Metabolomic Assessment of Embryo Viability

Seminars in Reproductive Medicine

Volumn 32, Issue 2, 2014, Pages 141-151

  Uyar, Asli ^a,b   Seli, Emre ^a  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b OKAN UNIVERSITY   (Turkey)

Author keywords

embryo assessment; metabolomics

Indexed keywords

AMINO ACID;

ANALYTIC METHOD; ARTICLE; BIOINFORMATICS; CARBOHYDRATE METABOLISM; CULTURE MEDIUM; DATA ANALYSIS; EMBRYO DEVELOPMENT; EMBRYO TRANSFER; FERTILIZATION IN VITRO; HUMAN; MASS SPECTROMETRY; METABOLITE; METABOLOMICS; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PREGNANCY; PREGNANCY RATE; PREIMPLANTATION EMBRYO; SPECTROSCOPY; VIBRATIONAL SPECTROSCOPY; BLASTOCYST; CELL SURVIVAL; CYTOLOGY; FEMALE; METABOLISM; METABOLOME; METHODOLOGY; NIDATION; PRENATAL DIAGNOSIS; REVIEW; STATISTICS;

BLASTOCYST; CELL SURVIVAL; EMBRYO IMPLANTATION; FEMALE; HUMANS; METABOLOME; METABOLOMICS; PREGNANCY; PREIMPLANTATION DIAGNOSIS;

EID: 84907623415     PISSN: 15268004     EISSN: 15264564     Source Type: Journal    
DOI: 10.1055/s-0033-1363556     Document Type: Article

References (67)

