Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis

Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors th...

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Vydané v:	Metabolism, clinical and experimental Ročník 63; číslo 8; s. 1071 - 1077
Hlavní autori:	Stuckey, Bronwyn G.A., Opie, Nicole, Cussons, Andrea J., Watts, Gerald F., Burke, Valerie
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY Elsevier Inc 01.08.2014 Elsevier
Predmet:	Adult Biological and medical sciences Cardiovascular Diseases - epidemiology Cluster Analysis Cohort Studies Endocrinology & Metabolism Feeding. Feeding behavior Female Female genital diseases Fundamental and applied biological sciences. Psychology Gynecology. Andrology. Obstetrics Humans Hypoglycemic Agents - therapeutic use Insulin resistance Medical sciences Metabolic syndrome Metformin - therapeutic use Non tumoral diseases Polycystic ovary syndrome Polycystic Ovary Syndrome - drug therapy Polycystic Ovary Syndrome - epidemiology Polycystic Ovary Syndrome - metabolism Principal Component Analysis Risk Factors Vertebrates: anatomy and physiology, studies on body, several organs or systems Young Adult Polycystic ovary syndrome 17-OHP CAH Metabolic syndrome E2 PCA HDL PCOS DHEAS LDL Insulin resistance FSH HOMA LH SHBG GnRH AMH BMI Principal component analysis congenital adrenal hyperplasia polycystic ovary syndrome anti-Mullerian hormone follicle stimulating hormone luteinising hormone body mass index oestradiol high density lipoprotein cholesterol homeostatic model assessment sex hormone binding globulin dihydroepiandrosterone sulphate 17-hydroxy progesterone principal component analysis low density lipoprotein cholesterol gonadotrophin releasing hormone Ovarian diseases Metabolic disorder Cyst Female sterility Benign neoplasm Polycystic ovary Endocrinology Female genital diseases
ISSN:	0026-0495, 1532-8600, 1532-8600
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Shrnutí:	Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors that may delineate subgroups within PCOS or suggest pathogenetic mechanisms. We used principal component analysis (PCA) to examine the endocrine and cardiometabolic variables associated with PCOS defined by the National Institutes of Health (NIH) criteria. Data were retrieved from the database of a single clinical endocrinologist. We included women with PCOS (N=378) who were not taking the oral contraceptive pill or other sex hormones, lipid lowering medication, metformin or other medication that could influence the variables of interest. PCA was performed retaining those factors with eigenvalues of at least 1.0. Varimax rotation was used to produce interpretable factors. We identified three principal components. In component 1, the dominant variables were homeostatic model assessment (HOMA) index, body mass index (BMI), high density lipoprotein (HDL) cholesterol and sex hormone binding globulin (SHBG); in component 2, systolic blood pressure, low density lipoprotein (LDL) cholesterol and triglycerides; in component 3, total testosterone and LH/FSH ratio. These components explained 37%, 13% and 11% of the variance in the PCOS cohort respectively. Multiple correlated variables from patients with PCOS can be reduced to three uncorrelated components characterised by insulin resistance, dyslipidaemia/hypertension or hyperandrogenaemia. Clustering of risk factors is consistent with different pathogenetic pathways within PCOS and/or differing cardiometabolic outcomes.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0026-0495 1532-8600 1532-8600
DOI:	10.1016/j.metabol.2014.05.004