Endophenotypes in the Genetic Analyses of Mental Disorders

Cognitive endophenotypes inform genome-wide expression profiling in schizophrenia

OBJECTIVE

We performed a whole-genome expression study to clarify the nature of the biological processes mediating between inherited genetic variations and cognitive dysfunction in schizophrenia.

METHOD

Gene expression was assayed from peripheral blood mononuclear cells using Illumina Human WG6 v3.0 chips in twins discordant for schizophrenia or bipolar disorder and control twins. After quality control, expression levels of 18,559 genes were screened for association with the California Verbal Learning Test (CVLT) performance, and any memory-related probes were then evaluated for variation by diagnostic status in the discovery sample (N = 190), and in an independent replication sample (N = 73). Heritability of gene expression using the twin design was also assessed.

RESULTS

After Bonferroni correction (p < 2.69 × 10-6), CVLT performance was significantly related to expression levels for 76 genes, 43 of which were differentially expressed in schizophrenia patients, with comparable effect sizes in the same direction in the replication sample. For 41 of these 43 transcripts, expression levels were heritable. Nearly all identified genes contain common or de novo mutations associated with schizophrenia in prior studies.

CONCLUSION

Genes increasing risk for schizophrenia appear to do so in part via effects on signaling cascades influencing memory. The genes implicated in these processes are enriched for those related to RNA processing and DNA replication and include genes influencing G-protein coupled signal transduction, cytokine signaling, and oligodendrocyte function.

Genetics and neuropsychology: A merger whose time has come

Genetics and neuropsychology have historically been 2 rather distant and unrelated fields. With the very rapid advances that have been taking place in genetics, research and treatment of disorders of cognition in the 21st century are likely to be increasingly informed by individual differences in genetics and epigenetics. Although neuropsychologists are not expected to become geneticists, it is our view that increased training in genetics should become more central to training in neuropsychology. This relationship should not be unidirectional. Here we note ways in which an understanding of genetics and epigenetics can inform neuropsychology. On the other hand, given the complexity of cognitive phenotypes, neuropsychology can also play a valuable role in informing and refining genetic studies. Greater integration of the 2 should advance both fields.

New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings

BACKGROUND

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder.

AIMS

To quantify the shared genetic variability between bipolar disorder and cognitive measures.

METHOD

Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder.

RESULTS

Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms.

CONCLUSIONS

Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder.

Role played by the SP4 gene in schizophrenia and major depressive disorder in the Han Chinese population

BACKGROUND

Psychiatric disorders such as schizophrenia and major depressive disorder (MDD) are likely to be caused by multiple susceptibility genes, each with small effects in increasing the risk of illness. Identifying DNA variants associated with schizophrenia and MDD is a crucial step in understanding the pathophysiology of these disorders.

AIMS

To investigate whether the SP4 gene plays a significant role in schizophrenia or MDD in the Han Chinese population.

METHOD

We focused on nine single nucleotide polymorphisms (SNPs) harbouring the SP4 gene and carried out case-control studies in 1235 patients with schizophrenia, 1045 patients with MDD and 1235 healthy controls recruited from the Han Chinese population.

RESULTS

We found that rs40245 was significantly associated with schizophrenia in both allele and genotype distributions (Pallele = 0.0005, Pallele = 0.004 after Bonferroni correction; Pgenotype = 0.0023, Pgenotype = 0.0184 after Bonferroni correction). The rs6461563 SNP was significantly associated with schizophrenia in the allele distributions (Pallele = 0.0033, Pallele = 0.0264 after Bonferroni correction).

CONCLUSIONS

Our results suggest that common risk factors in the SP4 gene are associated with schizophrenia, although not with MDD, in the Han Chinese population.

Multidimensional assessment of impulsivity in schizophrenia, bipolar disorder, and major depressive disorder: testing for shared endophenotypes

BACKGROUND

Impulsivity is associated with bipolar disorder as a clinical feature during and between manic episodes and is considered a potential endophenotype for the disorder. Schizophrenia and major depressive disorder share substantial genetic overlap with bipolar disorder, and these two disorders have also been associated with elevations in impulsivity. However, little is known about the degree of overlap among these disorders in discrete subfacets of impulsivity and whether any overlap is purely phenotypic or due to shared genetic diathesis.

METHOD

We focused on five subfacets of impulsivity: self-reported attentional, motor, and non-planning impulsivity, self-reported sensation seeking, and a behavioral measure of motor inhibition (stop signal reaction time; SSRT). We examined these facets within and across disorder proband and co-twin groups, modeled heritability, and tested for endophenotypic patterning in a sample of twin pairs recruited from the Swedish Twin Registry (N = 420).

