Predicting human age by detecting DNA methylation status in hair

Age prediction is of great importance for criminal investigation and judicial expertise. DNA methylation status is considered a promising method to infer tissue age by virtue of age-dependent changes on methylation sites. In recent years, forensic scientists have established various models to predict the chronological age of blood, saliva, and semen based on DNA methylation status. However, hair-inferred age has not been studied in the field of forensic science. In this study, we measured the methylation statuses of potential age-related CpG sites by using the multiplex methylation SNaPshot method. A total of 10 CpG sites from the LAG3, SCGN, ELOVL2, KLF14, C1orf132, SLC12A5, GRIA2, and PDE4C genes were found to be tightly associated with age in hair follicles. A correlation coefficient above 0.7 was found for four CpG sites (cg24724428 and Chr6:11044628 in ELOVL2, cg25148589 in GRIA2, and cg07547549 in SLC12A5). Among four age-prediction models, the multiple linear regression model consisting of 10 CpG sites provided the best-fitting results, with a median absolute deviation of 3.68 years. It is feasible to obtain both human identification and age information from a single scalp hair follicle. No significant differences in methylation degree were found between different sexes, hair types, or hair colors. In conclusion, we established a method to evaluate chronological age by assessing DNA methylation status in hair follicles.     

Development of a body fluid identification multiplex via DNA methylation analysis

The goal of this study is to develop an epigenetic multiplex for body fluid identification based on tissue specific DNA methylation. A series of genetic loci capable of discerning the origin of DNA as coming from saliva, blood, vaginal epithelia, or semen were used for this application. The markers – BCAS4, CG06379435, VE_8, and ZC3H12D – were amplified together and then sequenced via pyrosequencing. Methylation values for cytosine guanine dinucleotide (CpG) sites at each locus were then measured across the four markers. In total, 124 samples were collected, and bisulfite modified to convert unmethylated DNA to uracil. This converted DNA was then amplified via multiplex PCR with reverse primers containing a biotin molecule. Biotinylated PCR products were then analyzed using pyrosequencing to generate a series of pyrograms containing 18 CpG sites. The percent methylation at each CpG site was determined, and then agglomerative hierarchical cluster analysis was used to create a model to indicate sample origin. Further analysis reduced the number of CpG sites required for optimal determination of body fluid type to five. This study demonstrates an efficient multiplexed body fluid identification process utilizing DNA methylation that can be easily implemented in forensic laboratories.     

Genetic analyzer-dependent DNA methylation detection and its application to existing age prediction models

DNA methylation is the most promising biomarker for estimating human age. There are various methods used for analyzing DNA methylation. Among those, the SNaPshot assay-based method provides a semi-quantitative measurement of DNA methylation using capillary electrophoresis on genetic analyzers. However, DNA methylation measures produced using different types of genetic analyzers have never been compared, although differences in methylation values can directly affect age estimates. To evaluate the differences between the results generated by different genetic analyzers, we analyzed the same blood, saliva, and control methylated DNA using three genetic analyzers—the Applied Biosystems 3130, 3500, and SeqStudio—and compared the methylation values at five CpG sites: ELOVL2, FHL2, KLF14, MIR29B2C, and TRIM59. The methylation value at each of the five CpG sites decreased in the order 3130, 3500, and SeqStudio. The differences in the results produced by the different genetic analyzers resulted in significant errors when applying the 3500 and SeqStudio data to a previous age estimation model constructed using the 3130 Genetic Analyzer data. Therefore, DNA methylation measurements from 3500 and SeqStudio were corrected using the regression functions obtained by plotting the DNA methylation data of one instrument versus the other to facilitate the application of DNA methylation data from one instrument to the age prediction model based on other instruments. The age prediction accuracy obtained by applying corrected 3500 and SeqStudio data to the existing age estimation model was as high as observed in the 3130 data.     

Analysis of DNA methylation markers for tissue identification in individuals with different clinical phenotypes

Deoxyribonucleic acid (DNA) methylation patterns can be used to identify the type of tissue or body fluid found at a crime scene. However, tissue-related methylation levels have not been analyzed in individuals with different illnesses and medical conditions in forensic-specific studies. The primary goal of this study was to investigate if certain clinical phenotypes can alter the methylation levels of CpG sites in genes involved in tissue typing. Four studies with focus on DNA methylation analysis on individuals with different clinical conditions were selected from the Gene Expression Omnibus database. Then, a list of 137 CpG sites was compiled for further investigation. Statistical tests were performed to compare the beta-values results obtained for the control groups and the individuals affected by medical conditions. For each study, CpG sites that presented significant statistical differences between patients and control group were identified and it was possible to notice that DNA methylation levels can be affected in sites with potential forensic use. Although the observed DNA methylation variation (less than 10% difference) in this study would likely not cause any issues in body fluid identification, the results are important to show that this type of analysis should be taken into consideration when investigating and further validating body fluid markers. The CpG sites identified in this study should be further investigated by future studies on body fluids identification, and due to the significant difference in methylation levels in samples from affected individuals, caution must be taken before including these sites in tissue identification investigations.     

