Statistical genetics concepts and approaches in schizophrenia and related neuropsychiatric research

Endophenotypes in Schizophrenia: Digging Deeper to Identify Genetic Mechanisms

Schizophrenia (SZ) is a severe psychotic disorder that is highly heritable and common in the general population. The genetic heterogeneity of SZ is substantial, with contributions from common, rare, and de novo variants, in addition to environmental factors. Large genome-wide association studies have detected many variants that are associated with SZ, yet the pathways by which these variants influence risk remain largely unknown. SZ is also clinically heterogeneous, with patients exhibiting a broad range of deficits and symptom severity that vary over the course of illness and treatment, which has complicated efforts to identify risk variants. However, the underlying brain dysfunction forms a more stable trait marker that quantitative neurocognitive and neurophysiological endophenotypes may be able to objectively measure. These endophenotypes are less likely to be heterogeneous than the disorder and provide a neurobiological context to detect risk variants and underlying pathways among genes associated with SZ diagnosis. Furthermore, many endophenotypes are translational into animal model systems, allowing for direct evaluation of the neural circuit dysfunctions and neurobiological substrates. We review a selection of the most promising SZ endophenotypes, including prepulse inhibition, mismatch negativity, oculomotor antisaccade, letter-number sequencing, and continuous performance tests. We also highlight recent findings from large consortia that suggest the potential role of genes, particularly in the neuregulin and glutamate pathways, in several of these endophenotypes. Although endophenotypes require additional time and effort to assess, the insight into the underlying neurobiology that they provide may ultimately reveal the underlying genetic architecture for SZ and suggest novel treatment targets.

Random Projection for Fast and Efficient Multivariate Correlation Analysis of High-Dimensional Data: A New Approach

In recent years, the advent of great technological advances has produced a wealth of very high-dimensional data, and combining high-dimensional information from multiple sources is becoming increasingly important in an extending range of scientific disciplines. Partial Least Squares Correlation (PLSC) is a frequently used method for multivariate multimodal data integration. It is, however, computationally expensive in applications involving large numbers of variables, as required, for example, in genetic neuroimaging. To handle high-dimensional problems, dimension reduction might be implemented as pre-processing step. We propose a new approach that incorporates Random Projection (RP) for dimensionality reduction into PLSC to efficiently solve high-dimensional multimodal problems like genotype-phenotype associations. We name our new method PLSC-RP. Using simulated and experimental data sets containing whole genome SNP measures as genotypes and whole brain neuroimaging measures as phenotypes, we demonstrate that PLSC-RP is drastically faster than traditional PLSC while providing statistically equivalent results. We also provide evidence that dimensionality reduction using RP is data type independent. Therefore, PLSC-RP opens up a wide range of possible applications. It can be used for any integrative analysis that combines information from multiple sources.

The importance of endophenotypes in schizophrenia research

Endophenotypes provide a powerful neurobiological platform from which we can understand the genomic and neural substrates of schizophrenia and other common complex neuropsychiatric disorders. The Consortium on the Genetics of Schizophrenia (COGS) has conducted multisite studies on carefully selected key neurocognitive and neurophysiological endophenotypes in 300 families (COGS-1) and then in a follow up multisite case-control study of 2471 subjects (COGS-2). Endophenotypes are neurobiologically informed quantitative measures that show deficits in probands and their first degree relatives. They are more amenable to statistical analysis than are "fuzzy" qualitative clinical traits or confoundingly heterogeneous diagnostic categories. Endophenotypes are also viewed as uniquely informative in traditional diagnosis-based as well as emerging NIMH Research Domain (RDoC) contexts, offering a bridge between the two approaches to psychopathology classification and research. Endo- or intermediate phenotypes are heritable, and in the COGS-1 cohort their level of heritability is in the same range as is the heritability of schizophrenia itself, using the same statistical methods and subjects to assess both. Because we can demonstrate endophenotypes link to both gene networks and neural circuits on the one hand and also to real-life function, endophenotypes provide a critically important bridge for "connecting the dots" between genes, cells, circuits, information processing, neurocognition and functional impairment and personalized treatment selection in schizophrenia patients. By connecting schizophrenia risk genes with neurobiologically informed endophenotypes, and via the use of association, linkage, sequencing, stem cell and other strategies, we can provide our field with new neurobiologically informed information in our efforts to understand and treat schizophrenia. Evolving views, data and new analytic strategies about schizophrenia risk, pathology and treatment are described in this Viewpoint and in the accompanying Special Issue reports.