RESULTS

We found evidence of moderate to high levels of heritability for all five subfacets. All three proband groups and their unaffected co-twins showed elevations on attentional, motor, and non-planning impulsivity. Schizophrenia probands (but not their co-twins) showed significantly lower sensation seeking, and schizophrenia and bipolar disorder probands (but not in their co-twins) had significantly longer SSRTs, compared with healthy controls and the other groups.

CONCLUSIONS

Attentional, motor, and non-planning impulsivity emerged as potential shared endophenotypes for the three disorders, whereas sensation seeking and SSRT were associated with phenotypic affection but not genetic loading for these disorders.

Polymorphisms of BDNF and CACNA1C are not associated with cognitive functioning in bipolar disorder or healthy controls

INTRODUCTION

The cause of cognitive dysfunction in bipolar disorder (BD) is not well understood. BDNF and CACNA1C are two susceptibility genes for the disorder that have also been reported to be associated with cognitive deficits in the disorder, but the studies have been small and with conflicting results. We therefore attempted to replicate an association between cognitive dysfunction with the most commonly studied single nucleotide polymorphisms rs6265 and rs1006737.

METHODS

Regression models with five aggregated cognitive domains derived from a comprehensive test battery and IQ score were run using directly genotyped risk variants of SNPs rs6265 and rs1006737 as predictors with covariates as appropriate. Models were performed in a clinical sample of Swedish patients with BD (N = 114) and sex- and age-matched population controls (N = 104).

RESULTS

No significant associations (regardless of correction for multiple testing) between the BDNF and CACNA1C risk variants and cognitive functioning were found in either patients or controls.

CONCLUSIONS

Our results do not support that the common genetic risk variants in rs6265 and rs1006737 are associated with cognitive dysfunction.

Minor Allele Frequency Changes the Nature of Genotype by Environment Interactions

In the classical twin study, phenotypic variation is often partitioned into additive genetic (A), common (C) and specific environment (E) components. From genetical theory, the outcome of genotype by environment interaction is expected to inflate A when the interacting factor is shared (i.e., C) between the members of a twin pair. We show that estimates of both A and C can be inflated. When the shared interacting factor changes the size of the difference between homozygotes' means, the expected sibling or DZ twin correlation is .5 if and only if the minor allele frequency (MAF) is .5; otherwise the expected DZ correlation is greater than this value, consistent (and confounded) with some additional effect of C. This result is considered in the light of the distribution of minor allele frequencies for polygenic traits. Also discussed is whether such interactions take place at the locus level or affect an aggregated biological structure or system. Interactions with structures or endophenotypes that result from the aggregated effects of many loci will generally emerge as part of the A estimate.

Lexical processing deficits in children with developmental language disorder: An event-related potentials study

Lexical processing deficits in children with developmental language disorder (DLD) have been postulated to arise as sequelae of their grammatical deficits (either directly or via compensatory mechanisms) and vice versa. We examined event-related potential indices of lexical processing in children with DLD (n = 23) and their typically developing peers (n = 16) using a picture-word matching paradigm. We found that children with DLD showed markedly reduced N400 amplitudes in response both to auditorily presented words that had initial phonological overlap with the name of the pictured object and to words that were not semantically or phonologically related to the pictured object. Moreover, this reduction was related to behavioral indices of phonological and lexical but not grammatical development. We also found that children with DLD showed a depressed phonological mapping negativity component in the early time window, suggesting deficits in phonological processing or early lexical access. The results are partially consistent with the overactivation account of lexical processing deficits in DLD and point to the relative functional independence of lexical/phonological and grammatical deficits in DLD, supporting a multidimensional view of the disorder. The results also, although indirectly, support the neuroplasticity account of DLD, according to which language impairment affects brain development and shapes the specific patterns of brain responses to language stimuli.

Etiology of obsessions and compulsions: General and specific genetic and environmental factors

Evidence suggests that a general etiologic factor plays a role in many forms of psychopathology, possibly including obsessive-compulsive (OC) symptoms. A twin study (N=307 twin pairs) of OC symptoms and their endophenotypes was conducted to investigate the role of general and symptom-specific etiologic factors. OC symptoms and endophenotypes were found to have complex etiologies, being shaped by OC-specific genetic and environmental factors, and by genetic and environmental factors that shape psychopathology in general. Understanding the general and specific etiologies underlying OC symptoms has implications for improving treatments outcomes through the development of therapies that target general and/or specific factors.

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life

Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals' daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions.

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders--promises and limitations

BACKGROUND

Psychiatric science remains descriptive, with a categorical nosology intended to enhance interobserver reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles.

FINDINGS

A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality, and heterogeneity of neuropsychiatric data collected from multiple sources ('broad' data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits, and behaviors ('deep' data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders.

