A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. / Ramdas, Shweta; Judd, Jonathan; Graham, Sarah E.; Kanoni, Stavroula; Wang, Yuxuan; Surakka, Ida; Wenz, Brandon; Clarke, Shoa L.; Chesi, Alessandra; Wells, Andrew; Bhatti, Konain Fatima; Vedantam, Sailaja; Winkler, Thomas W.; Locke, Adam E.; Marouli, Eirini; Zajac, Greg J.M.; Wu, Kuan Han H.; Ntalla, Ioanna; Hui, Qin; Klarin, Derek; Hilliard, Austin T.; Wang, Zeyuan; Xue, Chao; Thorleifsson, Gudmar; Helgadottir, Anna; Gudbjartsson, Daniel F.; Holm, Hilma; Olafsson, Isleifur; Hwang, Mi Yeong; Han, Sohee; Zhao, Jing Hua; Aadahl, Mette; Bork-Jensen, Jette; Møllehave, Line T.; Liu, Jun; Wang, Jun-Sing; Vestergaard, Henrik; Jackson, Rebecca D; Kovacs, Peter; Pedersen, Oluf; Hansen, Torben; Lind, Lars; Loos, Ruth J.F.; Christensen, Kaare; Linneberg, Allan; Grarup, Niels; Dantoft, Thomas M.; Karpe, Fredrik; Wei, Wei Qi; Sun, Yan V.; Million Veterans Program; Global Lipids Genetics Consortium.

In: American Journal of Human Genetics, Vol. 109, No. 8, 2022, p. 1366-1387.

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

Harvard

Ramdas, S, Judd, J, Graham, SE, Kanoni, S, Wang, Y, Surakka, I, Wenz, B, Clarke, SL, Chesi, A, Wells, A, Bhatti, KF, Vedantam, S, Winkler, TW, Locke, AE, Marouli, E, Zajac, GJM, Wu, KHH, Ntalla, I, Hui, Q, Klarin, D, Hilliard, AT, Wang, Z, Xue, C, Thorleifsson, G, Helgadottir, A, Gudbjartsson, DF, Holm, H, Olafsson, I, Hwang, MY, Han, S, Zhao, JH, Aadahl, M, Bork-Jensen, J, Møllehave, LT, Liu, J, Wang, J-S, Vestergaard, H, Jackson, RD, Kovacs, P, Pedersen, O, Hansen, T, Lind, L, Loos, RJF, Christensen, K, Linneberg, A, Grarup, N, Dantoft, TM, Karpe, F, Wei, WQ, Sun, YV, Million Veterans Program & Global Lipids Genetics Consortium 2022, 'A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids', American Journal of Human Genetics, vol. 109, no. 8, pp. 1366-1387. https://doi.org/10.1016/j.ajhg.2022.06.012

APA

Ramdas, S., Judd, J., Graham, S. E., Kanoni, S., Wang, Y., Surakka, I., Wenz, B., Clarke, S. L., Chesi, A., Wells, A., Bhatti, K. F., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Zajac, G. J. M., Wu, K. H. H., Ntalla, I., Hui, Q., ... Global Lipids Genetics Consortium (2022). A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. American Journal of Human Genetics, 109(8), 1366-1387. https://doi.org/10.1016/j.ajhg.2022.06.012

Vancouver

Ramdas S, Judd J, Graham SE, Kanoni S, Wang Y, Surakka I et al. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. American Journal of Human Genetics. 2022;109(8):1366-1387. https://doi.org/10.1016/j.ajhg.2022.06.012

Author

Ramdas, Shweta ; Judd, Jonathan ; Graham, Sarah E. ; Kanoni, Stavroula ; Wang, Yuxuan ; Surakka, Ida ; Wenz, Brandon ; Clarke, Shoa L. ; Chesi, Alessandra ; Wells, Andrew ; Bhatti, Konain Fatima ; Vedantam, Sailaja ; Winkler, Thomas W. ; Locke, Adam E. ; Marouli, Eirini ; Zajac, Greg J.M. ; Wu, Kuan Han H. ; Ntalla, Ioanna ; Hui, Qin ; Klarin, Derek ; Hilliard, Austin T. ; Wang, Zeyuan ; Xue, Chao ; Thorleifsson, Gudmar ; Helgadottir, Anna ; Gudbjartsson, Daniel F. ; Holm, Hilma ; Olafsson, Isleifur ; Hwang, Mi Yeong ; Han, Sohee ; Zhao, Jing Hua ; Aadahl, Mette ; Bork-Jensen, Jette ; Møllehave, Line T. ; Liu, Jun ; Wang, Jun-Sing ; Vestergaard, Henrik ; Jackson, Rebecca D ; Kovacs, Peter ; Pedersen, Oluf ; Hansen, Torben ; Lind, Lars ; Loos, Ruth J.F. ; Christensen, Kaare ; Linneberg, Allan ; Grarup, Niels ; Dantoft, Thomas M. ; Karpe, Fredrik ; Wei, Wei Qi ; Sun, Yan V. ; Million Veterans Program ; Global Lipids Genetics Consortium. / A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. In: American Journal of Human Genetics. 2022 ; Vol. 109, No. 8. pp. 1366-1387.

