The Genetics Research Of Adult Height Prediction In Sichuan And Inner Mongolia Han Population Based On SNPs

BackgroundHuman height is a complex quantitative trait which is controlled by multiple genes,mainly caused by genetic factors.With the application of Genome-wide association study(GWAS),the genetic studies of human height have been made breakthrough achievements.By 2019,about 780 height-related variants were found,and height prediction currently are used by weighted allele sums(WAS)to predict population height.It is of great practical significance to estimate the height of adults based on single nucleotide polymorphism(SNPs)genetic markers for individual identification in the field of forensic science.ObjectiveIn order to screen out more genetic markers associated with height in Sichuan and Inner Mongolia Han population,31 SNPs markers were selected in this study to be verified for height genetic associations among 1221 Sichuan and Inner Mongolia Han samples.A height prediction model was constructed and assessed for the height inference ability of the model in the Sichuan and Inner Mongolia Han population.Methods1.Under informed consent,the venous blood from 964 cases of Sichuan Han,257 cases of Inner Mongolia Han were collected,and their genomic DNA was extracted for SNP detection.2.According to the previous literature survey,31 height-related SNPs were screened out;The SNaPshot technique was used as detection system including the 21-site and 10-site labelled with 4-color of fluorescence dye,respectively.The genotypes of each samples were then performed by Gene Mapper software.3.The samples were divided into 6 groups on the basis of factors such as geography and gender,and the data were analyzed by 3 protocols.The first two protocols were based on two multiple linear regression analyses;The third protocol was based on logistic regression analysis,and the correlation analysis of the two categorical variables was performed for each group of samples.Finally,the results of the correlation analysis of the six groups of samples were comprehensively analyzed to screen out the SNP genetic markers associated with height.4.Twenty-two SNPs were screened to establish a height prediction model.The samples were divided into four groups,and each group was further divided into both tall subgroup and short subgroup.The weighted allele sums(WAS)method was used to construct the height estimation model of the high height subgroup and the short height subgroup,then the receiver operating characteristic(ROC)and the area under the curve(Area under curve,AUC)were applied to evaluate the accuracy of height prediction separately.Finally,the height prediction accuracy of the four groups of models was combined and comprehensively evaluated.Results1.Based on the SNaPshot technique,31 SNP loci were used to infer the height.Depending on whether there were polymorphisms or beta values,22 SNPs genetic markers can be thus utilised to assess the height estimation models using weighted allele summation.2.3,4 and 6 SNP loci associated with height(P<0.05)were observed by using three height correlation analysis protocols,respectively.Out of them,rs3823418 and rs2166898 were associated with height in three programs(P<0.05).3.The prediction accuracy of height with the 22 SNP loci in 2 different populations:the highest predictive accuracy was for Sichuan males,and the AUC value was 0.67(95%CI 0.55-0.79).4.Drawing the WAS value density curve showed that the overlap height of the high height and low height density curves was large,indicating that the trend of low height to high height is not obvious.Conclusions1.A method for detecting 31 SNP loci based on SNaPshot technology for estimating height was established in Sichuan and Inner Mongolia Han population.2.Seven height-associated SNP genetic markers such as rs3823418 were screened out to have significant correlation with height in Chinese Han population in the north and south of China.3.The prediction accuracy of the height prediction model in Sichuan Han population is up to 0.67,which would provide the basic data and technical support for prediction of individual height in the area of forensic science.