CONCLUSIONS

We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis.

So close yet so far: Motor anomalies impacting on social functioning in autism spectrum disorder

Difficulties in the social domain and motor anomalies have been widely investigated in Autism Spectrum Disorder (ASD). However, they have been generally considered as independent, and therefore tackled separately. Recent advances in neuroscience have hypothesized that the cortical motor system can play a role not only as a controller of elementary physical features of movement, but also in a complex domain as social cognition. Here, going beyond previous studies on ASD that described difficulties in the motor and in the social domain separately, we focus on the impact of motor mechanisms anomalies on social functioning. We consider behavioral, electrophysiological and neuroimaging findings supporting the idea that motor cognition is a critical "intermediate phenotype" for ASD. Motor cognition anomalies in ASD affect the processes of extraction, codification and subsequent translation of "external" social information into the motor system. Intriguingly, this alternative "motor" approach to the social domain difficulties in ASD may be promising to bridge the gap between recent experimental findings and clinical practice, potentially leading to refined preventive approaches and successful treatments.

Clashing Diagnostic Approaches: DSM-ICD Versus RDoC

Since at least the middle of the past century, one overarching model of psychiatric classification has reigned supreme, namely, that of the Diagnostic and Statistical Manual of Mental Disorders and the International Statistical Classification of Diseases and Related Health Problems (herein referred to as DSM-ICD). This DSM-ICD approach embraces an Aristotelian view of mental disorders as largely discrete entities that are characterized by distinctive signs, symptoms, and natural histories. Over the past several years, however, a competing vision, namely, the Research Domain Criteria (RDoC) initiative launched by the National Institute of Mental Health, has emerged in response to accumulating anomalies within the DSM-ICD system. In contrast to DSM-ICD, RDoC embraces a Galilean view of psychopathology as the product of dysfunctions in neural circuitry. RDoC appears to be a valuable endeavor that holds out the long-term promise of an alternative system of mental illness classification. We delineate three sets of pressing challenges--conceptual, methodological, and logistical/pragmatic--that must be addressed for RDoC to realize its scientific potential. We conclude with a call for further research, including investigation of a rapprochement between Aristotelian and Galilean approaches to psychiatric classification.

Genetic Moderation of Stress Effects on Corticolimbic Circuitry

Stress exposure is associated with individual differences in corticolimbic structure and function that often mirror patterns observed in psychopathology. Gene x environment interaction research suggests that genetic variation moderates the impact of stress on risk for psychopathology. On the basis of these findings, imaging genetics, which attempts to link variability in DNA sequence and structure to neural phenotypes, has begun to incorporate measures of the environment. This research paradigm, known as imaging gene x environment interaction (iGxE), is beginning to contribute to our understanding of the neural mechanisms through which genetic variation and stress increase psychopathology risk. Although awaiting replication, evidence suggests that genetic variation within the canonical neuroendocrine stress hormone system, the hypothalamic-pituitary-adrenal axis, contributes to variability in stress-related corticolimbic structure and function, which, in turn, confers risk for psychopathology. For iGxE research to reach its full potential it will have to address many challenges, of which we discuss: (i) small effects, (ii) measuring the environment and neural phenotypes, (iii) the absence of detailed mechanisms, and (iv) incorporating development. By actively addressing these challenges, iGxE research is poised to help identify the neural mechanisms underlying genetic and environmental associations with psychopathology.

Electrophysiological Endophenotypes for Schizophrenia

Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABAergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating data sets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype.

The National Institute of Mental Health Research Domain Criteria: A Bridge Too Far

The National Institute of Mental Health is actively promoting Research Domain Criteria as a new model for the research on mental disorders. Research Domain Criteria approaches disorders through a matrix, linking units of analysis with domains, based on the assumption that psychopathology reflects abnormal connectivity in the brain. This review suggests that the Research Domain Criteria perspective is likely to fail to provide an adequate basis for clinical psychiatric theory and practice. First, it uses models from neuroscience that are insufficiently developed. Second, it is based on the premise that mental phenomena and mental disorders can be reduced to neural activity, without consideration of cognition, experience, and social interaction. Third, it downplays psychosocial factors in psychopathology and treatment. Research Domain Criteria may therefore prove inadequate for providing a neuroscientific basis for psychiatric nosology and treatment and needs to be supplemented with a broader view that incorporates insights from social sciences, psychology, and phenomenology.

