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Xiao C, Yi S, Huang D. Genome-wide identification of age-related CpG sites for age estimation from blood DNA of Han Chinese individuals. Electrophoresis 2021; 42:1488-1496. [PMID: 33978960 DOI: 10.1002/elps.202000367] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/07/2021] [Accepted: 05/05/2021] [Indexed: 11/11/2022]
Abstract
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.
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Affiliation(s)
- Chao Xiao
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, P. R. China
| | - Shaohua Yi
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, P. R. China
| | - Daixin Huang
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, P. R. China
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Iroanya OO, Obi JC, Ogunyinka OO, Bosede OT, Egwuatu TF, Adewole RA. Messenger RNA (mRNA)-based age determination using skin-specific markers of saliva epithelial cells. BENI-SUEF UNIVERSITY JOURNAL OF BASIC AND APPLIED SCIENCES 2020. [DOI: 10.1186/s43088-020-00067-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Age determination is a vital factor in biological identification in forensics. This study was carried out to determine the expression levels of three target genes (Keratin 9 (KRT9), Loricrin (LOR) and Corneodesmosin (CDSN)) in salivary epithelial cells and how they can be used in age determination using reference gene, β-actin. Thirty young adults participated in the study and were divided into three groups according to their ages (16–20, 21–25, and 26–30). Ribonucleic acid (RNA) extraction, complementary deoxyribonucleic acid (cDNA) synthesis and quantitative polymerase chain reaction (qPCR) were performed. Data analysis was done using IBM SPSS Version 26 and the comparative Ct method (2−∆∆Ct method).
Results
CDSN was detected in all the sampled age groups. Though the age group 16–20 had the highest (0.4237) expression of CDSN among the three age groups, there was no significant difference (p > 0.05) in the expression of the gene among the three age groups. The LOR gene was lowly expressed across all age groups used in the study. The expression of the gene did not significantly differ (p > 0.05) between the control and 26–30 years age group, but they were however significantly higher (F = 36.47, p ≤ 0.05) than the expression of the gene in both 16–20 and 21–25 years age groups. The KRT9 gene was expressed only in age groups 16–20 and 26–30 and the expression of the gene did not significantly (p > 0.05) differ between these age groups. Though the expression of all the target genes was low, it was observed that the LOR gene expression varied among 21–25 and 26–30 age groups; therefore, more data and further analyses are still required since this experimental approach for age determination using gene expression is still at an emerging stage.
Conclusion
Although RNA concentration was low and the expression values of the genes were low and could not be used in comparing the expression levels among the three age groups, it can be concluded that the three messenger ribonucleic acid (mRNA) markers CDSN, LOR and KRT9, as well as the ACTB reference mRNA marker analysed via the described qPCR assays, are suitable for identifying epithelial cells in saliva.
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Gao X, Liu S, Song H, Feng X, Duan M, Huang L, Zhou F. AgeGuess, a Methylomic Prediction Model for Human Ages. Front Bioeng Biotechnol 2020; 8:80. [PMID: 32211384 PMCID: PMC7075810 DOI: 10.3389/fbioe.2020.00080] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 01/29/2020] [Indexed: 12/15/2022] Open
Abstract
Aging was a biological process under regulations from both inherited genetic factors and various molecular modifications within cells during the lifespan. Multiple studies demonstrated that the chronological age may be accurately predicted using the methylomic data. This study proposed a three-step feature selection algorithm AgeGuess for the age regression problem. AgeGuess selected 107 methylomic features as the gender-independent age biomarkers and the Support Vector Regressor (SVR) model using these biomarkers achieved 2.0267 in the mean absolute deviation (MAD) compared with the real chronological ages. Another regression algorithm Ridge achieved a slightly better MAD 1.9859 using the same biomarkers. The gender-independent age prediction models may be further improved by establishing two gender-specific models. And it's interesting to observe that there were only two methylation biomarkers shared by the two gender-specific biomarker sets and these two biomarkers were within the two known age-associated biomarker genes CALB1 and KLF14.
