compared to non-risk allele carriers. NRGN rs12807809 non-risk allele (C) carriers showed reduced cortical gray matter thickness compared to risk allele homozygotes (TT) in an area comprising the right pericalcarine gyrus, the right cuneus, and the right lingual gyrus. Our study highlights the effects of schizophrenia risk variants in the NRGN gene on functional and structural brain-based intermediate phenotypes for schizophrenia. These results support recent GWAS findings and further implicate NRGN in the pathophysiology of schizophrenia by suggesting that genetic NRGN risk variants contribute to subtle changes in neural functioning and anatomy that can be quantified with neuroimaging methods.

Neuroimaging as a potential biomarker to optimize psychiatric research and treatment

Complex, polygenic phenotypes in psychiatry hamper our understanding of the underlying molecular pathways and mechanisms of many diseases. The unknown aetiology, together with symptoms which often show a large variability both across individuals and over time and also tend to respond comparatively slowly to medication, can be a problem for patient treatment and drug development. We argue that neuroimaging has the potential to improve psychiatric treatment in two ways. First, by reducing phenotypic complexity, neuroimaging intermediate phenotypes can help to identify disease-related genes and can shed light into the biological mechanisms of known risk genes. Second, quantitative neuroimaging markers - reflecting the spectrum of impairment on a brain-based level - can be used as a more sensitive, reliable and immediate treatment response biomarker. In the end, enhancing both our understanding of the pathophysiology of psychiatric disorders and the prediction of treatment success could eventually optimise current therapy plans.

Disorders and borders: psychiatric genetics and nosology

Over the past century, the definition and classification of psychiatric disorders has evolved through a combination of historical trends, clinical observations, and empirical research. The current nosology, instantiated in the DSM-5 and ICD-10, rests on descriptive criteria agreed upon by a consensus of experts. While the development of explicit criteria has enhanced the reliability of diagnosis, the validity of the current diagnostic categories has been the subject of debate and controversy. Genetic studies have long been regarded as a key resource for validating the boundaries among diagnostic categories. Genetic epidemiologic studies have documented the familiality and heritability of clinically defined psychiatric disorders and molecular genetic studies have begun to identify specific susceptibility variants. At the same time, there is growing evidence from family, twin and genomic studies that genetic influences on psychiatric disorders transcend clinical boundaries. Here I review this evidence for cross-disorder genetic effects and discuss the implications of these findings for psychiatric nosology. Psychiatric genetic research can inform a bottom-up reappraisal of psychopathology that may help the field move beyond a purely descriptive classification and toward an etiology-based nosology.

Cumulative genetic risk and prefrontal activity in patients with schizophrenia

The lack of consistency of genetic associations in highly heritable mental illnesses, such as schizophrenia, remains a challenge in molecular psychiatry. Because clinical phenotypes for psychiatric disorders are often ill defined, considerable effort has been made to relate genetic polymorphisms to underlying physiological aspects of schizophrenia (so called intermediate phenotypes), that may be more reliable. Given the polygenic etiology of schizophrenia, the aim of this work was to form a measure of cumulative genetic risk and study its effect on neural activity during working memory (WM) using functional magnetic resonance imaging. Neural activity during the Sternberg Item Recognition Paradigm was measured in 79 schizophrenia patients and 99 healthy controls. Participants were genotyped, and a genetic risk score (GRS), which combined the additive effects of 41 single-nucleotide polymorphisms (SNPs) from 34 risk genes for schizophrenia, was calculated. These risk SNPs were chosen according to the continuously updated meta-analysis of genetic studies on schizophrenia available at www.schizophreniaresearchforum.org. We found a positive relationship between GRS and left dorsolateral prefrontal cortex inefficiency during WM processing. GRS was not correlated with age, performance, intelligence, or medication effects and did not differ between acquisition sites, gender, or diagnostic groups. Our study suggests that cumulative genetic risk, combining the impact of many genes with small effects, is associated with a known brain-based intermediate phenotype for schizophrenia. The GRS approach could provide an advantage over studying single genes in studies focusing on the genetic basis of polygenic conditions such as neuropsychiatric disorders.

The role of zebrafish (Danio rerio) in dissecting the genetics and neural circuits of executive function

Zebrafish have great potential to contribute to our understanding of behavioral genetics and thus to contribute to our understanding of the etiology of psychiatric disease. However, progress is dependent upon the rate at which behavioral assays addressing complex behavioral phenotypes are designed, reported and validated. Here we critically review existing behavioral assays with particular focus on the use of adult zebrafish to explore executive processes and phenotypes associated with human psychiatric disease. We outline the case for using zebrafish as models to study impulse control and attention, discussing the validity of applying extant rodent assays to zebrafish and evidence for the conservation of relevant neural circuits.