Polymorphisms of dopamine pathway genes NRG1 and LMX1A are associated with cognitive performance in bipolar disorder

OBJECTIVES

LIM homeobox transcription factor 1, alpha (LMX1A) and neuregulin 1 (NRG1) are susceptibility genes for schizophrenia that have been implicated in the dopaminergic pathway and have been associated with altered cognitive functioning. We hypothesized that single nucleotide polymorphisms (SNPs) in LMX1A and NRG1 would be associated with cognitive functioning in bipolar disorder.

METHODS

In total, four SNPs were directly genotyped. Regression models with five aggregated cognitive domains and intelligence quotient (IQ) score were run using risk variants of LMX1A (rs11809911, rs4657412, rs6668493) and NRG1 (rs35753505) as predictors. Models were performed in a clinical sample of patients with bipolar disorder (n = 114) and healthy controls (n = 104).

RESULTS

The risk variants of the rs11809911 SNP in LMX1A were negatively associated with IQ score and memory/learning, whereas the risk variants of rs35753505 in NRG1 were positively associated with IQ score (adjusted R(2) = 0.17, Q = 0.006) and memory/learning (adjusted R(2) = 0.24, Q = 0.001). The risk variants of the rs35753505 SNP in NRG1 were positively associated with language (adjusted R(2) = 0.11, Q = 0.006), visuospatial functions (adjusted R(2) = 0.23, Q = 0.001), and attention/speed (adjusted R(2) = 0.25, Q = 0.001). Results could not be replicated in controls.

CONCLUSIONS

The risk variants of the rs35753505 SNP were associated with increased performance in several cognitive domains and IQ, whereas the risk variants of the rs11809911 SNP in LMX1A was associated with reduced IQ and memory/learning.

Multiple SNP Set Analysis for Genome-Wide Association Studies Through Bayesian Latent Variable Selection

The power of genome-wide association studies (GWAS) for mapping complex traits with single-SNP analysis (where SNP is single-nucleotide polymorphism) may be undermined by modest SNP effect sizes, unobserved causal SNPs, correlation among adjacent SNPs, and SNP-SNP interactions. Alternative approaches for testing the association between a single SNP set and individual phenotypes have been shown to be promising for improving the power of GWAS. We propose a Bayesian latent variable selection (BLVS) method to simultaneously model the joint association mapping between a large number of SNP sets and complex traits. Compared with single SNP set analysis, such joint association mapping not only accounts for the correlation among SNP sets but also is capable of detecting causal SNP sets that are marginally uncorrelated with traits. The spike-and-slab prior assigned to the effects of SNP sets can greatly reduce the dimension of effective SNP sets, while speeding up computation. An efficient Markov chain Monte Carlo algorithm is developed. Simulations demonstrate that BLVS outperforms several competing variable selection methods in some important scenarios.

Converging models of schizophrenia--Network alterations of prefrontal cortex underlying cognitive impairments

The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal.

Longitudinal stability and predictive utility of the visual P3 response in adults with externalizing psychopathology

We determined whether time-domain P3 amplitude and time-frequency principal component (TF-PC) reductions could serve as stable and predictive developmental endophenotypes of externalizing psychopathology. Participants from the Minnesota Twin Family Study were assessed at age 17 and again at age 29 for lifetime externalizing (EXT) disorders. Comparisons of P3 amplitude and TF-PCs at delta and theta frequencies were made between EXT and unaffected comparison subjects. P3 amplitude and all five extracted TF-PCs were significantly reduced in those presenting lifetime EXT disorders at both ages 17 and 29 and showed substantial 12-year rank-order stability. P3 amplitude and delta TF-PCs measured at age 17 also predicted subsequent development of EXT by age 29, with every 1-microvolt decrease in age 17 amplitude associated with an approximately 5% increase in risk for an EXT diagnosis by age 29. Overall, results from this study further confirm that these P3-derived brain measures maintain their potential as putative EXT endophenotypes through the third decade of life.

Executive functions as a potential neurocognitive endophenotype in anxiety disorders: A systematic review considering DSM-IV and DSM-5 diagnostic criteria classification

Evidence in the literature indicates that neurocognitive impairments may represent endophenotypes in psychiatric disorders.

Objective

This study aimed to conduct a systematic review on executive functions as a potential neurocognitive endophenotype in anxiety disorder diagnosis according to the DSM-IV and DSM-5 classifications.

Methods

A literature search of the LILACS, Cochrane Library, Index Psi Periódicos Técnico-Científicos, PubMed and PsycInfo databases was conducted, with no time limits. Of the 259 studies found, 14 were included in this review.

Results

Only studies on obsessive-compulsive disorder (OCD) were found. The executive function components of decision-making, planning, response inhibition, behavioral reversal/alternation, reversal learning and set-shifting/cognitive flexibility were considered to be a neurocognitive endophenotypes in OCD.

