Skip to main content

Advertisement

SpringerLink
Log in

A stepwise strategy to distinguish menstrual blood from peripheral blood by Fisher’s discriminant function

  • Original Article
  • Published:
International Journal of Legal Medicine Aims and scope Submit manuscript

A Correction to this article was published on 07 March 2022

This article has been updated

Abstract

Blood samples are the most common and important biological samples found at crime scenes, and distinguishing peripheral blood and menstrual blood samples is crucial for solving criminal cases. MicroRNAs (miRNAs) are important molecules with strong tissue specificity that can be used in forensic fields to identify the tissue properties of body fluid samples. In this study, the relative expression levels of four different miRNAs (miR-451, miR-205, miR-214 and miR-203) were analysed by real-time PCR, with 200 samples from 5 different body fluids, including two kinds of blood samples (peripheral blood and menstrual blood) and three kinds of non-blood samples (saliva, semen and vaginal secretion). Then, a strategy for identifying menstrual and peripheral blood based on Fisher’s discriminant function and the relative expression of multiple miRNAs was established. Two sets of functions were used: Z1 and Z2 were used to distinguish blood samples from non-blood samples, and Y1 and Y2 were used to distinguish peripheral blood from menstrual blood. A 100% accuracy rate was achieved when 50 test samples were used. Ten samples were used to test the sensitivity of the method, and 10 ng or more of total RNA from peripheral blood samples and 10 pg or more of total RNA from menstrual blood samples were sufficient for this method. The results provide a scientific reference to address the difficult forensic problem of distinguishing menstrual blood from peripheral blood.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Change history

References

  1. An JH, Shin KJ, Yang WI, Lee HY (2012) Body fluid identification in forensics. BMB Rep 45(10):545–553

    Article  CAS  Google Scholar 

  2. Li Z, Bai P, Peng D, Wang H, Guo Y, Jiang Y, He W, Tian H, Yang Y, Huang Y, Long B, Liang W, Zhang L (2017) Screening and confirmation of microRNA markers for distinguishing between menstrual and peripheral blood. Forensic Sci Int Genet 30:24–33

    Article  CAS  Google Scholar 

  3. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75(5):843–854

    Article  CAS  Google Scholar 

  4. Liang Y, Ridzon D, Wong L, Chen C (2007) Characterization of microRNA expression profiles in normal human tissues. BMC Genomics 8(1):166

    Article  Google Scholar 

  5. Silva SS, Lopes C, Teixeira AL, Carneiro de Sousa MJ, Medeiros R (2015) Forensic miRNA: potential biomarker for body fluids? Forensic Sci Int Genet 14:1–10

    Article  CAS  Google Scholar 

  6. Sauer E, Reinke AK, Courts C (2016) Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR. Forensic Sci Int Genet 22:89–99

    Article  CAS  Google Scholar 

  7. Wang Z, Luo H, Pan X, Liao M, Hou Y (2012) A model for data analysis of microRNA expression in forensic body fluid identification. Forensic Sci Int Genet 3:419–423

    Article  Google Scholar 

  8. Hanson EK, Mirza M, Rekab K, Ballantyne J (2014) The identification of menstrual blood in forensic samples by logistic regression modeling of miRNA expression. Electrophoresis 35:3087–3095

    Article  CAS  Google Scholar 

  9. van der Meer D, Uchimoto ML, Williams G (2013) Simultaneous Analysis of Micro-RNA and DNA for Determining the Body Fluid Origin of DNA Profiles. J Forensic Sci 58(4):967–971

  10. Wang Z, Zhang J, Wei W, Zhou D, Luo H, Chen X, Hou Y (2015) Identification of Saliva Using MicroRNA Biomarkers for Forensic Purpose. J Forensic Sci 60(3):702–706

  11. Li Y, Zhang J, Wei W, Wang Z, Prinz M, Hou Y (2014) A strategy for co-analysis of microRNAs and DNA. Forensic Sci Int Genet 12:24–29

  12. Williams G, L Uchimoto M, Coult N, World D, Beasley E, Avenell P (2013) Characterisation of body fluid specific miRNA markers by capillary electrophoresis. Forensic Science International: Genetics Supplement Series 4(1):e274–e275

  13. Tian H, Lv M, Li Z, Peng D, Tan Y, Wang H, Li Q, Li F, Liang W (2018) Semen-specific miRNAs: Suitable for the distinction of infertile semen in the body fluid identification? Forensic Sci Int Genet 33:161–167

  14. Hanson EK, Lubenow H, Ballantyne J (2009) Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs . Analytical Biochemistry 387:303–314

  15. Courts C, Madea B (2011) Specific Micro-RNA Signatures for the Detection of Saliva and Blood in Forensic Bodyfluid Identification . J Forensic Sci 56(6):1464–1469

  16. Grabmüller M, Madea B, Courts C (2015) Comparative evaluation of different extraction and quantification methods for forensic RNA analysis . Forensic Sci Int Genet 16:195–202

