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Articles by B Hedblad
Total Records ( 2 ) for B Hedblad
  S Enhorning , T. J Wang , P. M Nilsson , P Almgren , B Hedblad , G Berglund , J Struck , N. G Morgenthaler , A Bergmann , E Lindholm , L Groop , V Lyssenko , M Orho Melander , C Newton Cheh and O. Melander
 

Background— Animal studies suggest that the arginine vasopressin system may play a role in glucose metabolism, but data from humans are limited.

Methods and Results— We analyzed plasma copeptin (copeptin), a stable C-terminal fragment of the arginine vasopressin prohormone. Using baseline and longitudinal data from a Swedish population-based sample (n=4742; mean age, 58 years; 60% women) and multivariable logistic regression, we examined the association of increasing quartiles of copeptin (lowest quartile as reference) with prevalent diabetes mellitus at baseline, insulin resistance (top quartile of fasting plasma insulin among nondiabetic subjects), and incident diabetes mellitus on long-term follow-up. New-onset diabetes mellitus was ascertained through 3 national and regional registers. All models were adjusted for clinical and anthropometric risk factors, cystatin C, and C-reactive protein. In cross-sectional analyses, increasing copeptin was associated with prevalent diabetes mellitus (P=0.04) and insulin resistance (P<0.001). During 12.6 years of follow-up, 174 subjects (4%) developed new-onset diabetes mellitus. The odds of developing diabetes mellitus increased across increasing quartiles of copeptin, even after additional adjustment for baseline fasting glucose and insulin (adjusted odds ratios, 1.0, 1.37, 1.79, and 2.09; P for trend=0.004). The association with incident diabetes mellitus remained significant in analyses restricted to subjects with fasting whole blood glucose <5.4 mmol/L at baseline (adjusted odds ratios, 1.0, 1.80, 1.92, and 3.48; P=0.001).

Conclusions— Elevated copeptin predicts increased risk for diabetes mellitus independently of established clinical risk factors, including fasting glucose and insulin. These findings could have implications for risk assessment, novel antidiabetic treatments, and metabolic side effects from arginine vasopressin system modulation.

  J. G Smith , O Melander , H Lovkvist , B Hedblad , G Engstrom , P Nilsson , J Carlson , G Berglund , B Norrving and A. Lindgren
 

Background— Epidemiological studies indicate a genetic contribution to ischemic stroke risk, but specific genetic variants remain unknown, with the exception of a few rare variants. Recent genome-wide association studies identified and replicated common genetic variants on chromosome 9p21 to confer risk of coronary heart disease. We examined whether these variants are associated with ischemic stroke.

Methods and Results— We genotyped 6 common genetic variants on chromosome 9p21, previously associated with coronary artery disease in genome-wide association studies, in 2 population-based studies in southern Sweden, the Lund Stroke Register (n=1837 cases, 947 controls) and the Malmö Diet and Cancer study (MDC; n=888 cases, 893 controls). We examined association in each study and in the pooled dataset. Adjustments were made for cardiovascular risk factors and further for previous myocardial infarction in MDC. We found a modest increase in ischemic stroke risk for 2 common (minor allele frequencies 0.46 to 0.49) variants, rs2383207 (P=0.04 in Lund Stroke Register, P=0.01 in MDC) and rs10757274 (P=0.03 in Lund Stroke Register, P=0.03 in MDC), in each sample independently. The strength of the association increased when samples were pooled with an odds ratio of 1.15 (95% CI, 1.05 to 1.25; P=0.002) for the strongest variant rs2383207. Results were similar after adjustment for clinical covariates. rs1333049 also showed significant association in MDC, which increased in the pooled sample (P=0.004).

Conclusions— In this large sample (n=4565), we detected common genetic determinants for ischemic stroke on chromosome 9p21. Our findings indicate that ischemic stroke shares pathophysiological determinants with coronary heart disease and other arterial diseases and highlight the need for large sample sizes in stroke genetics.

 
 
 
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