The use of male pattern baldness SNP markers in forensic phenotyping

In forensic science, single nucleotide polymorphism (SNP) markers are utilised for identification, phenotyping, and lineage and ancestry determination. Recently, there has been a growing demand in determining physical characteristics such as eye, hair and skin colour, male pattern baldness, facial morphology and height by DNA analysis. Phenotypic information obtained from DNA is thought to be very useful in identifying unknown suspects, disaster victims or missing persons or as a elimination criteria. In this study, a multiplex panel consisting of 23-SNP (Single Nucleotide Polymorphism) markers identified in the literature to be highly significant with male pattern baldness (MPB) was designed and optimised. MPB prediction analysis was performed using buccal swab samples from a total of 144 individuals (86 models, 58 tests), consisting of 114 male volunteers aged 50 years and older classified as baldness Type 5-7 (significant baldness) according to Hamilton-Norwood classification criteria and 30 male volunteers aged 50 years and older who were nonbald (Type 1). SNP baldness markers were studied by SNaPshot method and baldness prediction was tested using binary logistic regression (BLR) analysis with IBM SPSS Statistics v.21. As a result of the statistical evaluation, 9-SNP markers were detected from TARDBP, WNT10, HDAC4, HDAC9, SSPN-ITPR2, SETBP1, AR/EDA2R loci, which were associated with the baldness phenotype according to the results of univariate binary logistic regression of 23 SNP markers. 9-SNP prediction model was generated by multivariate BLR analysis with rs12565727, rs7349332, rs9287638, rs2073963, rs9668810, rs10502861, rs1041668, rs1511061, rs16990427 markers. The accuracy of the 9-SNP prediction model was evaluated by calculating AUC (Area under the ROC Curve), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The 9-SNP prediction model predicted MPB with 98.5% sensitivity and 44% specificity with an AUC of 0.897, discriminating between no baldness (Type 1) and severe baldness (Type 5-7).