The Experts below are selected from a list of 183 Experts worldwide ranked by ideXlab platform

Hilary K Finucane - One of the best experts on this subject based on the ideXlab platform.

  • partitioning heritability by functional annotation using genome wide association summary statistics
    Nature Genetics, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Han Xu
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including Cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many Cell type-specific enrichments, including significant enrichment of central Nervous System Cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

  • partitioning heritability by functional category using gwas summary statistics
    bioRxiv, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Poru Loh, Chongzhi Zang, Kyle Kaihow Farh, Stephan Ripke
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including Cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many Cell-type-specific enrichments including significant enrichment of central Nervous System Cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

Verneri Anttila - One of the best experts on this subject based on the ideXlab platform.

  • partitioning heritability by functional annotation using genome wide association summary statistics
    Nature Genetics, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Han Xu
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including Cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many Cell type-specific enrichments, including significant enrichment of central Nervous System Cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

  • partitioning heritability by functional category using gwas summary statistics
    bioRxiv, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Poru Loh, Chongzhi Zang, Kyle Kaihow Farh, Stephan Ripke
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including Cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many Cell-type-specific enrichments including significant enrichment of central Nervous System Cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

Brendan Buliksullivan - One of the best experts on this subject based on the ideXlab platform.

  • partitioning heritability by functional annotation using genome wide association summary statistics
    Nature Genetics, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Han Xu
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including Cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many Cell type-specific enrichments, including significant enrichment of central Nervous System Cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

  • partitioning heritability by functional category using gwas summary statistics
    bioRxiv, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Poru Loh, Chongzhi Zang, Kyle Kaihow Farh, Stephan Ripke
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including Cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many Cell-type-specific enrichments including significant enrichment of central Nervous System Cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

Han Xu - One of the best experts on this subject based on the ideXlab platform.

  • partitioning heritability by functional annotation using genome wide association summary statistics
    Nature Genetics, 2015
    Co-Authors: Hilary K Finucane, Brendan Buliksullivan, Gosia Trynka, Alexander Gusev, Verneri Anttila, Yakir A Reshef, Han Xu
    Abstract:

    Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including Cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many Cell type-specific enrichments, including significant enrichment of central Nervous System Cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Leila K. Needham - One of the best experts on this subject based on the ideXlab platform.

  • Receptors for gangliosides and related glycosphingolipids on central and peripheral Nervous System Cell membranes.
    Progress in brain research, 1994
    Co-Authors: Ronald L. Schnaar, James A. Mahoney, Patti Swank-hill, Michael Tiemeyer, Leila K. Needham
    Abstract:

    Publisher Summary This chapter discusses the receptors for gangliosides and related glycosphingolipids on central and peripheral Nervous System Cell membranes. The chapter focuses on the detection and characterization of novel protein receptors for gangliosides and related glycosphingolipids in the Nervous System. The incorporated strategy is to identify ganglioside (and related) binding activities using synthetic glycosphingolipid-based radioligands, to characterize the structural and tissue specificity of binding activities, and to purify the responsible protein receptors. The chapter also discusses the identification of a ganglioside receptor in the central Nervous System and a receptor for sulfoglucuronyl glycosphingolipids in the peripheral Nervous System. Through the use of semi-synthetic glycosphingolipidbased neoglycoconjugates—which combine multivalence—sequestering or removal of the lipid moiety, and facile radioiodination, research is successful in demonstrating unique binding activities for gangliosides and sulfoglucuronyl glycosphingolipids in the central Nervous System (CNS) and peripheral Nervous System (PNS) respectively. Although the identification of the functional roles of these glycosphingolipid- specific binding activities await further studies, their differential tissue and membrane distribution suggests that they may be involved in ‘trans' interactions between myelinating Cells and axons.