Skip to main content
SpringerLink
Log in

The role of Kisspeptin levels in polycystic ovary syndrome: a systematic review and meta-analysis

  • Gynecologic Endocrinology and Reproductive Medicine
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Purpose

Polycystic ovarian syndrome (PCOS) is a complex and not fully elucidated pathology. This prevalent endocrinopathy affects patients in reproductive age, impacts on estrogen-dependent diseases, as well as in infertility. In this context, Kisspeptin (KP) may be considered a potential biomarker for PCOS diagnosis and follow-up. Here, we aimed to verify the levels of KP in obese and non-obese patients with PCOS, their relationship with other hormones, in comparison to healthy controls.

Methods

A systematic review and meta-analysis were performed according to the PRISMA guidelines. We searched MEDLINE, EMBASE, PsycINFO, Global Health, The Cochrane Library, Health Technology Assessment Database, and Web of Science for eligible studies. A random effects model meta-analysis of standardized mean difference (SMD) was conducted and the I2 was used to assess heterogeneity. Meta-regression was conducted through mixed-effects model.

Results

A total of 12 studies were included, comprising 660 PCOS patients and 600 controls. The KP levels were lower in the control group (0.76: 0.17–1.35; 95% CI). In the subgroup analyses, patients were divided in non-overweight/obese (BMI < 25) and overweight/obese (BMI ≥ 25) groups. The meta-regression revealed a difference between the obese and non-obese groups (z = 2.81; p = 0.0050).

Conclusions

PCOS patients showed higher KP levels than control, and obese non-PCOS patients also showed altered KP levels. All studies had poor descriptions of sample collection, pre-analytical and analytical procedures, which is critical considering structural characteristics of the KP molecule.

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
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of data and material

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Giampaolino P, Della Corte L, De Rosa N, Mercorio A, Bruzzese D, Bifulco G (2017) Ovarian volume and PCOS: a controversial issue. Gynecol Endocrinol 34:229–232. https://doi.org/10.1080/09513590.2017.1391205

    Article  CAS  PubMed  Google Scholar 

  2. Rotterdam ESHRE/ASRM-Sponsored PCOS consensus workshop group (2004) Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod 19:41–47. https://doi.org/10.1016/j.fertnstert.2003.10.004

    Article  Google Scholar 

  3. Laganà AS, Rossetti P, Buscema M, La Vignera S, Condorelli RA, Gullo G, Granese R, Triolo O (2016) Metabolism and ovarian function in PCOS women: a therapeutic approach with inositols. Int J Endocrinol 2016:6306410. https://doi.org/10.1155/2016/6306410

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Mani H, Levy MJ, Davies MJ, Morris DH, Gray LJ, Bankart J, Blackledge H, Khunti K, Howlett TA (2013) Diabetes and cardiovascular events in women with polycystic ovary syndrome: a 20-year retrospective cohort study. Clin Endocrinol (Oxf) 78:926–934. https://doi.org/10.1111/cen.12068

    Article  Google Scholar 

  5. Azziz R, Carmina E, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Futterweit W, Janssen OE, Legro RS, Norman RJ, Taylor AE, Witchel SF (2006) Positions statement: criteria for defining polycystic ovary syndrome as a predominantly hyperandrogenic syndrome: an androgen excess society guideline. J Clin Endocrinol Metab 91:4237–4245. https://doi.org/10.1210/jc.2006-0178

    Article  CAS  PubMed  Google Scholar 

  6. Palomba S, Falbo A, Russo T, Tolino A, Orio F, Zullo F (2010) Pregnancy in women with polycystic ovary syndrome: the effect of different phenotypes and features on obstetric and neonatal outcomes. Fertil Steril 94:1805–1811. https://doi.org/10.1016/j.fertnstert.2009.10.043

    Article  PubMed  Google Scholar 

  7. Laganà AS, Garzon S, Casarin J, Franchi M, Ghezzi F (2018) Inositol in polycystic ovary syndrome: restoring fertility through a pathophysiology-based approach. Trends Endocrinol Metab 29:768–780. https://doi.org/10.1016/j.tem.2018.09.001

    Article  CAS  PubMed  Google Scholar 

  8. Matsuzaki T, Tungalagsuvd A, Takeshi I, Munkhzaya M, Yanagihara R, Tokui T, Yano K, Mayila Y, Kato T, Kuwahara A, Matsui S, Irahara M (2017) Kisspeptin mRNA expression is increased in the posterior hypothalamus in the rat model of polycystic ovary syndrome. Endocr J 64:7–14. https://doi.org/10.1507/endocrj.EJ16-0282