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Affiliation(s)
- Xiaoqian Gao
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
| | - Shuai Liu
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
| | - Haoqiu Song
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China.,College of Computer Science, Hubei University of Technology, Wuhan, China
| | - Xin Feng
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
| | - Meiyu Duan
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
| | - Lan Huang
- Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
| | - Fengfeng Zhou
- BioKnow Health Informatics Laboratory Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Ministry of Education, Jilin University, Changchun, China
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Li L, Song F, Lang M, Hou J, Wang Z, Prinz M, Hou Y. Methylation-Based Age Prediction Using Pyrosequencing Platform from Seminal Stains in Han Chinese Males. J Forensic Sci 2019; 65:610-619. [PMID: 31498434 DOI: 10.1111/1556-4029.14186] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Revised: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 01/10/2023]
Abstract
Various methods have been performed to predict an unknown individual's age from biological traces in forensic investigations. A considerably accurate age prediction for the semen donor can help narrow down the search in a sexual assault case. The aim of this study was to develop an assay for age prediction from seminal stains in Han Chinese males. We built a sperm-specific linear regression model using bisulfite pyrosequencing. Validations were conducted with a Mean Absolute Deviation from the chronological age (MAD) of 4.219 years in liquid semen, 4.158 years in fresh seminal stains, 4.393 years in aged seminal stains, and 3.880 years in mixed stains, respectively. Furthermore, our strategy enables accurate age prediction using a forensic casework sample. The strategy indicated that we produced an accurate and reliable age prediction tool for the semen donors in Han Chinese males for forensic purposes.
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Affiliation(s)
- Luyao Li
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Feng Song
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Min Lang
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Jiayi Hou
- Institute for Genomic Medicine, University of California, La Jolla, San Diego, CA, 92093
| | - Zheng Wang
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Mechthild Prinz
- Department of Sciences, John Jay College of Criminal Justice, New York, NY, 10019
| | - Yiping Hou
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
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5
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DNA methylation-based age prediction using massively parallel sequencing data and multiple machine learning models. Forensic Sci Int Genet 2018; 37:215-226. [DOI: 10.1016/j.fsigen.2018.09.003] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 08/23/2018] [Accepted: 09/06/2018] [Indexed: 01/09/2023]
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6
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Zhao F, Lee EY, Shin Y. Improved Reversible Cross-Linking-Based Solid-Phase RNA Extraction for Pathogen Diagnostics. Anal Chem 2018; 90:1725-1733. [DOI: 10.1021/acs.analchem.7b03493] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Fei Zhao
- Department of Convergence Medicine, Asan Medical Center,
University of Ulsan College of Medicine, and Biomedical Engineering
Research Center, Asan Institute of Life Sciences, 88 Olympicro-43gil, Songpa-gu, Seoul 05505, Republic of Korea
| | - Eun Yeong Lee
- Department of Convergence Medicine, Asan Medical Center,
University of Ulsan College of Medicine, and Biomedical Engineering
Research Center, Asan Institute of Life Sciences, 88 Olympicro-43gil, Songpa-gu, Seoul 05505, Republic of Korea
| | - Yong Shin
- Department of Convergence Medicine, Asan Medical Center,
University of Ulsan College of Medicine, and Biomedical Engineering
Research Center, Asan Institute of Life Sciences, 88 Olympicro-43gil, Songpa-gu, Seoul 05505, Republic of Korea
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7
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Human age estimation from blood using mRNA, DNA methylation, DNA rearrangement, and telomere length. Forensic Sci Int Genet 2016; 24:33-43. [PMID: 27288716 DOI: 10.1016/j.fsigen.2016.05.014] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Revised: 05/23/2016] [Accepted: 05/23/2016] [Indexed: 11/22/2022]
Abstract
Establishing the age of unknown persons, or persons with unknown age, can provide important leads in police investigations, disaster victim identification, fraud cases, and in other legal affairs. Previous methods mostly relied on morphological features available from teeth or skeletal parts. The development of molecular methods for age estimation allowing to use human specimens that possess no morphological age information, such as bloodstains, is extremely valuable as this type of samples is commonly found at crime scenes. Recently, we introduced a DNA-based approach for human age estimation from blood based on the quantification of T-cell specific DNA rearrangements (sjTRECs), which achieves accurate assignment of blood DNA samples to one of four 20-year-interval age categories. Aiming at improving the accuracy of molecular age estimation from blood, we investigated different types of biomarkers. We started out by systematic genome-wide surveys for new age-informative mRNA and DNA methylation markers in blood from the same young and old individuals using microarray technologies. The obtained candidate markers were validated in independent samples covering a wide age range using alternative technologies together with previously proposed DNA methylation, sjTREC, and telomere length markers. Cross-validated multiple regression analysis was applied for estimating and validating the age predictive power of various sets of biomarkers within and across different marker types. We found that DNA methylation markers outperformed mRNA, sjTREC, and telomere length in age predictive power. The best performing model included 8 DNA methylation markers derived from 3 CpG islands reaching a high level of accuracy (cross-validated R(2)=0.88, SE±6.97 years, mean absolute deviation 5.07 years). However, our data also suggest that mRNA markers can provide independent age information: a model using a combined set of 5 DNA methylation markers and one mRNA marker could provide similarly high accuracy (cross-validated R(2)=0.86, SE±7.62 years, mean absolute deviation 4.60 years). Overall, our study provides new and confirms previously suggested molecular biomarkers for age estimation from blood. Moreover, our comparative study design revealed that DNA methylation markers are superior for this purpose over other types of molecular biomarkers tested. While the new and some previous findings are highly promising, before molecular age estimation can eventually meet forensic practice, the proposed biomarkers should be tested further in larger sets of blood samples from both healthy and unhealthy individuals, and markers and genotyping methods shall be validated to meet forensic standards.
