Polygenic Risk Scores Predicting Estimated GFR Validated With Iohexol Clearance

Area of Science:

• Genetics
• Nephrology
• Biostatistics

Background:

• Genome-wide association studies (GWAS) commonly use estimated glomerular filtration rate (eGFR) as a proxy for measured glomerular filtration rate (mGFR) due to cost and complexity.
• However, eGFR is influenced by non-GFR factors, potentially introducing bias into GWAS findings.
• This study directly compares genetic effects on mGFR versus eGFR to assess this potential bias.

Purpose of the Study:

• To investigate the potential bias in GWAS results by comparing aggregate genetic effects on measured GFR (mGFR) and estimated glomerular filtration rate (eGFR).

Main Methods:

• The study analyzed 1492 individuals from the Renal Iohexol Clearance Survey (RENIS) cohort.
• Measured GFR (mGFR) was determined using iohexol clearance.
• Three published polygenic risk scores (PGS) for eGFR were compared with mGFR, assessing narrow-sense heritability (h²), and the mean effect of single nucleotide variants (SNVs).

Main Results:

• Polygenic risk scores (PGS) performed differently for mGFR and eGFR, with best prediction for eGFRcr.
• However, the magnitude of genetic effects (beta coefficients) for SNVs was 11% to 46% greater for mGFR than for eGFR across most comparisons.
• Measured GFR (mGFR) exhibited higher heritability (h² = 0.47) compared to eGFRcr (0.21), eGFRcys (0.37), and eGFRcr-cys (0.42).

Conclusions:

• Single nucleotide variants (SNVs) with non-GFR effects on creatinine and cystatin C impact GWAS results.
• The findings suggest that GWAS results derived from eGFR should be validated using more precise experimental methods.