2014 — 2017 |
Mccarroll, Steven Andrew |
U01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
2/3-Whole Genome Sequencing For Schizophrenia and Bipolar Disorder in the Gpc
? DESCRIPTION (provided by applicant): The goal of this collaborative project among investigators led by Drs. Michael Boehnke at the University of Michigan, Steven McCarroll of Harvard University and the Broad Institute, and Carlos Pato at the University of Southern California, is to use high-throughput DNA sequencing to identify genes and pathways that contribute to the risk for schizophrenia and bipolar disorder, and to construct a data resource for future genetic studies of these and other psychiatric disorders. This proposal builds on active collaborations among our groups on these important disorders and more generally on our experience in building genome variation resources, such as the 1000 Genomes Project, that are used throughout human genetics. Our research team combines strengths in high-throughput genetics and genomics, development and application of innovative computational and statistical analyses that maximize the benefits of new technologies, and leadership of large scientific consortia. In four Specific Aims, we propose whole genome sequencing (at ~30x coverage) and statistical analysis of 10,000 well-phenotyped and re-contactable individuals from the Genomic Psychiatry Cohort (GPC), equally divided among schizophrenia cases, bipolar cases, and psychiatrically normal controls, and comprised of equal numbers of European-Ancestry (EA), African-Ancestry (AA), and Latino individuals. We will carry out association analysis comparing schizophrenia cases to controls, bipolar cases to controls, and the combined cases to controls in the resulting sequence data, and by collaboration and meta-analysis with other investigators with relevant sequence data that become available. We will also use these sequence data as part of a reference panel to impute into tens of thousands of other genomes in the broader Psychiatric GWAS Consortium (PGC) data to allow association analysis based on substantially larger numbers of individuals. Finally, we will share data and methods to support similar studies of other psychiatric phenotypes and more broadly across the scientific community. The successful completion of these aims will provide new insights into molecular etiology that could catalyze breakthroughs in the prevention, treatment, and diagnosis of schizophrenia and bipolar disorder.
|
0.903 |
2015 — 2017 |
Mccarroll, Steven Andrew |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
2/3-Genetic Analysis of the International Cohort Collection For Bipolar Disorder
? DESCRIPTION (provided by applicant): The grant, Genetic Analysis of the International Cohort Collection for Bipolar Disorder, is continuation of a long-standing collaborative effort funded in response to an RFA for sample collections in bipolar disorder. We are thus submitting the current new application from the original group of investigators to continue the collaboration and proceed to its next logical step analyses of data being generated. We developed the International Cohort Collection for Bipolar Disorder in response to a NIMH FOA MH08-130. Under the auspices of R01MH085542 (Smoller/Sklar, PIs) and philanthropic funding we implemented a phenotypically robust, rapid, and cost effective method for sample collection. During the five years of the grant we have banked DNA from ~18,000 cases and 16,000 controls never previously used for genomic study of bipolar disorder (BD). We propose here enhanced aims in a unique sample to increase our knowledge of BD and to keep this highly productive team intact. The samples studied here will more than double the available samples for GWAS, and will be among the first to analyze rare variants using exome chip and exome sequencing. These analyses will provide substantially enhanced power for detection of networks and loci that confer BD risk. In Aim 1 we will perform a genomic characterization of an independent cohort of 15,800 cases and 18,598 controls to identify high confidence genetic loci for risk of BD through association study of common single nucleotide polymorphisms, copy number variants, and rare single nucleotide variants. We will further use the data to explore genetic prediction models for BD for two specific clinical scenarios. In Aim 2 we will apply these data to characterize the spectrum of genotype-phenotype relationships by examining phenotypic subgroups, cross- disorder relationships, quantitative personality dimensions, and neurocognition. Our goal is to learn more about the genetics of BD and how genes might act to alter disease risk. We propose to do this using the largest and most comprehensively studied sample collection in the field that includes both genetic and phenotypic risk factors.
