Perimenopozal Polikistik Over Sendromlu Kadınlarda Monosit/HDL Oranının, Lipid Birikim Ürünleri, Karotis İntima Media Kalınlığı ve SCORE2 Kardiyovasküler Risk Hesaplama Sistemi Skoru ile Karşılaştırılması

Abstract

ÖZ Amaç: Polikistik over sendromu (PCOS), reprodüktif çağdaki kadınların en sık görülen endokrin hastalığıdır ve ilerleyen yaşlarda kardiyovasküler hastalık riskinde artış ile ilişkilendirilmiş bir çok komorbiditeye yol açmaktadır. Bu çalışma, kardiyovasküler risk faktörleri ile daha önceden ilişkilendirilmiş belirteçlerle monosit/HDL oranı (MHR) arasındaki potansiyel ilişkiyi belirlemeyi amaçlamaktadır. Gereç ve Yöntem: Kesitsel olarak tasarlanan bu çalışma, 40 tane menopozal geçiş dönemindeki PCOS tanısı almış hasta ile yaş ve beden kitle indeksi (BMI) açısından eşleşmiş 40 PCOS olmayan hasta üzerinde yürütülmüştür. Demografik ve antropometrik ölçümler, lipid profilleri, karotis intima-media kalınlığı (CIMT), serbest androjen indeksi (FAI), lipid birikim ürünleri (LAP) indeksi, homeostasis model assessment-insulin resistance (HOMA-IR), MHR ve SCORE2 risk skorları iki grup arasında karşılaştırılmıştır. Bulgular: Yapılan istatistik analizde; yaş, BMI, sigara içiciliği, lipid profilleri, açlık glukozu ve insülin seviyeleri, MHR, LAP indeksi, HOMA-IR değerleri ve SCORE2 skorları açısından anlamlı fark bulunamamıştır. Ancak, seks hormon bağlayıcı globulin ve total testosteron seviyeleri PCOS grubunda istatistiki anlamlı yüksek bulunmuştur (p<0,001). Metabolik sendrom oranları, FAI ve CIMT ölçümleri PCOS grubunda istatistiki anlamlı olacak şekilde yüksek bulunmuştur (sırasıyla p= 0,045; 0,003; 0,022). MHR; LAP indeksi, HOMA-IR, FAI değerleri ve CIMT ölçümleri ile pozitif korele bulunmuştur (sırasıyla r= 0,235; 0,297; 0,28; 0,215). Sonuç: PCOS hastası kadınlar, BMI açısından eşleştirilmiş PCOS olmayan yaşıtlarına göre artmış metabolik sendrom ve ortalama CIMT ölçümlerine sahiptir. Kardiyovasküler riskle ilişkisi daha önceden bilinen parametrelerle MHR arasındaki pozitif korelasyon değerleri, bu popülasyondaki kardiyovasküler risk faktörlerini değerlendirme konusunda dikkat çekmektedir ve perimenopozal PCOS hastalarında MHR’nin diğer kardiyovasküler risk prediktörlerine oranla çok daha ucuz bir prediktör olarak kullanılabilirliğini göstermektedir.

Keywords

• polikistik over sendromu
• monosit/HDL oranı
• lipid birikim ürünleri indeksi
• HOMA-IR
• karotis intima-media kalınlığı

Carotis Intima-Media Thickness, Lipid Accumulation Product Index, Cardiovascular Risk Calculation Score and Their Relationship with Monocyte to HDL Ratio in Middle-Aged Women with Polycystic Ovary Syndrome

Abstract

ABSTRACT Objectives: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women in the reproductive age and also associated with many comorbidities that increase the risk of cardiovascular disease in later ages. This study explores the potential correlation between the monocyte to HDL ratio (MHR) and established cardiovascular risk factors in women with PCOS. Material and method: This cross-sectional analysis includes PCOS-diagnosed women (n=40) in menopausal transition over 40 years old, and a control group of non-PCOS healthy women (n=40) matched for age and body-mass index (BMI). Various parameters, including demographic and anthropometric measurements, lipid profiles, carotis intima-media thickness (CIMT), free androgen index (FAI), lipid accumulation product (LAP) index, homeostasis model assessment-insulin resistance (HOMA-IR), MHR, and SCORE2 risk scores were compared between the groups. Results: Results indicate no significant differences in age, BMI, smoking, lipid profiles, fasting glucose, insulin levels, MHR, LAP index, HOMA-IR, and SCORE2 scores. However, sex-hormone binding globulin and total testosterone were higher in the PCOS group (p<0.001). Metabolic syndrome rates, FAI, and average CIMT were notably higher in the PCOS group (p=0.045, p=0.003, p=0.022). MHR was positively correlated with LAP index, HOMA-IR, FAI, and left CIMT (r=0.235; r=0.297; r=0.28; r=0.215; respectively). Conclusion: In conclusion, PCOS women exhibit higher metabolic syndrome rates and average CIMT measurements compared to healthy age and BMI matched counterparts. Positive correlations of the MHR with various risk factors emphasize the importance of assessing cardiovascular risk in this population and shows that MHR can be used as a much cheaper predictor of cardiovascular risk compared to other predictors in perimenopausal PCOS patients.