Genome-wide identification of age-related CpG sites for age estimation from blood DNA of Han Chinese individuals

Age-related CpG (AR-CpG) sites are currently the most promising molecular markers for forensic age estimation. However, the AR-CpG sites of Han Chinese population remains to be systematically characterized. In this study, we performed genome-wide methylation analyses on 42 whole blood DNA from healthy Han Chinese volunteers (aged from 18 to 62 years) using the Illumina MethylationEPIC BeadChip microarray. As expected, both known and novel AR-CpG sites were identified. Considering the sex difference in aging rate, we then separately selected AR-CpG candidates and built pyrosequencing-based multiple linear regression models for age estimation of males and females. The model constructed from the male sample group (n = 167, aged from 1.50 to 85.71 years) explained 95.22% of variation in age using five AR-CpG sites (chr6:11044864 ELOVL2, chr1:207997068 C1orf132, cg19283806 CCDC102B, cg17740900, and chr10:73740306 CHST3) and yielded a mean absolute error (MAE) of 2.79 years. The model constructed from the female sample group (n = 141, aged from 3.33 to 80.38 years) explained 94.90% of variation in age with six AR-CpG sites (chr6:11044867 ELOVL2, chr1:207997060 C1orf132, chr2:106015757 FHL2, cg26947034, chr16: 67184108 B3GNT9, and chr20:44658203 SLC12A5) and yielded an MAE of 2.53 years. Besides, the estimated age was highly correlated with the actual age (R > 0.97). The robustness of these AR-CpG markers was demonstrated by 10-fold cross-validations. In conclusion, we updated the AR-CpG sites of Han Chinese population and provided two sets of AR-CpG sites for accurate age estimation.     

A data-driven,high-throughput methodology to determine tissue-specific differentially methylated regions able to discriminate body fluids

Tissue-specific differentially methylated regions (tDMRs) are regions of the genome with methylation patterns that modulate gene expression in those tissue types. The detection of tDMRs in forensic evidence can permit the identification of body fluids at trace levels. In this report, we have performed a bioinformatic analysis of an existing array dataset to determine if new tDMRs could be identified for use in body fluid identification from forensic evidence. Once these sites were identified, primers were designed and bisulfite modification was performed. The relative methylation level for each body fluid at a given locus was then determined using qPCR with high-resolution melt analysis (HRM). After screening 127 tDMR's in multiple body fluids, we were able to identify four new markers able to discriminate blood (2 markers), vaginal epithelia (1 marker) and buccal cells (1 marker). One marker for each target body fluid was also tested with pyrosequencing showing results consistent with those obtained by HRM. This work successfully demonstrates the ability of in silico analysis to develop a novel set of tDMRs capable of being differentiated by real time PCR/HRM. The method can rapidly determine the body fluids left at crime scenes, assisting the triers of fact in forensic casework.     

The determination of tissue-specific DNA methylation patterns in forensic biofluids using bisulfite modification and pyrosequencing

The goal of this study is to explore the application of epigenetic markers in the identification of biofluids that are commonly found at the crime scene. A series of genetic loci were examined in order to define epigenetic markers that display differential methylation patterns between blood, saliva, semen, and epithelial tissue. Among the different loci tested, we have identified a panel of markers, C20orf117, ZC3H12D, BCAS4, and FGF7, that can be used in the determination of these four tissue types. Since methylation modifications occur at cytosine bases that are immediately followed by guanine bases (CpG sites), methylation levels were measured at CpG sites spanning each marker. Up to 11 samples of each tissue type were collected and subjected to bisulfite modification to convert unmethylated CpG-associated cytosine bases to thymine bases. The bisulfite modified DNA was then amplified via nested PCR using a primer set of which one primer was biotin labeled. Biotinylated PCR products were in turn analyzed and the methylation level at each CpG site was quantitated by pyrosequencing. The percent methylation values at each CpG site were determined and averaged for each tissue type. The results indicated significant methylation differences between the tissue types. The methylation patterns at the ZC3H12D and FGF7 loci differentiated sperm from blood, saliva, and epithelial cells. The C20orf117 locus differentiated blood from sperm, saliva, and epithelial cells and saliva was differentiated from blood, sperm, and epithelial cells at a fourth locus, BCAS4. The results of this study demonstrate the applicability of epigenetic markers as a novel tool for the determination of biofluids using bisulfite modification and pyrosequencing.     

