Browsing by Author "Dick, Danielle M"
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Item Open Access Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial.(J Policy Anal Manage, 2015) Albert, Dustin; Belsky, Daniel W; Crowley, D Max; Latendresse, Shawn J; Aliev, Fazil; Riley, Brien; Group, Conduct Problems Prevention Research; Dick, Danielle M; Dodge, Kenneth AEarly interventions are a preferred method for addressing behavioral problems in high-risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track randomized control trial, a 10-year-long intervention to prevent high-risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European-American children, a variant of NR3C1 identified by the single-nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African-American children. We discuss implications for efforts to prevent externalizing problems in high-risk children and for public policy in the genomic era.Item Open Access Genetic diversity fuels gene discovery for tobacco and alcohol use.(Nature, 2022-12) Saunders, Gretchen RB; Wang, Xingyan; Chen, Fang; Jang, Seon-Kyeong; Liu, Mengzhen; Wang, Chen; Gao, Shuang; Jiang, Yu; Khunsriraksakul, Chachrit; Otto, Jacqueline M; Addison, Clifton; Akiyama, Masato; Albert, Christine M; Aliev, Fazil; Alonso, Alvaro; Arnett, Donna K; Ashley-Koch, Allison E; Ashrani, Aneel A; Barnes, Kathleen C; Barr, R Graham; Bartz, Traci M; Becker, Diane M; Bielak, Lawrence F; Benjamin, Emelia J; Bis, Joshua C; Bjornsdottir, Gyda; Blangero, John; Bleecker, Eugene R; Boardman, Jason D; Boerwinkle, Eric; Boomsma, Dorret I; Boorgula, Meher Preethi; Bowden, Donald W; Brody, Jennifer A; Cade, Brian E; Chasman, Daniel I; Chavan, Sameer; Chen, Yii-Der Ida; Chen, Zhengming; Cheng, Iona; Cho, Michael H; Choquet, Hélène; Cole, John W; Cornelis, Marilyn C; Cucca, Francesco; Curran, Joanne E; de Andrade, Mariza; Dick, Danielle M; Docherty, Anna R; Duggirala, Ravindranath; Eaton, Charles B; Ehringer, Marissa A; Esko, Tõnu; Faul, Jessica D; Fernandes Silva, Lilian; Fiorillo, Edoardo; Fornage, Myriam; Freedman, Barry I; Gabrielsen, Maiken E; Garrett, Melanie E; Gharib, Sina A; Gieger, Christian; Gillespie, Nathan; Glahn, David C; Gordon, Scott D; Gu, Charles C; Gu, Dongfeng; Gudbjartsson, Daniel F; Guo, Xiuqing; Haessler, Jeffrey; Hall, Michael E; Haller, Toomas; Harris, Kathleen Mullan; He, Jiang; Herd, Pamela; Hewitt, John K; Hickie, Ian; Hidalgo, Bertha; Hokanson, John E; Hopfer, Christian; Hottenga, JoukeJan; Hou, Lifang; Huang, Hongyan; Hung, Yi-Jen; Hunter, David J; Hveem, Kristian; Hwang, Shih-Jen; Hwu, Chii-Min; Iacono, William; Irvin, Marguerite R; Jee, Yon Ho; Johnson, Eric O; Joo, Yoonjung Y; Jorgenson, Eric; Justice, Anne E; Kamatani, Yoichiro; Kaplan, Robert C; Kaprio, Jaakko; Kardia, Sharon LR; Keller, Matthew C; Kelly, Tanika N; Kooperberg, Charles; Korhonen, Tellervo; Kraft, Peter; Krauter, Kenneth; Kuusisto, Johanna; Laakso, Markku; Lasky-Su, Jessica; Lee, Wen-Jane; Lee, James J; Levy, Daniel; Li, Liming; Li, Kevin; Li, Yuqing; Lin, Kuang; Lind, Penelope A; Liu, Chunyu; Lloyd-Jones, Donald M; Lutz, Sharon M; Ma, Jiantao; Mägi, Reedik; Manichaikul, Ani; Martin, Nicholas G; Mathur, Ravi; Matoba, Nana; McArdle, Patrick F; McGue, Matt; McQueen, Matthew B; Medland, Sarah E; Metspalu, Andres; Meyers, Deborah A; Millwood, Iona Y; Mitchell, Braxton D; Mohlke, Karen L; Moll, Matthew; Montasser, May E; Morrison, Alanna C; Mulas, Antonella; Nielsen, Jonas B; North, Kari E; Oelsner, Elizabeth C; Okada, Yukinori; Orrù, Valeria; Palmer, Nicholette D; Palviainen, Teemu; Pandit, Anita; Park, S Lani; Peters, Ulrike; Peters, Annette; Peyser, Patricia A; Polderman, Tinca JC; Rafaels, Nicholas; Redline, Susan; Reed, Robert M; Reiner, Alex P; Rice, John P; Rich, Stephen S; Richmond, Nicole E; Roan, Carol; Rotter, Jerome I; Rueschman, Michael N; Runarsdottir, Valgerdur; Saccone, Nancy L; Schwartz, David A; Shadyab, Aladdin H; Shi, Jingchunzi; Shringarpure, Suyash S; Sicinski, Kamil; Skogholt, Anne Heidi; Smith, Jennifer A; Smith, Nicholas L; Sotoodehnia, Nona; Stallings, Michael C; Stefansson, Hreinn; Stefansson, Kari; Stitzel, Jerry A; Sun, Xiao; Syed, Moin; Tal-Singer, Ruth; Taylor, Amy E; Taylor, Kent D; Telen, Marilyn J; Thai, Khanh K; Tiwari, Hemant; Turman, Constance; Tyrfingsson, Thorarinn; Wall, Tamara L; Walters, Robin G; Weir, David R; Weiss, Scott T; White, Wendy B; Whitfield, John B; Wiggins, Kerri L; Willemsen, Gonneke; Willer, Cristen J; Winsvold, Bendik S; Xu, Huichun; Yanek, Lisa R; Yin, Jie; Young, Kristin L; Young, Kendra A; Yu, Bing; Zhao, Wei; Zhou, Wei; Zöllner, Sebastian; Zuccolo, Luisa; 23andMe Research Team; Biobank Japan Project; Batini, Chiara; Bergen, Andrew W; Bierut, Laura J; David, Sean P; Gagliano Taliun, Sarah A; Hancock, Dana B; Jiang, Bibo; Munafò, Marcus R; Thorgeirsson, Thorgeir E; Liu, Dajiang J; Vrieze, ScottTobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.