The impact of clinical heterogeneity in schizophrenia on genomic analyses

Though clinically useful, the diagnostic systems currently employed are not well equipped to capture the substantial clinical heterogeneity observed for most psychiatric disorders, as exemplified by the complex psychotic disorder(s) that Bleuler aptly labeled the "Group of Schizophrenias". The clinical heterogeneity associated with schizophrenia has likely frustrated decades of attempts to illuminate the underlying genetic architecture, although recent genome-wide association studies have begun to provide valuable insight into the role of common genetic risk variants. Here we demonstrate the importance of using diagnostic information to identify a core form of the disorder and to eliminate potential comorbidities in genetic studies. We also demonstrate why applying a diagnostic screening procedure to the control dataset to remove individuals with potentially related disorders is critical. Additionally, subjects may participate in multiple studies at different institutions or may have genotype data released by more than one research group. It is thus good practice to verify that no identical subjects exist within or between samples prior to conducting any type of genetic analysis to avoid potential confounding of results. While the availability of genomic data for large collections of subjects has facilitated many investigations that would otherwise not have been possible, we clearly show why one must use caution when acquiring data from publicly available sources. Although the broad vs. narrow debate in terms of phenotype definition in genetic analyses will remain, it is likely that both approaches will yield different results and that both will have utility in resolving the genetic architecture of schizophrenia.

Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology

With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.

Substantial genetic link between IQ and working memory: implications for molecular genetic studies on schizophrenia. the European twin study of schizophrenia (EUTwinsS)

While evidence is accumulating to support specific neurocognitive deficits as putative endophenotypes for schizophrenia, the heritability of these deficits in healthy subjects and whether they share common genetic influences, is not well established. In the present study, 529 healthy adult twins from two centers within the European Twin Study Network on Schizophrenia (EUTwinsS) were assessed on two domains that are consistently found to be particularly compromised in schizophrenia. Specifically, Intellectual Quotient Score (IQ) and the Letter-Number Sequencing Test (LNS), a measure of working memory, were measured in all twins. Latent variable components were explored through structural equation modeling, and common genetic underpinnings were examined using bivariate analyses. Results showed that the phenotypic correlation between IQ and working memory was almost entirely attributed to shared genetic variance (95.5%). We discuss the potential use of a combined measure of IQ and working memory to improve the power of molecular studies in detecting the genetic mechanisms underlying schizophrenia.

Genome-wide linkage analyses of 12 endophenotypes for schizophrenia from the Consortium on the Genetics of Schizophrenia

OBJECTIVE

The Consortium on the Genetics of Schizophrenia has undertaken a large multisite study to characterize 12 neurophysiological and neurocognitive endophenotypic measures as a step toward understanding the complex genetic basis of schizophrenia. The authors previously demonstrated the heritability of these endophenotypes; in the present study, genetic linkage was evaluated.

METHOD

Each family consisted of a proband with schizophrenia, at least one unaffected sibling, and both parents. A total of 1,286 participants from 296 families were genotyped in two phases, and 1,004 individuals were also assessed for the endophenotypes. Linkage analyses of the 6,055 single-nucleotide polymorphisms that were successfully assayed, 5,760 of which were common to both phases, were conducted using both variance components and pedigree-wide regression methods.

RESULTS

Linkage analyses of the 12 endophenotypes collectively identified one region meeting genome-wide significance criteria, with a LOD (log of odds) score of 4.0 on chromosome 3p14 for the antisaccade task, and another region on 1p36 nearly meeting genome-wide significance, with a LOD score of 3.5 for emotion recognition. Chromosomal regions meeting genome-wide suggestive criteria with LOD scores >2.2 were identified for spatial processing (2p25 and 16q23), sensorimotor dexterity (2q24 and 2q32), prepulse inhibition (5p15), the California Verbal Learning Test (8q24), the degraded-stimulus Continuous Performance Test (10q26), face memory (10q26 and 12p12), and the Letter-Number Span (14q23).