Keywords

• polycystic ovary syndrome
• monocyte to hdl ratio
• lipid accumulation product index
• homa-ir
• carotid intima-media thickness

References

1. 1. Yildiz BO, Bozdag G, Yapici Z, Esinler I, Yarali H. Prevalence, phenotype and cardiometabolic risk of polycystic ovary syndrome under different diagnostic criteria. Hum Reprod Oxf Engl. 2012;27(10):3067–73.
2. 2. Umland EM, Klootwyk J. Menstruation-Related Disorders. In: DiPiro JT, Talbert RL, Yee GC, Matzke GR, Wells BG, Posey LM, editors. Pharmacotherapy: A Pathophysiologic Approach, 10e [Internet]. New York, NY: McGraw-Hill Education; 2017 [cited 2022 Jun 18]. Available from: accesspharmacy.mhmedical.com/content.aspx?aid=1145817247
3. 3. Legro RS. Polycystic Ovary Syndrome and Cardiovascular Disease: A Premature Association? Endocr Rev. 2003;24(3):302–12.
4. 4. DeUgarte CM, Bartolucci AA, Azziz R. Prevalence of insulin resistance in the polycystic ovary syndrome using the homeostasis model assessment. Fertil Steril. 2005;83(5):1454–60.
5. 5. Strowitzki T, Capp E, von Eye Corleta H. The degree of cycle irregularity correlates with the grade of endocrine and metabolic disorders in PCOS patients. Eur J Obstet Gynecol Reprod Biol. 2010;149(2):178–81.
6. 6. 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):1726–31.
7. 7. Chiang JK, Koo M. Lipid accumulation product: a simple and accurate index for predicting metabolic syndrome in Taiwanese people aged 50 and over. BMC Cardiovasc Disord. 2012;12(1):78.
8. 8. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24(11):987–1003.

