Skip to main content
SpringerLink
Log in

Genomic imbalance in euploid pregnancy loss

  • Genetics
  • Published:
Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

Purpose

This study aims to investigate genomic imbalance in euploid products of conceptions (POCs) detected by chromosomal microarray analysis (CMA) and its association with clinical characteristics.

Methods

In a retrospective cohort study where all women with singleton pregnancy losses underwent CMA detection of POCs, only patients with euploid POCs were included in the analysis. The clinical features were compared between those with and without a copy number variant (CNV). The pathogenic CNVs and the variant of uncertain significance (VOUS) were analyzed, and the common pathogenic CNVs and uniparental disomy (UPD) were investigated.

Results

A total of 610 POCs were detected as chromosomal euploid, of which 176 were euploid with CNVs and 434 were euploid without CNVs. Regarding maternal age, gestational age, and history of pregnancy loss, no significant differences were found between the two groups. Furthermore, 104 pathogenic CNVs were identified in 93 POCs, and the deletion of 8p23.3 was found in 10 subjects. All CNVs greater than 3 Mb and 39.5% of CNVs ranging from 1 to 2 Mb were pathogenic, and only 3 CNVs < 1 Mb were pathogenic. UPD was detected in 12 POCs.

Conclusion

Besides aneuploidy, 15.24% pregnancy loss might have an association with pathogenic genomic imbalance, and the occurrence of genomic imbalance is not related to clinical characteristics. CNVs greater than 3 Mb in pregnancy losses have a high probability to be pathogenic, and approximately 40% of CNVs ranging from 1 to 2 Mb are pathogenic. The deletion of 8p23.3 is the most common pathogenic CVN in POCs of Chinese-Han women. The clinical significance of UPD in pregnancy loss needs further study.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

References

  1. Zinaman MJ, Clegg ED, Brown CC, O’Connor J, Selevan SG. Estimates of human fertility and pregnancy loss. Fertil Steril. 1996;65(3):503–9.

    Article  CAS  Google Scholar 

  2. RPL EGGo, Bender AR, Christiansen OB, Elson J, Kolte AM, Lewis S, et al.: ESHRE guideline: recurrent pregnancy loss. Hum Reprod Open. 2018; 2018(2): hoy004.

  3. Practice Committee of the American Society for Reproductive M: Evaluation and treatment of recurrent pregnancy loss: a committee opinion. Fertil Steril. 2012; 98(5): 1103–1111.

  4. Wang Y, Li Y, Chen Y, Zhou R, Sang Z, Meng L, et al. Systematic analysis of copy-number variations associated with early pregnancy loss. Ultrasound Obstet Gynecol. 2020;55(1):96–104.

    Article  CAS  Google Scholar 

  5. Gu C, Li K, Li R, Li L, Li X, Dai X, et al. Chromosomal aneuploidy associated with clinical characteristics of pregnancy loss. Front Genet. 2021;12: 667697.

    Article  Google Scholar 

  6. Grande M, Borrell A, Garcia-Posada R, Borobio V, Munoz M, Creus M, et al. The effect of maternal age on chromosomal anomaly rate and spectrum in recurrent miscarriage. Hum Reprod. 2012;27(10):3109–17.

    Article  Google Scholar 

  7. Hillman SC, Pretlove S, Coomarasamy A, McMullan DJ, Davison EV, Maher ER, et al. Additional information from array comparative genomic hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2011;37(1):6–14.

    Article  CAS  Google Scholar 

  8. Dhillon RK, Hillman SC, Morris RK, McMullan D, Williams D, Coomarasamy A, et al. Additional information from chromosomal microarray analysis (CMA) over conventional karyotyping when diagnosing chromosomal abnormalities in miscarriage: a systematic review and meta-analysis. BJOG. 2014;121(1):11–21.

    Article  CAS  Google Scholar 

  9. Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, et al. Global variation in copy number in the human genome. Nature. 2006;444(7118):444–54.

    Article  CAS  Google Scholar 

  10. Hurles ME, Dermitzakis ET, Tyler-Smith C. The functional impact of structural variation in humans. Trends Genet. 2008;24(5):238–45.

    Article  CAS  Google Scholar 

  11. Goldstein M, Svirsky R, Reches A, Yaron Y. Does the number of previous miscarriages influence the incidence of chromosomal aberrations in spontaneous pregnancy loss? J Matern Fetal Neonatal Med. 2017;30(24):2956–60.

