In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study

Diabetologia. 2019 Nov;62(11):1998-2006. doi: 10.1007/s00125-019-4960-8. Epub 2019 Aug 24.


Aims/hypothesis: The pathogenesis of type 2 diabetes is not fully understood. We investigated whether circulating levels of preselected proteins were associated with the outcome 'diabetes' and whether these associations were causal.

Methods: In 2467 individuals of the population-based, cross-sectional EpiHealth study (45-75 years, 50% women), 249 plasma proteins were analysed by the proximity extension assay technique. DNA was genotyped using the Illumina HumanCoreExome-12 v1.0 BeadChip. Diabetes was defined as taking glucose-lowering treatment or having a fasting plasma glucose of ≥7.0 mmol/l. The associations between proteins and diabetes were assessed using logistic regression. To investigate causal relationships between proteins and diabetes, a bidirectional two-sample Mendelian randomisation was performed based on large, genome-wide association studies belonging to the DIAGRAM and MAGIC consortia, and a genome-wide association study in the EpiHealth study.

Results: Twenty-six proteins were positively associated with diabetes, including cathepsin D, retinal dehydrogenase 1, α-L-iduronidase, hydroxyacid oxidase 1 and galectin-4 (top five findings). Three proteins, lipoprotein lipase, IGF-binding protein 2 and paraoxonase 3 (PON-3), were inversely associated with diabetes. Fourteen of the proteins are novel discoveries. The Mendelian randomisation study did not disclose any significant causal effects between the proteins and diabetes in either direction that were consistent with the relationships found between the protein levels and diabetes.

Conclusions/interpretation: The 29 proteins associated with diabetes are involved in several physiological pathways, but given the power of the study no causal link was identified for those proteins tested in Mendelian randomisation. Therefore, the identified proteins are likely to be biomarkers for type 2 diabetes, rather than representing causal pathways.

Keywords: Diabetes; Genotyping; Mendelian randomisation; Proteomics; Type 2 diabetes.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Alcohol Oxidoreductases / blood
  • Aryldialkylphosphatase / blood
  • Biomarkers / blood*
  • Cathepsin D / blood
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / blood*
  • Diabetes Mellitus, Type 2 / genetics
  • Female
  • Galectin 4 / blood
  • Gene Expression Regulation*
  • Genotype*
  • Humans
  • Iduronidase / blood
  • Insulin-Like Growth Factor Binding Protein 2 / blood
  • Lipoprotein Lipase / blood
  • Male
  • Mendelian Randomization Analysis
  • Middle Aged
  • Proteomics*
  • Registries
  • Retinal Dehydrogenase / blood
  • Sweden


  • Biomarkers
  • Galectin 4
  • IGFBP2 protein, human
  • Insulin-Like Growth Factor Binding Protein 2
  • Alcohol Oxidoreductases
  • HAO1 protein, human
  • Retinal Dehydrogenase
  • LPL protein, human
  • Lipoprotein Lipase
  • Aryldialkylphosphatase
  • PON3 protein, human
  • Iduronidase
  • Cathepsin D