Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

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Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease. / Baillie, J. Kenneth; Bretherick, Andrew; Haley, Christopher S.; Clohisey, Sara; Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B.; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin Gustav; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R. R.; Hume, David A.

In: PLoS Computational Biology, Vol. 14, No. 3, e1005934, 2018.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Baillie, JK, Bretherick, A, Haley, CS, Clohisey, S, Gray, A, Neyton, LPA, Barrett, J, Stahl, EA, Tenesa, A, Andersson, R, Brown, JB, Faulkner, GJ, Lizio, M, Schaefer, U, Daub, C, Itoh, M, Kondo, N, Lassmann, T, Kawai, J, Mole, D, Bajic, VB, Heutink, P, Rehli, M, Kawaji, H, Sandelin, AG, Suzuki, H, Satsangi, J, Wells, CA, Hacohen, N, Freeman, TC, Hayashizaki, Y, Carninci, P, Forrest, ARR & Hume, DA 2018, 'Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease', PLoS Computational Biology, vol. 14, no. 3, e1005934. https://doi.org/10.1371/journal.pcbi.1005934

APA

Baillie, J. K., Bretherick, A., Haley, C. S., Clohisey, S., Gray, A., Neyton, L. P. A., Barrett, J., Stahl, E. A., Tenesa, A., Andersson, R., Brown, J. B., Faulkner, G. J., Lizio, M., Schaefer, U., Daub, C., Itoh, M., Kondo, N., Lassmann, T., Kawai, J., ... Hume, D. A. (2018). Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease. PLoS Computational Biology, 14(3), [e1005934]. https://doi.org/10.1371/journal.pcbi.1005934

Vancouver

Baillie JK, Bretherick A, Haley CS, Clohisey S, Gray A, Neyton LPA et al. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease. PLoS Computational Biology. 2018;14(3). e1005934. https://doi.org/10.1371/journal.pcbi.1005934

Author

Baillie, J. Kenneth ; Bretherick, Andrew ; Haley, Christopher S. ; Clohisey, Sara ; Gray, Alan ; Neyton, Lucile P. A. ; Barrett, Jeffrey ; Stahl, Eli A. ; Tenesa, Albert ; Andersson, Robin ; Brown, J. Ben ; Faulkner, Geoffrey J. ; Lizio, Marina ; Schaefer, Ulf ; Daub, Carsten ; Itoh, Masayoshi ; Kondo, Naoto ; Lassmann, Timo ; Kawai, Jun ; Mole, Damian ; Bajic, Vladimir B. ; Heutink, Peter ; Rehli, Michael ; Kawaji, Hideya ; Sandelin, Albin Gustav ; Suzuki, Harukazu ; Satsangi, Jack ; Wells, Christine A. ; Hacohen, Nir ; Freeman, Thomas C. ; Hayashizaki, Yoshihide ; Carninci, Piero ; Forrest, Alistair R. R. ; Hume, David A. / Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease. In: PLoS Computational Biology. 2018 ; Vol. 14, No. 3.

Bibtex

@article{19c3d7f322904592ae7151126a44e019,
title = "Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease",
abstract = "Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.",
author = "Baillie, {J. Kenneth} and Andrew Bretherick and Haley, {Christopher S.} and Sara Clohisey and Alan Gray and Neyton, {Lucile P. A.} and Jeffrey Barrett and Stahl, {Eli A.} and Albert Tenesa and Robin Andersson and Brown, {J. Ben} and Faulkner, {Geoffrey J.} and Marina Lizio and Ulf Schaefer and Carsten Daub and Masayoshi Itoh and Naoto Kondo and Timo Lassmann and Jun Kawai and Damian Mole and Bajic, {Vladimir B.} and Peter Heutink and Michael Rehli and Hideya Kawaji and Sandelin, {Albin Gustav} and Harukazu Suzuki and Jack Satsangi and Wells, {Christine A.} and Nir Hacohen and Freeman, {Thomas C.} and Yoshihide Hayashizaki and Piero Carninci and Forrest, {Alistair R. R.} and Hume, {David A.}",
year = "2018",
doi = "10.1371/journal.pcbi.1005934",
language = "English",
volume = "14",
journal = "P L o S Computational Biology (Online)",
issn = "1553-734X",
publisher = "Public Library of Science",
number = "3",

}

RIS

TY - JOUR

T1 - Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

AU - Baillie, J. Kenneth

AU - Bretherick, Andrew

AU - Haley, Christopher S.

AU - Clohisey, Sara

AU - Gray, Alan

AU - Neyton, Lucile P. A.

AU - Barrett, Jeffrey

AU - Stahl, Eli A.

AU - Tenesa, Albert

AU - Andersson, Robin

AU - Brown, J. Ben

AU - Faulkner, Geoffrey J.

AU - Lizio, Marina

AU - Schaefer, Ulf

AU - Daub, Carsten

AU - Itoh, Masayoshi

AU - Kondo, Naoto

AU - Lassmann, Timo

AU - Kawai, Jun

AU - Mole, Damian

AU - Bajic, Vladimir B.

AU - Heutink, Peter

AU - Rehli, Michael

AU - Kawaji, Hideya

AU - Sandelin, Albin Gustav

AU - Suzuki, Harukazu

AU - Satsangi, Jack

AU - Wells, Christine A.

AU - Hacohen, Nir

AU - Freeman, Thomas C.

AU - Hayashizaki, Yoshihide

AU - Carninci, Piero

AU - Forrest, Alistair R. R.

AU - Hume, David A.

PY - 2018

Y1 - 2018

N2 - Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

AB - Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

U2 - 10.1371/journal.pcbi.1005934

DO - 10.1371/journal.pcbi.1005934

M3 - Journal article

C2 - 29494619

VL - 14

JO - P L o S Computational Biology (Online)

JF - P L o S Computational Biology (Online)

SN - 1553-734X

IS - 3

M1 - e1005934

ER -

ID: 195152931