Overview

Since 1987 when the Clinical Brain Disorders Branch (CBDB) was created, its resources have been focused on understanding neurobiologic mechanisms of neuropsychiatric diseases, particularly schizophrenia. The principal objective of the Branch is to make major scientific discoveries that will lead to a meaningful understanding of schizophrenia and related disorders and that will lessen the suffering of affected patients and their families. As the human genome project gathered momentum and success by the mid 1990s, it became clear that the tools for identifying genes for complex, common medical disorders, such as mental illnesses, would be available soon and that genes could be studied directly in the context of clinical neurobiology. A reorganization of the lab began in 1996 to concentrate on genetic mechanisms of risk for schizophrenia and genetic effects on brain functional systems implicated in psychosis. Since the review of 2000, this reorganization is nearly complete, as most of the discretionary resources of the lab are now devoted to this task. The presentations to the BSC review will focus on evidence of at least seven genes identified or confirmed in CBDB as imparting risk for schizophrenia and efforts to characterize the mechanisms in brain by which these genes contribute to disease pathogenesis and to clinical phenomenology. The genetic breakthroughs of the past few years are viewed by us as the most important leads we have had in realizing the raison d’etre of this laboratory. The primary objective of ongoing work in CBDB is to translate genetic variation related to schizophrenia into the biologic and clinical mechanisms of the disorder and ultimately into prevention and effective treatment.

Historically, researchers in CBDB have had a substantial impact on the landscape of schizophrenia research and on the lives of schizophrenic patients. Specifically: 1) CBDB is largely responsible for generating the hypothesis that the origins of schizophrenia involve factors affecting brain development; 2) CBDB has played a major role in the worldwide research renaissance of the analysis of postmortem tissue; 3) CBDB is largely responsible for the demonstration that cognitive dysfunction is a core manifestation of schizophrenia and of genetic risk for schizophrenia, and for cognition in schizophrenia being a centerpiece of academic and industry research worldwide; 4) CBDB is responsible for the majority of the replicable body of major neuroimaging findings that have been associated with schizophrenia; and 5) CBDB is responsible for the development of the first complex animal model of schizophrenia that reproduces a constellation of pharmacological, molecular, developmental and behavioral phenomena associated with the illness. Since the review of 2000, CBDB has made substantial further advances in our understanding of schizophrenia, by identifying several novel genetic associations, and by demonstrating the first credible mechanisms in living and postmortem human brain by which variations in putative susceptibility genes affect brain biology related to illness. CBDB investigators also have identified the first specific genetic mechanisms for normal variation in human brain processing of memory and of emotion. We have pioneered a paradigm shift in psychiatric genetics, moving the field from mapping illness loci to identifying gene effects on information processing in brain. This progress is exemplified by our findings that three genes weakly related to psychiatric disorders (i.e.COMT, BDNF, and 5’HTTLPR) are strongly related to cognitive and emotional processing in brain, discoveries recently cited in the annual “breakthrough of the year” edition of Science as centerpieces of the second biggest scientific breakthrough of 2003 (“decoding mental illness”). Investigators in CBDB have also introduced a novel application of functional neuroimaging as a phenotyping tool for understanding genetic variation at the level of brain information processing (“imaging genomics”). CBDB is in the process of transitioning from a free-standing laboratory to a component of a larger program called, “Genes, Cognition and Psychosis” (GCAP).

The primary goal of ongoing research is to characterize how genes associated with schizophrenia affect brain development/plasticity and function and how these effects relate to the biology and clinical manifestations of the illness. This goal mandates a multidisciplinary team approach and this approach necessitates a unique laboratory structure. The organization of CBDB is in some respects like a University Center and to a considerable extent like a RAND investigative team, with resources centered on large projects requiring multiple disciplines and levels of expertise. The principle focus of each project is understanding the clinical and basic mechanisms by which a specific gene implicated in risk for schizophrenia impacts on brain biology. Each gene may be studied at many levels of analysis, from clinical association with disease phenotype and with intermediate phenotypes involving cognition, imaging and electrophysiology, to molecular analyses of functional effects of humanized mutations in model systems, to expression of mRNA and protein in human and animal brain, to creation of transgenic animal models, and to original therapeutic trials. Many of these projects also involve collaborations outside of CBDB. To tackle this daunting agenda, the branch chief has encouraged CBDB scientists to function as members of translational research teams to scientifically enrich the overall effort and to achieve a whole that is much greater than any of its component parts. This approach is a longstanding tradition in this lab and is possible because of the common purpose, sustained commitment and mutual trust of its faculty.

