The Family Ascertainment, Linkage Analysis, and Informatics Core provides a comprehensive framework for clinical and statistical resources necessary to identify genes which predispose to human disease. These functions are highly interdependent and critical to the success of linkage studies. Central to both the family ascertainment and statistical components is the PEDIGENE database.. PEDIGENE is a relational database that integrates family history, clinical, and genotypic marker results together with DNA banking and genomics that integrates family history, clinical, and genotypic marker results together with DNA banking and genomics functions from Core B. This flexible, highly secure genetic database system continues to be instrumental in the rapid and accurate assimilation of and access to all types of genetic data. This core will serve as the umbrella for coordinating and performing all linkage studies in projects 1 and 3, from initial linkage through characterization of heterogeneity through fine mapping, in Mendelial diseases. These diseases include Charcot-Marie- Tooth disease type 2, familial spastic paraparesis, the autosomal dominant limb-girdle muscular dystrophies, facioscapulohumeral muscular dystrophy, and the Lumbee myopathy. The Core also provides consulting support for complex trait analysis such as in project 2, including non-parametric linkage analysis (siblink) and TDT. In addition, this core provides seed support for several projects under development including studies of neural tube defects and Chiari type 1 malformation. Ultimately, these projects will be developed to a point to ensure independent funding, thereby maximizing the impact of the availability of these critical core resources.

Project Start
1999-04-01
Project End
2000-03-31
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
11
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Duke University
Department
Type
DUNS #
071723621
City
Durham
State
NC
Country
United States
Zip Code
27705
Griswold, Anthony J; Van Booven, Derek; Cuccaro, Michael L et al. (2018) Identification of rare noncoding sequence variants in gamma-aminobutyric acid A receptor, alpha 4 subunit in autism spectrum disorder. Neurogenetics 19:17-26
Zhu, Zuobin; Lu, Xitong; Yuan, Dejian et al. (2017) Close genetic relationships between a spousal pair with autism-affected children and high minor allele content in cases in autism-associated SNPs. Genomics 109:9-15
Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M (2014) Protein interaction networks reveal novel autism risk genes within GWAS statistical noise. PLoS One 9:e112399
Gaugler, Trent; Klei, Lambertus; Sanders, Stephan J et al. (2014) Most genetic risk for autism resides with common variation. Nat Genet 46:881-5
Hadjixenofontos, Athena; Schmidt, Michael A; Whitehead, Patrice L et al. (2013) Evaluating mitochondrial DNA variation in autism spectrum disorders. Ann Hum Genet 77:9-21
Cukier, Holly N; Lee, Joycelyn M; Ma, Deqiong et al. (2012) The expanding role of MBD genes in autism: identification of a MECP2 duplication and novel alterations in MBD5, MBD6, and SETDB1. Autism Res 5:385-97
Griswold, Anthony J; Ma, Deqiong; Cukier, Holly N et al. (2012) Evaluation of copy number variations reveals novel candidate genes in autism spectrum disorder-associated pathways. Hum Mol Genet 21:3513-23
Casey, Jillian P; Magalhaes, Tiago; Conroy, Judith M et al. (2012) A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder. Hum Genet 131:565-79
Cuccaro, Michael L; Tuchman, Roberto F; Hamilton, Kara L et al. (2012) Exploring the relationship between autism spectrum disorder and epilepsy using latent class cluster analysis. J Autism Dev Disord 42:1630-41
Anney, Richard; Klei, Lambertus; Pinto, Dalila et al. (2012) Individual common variants exert weak effects on the risk for autism spectrum disorders. Hum Mol Genet 21:4781-92

Showing the most recent 10 out of 204 publications