1. Center for Disease Control and Prevention Web site. Assisted Reproductive Technology (ART). Available at: http://www.cdc.gov/art/index.htm. Accessed April 10, 2013
2. Ata B., Seli E. Economics of assisted reproductive technologies. Curr Opin Obstet Gynecol: 2010; 22 3 183 188
3. Bromer J. G., Seli E. Assessment of embryo viability in assisted reproductive technology: shortcomings of current approaches and the emerging role of metabolomics. Curr Opin Obstet Gynecol: 2008; 20 3 234 241
4. Sakkas D., Gardner D. K. Noninvasive methods to assess embryo quality. Curr Opin Obstet Gynecol: 2005; 17 3 283 288
5. Wong C. C., Loewke K. E., Bossert N. L., et al. Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nat Biotechnol: 2010; 28 10 1115 1121
6. Meseguer M., Rubio I., Cruz M., Basile N., Marcos J., Requena A. Embryo incubation and selection in a time-lapse monitoring system improves pregnancy outcome compared with a standard incubator: a retrospective cohort study. Fertil Steril: 2012; 98 6 1481 1489, e10
7. Uyar A., Seli E. Embryo assessment strategies and their validation for clinical use: a critical analysis of methodology. Curr Opin Obstet Gynecol: 2012; 24 3 141 150
8. Seli E., Robert C., Sirard M. A. OMICS in assisted reproduction: possibilities and pitfalls. Mol Hum Reprod: 2010; 16 8 513 530
9. Checa M. A., Alonso-Coello P., Solà I., Robles A., Carreras R., Balasch J. IVF/ICSI with or without preimplantation genetic screening for aneuploidy in couples without genetic disorders: a systematic review and meta-analysis. J Assist Reprod Genet: 2009; 26 5 273 283
10. Practice Committee of Society for Assisted Reproductive Technology; Practice Committee of American Society for Reproductive Medicine Preimplantation genetic testing: a Practice Committee opinion. Fertil Steril: 2008; 90 (5, Suppl): S136 S143
11. Harper J., Coonen E., De Rycke M., et al. What next for preimplantation genetic screening (PGS)? A position statement from the ESHRE PGD Consortium Steering Committee. Hum Reprod: 2010; 25 4 821 823
12. Sher G., Keskintepe L., Keskintepe M., Maassarani G., Tortoriello D., Brody S. Genetic analysis of human embryos by metaphase comparative genomic hybridization (mCGH) improves efficiency of IVF by increasing embryo implantation rate and reducing multiple pregnancies and spontaneous miscarriages. Fertil Steril: 2009; 92 6 1886 1894
13. Schoolcraft W. B., Treff N. R., Stevens J. M., Ferry K., Katz-Jaffe M., Scott R. T. Jr. Live birth outcome with trophectoderm biopsy, blastocyst vitrification, and single-nucleotide polymorphism microarray-based comprehensive chromosome screening in infertile patients. Fertil Steril: 2011; 96 3 638 640
14. Uyar A., Torrealday S., Seli E. Cumulus and granulosa cell markers of oocyte and embryo quality. Fertil Steril: 2013; 99 4 979 997
15. Katz-Jaffe M. G., Schoolcraft W. B., Gardner D. K. Analysis of protein expression (secretome) by human and mouse preimplantation embryos. Fertil Steril: 2006; 86 3 678 685
16. Domínguez F., Gadea B., Esteban F. J., Horcajadas J. A., Pellicer A., Simón C. Comparative protein-profile analysis of implanted versus non-implanted human blastocysts. Hum Reprod: 2008; 23 9 1993 2000
17. Dominguez F., Gadea B., Mercader A., Esteban F. J., Pellicer A., Simón C. Embryologic outcome and secretome profile of implanted blastocysts obtained after coculture in human endometrial epithelial cells versus the sequential system. Fertil Steril: 2010; 93 3 774 782, e1
18. Seli E., Sakkas D., Scott R., Kwok S. C., Rosendahl S. M., Burns D. H. Noninvasive metabolomic profiling of embryo culture media using Raman and near-infrared spectroscopy correlates with reproductive potential of embryos in women undergoing in vitro fertilization. Fertil Steril: 2007; 88 5 1350 1357
19. Scott R., Seli E., Miller K., Sakkas D., Scott K., Burns D. H. Noninvasive metabolomic profiling of human embryo culture media using Raman spectroscopy predicts embryonic reproductive potential: a prospective blinded pilot study. Fertil Steril: 2008; 90 1 77 83
