Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis

Hatice Çalışkan Burgucu; Emel Yılmaz Kaya; Ayşen Yümlü; Mehmet Korkmaz; Melike Geyik Bayman; Oğuzhan Aksu

Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis

Abstract

Aims: Polycystic ovary syndrome (PCOS) is associated with significant metabolic and cardiometabolic abnormalities. This study aimed to evaluate prolactin levels and cardiometabolic surrogate indices across PCOS phenotypes and to examine the relationship between prolactin and cardiometabolic parameters in women with PCOS. Methods: A retrospective cohort of 206 women, including 126 with PCOS and 80 controls, was analyzed. Women with PCOS were classified into four phenotypes (A-D). Demographic, anthropometric, metabolic, hormonal, and cardiometabolic variables were assessed. Correlation analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis were performed. Results: Compared with controls, women with PCOS had higher body weight, body-mass index (BMI), waist circumference (WC), triglyceride (TG) levels, insulin resistance-related parameters, triglyceride-glucose (TyG) Index, lipid accumulation product (LAP), and Atherogenic Index of Plasma (AIP), whereas high-density lipoprotein cholesterol (HDL-C) and single point insulin sensitivity estimator (SPISE) values were lower (all p<0.01). Prolactin levels were similar between groups (p=0.182) and across phenotypes. In the PCOS group, prolactin was negatively correlated with BMI, WC, homeostasis model assessment of insulin resistance (HOMA-IR), TyG, LAP, and AIP, and positively correlated with SPISE (all p<0.05). After adjustment for age and BMI, prolactin remained significantly associated with PCOS status. Among the evaluated cardiometabolic indices, LAP showed the highest discriminatory performance (AUC=0.784), followed by SPISE (AUC=0.769). Conclusion: Women with PCOS exhibited adverse metabolic and cardiometabolic profiles. Among the evaluated cardiometabolic surrogate markers, LAP and SPISE showed the highest discriminatory performance and may provide additional information for cardiometabolic risk assessment in women with PCOS.

Keywords

Supporting Institution

none

Ethical Statement

Ethical approval for this study was obtained from the Non-Interventional Clinical Research Ethics Committee of Konya City Hospital (meeting number: 2026/04; decision number: 2026/98; meeting date: 13.04.2026).

Thanks

none

References

Lizneva D, Suturina L, Walker W, Brakta S, Gavrilova-Jordan L, Azziz R. Criteria, prevalence, and phenotypes of polycystic ovary syndrome. Fertil Steril. 2016;106(1):6-15. doi:10.1016/j.fertnstert.2016.05.003
Teede HJ, Tay CT, Laven JJE, et al. Recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome. J Clin Endocrinol Metab. 2023;108(10):2447-2469. doi:10.1210/clinem/dgad463
Sachdeva G, Gainder S, Suri V, Sachdeva N, Chopra S. Comparison of the different PCOS phenotypes based on clinical metabolic, and hormonal profile, and their response to clomiphene. Indian J Endocrinol Metab. 2019;23(3):326-331. doi:10.4103/ijem.IJEM_30_19
Ma YC, Law KS, Wang WS, Chang HM. Phenotypic variations in polycystic ovary syndrome: metabolic risks and emerging biomarkers. J Endocrinol. 2025;267(1):e250226. doi:10.1530/JOE-25-0226
Teede HJ, Khomami MB, Morman R, et al. Polyendocrine metabolic ovarian syndrome, the new name for polycystic ovary syndrome: a multistep global consensus process. Lancet. 2026;407(10545):2329-2339. doi:10.1016/S0140-6736(26)00717-8
Glintborg D, Altinok M, Mumm H, Buch K, Ravn P, Andersen M. Prolactin is associated with metabolic risk and cortisol in 1007 women with polycystic ovary syndrome. Hum Reprod. 2014;29(8):1773-1779. doi:10.1093/humrep/deu133
Macotela Y, Ruiz-Herrera X, Vázquez-Carrillo DI, Ramírez-Hernandez G, Martínez de la Escalera G, Clapp C. The beneficial metabolic actions of prolactin. Front Endocrinol (Lausanne). 2022;13:1001703. doi:10.3389/fendo.2022.1001703
Guerrero-Romero F, Simental-Mendía LE, González-Ortiz M, et al. The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp. J Clin Endocrinol Metab. 2010;95(7):3347-3351. doi:10.1210/jc.2010-0288

