Volume 19, Issue 2 (February 2021)                   IJRM 2021, 19(2): 121-128 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Moazeni Pourasil R S, Gilany K. Fast diagnosis of men’s fertility using Raman spectroscopy combined with chemometric methods: An experimental study. IJRM. 2021; 19 (2) :121-128
URL: http://journals.ssu.ac.ir/ijrmnew/article-1-1287-en.html
1- Department of Analytical Chemistry, Faculty of Chemistry, Kharazmi University, Tehran, Iran.
2- Reproductive Biotechnology Research Center, Avicenna Research Institute, ACECER, Tehran, Iran. Integrative Oncology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran. , k.gilany@avicenna.ac.ir & k.gilany@ari.ir
Abstract:   (441 Views)
Background: Idiopathic infertile men suffer from unexplained male infertility; they are infertile despite having a normal semen analysis, a normal history, and physical examination, and when female infertility factor has been ruled out.
Objective: The present study aimed to develop a metabolic fingerprinting methodology using Raman spectroscopy combined with Chemometrics to detect idiopathic infertile men vs. fertile ones by seminal plasma.
Materials and Methods: In this experimental study, the seminal plasma of 26 men including 13 fertile and 13 with unexplained infertility who reffered to, Avicenna Infertility Clinic, 2018, Tehran, Iran, have been investigated. The seminal metabolomic fingerprinting was evaluated using Raman spectrometer from 100 to 4250 cm-1. The principal component analysis and discriminate analysis methods were used.
Results: The total of 26 samples were divided into 20 training and 6 test sets. The Principal component analysis score plot of the training set showed that the data were perfectly divided into two sides of the plot, which statistically approves the direct effect of semen metabolome changes on the Raman spectra. A classification model was constructed by linear discriminant analysis using the training set and evaluated by the test group which resulted in completely correct classification. While three of the six test samples appeared in the fertile group, the rest appeared in the infertile as expected.
Conclusion: Metabolic fingerprinting of seminal plasma using Raman spectroscopy combined with chemometric classification methods accurately discriminated between the idiopathic infertile men and the fertile ones and predicted their fertility type.
Full-Text [PDF 1278 kb]   (119 Downloads) |   |   Full-Text (HTML)  (42 Views)  
Type of Study: Review Article | Subject: Fertility & Infertility

References
1. Hamada A, Esteves SC, Agarwal A. Unexplained male infertility: Potential causes and management. Hum Androl 2011; 1: 2-16. [DOI:10.1097/01.XHA.0000397686.82729.09]
2. Esteves SC, Miyaoka R, Agarwal A. An update on the clinical assessment of the infertile male. Clinics 2011; 66: 691-700. [DOI:10.1590/S1807-59322011000400026] [PMID] [PMCID]
3. Cooper TG, Noonan E, von Eckardstein S, Auger J, Baker HWG, Behre HM, et al. World Health Organization reference values for human semen characteristics. Hum Reprod Update 2010; 16: 231-245. https://doi.org/10.1093/humupd/dmp048 [DOI:10.1093/humupd/dmq020] [PMID]
4. Esteves SC. A clinical appraisal of the genetic basis in unexplained male infertility. J Hum Reprod Sci 2013; 6: 176-182. [DOI:10.4103/0974-1208.121419] [PMID] [PMCID]
5. Griffin JL, Vidal-Puig A. Current challenges in metabolomics for diabetes research: A vital functional genomic tool or just a ploy for gaining funding? Physiol Genomics 2008; 34: 1-5. [DOI:10.1152/physiolgenomics.00009.2008] [PMID]
6. Weiss RH, Kim K. Metabolomics in the study of kidney diseases. Nat Rev Nephrol 2012; 8: 22-33. [DOI:10.1038/nrneph.2011.152] [PMID]
7. Ellis DI, Dunn WB, Griffin JL, Allwood JW, Goodacre R. Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics 2007; 8: 1243-1266. [DOI:10.2217/14622416.8.9.1243] [PMID]
8. Botros L, Sakkas D, Seli E. Metabolomics and its application for non-invasive embryo assessment in IVF. Mol Hum Reprod 2008; 14: 679-690. [DOI:10.1093/molehr/gan066] [PMID] [PMCID]
9. Dunn WB, Bailey NJ, Johnson HE. Measuring the metabolome: Current analytical technologies. Analyst 2005; 130: 606-625. [DOI:10.1039/b418288j] [PMID]
10. Gilany K, Moazeni-Pourasil RS, Sadeghi MR. Fourier transform infrared spectroscopy: A potential technique for noninvasive detection of spermatogenesis. Avicenna J Med Biotechnol 2014; 6: 47-52.
11. Zhao K, Zhang J, Xu Zh, Xu Y, Xu A, Chen W, et al. Metabolomic profiling of human spermatozoa in idiopathic asthenozoospermia patients using gas chromatography-mass spectrometry. BioMed Res Int 2018; 2018: 8327506. 1-9. [DOI:10.1155/2018/8327506] [PMID] [PMCID]
12. Liu Y, Zhu Y, Li Zh. Application of Raman spectroscopy in andrology: Non-invasive analysis of tissue and single cell. Transl Androl Urol 2014; 3: 125-133.
13. Gilany K, Moazeni-Pourasil RS, Jafarzadeh N, Savadi-Shiraz E. Metabolomics fingerprinting of the human seminal plasma of asthenozoospermic patients. Mol Reprod Dev 2014; 81: 84-86. [DOI:10.1002/mrd.22284] [PMID]
14. Thielemans A, Massart DL. The use of principal component analysis as a display method in the interpretation of analytical chemical, biochemical, environmental, and epidemiological data. Chimia 1985; 39: 236-242.
15. Gemperline P. Practical guide to Chemometrics, 2nd. Boca Raton, USA: CRC Press; 2006. [DOI:10.1201/9781420018301]
16. Smilde A, Bro R, Geladi P. Multi-way analysis with applications in the chemical sciences. Hoboken, USA: John Wiley & Sons; 2004. [DOI:10.1002/0470012110]
17. Brereton RG. Chemometrics for pattern recognition. Hoboken, USA: John Wiley & Sons; 2009. [DOI:10.1002/9780470746462]
18. Andersen CM, Bro R. Variable selection in regression-a tutorial. J Chemometrics 2010; 24: 728-737. [DOI:10.1002/cem.1360]
19. S'anchez FC, Toft J, van den Bogaert B, Massart DL. Orthogonal projection approach applied to peak purity assessment. Anal Chem 1996; 68: 79-85. [DOI:10.1021/ac950496g] [PMID]
20. Deepinder F, Chowdary HT, Agarwal A. Role of metabolomic analysis of biomarkers in the management of male infertility. Exp Rev Mol Diagn 2007: 7: 351-358. [DOI:10.1586/14737159.7.4.351] [PMID]
21. Liu Y, Zhu Y, Di L, Osterberg ECh, Liu F, He L, et al. Raman spectroscopy as an ex vivo noninvasive approach to distinguish complete and incomplete spermatogenesis within human seminiferous tubules. Fertil Steril 2014; 102: 54-60. [DOI:10.1016/j.fertnstert.2014.03.035] [PMID]

Send email to the article author


© 2021 CC BY-NC 4.0 | International Journal of Reproductive BioMedicine

Designed & Developed by : Yektaweb