Conclusion

Further studies on executive functions as a neurocognitive endophenotype in other anxiety disorders are needed since these may have different neurocognitive endophenotypes and require other prevention and treatment approaches.

Whole-brain functional hypoconnectivity as an endophenotype of autism in adolescents

Endophenotypes are heritable and quantifiable markers that may assist in the identification of the complex genetic underpinnings of psychiatric conditions. Here we examined global hypoconnectivity as an endophenotype of autism spectrum conditions (ASCs). We studied well-matched groups of adolescent males with autism, genetically-related siblings of individuals with autism, and typically-developing control participants. We parcellated the brain into 258 regions and used complex-network analysis to detect a robust hypoconnectivity endophenotype in our participant group. We observed that whole-brain functional connectivity was highest in controls, intermediate in siblings, and lowest in ASC, in task and rest conditions. We identified additional, local endophenotype effects in specific networks including the visual processing and default mode networks. Our analyses are the first to show that whole-brain functional hypoconnectivity is an endophenotype of autism in adolescence, and may thus underlie the heritable similarities seen in adolescents with ASC and their relatives.

Neuroimaging endophenotypes in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response, and lead to the development of new therapies.

Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood

Neurocognitive abilities constitute complex traits with considerable heritability. Impaired neurocognition is typically observed in schizophrenia (SZ), whereas convergent evidence has shown shared genetic determinants between neurocognition and SZ. Here, we report a genome-wide association study (GWAS) on neuropsychological and oculomotor traits, linked to SZ, in a general population sample of healthy young males (n = 1079). Follow-up genotyping was performed in an identically phenotyped internal sample (n = 738) and an independent cohort of young males with comparable neuropsychological measures (n = 825). Heritability estimates were determined based on genome-wide single-nucleotide polymorphisms (SNPs) and potential regulatory effects on gene expression were assessed in human brain. Correlations with general cognitive ability and SZ risk polygenic scores were tested utilizing meta-analysis GWAS results by the Cognitive Genomics Consortium (COGENT) and the Psychiatric Genomics Consortium (PGC-SZ). The GWAS results implicated biologically relevant genetic loci encoding protein targets involved in synaptic neurotransmission, although no robust individual replication was detected and thus additional validation is required. Secondary permutation-based analysis revealed an excess of strongly associated loci among GWAS top-ranked signals for verbal working memory (WM) and antisaccade intra-subject reaction time variability (empirical P < 0.001), suggesting multiple true-positive single-SNP associations. Substantial heritability was observed for WM performance. Further, sustained attention/vigilance and WM were suggestively correlated with both COGENT and PGC-SZ derived polygenic scores. Overall, these results imply that common genetic variation explains some of the variability in neurocognitive functioning among young adults, particularly WM, and provide supportive evidence that increased SZ genetic risk predicts neurocognitive fluctuations in the general population.

Distinguishing Adolescents With ADHD From Their Unaffected Siblings and Healthy Comparison Subjects by Neural Activation Patterns During Response Inhibition

OBJECTIVE

Dysfunctional response inhibition is a key executive function impairment in attention deficit hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate affected from unaffected individuals. The authors therefore investigated neural correlates of response inhibition and the familial nature of these neural correlates.

METHODS

Functional MRI measurements of neural activation during the stop-signal task and behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy comparison subjects (N=124).

RESULTS

Stop-signal task reaction times were longer and error rates were higher in participants with ADHD, but not in their unaffected siblings, while reaction time variability was higher in both groups than in comparison subjects. Relative to comparison subjects, participants with ADHD and unaffected siblings had neural hypoactivation in frontal-striatal and frontal-parietal networks, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between levels of participants with ADHD and comparison subjects. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity.

CONCLUSIONS

Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings supports the familial nature of the underlying neural process. Activation deficits in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family.

Association of Oxytocin Receptor Gene (OXTR) rs53576 Polymorphism with Sociality: A Meta-Analysis

A common variant in the oxytocin receptor gene (OXTR), rs53576, has been broadly linked to socially related personality traits and behaviors. However, the pattern of published results is inconsistent. Here, we performed a meta-analysis to comprehensively evaluate the association. The literature was searched for relevant studies and effect sizes between individuals homozygous for the G allele (GG) and individuals with A allele carriers (AA/AG). Specifically, two indices of sociality were evaluated independently: i) general sociality (24 samples, n = 4955), i.e., how an individual responds to other people in general; and ii) close relationships (15 samples, n = 5262), i.e., how an individual responds to individuals with closed connections (parent-child or romantic relationship). We found positive association between the rs53576 polymorphism and general sociality (Cohen’s d = 0.11, p = .02); G allele homozygotes had higher general sociality than the A allele carriers. However, the meta-analyses did not detect significant genetic association between rs53576 and close relationships (Cohen’s d = 0.01, p = .64). In conclusion, genetic variation in the rs53576 influences general sociality, which further implies that it is worthy to systematically examine whether the rs53576 is a valid genetic marker for socially related psychiatric disorders.

