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Adipose Tissue Cell

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Kerrin S Small – One of the best experts on this subject based on the ideXlab platform.

  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    American Journal of Human Genetics, 2019
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of Cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-Tissue transcriptomes. Here, we investigate Cell-type heterogeneity in two population-level subcutaneous AdiposeTissue RNA-seq datasets (TwinsUK, n = 766 and the Genotype-Tissue Expression project [GTEx], n = 326) by estimating the relative proportions of four distinct Cell types (adipocytes, macrophages, CD4+ T Cells, and micro-vascular endothelial Cells). We find significant Cellular heterogeneity within and between the TwinsUK and GTEx Adipose datasets. We find that Adipose Cell-type composition is heritable and confirm the positive association between Adipose-resident macrophage proportion and obesity (high BMI), but we find a stronger BMI-independent association with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits. We benchmark the impact of AdiposeTissue Cell composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks, and cis-eQTL discovery. Our results indicate that it is critical to account for Cell-type composition when combining Adipose transcriptome datasets in co-expression analysis and in differential expression analysis with obesity-related traits. We applied gene expression by Cell-type proportion interaction models (G × Cell) to identify 26 Cell-type-specific expression quantitative trait loci (eQTLs) in 20 genes, including four autoimmune disease genome-wide association study (GWAS) loci. These results identify Cell-specific eQTLs and demonstrate the potential of in silico deconvolution of bulk Tissue to identify Cell-type-restricted regulatory variants.

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  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    bioRxiv, 2018
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is comprised of a heterogeneous collection of Cell-types which can differentially impact disease phenotypes. We investigated Cell-type heterogeneity in two population-level subcutaneous Adipose Tissue RNAseq datasets (TwinsUK, N =766 and GTEx, N=326). We find that Adipose Cell-type composition is heritable and confirm the positive association between macrophage proportion and obesity (BMI), but find a stronger BMI-independent association with DXA-derived body-fat distribution traits. Cellular heterogeneity can confound omic analyses, but is rarely taken into account in analysis of solid-Tissue transcriptomes. We benchmark the impact of Adipose Tissue Cell-composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks and cis-eQTL discovery. We applied G x Cell Type Proportion interaction models to identify 26 Cell-type specific eQTLs in 20 genes, including 4 autoimmune disease GWAS loci, demonstrating the potential of in silico deconvolution of bulk Tissue to identify Cell-type restricted regulatory variants.

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Craig A Glastonbury – One of the best experts on this subject based on the ideXlab platform.

  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    American Journal of Human Genetics, 2019
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of Cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-Tissue transcriptomes. Here, we investigate Cell-type heterogeneity in two population-level subcutaneous AdiposeTissue RNA-seq datasets (TwinsUK, n = 766 and the Genotype-Tissue Expression project [GTEx], n = 326) by estimating the relative proportions of four distinct Cell types (adipocytes, macrophages, CD4+ T Cells, and micro-vascular endothelial Cells). We find significant Cellular heterogeneity within and between the TwinsUK and GTEx Adipose datasets. We find that Adipose Cell-type composition is heritable and confirm the positive association between Adipose-resident macrophage proportion and obesity (high BMI), but we find a stronger BMI-independent association with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits. We benchmark the impact of AdiposeTissue Cell composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks, and cis-eQTL discovery. Our results indicate that it is critical to account for Cell-type composition when combining Adipose transcriptome datasets in co-expression analysis and in differential expression analysis with obesity-related traits. We applied gene expression by Cell-type proportion interaction models (G × Cell) to identify 26 Cell-type-specific expression quantitative trait loci (eQTLs) in 20 genes, including four autoimmune disease genome-wide association study (GWAS) loci. These results identify Cell-specific eQTLs and demonstrate the potential of in silico deconvolution of bulk Tissue to identify Cell-type-restricted regulatory variants.

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  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    bioRxiv, 2018
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is comprised of a heterogeneous collection of Cell-types which can differentially impact disease phenotypes. We investigated Cell-type heterogeneity in two population-level subcutaneous Adipose Tissue RNAseq datasets (TwinsUK, N =766 and GTEx, N=326). We find that Adipose Cell-type composition is heritable and confirm the positive association between macrophage proportion and obesity (BMI), but find a stronger BMI-independent association with DXA-derived body-fat distribution traits. Cellular heterogeneity can confound omic analyses, but is rarely taken into account in analysis of solid-Tissue transcriptomes. We benchmark the impact of Adipose Tissue Cell-composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks and cis-eQTL discovery. We applied G x Cell Type Proportion interaction models to identify 26 Cell-type specific eQTLs in 20 genes, including 4 autoimmune disease GWAS loci, demonstrating the potential of in silico deconvolution of bulk Tissue to identify Cell-type restricted regulatory variants.

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Alexessander Couto Alves – One of the best experts on this subject based on the ideXlab platform.

  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    American Journal of Human Genetics, 2019
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of Cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-Tissue transcriptomes. Here, we investigate Cell-type heterogeneity in two population-level subcutaneous AdiposeTissue RNA-seq datasets (TwinsUK, n = 766 and the Genotype-Tissue Expression project [GTEx], n = 326) by estimating the relative proportions of four distinct Cell types (adipocytes, macrophages, CD4+ T Cells, and micro-vascular endothelial Cells). We find significant Cellular heterogeneity within and between the TwinsUK and GTEx Adipose datasets. We find that Adipose Cell-type composition is heritable and confirm the positive association between Adipose-resident macrophage proportion and obesity (high BMI), but we find a stronger BMI-independent association with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits. We benchmark the impact of AdiposeTissue Cell composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks, and cis-eQTL discovery. Our results indicate that it is critical to account for Cell-type composition when combining Adipose transcriptome datasets in co-expression analysis and in differential expression analysis with obesity-related traits. We applied gene expression by Cell-type proportion interaction models (G × Cell) to identify 26 Cell-type-specific expression quantitative trait loci (eQTLs) in 20 genes, including four autoimmune disease genome-wide association study (GWAS) loci. These results identify Cell-specific eQTLs and demonstrate the potential of in silico deconvolution of bulk Tissue to identify Cell-type-restricted regulatory variants.

    Free Register to Access Article

  • Cell type heterogeneity in Adipose Tissue is associated with complex traits and reveals disease relevant Cell specific eqtls
    bioRxiv, 2018
    Co-Authors: Craig A Glastonbury, Alexessander Couto Alves, Julia Elsayed S Moustafa, Kerrin S Small

    Abstract:

    Adipose Tissue is comprised of a heterogeneous collection of Cell-types which can differentially impact disease phenotypes. We investigated Cell-type heterogeneity in two population-level subcutaneous Adipose Tissue RNAseq datasets (TwinsUK, N =766 and GTEx, N=326). We find that Adipose Cell-type composition is heritable and confirm the positive association between macrophage proportion and obesity (BMI), but find a stronger BMI-independent association with DXA-derived body-fat distribution traits. Cellular heterogeneity can confound omic analyses, but is rarely taken into account in analysis of solid-Tissue transcriptomes. We benchmark the impact of Adipose Tissue Cell-composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks and cis-eQTL discovery. We applied G x Cell Type Proportion interaction models to identify 26 Cell-type specific eQTLs in 20 genes, including 4 autoimmune disease GWAS loci, demonstrating the potential of in silico deconvolution of bulk Tissue to identify Cell-type restricted regulatory variants.

    Free Register to Access Article