Browsing by Author "Wu, Sijie"

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    Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair
    (Oxford University Press, 2018-02-01) Liu, Fan; Chen, Yan; Zhu, Gu; Hysi, Pirro G.; Wu, Sijie; Adhikari, Kaustubh; Breslin, Krystal; Pośpiech, Ewelina; Hamer, Merel A.; Peng, Fuduan; Muralidharan, Charanya; Acuna-Alonzo, Victor; Canizales-Quinteros, Samuel; Bedoya, Gabriel; Gallo, Carla; Poletti, Giovanni; Rothhammer, Francisco; Bortolini, Maria Catira; Gonzalez-Jose, Rolando; Zeng, Changqing; Xu, Shuhua; Jin, Li; Uitterlinden, André G.; Ikram, M. Arfan; van Duijn, Cornelia M.; Nijsten, Tamar; Walsh, Susan; Branicki, Wojciech; Wang, Sijia; Ruiz-Linares, Andrés; Spector, Timothy D.; Martin, Nicholas G.; Medland, Sarah E.; Kayser, Manfred; Biology, School of Science
    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 (P < 5e-8). All except one (1p36.22 PEX14) were replicated with nominal significance in at least one of the 6 additional cohorts of European, Native American and East Asian origins. Three additional previously known genes (EDAR, OFCC1, and PRSS53) were confirmed at the nominal significance level. A multivariable regression model revealed that 14 SNPs from different genes significantly and independently contribute to hair shape variation, reaching a cross-validated AUC value of 0.66 (95% CI: 0.62-0.70) and an AUC value of 0.64 in an independent validation cohort, providing an improved accuracy compared with a previous model. Prediction outcomes of 2504 individuals from a multiethnic sample were largely consistent with general knowledge on the global distribution of hair shape variation. Our study thus delivers target genes and DNA variants for future functional studies to further evaluate the molecular basis of hair shape in humans.
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    Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA
    (Elsevier, 2018-11) Pośpiech, Ewelina; Chen, Yan; Kukla-Bartoszek, Magdalena; Breslin, Krystal; Aliferi, Anastasia; Andersen, Jeppe D.; Ballard, David; Chaitanya, Lakshmi; Freire-Aradas, Ana; van der Gaag, Kristiaan J.; Girón-Santamaría, Lorena; Gross, Theresa E.; Gysi, Mario; Huber, Gabriela; Mosquera-Miguel, Ana; Muralidharan, Charanya; Skowron, Malgorzata; Carracedo, Ángel; Haas, Cordula; Morling, Niels; Parson, Walther; Phillips, Christopher; Schneider, Peter M.; Sijen, Titia; Syndercombe-Court, Denise; Vennemann, Marielle; Wu, Sijie; Xu, Shuhua; Jin, Li; Wang, Sijia; Zhu, Ghu; Martin, Nick G.; Medland, Sarah E.; Branicki, Wojciech; Walsh, Susan; Liu, Fan; Kayser, Manfred; Biology, School of Science
    Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.