| Background In forensic science,it is great to predict the age of a criminal suspect or an unidentified person by the biological samples which were collected on the spot for detecting the cases.Although DNA methylation markers are ideal in a series of individual age estimation indexes reported so far,their accuracy is still difficult to meet the needs of forensic “accurate identification”.The best way to predict an individual’s age with high accuracy is the joint analysis of multiple age-related biomarkers.Therefore,it is necessary to continue to search for new biomarkers for forensic age estimation.CircularRNAs(circRNAs)are a novel class of regulatoryRNAs that have been widely concerned in recent years.Studies have shown that circRNAs exist widely in various types of human cells,and are not easy to be hydrolyzed by Rnase R.They have higher stability and longer half-life than mRNA.Moreover,circRNAs play a role in the aging process of many organisms(such as mice and nematodes),and their expression levels are up-regulated or down regulated with aging.Therefore,circRNAs may be another kind of ideal biomarker for forensic age estimation.Objective The purposes of this project are to systematically study the feasibility,effectiveness and applicability of individual age estimation based on the expression differences of circRNAs,and look for new biomarker or method for individual age estimation of forensic biological materials and then to lay the foundation for the future study on age-dependent expression changes of circRNAs in other human body fluids and tissues.Methods(1)42 healthy unrelated individuals’ vitro anticoagulant 2 ml aged60 ± 2 years,40 ± 2 years and 20 ± 2 years in Chinese Han population(7 males and 7females in each group)were collected.AfterRNA extraction,the expression profiles of circRNAs were detected by human circRNAs microarray.And F-test of Random Variance Model(RVM)was used to screen different expression of circRNAs.Then combined with Series Test of Cluster analysis(STC)and hierarchical cluster analysis,circRNAs whose expression level changed significantly with aging were selected as candidate markers.(2)According to the sequences of candidate circRNAs,we designed divergent primers to verify the expression trend of candidate circRNAs with aging by real-time quantitative PCR(RT-q PCR)in small samples,and further screened them according to Spearman correlation coefficient for determining the final target circRNAs markers.(3)RT-q PCR technology was still used to quantitatively study the age-related changes and gender differences of target circRNAs expression,and the age-related expression curves were drawn.Finally,Multiple linear regression and support vector regression were used to develop the age estimation models.Results(1)The results of circRNAs microarray:(1)412 differentially expressed circRNAs were obtained from male samples and 771 differentially expressed circRNAs were obtained from female samples by screening.(2)The hierarchical cluster diagram showed that,there were some differences between the youth group and the elderly group,and between the youth group and the middle-aged group,while significant differences between the middle-aged group and the elderly group in male samples;there were significant differences between the youth group and the elderly group,and between the middle-aged group and the elderly group,but there was no significant difference between the youth group and the middle-aged group in the female samples.(3)Profile4,Profile 7,and Profile 9 of male samples were selected,and Profile 9,and Profile 11 of female samples were selected by STC analysis.A total of20 candidate circRNAs markers were obtained from male and female samples for subsequent RT-q PCR validation.(2)Validation results of candidate circRNAs: Among the 20 candidate circRNAs,16 could be amplified specifically.After preliminary verification by RT-q PCR,we selected 8 circRNAs whose Spearman correlation coefficient absolute value was greater than or equal to 0.2 for as age-related target circRNAs markers.Among them,the expression trends of hsa＿circ＿0001432 verified by female samples、hsa＿circ＿0006148 and hsa＿circ＿0005615 were consistent with microarray analysis,and the expression levels of hsa＿circ＿0006148 was up-regulated with aging,and hsa＿circ＿0001432 verified by female samples and hsa＿circ＿0005615were decreased with aging.However,the expression trends of hsa＿circ＿0001432verified by male samples、hsa＿circ＿0085129、hsa＿circ＿0009061、hsa＿circ＿0004412、hsa＿circ＿0002113 and hsa＿circ＿0087890 were not consistent with microarray analysis,and the expression levels of circRNAs were up-regulated with aging.(3)Quantitative study of target circRNAs: the results of 103 male blood samples showed that the absolute value of Spearman correlation coefficient of hsa＿circ＿0001432、hsa＿circ＿0085129、hsa＿circ＿0009061、hsa＿circ＿0006148、hsa＿circ＿0004412、hsa＿circ＿0002113 and hsa＿circ＿87890 ranged from 0.0740 to 0.3911,and the Spearman correlation coefficients of hsa＿circ＿0005615 and hsa＿circ＿0001432 were 0.2911 and0.0106,respectively in female samples.(4)Individual age estimation model: In male samples,SVR reached a higher age prediction accuracy with a MAE of 6.81 years(r =0.6973),while MLR has a lower age prediction accuracy(MAE = 9.60,r = 0.4274).In female samples,SVR showed the little lower accuracy with a MAE of 9.80 years(r= 0.3042),while MLR reached the higher accuracy(MAE = 9.72,r = 0.3064).Conclusion The expression of some circRNAs in human blood samples does change with aging,which can be used as a new biomarker for the age estimation in forensic medicine.At the same time,it also lays a foundation for the future joint analysis of multiple age-related biomarkers with high precision and can provide additional clues for forensic investigation. |
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