Dobiásová M. AIP-Atherogenic Index of Plasma as a significant predictor of cardiovascular risk: from research to practice. Vnitr Lek. 2006;52(1):64-71.
Paulmichl K, Hatunic M, Højlund K, et al. Modification and validation of the triglyceride-to-HDL cholesterol ratio as a surrogate of insulin sensitivity in white juveniles and adults without diabetes mellitus: the single point insulin sensitivity estimator (SPISE). Clin Chem. 2016; 62(9):1211-1219. doi:10.1373/clinchem.2016.257436
Wu TT, Gao Y, Zheng YY, Ma YT, Xie X. Atherogenic Index of Plasma (AIP): a novel predictive indicator for the coronary artery disease in postmenopausal women. Lipids Health Dis. 2018;17(1):197. doi:10.1186/s12944-018-0828-z
Ahn N, Baumeister SE, Amann U, et al. Visceral Adiposity Index (VAI), lipid accumulation product (LAP), and product of triglycerides and glucose (TyG) to discriminate prediabetes and diabetes. Sci Rep. 2019; 9(1):9693. doi:10.1038/s41598-019-46187-8
Wild RA, Carmina E, Diamanti-Kandarakis E, et al. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome: a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab. 2010;95(5):2038-2049. doi:10.1210/jc.2009-2724
Fauser BC, Tarlatzis BC, Rebar RW, et al. Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group. Fertil Steril. 2012;97(1):28-38.e25. doi:10.1016/j.fertnstert.2011.09.024
Lambrinoudaki I, Kazani MV, Armeni E, et al. The TyG Index as a marker of subclinical atherosclerosis and arterial stiffness in lean and overweight postmenopausal women. Heart Lung Circ. 2018;27(6):716-724. doi:10.1016/j.hlc.2017.05.142
Khan SH, Sobia F, Niazi NK, Manzoor SM, Fazal N, Ahmad F. Metabolic clustering of risk factors: evaluation of Triglyceride-Glucose Index (TyG Index) for evaluation of insulin resistance. Diabetol Metab Syndr. 2018; 10:74. doi:10.1186/s13098-018-0376-8
Arslan G, Karakelleoğlu G, Karadağ C. Status of a lipid accumulation product, Triglycerides/Glucose Index and Visceral Adiposity Index on cardiometabolic risk factors in young polycystic ovary syndrome patients. Ceska Gynekol. 2025;90(6):457-462. doi:10.48095/cccg2025457
Wiltgen D, Benedetto IG, Mastella LS, Spritzer PM. Lipid Accumulation Product Index: a reliable marker of cardiovascular risk in polycystic ovary syndrome. Hum Reprod. 2009;24(7):1726-1731. doi:10.1093/humrep/dep072
Çakır Biçer N, Ermiş AA, Baş D. The role of different methods in defining cardiometabolic risk and metabolic syndrome in women with polycystic ovary syndrome. Life (Basel). 2023;13(10):1959. doi:10.3390/life13101959
Xiang S, Hua F, Chen L, Tang Y, Jiang X, Liu Z. Lipid accumulation product is related to metabolic syndrome in women with polycystic ovary syndrome. Exp Clin Endocrinol Diabetes. 2013;121(2):115-118. doi:10.1055/s-0032-1333261
Demirci H, Menekse B, Ucgul E, Onaran Y, Bayram SM, Cakal E. Impact of polycystic ovary syndrome on the Atherogenic Plasma Index: a retrospective analysis. BMC Endocr Disord. 2025;25(1):185. doi:10.1186/s12902-025-02008-w
Uysal E, Tammo O, Soylemez E, Incebıyık M, Filiz D, Alci M. Significance of measuring anthropometric and atherogenic indices in patients with polycystic ovary syndrome. BMC Endocr Disord. 2024; 24(1):160. doi:10.1186/s12902-024-01701-6
Seo MW, Cho W, Kim JY. The Single Point Insulin Sensitivity Estimator (SPISE) Index as a predictor of metabolic syndrome in Korean adults. Obes Res Clin Pract. 2023;17(3):198-202. doi:10.1016/j.orcp.2023.05.001
Welt CK, Gudmundsson JA, Arason G, et al. Characterizing discrete subsets of polycystic ovary syndrome as defined by the Rotterdam criteria: the impact of weight on phenotype and metabolic features. J Clin Endocrinol Metab. 2006;91(12):4842-4848. doi:10.1210/jc.2006-1327
Wen X, Wang L, Bai E. Metabolic characteristics of different phenotypes in reproductive-aged women with polycystic ovary syndrome. Front Endocrinol (Lausanne). 2024;15:1370578. doi:10.3389/fendo.2024.1370578
Pililis S, Lampsas S, Kountouri A, et al. The cardiometabolic risk in women with polycystic ovarian syndrome (PCOS): from pathophysiology to diagnosis and treatment. Medicina (Kaunas). 2024;60(10):1656. doi:10.3390/medicina60101656
Barchetta I, Dule S, Bertoccini L, et al. The Single-Point Insulin Sensitivity Estimator (SPISE) Index is a strong predictor of abnormal glucose metabolism in overweight/obese children: a long-term follow-up study. J Endocrinol Invest. 2022;45(1):43-51. doi:10.1007/s40618-021-01612-6
Bil E, Dilbaz B, Cirik DA, Ozelci R, Ozkaya E, Dilbaz S. Metabolic syndrome and metabolic risk profile according to polycystic ovary syndrome phenotype. J Obstet Gynaecol Res. 2016;42(7):837-843. doi:10.1111/jog.12985
Bahadur A, Verma N, Mundhra R, et al. Correlation of homeostatic model assessment-insulin resistance, anti-Mullerian hormone, and BMI in the characterization of polycystic ovary syndrome. Cureus. 2021;13(6):e16047. doi:10.7759/cureus.16047
Saei Ghare Naz M, Mousavi M, Mahboobifard F, Niknam A, Ramezani Tehrani F. A meta-analysis of observational studies on prolactin levels in women with polycystic ovary syndrome. Diagnostics (Basel). 2022; 12(12):2924. doi:10.3390/diagnostics12122924
Yanachkova V, Stankova T. Abnormally increased prolactin levels in women with polycystic ovarian syndrome are associated with risk of obesity, insulin resistance and prediabetes. Int J Mol Sci. 2025;26(9):4239. doi:10.3390/ijms26094239
Chan JL, Masini I, Pisarska MD. Polyendocrine metabolic ovarian syndrome (PMOS)/polycystic ovary syndrome (PCOS): current and future trends. J Clin Invest. 2026;136(12):e202824. doi:10.1172/JCI202824

