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Kidney Week

Abstract: FR-OR42

Proteome-Wide and Transcriptome-Wide Association Studies of Kidney Function

Session Information

Category: Pathology and Lab Medicine

  • 1600 Pathology and Lab Medicine

Authors

  • Schlosser, Pascal, Johns Hopkins University Department of Epidemiology, Baltimore, United States
  • Zhang, Jingning, Johns Hopkins University Department of Biostatistics, Baltimore, Maryland, United States
  • Liu, Hongbo, Department of Medicine and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Surapaneni, Aditya L., Johns Hopkins University Welch Center for Prevention Epidemiology and Clinical Research, Baltimore, Maryland, United States
  • Yu, Bing, The University of Texas Health Science Center at Houston, Houston, Texas, United States
  • Boerwinkle, Eric, The University of Texas Health Science Center at Houston, Houston, Texas, United States
  • Chatterjee, Nilanjan, Johns Hopkins University Department of Biostatistics, Baltimore, Maryland, United States
  • Susztak, Katalin, Department of Medicine and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Kottgen, Anna, Johns Hopkins University Department of Epidemiology, Baltimore, United States
  • Coresh, Josef, Johns Hopkins University Department of Epidemiology, Baltimore, Maryland, United States
  • Grams, Morgan, Johns Hopkins University Department of Epidemiology, Baltimore, Maryland, United States
Background

Large-scale genome-wide association studies (GWAS) have implicated 424 loci associated with eGFR based on creatinine (eGFRcr), including 320 also associated with eGFR based on cystatin C (eGFRcys). However, the mechanisms by which genetic variation in these loci lead to differences in kidney function remain largely unknown. Combining genetic association statistics from GWAS of eGFR with those from the plasma proteome and gene expression in multiple tissues can reveal potentially causal genes and proteins affecting kidney function.

Methods

We applied proteome-wide association studies (PWAS) for eGFRcr and eGFRcys using summary-statistics from the CKDGen Consortium (EA, NeGFRcr=1,004,041; NeGFRcys=460,826) and 1,318 genetic plasma protein level prediction models developed in the Atherosclerosis Risk in Communities (ARIC) study (N=7,213 European American (EA) participants). Similarly, we conducted transcriptome-wide association studies (TWAS) based on prediction models developed in 49 human tissues (GTEx) and from 121 kidney tubule samples.

Results

We identified 62 proteins which were associated with eGFRcr and 42 with eGFRcys (p<0.05/1,318). Of these, 19 were associated with both kidney function measures in a directionally consistent manner, nominating novel gene annotations in 18 of the 19 genetically associated regions. The enzyme isopentenyl-diphosphate delta isomerase 2 (IDI2) showed the strongest associations (peGFRcr=4.8e-37, peGFRcys=1.0e-15). TWAS identified 1,799 and 845 transcripts for eGFRcr and eGFRcys, respectively (p<0.05/235,763). Of these, 544 were associated with both kidney function measures, including 13 of the 19 PWAS genes. There were also 27 identified in kidney tubule expression, including DACH1 and MANBA, which were recently identified as contributors to kidney fibrosis.

Conclusion

We were able to consistently implicate 13 genes/proteins for eGFRcrea and eGFRcys across both PWAS and TWAS. Based on our human in vivo data these proteins are excellent candidates for downstream functional studies and for potential drug repurposing in the context of chronic kidney disease.

Funding

  • Government Support – Non-U.S.