CONCLUSIONS

Twelve regions meeting genome-wide significant and suggestive criteria for previously identified heritable, schizophrenia-related endophenotypes were observed, and several genes of potential neurobiological interest were identified. Replication and further genomic studies are needed to assess the biological significance of these results.

Systems biology, bioinformatics, and biomarkers in neuropsychiatry

Although neuropsychiatric (NP) disorders are among the top causes of disability worldwide with enormous financial costs, they can still be viewed as part of the most complex disorders that are of unknown etiology and incomprehensible pathophysiology. The complexity of NP disorders arises from their etiologic heterogeneity and the concurrent influence of environmental and genetic factors. In addition, the absence of rigid boundaries between the normal and diseased state, the remarkable overlap of symptoms among conditions, the high inter-individual and inter-population variations, and the absence of discriminative molecular and/or imaging biomarkers for these diseases makes difficult an accurate diagnosis. Along with the complexity of NP disorders, the practice of psychiatry suffers from a "top-down" method that relied on symptom checklists. Although checklist diagnoses cost less in terms of time and money, they are less accurate than a comprehensive assessment. Thus, reliable and objective diagnostic tools such as biomarkers are needed that can detect and discriminate among NP disorders. The real promise in understanding the pathophysiology of NP disorders lies in bringing back psychiatry to its biological basis in a systemic approach which is needed given the NP disorders' complexity to understand their normal functioning and response to perturbation. This approach is implemented in the systems biology discipline that enables the discovery of disease-specific NP biomarkers for diagnosis and therapeutics. Systems biology involves the use of sophisticated computer software "omics"-based discovery tools and advanced performance computational techniques in order to understand the behavior of biological systems and identify diagnostic and prognostic biomarkers specific for NP disorders together with new targets of therapeutics. In this review, we try to shed light on the need of systems biology, bioinformatics, and biomarkers in neuropsychiatry, and illustrate how the knowledge gained through these methodologies can be translated into clinical use providing clinicians with improved ability to diagnose, manage, and treat NP patients.

Association analysis of 94 candidate genes and schizophrenia-related endophenotypes

While it is clear that schizophrenia is highly heritable, the genetic basis of this heritability is complex. Human genetic, brain imaging, and model organism studies have met with only modest gains. A complementary research tactic is to evaluate the genetic substrates of quantitative endophenotypes with demonstrated deficits in schizophrenia patients. We used an Illumina custom 1,536-SNP array to interrogate 94 functionally relevant candidate genes for schizophrenia and evaluate association with both the qualitative diagnosis of schizophrenia and quantitative endophenotypes for schizophrenia. Subjects included 219 schizophrenia patients and normal comparison subjects of European ancestry and 76 schizophrenia patients and normal comparison subjects of African ancestry, all ascertained by the UCSD Schizophrenia Research Program. Six neurophysiological and neurocognitive endophenotype test paradigms were assessed: prepulse inhibition (PPI), P50 suppression, the antisaccade oculomotor task, the Letter-Number Span Test, the California Verbal Learning Test-II, and the Wisconsin Card Sorting Test-64 Card Version. These endophenotype test paradigms yielded six primary endophenotypes with prior evidence of heritability and demonstrated schizophrenia-related impairments, as well as eight secondary measures investigated as candidate endophenotypes. Schizophrenia patients showed significant deficits on ten of the endophenotypic measures, replicating prior studies and facilitating genetic analyses of these phenotypes. A total of 38 genes were found to be associated with at least one endophenotypic measure or schizophrenia with an empirical p-value<0.01. Many of these genes have been shown to interact on a molecular level, and eleven genes displayed evidence for pleiotropy, revealing associations with three or more endophenotypic measures. Among these genes were ERBB4 and NRG1, providing further support for a role of these genes in schizophrenia susceptibility. The observation of extensive pleiotropy for some genes and singular associations for others in our data may suggest both converging and independent genetic (and neural) pathways mediating schizophrenia risk and pathogenesis.