In addition to its PI’s, the lab has several core facilities that operate to provide archival datasets for the multidisciplinary teams and for PIs. These cores include: 1) A clinical study core directed by Michael Egan, M.D. which is responsible for all aspects of recruitment, clinical management, and data collection from the outpatient “Sibling Study”, the principal clinical genetic data engine, for recruitment and evaluation of inpatients for therapeutic trials, and for the maintenance and analyses of all archival datasets from these projects; 2) a neuropsychology core, directed by Terry Goldberg, Ph.D., which is responsible for the development and implementation of neurocognitive paradigms used in the Sibling Study and in therapeutic trials, and for the maintenance and analysis of these archival datasets; 3) a neuroimaging core, directed by Anand Mattay, M.D., which implements quality control procedures, optimizes and updates imaging protocols, and collects all clinical imaging data from the sibling and inpatients studies and maintains and analyzes all structural, spectroscopy, DTI, and large scale archival fMRI datasets used in these studies; 5) a postmortem tissue core, directed by Tomas Hyde, M.D., Ph.D, which is responsible for all aspects of postmortem human brain procurement, processing and database maintenance; and 6) a genetics/informatics core directed by Richard Straub, Ph.D, which is responsible for all DNA processing, genotyping, and gene informatics on clinical and postmortem samples, and for statistical analyses of all archival genetic data. Karen Berman, M.D. recently earned tenure and directs an independent neuroimaging unit within the branch that also studies data collected in the clinical, imaging, and genomics cores.

Because statistical association in complex genetic disorders, such as schizophrenia, is typically weak, and identification of functional mutations has been difficult, we have aimed to strengthen the statistical data with convergent biological evidence that genetic variation affects aspects of brain function implicated in the disorder. Our approach assumes that causative genes for complex disorders such as schizophrenia will not be conclusively identified by statistics, but will require evidence that the biology of the gene variation and the pathobiology of the illness converge (Weiss and Terwilliger 2001). This emphasis on genetic mechanisms of brain abnormalities associated with schizophrenia is based on the assumption that schizophrenia, per se, is not a singular genetic illness, but a variable combination of component traits (and genes) that interact with each other, with modifying nonsusceptibility alleles, and with the environment to produce the complex clinical phenotype (Weinberger 1999, Weinberger et al 2001). Further, hallucinations, delusions, and thought disorganization, the diagnostic symptoms of the disorder, are assumed to represent emergent manifestations of specific deficits in brain information processing, which can be decomposed at the biological and genetic levels. Results of our scientific work over the past four years have advanced our appreciation of the validity of these assumptions.

Summary of progress since 2000 BSC review

The “CBDB Sibling Study,” the centerpiece of the Clinical Studies Section, has studied over 360 families from around the USA, recruited as a family association “quad-based” dataset, comprising approximately 400 index cases, 470 unaffected siblings, both parents in most families, and also 450 unrelated controls. Lymphoblast cell lines have been established from most of these individuals. In addition to standard clinical instruments, subjects have undergone extensive examinations aimed at characterizing biologic intermediate phenotypes, including cognitive testing, eye tracking, functional and structural MRI, MRSI, various EEG evoked potentials (including P50 and P300), and recently MEG. In this sample, which represents the largest and most extensively investigated population of psychiatrically healthy siblings of patients with schizophrenia (by virtually an order of magnitude compared with most other studies), we have shown that phenotypes related to poor “signal to noise” of prefrontal cortical information processing, (e.g. measured with tests of executive cognition (Egan et al 2001, Goldberg et al Arch Gen Psych 2003), with fMRI (Callicott et al 2003) and with p300 (Winterer et al 2003)), are robust biological traits related to genetic risk for schizophrenia. We have genotyped approximately 500 SNPs in over 100 genes in the CBDB dataset, in 150 of the NIMHGI families and in several collaborative datasets. Significant associations based on distorted allele transmission to affected (but not unaffected) offspring in families have been found for a number of genes, including: COMT (22q), DTNBP1 (6p), GRM3 (7q), GAD1 (2q), NRG1 (8p), DISC1 (1q), and MRDS1 (6p). In addition, evidence will be presented that all of these genes show greater penetrance for intermediate phenotypes based on specific brain information processing paradigms (e.g. cognitive assays of memory, fMRI during prefrontal engagement) than for clinical diagnosis, and that some genes that are negative for clinical diagnosis in our datasets show association with these intermediate phenotypes (e.g. RGS4, G72). These findings argue strongly that susceptibility genes for schizophrenia impact on specific aspects of cortical information processing, that these effects can be studied with in vivo assessments even in well individuals, and that these effects are more directly related to susceptibility gene biology than are the clinical symptoms. Moreover, the biological associations in brain point to pathways and mechanisms by which genes impact on risk and these insights inform us about the basic nature of the disease. We are using genetic information in novel pharmacological trials, including genotype based studies of drugs aimed at enchancing prefrontal cortical signal to noise ratio, including amphetamine, modafinil, atomoxatine, and tolcopone.

