title: Exploring genetic variants predisposing to diabetes mellitus and their association with indicators of socioeconomic status.
abstract: BACKGROUND
  The relevance of disease-related genetic variants for the explanation of social inequalities in complex diseases is unclear and empirical analyses are largely missing. The aim of our study was to examine whether genetic variants predisposing to diabetes mellitus are associated with socioeconomic status in a population-based cohort.
  
  
  METHODS
  We genotyped 11 selected diabetes-related single nucleotide polymorphisms in 4655 participants (age 45-75 years) of the Heinz Nixdorf Recall study. Diabetes status was self-reported or defined by blood glucose levels. Education, income and paternal occupation were assessed as indicators of socioeconomic status. Multiple regression analyses were used to examine the association of socioeconomic status and diabetes by estimating sex-specific and age-adjusted prevalence ratios and their corresponding 95%-confidence intervals. To explore the relationship between individual single nucleotide polymorphisms and socioeconomic status sex- and age-adjusted odds ratios were computed. We adjusted the alpha-level for multiple testing of 11 single nucleotide polymorphisms using Bonferroni's method (α(BF) ~ 0.005). In addition, we explored the association of a genetic risk score with socioeconomic status.
  
  
  RESULTS
  Social inequalities in diabetes were observed for all indicators of socioeconomic status. However, there were no significant associations between individual diabetes-related risk alleles and socioeconomic status with odds ratios ranging from 0.87 to 1.23. Similarly, the genetic risk score analysis revealed no evidence for an association.
  
  
  CONCLUSIONS
  Our data provide no evidence for an association between 11 diabetes-related risk alleles and different indicators of socioeconomic status in a population-based cohort, suggesting that the explored genetic variants do not contribute to health inequalities in diabetes.
authors.affiliation: Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstraße 55, 45147 Essen, Germany. boerge.schmidt@uk-essen.de.
authors.forename: Börge
authors.initials: B
authors.lastname: Schmidt
authors.forename: Nico
authors.initials: N
authors.lastname: Dragano
authors.forename: André
authors.initials: A
authors.lastname: Scherag
authors.forename: Sonali
authors.initials: S
authors.lastname: Pechlivanis
authors.forename: Per
authors.initials: P
authors.lastname: Hoffmann
authors.forename: Markus M
authors.initials: MM
authors.lastname: Nöthen
authors.forename: Raimund
authors.initials: R
authors.lastname: Erbel
authors.forename: Karl-Heinz
authors.initials: KH
authors.lastname: Jöckel
authors.forename: Susanne
authors.initials: S
authors.lastname: Moebus
mesh_terms: D000368:Aged; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000235:genetics; D005260:Female; D020022:Genetic Predisposition to Disease; D005858:Germany / Q000453:epidemiology; D054625:Healthcare Disparities; D006801:Humans; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D015995:Prevalence; D012307:Risk Factors; D012959:Socioeconomic Factors