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8
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A novel strategy for forensic age prediction by DNA methylation and support vector regression model. Sci Rep 2015; 5:17788. [PMID: 26635134 PMCID: PMC4669521 DOI: 10.1038/srep17788] [Citation(s) in RCA: 91] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 11/05/2015] [Indexed: 11/09/2022] Open
Abstract
High deviations resulting from prediction model, gender and population difference have limited age estimation application of DNA methylation markers. Here we identified 2,957 novel age-associated DNA methylation sites (P < 0.01 and R(2) > 0.5) in blood of eight pairs of Chinese Han female monozygotic twins. Among them, nine novel sites (false discovery rate < 0.01), along with three other reported sites, were further validated in 49 unrelated female volunteers with ages of 20-80 years by Sequenom Massarray. A total of 95 CpGs were covered in the PCR products and 11 of them were built the age prediction models. After comparing four different models including, multivariate linear regression, multivariate nonlinear regression, back propagation neural network and support vector regression, SVR was identified as the most robust model with the least mean absolute deviation from real chronological age (2.8 years) and an average accuracy of 4.7 years predicted by only six loci from the 11 loci, as well as an less cross-validated error compared with linear regression model. Our novel strategy provides an accurate measurement that is highly useful in estimating the individual age in forensic practice as well as in tracking the aging process in other related applications.
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9
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Molecular approaches for forensic cell type identification: On mRNA, miRNA, DNA methylation and microbial markers. Forensic Sci Int Genet 2015; 18:21-32. [DOI: 10.1016/j.fsigen.2014.11.015] [Citation(s) in RCA: 113] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2014] [Revised: 11/15/2014] [Accepted: 11/17/2014] [Indexed: 02/06/2023]
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10
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Majem B, Rigau M, Reventós J, Wong DT. Non-coding RNAs in saliva: emerging biomarkers for molecular diagnostics. Int J Mol Sci 2015; 16:8676-98. [PMID: 25898412 PMCID: PMC4425103 DOI: 10.3390/ijms16048676] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2015] [Revised: 04/02/2015] [Accepted: 04/08/2015] [Indexed: 01/05/2023] Open
Abstract
Saliva is a complex body fluid that comprises secretions from the major and minor salivary glands, which are extensively supplied by blood. Therefore, molecules such as proteins, DNA, RNA, etc., present in plasma could be also present in saliva. Many studies have reported that saliva body fluid can be useful for discriminating several oral diseases, but also systemic diseases including cancer. Most of these studies revealed messenger RNA (mRNA) and proteomic biomarker signatures rather than specific non-coding RNA (ncRNA) profiles. NcRNAs are emerging as new regulators of diverse biological functions, playing an important role in oncogenesis and tumor progression. Indeed, the small size of these molecules makes them very stable in different body fluids and not as susceptible as mRNAs to degradation by ribonucleases (RNases). Therefore, the development of a non-invasive salivary test, based on ncRNAs profiles, could have a significant applicability to clinical practice, not only by reducing the cost of the health system, but also by benefitting the patient. Here, we summarize the current status and clinical implications of the ncRNAs present in human saliva as a source of biological information.
