A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features

Siyuan Du; Jieyi Chen; Jiarui Li; Wei Qian; Sijie Wu; Qianqian Peng; Yu Liu; Ting Pan; Yi Li; Sibte Syed Hadi; Jingze Tan; Ziyu Yuan; Jiucun Wang; Kun Tang; Zhuo Wang; Yanqin Wen; Xinran Dong; Wenhao Zhou; Andrés Ruiz-Linares; Yongyong Shi; Li Jin; Fan Liu; Manfei Zhang; Sijia Wang

doi:10.1016/j.jgg.2024.07.005

A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features

J Genet Genomics. 2024 Jul 11:S1673-8527(24)00181-4. doi: 10.1016/j.jgg.2024.07.005. Online ahead of print.

Authors

Siyuan Du¹, Jieyi Chen², Jiarui Li³, Wei Qian³, Sijie Wu³, Qianqian Peng³, Yu Liu³, Ting Pan⁴, Yi Li³, Sibte Syed Hadi⁵, Jingze Tan⁶, Ziyu Yuan⁷, Jiucun Wang⁸, Kun Tang³, Zhuo Wang⁴, Yanqin Wen⁴, Xinran Dong⁹, Wenhao Zhou¹⁰, Andrés Ruiz-Linares¹¹, Yongyong Shi⁴, Li Jin⁸, Fan Liu¹², Manfei Zhang¹³, Sijia Wang¹⁴

Affiliations

¹ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China.
² CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China.
³ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China.
⁴ Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China.
⁵ Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia.
⁶ Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.
⁷ Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China.
⁸ Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China.
⁹ Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China.
¹⁰ Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China; Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China.
¹¹ Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Aix-Marseille Université, CNRS, EFS, ADES, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK.
¹² Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, 3015 CN Rotterdam, the Netherlands.
¹³ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China. Electronic address: zhangmanfei@sjtu.edu.cn.
¹⁴ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China. Electronic address: wangsijia@picb.ac.cn.

PMID: 39002897
DOI: 10.1016/j.jgg.2024.07.005

Abstract

Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conducted a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identified 71 genomic loci associated with facial features, including 21 novel loci. We developed a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibited relevant correlations with observed facial features. Furthermore, we applied the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and aligned predictions with the fossil records. Our results suggested that Neanderthals and Denisovans likely shared similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width was characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.

Keywords: Ancient DNA; Archaic human; Facial morphology; Facial polygenic score; Genome-wide association study; Multi-ethnic meta-analysis.