Genome-Wide Association Study

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Yang, Z., Wang, C., Liu, L., Khan, A., Lee, A., Vardarajan, B., Mayeux, R., Kiryluk, K., & Ionita-Laza, I. (2023). CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses. Nature Genetics, 55(6), 1057–1065. https://doi.org/10.1038/s41588-023-01392-0
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Pahl, M. C., Grant, S. F. A., Leibel, R. L., & Stratigopoulos, G. (2023). Technologies, strategies, and cautions when deconvoluting genome‐wide association signals: FTO in focus. Obesity Reviews, 24(5). Portico. https://doi.org/10.1111/obr.13558
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Song, Z., Gurinovich, A., Nygaard, M., Mengel-From, J., Andersen, S., Cosentino, S., Schupf, N., Lee, J., Zmuda, J., Ukraintseva, S., Arbeev, K., Christensen, K., Perls, T., & Sebastiani, P. (2023). Rare genetic variants correlate with better processing speed. Neurobiology of Aging, 125, 115–122. https://doi.org/10.1016/j.neurobiolaging.2022.11.018
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Dueker, N., Wang, L., Gardener, H., Gomez, L., Kaur, S., Beecham, A., Blanton, S. H., Dong, C., Gutierrez, J., Cheung, Y. K., Moon, Y. P., Levin, B., Wright, C. B., Elkind, M. S. V., Sacco, R. L., & Rundek, T. (2023). Genome-wide association study of executive function in a multi-ethnic cohort implicates LINC01362: Results from the northern Manhattan study. Neurobiology of Aging, 123, 216–221. https://doi.org/10.1016/j.neurobiolaging.2022.11.016
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Lim, T. Y., Verbitsky, M., & Sanna-Cherchi, S. (2023). ParseCNV2: a versatile and integrated tool for copy number variation association studies. European Journal of Human Genetics, 31(3), 275–277. https://doi.org/10.1038/s41431-022-01280-x
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Dapas, M., Thompson, E. E., Wentworth-Sheilds, W., Clay, S., Visness, C. M., Calatroni, A., Sordillo, J. E., Gold, D. R., Wood, R. A., Makhija, M., Khurana Hershey, G. K., Sherenian, M. G., Gruchalla, R. S., Gill, M. A., Liu, A. H., Kim, H., Kattan, M., Bacharier, L. B., Rastogi, D., … Ober, C. (2023). Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings. PLOS Genetics, 19(1), e1010594. https://doi.org/10.1371/journal.pgen.1010594
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Huang, J., Huffman, J. E., Huang, Y., Do Valle, Í., Assimes, T. L., Raghavan, S., Voight, B. F., Liu, C., Barabási, A.-L., Huang, R. D. L., Hui, Q., Nguyen, X.-M. T., Ho, Y.-L., Djousse, L., Lynch, J. A., Vujkovic, M., Tcheandjieu, C., Tang, H., Damrauer, S. M., … O’Donnell, C. J. (2022). Genomics and phenomics of body mass index reveals a complex disease network. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-35553-2
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Kanoni, S., Graham, S. E., Wang, Y., Surakka, I., Ramdas, S., Zhu, X., Clarke, S. L., 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., Klarin, D., Hilliard, A. T., Wang, Z., … Peloso, G. M. (2022). Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis. Genome Biology, 23(1). https://doi.org/10.1186/s13059-022-02837-1
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Loh, M., Zhang, W., Ng, H. K., Schmid, K., Lamri, A., Tong, L., Ahmad, M., Lee, J.-J., Ng, M. C. Y., Petty, L. E., Spracklen, C. N., Takeuchi, F., Islam, Md. T., Jasmine, F., Kasturiratne, A., Kibriya, M., Mohlke, K. L., Paré, G., Prasad, G., … Chambers, J. C. (2022). Identification of genetic effects underlying type 2 diabetes in South Asian and European populations. Communications Biology, 5(1). https://doi.org/10.1038/s42003-022-03248-5
