Kidney Week

Abstract: SA-PO793

Using an IgA Genetic Risk Score to Estimate the Prevalence and Improve Diagnosis of IgA Nephropathy

Session Information

• CKD: Epidemiology, Risk Factors, Prevention - III
  October 27, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

• 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Sukcharoen, Kittiya, Royal Devon and Exeter Foundation Trust, Exeter, United Kingdom

Kittiya Sukcharoen,

• Sharp, Seth A., University of Exeter, Exeter, United Kingdom

Seth A. Sharp,

• Kimmitt, Robert A., Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom

Robert A. Kimmitt,

• Harrison, Jamie W., University of exeter medical school, Tiverton, United Kingdom

Jamie W. Harrison,

• Bingham, Coralie, Royal Devon and Exeter Hospital, Exeter, United Kingdom

Coralie Bingham,

• Mozere, Monika, UCL, London, United Kingdom

Monika Mozere,

• Weedon, Michael, University of Exeter, Exeter, United Kingdom

Michael Weedon,

• Barratt, Jonathan, University of Leicester, Leicester, United Kingdom

Jonathan Barratt,

• Gale, Daniel P., University College London, London, United Kingdom

Daniel P. Gale,

• Oram, Richard A., University of Exeter Medical School, Exeter, United Kingdom

Richard A. Oram,

Background

IgA nephropathy(IgAN) is the commonest glomerulonephritis worldwide. It is difficult to assess true prevalence of IgAN, people with mild disease do not commonly receive a biopsy. Multiple single-nucleotide polymorphisms(SNPs) are associated with IgAN. We aimed to generate and validate an IgAN genetic risk score(GRS) and assess the excess IgAN genetic risk in people with haematuria, hypertension and microalbuminuria in UK Biobank(UKBB) to estimate the proportion of these phenotypes.

Methods

We calculated the IgAN GRS using 14 SNPs associated with IgAN in Caucasians using established methods. We generated the GRS in 464 biopsy proven IgAN from the UK Glomerulonephritis (UK GN) DNA Bank, and in 344,244 Caucasians from UKBB, using SNP array data. We accessed diagnostic codes from electronically linked healthcare records, questionnaire data and baseline albumin creatinine ratio from UKBB.
We compared the IgAN GRS in UK GN cases with healthy individuals in UKBB. We assessed the proportion of hypertension and microalbuminuria by comparing IgA GRS using this formula:
Proportion=(phenotype - control)/(IgAN - control)

Results

The IgA GRS was discriminative of IgAN v non-IgAN (Mean[95% confidence interval]) GRS 4.35 (4.26,4.41) v 3.98 (3.96,3.99); P <0.0001. UKBB participants with an ICD10 diagnosis of IgAN (N=116) GRS 4.19(4.01, 4.36) had a similar GRS to the IgA GN cohort; P=0.1 and combined score of 4.307 (4.24,4.38).
The GRS was higher in phenotypes with possible undiagnosed IgAN compared to healthy subjects, haematuria (N=13,119) GRS 4.04(4.03, 4.06); P<0.0001, haematuria and proteinuria (N=1827) GRS 4.06(4.01,4.1); P=0.002, and haematuria, hypertension and microalbuminuria (N=1431) GRS 4.07(4.02,4.11); P=0.002.
We calculated that IgA accounted for 19% (15-25) of haematuria, 22% (10-37) haematuria and microalbuminuria and 27% (13-40) haematuria, hypertension and microalbuminuria in UKBB.

Conclusion

We used a novel GRS approach to estimate the prevalence of IgAN contributing to common phenotypes that would not normally be biopsied. These data may allow a UK population estimate for the prevalence of undiagnosed IgAN. Further work is needed to assess if an IgAN GRS may be useful for individual diagnosis.

Funding

• Other NIH Support