Additional mechanisms conferring genetic susceptibility to Alzheimer's disease

Familial Alzheimer’s disease (AD), mostly associated with early onset, is caused by mutations in three genes (APP, PSEN1, and PSEN2) involved in the production of the amyloid β peptide. In contrast, the molecular mechanisms that trigger the most common late onset sporadic AD remain largely unknown. With the implementation of an increasing number of case-control studies and the upcoming of large-scale genome-wide association studies there is a mounting list of genetic risk factors associated with common genetic variants that have been associated with sporadic AD. Besides apolipoprotein E, that presents a strong association with the disease (OR∼4), the rest of these genes have moderate or low degrees of association, with OR ranging from 0.88 to 1.23. Taking together, these genes may account only for a fraction of the attributable AD risk and therefore, rare variants and epistastic gene interactions should be taken into account in order to get the full picture of the genetic risks associated with AD. Here, we review recent whole-exome studies looking for rare variants, somatic brain mutations with a strong association to the disease, and several studies dealing with epistasis as additional mechanisms conferring genetic susceptibility to AD. Altogether, recent evidence underlines the importance of defining molecular and genetic pathways, and networks rather than the contribution of specific genes.

Targeting dynamic interplay among disordered domains or endophenotypes to understand complex neuropsychiatric disorders: Translational lessons from preclinical models

Contemporary biological psychiatry uses clinical and experimental (animal) models to increase our understanding of brain pathogenesis. Modeling psychiatric disorders is currently performed by targeting various key neurobehavioral clusters of phenotypic traits (domains), including affective, cognitive, social, motor and reward. Analyses of such domains and their 'smaller units' - individual endophenotypes - are critical for the study of complex brain disorders and their neural underpinnings. The spectrum nature of brain disorders and the importance of pathogenetic linkage among various disordered domains or endophenotypes have also been recognized as an important strategic direction of translational research. Here, we discuss cross-domain analyses of animal models, and focus on their value for mimicking the clinical overlap between disordered neurobehavioral domains in humans. Based on recent experimental evidence, we argue that understanding of brain pathogenesis requires modeling the clinically relevant inter-relationships between various individual endophenotypes (or their domains).

Response inhibition in a subclinical obsessive-compulsive sample

BACKGROUND AND OBJECTIVES

Inconsistent findings across studies challenge the viability of response inhibition (RI) as an endophenotype of obsessive-compulsive disorder (OCD). Contemporary conceptualization of endophenotypes in psychiatric disorders suggests that these markers vary continuously in the general population, highlighting the importance of analogue sample research. Although neuropsychological functions have been studied in subclinical obsessive-compulsive (OC) samples, no study to date had examined RI in the context of the go/no-go paradigm.

METHODS

A subclinical OC sample (HOC; n = 27) and a low OC symptoms control sample (LOC; n = 25), as determined by the Obsessive-Compulsive Inventory-Revised, completed a go/no-go task and clinical questionnaires.

RESULTS

The groups did not differ on age, gender, or state anxiety. Controlling for depressive severity, the HOC group made significantly more commission errors and exhibited larger response time variability on the go/no-go task. However, standardized scores produced using population norms revealed that the HOC group performed within normative range.

LIMITATIONS

This study used a non-clinical sample and no structured clinical screening was performed.

CONCLUSIONS

Compared to LOC participants, a psychometrically-defined subclinical OC sample exhibited deficient RI and sustained attention. However, when raw scores were converted to age and education adjusted standardized scores according to the test's population norms, the HOC group task performance was in the normative range. These results, are in line with findings in OCD samples, suggesting that moderate degree of RI deficiencies is associated with the presence of OC symptomatology regardless of clinical status. However, the conceptualization of RI underperformance as an OCD disorder-specific impairment, remains controversial.

Endophenotypes for Alcohol Use Disorder: An Update on the Field

The endophenotype concept was first proposed as a strategy to use (purportedly) genetically simpler phenotypes in gene identification studies for psychiatric disorders, and is distinct from the closely related concept of intermediate phenotypes. In the area of alcohol use disorder (AUD) research, two candidate endophenotypes have produced replicable genetic associations: level of response to alcohol and neurophysiology markers (e.g., event-related oscillations and event-related potentials). Additional candidate endophenotypes from the cognitive, sensory, and neuroimaging literatures show promise, although more evidence is needed to fully evaluate their potential utility. Translational approaches to AUD endophenotypes have helped characterize the underlying neurobiology and genetics of AUD endophenotypes and identified relevant pharmacological interventions. Future research that capitalizes on the polygenic nature of endophenotypes and emphasizes endophenotypes that may change across development will enhance the usefulness of this concept to understand the genetically-influenced pathways toward AUD.

