An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms.
An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms.
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DOI：
10.1002/ajmg.b.32829
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发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Derks EM
中科院分区：
文献类型：
--
作者：
Gerring ZF;Vargas AM;Gamazon ER;Derks EM
全基因组关联研究已经确定了药物使用易感性的多种遗传风险因素，但功能基因和生物学机制仍然知之甚少。通过整合全基因组关联数据和跨生物相关组织和/或细胞类型的基因表达数据，识别因DNA序列变化而改变表达的基因（表达数量性状位点；eQTLs），可以促进风险基因的发现和表征。基因表达数据的整合可以扩展到基因共表达的研究，在生物学上有效的假设下，基因形成共表达网络来影响疾病或性状的表现。在这里，我们整合了全基因组关联数据和来自13个脑组织的基因表达数据，以确定8种物质使用表型的候选风险基因。然后，我们在组织特异性基因共表达网络中测试候选风险基因的富集程度，以确定功能相关基因的模块（或组），其失调与物质使用的变化有关。我们在大脑中发现了8个基因模块，这些基因模块富含基于基因的物质使用表型关联信号。例如，一个由40个共表达基因组成的单一模块，富含与每周饮酒有关的基因，以及涉及GABA合成、释放、再摄取和降解的生物途径。我们的研究证明了eQTL和基因共表达分析在揭示物质使用性状的新的生物学机制方面的效用。
Genome-wide association studies have identified multiple genetic risk factors underlying susceptibility to substance use, however the functional genes and biological mechanisms remain poorly understood. The discovery and characterisation of risk genes can be facilitated by the integration of genome-wide association data and gene expression data across biologically relevant tissues and/or cell types to identify genes whose expression is altered by DNA sequence variation (expression quantitative trait loci; eQTLs). The integration of gene expression data can be extended to the study of genetic co-expression, under the biologically valid assumption that genes form co-expression networks to influence the manifestation of a disease or trait. Here, we integrate genome-wide association data with gene expression data from 13 brain tissues to identify candidate risk genes for 8 substance use phenotypes. We then test for the enrichment of candidate risk genes within tissue-specific gene co-expression networks to identify modules (or groups) of functionally related genes whose dysregulation is associated with variation in substance use. We identified 8 gene modules in brain that were enriched with gene-based association signals for substance use phenotypes. For example, a single module of 40 co-expressed genes was enriched with gene-based associations for drinks per week and biological pathways involved in GABA synthesis, release, reuptake and degradation. Our study demonstrates the utility of eQTL and gene co-expression analysis to uncover novel biological mechanisms for substance use traits.
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影响因子：
4.2
作者：
Marees, Andries T.;Gamazon, Eric R.;Gerring, Zachary;Vorspan, Florence;Fingal, Josh;van den Brink, Wim;Smit, Dirk J. A.;Verweij, Karin J. H.;Kranzler, Henry R.;Sherva, Richard;Farrer, Lindsay;Stringer, Sven;Minica, Camelia C.;Mbarek, Hamdi;Bernard, Manon;Derringer, Jaime;van Eijk, Kristel R.;Isen, Joshua D.;Loukola, Anu;Maciejewski, Dominique F.;Mihailov, Evelin;van der Most, Peter J.;Sanchez-Mora, Cristina;Roos, Leonie;Walters, Raymond;Ware, Jennifer J.;Abdellaoui, Abdel;Bigdeli, Timothy B.;Branje, Susan J. T.;Brown, Sandra A.;Bruinenberg, Marcel;Casas, Miguel;Esko, Tonu;Garcia-Martinez, Iris;Gordon, Scott D.;Harris, Juliette M.;Hartman, Catharina A.;Henders, Anjali K.;Heath, Andrew C.;Hickie, Ian B.;Hickman, Matthew;Hopfer, Christian J.;Hottenga, Jouke Jan;Huizink, Anja C.;Irons, Daniel E.;Kahn, Rene S.;Korhonen, Tellervo;Krauter, Ken;van Lier, Pol A. C.;Lubke, Gitta H.;Madden, Pamela A. F.;Magi, Reedik;McGue, Matt K.;Medland, Sarah E.;Meeus, Wim H. J.;Miller, Michael B.;Montgomery, Grant W.;Nivard, Michel G.;Nolte, Ilja M.;Oldehinkel, Albertine J.;Pausova, Zdenka;Qaiser, Beenish;Quaye, Lydia;Ramos-Quiroga, Josep A.;Richarte, Vanesa;Rose, Richard J.;Shin, Jean;Stallings, Michael C.;Stiby, Alex I.;Wall, Tamara L.;Wright, Margaret J.;Koot, Hans M.;Paus, Tomas;Hewitt, John K.;Ribases, Marta;Kaprio, Jaakko;Boks, Marco P.;Snieder, Harold;Spector, Tim;Munafo, Marcus R.;Metspalu, Andres;Boomsma, Dorret I.;Iacono, William G.;Martini, Nicholas G.;Gillespie, Nathan A.;Vink, Jacqueline M.;Gelernter, Joel;Derks, Eske M.
通讯作者：
Derks, Eske M.
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
4.4
作者：
de Jong S;Chepelev I;Janson E;Strengman E;van den Berg LH;Veldink JH;Ophoff RA
通讯作者：
Ophoff RA
影响因子：
4.3
作者：
Langfelder P;Luo R;Oldham MC;Horvath S
通讯作者：
Horvath S
DOI：
10.1126/science.1262110
发表时间：
2015-05-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
GTEx Consortium
通讯作者：
GTEx Consortium