The Neuropathology Section has transformed itself into a seamless component of the gene discovery program. Expression of mRNA and protein for each of the susceptibility genes is in various stages of progress (qRT-PCR, ELISA, Immuno blots, slide based mRNA and protein analyses) and examples will be presented for COMT, DTNBP1, NRG1, GRM3 and DISC1. Genotype at each of the loci implicated in the clinical data is being used as a grouping variable for candidate molecular expression analyses that address potential pathophysiologic mechanisms (e.g. COMT and TH, GRM3 and BDNF, and DTNBP1 and GABRa), and for region-specific gene expression profiling. We are in the process of completing expression profile analyses based on COMT genotype and similarly for other genes (using cDNA filter arrays, glass oligonucleotide arrays [NHGRI and AFFY], and MPSS). Future studies are aimed at characterization of genotype effects on transcript splicing, protein profiling, and gene and protein expression analyses of transgenic mice including siRNA mice (which have the potential to abnormally express multiple susceptibility alleles in the same animal). The principal future goal is discovery and in depth molecular characterization of novel targets based on convergence of expression analyses of human and animal tissue parsed by the genetic architecture of risk.

Highlights of Genetic Findings:

COMT: The role of the val¹⁵⁸met functional polymorphism in COMT as a risk gene for psychosis has been elaborated at a number of levels. We have found further association for schizophrenia in the NIMHGI dataset, and have shown that there is an interaction with sex and val/met genotype, potentially related to the role of estrogen in COMT transcriptional regulation or to differential implications of prefrontal deficits on illness expressivity. Interestingly, there is evidence of potential allelic heterogeneity in COMT, as a promoter SNP is associated with schizophrenia in one of our three family association datasets, the other two being positive for val. We have performed studies of enzyme activity in lymphoblasts and in a large sample of postmortem human brain specimens (over 150) and find very strong effects of the val/met polymorphism, a moderate effect of the promoter variant, but no effects of other SNPs. Both alleles associated with schizophrenia (i.e. val and the common promoter variant) are high COMT activity alleles. Basic science evidence that COMT critically impacts on prefrontal DA signaling has led to a series of hypothesis-driven experiments to elucidate the effects of COMT val/met genotype in brain. For example, we have shown that COMT genotype predicts TH mRNA expression in normal human brainstem, accounting for a two-fold variation (Akil et al 2003). We have confirmed our original finding of an effect of COMT genotype on prefrontal cortical executive cognition (Goldberg et al 2003), which now has been replicated by over six other groups around the world, and which represents the first genetic mechanism of normal variation in human executive cognition. We also have replicated in several new datasets our original observation that COMT genotype predicts the efficiency or focusing of prefrontal activity measured with fMRI, and we have shown that this effect interacts with amphetamine in normal subjects (Mattay et al 2003). This study represents the first demonstration of a potential genetic mechanism of variable responses to amphetamine. We preformed the first in situ histochemistry analysis of COMT mRNA expression in normal human brain and have shown that its expression is most abundant in prefrontal and hippocampal neurons (Matsumoto et al 2003). Finally, initial studies in normal subjects of tolcopone, a CNS active COMT inhibitor, reveal that as predicted, it enhances prefrontal cortical efficiency measured with fMRI but appears not to impact on striatal function.

Dysbindin (DTNBP1): We have performed the most comprehensive genetic and biologic investigations of DTNBP1 to date, including extensive SNP genotyping and resequencing . We have confirmed strong association in two independent family datasets and have narrowed the haplotype to a potential intronic regulatory region. The DTNBP1 risk alleles in our patients appear to impact on basic aspects of cortical function, including IQ and speed of information processing, and a spectrum of prefrontal and temporal related cognitive functions. In human brain, we have shown that dysbindin mRNA and dysbindin protein are both reduced in schizophrenic cases and expression is predicted by variation in the gene (Shannon-Weickert et al in press).

GRM3: We have identified association with variation in GRM3 also in three family datasets and strong relationships to other measures of glutamate signaling in living and in postmortem brain, including: prefrontal and hippocampal cognition, fMRI measures of hippocampal and prefrontal function, and NAA concentrations in both regions in living subjects. In postmortem tissue, GRM3 genotype is related to molecular markers of synaptic activity, including at presynaptic, postsynaptic, and astroglial sites. The high risk GRM3 genotype is related to underexpression of two presynaptic proteins in the hippocampus, SNAP-25 and synaptophysin, to reduced expression of BDNF in postsynaptic neurons, and to reduced expression of EAAT2, the glial glutamate transporter, which is regulated by GRM3 and is critically important in synaptic glutamate levels (Egan et al in press).