Determining the global DNA methylation status of rat according to the identifier repetitive elements

A large portion of the genome represents repetitive elements. Identifier (ID) elements, the major elements of short interspersed repetitive elements, are widespread with about 150 000 copies in the rat genome. Each ID element contains six CpG dinucleotides, which might account for the global methylation status of rat. We validated the CpG methylation of the ID elements by various methods. The methylation of one CpG site (CpG-3) of the ID element was investigated by performing pyrosequencing. The methylation percentage of the CpG-3 site was 53.6% (SD = 2.2) on average from six rat tissues with blood, but 24.6% (SD = 1.0) in rat pheochromocytoma, PC-12, cell line. This CpG-3 methylation was further verified by whole genome amplification (WGA), 5-azacytidine treatment, and proportional mixing of rat WGA genomic DNA (gDNA) with liver gDNA. Methylation-sensitive restriction enzyme PCR method showed that three other CpG sites (CpG-1, CpG-4, and CpG-5) within the ID element were also methylated (about 60%) in rat gDNA, but not in WGA gDNA. The ID elements may be good candidates for routine analysis of the global DNA methylation changes of rat for pharmaceutical treatment and their use can make basic epigenetic research possible with high accuracy.     

Detection of DNA methylation by hyperbranched rolling circle amplification and DNA microarray

Aberrant DNA methylation of CpG sites has been confirmed to be closely associated with carcinogenesis.Based on the hyperbranched rolling circle amplification(HRCA) and microarray techniques,a new method for qualitative detection of methylation was developed.In the present study,padlock probes hybridize the sample DNA at the methylation site to form a probe-DNA complex which is ligated and digested simultaneously by methylation specific enzymes.Only at the methylated CpG site is the padlock probe ligated successfully to form a circle template for the HRCA reaction.Utilizing the method of 3-dimensional polyacrylamide gel-based microarray,the HRCA product will be immobilized on the slide to form a DNA microarray,which can universally hybridize the Cy3-labeled oligonucleotide probe to detect the methylation status of CpG sites.To control the false positive signals,DNA ligase and temperature of ligation/digestion are optimized.Methylation status of four CpG sites located in P15,Ecadherin,hMLH1 and MGMT genes were analyzed successfully with this method and all the results were compatible with that of methylation-specific PCR.Our research proves that this method is simple and inexpensive,and could be applied as a high-throughput tool to qualitatively determine the methylation status of CpG sites.     

Multiplex pyrosequencing of InDel markers for forensic DNA analysis

The capillary electrophoresis (CE) technology is commonly used for fragment length separation of markers in forensic DNA analysis. In this study, pyrosequencing technology was used as an alternative and rapid tool for the analysis of biallelic InDel (insertion/deletion) markers for individual identification. The DNA typing is based on a subset of the InDel markers that are included in the Investigator^® DIPplex Kit, which are sequenced in a multiplex pyrosequencing analysis. To facilitate the analysis of degraded DNA, the polymerase chain reaction (PCR) fragments were kept short in the primer design. Samples from individuals of Swedish origin were genotyped using the pyrosequencing strategy and analysis of the Investigator^® DIPplex markers with CE. A comparison between the pyrosequencing and CE data revealed concordant results demonstrating a robust and correct genotyping by pyrosequencing. Using optimal marker combination and a directed dispensation strategy, five markers could be multiplexed and analyzed simultaneously. In this proof‐of‐principle study, we demonstrate that multiplex InDel pyrosequencing analysis is possible. However, further studies on degraded samples, lower DNA quantities, and mixtures will be required to fully optimize InDel analysis by pyrosequencing for forensic applications. Overall, although CE analysis is implemented in most forensic laboratories, multiplex InDel pyrosequencing offers a cost‐effective alternative for some applications.     

基于激光诱导击穿光谱(LIBS)的煤灰熔点快速检测

炉内结渣是影响火电机组和气化工艺可靠运行的关键因素之一,准确预测灰熔点可以提前调整炉膛出口温度以避免结渣。本论文采用激光诱导击穿光谱（LIBS）采集煤灰样中金属元素的光谱,分别建立煤灰中的金属元素的谱线强度与煤灰熔点的随机森林模型、支持向量机回归模型和线性回归模型,直接预测煤灰熔点温度。采用基于马氏距离(MD)的异常数据剔除算法和基于稀疏矩阵的基线估计与降噪算法（BEADS）,对粉煤灰样的全光谱数据进行了预处理。随机森林模型对粉煤灰熔点的预测平均相对误差（MRE）为54.74%,支持向量机回归模型的预测平均相对误差为60.08%,而线性回归模型的预测平均相对误差达到了9.78%。研究结果表明,线性回归模型对煤灰熔点的预测结果更准确。     

DNA methylation ratio variability may impede clinical application of cancer diagnostic markers