Bibtex

@article{fd718a4ef15b48a09f6665094fb8d1a3,
title = "A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids",
abstract = "A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.",
keywords = "complex traits, fine-mapping, functional genomics, lipid biology, post-GWAS, regulatory mechanism, variant prioritization",
author = "Shweta Ramdas and Jonathan Judd and Graham, {Sarah E.} and Stavroula Kanoni and Yuxuan Wang and Ida Surakka and Brandon Wenz and Clarke, {Shoa L.} and Alessandra Chesi and Andrew Wells and Bhatti, {Konain Fatima} and Sailaja Vedantam and Winkler, {Thomas W.} and Locke, {Adam E.} and Eirini Marouli and Zajac, {Greg J.M.} and Wu, {Kuan Han H.} and Ioanna Ntalla and Qin Hui and Derek Klarin and Hilliard, {Austin T.} and Zeyuan Wang and Chao Xue and Gudmar Thorleifsson and Anna Helgadottir and Gudbjartsson, {Daniel F.} and Hilma Holm and Isleifur Olafsson and Hwang, {Mi Yeong} and Sohee Han and Zhao, {Jing Hua} and Mette Aadahl and Jette Bork-Jensen and M{\o}llehave, {Line T.} and Jun Liu and Jun-Sing Wang and Henrik Vestergaard and Jackson, {Rebecca D} and Peter Kovacs and Oluf Pedersen and Torben Hansen and Lars Lind and Loos, {Ruth J.F.} and Kaare Christensen and Allan Linneberg and Niels Grarup and Dantoft, {Thomas M.} and Fredrik Karpe and Wei, {Wei Qi} and Sun, {Yan V.} and {Million Veterans Program} and {Global Lipids Genetics Consortium}",
note = "Publisher Copyright: {\textcopyright} 2022 American Society of Human Genetics",
year = "2022",
doi = "10.1016/j.ajhg.2022.06.012",
language = "English",
volume = "109",
pages = "1366--1387",
journal = "American Journal of Human Genetics",
issn = "0002-9297",
publisher = "Cell Press",
number = "8",

}

RIS

TY - JOUR

T1 - A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

AU - Ramdas, Shweta

AU - Judd, Jonathan

AU - Graham, Sarah E.

AU - Kanoni, Stavroula

AU - Wang, Yuxuan

AU - Surakka, Ida

AU - Wenz, Brandon

AU - Clarke, Shoa L.

AU - Chesi, Alessandra

AU - Wells, Andrew

AU - Bhatti, Konain Fatima

AU - Vedantam, Sailaja

AU - Winkler, Thomas W.

AU - Locke, Adam E.

AU - Marouli, Eirini

AU - Zajac, Greg J.M.

AU - Wu, Kuan Han H.

AU - Ntalla, Ioanna

AU - Hui, Qin

AU - Klarin, Derek

AU - Hilliard, Austin T.

AU - Wang, Zeyuan

AU - Xue, Chao

AU - Thorleifsson, Gudmar

AU - Helgadottir, Anna

AU - Gudbjartsson, Daniel F.

AU - Holm, Hilma

AU - Olafsson, Isleifur

AU - Hwang, Mi Yeong

AU - Han, Sohee

AU - Zhao, Jing Hua

AU - Aadahl, Mette

AU - Bork-Jensen, Jette

AU - Møllehave, Line T.

AU - Liu, Jun

AU - Wang, Jun-Sing

AU - Vestergaard, Henrik

AU - Jackson, Rebecca D

AU - Kovacs, Peter

AU - Pedersen, Oluf

AU - Hansen, Torben

AU - Lind, Lars

AU - Loos, Ruth J.F.

AU - Christensen, Kaare

AU - Linneberg, Allan

AU - Grarup, Niels

AU - Dantoft, Thomas M.

AU - Karpe, Fredrik

AU - Wei, Wei Qi

AU - Sun, Yan V.

AU - Million Veterans Program

AU - Global Lipids Genetics Consortium

N1 - Publisher Copyright: © 2022 American Society of Human Genetics

PY - 2022

Y1 - 2022

N2 - A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

AB - A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

KW - complex traits

KW - fine-mapping

KW - functional genomics

KW - lipid biology

KW - post-GWAS

KW - regulatory mechanism

KW - variant prioritization

U2 - 10.1016/j.ajhg.2022.06.012

DO - 10.1016/j.ajhg.2022.06.012

M3 - Journal article

C2 - 35931049

AN - SCOPUS:85135598739

VL - 109

SP - 1366

EP - 1387

JO - American Journal of Human Genetics

JF - American Journal of Human Genetics

SN - 0002-9297

IS - 8

ER -

ID: 319153369