Research Article

The importance of gestational age in first trimester, maternal urine MALDI-Tof MS screening tests for Down Syndrome

Ray K Iles*, Nicolaides K, Pais RJ, Zmuidinaite R, Keshavarz S, Poon LCY and Butler SA

Published: 12/31/2019 | Volume 3 - Issue 1 | Pages: 010-017

Abstract

Background: The proposal that MALDI-ToF mass spectrometry could be used as a direct, rapid and affordable diagnostic tool in clinical laboratory medicine has moved from a theoretical possibility to a reality for Microbiology. Several studies have proposed the application of this technology in obstetric and gynaecological evaluation of patients. In particular, we have proposed that the adoption of MALDI-ToF mass spectrometry in examination of maternal pregnancy urine samples for the detection of Downs syndrome.

Methods: A retrospective collection of 20 Down Syndrome and 100 non-aneuploid pregnancy urines at 12 to 14 weeks gestation, collected in 2007-2008 from high risk pregnancy cohorts, were examined by MALDI-ToF mass spectrometry in the mass/charge range between 1000 and 100000 m/z. Normalisation of spectral data was defined using mass bins of 100 m/z expressed as a percentage of the total ion count of the mass spectra from 2000 to 11000 m/z. Of the ninety 100 m/z bins, forty-six were identified as m/z bins at which statistically significant differences in spectra occurred between Downs and control/non-aneuploid samples. Based on the differences and variance, for values at these bins, weighted scores of the probability of being Downs were assigned. Comparative algorithms consisting of various mass bins were tested for ability to distinguish Down syndrome from non-aneuploid pregnancy.

Results: Although various algorithms could distinguish Downs from non-aneuploid controls, it was found that gestational age was a confounding factor and that if separated into gestational age matched cohorts the ability to distinguish the groups improved dramatically e.g. whilst a 19 bins algorithm separated 100% of Downs from non-aneuploid pregnancies for a 9% false positive rate in the mixed gestational ages group; a two bin algorithm distinguished 100% of Downs for a 6% false positive rate for the 12 weeks gestational age pregnancies.

Conclusion: Normalised MALDI-ToF mass spectra, at 2000 to 11000 m/z, of maternal urine gives rise to gestational age specific screening tests algorithms for Downs’s syndrome.

