Browsing by Subject "Multifactorial Inheritance"

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    ItemOpen Access
    An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.
    (Genome medicine, 2021-05) Wang, Liuyang; Balmat, Thomas J; Antonia, Alejandro L; Constantine, Florica J; Henao, Ricardo; Burke, Thomas W; Ingham, Andy; McClain, Micah T; Tsalik, Ephraim L; Ko, Emily R; Ginsburg, Geoffrey S; DeLong, Mark R; Shen, Xiling; Woods, Christopher W; Hauser, Elizabeth R; Ko, Dennis C

    Background

    While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

    Results

    Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

    Conclusions

    Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
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    ItemOpen 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, Scott
    Tobacco 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.
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    ItemOpen Access
    The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data.
    (Translational psychiatry, 2011-10-18) Middeldorp, CM; de Moor, MHM; McGrath, LM; Gordon, SD; Blackwood, DH; Costa, PT; Terracciano, A; Krueger, RF; de Geus, EJC; Nyholt, DR; Tanaka, T; Esko, T; Madden, PAF; Derringer, J; Amin, N; Willemsen, G; Hottenga, J-J; Distel, MA; Uda, M; Sanna, S; Spinhoven, P; Hartman, CA; Ripke, S; Sullivan, PF; Realo, A; Allik, J; Heath, AC; Pergadia, ML; Agrawal, A; Lin, P; Grucza, RA; Widen, E; Cousminer, DL; Eriksson, JG; Palotie, A; Barnett, JH; Lee, PH; Luciano, M; Tenesa, A; Davies, G; Lopez, LM; Hansell, NK; Medland, SE; Ferrucci, L; Schlessinger, D; Montgomery, GW; Wright, MJ; Aulchenko, YS; Janssens, ACJW; Oostra, BA; Metspalu, A; Abecasis, GR; Deary, IJ; Räikkönen, K; Bierut, LJ; Martin, NG; Wray, NR; van Duijn, CM; Smoller, JW; Penninx, BWJH; Boomsma, DI
    The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.