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees

BACKGROUND

Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees.

METHODS

A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage.

RESULTS

Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia.

CONCLUSIONS

With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

Missense variants in CFTR nucleotide-binding domains predict quantitative phenotypes associated with cystic fibrosis disease severity

Predicting the impact of genetic variation on human health remains an important and difficult challenge. Often, algorithmic classifiers are tasked with predicting binary traits (e.g. positive or negative for a disease) from missense variation. Though useful, this arrangement is limiting and contrived, because human diseases often comprise a spectrum of severities, rather than a discrete partitioning of patient populations. Furthermore, labeling variants as causal or benign can be error prone, which is problematic for training supervised learning algorithms (the so-called garbage in, garbage out phenomenon). We explore the potential value of training classifiers using continuous-valued quantitative measurements, rather than binary traits. Using 20 variants from cystic fibrosis transmembrane conductance regulator (CFTR) nucleotide-binding domains and six quantitative measures of cystic fibrosis (CF) severity, we trained classifiers to predict CF severity from CFTR variants. Employing cross validation, classifier prediction and measured clinical/functional values were significantly correlated for four of six quantitative traits (correlation P-values from 1.35 × 10(-4) to 4.15 × 10(-3)). Classifiers were also able to stratify variants by three clinically relevant risk categories with 85-100% accuracy, depending on which of the six quantitative traits was used for training. Finally, we characterized 11 additional CFTR variants using clinical sweat chloride testing, two functional assays, or all three diagnostics, and validated our classifier using blind prediction. Predictions were within the measured sweat chloride range for seven of eight variants, and captured the differential impact of specific variants on the two functional assays. This work demonstrates a promising and novel framework for assessing the impact of genetic variation.

Refining the latent structure of neuropsychological performance in schizophrenia

BACKGROUND

Elucidating the cognitive architecture of schizophrenia promises to advance understanding of the clinical and biological substrates of the illness. Traditional cross-sectional neuropsychological approaches differentiate impaired from normal cognitive abilities but are limited in their ability to determine latent substructure. The current study examined the latent architecture of abnormal cognition in schizophrenia via a systematic approach.

METHOD

Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were carried out on a large neuropsychological dataset including the Brief Assessment of Cognition in Schizophrenia, Continuous Performance Test, Wisconsin Card Sorting Test, Benton Judgment of Line Orientation Test, and Wechsler Abbreviated Scale of Intelligence matrix reasoning derived from 1012 English-speaking ethnic Chinese healthy controls and 707 schizophrenia cases recruited from in- and out-patient clinics.

RESULTS

An initial six-factor model fit cognitive data in healthy and schizophrenia subjects. Further modeling, which accounted for methodological variance between tests, resulted in a three-factor model of executive functioning, vigilance/speed of processing and memory that appeared to best discriminate schizophrenia cases from controls. Factor analytic-derived g estimands and conventionally calculated g showed similar case-control discrimination. However, agreement analysis suggested systematic differences between both g indices.

CONCLUSIONS

Factor structures derived in the current study were broadly similar to those reported previously. However, factor structures between schizophrenia subjects and healthy controls were different. Roles of factor analytic-derived g estimands and conventional composite score g were further discussed. Cognitive structures underlying cognitive deficits in schizophrenia may prove useful for interrogating biological substrates and enriching effect sizes for subsequent work.

Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease

Intermediate phenotypes are traits positioned somewhere between genetic variation and disease. They represent a target for attempts to find disease-associated genetic variants and elucidation of mechanisms. Psychiatry has been particularly enamoured with intermediate phenotypes, due to uncertainty about disease aetiology, inconclusive results in early psychiatric genetic studies, and their appeal relative to traditional diagnostic categories. In this review, we argue that new genetic findings are relevant to the question of the utility of these constructs. In particular, results from genome-wide association studies of psychiatric disorders now allow an assessment of the potential role of particular intermediate phenotypes. Based on such an analysis, as well as other recent results, we conclude that intermediate phenotypes are likely to be most valuable in understanding mechanism.