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Dennis, J., Tyrer, J. P., Walker, L. C., Michailidou, K., Dorling, L., Bolla, M. K., Wang, Q., Ahearn, T. U., Andrulis, I. L., Anton-Culver, H., Antonenkova, N. N., Arndt, V., Aronson, K. J., Freeman, L. E. B., Beckmann, M. W., Behrens, S., Benitez, J., Bermisheva, M., Bogdanova, N. V., … Easton, D. F. (2022). Rare germline copy number variants (CNVs) and breast cancer risk. Communications Biology, 5(1). https://doi.org/10.1038/s42003-021-02990-6
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Ge, T., Irvin, M. R., Patki, A., Srinivasasainagendra, V., Lin, Y.-F., Tiwari, H. K., Armstrong, N. D., Benoit, B., Chen, C.-Y., Choi, K. W., Cimino, J. J., Davis, B. H., Dikilitas, O., Etheridge, B., Feng, Y.-C. A., Gainer, V., Huang, H., Jarvik, G. P., Kachulis, C., … Karlson, E. W. (2022). Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations. Genome Medicine, 14(1). https://doi.org/10.1186/s13073-022-01074-2
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Moore, A., Busch, M. P., Dziewulska, K., Francis, R. O., Hod, E. A., Zimring, J. C., D’Alessandro, A., & Page, G. P. (2022). Genome-wide metabolite quantitative trait loci analysis (mQTL) in red blood cells from volunteer blood donors. Journal of Biological Chemistry, 298(12), 102706. https://doi.org/10.1016/j.jbc.2022.102706
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Levin, M. G., Tsao, N. L., Singhal, P., Liu, C., Vy, H. M. T., Paranjpe, I., Backman, J. D., Bellomo, T. R., Bone, W. P., Biddinger, K. J., Hui, Q., Dikilitas, O., Satterfield, B. A., Yang, Y., Morley, M. P., Bradford, Y., Burke, M., Reza, N., Charest, B., … Damrauer, S. M. (2022). Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-34216-6
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He, K. Y., Kelly, T. N., Wang, H., Liang, J., Zhu, L., Cade, B. E., Assimes, T. L., Becker, L. C., Beitelshees, A. L., Bielak, L. F., Bress, A. P., Brody, J. A., Chang, Y.-P. C., Chang, Y.-C., de Vries, P. S., Duggirala, R., Fox, E. R., Franceschini, N., Furniss, A. L., … Zhu, X. (2022). Rare coding variants in RCN3 are associated with blood pressure. BMC Genomics, 23(1). https://doi.org/10.1186/s12864-022-08356-4
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Jang, S.-K., Evans, L., Fialkowski, A., Arnett, D. K., Ashley-Koch, A. E., Barnes, K. C., Becker, D. M., Bis, J. C., Blangero, J., Bleecker, E. R., Boorgula, M. P., Bowden, D. W., Brody, J. A., Cade, B. E., Jenkins, B. W. C., Carson, A. P., Chavan, S., Cupples, L. A., Custer, B., … Vrieze, S. (2022). Rare genetic variants explain missing heritability in smoking. Nature Human Behaviour, 6(11), 1577–1586. https://doi.org/10.1038/s41562-022-01408-5
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Namjou, B., Lape, M., Malolepsza, E., DeVore, S. B., Weirauch, M. T., Dikilitas, O., Jarvik, G. P., Kiryluk, K., Kullo, I. J., Liu, C., Luo, Y., Satterfield, B. A., Smoller, J. W., Walunas, T. L., Connolly, J., Sleiman, P., Mersha, T. B., Mentch, F. D., Hakonarson, H., … Kottyan, L. (2022). Multiancestral polygenic risk score for pediatric asthma. Journal of Allergy and Clinical Immunology, 150(5), 1086–1096. https://doi.org/10.1016/j.jaci.2022.03.035
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Zhong, G., & Shen, Y. (2022). Statistical models of the genetic etiology of congenital heart disease. Current Opinion in Genetics & Development, 76, 101967. https://doi.org/10.1016/j.gde.2022.101967