|
0.903 |
2017 — 2021 |
Mccarroll, Steven Andrew |
P50Activity Code Description: To support any part of the full range of research and development from very basic to clinical; may involve ancillary supportive activities such as protracted patient care necessary to the primary research or R&D effort. The spectrum of activities comprises a multidisciplinary attack on a specific disease entity or biomedical problem area. These grants differ from program project grants in that they are usually developed in response to an announcement of the programmatic needs of an Institute or Division and subsequently receive continuous attention from its staff. Centers may also serve as regional or national resources for special research purposes. |
Computational and Statistical Genomics Analysis Core @ Boston Children's Hospital
PROJECT SUMMARY / ABSTRACT Research Support Core The goal of this research support core is to facilitate the successful utilization of genome sequencing, RNA sequencing, and Drop-seq across the Conte projects by providing software, statistical analysis, scientist- friendly analysis tools, and advice to scientists across all projects. We will do this by providing expert, timely analyses and advising scientists in the statistical interpretation of genome-scale data.
|
0.901 |
2017 — 2021 |
Mccarroll, Steven Andrew |
P50Activity Code Description: To support any part of the full range of research and development from very basic to clinical; may involve ancillary supportive activities such as protracted patient care necessary to the primary research or R&D effort. The spectrum of activities comprises a multidisciplinary attack on a specific disease entity or biomedical problem area. These grants differ from program project grants in that they are usually developed in response to an announcement of the programmatic needs of an Institute or Division and subsequently receive continuous attention from its staff. Centers may also serve as regional or national resources for special research purposes. |
Critical Periods and Complement Regulation in Diverse Cns Cell Types @ Boston Children's Hospital
PROJECT SUMMARY / ABSTRACT Project 1 In Conte Center Project 1, we will work to understand how cells of the central nervous system regulate the expression of complement and other immune proteins, and the extent to which this regulation is coupled to function and dysfunction at synapses. We will pursue these questions through experiments on clinical, post mortem, and biological samples. We will determine how the expression of C4A and C4B is regulated by allelic variation, cell type, and upstream biology (Aim 1). We will describe at single-cell resolution how diverse CNS cell types respond to synaptic dysfunction, utilizing the Drop-seq technology we developed to analyzed transcriptional responses in tens of thousands of individual cells (Aim 2). Finally, we will carefully evaluate cerebrospinal fluid as a potential reservoir of information about neural-immune interactions in the CNS (Aim 3). Through this work, we hope to better understand how neural-immune interactions play out through gene expression and may become visible in a clinical context.
|
0.901 |
2017 — 2021 |
Arlotta, Paola (co-PI) [⬀] Babadi, Mehrtash (co-PI) [⬀] Mccarroll, Steven Andrew Nehme, Ralda |
U01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes
Genetic studies have identified many specific loci with significant associations to psychiatric disorders. However, unless we can develop useful approaches for systematically turning genetic information into neurobiological insights about brain disorders, there is a danger that costly and hard-won genetic findings will not be exploitable to understand pathophysiology and generate important therapeutic hypotheses. The goal of our collaborative, interdisciplinary effort is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease. To do this, we propose to develop new experimental and inferential systems to bridge a longstanding gap between human genetics and experimental biology. We aim to identify biological causes and effects that span the genetic, molecular, and cellular levels of the nervous system. Our interdisciplinary team will develop new experimental systems that measure genetic influences across levels of analysis (RNA, proteins, and cellular function including physiology) in precise, scalable, well- controlled ways. We will make use of emerging cellular systems including three-dimensional cortical spheroids and organoids, and radically novel ?population in a dish? experimental systems that collect data on cells from hundreds of donors in a shared environment, inferring donor identity at the time of phenotypic readout. The analysis of such systems in turn requires sophisticated inferential strategies and new ideas from computer science. We propose to develop and widely share experimental and computational resources, including cell lines, methods, datasets, and analytic tools. The successful completion of this work will identify key neurobiological processes for multiple psychiatric disorders, and fortify many other scientists in making such connections in their own work. We hope in so doing to create a new kind of interdisciplinary science that ? by combining the strengths of data-driven, unbiased human genetics with the power of emerging experimental systems ? transforms the rate at which human- genetic leads lead to insights about disease mechanisms.