    Article  CAS  PubMed  Google Scholar 

  9. Albalawi FS, Daghestani MH, Daghestani MH, Eldali A, Warsy AS (2018) rs4889 polymorphism in KISS1 gene, its effect on polycystic ovary syndrome development and anthropometric and hormonal parameters in Saudi women. J Biomed Sci 25:50. https://doi.org/10.1186/s12929-018-0452-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cortés ME, Carrera B, Rioseco H, Pablo del Rio J, Vigil P (2015) The role of kisspeptin in the onset of puberty and in the ovulatory mechanism: a mini-review. J Pediatr Adolesc Gynecol 28:286–291. https://doi.org/10.1016/j.jpag.2014.09.017

    Article  PubMed  Google Scholar 

  11. Trevisan CM, Montagna E, de Oliveira R, Christofolini DM, Barbosa CP, Crandall KA, Bianco B (2018) Kisspeptin/GPR54 system: what do we know about its role in human reproduction? Cell Physiol Biochem 49:1259–1276. https://doi.org/10.1159/000493406

    Article  CAS  PubMed  Google Scholar 

  12. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, PRISMA-P Group (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 350:g7647. https://doi.org/10.1136/bmj.g7647

    Article  PubMed  Google Scholar 

  13. National Center for Biotechnology Information. Available at https://pubchem.ncbi.nlm.nih.gov/compound/71306396. Accessed 27 Feb 2019

  14. Hozo SP, Djulbegovic B, Hozo I (2005) Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 5:13. https://doi.org/10.1186/1471-2288-5-13

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wells G, Shea B, O’Connell D, Peterson G, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available at http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 27 Feb 2019

  16. Borenstein M, Hedges LV, Higgins JPT, Rothstein RH (2009) Introduction to meta-analysis. Wiley, West Sussex

    Book  Google Scholar 

  17. Higgins JPT (2003) Measuring inconsistency in meta-analyses. BMJ 327:557–560. https://doi.org/10.1136/bmj.327.7414.557

    Article  PubMed  PubMed Central  Google Scholar 

  18. Aung T, Halsey J, Kromhout D, Gerstein HC, Marchioli R, Tavazzi L, Geleijnse JM, Rauch B, Ness A, Galan P, Chew EY, Bosch J, Collins R, Lewington S, Armitage J, Clarke R, Omega-3 Treatment Trialists’ Collaboration (2018) Associations of omega-3 fatty acid supplement use with cardiovascular disease risks: meta-analysis of 10 trials involving 77 917 individuals. JAMA Cardiol 3:225–234. https://doi.org/10.1001/jamacardio.2017.5205

    Article  PubMed  Google Scholar 

  19. Sterne JAC, Egger M (2001) Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol 54:1046–1055. https://doi.org/10.1016/S0895-4356(01)00377-8

    Article  CAS  PubMed  Google Scholar 

  20. Baujat B, Mahé C, Pignon J-P, Hill C (2002) A graphical method for exploring heterogeneity in meta-analyses: application to a meta-analysis of 65 trials: graphical method for exploring heterogeneity in meta-analyses. Stat Med 21:2641–2652. https://doi.org/10.1002/sim.1221

    Article  PubMed  Google Scholar 

  21. Estébanez N, Gómez-Acebo I, Palazuelos C, Llorca J, Dierssen-Sotos T (2018) Vitamin D exposure and risk of breast cancer: a meta-analysis. Sci Rep 8:9039. https://doi.org/10.1038/s41598-018-27297-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Schwarzer G, Carpenter JR, Rücker G (2015) Meta-analysis with R. Springer International Publishing, Switzerland

    Book  Google Scholar 

  23. Viechtbauer W (2010) Conducting meta-analyses in R with the metafor package. J Stat Softw 36:1–48. https://doi.org/10.18637/jss.v036.i03

    Article  Google Scholar 

  24. Branavan U, Muneeswaran K, Wijesundera WSS, Senanayake A, Chandrasekharan NV, Wijeyaratne CN (2019) Association of KISS1 and GPR54 gene polymorphisms with polycystic ovary syndrome among sri lankan women. Biomed Res Int 2019:6235680. https://doi.org/10.1155/2019/6235680

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Umayal B, Jayakody SN, Chandrasekharan NV, Wijesundera WS, Wijeyaratne CN (2019) Polycystic ovary syndrome (PCOS) and kisspeptin: a Sri Lankan study. J Postgrad Med 65:18–23. https://doi.org/10.4103/jpgm.JPGM_683_17