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Kim, M. S., Naidoo, D., Hazra, U., Quiver, M. H., Chen, W. C., Simonti, C. N., Kachambwa, P., Harlemon, M., Agalliu, I., Baichoo, S., Fernandez, P., Hsing, A. W., Jalloh, M., Gueye, S. M., Niang, L., Diop, H., Ndoye, M., Snyper, N. Y., Adusei, B., … Lachance, J. (2022). Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa. Genome Biology, 23(1). https://doi.org/10.1186/s13059-022-02766-z
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Tahir, U. A., Katz, D. H., Avila-Pachecho, J., Bick, A. G., Pampana, A., Robbins, J. M., Yu, Z., Chen, Z.-Z., Benson, M. D., Cruz, D. E., Ngo, D., Deng, S., Shi, X., Zheng, S., Eisman, A. S., Farrell, L., Hall, M. E., Correa, A., Tracy, R. P., … Gerszten, R. E. (2022). Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-32275-3
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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., … Brown, C. D. (2022). A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. The American Journal of Human Genetics, 109(8), 1366–1387. https://doi.org/10.1016/j.ajhg.2022.06.012
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Bryois, J., Calini, D., Macnair, W., Foo, L., Urich, E., Ortmann, W., Iglesias, V. A., Selvaraj, S., Nutma, E., Marzin, M., Amor, S., Williams, A., Castelo-Branco, G., Menon, V., De Jager, P., & Malhotra, D. (2022). Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nature Neuroscience, 25(8), 1104–1112. https://doi.org/10.1038/s41593-022-01128-z
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Tcheandjieu, C., Zhu, X., Hilliard, A. T., Clarke, S. L., Napolioni, V., Ma, S., Lee, K. M., Fang, H., Chen, F., Lu, Y., Tsao, N. L., Raghavan, S., Koyama, S., Gorman, B. R., Vujkovic, M., Klarin, D., Levin, M. G., Sinnott-Armstrong, N., Wojcik, G. L., … Assimes, T. L. (2022). Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nature Medicine, 28(8), 1679–1692. https://doi.org/10.1038/s41591-022-01891-3
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Sorosina, M., Barizzone, N., Clarelli, F., Anand, S., Lupoli, S., Salvi, E., Mangano, E., Bordoni, R., Roostaei, T., Mascia, E., Zuccalà, M., Vecchio, D., Cavalla, P., Santoro, S., Ferrè, L., Zollo, A., Florio, L., Ragonese, P., … Martinelli Boneschi, F. (2022). A multi-step genomic approach prioritized TBKBP1 gene as relevant for multiple sclerosis susceptibility. Journal of Neurology, 269(8), 4510–4522. https://doi.org/10.1007/s00415-022-11109-8
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Herrera‐Luis, E., Ortega, V. E., Ampleford, E. J., Sio, Y. Y., Granell, R., de Roos, E., Terzikhan, N., Vergara, E. E., Hernandez‐Pacheco, N., Perez‐Garcia, J., Martin‐Gonzalez, E., Lorenzo‐Diaz, F., Hashimoto, S., Brinkman, P., Jorgensen, A. L., Yan, Q., Forno, E., Vijverberg, S. J., … Pino‐Yanes, M. (2022). Multi‐ancestry genome‐wide association study of asthma exacerbations. Pediatric Allergy and Immunology, 33(6). Portico. https://doi.org/10.1111/pai.13802
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Vujkovic, M., Ramdas, S., Lorenz, K. M., Guo, X., Darlay, R., Cordell, H. J., He, J., Gindin, Y., Chung, C., Myers, R. P., Schneider, C. V., Park, J., Lee, K. M., Serper, M., Carr, R. M., Kaplan, D. E., Haas, M. E., MacLean, M. T., Witschey, W. R., … Chang, K.-M. (2022). A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation. Nature Genetics, 54(6), 761–771. https://doi.org/10.1038/s41588-022-01078-z
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Shu, C., Jaffe, A. E., Sabunciyan, S., Ji, H., Astemborski, J., Sun, J., Bakulski, K. M., Sosnowski, D. W., Mehta, S. H., Kirk, G. D., & Maher, B. S. (2022). Epigenome-wide association analyses of active injection drug use. Drug and Alcohol Dependence, 235, 109431. https://doi.org/10.1016/j.drugalcdep.2022.109431