9. 9. SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021;42(25):2439–54.
10. 10. Naqvi TZ, Lee MS. Carotid intima-media thickness and plaque in cardiovascular risk assessment. JACC Cardiovasc Imaging. 2014;7(10):1025–38.
11. 11. Jabbour R, Ott J, Eppel W, Frigo P. Carotid intima-media thickness in polycystic ovary syndrome and its association with hormone and lipid profiles. PloS One. 2020;15(4):e0232299.
12. 12. Usta A, Avci E, Bulbul CB, Kadi H, Adali E. The monocyte counts to HDL cholesterol ratio in obese and lean patients with polycystic ovary syndrome. Reprod Biol Endocrinol. 2018;16(1):34.
13. 13. Dobbelsteyn CJ, Joffres MR, MacLean DR, Flowerdew G. A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors. The Canadian Heart Health Surveys. Int J Obes. 2001;25(5):652–61.
14. 14. Al Kindi MK, Al Essry FS, Al Essry FS, Mula-Abed WAS. Validity of Serum Testosterone, Free Androgen Index, and Calculated Free Testosterone in Women with Suspected Hyperandrogenism. Oman Med J. 2012 ;27(6):471–4.
15. 15. Wallace TM, Matthews DR. The assessment of insulin resistance in man. Diabet Med J Br Diabet Assoc. 2002;19(7):527–34.
16. 16. Nascimento JXPT, Chein MB da C, de Sousa RML, Ferreira A dos S, Navarro PA, Brito LMO. Importance of lipid accumulation product index as a marker of CVD risk in PCOS women. Lipids Health Dis. 2015 ;14(1):62.
17. 17. Grau M, Subirana I, Marrugat J, Elosua R. Percentiles of Carotid Intima-media Thickness in a Spanish Population With and Without Cardiovascular Risk Factors. Rev Esp Cardiol Engl Ed. 2013 ;66(9):749–51.
18. 18. Dincgez Cakmak B, Dundar B, Ketenci Gencer F, Aydin BB, Yildiz DE. TWEAK and monocyte to HDL ratio as a predictor of metabolic syndrome in patients with polycystic ovary syndrome. Gynecol Endocrinol Off J Int Soc Gynecol Endocrinol. 2019;35(1):66–71.
19. 19. Zhao L, Zhu Z, Lou H, Zhu G, Huang W, Zhang S, et al. Polycystic ovary syndrome (PCOS) and the risk of coronary heart disease (CHD): a meta-analysis. Oncotarget. 2016;7(23):33715–21.
20. 20. Çelik Ö, Köse MF. An overview of polycystic ovary syndrome in aging women. J Turk-Ger Gynecol Assoc. 2021;22(4):326–33.
21. 21. Wild S, Pierpoint T, McKeigue P, Jacobs H. Cardiovascular disease in women with polycystic ovary syndrome at long-term follow-up: a retrospective cohort study. Clin Endocrinol (Oxf). 2000;52(5):595–600.
22. 22. Lo JC, Feigenbaum SL, Yang J, Pressman AR, Selby JV, Go AS. Epidemiology and adverse cardiovascular risk profile of diagnosed polycystic ovary syndrome. J Clin Endocrinol Metab. 2006;91(4):1357–63.
23. 23. Zhang DP, Baituola G, Wu TT, Chen Y, Hou XG, Yang Y, et al. An elevated monocyte-to-high-density lipoprotein–cholesterol ratio is associated with mortality in patients with coronary artery disease who have undergone PCI. Biosci Rep. 2020;40(8):BSR20201108.
24. 24. Herkiloglu D, Gokce S. Correlation of monocyte/HDL ratio (MHR) with inflammatory parameters in obese patients diagnosed with polycystic ovary syndrome. Ginekol Pol. 2021;92(8):537–43.
25. 25. Cakir I, Yasin Simsek. Total cholesterol/HDL cholesterol ratio and monocyte/HDL cholesterol ratio are related with subclinical hypothyroidism in polycystic ovary syndrome. Turk J Biochem. 47(1, 2022):65–9.
26. 26. Gürbüz T, Okçu NT, Güngör ND. Monocyte/HDL ratio in women with polycystic ovary syndrome and healthy controls. Anatol Curr Med J. 2021;3(2):98–103.
27. 27. Soysal C, Bıyık İ, İnce O, Erten Ö, Taşçı Y, Keskin N. Comparison of the different PCOS phenotypes based on monocyte to HDL cholesterol ratio. J Obstet Gynaecol. 2022 Feb 14;1–6.
28. 28. Kałużna M, Człapka-Matyasik M, Wachowiak-Ochmańska K, Moczko J, Kaczmarek J, Janicki A, et al. Effect of Central Obesity and Hyperandrogenism on Selected Inflammatory Markers in Patients with PCOS: A WHtR-Matched Case-Control Study. J Clin Med. 2020;9(9):3024.
29. 29. Meyer ML, Malek AM, Wild RA, Korytkowski MT, Talbott EO. Carotid artery intima-media thickness in polycystic ovary syndrome: a systematic review and meta-analysis. Hum Reprod Update. 2012;18(2):112–26.
30. 30. Luo X, Yang Y, Cao T, Li Z. Differences in left and right carotid intima-media thickness and the associated risk factors. Clin Radiol. 2011;66(5):393–8.
31. 31. Zhu ZQ, Chen LS, Wang H, Liu FM, Luan Y, Wu LL, et al. Carotid stiffness and atherosclerotic risk: non-invasive quantification with ultrafast ultrasound pulse wave velocity. Eur Radiol. 2019 ;29(3):1507–17.
32. 32. Barrea L, Arnone A, Annunziata G, Muscogiuri G, Laudisio D, Salzano C, et al. Adherence to the Mediterranean Diet, Dietary Patterns and Body Composition in Women with Polycystic Ovary Syndrome (PCOS). Nutrients. 2019;11(10):2278.
33. 33. Polotsky AJ, Allshouse A, Crawford SL, Harlow SD, Khalil N, Santoro N, et al. Relative contributions of oligomenorrhea and hyperandrogenemia to the risk of metabolic syndrome in midlife women. J Clin Endocrinol Metab. 2012;97(6):E868-877.
34. 34. Hosseinpanah F, Barzin M, Erfani H, Serahati S, Ramezani Tehrani F, Azizi F. Lipid accumulation product and insulin resistance in Iranian PCOS prevalence study. Clin Endocrinol (Oxf). 2014;81(1):52–7.
35. 35. Anık İlhan G, Yıldızhan B. Visceral adiposity indicators as predictors of metabolic syndrome in postmenopausal women. Turk J Obstet Gynecol. 2019;16(3):164–8.
36. 36. Kokosar M, Benrick A, Perfilyev A, Fornes R, Nilsson E, Maliqueo M, et al. Epigenetic and Transcriptional Alterations in Human Adipose Tissue of Polycystic Ovary Syndrome. Sci Rep. 2016;6:22883.
37. 37. Yu R, Kim CS, Kwon BS, Kawada T. Mesenteric Adipose Tissue-Derived Monocyte Chemoattractant Protein-1 Plays a Crucial Role in Adipose Tissue Macrophage Migration and Activation in Obese Mice. Obesity. 2006;14(8):1353–62.
38. 38. Hard Coronary Heart Disease (10-year risk) | Framingham Heart Study [Internet]. [cited 2022 Jun 24]. Available from: https://www.framinghamheartstudy.org/fhs-risk-functions/hard-coronary-heart-disease-10-year-risk/
39. 39. Günaydın ZY, Karagöz A, Bektaş O, Kaya A, Kırış T, Erdoğan G, et al. Comparison of the Framingham risk and SCORE models in predicting the presence and severity of coronary artery disease considering SYNTAX score. Anatol J Cardiol. 2016;16(6):412–8.