Linda M. Brzustowicz - US grants

DESCRIPTION (Adapted from applicant's abstract): This is a revised application for a Mentored Clinical Scientist Development Award. The purpose of this application is to acquire a theoretical statistical background and training in particular multivariate techniques, to be used to examine psychiatric symptom data in the members of families with a high rate of schizophrenia, to develop alternative classifications of affection status for use in genetic linkage studies. Support through this award would enable the applicant to develop a unique area of expertise within the field of psychiatric genetics, contributing to the long-term career goal of research independence. The contribution of genetic factors to the etiology of schizophrenia is well accepted. Multiple family studies have demonstrated elevated rates of schizophrenia and other psychiatric disorders within the families of schizophrenic probands. Numerous unsuccessful gene linkage studies of schizophrenia have been conducted, using traditional clinical diagnoses to define affection status. One possible factor contributing to these difficulties is that current clinical diagnoses do not accurately correspond to the patterns of symptoms seen in individuals from families with a high rate of schizophrenia. Analysis of the transmission patterns of individual symptom data, not only the overall diagnosis, may lead to a more useful definition of affection status for linkage studies.

DESCRIPTION (Investigator's Abstract): Schizophrenia is a serious neuropsychiatric illness estimated to affect 1.3 percent of the adult population in the United States. Family, twin and adoption studies have demonstrated that schizophrenia is predominantly genetic, with a high heritability. The complex genetics, phenotypic uncertainty, and unclear role of environmental interactions have led to the discouraged view that significant genetic linkage will not be easily obtained. None of the linkage reports published to date detail a finding of significant magnitude to serve as a starting point for positional cloning. We have recently concluded a genome-wide search for loci contributing to risk for schizophrenia, and multipoint analysis with markers from 1q21-22 have produced a maximum LOD score of 6.50 between the markers D1S1653 and D1S1679, with an estimated 75 percent of families linked to this locus. Further mapping has reduced the interval containing this gene to less than 2 Mb. We propose a project to develop a dense map of polymorphic markers within this currently defined minimum genetic region, for use in crossover and linkage disequilibrium analyses to further narrow the region containing the gene. Using sequence data from the Human Genome Project, we then plan to identify a comprehensive list of gene in the new minimum genetic region and systematically screen them for mutations using temperature gradient gel electrophoresis on a sample of subjects with very high (greater than 95 percent) conditional probability of linkage to 1Q21-22. Simulation studies suggest that we will have sufficient power to identify the true susceptibility gene. We plan to screen this gene for mutations in the remainder of our linkage sample and in the schizophrenia subjects in the NIMH Center for Genetics Studies sample. The identification of a gene involved in schizophrenia susceptibility will allow insight into the earliest genesis of this debilitating illness. Screening for mutations in this gene in larger, unrelated samples will allow for an estimate of the prevalence of the effect of this locus in the general population. Controlling for the effects of this gene in genetic linkage studies should increase the power to identify other susceptibility loci. Unraveling the genetics of this complex disorder will also facilitate the investigation of the environmental triggers of disease expression, and could ultimately lead to strategies to prevent the onset of clinical symptoms.