Read Full Article HTML DOI: 10.29328/journal.apb.1001008 Cite this Article

References

  1. Seng P, Drancourt M, Gouriet F, La Scola B, Fournier PE, et al. Ongoing Revolution in Bacteriology: Routine Identification of Bacteria by Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry. Clin Infect Dis. 2009; 49: 543-551. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19583519
  2. Fall B, Lo CI, Samb-Ba B, Perrot N, Diawara S, et al. The ongoing revolution of MALDI-TOF mass spectrometry for microbiology reaches tropical Africa. Am J Trop Med Hyg. 2015; 92: 641-647. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25601995
  3. Nomura F. Proteome-based bacterial identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS): Arevolutionary shift in clinical diagnostic microbiology. Biochim Biophys Acta. 2015; 1854: 528-537. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25448014
  4. Gaillot O, Blondiaux N, Loïez C, Wallet F, Lemaître N, et al. Cost-effectiveness of switch to matrix-assisted laser desorption ionization-time of flight mass spectrometry for routine bacterial identification. J Clin Microbiol. 2011; 49: 4412. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21998417
  5. Tan KE, Ellis BC, Lee R, Stamper PD, Zhang SX, et al. Prospective evaluation of a matrix-assisted laser desorption ionization-time of flight mass spectrometry system in a hospital clinical microbiology laboratory for identification of bacteria and yeasts: a bench-by-bench study for assessing the impact on time to identification and cost-effectiveness. J Clin Microbiol. 2012; 50: 3301-3308. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22855510
  6. Lee SM, Park JS, Norwitz ER, Kim SM, Kim BJ, et al. Characterization of discriminatory urinary proteomic biomarkers for severe preeclampsia using SELDI-TOF mass spectrometry. J Perinat Med. 2011; 39: 391-396. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21557676
  7. Shin JK, Baek JC, Kang MY, Park JK, Lee SA, et al. Proteomic analysis reveals an elevated expression of heat shock protein 27 in pre-eclamptic placentas. Gynecol Obstet Invest. 2011; 71: 151-157.
  8. Narasimhan K, Lin SL, Tong T, Baig S, Ho S, et al. Maternal serum protein profile and immune response protein subunits as markers for non-invasive prenatal diagnosis of trisomy 21, 18, and 13. Prenat Diagn. 2013; 33: 223-231. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23371439
  9. Siciliano RA, Mazzeo MF, Spada V, Facchiano A, d’Acierno A, et al. Rapid peptidomic profiling of peritoneal fluid by MALDI-TOF mass spectrometry for the identification of biomarkers of endometriosis. Gynecol Endocrinol. 2014; 30: 872-876. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25111755
  10. Wang L, Liu HY, Shi HH, Lang JH, Sun W. Urine peptide patterns for non-invasive diagnosis of endometriosis: a preliminary prospective study. Eur J Obstet Gynecol Reprod Biol. 2014; 177: 23-28. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24694773
  11. Wölter M, Röwer C, Koy C, Rath W, Pecks U, et al. Proteoform profiling of peripheral blood serum proteins from pregnant women provides a molecular IUGR signature. J Proteomics. 2016; 3919: 30148-30158. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27109350
  12. Butler SA, Luttoo J, Abban TK, Musthan ZB, Borrelli PTA, et al. Truncated Human Chorionic Gonadotropin Variant in Hyperemesis Gravidarum: Possible Links to Hyperthyroidism and Emesis as a Thyroid Stimulating Hormone Analogue. 2018.
  13. Iles RK, Shahpari ME, Cuckle H, Butler SA. Direct and rapid mass spectral fingerprinting of maternal urine for the detection of Down syndrome pregnancy. Clin Proteomics. 2015; 12: 9. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25878568
  14. Poon LC, Kametas N, Bonino S, Vercellotti E, Nicolaides KH. Urine albumin concentration and albumin-to-creatinine ratio at 11(+0) to 13(+6) weeks in the prediction of pre-eclampsia. BJOG. 2008; 115: 866-873. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18485165
  15. Butler SA, Luttoo J, Freire MO, Abban TK, Borrelli PT, et al. Human chorionic gonadotropin (hCG) in the secretome of cultured embryos: hyperglycosylated hCG and hCG-free beta subunit are potential markers for infertility management and treatment. Reprod Sci. 2013; 20: 1038-1045. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23439616
  16. Iles RK, Cole LA, Butler SA. Direct analysis of hCGβcf glycosylation in normaland aberrant pregnancy by matrix-assisted laser desorption/ionizationtime-of-flight mass spectrometry. Int J Mol Sci. 2014; 15: 10067-10082.
  17. Lillehoj EP, Poulik MD. Normal and abnormal aspects of proteinuria. Part I: Mechanisms, characteristics and analyses of urinary protein. Part II: Clinical considerations. Exp Pathol. 1986; 29: 1-28. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/2422051
  18. Mutti A, Alinovi R, Ghiggeri GM, Bergamaschi E, Candiano G, et al. Urinary excretion of brush-border antigen and plasma proteins in early stages of diabetic nephropathy. Clin Chim Acta. 1990; 188: 93-100. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/2379316
  19. Fomina EV, Lisova NIu, Kireev KS, Tiys ES, Kononikhin AS, et al. Kidney function and urine protein composition in healthy volunteers during space station fitness tests. Aerosp Med Hum Perform. 2015; 86: 472-476. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25945665
  20. Jacoby ES, Kicman AT, Laidler P, Iles RK. Determination of the glycoforms ofhuman chorionic gonadotropin beta-core fragment by matrix-assisted laserdesorption/ionization time-of-flight mass spectrometry. Clin Chem. 2000; 46: 1796-1803. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11067815
  21. Mariona FG, Hassan MM, Syner FN, Chik LC, Sokol RJ. Maternal serum alpha-fetoprotein (MSAFP) and fetal growth. J Perinat Med. 1984; 12: 179-183. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/6210354
  22. Westergaard JG, Teisner B, Grudzinskas JG, Chard T. Single measurements ofchorionic gonadotropin and schwangerschafts protein for assessing gestational ageand predicting the day of delivery. J Reprod Med. 1985; 30: 57-60. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/3871857
  23. Pedersen JF, Sørensen S, Ruge S. Human placental lactogen and pregnancy-associated plasma protein A in first trimester and subsequent fetal growth. Acta Obstet Gynecol Scand. 1995; 74: 505-508. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/7542426
  24. Alldred SK, Takwoingi Y, Guo B, Pennant M, Deeks JJ, et al. First trimester serum tests for Down’s syndrome screening. Cochrane Database Syst Rev. 2015; 11: CD011975. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26617074
  25. Alldred SK, Guo B, Takwoingi Y, Pennant M, Wisniewski S, et al. Urine tests for Down’s syndrome screening. Cochrane Database Syst Rev. 2015; 12: CD011984. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26662198
  26. Roberts CJ, Hibbard BM, Evans DR, Evans KT, Laurence KM, et al. Precision in estimating gestational age and its influence on sensitivity of alphafetoprotein screening. Br Med J. 1979; 1: 981-983. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/86376
  27. Hadlock FP, Deter RL, Harrist RB, Park SK. Estimating fetal age: computer-assisted analysis of multiple fetal growth parameters. Radiology. 1984; 152: 497-501. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/6739822
  28. Morin JF, Moineau MP, Richard-Girème A, Talon H. Development of medians generators for the calculation of MoM for the first-trimester Down syndrome maternal serum markers. Ann Biol Clin. 2016; 74: 293-298. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27237803
  29. Trivedi DK, Iles RK. HILIC-MS-based shotgun metabolomic profiling of maternal urine at 9-23 weeks of gestation - establishing the baseline changes in the maternal metabolome. Biomed Chromatogr. 2015; 29: 240-245. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24898723
  30. Trivedi DK, Iles RK. Do not just do it, do it right: urinary metabolomics - establishing clinically relevant baselines. Biomed Chromatogr. 2014; 28: 1491-1501. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24788800
  31. Trivedi DK, Iles RK. Shotgun metabolomic profiles in maternal urine identify potential mass spectral markers of abnormal fetal biochemistry - dihydrouracil and progesterone in the metabolism of Down syndrome. Biomed Chromatogr. 2015; 29: 1173-1183. PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25545476
  32. Iles RK, Butler SA. Prenatal Screening - US Patent App. 2016.
  33. Palomaki GE, Kloza EM. Prenatal cell-free DNA screening test failures: a systematic review of failure rates, risks of Down syndrome, and impact of repeat testing. Genetics in Medicine. 2018.