Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair

Shape variation of human head hair shows striking variation within and between human populations, while its genetic basis is far from being understood. We performed a series of genome-wide association studies (GWASs) and replication studies in a total of 28 964 subjects from 9 cohorts from multiple geographic origins. A meta-analysis of three European GWASs identified 8 novel loci (1p36.23

Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair

Shape variation of human head hair shows striking variation within and between human populations, while its genetic basis is far from being understood. We performed a series of genome-wide association studies (GWASs) and replication studies in a total of 28 964 subjects from 9 cohorts from multiple geographic origins. A meta-analysis of three European GWASs identified 8 novel loci (1p36.23 ERRFI1/SLC45A1, 1p36.22 PEX14, 1p36.13 PADI3, 2p13.3 TGFA, 11p14.1 LGR4, 12q13.13 HOXC13, 17q21.2 KRTAP, and 20q13.33 PTK6), and confirmed 4 previously known ones (1q21.3 TCHH/TCHHL1/LCE3E, 2q35 WNT10A, 4q21.21 FRAS1, and 10p14 LINC00708/GATA3), all showing genome-wide significant association with hair shape (

Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology

Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.Fil: Li, Yi. Chinese Academy of Sciences; República de China. Shanghai Institute Of Nutrition And Health; ChinaFil: Xiong, Ziyi. Erasmus University (erasmus University);Fil: Zhang, Manfei. Fudan University; China. Shanghai Institute Of Nutrition And Health; China. Shanghai Jiao Tong University; ChinaFil: Hysi, Pirro G.. Kings College London (kcl);Fil: Qian, Yu. Chinese Academy of Sciences; República de China. Beijing No.8 High School; ChinaFil: Adhikari, Kaustubh. Colegio Universitario de Londres; Reino Unido. The Open University (ou); Reino UnidoFil: Weng, Jun. Chinese Academy of Sciences; República de ChinaFil: Wu, Sijie. Fudan University; China. Fudan University; China. Shanghai Institute Of Nutrition And Health; ChinaFil: Du, Siyuan. Shanghai Institute Of Nutrition And Health; China. Shanghai Jiao Tong University; China. Chinese Academy of Sciences; República de ChinaFil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; ArgentinaFil: Schuler-Faccini, Lavinia. Universidade Federal do Rio Grande do Sul; BrasilFil: Bortolini, Maria Catira. Universidade Federal do Rio Grande do Sul; BrasilFil: Acuna Alonzo, Victor. National School Of Anthropology And History; MéxicoFil: Canizales Quinteros, Samuel. Instituto Nacional de Medicina Genómica; MéxicoFil: Gallo, Carla. Universidad Peruana Cayetano Heredia; PerúFil: Poletti, Giovanni. Universidad Peruana Cayetano Heredia; PerúFil: Bedoya, Gabriel. Universidad de Antioquia; ColombiaFil: Rothhammer, Francisco. Universidad de Tarapacá; ChileFil: Wang, Jiucun. Fudan University; ChinaFil: Tan, Jingze. Fudan University; ChinaFil: Yuan, Ziyu. Fudan-taizhou Institute Of Health Sciences; ChinaFil: Jin, Li. Shanghai Institute Of Nutrition And Health; China. Fudan-taizhou Institute Of Health Sciences; China. Fudan University; ChinaFil: Uitterlinden, André G.. Erasmus University (erasmus University);Fil: Ghanbari, Mohsen. Erasmus University (erasmus University);Fil: Ikram, M. Arfan. Erasmus University (erasmus University);Fil: Nijsten, Tamar. Erasmus University (erasmus University);Fil: Zhu, Xiangyu. Chinese Academy of Sciences; República de ChinaFil: Lei, Zhen. Chinese Academy of Sciences; República de ChinaFil: Jia, Peilin. Chinese Academy of Sciences; República de ChinaFil: Ruiz-Linares, Andres. Aix-Marseille Universite; Francia. Fudan University; China. University College London; Estados UnidosFil: Spector, Timothy D.. Kings College London (kcl);Fil: Wang, Sijia. Shanghai Institute Of Nutrition And Health; China. Chinese Academy of Sciences; República de ChinaFil: Kayser, Manfred. Erasmus University (erasmus University);Fil: Liu, Fan. Chinese Academy of Sciences; República de China. Erasmus University (erasmus University)

Two distinct clusters of 136 ear phenotypes derived from unsupervised hierarchical clustering.

(A) Two clusters for 136 phenotypes. (B) Phenotypic (right up) and genetic correlation matrix (left down) within and between the cluster. (TIF)</p

Characteristics of 136 ear phenotypes in 5 cohorts.

Characteristics of 136 ear phenotypes in 5 cohorts.</p

Definition of 21 ear landmarks in mice.

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.</div

16 ear-associated loci we identified in our current MinGWAS and C-GWAS.

The first 8 (A-H) were novel loci, others 8 were previously reported loci (I-P). Each figure includes three figures, LocusZoom (up) shows regional association plots for the top-associated ear phenotype (p values in CGWAS, except for the 6q21 PRDM1/ATG5, which solely identified by meta-analysis) with candidate genes aligned below according to the chromosomal positions (GRCh37.p13) followed by the linkage disequilibrium (LD) patterns (r2) of European. Ear map (left lower) shows the association (p values in Meta-analysis) between all ear phenotypes (P (DOCX)</p

Effects of sex (left) and age (right) on 136 ear phenotypes in RS.

Please note the different figure legends in these two figures. (TIF)</p

The effects of age and sex on 136 ear phenotypes in the RS cohort.

The effects of age and sex on 136 ear phenotypes in the RS cohort.</p