    Article  Google Scholar 

  12. Hardy K, Hardy PJ, Jacobs PA, Lewallen K, Hassold TJ. Temporal changes in chromosome abnormalities in human spontaneous abortions: results of 40 years of analysis. Am J Med Genet A. 2016;170(10):2671–80.

    Article  CAS  Google Scholar 

  13. Kotzot D. Prenatal testing for uniparental disomy: indications and clinical relevance. Ultrasound Obstet Gynecol. 2008;31(1):100–5.

    Article  CAS  Google Scholar 

  14. Fritz B, Aslan M, Kalscheuer V, Ramsing M, Saar K, Fuchs B, et al. Low incidence of UPD in spontaneous abortions beyond the 5th gestational week. Eur J Hum Genet. 2001;9(12):910–6.

    Article  CAS  Google Scholar 

  15. Doubilet PM, Benson CB, Bourne T, Blaivas M. Society of Radiologists in Ultrasound Multispecialty Panel on early first trimester diagnosis of M, exclusion of a viable intrauterine P: diagnostic criteria for nonviable pregnancy early in the first trimester. Ultrasound Q. 2014;30(1):3–9.

    Article  Google Scholar 

  16. Diego-Alvarez D, Garcia-Hoyos M, Trujillo MJ, Gonzalez-Gonzalez C, Rodriguez de Alba M, Ayuso C, et al. Application of quantitative fluorescent PCR with short tandem repeat markers to the study of aneuploidies in spontaneous miscarriages. Hum Reprod. 2005;20(5):1235–43.

    Article  CAS  Google Scholar 

  17. Nagan N, Faulkner NE, Curtis C, Schrijver I. Committee MCCGWGotAfMPCP: Laboratory guidelines for detection, interpretation, and reporting of maternal cell contamination in prenatal analyses a report of the association for molecular pathology. J Mol Diagn. 2011;13(1):7–11.

    Article  Google Scholar 

  18. Kearney HM, Thorland EC, Brown KK, Quintero-Rivera F, South ST. Working Group of the American College of Medical Genetics Laboratory Quality Assurance C: American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med. 2011;13(7):680–5.

    Article  Google Scholar 

  19. Riggs ER, Andersen EF, Cherry AM, Kantarci S, Kearney H, Patel A, et al. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med. 2020;22(2):245–57.

    Article  Google Scholar 

  20. Colley E, Hamilton S, Smith P, Morgan NV, Coomarasamy A, Allen S. Potential genetic causes of miscarriage in euploid pregnancies: a systematic review. Hum Reprod Update. 2019;25(4):452–72.

    Article  CAS  Google Scholar 

  21. Pauta M, Grande M, Rodriguez-Revenga L, Kolomietz E, Borrell A. Added value of chromosomal microarray analysis over karyotyping in early pregnancy loss: systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2018;51(4):453–62.

    Article  CAS  Google Scholar 

  22. Wang Y, Cheng Q, Meng L, Luo C, Hu H, Zhang J, et al. Clinical application of SNP array analysis in first-trimester pregnancy loss: a prospective study. Clin Genet. 2017;91(6):849–58.

    Article  CAS  Google Scholar 

  23. Chen L, Wang L, Tang F, Zeng Y, Yin D, Zhou C, et al. Copy number variation sequencing combined with quantitative fluorescence polymerase chain reaction in clinical application of pregnancy loss. J Assist Reprod Genet. 2021;38(9):2397–404.

    Article  Google Scholar 

  24. Morikawa M, Yamada H, Kato EH, Shimada S, Yamada T, Minakami H. Embryo loss pattern is predominant in miscarriages with normal chromosome karyotype among women with repeated miscarriage. Hum Reprod. 2004;19(11):2644–7.

    Article  Google Scholar 

  25. Ogasawara M, Aoki K, Okada S, Suzumori K. Embryonic karyotype of abortuses in relation to the number of previous miscarriages. Fertil Steril. 2000;73(2):300–4.

    Article  CAS  Google Scholar 

  26. Hurles M. Gene duplication: the genomic trade in spare parts. PLoS Biol. 2004;2(7):E206.

    Article  Google Scholar 

  27. Uddin M, Tammimies K, Pellecchia G, Alipanahi B, Hu P, Wang Z, et al. Brain-expressed exons under purifying selection are enriched for de novo mutations in autism spectrum disorder. Nat Genet. 2014;46(7):742–7.

    Article  CAS  Google Scholar 

  28. Sheng YR, Hou SY, Hu WT, Wei CY, Liu YK, Liu YY, et al.: Characterization of copy-number variations and possible candidate genes in recurrent pregnancy losses. Genes (Basel) 2021;12(2).