|
0.903 |
2017 — 2021 |
Carroll, Michael Craig Mccarroll, Steven Andrew Stevens, Beth Ann [⬀] |
P50Activity Code Description: To support any part of the full range of research and development from very basic to clinical; may involve ancillary supportive activities such as protracted patient care necessary to the primary research or R&D effort. The spectrum of activities comprises a multidisciplinary attack on a specific disease entity or biomedical problem area. These grants differ from program project grants in that they are usually developed in response to an announcement of the programmatic needs of an Institute or Division and subsequently receive continuous attention from its staff. Centers may also serve as regional or national resources for special research purposes. |
Neural-Immune Mechanisms and Synaptic Connectivity in Psychiatric Illness @ Boston Children's Hospital
The pathophysiological processes underlying neuropsychiatric disorders have been unknown; as a result, these disorders have lacked innovative medical therapies with new mechanisms of action. We recently identified the alleles underlying the human genome's largest population-level influence on risk of schizophrenia ? a series of structural alleles of the complement C4A and C4B genes, each of which appears to affect schizophrenia risk in proportion to the amount of C4A expression it generates in the brain. We also found that C4 shapes synaptic refinement in a mouse model of postnatal activity-dependent synapse elimination. These findings may help explain known features of schizophrenia, including reduced numbers of synapses in key cortical regions and an adolescent age of onset that corresponds with developmentally timed waves of synaptic pruning in these regions. The goal of the work we envision for a Conte Center is to develop our understanding of neural-immune interactions and synapses while also generating novel scientific resources that can be used to evaluate current and future hypotheses about schizophrenia-implicated genes, neural-immune interactions, and critical periods for synaptic refinement. Our proposed work arises from close, successful collaboration of scientists with expertise in genomics, immunology, and neuroscience. We aim to accomplish our Center's missions through scientific projects and cores. Project 1 will seek to understand how CNS cells regulate the expression of complement and reprogram gene expression as they traverse critical periods in the maturation of their circuits. Project 2 will create mice that carry human C4 genes and alleles; examining how human C4 allelic diversity and expression levels affect microglia-mediated synaptic pruning and other processes. Project 3 will reveal the functional consequences of complement-cascade dysregulation ? both over- and under-pruning ? on circuit function and behavior. A Computational and Statistical Analysis Core will contribute to research in all three projects by facilitating analyses of genome-wide expression data and genome sequence data. An administrative core will coordinate biweekly lab meetings and outward-facing activities, including an annual symposium on emerging research at the interface of neuroscience, immunology and genomics. We hope to advance the search for molecular understanding of schizophrenia while advancing the understanding of brain development, the interacting influences of genes and environment on brain and behavior, and possibly general principles that could be applicable to the mechanisms and pathways that go awry in other mental illnesses.
|
0.901 |
2018 |
Mccarroll, Steven Andrew |
U01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Whole Genome Sequencing For Schizophrenia and Bipolar Disorder in the Gpc
SUMMARY The goal of this collaborative project among investigators led by Drs. Michael Boehnke at the University of Michigan, Steven McCarroll of Harvard University and the Broad Institute, and Carlos Pato at the University of Southern California, is to use high-throughput DNA sequencing to identify genes and pathways that contribute to the risk for schizophrenia and bipolar disorder, and to construct a data resource for future genetic studies of these and other psychiatric disorders. This proposal builds on active collaborations among our groups on these important disorders and more generally on our experience in building genome variation resources, such as the 1000 Genomes Project, that are used throughout human genetics. Our research team combines strengths in high-throughput genetics and genomics, development and application of innovative computational and statistical analyses that maximize the benefits of new technologies, and leadership of large scientific consortia. In four Specific Aims, we propose whole genome sequencing (at ~30x coverage) and statistical analysis of 10,000 well-phenotyped and re-contactable individuals from the Genomic Psychiatry Cohort (GPC), equally divided among schizophrenia cases, bipolar cases, and psychiatrically normal controls, and comprised of equal numbers of European-Ancestry (EA), African-Ancestry (AA), and Latino individuals. We will carry out association analysis comparing schizophrenia cases to controls, bipolar cases to controls, and the combined cases to controls in the resulting sequence data, and by collaboration and meta-analysis with other investigators with relevant sequence data that become available. We will also use these sequence data as part of a reference panel to impute into tens of thousands of other genomes in the broader Psychiatric GWAS Consortium (PGC) data to allow association analysis based on substantially larger numbers of individuals. Finally, we will share data and methods to support similar studies of other psychiatric phenotypes and more broadly across the scientific community. The successful completion of these aims will provide new insights into molecular etiology that could catalyze breakthroughs in the prevention, treatment, and diagnosis of schizophrenia and bipolar disorder.
|
0.903 |