Brain electrophysiological endophenotypes for externalizing psychopathology: a multivariate approach

Abnormalities in electrophysiological measures of stimulus-evoked brain activity (including the P3 event-related potential (ERP) and its associated delta and theta time-frequency (TF) components), and intrinsic, resting state brain activity (including EEG in the beta frequency band) have each been associated with biological vulnerability to a variety of externalizing (EXT) spectrum disorders, such as substance use disorders, conduct disorder, and antisocial behavior. While each of these individual measures has shown promise as an endophenotype for one or more aspects of EXT, we proposed that the power to identify EXT-related genes may be enhanced by using these measures collectively. Thus, we sought to explore a multivariate approach to identifying electrophysiological endophenotypes related to EXT, using measures identified in the literature as promising individual endophenotypes for EXT. Using data from our large twin sample (634 MZ and 335 DZ, male and female same-sex pairs), and fitting multivariate biometric Cholesky models, we found that these measures (1) were heritable, (2) showed significant phenotypic and genetic correlation with a general vulnerability to EXT (which is itself highly heritable), (3) showed modest phenotypic and genetic correlation with each other, and (4) were sensitive to genetic effects that differed as a function of gender. These relationships suggest that these endophenotypes are likely tapping into neurophysiological processes and genes that are both common across them and unique to each-all of which are relevant to a biological vulnerability to EXT psychopathology.

Heritability of neurocognitive traits in familial schizophrenia

Neurocognitive deficits are considered promising endophenotypes for gene discovery in schizophrenia. Understanding the heritability and genetic inter-relationships of neurocognitive traits could support their use as alternatives to diagnosis. Participants were 85 adults from 17 multiplex Canadian families with familial schizophrenia linked to 1q23 who had neurocognitive testing results available. Heritability of 13 standard measures assessing motor skills, processing speed, verbal, and visuospatial memory, attention/working memory, executive functioning, and IQ was estimated using variance component models and SOLAR software. We then investigated bivariate relationships between those variables found to be heritable. IQ showed the highest heritability (h(2) = 0.64-0.74) and seven other neurocognitive measures, reflecting immediate and delayed verbal memory, attention/working memory, delayed visual memory, processing speed and motor skills, showed significant heritability (h(2) = 0.31-0.62) under one or more of the models assessed. A schizophrenia diagnostic covariate was significant (P < 0.0001) for all heritable variables. Bivariate analyses suggested that memory-IQ and visuomotor-processing speed formed two groups of heritable traits. The results provide further evidence of the heritability of selected neurocognitive measures, and their relationship to schizophrenia and underlying genetic architecture. Composite measures of memory or processing speed may be heritable phenotypes useful for studies of neurocognition.

Toward a better identification and treatment of schizophrenia prodrome

The prodromal period leading to schizophrenia has been the focus of significant interest in recent years. This is due not only to the possibility of identification of preschizophrenic states but also to the potential for improving prognosis as a result of early intervention. There are many approaches to the identification of the schizophrenia prodrome. Interventions in the prodromal period have met with various degrees of success. In this article, the authors present an overview of the literature reflecting the development of the prodromal concept and its implications for early identification. They also discuss various interventions proposed for this period and some ethical considerations related to these interventions. Despite the growing body of knowledge in this field, there is a need for more research data to support the establishment of treatment guidelines. Future directions of research are also discussed.

Expression of NR1, NR2A and NR2B NMDA receptor subunits is not altered in the genetically-inbred Balb/c mouse strain with heightened behavioral sensitivity to MK-801, a noncompetitive NMDA receptor antagonist