  29. Sato T, Migita O, Hata H, Okamoto A, Hata K. Analysis of chromosome microstructures in products of conception associated with recurrent miscarriage. Reprod Biomed Online. 2019;38(5):787–95.

    Article  CAS  Google Scholar 

  30. Founds SA, Stolz DB. Gene expression of four targets in situ of the first trimester maternal-fetoplacental interface. Tissue Cell. 2020;64: 101313.

    Article  CAS  Google Scholar 

  31. Gu C, Gao H, Li K, Dai X, Yang Z, Li R, Wen C, He Y. Copy number variation analysis of euploid pregnancy loss. Front Genet. 2022;13: 766492.

    Article  CAS  Google Scholar 

  32. Shaffer LG, Bejjani BA. A cytogeneticist’s perspective on genomic microarrays. Hum Reprod Update. 2004;10(3):221–6.

    Article  CAS  Google Scholar 

  33. Sahoo T, Dzidic N, Strecker MN, Commander S, Travis MK, Doherty C, et al. Comprehensive genetic analysis of pregnancy loss by chromosomal microarrays: outcomes, benefits, and challenges. Genet Med. 2017;19(1):83–9.

    Article  CAS  Google Scholar 

  34. Zarrei M, MacDonald JR, Merico D, Scherer SW. A copy number variation map of the human genome. Nat Rev Genet. 2015;16(3):172–83.

    Article  CAS  Google Scholar 

  35. Devriendt K, Matthijs G, Van Dael R, Gewillig M, Eyskens B, Hjalgrim H, et al.: Delineation of the critical deletion region for congenital heart defects, on chromosome 8p23.1. Am J Hum Genet. 1999;64(4): 1119-1126

  36. Barber JC, Maloney VK, Huang S, Bunyan DJ, Cresswell L, Kinning E, et al. 8p23.1 duplication syndrome; a novel genomic condition with unexpected complexity revealed by array CGH. Eur J Hum Genet. 2008;16(1):18–27.

    Article  CAS  Google Scholar 

  37. Habhab W, Mau-Holzmann U, Singer S, Riess A, Kagan KO, Gerbig I, et al.: Pre- and postnatal findings in a patient with a recombinant chromosome rec(8)(qter-->q21.11::p23.3-->qter) due to a paternal pericentric inversion inv(8)(p23.3q21.11) and review of the literature. Am J Med Genet A 2020;182(11): 2680-2684

  38. Yamazawa K, Ogata T, Ferguson-Smith AC. Uniparental disomy and human disease: an overview. Am J Med Genet C Semin Med Genet. 2010;154C(3):329–34.

    Article  Google Scholar 

  39. Benn P. Uniparental disomy: origin, frequency, and clinical significance. Prenat Diagn. 2021;41(5):564–72.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank all patients who paid their antenatal care in our hospital and all physicians who recorded the data on pregnancies and pregnancy outcomes.

Funding

The study was supported by a grant from the Guangzhou Women and Children’s Medical Center, Guangzhou, China (1600067–04), and a grant from the Guangzhou Municipal Science and Technology Bureau, Guangzhou, China (202102010311). The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, 9 Jinsui Road, Tianhe District, Guangzhou, 510623, China

    Chongjuan Gu & Yaojuan He

  2. Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China

    Kuanrong Li & Ling Li

  3. Department of Toxicology, School of Public Health, Sun Yat-Sen University, Guangzhou, China

    Huan Gao

  4. Prenatal Diagnostic Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China

    Ru Li

Authors
  1. Chongjuan Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kuanrong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ling Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Huan Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ru Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yaojuan He
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CG and YH contributed to the conception of the study and drafted the manuscript. CG and KL contributed to the design of the research and control of the data quality. RL and LL contributed to data management and prepared the retrospective data for analysis. HG preform the bioinformatics analysis. All authors reviewed, read, and approved the final manuscript.

Corresponding author

Correspondence to Chongjuan Gu.

Ethics declarations

Ethics statement

The studies involving human participants were reviewed and approved by the Ethical Committee of the Guangzhou Women and Children’s Medical Center (2020–15001). The patients provided their written informed consent to participate in this study.

Conflict of interests

The authors declare no competing interests.

Additional information

Publisher's note

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

Supplementary information

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 20 KB)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gu, C., Li, K., Li, L. et al. Genomic imbalance in euploid pregnancy loss. J Assist Reprod Genet 39, 2115–2124 (2022). https://doi.org/10.1007/s10815-022-02527-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10815-022-02527-8

Keywords

Search

Navigation