Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction

Ziyi Xiong, Yi Li, Xianjing Liu, Haojie Lu, Pirro G. Hysi, Luba M. Pardo, Andre G. Uitterlinden, Fernando Rivadeneira, M. Arfan Ikram, Mohsen Ghanbari, Eppo B. Wolvius, Gennady V. Roshchupkin, Stephen Richmond, Tamar Nijsten, Timothy D. Spector, Sijia Wang, Fan Liu () and Manfred Kayser ()
Additional contact information
Ziyi Xiong: Erasmus MC University Medical Center Rotterdam
Yi Li: Chinese Academy of Sciences
Xianjing Liu: Erasmus MC University Medical Center Rotterdam
Haojie Lu: Erasmus MC University Medical Center Rotterdam
Pirro G. Hysi: King’s College London
Luba M. Pardo: Erasmus MC University Medical Center Rotterdam
Andre G. Uitterlinden: Erasmus MC University Medical Center Rotterdam
Fernando Rivadeneira: Erasmus MC University Medical Center Rotterdam
M. Arfan Ikram: Erasmus MC University Medical Center Rotterdam
Mohsen Ghanbari: Erasmus MC University Medical Center Rotterdam
Eppo B. Wolvius: Erasmus MC University Medical Center Rotterdam
Gennady V. Roshchupkin: Erasmus MC University Medical Center Rotterdam
Stephen Richmond: Cardiff University
Tamar Nijsten: Erasmus MC University Medical Center Rotterdam
Timothy D. Spector: King’s College London
Sijia Wang: Chinese Academy of Sciences
Fan Liu: Erasmus MC University Medical Center Rotterdam
Manfred Kayser: Erasmus MC University Medical Center Rotterdam

Nature Communications, 2025, vol. 16, issue 1, 1-19

Abstract: Abstract Facial appearance, one of the most recognizable and heritable human traits, exhibits substantial variation across individuals within and between populations due to its complex genetic underpinning, which remains largely elusive. Here, we report a combined genome-wide association study (C-GWAS) of 946 facial features derived from 44 landmarks obtained from 3D digital facial images of 11,662 individuals of European descent. We identify 253 unlinked single nucleotide polymorphisms (SNPs) across 188 distinct genetic loci significantly associated with facial variation, including 64 SNPs at 62 novel loci and 33 novel SNPs within 29 previously reported face loci that are in very low LD with the previously reported top SNPs. Together, these SNPs account for up to 7.9% of the facial variation per trait, marking an average 2.25-fold increase over previous estimates. Cross-ancestry replication in 9,674 Chinese confirms the effect of 70% of these SNPs. A 382-SNPs prediction model of five nose traits achieves an AUC of 0.67 for individual re-identification from nose images. DNA predicted faces of archaic humans differ more from those of Europeans than from Africans. In genetically modelled Neanderthal faces, 15 of 16 DNA-predicted facial features are in line with skull evidence. Ten DNA-predicted facial features differentiate Neanderthals from Denisovans. Overall, this study substantially enhances our genetic understanding of human facial variation and provides improvements of genetic face prediction in modern and archaic humans.

Date: 2025
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DOI: 10.1038/s41467-025-61761-7

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