20. Vergouw C. G., Botros L. L., Roos P., et al. Metabolomic profiling by near-infrared spectroscopy as a tool to assess embryo viability: a novel, non-invasive method for embryo selection. Hum Reprod: 2008; 23 7 1499 1504
21. Seli E., Vergouw C. G., Morita H., et al. Noninvasive metabolomic profiling as an adjunct to morphology for noninvasive embryo assessment in women undergoing single embryo transfer. Fertil Steril: 2010; 94 2 535 542
22. Hardarson T., Ahlström A., Rogberg L., et al. Non-invasive metabolomic profiling of Day 2 and 5 embryo culture medium: a prospective randomized trial. Hum Reprod: 2012; 27 1 89 96
23. Vergouw C. G., Kieslinger D. C., Kostelijk E. H., et al. Day 3 embryo selection by metabolomic profiling of culture medium with near-infrared spectroscopy as an adjunct to morphology: a randomized controlled trial. Hum Reprod: 2012; 27 8 2304 2311
24. Guzeloglu-Kayisli O., Lalioti M. D., Aydiner F., et al. Embryonic poly(A)-binding protein (EPAB) is required for oocyte maturation and female fertility in mice. Biochem J: 2012; 446 1 47 58
25. Tay J., Richter J. D. Germ cell differentiation and synaptonemal complex formation are disrupted in CPEB knockout mice. Dev Cell: 2001; 1 2 201 213
26. Ruggiu M., Speed R., Taggart M., et al. The mouse Dazla gene encodes a cytoplasmic protein essential for gametogenesis. Nature: 1997; 389 6646 73 77
27. Lin Y., Page D. C. Dazl deficiency leads to embryonic arrest of germ cell development in XY C57BL/6 mice. Dev Biol: 2005; 288 2 309 316
28. Racki W. J., Richter J. D. CPEB controls oocyte growth and follicle development in the mouse. Development: 2006; 133 22 4527 4537
29. Chen J., Melton C., Suh N., et al. Genome-wide analysis of translation reveals a critical role for deleted in azoospermia-like (Dazl) at the oocyte-to-zygote transition. Genes Dev: 2011; 25 7 755 766
30. Clegg K. B., Pikó L. RNA synthesis and cytoplasmic polyadenylation in the one-cell mouse embryo. Nature: 1982; 295 5847 343 344
31. Flach G., Johnson M. H., Braude P. R., Taylor R. A., Bolton V. N. The transition from maternal to embryonic control in the 2-cell mouse embryo. EMBO J: 1982; 1 6 681 686
32. Braude P., Bolton V., Moore S. Human gene expression first occurs between the four- and eight-cell stages of preimplantation development. Nature: 1988; 332 6163 459 461
33. Biggers J. D., Whittingham D. G., Donahue R. P. The pattern of energy metabolism in the mouse oöcyte and zygote. Proc Natl Acad Sci U S A: 1967; 58 2 560 567
34. Gardner D. K., Leese H. J. The role of glucose and pyruvate transport in regulating nutrient utilization by preimplantation mouse embryos. Development: 1988; 104 3 423 429
35. Gott A. L., Hardy K., Winston R. M., Leese H. J. Non-invasive measurement of pyruvate and glucose uptake and lactate production by single human preimplantation embryos. Hum Reprod: 1990; 5 1 104 108
36. Conaghan J., Hardy K., Handyside A. H., Winston R. M., Leese H. J. Selection criteria for human embryo transfer: a comparison of pyruvate uptake and morphology. J Assist Reprod Genet: 1993; 10 1 21 30
37. Conaghan J., Handyside A. H., Winston R. M., Leese H. J. Effects of pyruvate and glucose on the development of human preimplantation embryos in vitro. J Reprod Fertil: 1993; 99 1 87 95
38. Gardner D. K., Lane M., Stevens J., Schoolcraft W. B. Noninvasive assessment of human embryo nutrient consumption as a measure of developmental potential. Fertil Steril: 2001; 76 6 1175 1180
39. Leese H. J., Barton A. M. Pyruvate and glucose uptake by mouse ova and preimplantation embryos. J Reprod Fertil: 1984; 72 1 9 13
40. Brison D. R., Leese H. J. Energy metabolism in late preimplantation rat embryos. J Reprod Fertil: 1991; 93 1 245 251
41. Botros L., Sakkas D., Seli E. Metabolomics and its application for non-invasive embryo assessment in IVF. Mol Hum Reprod: 2008; 14 12 679 690
42. Hardy K., Hooper M. A., Handyside A. H., Rutherford A. J., Winston R. M., Leese H. J. Non-invasive measurement of glucose and pyruvate uptake by individual human oocytes and preimplantation embryos. Hum Reprod: 1989; 4 2 188 191