EXCEED THE. SPACE PROVIDED. Autism is a serious neurodevelopmental disorder characterized by deficits in communication, abnormal social interactions, and rigid or repetitive interests and behaviors. Although there is strong evidence of an important genetic contribution to the cause of autism, the isolation of specific genetic defects that cause autism has been difficult. We plan to pursue two complementary avenues to search for autism susceptibility genes. First, we will conduct linkage analysis on a set of 150 nuclear family units collected and assessed for this project. Ascertained through a proband with autism, immediate and, when available, extended family members will be characterized by a battery of instruments that examine the domains of language ability, social relatedness, and repetitive and rigid/compulsive behavior. Each of these domains has demonstrated heritability, and impariments in these domains are found at increased rates among non-autistic relatives of probands with autism. Our recent genetic linkage study on specific language impairment (SLI) suggests that at least one susceptibility locus is shared between SLI and autism. We plan to calculate the heritability of the items in our test battery in our sample, and select the most heritable for use in linkage analysis. We will use a two-stage design, completing a full 9 cM density genome scan on the first 75 families, genotyping the remaining families at loci producing suggestive linkage results. The entire sample will be used for fine-mapping of any highly suggestive or significant linkage results. The second strategy to search for autism susceptibility genes will be to conduct large-scale association analyses using trios (proband with autism and two parents) from the families collected for this project, as well as the collections from AGRE, the NIMH Human Genetics Initiative samples and the Coriell Autism Resource samples. We anticipate approximately 850 trios will be suitable and available for use. As association methods have power to detect genetic effects that may be poorly detected by linkage, we will use this sample to investigate regions that have demonstrated suggestive linkage to autism or language phenotypes in our work and the work of others.

DESCRIPTION (provided by applicant): Schizophrenia is a serious neuropsychiatric illness estimated to affect approximately 1% of the general population. Family, twin and adoption studies have demonstrated that schizophrenia is predominantly a genetic disorder, with a high heritability. Segregation analyses have failed to clearly support a single model of inheritance and suggest at least several, possibly interacting, susceptibility loci. We have previously identified a strong linkage signal (hlod=6.5, empirical p less than 0.0002) to 1q22 in a set of medium-sized Canadian families, selected for study because multiple relatives were clinically diagnosed with schizophrenia or schizoaffective disorder. Fine-map linkage analysis has identified an approximately 1.3 Mb interval that appears very likely to harbor the susceptibility gene, with a 300 kb sub-region identified by linkage as most likely to contain the gene. We have further identified significant linkage disequilibrium (LD) within a 100 kb portion of this sub-interval. The region of LD is contained within the over 300 kb genomic extent of the gene ICAPON, and there is evidence that additional genes may exist within the introns of this large gene. We plan to search this region for additional transcribed sequences to screen for variants associated with schizophrenia susceptibility. We also plan to use comparative genomic techniques to identify conserved regulatory regions within this area. These will also be assessed for variation that is associated with schizophrenia susceptibility. The sample with strong linkage to this region will first be tested for LD, with the NIMH-HGI collection and a Canadian case-control sample also genotyped with markers producing significant LD in the linkage sample. We also plan to conduct expression studies of protein and RNA, using RNA from the Stanley Array Collection, post-mortem brains from the Harvard Brain Bank, and lymphoblastoid cell lines from our linkage sample and the NIMH-HGI collection. We hope to use our investigations of this locus in this sample as a testbed for refining a comprehensive approach to susceptibility gene identification, combining linkage and linkage disequilibrium mapping, evolutionary based sequence comparison methods, and complementary gene expression studies. We anticipate that these methods will be of future use for finding additional susceptibility genes for schizophrenia and other complex disorders.