The genetically-inbred Balb/c mouse strain shows heightened sensitivity to the ability of MK-801 (dizocilpine), a noncompetitive NMDA receptor antagonist, to raise the threshold voltage necessary to precipitate tonic hindlimb extension and elicit irregular episodes of intense jumping behavior (referred to as "popping"), relative to other inbred mouse strains and the outbred NIH Swiss mouse. Moreover, an allosteric modulatory effect of sarcosine, a glycine reuptake inhibitor, on MK-801's antagonism of electrically precipitated seizures was detected 24 h after Balb/c mice were forced to swim in cold water for up to 10 min; this was not observed in unstressed Balb/c mice or stressed or unstressed NIH Swiss mice. Phencyclidine (PCP), a noncompetitive NMDA receptor antagonist that binds to the same hydrophobic channel domain as MK-801, precipitates a schizophreniform psychosis in susceptible individuals that shares descriptive similarities with schizophrenia. This observation has led to the hypothesis that NMDA receptor hypofunction (NRH) is involved in the pathophysiology of schizophrenia and the testing of pharmacotherapeutic strategies to facilitate NMDA receptor-mediated neurotransmission in patients with this disorder (e.g., glycine reuptake inhibitors). The heightened behavioral sensitivity of the Balb/c mouse to MK-801 suggests that this mouse strain may be a useful model to study "psychosis-proneness" and screen for positive allosteric modulators of NMDA receptor-mediated neurotransmission. Conceivably, strain differences in the pharmacology of the NMDA receptor are due to differences in the relative expression of individual NMDA receptor subunits to each other (i.e., combinatorial regulation). The current study compared the normal protein expression patterns of six of the eight identified splice variant isoforms of the NR1 NMDA receptor subunit, and NR2A and NR2B subunits in the hippocampus and cerebral cortex of Balb/c and NIH Swiss mice. The heightened behavioral sensitivity of the Balb/c genetically-inbred mouse strain to MK-801, compared to the outbred NIH Swiss mouse strain, does not appear to result from relative alterations of expression of these NMDA receptor protein subunits that were examined.

Verbal working memory impairments in individuals with schizophrenia and their first-degree relatives: findings from the Consortium on the Genetics of Schizophrenia

Working memory (WM) impairment is a promising candidate endophenotype for schizophrenia that could facilitate the identification of susceptibility genes for this disorder. The validity of this putative endophenotype was assessed by determining whether 149 probands with schizophrenia and 337 of their first-degree relatives demonstrated WM impairment as compared to 190 unaffected community comparison subjects. Subjects were participants in the Consortium on the Genetics of Schizophrenia (COGS) project, a seven-site research network that was established to investigate the genetic architecture of endophenotypes for schizophrenia. Participants received comprehensive clinical assessments and completed two verbal WM tasks, one requiring transient on-line storage and another requiring maintenance plus complex manipulation of information by reordering the stimuli. Schizophrenia probands performed worse than the other groups on both tasks, with larger deficits found for the more challenging reordering WM task. The probands' relatives performed more poorly than community comparison subjects on both tasks, but the difference was significant only for the more challenging maintenance plus complex manipulation WM task. This WM impairment was not attributable to diagnoses of schizophrenia spectrum disorder, mood disorders, or substance use disorders in the relatives. In conjunction with evidence that WM abilities are substantially heritable, the current results support the validity and usefulness of verbal WM impairments in manipulation of information as endophenotypes for schizophrenia in large-scale genetic linkage and association studies.

Powerful designs for genetic association studies that consider twins and sibling pairs with discordant genotypes

Genetic association studies are becoming commonplace due to the availability of cost-effective yet sophisticated DNA sequencing and genotyping resources and technologies. In addition, technologies designed to identify molecular and subclinical phenotypes that reflect disease pathogenesis are continually being developed and refined (consider, e.g., imaging technologies, microarray-based gene expression and proteomic platforms, histological analyses of excised tissues, etc.). Unfortunately, the large-scale use of many of these molecular and subclinical phenotyping technologies in genetic association studies is difficult logistically and is currently cost-prohibitive. In this paper, we consider efficient designs for testing the association between particular genetic variations and expensive, yet appropriate, subclinical phenotypes of relevance to a disease that take advantage of twins or sibling pairs discordant for genotypes at the locus (or loci) being tested. We demonstrate that including genotypically discordant twins or siblings in an association study can result in a substantial increase in power over designs that use monozygotic twins or only unrelated individuals. We ultimately argue that, from a practical standpoint, sampling from existing family or twin-based cohorts in which: (1) follow-up studies of a genetic association are warranted in order to assess the in vivo significance of an association with respect to more refined pathological phenotypes; and/or (2) large-scale, genome-wide linkage and association studies have been pursued that have focused on clinical endpoints for which the study subjects have consented to more elaborate follow-up studies, is a powerful way to test associations.

