ID
45579
Description
Principal Investigator: David Goldstein, PhD, Duke University, Durham, NC, USA MeSH: Schizophrenia,Schizoaffective disorder,Attention Deficit Hyperactivity Disorder,Seizures,Oppositional defiant disorder,Anxiety,Depression,Autism,Autism Spectrum Disorders,Bipolar Disorder,Developmental Disabilities,Ataxia,Migraine,Paranoid schizophrenia,Obsessive compulsive disorder,Kluver-Bucy syndrome,Intellectual disability https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000682 Although schizophrenia is a highly heritable disease, relatively little progress had been made in securely identifying the genetic causes of this disorder, and most instances of schizophrenia in the general population remain unexplained. One avenue of explanation for the genetic basis of schizophrenia, however, has been effectively closed by recent research. Genome-wide association studies (GWAS) have now shown that common variation makes at most a modest contribution to the risk of schizophrenia. At the same time that the role of common variation has been circumscribed by GWAS, however, the analysis of copy number variants that are detectable on a genome-wide scale has revealed and replicated a number of very rare variants that associate with schizophrenia. These rare copy number variants that have been implicated in schizophrenia, however, have one striking feature in common: they are all risk factors for other brain related disorders beyond schizophrenia such as mental retardation, autism and epilepsy. These findings argue that genetic risk factors may confer a highly penetrant vulnerability to neuropsychiatric disorder, which is then further modified by interacting genetic or environmental factors to determine the ultimate manifestation. Most schizophrenia collections that are being studied today, however, have been selected precisely for their homogeneity: including only schizophrenia patients with no comorbidities, or schizophrenia patients with relatives who have schizophrenia but no other neuropsychiatric conditions. These selection criteria are inconsistent with what we now know about the bulk of the genetic differences that have been associated with disease. The central hypothesis of this project is that there are rare genetic variants that strongly elevate the risk of various neuropsychiatric diseases, and that these risk factors can be identified most readily in families segregating multiple neuropsychiatric conditions.
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Versions (1)
- 1/24/23 1/24/23 - Chiara Middel
Copyright Holder
David Goldstein, PhD, Duke University, Durham, NC, USA
Uploaded on
January 24, 2023
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License
Creative Commons BY 4.0
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dbGaP phs000682 Genetics of Neuropsychiatric and Neurodevelopmental Disorders
The subject phenotype table includes sex, race, age, and clinical diagnosis using DSM-IV.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent (SCL) table contains subject IDs, consent group information, subject aliases, and affection status.
- The pedigree table includes subject IDs, family IDs, father IDs, mother IDs, sex, and twin IDs.
- The subject sample mapping (SSM) table includes a mapping of study subject IDs to sample IDs and sample aliases. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- The subject phenotype table includes sex, race, age, and clinical diagnosis using DSM-IV.
- The sample attributes table includes sample analyte type and DNA source.
Similar models
The subject phenotype table includes sex, race, age, and clinical diagnosis using DSM-IV.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent (SCL) table contains subject IDs, consent group information, subject aliases, and affection status.
- The pedigree table includes subject IDs, family IDs, father IDs, mother IDs, sex, and twin IDs.
- The subject sample mapping (SSM) table includes a mapping of study subject IDs to sample IDs and sample aliases. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- The subject phenotype table includes sex, race, age, and clinical diagnosis using DSM-IV.
- The sample attributes table includes sample analyte type and DNA source.
C2348585 (UMLS CUI [1,2])
C1317250 (UMLS CUI [1,2])
C0220952 (UMLS CUI [1,2])