title: Copeptin predicts coronary artery disease cardiovascular and total mortality.
abstract: OBJECTIVE
  In a middle-aged population, it was recently shown that the stable vasopressin marker plasma copeptin (copeptin) predicts development of diabetes mellitus, diabetic heart disease and death. Here, it was hypothesised whether copeptin predicts a risk of coronary artery disease (CAD), and cardiovascular mortality in an older population.
  
  
  METHODS
  Between 2002 and 2006, fasting plasma copeptin was examined and measured in 5386 participants of a population-based longitudinal study (mean age 69.4±6.2 years, 69.8% males) and related copeptin to risk of CAD (first myocardial infarction or coronary revascularisation), cardiovascular and total mortality during a mean follow-up time of 6.5 years using multivariate adjusted (age, gender, systolic blood pressure, antihypertensive therapy, smoking, diabetes, low-density lipoprotein and high-density lipoprotein cholesterol) Cox proportional hazards models.
  
  
  RESULTS
  Among subjects free from CAD at baseline, the multivariate adjusted HR (95% CI) per 1 SD increment of log-transformed copeptin for risk of CAD development was 1.20 (1.08 to 1.33) (p=0.001). There was a borderline significant interaction between diabetes and copeptin on CAD risk (p=0.08) with higher copeptin-associated risk in subjects with diabetes (1.49 (1.14 to 1.95); p=0.004) than in non-diabetic subjects (1.15 (1.02 to 1.50); p=0.02). Moreover, each SD increment of copeptin independently predicted total mortality (1.31 (1.21 to 1.41); p<0.001), an effect driven by the copeptin association with cardiovascular mortality (1.36 (1.21 to 1.53); p<0.001). The absolute risks for CAD were 4.9%, 9.3% and 2.9%, total and CV mortality were 4.9%, 9.3% and 2.9% in quartile 1, 7.1%, 9.4% and 3.5% in quartile 2, 8.3%, 14.2% and 5.6% in quartile 3, and 10.3%, 23.3% and 9.1% in quartile 4, respectively.
  
  
  CONCLUSIONS
  Copeptin predicts development of CAD and cardiovascular mortality both in diabetics and non-diabetics.
authors.affiliation: Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Irina
authors.initials: I
authors.lastname: Tasevska
authors.affiliation: Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Sofia
authors.initials: S
authors.lastname: Enhörning
authors.affiliation: Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Margaretha
authors.initials: M
authors.lastname: Persson
authors.affiliation: Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Nilsson
authors.affiliation: Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Olle
authors.initials: O
authors.lastname: Melander
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D003324:Coronary Artery Disease / Q000097:blood / Q000175:diagnosis / Q000401:mortality; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000378:metabolism; D005260:Female; D006020:Glycopeptides / Q000097:blood*; D006801:Humans; D008075:Lipoproteins, HDL / Q000097:blood*; D008077:Lipoproteins, LDL / Q000097:blood*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*; D013548:Sweden / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D006020:Glycopeptides; D008075:Lipoproteins, HDL; D008077:Lipoproteins, LDL; C048197:copeptins