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Affiliation(s)
- Blanca Majem
- Research Unit in Biomedicine and Translational Oncology, Lab 209, Collserola Building, Vall Hebron Research Institute (VHIR) and University Hospital, Pg. Vall Hebron 119-129, 08035 Barcelona, Spain.
| | - Marina Rigau
- Research Unit in Biomedicine and Translational Oncology, Lab 209, Collserola Building, Vall Hebron Research Institute (VHIR) and University Hospital, Pg. Vall Hebron 119-129, 08035 Barcelona, Spain.
| | - Jaume Reventós
- Research Unit in Biomedicine and Translational Oncology, Lab 209, Collserola Building, Vall Hebron Research Institute (VHIR) and University Hospital, Pg. Vall Hebron 119-129, 08035 Barcelona, Spain.
- IDIBELL-Bellvitge Biomedical Research Institute & Universitat Internacional de Catalunya, 08908 Barcelona, Spain.
| | - David T Wong
- Center for Oral/Head & Neck Oncology Research, University of California, Los Angeles, CA 90095, USA.
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11
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Exploring the utility of genetic markers for predicting biological age. Leg Med (Tokyo) 2012; 14:279-85. [PMID: 22770678 DOI: 10.1016/j.legalmed.2012.05.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2012] [Accepted: 05/31/2012] [Indexed: 12/28/2022]
Abstract
DNA evidence can be analyzed for genetic markers to determine phenotypes such as hair and eye color, ancestry, and even age estimation. Currently, telomere length is the only genetic biomarker that has been correlated to cell replication and replicative cell senescence--both strong indicators of tissue aging in humans. Unfortunately, while many studies have found a strong correlation between telomere length and age, many data sets show extreme variability, technical assay malfunction, inadequate evaluation of other variables that can impact telomere, altogether conflicting results, or insignificant correlations due to low sample size. Other, non-telomere based methods are problematic, as they often have only the ability to identify newborns or are only viable for specific tissue or cell types, and for most, the effects of outside variables have not been fully evaluated. Thus, telomeres remain the most promising biomarker for age estimation; mechanisms for telomere repeat attrition over time have been well documented. Unfortunately, assays currently used determine mean telomere length of a sample, are not precise or reproducible. New techniques should be robust enough to determine age across a broad spectrum of age ranges, and the effect of other variables (gender, race, disease, etc.), must be explored.
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12
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Hanson E, Albornoz A, Ballantyne J. Validation of the hemoglobin (Hb) hypsochromic shift assay for determination of the time since deposition (TSD) of dried bloodstains. FORENSIC SCIENCE INTERNATIONAL GENETICS SUPPLEMENT SERIES 2011. [DOI: 10.1016/j.fsigss.2011.09.016] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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13
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Hanson EK, Ballantyne J. A blue spectral shift of the hemoglobin soret band correlates with the age (time since deposition) of dried bloodstains. PLoS One 2010; 5:e12830. [PMID: 20877468 PMCID: PMC2942901 DOI: 10.1371/journal.pone.0012830] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2010] [Accepted: 08/20/2010] [Indexed: 02/05/2023] Open
Abstract
The ability to determine the time since deposition of a bloodstain found at a crime scene could prove invaluable to law enforcement investigators, defining the time frame in which the individual depositing the evidence was present. Although various methods of accomplishing this have been proposed, none has gained widespread use due to poor time resolution and weak age correlation. We have developed a method for the estimation of the time since deposition (TSD) of dried bloodstains using UV-VIS spectrophotometric analysis of hemoglobin (Hb) that is based upon its characteristic oxidation chemistry. A detailed study of the Hb Soret band (λmax=412 nm) in aged bloodstains revealed a blue shift (shift to shorter wavelength) as the age of the stain increases. The extent of this shift permits, for the first time, a distinction to be made between bloodstains that were deposited minutes, hours, days and weeks prior to recovery and analysis. The extent of the blue shift was found to be a function of ambient relative humidity and temperature. The method is extremely sensitive, requiring as little as a 1 µl dried bloodstain for analysis. We demonstrate that it might be possible to perform TSD measurements at the crime scene using a portable low-sample-volume spectrophotometer.