DESCRIPTION (provided by applicant): The autism spectrum disorders (ASD) are a group of serious neurodevelopmental disorders characterized by deficits in communication, abnormal social interactions, and rigid or repetitive interests and behaviors. Although there is strong evidence of an important genetic contribution to the cause of ASD, the isolation of specific causative genetic defects has been difficult. This project will use existing DMA and clinical data from the AGRE and NIMH repositories to search for ASD susceptibility genes. Aim 1 will focus on the analysis of genotype data using an alternative, Bayesian approach to linkage analysis, based on the posterior probability of linkage (PPL). This method was selected as the main analysis approach as it has been demonstrated to be far more effective in extracting accurate information from gene-mapping studies of heterogeneous disorders than any of the current model-based or model-free alternatives, greatly aiding the localization of susceptibility genes. Aim 2 will focus on fine linkage and linkage disequilibrium mapping of regions identified in Aim 1. PPL linkage peaks will initially be narrowed through 1-2 cM density microsatellite mapping, followed by very high density SNP mapping. SNP genotyping will be conducted using an inexpensive, robust, flexible and scalable genotyping system based on allele-specific ligation. An extension of the PPL that incorporates Linkage Disequilibrium (LD) will be used for LD mapping of candidate genes within the linkage peaks. Aim 3 will investigate whether associated haplotypes functionally alter the candidate genes using lymphoblastoid and post-mortem samples as well as in vitro neuronal cultures and mouse knock-ins to analyze developmentally relevant cell types. Upon completion of these experiments, it is likely that ASD-associated alleles for multiple genes will be identified. Through our extensive functional analysis, we will be able to demonstrate that some of the associated haplotypes functionally alter the associated genes, making them likely candidates for risk alleles and providing genetic evidence that these genes likely act as ASD susceptibility loci. The mouse models that will be generated for some of these associated haplotypes will provide a more amenable system for future developmental, behavioral and toxicology experiments. These accomplishments will lead to important translational research so that better diagnoses, treatments and preventions can be developed for ASD.

[unreadable] DESCRIPTION (provided by applicant): microRNAs are powerful regulatory molecules that are abundantly expressed in the developing and adult mammalian brain. Many primate-specific microRNAs are now known, making this class of genes attractive candidates for involvement in brain disorders such as schizophrenia and bipolar affective disorder. Little is know about the pattern of expression of microRNAs in the brains of normally developing humans or individuals with these disorders. Multiple possible mechanisms exist through which microRNAs could play a role in disease. This project will utilize a variety of experimental approaches to increase our knowledge of the normal expression and function of microRNAs in the developing and adult brain, and investigate the possible role of microRNA in the susceptibility to schizophrenia and bipolar disorder. First, we will quantify microRNA expression in normal human brain tissue from several developmental stages as well as from a matched set of samples from individuals with schizophrenia, bipolar disorder, and psychiatrically normal controls (35 individuals from each group) to provide baseline knowledge about microRNA expression in the normally developing human brain and search for evidence that some microRNAs are improperly expressed in schizophrenia and/or bipolar disorder. Second, we will search for population variability in the sequences of microRNAs and their targets in mRNAs of interest in schizophrenia and bipolar disorder, as these may be functional variants that increase disease risk. Third, we will test these candidate variants, as well as tagSNPs from a limited number of microRNA clusters, for association to schizophrenia and bipolar disorder using trios from the NIMH Genetic Initiative collection. Fourth, we will develop a list of 12 microRNAs of greatest interest based on evidence of involvement in the biology of schizophrenia and bipolar disorder from the prior three steps, and use a cell culture/transfection system to manipulate microRNA expression and validate mRNA targets. Fifth, we will characterize the temporal and spatial expression of the 12 microRNAs of interest and select targets. Sixth, we will use a cell culture/transfection system to systematically characterize the cell biological consequences of alteration in microRNA expression on neuronal development and functioning. A better understanding of microRNA function in the normal and pathological state could provide novel insights into new therapeutic approaches for schizophrenia and bipolar disorder. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): The autism spectrum disorders (ASD) are a group of serious neurodevelopmental disorders characterized by deficits in communication, abnormal social interactions, and rigid or repetitive interests and behaviors. Although there is strong evidence of an important genetic contribution to the cause of ASD, the isolation of specific causative genetic defects has been difficult. This project will use existing DMA and clinical data from the AGRE and NIMH repositories to search for ASD susceptibility genes. Aim 1 will focus on the analysis of genotype data using an alternative, Bayesian approach to linkage analysis, based on the posterior probability of linkage (PPL). This method was selected as the main analysis approach as it has been demonstrated to be far more effective in extracting accurate information from gene-mapping studies of heterogeneous disorders than any of the current model-based or model-free alternatives, greatly aiding the localization of susceptibility genes. Aim 2 will focus on fine linkage and linkage disequilibrium mapping of regions identified in Aim 1. PPL linkage peaks will initially be narrowed through 1-2 cM density microsatellite mapping, followed by very high density SNP mapping. SNP genotyping will be conducted using an inexpensive, robust, flexible and scalable genotyping system based on allele-specific ligation. An extension of the PPL that incorporates Linkage Disequilibrium (LD) will be used for LD mapping of candidate genes within the linkage peaks. Aim 3 will investigate whether associated haplotypes functionally alter the candidate genes using lymphoblastoid and post-mortem samples as well as in vitro neuronal cultures and mouse knock-ins to analyze developmentally relevant cell types. Upon completion of these experiments, it is likely that ASD-associated alleles for multiple genes will be identified. Through our extensive functional analysis, we will be able to demonstrate that some of the associated haplotypes functionally alter the associated genes, making them likely candidates for risk alleles and providing genetic evidence that these genes likely act as ASD susceptibility loci. The mouse models that will be generated for some of these associated haplotypes will provide a more amenable system for future developmental, behavioral and toxicology experiments. These accomplishments will lead to important translational research so that better diagnoses, treatments and preventions can be developed for ASD.