Details

Primary Language

English

Subjects

Endocrinology, Internal Diseases, Obstetrics and Gynaecology

Journal Section

Research Article

Authors

Hatice Çalışkan Burgucu ^*
0000-0001-7699-4580
Türkiye

Emel Yılmaz Kaya
0000-0003-1401-6102
Türkiye

Ayşen Yümlü
0009-0009-3798-0675
Türkiye

Mehmet Korkmaz
0009-0004-8188-2865
Türkiye

Melike Geyik Bayman
0000-0003-0008-2205
Türkiye

Oğuzhan Aksu
0000-0003-4666-7129
Türkiye

Publication Date

September 11, 2026

Submission Date

June 19, 2026

Acceptance Date

August 15, 2026

Published in Issue

Year 2026 Volume: 8 Number: 5

IZ

https://izlik.org/JA73HH32RY

Cite

RIS / Bibtex

APA

Çalışkan Burgucu, H., Yılmaz Kaya, E., Yümlü, A., Korkmaz, M., Geyik Bayman, M., & Aksu, O. (2026). Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis. Anatolian Current Medical Journal, 8(5), 1047-1054. https://izlik.org/JA73HH32RY

AMA

1.Çalışkan Burgucu H, Yılmaz Kaya E, Yümlü A, Korkmaz M, Geyik Bayman M, Aksu O. Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis. Anatolian Curr Med J / ACMJ / acmj. 2026;8(5):1047-1054. https://izlik.org/JA73HH32RY

Chicago

Çalışkan Burgucu, Hatice, Emel Yılmaz Kaya, Ayşen Yümlü, Mehmet Korkmaz, Melike Geyik Bayman, and Oğuzhan Aksu. 2026. “Association of Prolactin With Cardiometabolic Risk Markers in Women With Polycystic Ovary Syndrome: A Phenotype-Based Analysis”. Anatolian Current Medical Journal 8 (5): 1047-54. https://izlik.org/JA73HH32RY.

EndNote

Çalışkan Burgucu H, Yılmaz Kaya E, Yümlü A, Korkmaz M, Geyik Bayman M, Aksu O (September 1, 2026) Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis. Anatolian Current Medical Journal 8 5 1047–1054.

IEEE

[1]H. Çalışkan Burgucu, E. Yılmaz Kaya, A. Yümlü, M. Korkmaz, M. Geyik Bayman, and O. Aksu, “Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis”, Anatolian Curr Med J / ACMJ / acmj, vol. 8, no. 5, pp. 1047–1054, Sept. 2026, [Online]. Available: https://izlik.org/JA73HH32RY

ISNAD

Çalışkan Burgucu, Hatice - Yılmaz Kaya, Emel - Yümlü, Ayşen - Korkmaz, Mehmet - Geyik Bayman, Melike - Aksu, Oğuzhan. “Association of Prolactin With Cardiometabolic Risk Markers in Women With Polycystic Ovary Syndrome: A Phenotype-Based Analysis”. Anatolian Current Medical Journal 8/5 (September 1, 2026): 1047-1054. https://izlik.org/JA73HH32RY.

JAMA

1.Çalışkan Burgucu H, Yılmaz Kaya E, Yümlü A, Korkmaz M, Geyik Bayman M, Aksu O. Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis. Anatolian Curr Med J / ACMJ / acmj. 2026;8:1047–1054.

MLA

Çalışkan Burgucu, Hatice, et al. “Association of Prolactin With Cardiometabolic Risk Markers in Women With Polycystic Ovary Syndrome: A Phenotype-Based Analysis”. Anatolian Current Medical Journal, vol. 8, no. 5, Sept. 2026, pp. 1047-54, https://izlik.org/JA73HH32RY.

Vancouver

1.Hatice Çalışkan Burgucu, Emel Yılmaz Kaya, Ayşen Yümlü, Mehmet Korkmaz, Melike Geyik Bayman, Oğuzhan Aksu. Association of prolactin with cardiometabolic risk markers in women with polycystic ovary syndrome: a phenotype-based analysis. Anatolian Curr Med J / ACMJ / acmj [Internet]. 2026 Sep. 1;8(5):1047-54. Available from: https://izlik.org/JA73HH32RY