43. Turner K., Martin K. L., Woodward B. J., Lenton E. A., Leese H. J. Comparison of pyruvate uptake by embryos derived from conception and non-conception natural cycles. Hum Reprod: 1994; 9 12 2362 2366
44. Devreker F., Hardy K., Van den Bergh M., Vannin A. S., Emiliani S., Englert Y. Amino acids promote human blastocyst development in vitro. Hum Reprod: 2001; 16 4 749 756
45. Lane M., Gardner D. K. Nonessential amino acids and glutamine decrease the time of the first three cleavage divisions and increase compaction of mouse zygotes in vitro. J Assist Reprod Genet: 1997; 14 7 398 403
46. Houghton F. D., Hawkhead J. A., Humpherson P. G., et al. Non-invasive amino acid turnover predicts human embryo developmental capacity. Hum Reprod: 2002; 17 4 999 1005
47. Leese H. J., Baumann C. G., Brison D. R., McEvoy T. G., Sturmey R. G. Metabolism of the viable mammalian embryo: quietness revisited. Mol Hum Reprod: 2008; 14 12 667 672
48. Brison D. R., Houghton F. D., Falconer D., et al. Identification of viable embryos in IVF by non-invasive measurement of amino acid turnover. Hum Reprod: 2004; 19 10 2319 2324
49. Seli E., Botros L., Sakkas D., Burns D. H. Noninvasive metabolomic profiling of embryo culture media using proton nuclear magnetic resonance correlates with reproductive potential of embryos in women undergoing in vitro fertilization. Fertil Steril: 2008; 90 6 2183 2189
50. Nicholson J. K., O'Flynn M. P., Sadler P. J., Macleod A. F., Juul S. M., Sönksen P. H. Proton-nuclear-magnetic-resonance studies of serum, plasma and urine from fasting normal and diabetic subjects. Biochem J: 1984; 217 2 365 375
51. Nicholson J. K., Connelly J., Lindon J. C., Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov: 2002; 1 2 153 161
52. Dunn W. B., Ellis D. I. Metabolomics: Current analytical platforms and methodologies. Trends Analyt Chem: 2005; 24 4 285 294
53. Garcia A., Barbas C. Gas chromatography-mass spectrometry (GC-MS)-based metabolomics. Methods Mol Biol: 2011; 708 191 204
54. Zhou B., Xiao J. F., Tuli L., Ressom H. W. LC-MS-based metabolomics. Mol Biosyst: 2012; 8 2 470 481
55. Soga T. Capillary electrophoresis-mass spectrometry for metabolomics. Methods Mol Biol: 2007; 358 129 137
56. Monton M. R., Soga T. Metabolome analysis by capillary electrophoresis-mass spectrometry. J Chromatogr A: 2007; 1168 1-2 237 246, discussion 236
57. Büscher J. M., Czernik D., Ewald J. C., Sauer U., Zamboni N. Cross-platform comparison of methods for quantitative metabolomics of primary metabolism. Anal Chem: 2009; 81 6 2135 2143
58. Ellis D. I., Goodacre R. Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy. Analyst (Lond): 2006; 131 8 875 885
59. Bajad S., Shulaev V. LC-MS-based metabolomics. Methods Mol Biol: 2011; 708 213 228
60. Shulaev V. Metabolomics technology and bioinformatics. Brief Bioinform: 2006; 7 2 128 139
61. Alpaydin E. Introduction to Machine Learning. 2nd ed. Cambridge, MA MIT Press: 2010
62. Kim J. H. Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap. Comput Stat Data Anal: 2009; 53 11 3735 3745
63. Mehrotra B., Mendes P. Bioinformatics approaches to integrate metabolomics and other systems biology data. In: Saito K., Dixon R. A., Willmitzer L., eds. Plant Metabolomics. Vol 57. Berlin, Heidelberg Springer-Verlag: 2006; 105 115
64. Ahlström A., Wikland M., Rogberg L., Barnett J. S., Tucker M., Hardarson T. Cross-validation and predictive value of near-infrared spectroscopy algorithms for day-5 blastocyst transfer. Reprod Biomed Online: 2011; Jan 24
65. Seli E., Bruce C., Botros L., et al. Receiver operating characteristic (ROC) analysis of day 5 morphology grading and metabolomic Viability Score on predicting implantation outcome. J Assist Reprod Genet: 2011; 28 2 137 144
66. Katz-Jaffe M. G., Gardner D. K., Schoolcraft W. B. Proteomic analysis of individual human embryos to identify novel biomarkers of development and viability. Fertil Steril: 2006; 85 1 101 107
67. Sfontouris I. A., Lainas G. T., Sakkas D., et al. Assessment of embryo selection using non-invasive metabolomic analysis as an adjunct to morphology indicates improvement in implantation and fetal cardiac activity rates. Hum Reprod: 2011; 26 01 86