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific Challenge Topic 03-MH-101*: Biomarkers in Mental Disorders. The overall goal of this proposal is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Clearly, alternative genetic study designs are needed to complement existing studies. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. This critical gap will be filled by our project. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Overall, we plan to combine analysis of behavioral and genetic biomarkers to develop more accurate models for the prediction of risk for autism spectrum disorders. Our existing detailed clinical and behavioral information, as well as plans for follow-up assessments, will also provide important preliminary data for future comparative effectiveness studies on elements of clinical course and treatment response related to specific biomarkers. It is hoped that these studies will provide substantive insights into the causes of, and effective treatments for, autism. Autism is a serious and debilitating disorder. While there is strong evidence supporting a significant genetic component to the disorder, the identification of specific susceptibility genes has been difficult. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

DESCRIPTION (provided by applicant): One childhood stressor - child maltreatment - represents a serious public health concern. In 2007, over 3 million children were referred to child protection service agencies for suspected maltreatment in the United States and about 794,000 were determined by state and local child protective service agencies to be victims of maltreatment (DHHS, 2009). Increasing evidence shows that childhood physical and sexual abuse and (more recently) neglect have extensive short- and long-term consequences across multiple domains, including psychiatric, social, emotional, behavioral, academic, and physical functioning, and developmental time points. The associated costs to society have been estimated at billions of dollars annually. At the same time, the negative sequelae of childhood victimization are not inevitable. While explanations for these different outcomes remain unknown, research has begun to examine factors that might buffer or protect maltreated children from negative consequences. Recent research has reported significant interactions between childhood maltreatment and genetic variation in predicting psychological and behavioral outcomes, including violence and antisocial behavior, depression, anxiety, suicidality, alcoholism, and substance use. The overarching goal of the proposed research is to test three competing models of the processes whereby child abuse and neglect lead to mental and physical health consequences in adulthood. The research proposed here represents a continuation of a longitudinal study begun in 1986 with a large group of documented cases of childhood physical and sexual abuse and neglect (ages 0-11) and a comparison group of non-abused and non-neglected children who were matched on the basis of age, sex, race/ethnicity, and approximate family social class and followed up into adulthood with four interviews. We propose to use blood and saliva samples that have already been collected as part of previous waves of the study. Our goal is to identify, genotype, and analyze genetic variants and to determine whether they play a role in the long-term physical and mental health consequences of child abuse and neglect. The proposed research will lead to increased understanding of the multiple pathways through which stressful childhood experiences (such as child neglect and abuse) lead to the development of different mental and physical health outcomes and is in keeping with President Obama's emphasis on health care education and the prevention of negative health outcomes. Determining the interplay between genetic and environmental factors that increase risk for negative physical and mental health outcomes or promote resiliency among abused and neglected children has implications for treatment and prevention efforts for these children. By determining whether a particular environment (such as an abusive or neglectful home) is particularly problematic for children with certain genes, we hope that the proposed research will provide directions for focused interventions. PUBLIC HEALTH RELEVANCE: Child maltreatment, one major source of childhood stress, is a serious public health problem, with about 800,000 substantiated cases of childhood victimization each year. Recent research has reported significant interactions between child maltreatment and genetic variations in predicting psychological and behavioral outcomes. The overarching goal of the proposed research is to test three models that have been proposed to understand the linkages between childhood maltreatment and long-term physical and mental health consequences and, ultimately, may lead to the development of appropriate intervention strategies.