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Panidis D, Rousso D, Koliakos G, Kourtis A, Katsikis I, Farmakiotis D, Votsi E, Diamantikandarakis E (2006) Plasma metastin levels are negatively correlated with insulin resistance and free androgens in women with polycystic ovary syndrome. Fertil Steril 85:1778–1783. https://doi.org/10.1016/j.fertnstert.2005.11.044

    Article  CAS  PubMed  Google Scholar 

  27. Chen X, Mo Y, Li L, Chen Y, Li Y, Yang D (2010) Increased plasma metastin levels in adolescent women with polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 149:72–76. https://doi.org/10.1016/j.ejogrb.2009.11.018

    Article  CAS  PubMed  Google Scholar 

  28. Jeon YE, Lee KE, Jung JA, Yim SY, Kim H, Seo SK, Cho S, Choi YS, Lee BS (2013) Kisspeptin, leptin, and retinol-binding protein 4 in women with polycystic ovary syndrome. Gynecol Obstet Invest 75:268–274. https://doi.org/10.1159/000350217

    Article  CAS  PubMed  Google Scholar 

  29. Yilmaz SA, Kerimoglu OS, Pekin AT, Incesu F, Dogan NU, Celik C, Unlu A (2014) Metastin levels in relation with hormonal and metabolic profile in patients with polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 180:56–60. https://doi.org/10.1016/j.ejogrb.2014.06.004

    Article  CAS  PubMed  Google Scholar 

  30. Emekci Ozay O, Ozay AC, Acar B, Cagliyan E, Seçil M, Küme T (2016) Role of kisspeptin in polycystic ovary syndrome (PCOS). Gynecol Endocrinol 32:718–722. https://doi.org/10.3109/09513590.2016.1161019

    Article  CAS  PubMed  Google Scholar 

  31. Nyagolova PV, Mitkov MD, Orbetzova MM, Terzieva DD (2016) Kisspeptin and galanin-like peptide (galp) levels in women with polycystic ovary syndrome. Int J Pharmaceut Med Res 4:6–12

    Google Scholar 

  32. Gorkem U, Togrul C, Arslan E, Sargin Oruc A, Buyukkayaci Duman N (2018) Is there a role for kisspeptin in pathogenesis of polycystic ovary syndrome? Gynecol Endocrinol 34:157–160. https://doi.org/10.1080/09513590.2017.1379499

    Article  CAS  PubMed  Google Scholar 

  33. Daghestani MH (2018) Evaluation of biochemical, endocrine, and metabolic biomarkers for the early diagnosis of polycystic ovary syndrome among non-obese Saudi women. Int J Gynecol Obstet 142:162–169. https://doi.org/10.1002/ijgo.12527

    Article  CAS  Google Scholar 

  34. Kaya C, Alay İ, Babayeva G, Gedikbaşı A, Ertaş Kaya S, Ekin M, Yaşar L (2019) Serum Kisspeptin levels in unexplained infertility, polycystic ovary syndrome, and male factor infertility. Gynecol Endocrinol 35:228–232. https://doi.org/10.1080/09513590.2018.1519792

    Article  CAS  PubMed  Google Scholar 

  35. Wang T, Han S, Tian W, Zhao M, Zhang H (2019) Effects of kisspeptin on pathogenesis and energy metabolism in polycystic ovarian syndrome (PCOS). Gynecol Endocrinol 5:1. https://doi.org/10.1080/09513590.2019.1597343 (Epub ahead of print)

    Article  CAS  Google Scholar 

  36. Cela V, Obino MER, Alberga Y, Pinelli S, Sergiampietri C, Casarosa E, Simi G, Papini F, Artini PG (2018) Ovarian response to controlled ovarian stimulation in women with different polycystic ovary syndrome phenotypes. Gynecol Endocrinol 34(6):518–523. https://doi.org/10.1080/09513590.2017.1412429

    Article  PubMed  Google Scholar 

  37. Jamil AS, Alalaf SK, Al-Tawil NG, Al-Shawaf T (2016) Comparison of clinical and hormonal characteristics among four phenotypes of polycystic ovary syndrome based on the Rotterdam criteria. Arch Gynecol Obstet 293:447–456. https://doi.org/10.1007/s00404-015-3889-5

    Article  CAS  PubMed  Google Scholar 

  38. Lizneva D, Suturina L, Walker W, Brakta S, Gavrilova-Jordan L, Azziz R (2016) Criteria, prevalence, and phenotypes of polycystic ovary syndrome. Fertil Steril 106:6–15. https://doi.org/10.1016/j.fertnstert.2016.05.003

