Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M., Al Thani, Asma, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Damrauer, Scott M., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Ioannidis, Alexander, Jansonius, Nomdo M., Konuma, Takahiro, Lee, Ming Ta Michael, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E., Moatamed, Babak, Nava-Aguilar, Marco A., Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Katsanis, Nicholas, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Takano, Tomohiro, Trembath, Richard C., Vonk, Judith M., Whiteman, David C., Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Bustamante, Carlos D., Cox, Nancy J., Fatumo, Segun, Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lee, Seunggeun, Lin, Yen-Feng, Mbarek, Hamdi, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Rader, Daniel J., Ritchie, Marylyn D., Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., Neale, Benjamin M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903716/
https://www.ncbi.nlm.nih.gov/pubmed/36777996
http://dx.doi.org/10.1016/j.xgen.2022.100192
Descripción
Sumario:Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Ejemplares similares