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Campbell, C., McCormack, M., Patel, S., Stapleton, C., Bobbili, D., Krause, R., Depondt, C., Sills, G. J., Koeleman, B. P., Striano, P., Zara, F., Sander, J. W., Lerche, H., Kunz, W. S., Stefansson, K., Stefansson, H., Doherty, C. P., Heinzen, E. L., Scheffer, I. E., … Cavalleri, G. L. (2022). A pharmacogenomic assessment of psychiatric adverse drug reactions to levetiracetam. Epilepsia, 63(6), 1563–1570. Portico. https://doi.org/10.1111/epi.17228
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Columbia Affiliation
Millischer, V., Matheson, G. J., Bergen, S. E., Coombes, B. J., Ponzer, K., Wikström, F., Jagiello, K., Lundberg, M., Stenvinkel, P., Biernacka, J. M., Breuer, O., Martinsson, L., Landén, M., Backlund, L., Lavebratt, C., & Schalling, M. (2022). Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden. The Lancet Psychiatry, 9(6), 447–457. https://doi.org/10.1016/s2215-0366(22)00100-6
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Wojczynski, M. K., Jiuan Lin, S., Sebastiani, P., Perls, T. T., Lee, J., Kulminski, A., Newman, A., Zmuda, J. M., Christensen, K., & Province, M. A. (2021). NIA Long Life Family Study: Objectives, Design, and Heritability of Cross-Sectional and Longitudinal Phenotypes. The Journals of Gerontology: Series A, 77(4), 717–727. https://doi.org/10.1093/gerona/glab333
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Li, X., Yung, G., Zhou, H., Sun, R., Li, Z., Hou, K., Zhang, M. J., Liu, Y., Arapoglou, T., Wang, C., Ionita-Laza, I., & Lin, X. (2022). A multi-dimensional integrative scoring framework for predicting functional variants in the human genome. The American Journal of Human Genetics, 109(3), 446–456. https://doi.org/10.1016/j.ajhg.2022.01.017
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Ha, E. E., Quartuccia, G. I., Ling, R., Xue, C., Karikari, R. A., Hernandez-Ono, A., Hu, K. Y., Matias, C. V., Imam, R., Cui, J., Pellegata, N. S., Herzig, S., Georgiadi, A., Soni, R. K., & Bauer, R. C. (2022). Adipocyte-specific tribbles pseudokinase 1 regulates plasma adiponectin and plasma lipids in mice. Molecular Metabolism, 56, 101412. https://doi.org/10.1016/j.molmet.2021.101412
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Tsapanou, A., Mourtzi, N., Charisis, S., Hatzimanolis, A., Ntanasi, E., Kosmidis, M. H., Yannakoulia, M., Hadjigeorgiou, G., Dardiotis, E., Sakka, P., Stern, Y., & Scarmeas, N. (2021). Sleep Polygenic Risk Score Is Associated with Cognitive Changes over Time. Genes, 13(1), 63. https://doi.org/10.3390/genes13010063
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Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Hwang, M. Y., Han, S., Narita, A., Choudhury, A., Bentley, A. R., Ekoru, K., Verma, A., … Willer, C. J. (2021). The power of genetic diversity in genome-wide association studies of lipids. Nature, 600(7890), 675–679. https://doi.org/10.1038/s41586-021-04064-3
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Ng, B., Casazza, W., Kim, N. H., Wang, C., Farhadi, F., Tasaki, S., Bennett, D. A., De Jager, P. L., Gaiteri, C., & Mostafavi, S. (2021). Cascading epigenomic analysis for identifying disease genes from the regulatory landscape of GWAS variants. PLOS Genetics, 17(11), e1009918. https://doi.org/10.1371/journal.pgen.1009918
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Auerbach, B. J., Hu, J., Reilly, M. P., & Li, M. (2021). Applications of single-cell genomics and computational strategies to study common disease and population-level variation. Genome Research, 31(10), 1728–1741. https://doi.org/10.1101/gr.275430.121
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