| Autor: |
Robin Walters, Zammy Fairhurst-Hunter, Kuang Lin, Iona Millwood, Alfred Pozarickij, Tzu-Ting Chen, Jason M. Torres, Jian'an Luan, Christiana Kartsonaki, Wei Gan, Anubha Mahajan, Huaidong Du, Rajani Sohoni, Yu Guo, Sam Sansome, Ling Yang, Canqing Yu, Yiping Chen, Jun Lv, Gibran Hemani, Masaru Koido, Yoichiro Kamatani, Cassandra Spracklen, Penny Gordon-Larsen, Mine Koprulu, Xiangrui Meng, Karoline Kuchenbaecker, Segun Fatumo, Laxmi Bhatta, Ben Brumpton, Jesus Alegre-Diaz, Pablo Kuri-Morales, Roberto Tapia-Conyer, Sarah Graham, Cristen Willer, Matthew Neville, Fredrik Karpe, Mariaelisa Graff, Kari North, Ruth Loos, Christopher Haiman, Ulrike Peters, Steven Buyske, Christopher Gignoux, Genevieve Wojcik, Yen-Feng Lin, Liming Li, Mark McCarthy, Zhengming Chen, Michael Holmes |
| Rok vydání: |
2022 |
| Popis: |
Genome-wide association studies (GWAS) in predominately European-ancestry (EUR) populations have identified numerous genetic variants associated with adiposity-related traits. An emerging challenge is the limited transferability of genetic scores constructed based on GWAS results from one ancestry for trait prediction in other ancestries. We performed trans-ancestry meta-analysis (TAMA) for eight adiposity-related traits using genetic data from 96,124 East Asian (EAS) and 443,359 EUR individuals. We identified >1400 genomic regions significantly associated with one or more traits. Despite EAS comprising only ~20% of the study population, genetic scores constructed from the trans-ancestry (TA) results accounted for between 30% and 79% more variation in the adiposity traits in EAS compared with scores derived from the EUR GWAS alone. Furthermore, TA scores also modestly improved variance explained in African/African American, Hispanic and South Asian populations. Our findings highlight the utility of TAMA for increasing variance explained by genetic scores across populations of different ancestries. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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