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microRNA Expression in Women With and Without Polycystic Ovarian Syndrome Matched for Body Mass Index

journal contribution
submitted on 2024-06-24, 07:10 and posted on 2024-06-24, 10:02 authored by Alexandra E. Butler, Vimal Ramachandran, Thozhukat Sathyapalan, Rhiannon David, Nigel J. Gooderham, Manasi Benurwar, Soha R. Dargham, Shahina Hayat, S. Hani Najafi-Shoushtari, Stephen L. Atkin


Despite several authors who have hypothesized that alterations of small noncoding RNAs (miR) are implicated in the etiopathogenesis of polycystic ovarian syndrome (PCOS), contrasting findings have been reported so far. Discrepancies in body mass index (BMI) levels may account for these differences; therefore, the aim of the present study was to determine whether miR differed in serum samples collected from age- and BMI-matched control and PCOS women.


In a cross-sectional study, miR were measured using quantitative polymerase chain reaction in 29 women with anovulatory PCOS women and 29 control women who were in the follicular phase of their menstrual cycle, from the local biobank.


One hundred seventy-six miR were detected, of which 15 miR passed the false discovery rate (FDR; p < 0.05) that differed between PCOS and control women. There was no association of the top 9 miR (p < 0.02) (miR-486-5p, miR-24-3p, miR-19b-3p, miR-22-3p, miR-19a-3p, miR-339-5p, miR-185-5p, miR-101-3p, miR-let-7i-5p) with BMI, androgen levels, insulin resistance, or antimullerian hormone (AMH) in either PCOS or normal women. Ingenuity pathway assessment showed the pathways were interrelated for abnormalities of the reproductive system.


When the confounding influence of weight was accounted for, miR levels differed between anovulatory PCOS women and control women in the follicular phase of the menstrual cycle. Interestingly, the differing miR were associated with the pathways of reproductive abnormalities but did not associate with AMH or metabolic parameters.

Other Information

Published in: Frontiers in Endocrinology
See article on publisher's website:



  • English



Publication Year

  • 2020

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Biomedical Research Institute - HBKU
  • Diabetes Research Center - QBRI
  • Weill Cornell Medicine - Qatar