English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 912349      Online Users : 1169
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/14489


    Title: A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
    Authors: 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, KH;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;Akiyama, M;Sakaue, S;Terao, C;Kanai, M;Zhou, W;Brumpton, BM;Rasheed, H;Havulinna, AS;Veturi, Y;Pacheco, JA;Rosenthal, EA;Lingren, T;Feng, Q;Kullo, IJ;Narita, A;Takayama, J;Martin, HC;Hunt, KA;Trivedi, B;Haessler, J;Giulianini, F;Bradford, Y;Miller, JE;Campbell, A;Lin, K;Millwood, IY;Rasheed, A;Hindy, G;Faul, JD;Zhao, W;Weir, DR;Turman, C;Huang, H;Graff, M;Choudhury, A;Sengupta, D;Mahajan, A;Brown, MR;Zhang, W;Yu, K;Schmidt, EM;Pandit, A;Gustafsson, S;Yin, X;Luan, J;Zhao, JH;Matsuda, F;Jang, HM;Yoon, K;Medina-Gomez, C;Pitsillides, A;Hottenga, JJ;Wood, AR;Ji, Y;Gao, Z;Haworth, S;Mitchell, RE;Chai, JF;Aadahl, M;Bjerregaard, AA;Yao, J;Manichaikul, A;Lee, WJ;Hsiung, CA;Warren, HR;Ramirez, J;Bork-Jensen, J;Kårhus, LL;Goel, A;Sabater-Lleal, M, .;et al.
    Contributors: Institute of Population Health Sciences
    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.
    Date: 2022-08-04
    Relation: American Journal of Human Genetics. 2022 Aug 4;109(8):1366-1387.
    Link to: http://dx.doi.org/10.1016/j.ajhg.2022.06.012
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0002-9297&DestApp=IC2JCR
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85135598739
    Appears in Collections:[熊昭] 期刊論文

    Files in This Item:

    File Description SizeFormat
    PUB35931049.pdf2246KbAdobe PDF218View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback