Combining the third molar mineralization to further improve the accuracy of the Kvaal's method in dental age estimation of subadults in northern China.

The morphological changes based on deposition of secondary dentin and mineralization of the third molar have been proven to be related to chronological age. However, Kvaal's method on the theory of deposition of secondary dentin was controversial with respect to dental age estimation in the recent research. The aim of this study was to combine the parameters of Kvaal's method with relatively high correlation coefficients and mineralization stages of the third molar to improve the accuracy of predicting the dental age of subadults in northern China. A total of 340 digital orthopantomograms of subadults aged from 15 to 21 years were analysed. A training group was used to test the accuracy of the original Kvaal's method and to establish novel methods for subadults in northern China. A testing group was used to compare the accuracy of the newly established methods with the Kvaal's original method and with published method specifically used in northern China. To increase the feasibility of our estimation model, we combined the mineralization of the third molar to build a combined specific formula. The results showed that the combined specific model increased the coefficient of determination to 0.513, and the standard error of the estimate was reduced to 1.482 years. We concluded that the combined specific model based on the deposition of secondary dentin and mineralization of the third molar could improve the accuracy of dental age assessment of subadults in northern China. Key Points: The decrease in the dental pulp cavity based on deposition of secondary dentin is a useful variable for assessing age.A total of 340 orthopantomographs were used in this research, including 278 in training groups and 62 in testing groups.Original Kvaal's method underestimated the dental age for subadults in northern China.The equation of combined specific method constructed in our study was proved more suitable to calculate dental age for subadults in northern China.

Application of Cameriere's method for dental age estimation in children in South China.

The aim of this study was to evaluate the applicability of Cameriere's European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children. Moreover, the performance of dental age estimation based on Cameriere's method combining the developmental information of permanent teeth (PT) and third molar (TM) was also analysed. Orthopantomographs of 720 healthy children in Group A, and orthopantomographs of 320 children and 280 subadults in Group B were assessed. The samples of Group A were divided into training dataset 1 and test dataset 1, and the samples of Group B were also divided into training dataset 2 and test dataset 2. A South China-specific formula was established based on the training dataset 1, and the comparison of accuracy between the Cameriere's European formula and the South China-specific formula was conducted with the test dataset 1. Additionally, a PT regression model, a TM regression model, and a combined regression model (PT + TM) were established based on the training dataset 2, and the performance of these three models were validated on the test dataset 2. The Cameriere's European formula underestimated chronological age with a mean difference (ME) of -0.47 ± 1.11 years in males and -0.69 ± 1.19 years in females. However, the South China-specific formula underestimated chronological age, with a mean difference (ME) of -0.02 ± 0.71 years in males and -0.14 ± 0.73 years in females. Compared with PT model and TM model, the PT and TM combined model obtained the smallest root mean square error (RMSE) of 1.29 years in males and 0.93 years in females. In conclusion, the South China-specific formula was more suitable for assessing the dental age of children in South China, and the PT and TM combined model can improve the accuracy of dental age estimation in children.Key pointsOrthopantomographs of 720 healthy children in Group A, and orthopantomographs of 320 children and 280 subadults in Group B were assessed.A South China-specific formula was established based on the training dataset 1, and the comparison of accuracy between the Cameriere's European formula and the South China-specific formula was conducted with the test dataset 1.A PT regression model, a TM regression model, and a combined regression model (PT + TM) were established based on the training dataset 2, and the performance of these three models were validated on the test dataset 2.The South China-specific formula was more suitable for assessing the dental age of children in South China, and the PT and TM combined model can improve the accuracy of dental age estimation in children.

Considering the flanking region variants of nonbinary SNP and phenotype-informative SNP to constitute 30 microhaplotype loci for increasing the discriminative ability of forensic applications.

The flanking region variants of nonbinary SNPs and phenotype-informative SNPs (piSNPs) have been observed, which may greatly improve the discriminative ability after constituting microhaplotype. In this study, 30 microhaplotype loci based on the nonbinary SNPs and piSNPs (shown to be related to phenotypes such as hair and eye color) were selected. Genotyping were conducted on 100 unrelated northern Han Chinese, and the 26 populations from the 1000 Genome Project were also included for comparison of populations differentiation. The simulated study was conducted for evaluating the efficiency of kinship testing. These 30 microhaplotype loci we selected had good polymorphism, with a mean effective number of alleles (Ae) of 3.46. The average Ae increase was 1.27 compared with the target SNPs. The populations from the five regions worldwide could also be distinguished using these loci. The results of kinship testing showed that these microhaplotype loci had the similar ability as 15 STR loci of AmpFlSTRR IdentifilerR PCR Amplification Kit to identify the biological parent and a stronger ability to exclude the nonbiological parents. So, these 30 microhaplotype loci may be multifunctional for forensic application, including the ability of personal identification and kinship testing equivalent to 15 STR loci, and the power of ancestry inference for distinguishing the main intercontinental population. Moreover, our selected phenotypic microhaplotype loci may theoretically have phenotype prediction capabilities. But the phenotype prediction efficiency of these phenotypic microhaplotype loci may be worse than that of piSNPs and the detailed prediction accuracy of different populations needs to be further studied.

Construction and forensic application of 20 highly polymorphic microhaplotypes.

Microhaplotype markers have become an important research focus in forensic genetics. However, many reported microhaplotype markers have limited polymorphisms. In this study, we developed a set of highly polymorphic microhaplotype markers based on tri-allelic single-nucleotide polymorphisms. Eleven newly discovered microhaplotypes along with nine previously identified in our laboratory were studied. The microhaplotype genotypes of unrelated individuals and familial samples were generated on the MiSeq PE300 platform. These 20 loci have an average greater than 3.5 effective number of alleles. Over the whole set, the cumulative power of discrimination was 1-3.3 × 10-18, the cumulative power of exclusion was 1-1.928 × 10-7 and the theoretical probability of detecting a mixture was 1-1.427 × 10-6. Differentiation comparisons of 26 populations from the 1000 Genomes Project distinguished among East Asian, South Asian, African and European populations. Overall, these markers enrich the current microhaplotype marker databases and can be applied for individual identification, paternity testing and biogeographic ancestry distinction.

Development and application of a nonbinary SNP-based microhaplotype panel for paternity testing involving close relatives.

Paternity testing involving close relatives is facing challenges in the field of forensic genetics. Microhaplotype has been proposed as a promising genetic marker for their low mutation rates and high discrimination power recently. In this study, we selected 30 microhaplotypes from 1000 genome projects, including one non-binary SNP, and other six microhaplotypes from published studies containing only binary SNPs to established a panel of microhaplotypes for paternity testing. Most microhaplotypes generated a high effective number of alleles (Ae) with the harmonic mean value of Ae of 3.91 and the arithmetic mean value of heterozygosity of 0.74, respectively. We collected 54 unrelated individuals and 53 samples from six extended families. It was noting that 13 samples from six extended families were unrelated so they were also included in unrelated individuals. The pedigrees of 38 parent-child duos, 55 uncle/aunt/grandparent-child duos (non-biological parent-child duos) and 29 full sibling pairs were constructed based on 53 samples from six extended families. The genotype and haplotype results demonstrated that the combined power of discrimination (CPD) reached 0.99999999999999999999999999999999799 and the cumulative probability of exclusion (CPE) reached 0.999999999999548. The combined probability of excluding relatives (uncle/aunt/grandparent) (CPER) was 0.999999993 (>0.9999), indicating that our panel had good effectiveness in preventing the misinterpretation of close relatives being biological parents. For 38 parent-child duos, the CPI by using the microhaplotypes panel was higher than the one by using Goldeneye 20A kit due to higher polymorphism and more loci in our panel. For 55 non-biological parent-child duos, the CPIs by using STR loci could not help determine 9 non-biological parent-child duos as "exclusions" of paternity while the CPIs by using microhaplotype loci could not help exclude the parenthood of 4 non-biological parent-child duos (CPI > 0.0001). Using the CPI derived from both datasets of STRs and microhaplotypes, all the non-biological parent-child duos could be considered as exclusions. The efficiency of excluding close relatives for this panel was evaluated by analyzing the parameters of 2000 simulated pairs, and the effectiveness was 0.988 at the threshold of t1 = 4 and t2 = -4. Moreover, the average Log10 combined full sibling index (CFSI) for all 29 full sibling pairs was about 7.55 after physical linkage taken account. These data demonstrated that this nonbinary SNPs-based microhaplotype panel has advantages in paternity testing, especially in STR mutated or close relatives involved cases.

Genetic polymorphisms of new 22 autosomal STR loci in the Mongolian ethnic group.

The Microreader™ 23SP ID System is a novel STR kit, but there are no Mongolian data related to this kit. In this study, allelic frequencies and forensic parameters were obtained from 505 unrelated healthy Mongolians. These samples were amplified using the kit. The dataset successfully passed quality control after being submitted to STRidER (STRidER dataset reference STR000198). A total of 264 alleles were observed, with corresponding allelic frequencies ranged from 0.001 to 0.378. The combined power of discrimination (CPD) and combined probability of exclusion (CPE) of the 22 autosomal STR loci were 0.999999999999999999999999999217318 and 0.999999999776042, respectively. Furthermore, population differentiation comparisons involving previously reported groups were conducted.

Accuracy of the Demirjian and Willems methods of dental age estimation for children from central southern China.

The aim of this study was to compare the accuracy of the Demirjian method and the Demirjian method as revised by Willems for age estimation based on orthopantomograms from central southern Chinese Han population aged 8-16 years. Discrepancies between chronological and estimated ages were statistically evaluated by analyzing 1249 orthopantomograms from 603 girls and 646 boys. Using the Demirjian method, the mean age estimates underestimated chronological age by 0.03 years (p = 0.48) for girls and overestimated it by 0.03 years (p = 0.59) for boys; these differences with respect to chronological age were not statistically significant. In contrast, the Willems method underestimated chronological age by 0.54 years (p < 0.01) for girls and 0.44 years (p < 0.01) for boys; these differences with respect to chronological age were statistically significant. Compared to the Demirjian method, the overall mean absolute error generated using the Willems method was slightly higher (0.85 and 0.86 years, respectively). Since the Demirjian method was more accurate, we highly recommend that it should be applied when estimating dental age in the Chinese Han population. Further modifications of these two methods for populations from other regions and additional studies of other age groups are warranted.