title: Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis.
abstract: BACKGROUND
  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.
  
  
  OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Keogh Institute for Medical Research, Nedlands, Western Australia, Australia; Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia; School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia. Electronic address: bronwyn.stuckey@uwa.edu.au.
authors.forename: Bronwyn G A
authors.initials: BG
authors.lastname: Stuckey
authors.affiliation: Keogh Institute for Medical Research, Nedlands, Western Australia, Australia.
authors.forename: Nicole
authors.initials: N
authors.lastname: Opie
authors.affiliation: Department of Endocrinology and Diabetes, Royal Perth Hospital, Perth, Western Australia, Australia.
authors.forename: Andrea J
authors.initials: AJ
authors.lastname: Cussons
authors.affiliation: School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia.
authors.forename: Gerald F
authors.initials: GF
authors.lastname: Watts
authors.affiliation: School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia.
authors.forename: Valerie
authors.initials: V
authors.lastname: Burke
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D016000:Cluster Analysis; D015331:Cohort Studies; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D008687:Metformin / Q000627:therapeutic use; D011085:Polycystic Ovary Syndrome / Q000188:drug therapy / Q000453:epidemiology / Q000378:metabolism*; D025341:Principal Component Analysis; D012307:Risk Factors; D055815:Young Adult
chemical_list: D007004:Hypoglycemic Agents; D008687:Metformin
keywords: Insulin resistance; Metabolic syndrome; Polycystic ovary syndrome; Principal component analysis