DESCRIPTION (provided by applicant): One childhood stressor - child maltreatment - represents a serious public health concern. In 2007, over 3 million children were referred to child protection service agencies for suspected maltreatment in the United States and about 794,000 were determined by state and local child protective service agencies to be victims of maltreatment (DHHS, 2009). Increasing evidence shows that childhood physical and sexual abuse and (more recently) neglect have extensive short- and long-term consequences across multiple domains, including psychiatric, social, emotional, behavioral, academic, and physical functioning, and developmental time points. The associated costs to society have been estimated at billions of dollars annually. At the same time, the negative sequelae of childhood victimization are not inevitable. While explanations for these different outcomes remain unknown, research has begun to examine factors that might buffer or protect maltreated children from negative consequences. Recent research has reported significant interactions between childhood maltreatment and genetic variation in predicting psychological and behavioral outcomes, including violence and antisocial behavior, depression, anxiety, suicidality, alcoholism, and substance use. The overarching goal of the proposed research is to test three competing models of the processes whereby child abuse and neglect lead to mental and physical health consequences in adulthood. The research proposed here represents a continuation of a longitudinal study begun in 1986 with a large group of documented cases of childhood physical and sexual abuse and neglect (ages 0-11) and a comparison group of non-abused and non-neglected children who were matched on the basis of age, sex, race/ethnicity, and approximate family social class and followed up into adulthood with four interviews. We propose to use blood and saliva samples that have already been collected as part of previous waves of the study. Our goal is to identify, genotype, and analyze genetic variants and to determine whether they play a role in the long-term physical and mental health consequences of child abuse and neglect. The proposed research will lead to increased understanding of the multiple pathways through which stressful childhood experiences (such as child neglect and abuse) lead to the development of different mental and physical health outcomes and is in keeping with President Obama's emphasis on health care education and the prevention of negative health outcomes. Determining the interplay between genetic and environmental factors that increase risk for negative physical and mental health outcomes or promote resiliency among abused and neglected children has implications for treatment and prevention efforts for these children. By determining whether a particular environment (such as an abusive or neglectful home) is particularly problematic for children with certain genes, we hope that the proposed research will provide directions for focused interventions.

DESCRIPTION (provided by applicant): The goal of the NIMH Human Genetics Initiative (HGI) is to further understand the genetic and environmental etiologies of mental disorders. One of the major mechanisms for accomplishing this goal is the NIMH Center for Collaborative Genomics Research on Mental Disorders (the Center), which receives raw biosamples such as blood from NIMH PIs. The Center processes samples to DNA, RNA, cDNA or cell lines, which can then be submitted for genomic analyses. Along with biosamples the Center receives clinical/phenotypic data for each subject and, eventually, the results of genomic analyses. After a proprietary period, the clinical data, genomic data, DNA, RNA, cDNA and cell lines are made available to all NIMH-approved researchers through a. secure web site. This sharing of uniformly processed biological samples and clinical and genomic data from many cohorts leverages the NIMH investment in a large number of HGI grants. It provides critical research power by providing a large body of data applicable to investigations on the genetic bases for individual mental disorders. Since October 1998, >147,000 subject samples have been submitted and the Center has distributed >310,000 DNA samples and >9,000 cell lines. There have been >450 distributions of clinical and genotype data to ~340 investigators and >260 publications using these samples and data. Starting in 2011 the Center provided cell line banking and characterization services for induced pluripotent stem cells (iPSC) and their progenitor somatic cells. The Center also develops novel bioinformatics and computational genomics tools and methodologies designed to integrate and analyze large, independent sets of genotypic and phenotypic data while resolving phenotype and/or genotype discrepancies in datasets. As its guiding aim, the Center will continue to innovate in order to serve the scientific needs of NIMH PIs in a flexible and highly accessible manner, while respecting subject confidentiality, informed consent issues and PI prerogatives.