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Affiliation(s)
- Erin K. Hanson
- National Center for Forensic Science, Orlando, Florida, United States of America
| | - Jack Ballantyne
- National Center for Forensic Science, Orlando, Florida, United States of America
- Department of Chemistry, University of Central Florida, Orlando, Florida, United States of America
- * E-mail:
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14
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Anderson SE, Hobbs GR, Bishop CP. Multivariate analysis for estimating the age of a bloodstain. J Forensic Sci 2010; 56:186-93. [PMID: 21198594 DOI: 10.1111/j.1556-4029.2010.01551.x] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Our objective is to provide crime laboratories with a technique for estimating the age of a bloodstain. Toward that goal, we have used multiplexed, real-time RT-PCR (or qPCR) to determine the relative stability of different-sized segments of the same RNA species as well as differences in stability between two different RNAs' change over time in bloodstains. Our results indicate that a multivariate analysis of the changing ratio of the different RNA segments can be used to differentiate between samples of different ages in the defined population. Bloodstains from 29 of 30 donors could be partitioned into different ages using this technique. Although further improvements will be required before this approach can be implemented in crime laboratories, the multivariate analysis holds promise of providing a reliable approach for temporally linking a bloodstain to the commission of a crime or excluding a bloodstain as being irrelevant to the case in question.
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Affiliation(s)
- Stacey E Anderson
- Department of Biology, West Virginia University, PO Box 6057, Morgantown, WV 26506-6057, USA
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15
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Hagan KA, Meier WL, Ferrance JP, Landers JP. Chitosan-Coated Silica as a Solid Phase for RNA Purification in a Microfluidic Device. Anal Chem 2009; 81:5249-56. [DOI: 10.1021/ac900820z] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kristin A. Hagan
- Departments of Chemistry and Mechanical Engineering, University of Virginia, Charlottesville, Virginia 22904, and Department of Pathology, University of Virginia Health Science Center, Charlottesville, Virginia 22908
| | - Whitney L. Meier
- Departments of Chemistry and Mechanical Engineering, University of Virginia, Charlottesville, Virginia 22904, and Department of Pathology, University of Virginia Health Science Center, Charlottesville, Virginia 22908
| | - Jerome P. Ferrance
- Departments of Chemistry and Mechanical Engineering, University of Virginia, Charlottesville, Virginia 22904, and Department of Pathology, University of Virginia Health Science Center, Charlottesville, Virginia 22908
| | - James P. Landers
- Departments of Chemistry and Mechanical Engineering, University of Virginia, Charlottesville, Virginia 22904, and Department of Pathology, University of Virginia Health Science Center, Charlottesville, Virginia 22908
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16
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Alvarez M, Ballantyne J. Identification of four novel developmentally regulated gamma hemoglobin mRNA isoforms. Exp Hematol 2009; 37:285-93. [DOI: 10.1016/j.exphem.2008.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2008] [Revised: 10/01/2008] [Accepted: 10/09/2008] [Indexed: 10/21/2022]
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17
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Juusola J, Ballantyne J. mRNA profiling for body fluid identification by multiplex quantitative RT-PCR. J Forensic Sci 2007; 52:1252-62. [PMID: 17868268 DOI: 10.1111/j.1556-4029.2007.00550.x] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
An alternative approach to conventional protein-based body fluid identification is gene expression profiling analysis. In the present work, we report the development of sensitive and robust multiplex quantitative reverse transcriptase-PCR assays for the identification of blood, saliva, semen, and menstrual blood. Each body fluid assay comprises a triplex system that detects transcripts from two body fluid-specific genes and a housekeeping gene GAPDH. The body fluid-specific genes include erythroid delta-aminolevulinate synthase (ALAS2) and beta-spectrin (SPTB) for blood, statherin (STATH) and histatin 3 (HTN3) for saliva, protamine 1 (PRM1) and protamine 2 (PRM2) for semen, and matrix metalloproteinase 7 (MMP7) and matrix metalloproteinase 10 (MMP10) for menstrual blood. Normalization of both body fluid-specific genes to the housekeeping gene by means of appropriate cycle threshold metrics ensures the high specificity of each assay for its cognate body fluid.
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Affiliation(s)
- Jane Juusola
- Graduate Program in Biomolecular Sciences, University of Central Florida, Orlando, FL, 32816-2366, USA
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18
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19
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Affiliation(s)
- T A Brettell
- Department of Chemical and Physical Sciences, Cedar Crest College, 100 College Drive, Allentown, Pennsylvania 18104-6196, USA
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