The Consortium on the Genetics of Endophenotypes in Schizophrenia: model recruitment, assessment, and endophenotyping methods for a multisite collaboration

BACKGROUND

The Consortium on the Genetics of Schizophrenia (COGS) is an ongoing, National Institute of Mental Health-funded, 7-site collaboration investigating the occurrence and genetic architecture of quantitative endophenotypes related to schizophrenia. The purpose of this article is to provide a description of the COGS structure and methods, including participant recruitment and assessment.

METHODS

The hypothesis-driven recruitment strategy ascertains families that include a proband with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosis of schizophrenia, and at least one unaffected full sibling available for genotyping and endophenotyping, along with parents available for genotyping and (optional depending on age) endophenotyping. The family structure is selected to provide contrast in quantitative endophenotypic traits and thus to maximize the power of the planned genetic analyses. Probands are recruited from many sources including clinician referrals, local National Alliance for the Mentally Ill chapters, and advertising via the media. All participants undergo a standardized protocol that includes clinical characterization, a blood draw for genotyping, and endophenotype assessments (P50 suppression, prepulse inhibition, antisaccade performance, continuous performance tasks, letter-number span, verbal memory, and a computerized neurocognitive battery). Investigators participate in weekly teleconferences to coordinate and evaluate recruitment, clinical assessment, endophenotyping, and continuous quality control of data gathering and analyses. Data integrity is maintained through use of a highly quality-assured, centralized web-based database.

RESULTS

As of February 2006, 355 families have been enrolled and 688 participants have been endophenotyped, including schizophrenia probands (n = 154, M:F = 110:44), first-degree biological relatives (n = 343, M:F = 151:192), and community comparison subjects (n = 191, M:F = 81:110).

DISCUSSION

Successful multisite genetics collaborations must institute standardized methodological criteria for assessment and recruitment that are clearly defined, well communicated, and uniformly applied. In parallel, studies utilizing endophenotypes require strict adherence to criteria for cross-site data acquisition, equipment calibration and testing and software equivalence, and continuous quality assurance for many measures obtained across sites. This report describes methods and presents the structure of the COGS as a model of multisite endophenotype genetic studies. It also provides demographic information after the first 2 years of data collection on a sample for whom the behavioral data and genetics of endophenotype performance will be fully characterized in future articles. Some issues discussed in the reviews that follow reflect the challenges of evaluating endophenotypes in studies of the genetic architecture of endophenotypes in schizophrenia.

Deconstructing schizophrenia: an overview of the use of endophenotypes in order to understand a complex disorder

The genetics of schizophrenia has been approached utilizing a variety of methods. One emerging strategy is the use of endophenotypes in order to understand and identify the functional importance of genetically transmitted, brain-based deficits across schizophrenia kindreds. The endophenotype strategy is a topic of this issue of Schizophrenia Bulletin. Endophenotypes are quantitative, heritable, trait-related deficits typically assessed by laboratory-based methods rather than clinical observation. Endophenotypes are seen as closer to genetic variation than are clinical symptoms of schizophrenia, and are therefore closely linked to heritable risk factors. There has been a broad expansion of opportunities available to psychiatric neuroscientists who use the endophenotype strategy to understand the genetic basis of schizophrenia. In this context, genetic variation such as single nucleotide polymorphisms (SNPs) induces abnormalities in endophenotypic domains such as neurocognition, neurodevelopment, metabolism, and neurophysiology. This article discusses the challenges that abound in genetic research of schizophrenia, including issues in ascertainment, epistasis, ethnic diversity, and the potentially normalizing effects of second-generation antipsychotic medications on neurocognitive and neurophysiological measures. Robust strategies for meeting these challenges are discussed in this review and the subsequent articles in this issue. This article summarizes conceptual advances and progress in the measurement and use of endophenotypes in schizophrenia that form the basis of the multisite National Institute of Mental Health Consortium on the Genetics of Schizophrenia. The endophenotype strategy offers powerful and exciting opportunities to understand the genetically conferred neurobiological vulnerabilities and possible new strong inference and molecularly based treatments for schizophrenia.