  17. Wang Z, Zhang J, Luo H, Ye Y, Yan J, Hou Y (2013) Screening and confirmation of microRNA markers for forensic body fluid identification. Forensic Sci Int Genet 7:116–123

    Article  CAS  Google Scholar 

  18. Li Z, Bai P, Peng D, Long B , Zhang L , Liang W (2015) Influences of different RT-qPCR methods on forensic body fluid identification by microRNA . Forensic Science International: Genetics Supplement Series 5: e295–e297

  19. Sirker M, Fimmers R, Schneider PM, Gomes I (2017) Evaluating the forensic application of 19 target microRNAs as biomarkers in body fluid and tissue identification . Forensic Sci Int Genet 27:41–49

  20. Mayes C, Seashols-Williams S, Hughes-Stamm S (2018) A capillary electrophoresis method for identifying forensically relevant body fluids using miRNAs . Leg Med (Tokyo) 30: 1–4

  21. O Leary KR, Glynn CL. Glynn (2018) Investigating the Isolation and Amplification of microRNAs for Forensic Body Fluid Identification . Microrna 7(3):187–194

  22. Masaki S, Ohtsuka R, Abe Y, Muta K, Umemura T (2007) Expression patterns of microRNAs 155 and 451 during normal human erythropoiesis . Biochem Biophys Res Commun 364(3): 509–514

  23. Sonkoly E, Wei T, Janson PC, Sääf A, Lundeberg L, Tengvall-Linder M, Norstedt G, Alenius H, Homey B, Scheynius A, Ståhle M, Pivarcsi A (2007) MicroRNAs: novel regulators involved in the pathogenesis of psoriasis? PLoS One 2(7):e610

  24. Qin AY, Zhang XW, Liu L, Yu JP, Li H, Wang SZ, Ren XB, Cao S (2013) MiR-205 in cancer: an angel or a devil . Eur J Cell Biol 92:54–60

  25. Qiang R, Wang F, Shi LY, Liu M, Chen S, Wan HY, Li YX, Li X, Gao SY, Sun BC, Tang H (2011) Plexin-B1 is a target of miR-214 in cervical cancer and promotes the growth and invasion of HeLa cells. Int J Biochem Cell Biol 43(4): 632–641

  26. Jakubowska J, Maciejewska A, Bielawski KP, Pawłowski R (2014) mRNA heptaplex protocol for distinguishing between menstrual and peripheral blood . Forensic Sci Int Genet 13:53–60

Download references

Acknowledgements

In addition, we want to thank Prof. Guo Xiangqian from Henan University for help with the sample collection, and we would also like to thank all the volunteers who contributed samples to this research.

Authors’ contributions statement

Conceptualization—Anquan Ji, Sun Qifan and Qinglan Kong.

Methodology—Qifan Sun, Hongxia He, Yixia Zhao, and Sheng Hu.

Software—Hongxia He and Li Jiang.

Formal analysis—Hongxia He, Na Han and Qifan Sun.

Statistical modelling—Hongxia He and Qinglan Kong.

Investigation—Qifan Sun, Anquan Ji and Sheng Hu.

Resources—Anquan Ji, Qifan Sun. Jian Ye and Yao Liu.

Data curation—Qifan Sun, Yixia Zhao, and Anquan Ji.

Writing and original draft—Hongxia He, and Qifan Sun.

Writing and review and editing—Hongxia He, Na Han and Qifan Sun.

Project administration—Qifan Sun, Jian Ye and Yao Liu.

Funding acquisition—Qifan Sun and Anquan Ji.

Funding

This work was supported by grants from the National Key R&D Programme (No. 2017YFC0803503) and the Basic Research Project from the Institute of Forensic Science, Ministry of Public Security, China (No. 2019JB010).

Author information

Author notes

  1. Hongxia He and Anquan Ji contributed equally to this work.

Authors and Affiliations

  1. MPS’s Key Laboratory of Forensic Genetics, National Engineering Laboratory for Crime Scene Evidence Investigation and Examination, Institute of Forensic Science, Ministry of Public Security (MPS), Beijing, 100038, China

    Hongxia He, Anquan Ji, Yixia Zhao, Sheng Hu, Li Jiang, Jian Ye, Yao Liu & Qifan Sun

  2. Faculty of Forensic Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, People’s Republic of China

    Hongxia He & Yao Liu

  3. Chinese Center For Disease Control And Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, 102206, China

    Na Han

  4. Faculty of Mathematics and Statistics, Zaozhuang University, Zaozhuang, 277160, Shandong, People’s Republic of China

    Qinglan Kong

Authors
  1. Hongxia He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anquan Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yixia Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Na Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sheng Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qinglan Kong
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Li Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jian Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Qifan Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Yao Liu or Qifan Sun.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(XLSX 105 kb)

ESM 2

(XLSX 24 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, H., Ji, A., Zhao, Y. et al. A stepwise strategy to distinguish menstrual blood from peripheral blood by Fisher’s discriminant function. Int J Legal Med 134, 845–851 (2020). https://doi.org/10.1007/s00414-019-02196-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00414-019-02196-w

Keywords

Search

Navigation