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The Expression of microRNAs and Their Involvement in Recurrent Pregnancy Loss.

Maria-Markella PatroniaAnastasios PotirisDespoina MavrogianniEirini DrakakiTheodoros KarampitsakosPavlos MachairoudiasSpyridon TopisAthanasios ZikopoulosDionysios VrachnisEfthalia MoustakliChara SkentouEkaterini DomaliNikolaos DrakoulisPeter DrakakisSofoklis Stavros
Published in: Journal of clinical medicine (2024)
Background: Recurrent pregnancy loss refers to the spontaneous demise of two or more pregnancies before the 24 weeks of gestation. In almost half of the cases of recurrent miscarriages, the causes remain unknown since there is no reliable way of prognosis, early diagnosis, or treatment. Recent research has detected differential expression of certain miRNAs in reproductive system pathologies. Methods: The aim of the present review is to focus on microRNAs and their relationship with idiopathic recurrent miscarriages and to correlate miRNA expression with recurrent miscarriage and examine their potential role as biomarkers. Pubmed/Medline and Scopus databases were searched up to 31st January 2024 with terms related to recurrent pregnancy loss and miRNAs. Results: In total, 21 studies were selected for the review. A total of 75 different miRNAs were identified, showing a statistically significant differential expression. Around 40 miRNAs had increased expression, such as miR-520, miR-184 and miR-100-5p, 21 decreased, such as let-7c, and 14 had either increased or decreased expression depending on the study, such as miR-21. Conclusions: The dysregulation of miRNA expression is strongly associated with recurrent miscarriages. The circulating in the peripheral blood miRNAs, miR-100-5p and let-7c, might be utilized as biomarkers and establish a valuable non-invasive prognostic and diagnostic tool in the future.
Keyphrases
  • poor prognosis
  • long non coding rna
  • cell proliferation
  • preterm birth
  • peripheral blood
  • binding protein
  • long noncoding rna
  • preterm infants
  • machine learning
  • pregnant women
  • big data
  • replacement therapy