    Article  PubMed  Google Scholar 

  39. Tolson KP, Garcia C, Yen S, Simonds S, Stefanidis A, Lawrence A, Smith JT, Kauffman AS (2014) Impaired kisspeptin signaling decreases metabolism and promotes glucose intolerance and obesity. J Clin Invest. 124:3075–3079. https://doi.org/10.1172/JCI71075

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Holmes D (2014) Kisspeptin signalling linked to obesity. Nat Rev Endocrinol 10:511. https://doi.org/10.1038/nrendo.2014.106

    Article  PubMed  Google Scholar 

  41. Katulski K, Podfigurna A, Czyzyk A, Meczekalski B, Genazzani AD (2018) Kisspeptin and LH pulsatile temporal coupling in PCOS patients. Endocrine 61:149–157. https://doi.org/10.1007/s12020-018-1609-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. d’Anglemont de Tassigny X, Jayasena CN, Murphy KG, Dhillo WS, Colledge WH (2017) Mechanistic insights into the more potent effect of KP-54 compared to KP-10 in vivo. PLoS One 12:e0176821. https://doi.org/10.1371/journal.pone.0176821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kolodziejski PA, Pruszynska-Oszmalek E, Korek E, Sassek M, Szczepankiewicz D, Kaczmarek P, Nogowski L, Mackowiak P, Nowak KW, Krauss H, Strowski MZ (2018) Serum levels of spexin and kisspeptin negatively correlate with obesity and insulin resistance in women. Physiol Res 67:45–56. https://doi.org/10.33549/physiolres.933467

    Article  CAS  PubMed  Google Scholar 

  44. Kasum M, Franulić D, Čehić E, Orešković S, Lila A, Ejubović E (2017) Kisspeptin as a promising oocyte maturation trigger for in vitro fertilisation in humans. Gynecol Endocrinol 33:583–587. https://doi.org/10.1080/09513590.2017.1309019

    Article  CAS  PubMed  Google Scholar 

  45. Decourt C, Robert V, Anger K, Galibert M, Madinier J-B, Liu X, Dardente H, Lomet D, Delmas AF, Caraty A, Herbison AE, Anderson GM, Aucagne V, Beltramo M (2016) A synthetic kisspeptin analog that triggers ovulation and advances puberty. Sci Rep 6:26908. https://doi.org/10.1038/srep26908

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Dr. Bianca Bianco for the support in the manuscript preparation.

Funding

None.

Author information

Authors and Affiliations

  1. Postgraduate Program in Health Sciences, Faculdade de Medicina do ABC, Av. Lauro Gomes, 2000, Santo André, Brazil

    Nicole Paloma de Assis Rodrigues, Victor Zaia, Caio Parente Barbosa, Renato de Oliveira, Camila Martins Trevisan & Erik Montagna

  2. Department of Obstetrics and Gynecology, “Filippo Del Ponte” Hospital, University of Insubria, Varese, Italy

    Antonio Simone Laganà

  3. Department of Women and Children’s Health, Unit of Gynecology and Obstetrics, University of Padua, Padua, Italy

    Amerigo Vitagliano

  4. Discipline of Sexual and Reproductive Health and Populational Genetics, Department of Collective Health, Faculdade de Medicina do ABC, Santo André, Brazil

    Caio Parente Barbosa & Renato de Oliveira

Authors
  1. Nicole Paloma de Assis Rodrigues
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonio Simone Laganà
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor Zaia
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amerigo Vitagliano
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Caio Parente Barbosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Renato de Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Camila Martins Trevisan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Erik Montagna
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NP Assis Rodrigues: design of the study, literature review, data collection, data analysis and manuscript writing; AS Laganà: data analysis, manuscript writing and editing; V Zaia: data collection, data analysis and review of the manuscript; A Vitagliano: data analysis and review of the manuscript; CP Barbosa: review of the manuscript; R Oliveira: data analysis, review and manuscript writing; CM Trevisan: data collection, data analysis and review of the manuscript; E Montagna: design of the study, literature review, data analysis and manuscript writing/review. All authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Erik Montagna.

Ethics declarations

Conflict of interest

The authors have no conflicts of interest to disclose.

Informed consent

Not applicable.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Assis Rodrigues, N.P., Laganà, A., Zaia, V. et al. The role of Kisspeptin levels in polycystic ovary syndrome: a systematic review and meta-analysis. Arch Gynecol Obstet 300, 1423–1434 (2019). https://doi.org/10.1007/s00404-019-05307-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00404-019-05307-5

Keywords

Search

Navigation