Genetic influences on alcohol use across stages of development: GABRA2 and longitudinal trajectories of drunkenness from adolescence to young adulthood

Longitudinal analyses allow us to understand how genetic risk unfolds across development, in a way that is not possible with cross-sectional analyses of individuals at different ages. This has received little attention in genetic association analyses. In this study, we test for genetic effects of GABRA2, a gene previously associated with alcohol dependence, on trajectories of drunkenness from age 14 to 25. We use data from 1070 individuals who participated in the prospective sample of the Collaborative Study on the Genetics of Alcoholism, in order to better understand the unfolding of genetic risk across development. Piecewise linear growth models were fit to model the influence of genotype on rate of increase in drunkenness from early adolescence to young adulthood (14-18 years), the change in drunkenness during the transition to adulthood (18-19 years) and the rate of change in drunkenness across young adulthood (≥ 19 years). Variation in GABRA2 was associated with an increase in drunkenness that occurred at the transition between adolescence and adulthood. The genotypic effect was more pronounced in females. These analyses illustrate the importance of longitudinal data to characterize how genetic effects unfold across development. The findings suggest that transitions across important developmental periods may alter the relative importance of genetic effects on patterns of alcohol use. The findings also suggest the importance of considering gender when evaluating genetic effects on drinking patterns in males and females.

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

Neurodevelopmental processes are widely believed to underlie schizophrenia. Analysis of brain texture from conventional magnetic resonance imaging (MRI) can detect disturbance in brain cytoarchitecture. We tested the hypothesis that patients with schizophrenia manifest quantitative differences in brain texture that, alongside discrete volumetric changes, may serve as an endophenotypic biomarker. Texture analysis (TA) of grey matter distribution and voxel-based morphometry (VBM) of regional brain volumes were applied to MRI scans of 27 patients with schizophrenia and 24 controls. Texture parameters (uniformity and entropy) were also used as covariates in VBM analyses to test for correspondence with regional brain volume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia.

Wnt signaling in neuropsychiatric disorders: ties with adult hippocampal neurogenesis and behavior

In an effort to better understand and treat mental disorders, the Wnt pathway and adult hippocampal neurogenesis have received increased attention in recent years. One is a signaling pathway regulating key aspects of embryonic patterning, cell specification and adult tissue homeostasis. The other is the generation of newborn neurons in adulthood that integrate into the neural circuit and function in learning and memory, and mood behavior. In this review, we discuss the growing relationship between Wnt signaling-mediated regulation of adult hippocampal neurogenesis as it applies to neuropsychiatric disorders. Evidence suggests dysfunctional Wnt signaling may aberrantly regulate new neuron development and cognitive function. Indeed, altered expression of key Wnt pathway components are observed in the hippocampus of patients suffering from neuropsychiatric disorders. Clinically-utilized mood stabilizers also proceed through modulation of Wnt signaling in the hippocampus, while Wnt pathway antagonists can regulate the antidepressant response. Here, we review the role of Wnt signaling in disease etiology and pathogenesis, regulation of adult neurogenesis and behavior, and the therapeutic targeting of disease symptoms.

Effects of omega-3 on behavioral and biochemical parameters in rats submitted to chronic mild stress

Major depression is a heterogeneous psychiatric disorder whose pathophysiology is not clearly established yet. Some studies have shown that oxidative stress and mitochondrial dysfunction are involved in the development of major depression. Since most depressed patients do not achieve complete remission of symptoms, new therapeutic alternatives are needed and omega-3 has been highlighted in this scenario. Therefore, we have investigated the effects of omega-3 on behavioral and biochemical parameters in rats submitted to chronic mild stress (CMS). Male Wistar rats were submitted to CMS for 40 days. After the CMS period, we administered a 500 mg/kg dose of omega-3 orally, once a day, for 7 days. The animals submitted to CMS presented anhedonia, had no significant weight gain, presented increased levels of lipid peroxidation and protein carbonylation, and inhibition of complex I and IV activities of the mitochondrial respiratory chain. The treatment with omega-3 did not reverse anhedonia; however, it reversed weight change, increased lipid peroxidation and protein carbonylation levels, and partially reversed the inhibition of mitochondrial respiratory chain complexes. The findings support studies that state that major depression is associated with mitochondrial dysfunction and oxidative stress, and that omega-3 supplementation could reverse some of these changes, probably due to its antioxidant properties.

A review of selected candidate endophenotypes for depression

Endophenotypes are proposed to occupy an intermediate position in the pathway between genotype and phenotype in genetically complex disorders such as depression. To be considered an endophenotype, a construct must meet a set of criteria proposed by Gottesman and Gould (2003). In this qualitative review, we summarize evidence for each criterion for several putative endophenotypes for depression: neuroticism, morning cortisol, frontal asymmetry of cortical electrical activity, reward learning, and biases of attention and memory. Our review indicates that while there is strong support for some depression endophenotypes, other putative endophenotypes lack data or have inconsistent findings for core criteria.