Albuminuria-Related Genetic Biomarkers: Replication and Predictive Evaluation in Individuals with and without Diabetes from the UK Biobank

Author:

Cañadas-Garre Marisa1234ORCID,Kunzmann Andrew T.5,Anderson Kerry1,Brennan Eoin P.6,Doyle Ross678,Patterson Christopher C.1ORCID,Godson Catherine67,Maxwell Alexander P.19ORCID,McKnight Amy Jayne1

Affiliation:

1. Molecular Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast BT12 6BA, UK

2. Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer-University of Granada-Andalusian Regional Government, PTS Granada, Avenida de la Ilustración 114, 18016 Granada, Spain

3. Hematology Department, Hospital Universitario Virgen de las Nieves, Avenida de las Fuerzas Armadas 2, 18014 Granada, Spain

4. Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), Avenida de Madrid, 15, 18012 Granada, Spain

5. Cancer Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast BT12 6BA, UK

6. UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, D04 V1W8 Dublin, Ireland

7. School of Medicine, University College Dublin, Health Sciences Centre, Belfield, D04 V1W8 Dublin, Ireland

8. Mater Misericordiae University Hospital, Eccles St., D07 R2WY Dublin, Ireland

9. Regional Nephrology Unit, Level 11, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, UK

Abstract

Increased albuminuria indicates underlying glomerular pathology and is associated with worse renal disease outcomes, especially in diabetic kidney disease. Many single nucleotide polymorphisms (SNPs), associated with albuminuria, could be potentially useful to construct polygenic risk scores (PRSs) for kidney disease. We investigated the diagnostic accuracy of SNPs, previously associated with albuminuria-related traits, on albuminuria and renal injury in the UK Biobank population, with a particular interest in diabetes. Multivariable logistic regression was used to evaluate the influence of 91 SNPs on urine albumin-to-creatinine ratio (UACR)-related traits and kidney damage (any pathology indicating renal injury), stratifying by diabetes. Weighted PRSs for microalbuminuria and UACR from previous studies were used to calculate the area under the receiver operating characteristic curve (AUROC). CUBN-rs1801239 and DDR1-rs116772905 were associated with all the UACR-derived phenotypes, in both the overall and non-diabetic cohorts, but not with kidney damage. Several SNPs demonstrated different effects in individuals with diabetes compared to those without. SNPs did not improve the AUROC over currently used clinical variables. Many SNPs are associated with UACR or renal injury, suggesting a role in kidney dysfunction, dependent on the presence of diabetes in some cases. However, individual SNPs or PRSs did not improve the diagnostic accuracy for albuminuria or renal injury compared to standard clinical variables.

Funder

Science Foundation Ireland and the Department for the Economy, Northern Ireland partnership

Science Foundation Ireland and the Department for the Economy, Northern Ireland Investigator Program Partnership

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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