Hypermethylation at promoter regions of tumour suppressor genes is diagnostic for many cancers. Many genomic regions that may be the targets for clinical diagnostic assays have been identified through use of measuring systems reliant on bisulphite conversion, but few of these promising markers are in clinical use. The comparability of a widely used DNA methylation measuring system involving bisulphite conversion was evaluated by supplying three experienced centres with methylated DNA reference material mixtures that were independently prepared and characterised by mass spectrometry and high-pressure liquid chromatography. A replication scheme was designed to evaluate reproducibility of key analytical steps within and between laboratories by regression analysis. In general, methylation was underestimated and methylation ratio values were highly variable. The difference in methylation ratio between CpG sites was the key contributor to variable results. The CpG site effect followed a similar pattern at all centres and at all methylation levels examined indicating that sequence context had a major effect on methylation ratio measurement using the bisulphite conversion process. The magnitude of underestimation combined with the variability of measurements between CpG sites compromises the concept of measuring genomic regional methylation by averaging the methylation ratios of many CpG sites. There were no significant differences in replicate bisulphite conversions or sample work-up and instrument analysis at each centre thus making this technique suitable for comparative intralaboratory investigations. However, it may not be suitable for a routine diagnostic assay without extensive standardisation efforts.     

Predicting methylation status of human DNA sequences by pseudo-trinucleotide composition

DNA methylation plays a key role in the regulation of gene expression. The most common type of DNA modification consists of the methylation of cytosine in the CpG dinucleotide. The detections of DNA methylation have been determined mostly by experimental methods; however, these methods were time-consuming, expensive, and difficult to meet the requirements of modern large-scale sequencing technology. Accordingly, it is necessary to develop automatic and reliable prediction methods for DNA methylation.In this study, the pseudo-trinucleotide composition was proposed, and a novel method was developed by support vector machine (SVM) with the pseudo-trinucleotide composition as input parameter to represent DNA sequence for DNA methylation prediction. The model was evaluated on two datasets, including a dataset of Rollins (dataset_1) and a dataset collected healthy human records from the MethDB database (dataset_2). For dataset_1, the Matthews correlation coefficient (MCC) and accuracy (ACC) by jackknife validation were 0.8051 and 0.6098, respectively. For dataset_2, the MCC and ACC were 0.8500 and 0.7203, respectively. The good prediction results reveal that the pseudo-trinucleotide composition is an effective representation method for DNA sequence and plays a very important role in the prediction of DNA function.     

DNA microarray: a high throughput approach for methylation detection

We described a DNA microarray-based method combined with bisulphite treatment of DNA and regular PCR to examine hyper-methylation in promoter 1A of APC gene. A set of oligonucleotide probes were designed and immobilized on the aldehyde-coated glass slides for detecting the methylation pattern of 15 selected CpG sites in the region. The methylation status of 30 colorectal tumor samples have been examined by both of methylation-specific PCR (MS-PCR) and the present microarray method. The methylation pattern of the 15 CpG sites for the samples have been obtained with the microarray. A total of 19 samples out of 30 were methylated by microarray, in which five samples cannot be detected by MS-PCR due to the methylated CpG patterns not accordant to the MS-PCR primers. The detecting ratio for methylation of APC gene of colorectal tumor samples increased from 46.7% with MS-PCR to 63.3% with the microarray, which successfully demonstrated that DNA microarray-based method not only can obtained the methylation patterns for the related genes, but also decrease the false-negative results of methylation status by the conventional MS-PCR for the investigated genes.     

High-resolution melt analysis for the detection of skin/sweat via DNA methylation

The determination of tissue type is important when reconstructing a crime scene as skin cells may indicate innocent contact, whereas other types of cells, such as blood and semen, may indicate foul play. Up to now, there has been no specific DNA methylation-based marker to distinguish skin cell DNA from other body fluids. The goal of this study is to develop a DNA methylation-based assay to detect and identify skin cells collected at forensic crime scenes for use in DNA typing. For this reason, we have utilized a DNA methylation chip array-based genome-wide association study to identify skin-specific DNA methylation markers. DNA obtained from skin along with other body fluids, such as semen, saliva, blood, and vaginal epithelia, were tested using five genes that were identified as sites for potential new epigenetic skin markers. Samples were collected, bisulfite converted, and subjected to real-time polymerase chain reaction (PCR) with high-resolution melt analysis. In our studies, when using WDR11, PON2, and NHSL1 assays with bisulfite-modified PCR, skin/sweat amplicons melted at lower temperatures compared to blood, saliva, semen, and vaginal epithelia. One-way analysis of variance demonstrates that these three skin/sweat markers are significantly different when compared with other body fluids (p < 0.05). These results demonstrate that high-resolution melt analysis is a promising technology to detect and identify skin/sweat DNA from other body fluids.