Variation in the major histocompatibility complex [MHC] gene family in schizophrenia: associations and functional implications

Schizophrenia is a chronic debilitating neuropsychiatric disorder with a complex genetic contribution. Although multiple genetic, immunological and environmental factors are known to contribute to schizophrenia susceptibility, the underlying neurobiological mechanism(s) is yet to be established. The immune system dysfunction theory of schizophrenia is experiencing a period of renewal due to a growth in evidence implicating components of the immune system in brain function and human behavior. Current evidence indicates that certain immune molecules such as Major Histocompatibility Complex (MHC) and cytokines, the key regulators of immunity and inflammation are directly involved in the neurobiological processes related to neurodevelopment, neuronal plasticity, learning, memory and behavior. However, the strongest support in favor of the immune hypothesis has recently emerged from on-going genome wide association studies advocating MHC region variants as major determinants of one's risk for developing schizophrenia. Further identification of the interacting partners and receptors of MHC molecules in the brain and their role in down-stream signaling pathways of neurotransmission have implicated these molecules as potential schizophrenia risk factors. More recently, combined brain imaging and genetic studies have revealed a relationship between genetic variations within the MHC region and neuromorphometric changes during schizophrenia. Furthermore, MHC molecules play a significant role in the immune-infective and neurodevelopmental pathogenetic pathways, currently hypothesized to contribute to the pathophysiology of schizophrenia. Herein, we review the immunological, genetic and expression studies assessing the role of the MHC in conferring risk for developing schizophrenia, we summarize and discuss the possible mechanisms involved, making note of the challenges to, and future directions of, immunogenetic research in schizophrenia.

Recruitment of the left hemispheric emotional attention neural network in risk for and protection from depression

BACKGROUND

Family history of major depressive disorder (MDD) increases individuals' vulnerability to depression and alters the way depression manifests itself. Emotion processing and attention shifting are functions altered by MDD and family history of the disease; therefore, it is important to recognize the neural correlates of these functions in association with both factors.

METHODS

Our study determines neural correlates of emotion processing and attention shifting for healthy individuals and patients with MDD with and without family history of depression. We compared the performance and neural activity in a functional magnetic resonance imaging experiment examining emotion processing and attention shifting in all participants.

RESULTS

Our sample included 4 study groups: healthy controls without family history of depression (n = 25), patients with MDD without family history of the disease (n = 20), unaffected healthy first-degree relatives of patients with MDD (n = 21) and patients with MDD with family history of MDD (n = 30). Compared with healthy controls, unaffected first-degree relatives overactivate the somatosensory cortex and the attention controlling areas during both emotion processing and attention shifting. Patients with family history of MDD have stronger neural activation in subcortical areas during shifting attention from negative stimuli. Patients without family history of MDD have less activation in the paralimbic regions and more activation in core limbic areas, especially during emotion processing.

LIMITATIONS

The conclusions about the intergroup differences in activation can be drawn only about neural areas engaged in the task.

CONCLUSION

Unaffected first-degree relatives of patients with MDD overreact to external emotional cues and compensate for the vulnerability with increased involvement of executive control. Patients with a family history of MDD have less executive control over their attentional shifts in the face of negative stimuli. Patients without a family history of MDD process emotional stimuli in a more visceral way than controls.

Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression

We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4, and CDH13. The top genes we identified with this method also displayed significant and widespread post hoc effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2. We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8 ± 2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

Predicting white matter integrity from multiple common genetic variants

Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ≈ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

A latent modeling approach to genotype-phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype

This study illustrates the application of a latent modeling approach to genotype-phenotype relationships and gene × environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the monoamine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N = 192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA × physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA.

Altered inhibition of negative emotions in subjects at family risk of major depressive disorder

Unaffected 1st degree relatives of patients with major depressive disorder (MDD) are more likely to develop MDD than healthy controls. The aim of our study was to establish neuronal correlates of familial susceptibility in the process of inhibition of emotional information. Unaffected 1st degree relatives of patients with MDD (N = 21) and matched healthy controls (N = 25) underwent a functional magnetic resonance imaging procedure with an inhibition task. Blood oxygenated level dependent signal was evaluated for the two groups during inhibition of positive, negative and neutral information. In a 2 × 3 ANOVA unaffected relatives of patients with MDD were compared to healthy controls, jointly and separately for all three levels of emotional valence of the information. The interaction between group and emotional valence of the inhibited information was significant, indicating "a negative neural drift" in unaffected relatives of patients with MDD. The unaffected relatives of patients with MDD displayed an increased activation during inhibiting of negative material in the right middle cingulate cortex and the left caudate nucleus (p < 0.05, family wise error corrected). There was no difference between the two groups in terms of inhibiting positive or neutral stimuli. Our findings provide the first evidence that unaffected relatives of patients with MDD differ from the standard population in terms of neural correlates of inhibition of negative emotional information. Overactivation of cingulate cortex and caudate nucleus may indicate a learnt strategy aimed at coping with increased susceptibility to negative information schemata and may have future consequences for therapy.

