Abstract: SA-PO133

Identification of Novel Genetic Factors Linked to Diabetic Nephropathy

Session Information

Category: Diabetes

  • 503 Diabetes Mellitus and Obesity: Translational

Authors

  • Guarnieri, Paolo, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Susztak, Katalin, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Qiu, Chengxiang, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Hawkins, Julie, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Hill, Jonathan, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Niu, Weiling, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Palmer, Matthew, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Yue, Yong G, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Pullen, Steven S., Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Boustany, Carine, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
Background

Diabetic nephropathy (DN) is serious kidney condition and the leading cause of chronic kidney disease in the USA contributing to 30-40 % of all end-stage renal disease cases. In order to provide a better insight into its molecular mechanism, genetic determinants and finally identify novel targets, we first generated a novel dataset from a cohort of 250 patients undergoing nephrectomy and then we analytically integrated the results with public domain data from genome-wide association studies (GWAS).

Methods

Patients in the study were genotyped using high density Axiom arrays and phenotyped using collected clinical records. Each matched kidney specimen was histologically assessed and RNA-seq transcriptionally profiled separating tubules from glomeruli.

Results

Our analysis identified several genes associated with kidney function decline (estimated glomerular filtration rate), many also responsible for the progressive increase in interstitial fibrosis and/or associated with lymphocytic infiltration. Cell type specific gene signatures used with deconvolution algorithms revealed that several immune cells, mostly T lymphocytes, are active since the early stages of the disease. Our distinctive study design enabled the first human kidney specific eQTL analysis and helped focus on genes for which expression in kidney is genetically determined either in tubules, in glomeruli or both. We completed the expression to genotype to trait associations by performing a Bayesian co-localization analysis between our results with those available from GWAS and then matched the direction of the expression change with the effect on the trait.

Conclusion

In this study we generated a high resolution tissue and disease specific transcriptome database which allowed the study of genes and processes implicated in DN.

Funding

  • Commercial Support