Project Summary The goal of the NIMH Repository and Genomics Resource (NRGR) is to further the understanding of the genetic and environmental etiologies of mental disorders. The NRGR receives raw biosamples, such as blood, from NIMH-supported research projects. The NRGR processes these samples to DNA, RNA, cDNA, or cell lines, which can then be used for genomic analyses. The NRGR also receives, curates, and harmonizes clinical/phenotypic data for each subject. Results of genomic analyses on samples in the NRGR are either directly deposited in the NRGR or are linked to a deposit in another public repository. After a proprietary period, the clinical data, genomic data, DNA, RNA, cDNA, and cell lines are made available to all NIMH- approved researchers through a secure web portal. This sharing of uniformly processed biological samples and curated clinical and genomic data from many cohorts leverages the NIMH investment in genetic studies. It provides critical research power by making a very large body of data available for study of the genetic bases for individual mental disorders. Since October 1998, >203K subject samples have been submitted to NRGR and >590K DNA and >15K cell lines have been distributed. There have been >1,500 distributions of clinical and genomic data to nearly 1,000 investigators, resulting in >700 publications using NRGR samples and data. Starting in 2011, the NRGR has provided in-depth characterization services for induced pluripotent stem cells (iPSC) and their progenitor somatic cells, as well as limited iPSC production. The NRGR also develops novel bioinformatics and computational genomics tools and methodologies designed to integrate and analyze large, independent sets of genotypic and phenotypic data while resolving phenotype and/or genotype discrepancies. As its guiding aim, the NRGR will continue to innovate in order to serve the scientific needs of NIMH PIs in a flexible and highly accessible manner, while respecting subject confidentiality, informed consent issues, and PI prerogatives.

Project Summary The goal of the NIMH Repository and Genomics Resource (NRGR) is to further the understanding of the genetic and environmental etiologies of mental disorders. The NRGR receives raw biosamples, such as blood, from NIMH-supported research projects. The NRGR processes these samples to DNA, RNA, cDNA, or cell lines, which can then be used for genomic analyses. The NRGR also receives, curates, and harmonizes clinical/phenotypic data for each subject. Results of genomic analyses on samples in the NRGR are either directly deposited in the NRGR or are linked to a deposit in another public repository. After a proprietary period, the clinical data, genomic data, DNA, RNA, cDNA, and cell lines are made available to all NIMH- approved researchers through a secure web portal. This sharing of uniformly processed biological samples and curated clinical and genomic data from many cohorts leverages the NIMH investment in genetic studies. It provides critical research power by making a very large body of data available for study of the genetic bases for individual mental disorders. Since October 1998, >250K subject samples have been submitted to NRGR and >615K DNA and >15K cell lines have been distributed. There have been >1,700 distributions of clinical and genomic data to >1,000 investigators, resulting in >1,000 publications using NRGR samples and data. Starting in 2011, the NRGR has provided in-depth characterization services for induced pluripotent stem cells (iPSC) and their progenitor somatic cells, as well as limited iPSC production. As its guiding aim, the NRGR will continue to innovate in order to serve the scientific needs of NIMH PIs in a flexible and highly accessible manner, while respecting subject confidentiality, informed consent issues, and PI prerogatives.