Multilocus genetic analysis of brain images

The quest to identify genes that influence disease is now being extended to find genes that affect biological markers of disease, or endophenotypes. Brain images, in particular, provide exquisitely detailed measures of anatomy, function, and connectivity in the living brain, and have identified characteristic features for many neurological and psychiatric disorders. The emerging field of imaging genomics is discovering important genetic variants associated with brain structure and function, which in turn influence disease risk and fundamental cognitive processes. Statistical approaches for testing genetic associations are not straightforward to apply to brain images because the data in brain images is spatially complex and generally high dimensional. Neuroimaging phenotypes typically include 3D maps across many points in the brain, fiber tracts, shape-based analyses, and connectivity matrices, or networks. These complex data types require new methods for data reduction and joint consideration of the image and the genome. Image-wide, genome-wide searches are now feasible, but they can be greatly empowered by sparse regression or hierarchical clustering methods that isolate promising features, boosting statistical power. Here we review the evolution of statistical approaches to assess genetic influences on the brain. We outline the current state of multivariate statistics in imaging genomics, and future directions, including meta-analysis. We emphasize the power of novel multivariate approaches to discover reliable genetic influences with small effect sizes.

The early auditory gamma-band response is heritable and a putative endophenotype of schizophrenia

BACKGROUND

Reduced power and phase locking of the early auditory gamma-band response (EAGBR) have been reported in schizophrenia, but findings are equivocal. Further, little is known about genetic (heritability) and environmental influences on the EAGBR or its potential as an endophenotype of schizophrenia. The present study used a twin design to examine whether EAGBR power and phase locking are heritable and reduced in schizophrenic patients and their unaffected co-twins and thus putative endophenotypes of schizophrenia.

METHODS

The study sample included a total of 194 individuals, consisting of 15 monozygotic [MZ] twin pairs concordant for schizophrenia, 9 MZ twin pairs discordant for schizophrenia, and 42 MZ and 31 dizygotic (DZ) control pairs. Evoked power and phase-locking factor of the EAGBR were computed on Morlet wavelet-transformed electroencephalogram responses to standard tones during an auditory oddball target detection task. Structural equation modeling was applied to estimate heritability and genetic and environmental correlations with schizophrenia for the EAGBR measures.

RESULTS

Both evoked power and phase-locking phenotypes were heritable traits (power: h(2) = 0.65; phase locking: h(2) = 0.63). Impaired EAGBR measures were significantly associated with schizophrenia. Patients with schizophrenia and their unaffected identical co-twins exhibited significantly reduced EAGBR power compared with control subjects. In each phenotype, shared genetic factors were likely the source of the observed associations with schizophrenia.

CONCLUSIONS

Our results support EAGBR measures as putative endophenotypes of schizophrenia, likely reflecting an ubiquitous local cortical circuit deficit.

The genetic and environmental influences of event-related gamma oscillations on bipolar disorder

OBJECTIVES

Gamma oscillations have been proposed to play an important role in neural information coding. There have been a limited number of electrophysiology studies in evoked gamma band responses (GBRs) in bipolar disorder (BPD). It is also unclear whether GBR deficits, if present, are potential endophenotypes for BPD as little is known about the heritability of GBRs. The present study aimed to examine whether GBRs derived from two auditory tasks, the oddball task and the dual-click paradigm, are potential BPD endophenotypes.

METHODS

A total of 308 subjects were included in this study: 198 healthy controls, 59 BPD patients (22 monozygotic BPD twins and 37 BPD patients from 31 families), and 51 unaffected relatives. The evoked gamma responses were calculated using a Morlet wavelet transformation. Structural equation modelling was applied to obtain the genetic (heritability) and environment estimates in each GBR variable and their (genetic) overlap with BPD.

RESULTS

The heritability estimates of GBR to standard stimuli were 0.51 and 0.35 to target stimuli in the oddball task. However, neither response type was impaired in BPD patients or their unaffected relatives. The heritability estimates of GBR to S1 stimuli were 0.54 and 0.50 to S2 stimuli in the dual-click paradigm. BPD patients had reduced gamma power and suppression to S1 stimuli but their unaffected relatives did not.

CONCLUSIONS

Evoked GBRs are heritable traits. However, GBR deficits are not observed in clinically unaffected relatives nor associated with BPD. Gamma responses do not appear to satisfy criteria for being BPD endophenotypes.

Neurocognitive phenotypes and genetic dissection of disorders of brain and behavior

Elucidating the molecular mechanisms underlying quantitative neurocognitive phenotypes will further our understanding of the brain's structural and functional architecture and advance the diagnosis and treatment of the psychiatric disorders that these traits underlie. Although many neurocognitive traits are highly heritable, little progress has been made in identifying genetic variants unequivocally associated with these phenotypes. A major obstacle to such progress is the difficulty in identifying heritable neurocognitive measures that are precisely defined and systematically assessed and represent unambiguous mental constructs, yet are also amenable to the high-throughput phenotyping necessary to obtain adequate power for genetic association studies. In this perspective we compare the current status of genetic investigations of neurocognitive phenotypes to that of other categories of biomedically relevant traits and suggest strategies for genetically dissecting traits that may underlie disorders of brain and behavior.