Combining genome-wide association studies highlight novel loci involved in human facial variation

Ziyi Xiong; Xingjian Gao; Yan Chen; Zhanying Feng; Siyu Pan; Haojie Lu; Andre G. Uitterlinden; Tamar Nijsten; Arfan Ikram; Fernando Rivadeneira; Mohsen Ghanbari; Yong Wang; Manfred Kayser; Fan Liu

doi:10.1038/s41467-022-35328-9

Nature Communications (Dec 2022)

Combining genome-wide association studies highlight novel loci involved in human facial variation

Ziyi Xiong,
Xingjian Gao,
Yan Chen,
Zhanying Feng,
Siyu Pan,
Haojie Lu,
Andre G. Uitterlinden,
Tamar Nijsten,
Arfan Ikram,
Fernando Rivadeneira,
Mohsen Ghanbari,
Yong Wang,
Manfred Kayser,
Fan Liu

Affiliations

Ziyi Xiong: Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam
Xingjian Gao: CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences
Yan Chen: Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam
Zhanying Feng: CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Siyu Pan: CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences
Haojie Lu: Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam
Andre G. Uitterlinden: Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam
Tamar Nijsten: Department of Dermatology, Erasmus MC, University Medical Center Rotterdam
Arfan Ikram: Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam
Fernando Rivadeneira: Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam
Mohsen Ghanbari: Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam
Yong Wang: CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Manfred Kayser: Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam
Fan Liu: Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam

DOI: https://doi.org/10.1038/s41467-022-35328-9
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 20

Abstract

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Combining multiple related traits can increase power in genetic association studies. Here, the authors develop a method to integrate GWAS statistics for multiple traits and apply it to find genetic loci affecting human facial variation.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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