DISC1: We have identified the first high-risk SNP and haplotype in DISC1 associated with schizophrenia, and have a potentially functional polymorphism in the gene showing positive association. This high-risk ser allele also is associated with abnormalities in prefrontal and hippocampal function even in normal subjects, and also with a striking effect on hippocampal volume in normal subjects (Callicott et al submitted). Two common DISC1 transcripts have been measured with qRTPCR in human prefrontal and hippocampal cortices of adult brain, but no effects of genotype or of disease have been found for these transcripts.

NRG1: We have confirmed association to NRG1 in our family datasets, but our high-risk haplotype is near the Type III promoter, not near the core haplotype of the original reports from Europe. Our NRG1 risk alleles predict aspects of memory function and NAA measures in prefrontal cortex. We have performed the first quantitative gene expression analysis of NRG1 in human brain and found an abnormal ratio of NRG1 isoforms in schizophrenic prefrontal cortex (Hashimoto et al 2003). Due to space constraints, the clinical genetic data about NRG1 are not described in Section on Clinical Studies report.

MRDS1: We have discovered a novel gene in the 6p24 linkage region and have identified genetic variations that are associated with schizophrenia in two independent datasets. We have cloned multiple transcripts from human brain and have shown that genetic variation in the gene also is associated with variation in working and episodic memory.

GAD1: We have identified the first genetic association to variation in GAD1, which is the gene most consistently found to be abnormally expressed in schizophrenic brain tissue. Variation in GAD1 was strongly associated with abnormal cognitive processing of episodic and working memory.

BDNF: We performed a series of translational studies on a potential functional variation in the signal sequence of BDNF (val⁶⁶met) and demonstrated in neuronal culture that trafficking and regulated secretion of BDNF were disrupted by the derived allele (Egan et al 2003). In human populations, this allele affected hippocampal function and memory and had a dramatic impact in normal subjects on declarative memory efficacy (Hariri et al 2003). This was the first evidence in humans of a role of BDNF in hippocampal function and in learning and memory and the first specific gene related to normal variation in human episodic memory in young people. Our original finding of a relationship between BDNF genotype and episodic memory has been independently replicated by investigators at the Institute of Psychiatry in London (R. Murray, personal communication).

5HTTLPR: Interest in the serotonin transporter promoter functional polymorphism has been considerable, but the clinical literature is weak and inconsistent. We were the first to show with neuroimaging that this variation affected the expression of the protein as assayed with in vivo radioligand binding potential (Heinz et al 2000). We studied with fMRI the effect of this polymorphism at the level of emotional processing in the amygdala and showed a dramatic effect, consistent with models of stress and depression and amygdala processing (Hariri et al 2002). This fMRI study has been now replicated by two other groups, as well as by us in a large sample of over ninety normal subjects. We have found, moreover, that this polymorphism is associated with specific changes in amygdala volume in normal subjects, a possible developmental anlagen of risk for mood and anxiety disorders.

Future Studies

Investigators in CBDB are using these genetic leads to broaden our understanding of disease mechanisms, to search for new potential treatment targets, and to define the genetic architecture of risk. These future efforts will take place in the larger context of the Genes, Cognition and Psychosis program, which will move this effort ahead in several specific dimensions: 1) We will expand collection of CBDB-type clinical datasets, including the establishment of at least three new CBDB Sibling Study “clones” at other academic centers in the USA and in Europe. This will strengthen the effort to identify gene-gene and gene-environment interactions. 2) We will revise phenotype characterizations, including focusing on specific subsystems in working memory and executive cognition, to utilize MEG to achieve greater temporal resolution with high spatial fidelity for early information processing phenotypes. 3) Extensive resequencing of clinical samples for each of the susceptibility genes will be completed within the next year, and genotyping of promising functional polymorphisms will follow. Reanalysis of the intermediate phenotype database will serve as a triage strategy for identifying potentially functional alleles. 4) Therapeutic trials based on drugs that target pathways implicated by these genes, with genotype as a grouping variable, will be initiated at the NIMH and at our collaborating centers. 5) Basic studies of gene structure and function will commence within the larger program structure, to include full transcript characterization of each gene in several human brain regions and cell populations, to develop functional cell based assays for characterizing gene and allele function and interacting metabolic networks, and to create animal models based on humanized alleles. 6) Postmortem brain studies will include further characterization of gene and protein expression patterns in normal and in schizophrenic tissue and gene and protein expression profiling techniques, which will stress carefully matched samples of normal subjects grouped by genotype, using updated information from resequencing and functional assays, to search for molecular pathways that are impacted by functional variation in the target genes. In the long run, we will aim to map and integrate the pathways of convergence of risk factors and to elucidate the molecular networks that they engage.