Genome wide association study of premorbid disease histories converging on chronic kidney disease in individuals with and without comorbid type 2 diabetes from the UK Biobank

Research output: Contribution to journalMeeting Abstractpeer-review

Abstract

Background and aims: Chronic kidney disease (CKD) affects 10% of adults. Diabetes is the leading cause of CKD and approximately one third of adults with type 2 diabetes mellitus (T2DM) go on to develop CKD. T2DM patients with CKD frequently experience adverse events and mortality is 10-fold higher for T2DM patients with CKD than without. The comorbidity burden experienced by patients with CKD is high and improvement of the health outcomes of individuals with CKD requires consideration of comorbidities. There is a clear need to improve phenotyping of interactions between CKD and comorbidities to identify and better treat patients with a high risk of hospitalisation and mortality.

Materials and methods: We analysed UK Biobank primary and secondary care diagnosis data for 207,406 patients, which includes the timing of each diagnosis, to assess the impact of the timing and order of comorbidity development. Cox models were used to identify comorbidities that increase the risk of CKD after T2DM diagnosis and this was compared to non-diabetic patients.

Results: We identified 18,805 participants with evidence of CKD stage 3 and above. Of these, 4,184 (22.2%) had a diagnosis of T2DM and 14,621 (77.8%) had no T2DM diagnosis before or after CKD diagnosis. We removed 1458 patients with evidence of T2DM development after CKD diagnosis from analysis, leaving 2,726 participants with premorbid T2DM at their CKD diagnosis. We identified 18 premorbid comorbidities that significantly increased the risk of CKD development in both T2DM and non-diabetic patients. These premorbid comorbidities were broad, affecting cardiometabolic, blood, eye, respiratory, digestive and sleep disorders. Genome-wide association studies (GWAS) were performed on each cohort with a premorbid comorbidity for CKD. We identified 59 SNPs conditionally associated (P-value < 5x10-8) with CKD in a number of previously unexplored disease contexts exhibiting increased CKD risk including cataracts (2 SNPs), hypotension (1 SNPs), pneumonia (2 SNPs), gastritis (2 SNPs), and peripheral vascular disease (2 SNPs). We undertook validation by replicating the identified loci-CKD associations in the ~270,000 individuals of the UK Biobank initially excluded because only secondary care data was available. Loci associated with premorbid comorbidities were identified that may mediate their shared and unique genetic impact on CKD risk. The identification of non-cardiovascular-mediated genetic risk indicates that genetic interactions between CKD and comorbidities extend beyond traditionally associated diseases.

Conclusion: We identified genetic variants associated with CKD risk in previously unexplored premorbid disease contexts increasing risk of CKD development. This work provides a genetic foundation for the investigation of how comorbidities affect the development of CKD and could be used to discover potential biomarkers and/or drug targets for CKD.
Original languageEnglish
Article number873
Pages (from-to)S448-S449
JournalDiabetologia
Volume66
Issue numberSuppl 1
DOIs
Publication statusPublished online - 4 Sept 2023
EventEASD Annual Meeting - Hamburg Exhibition and Congress, Hamburg, Germany
Duration: 2 Oct 20236 Oct 2023
Conference number: 59
https://www.easd.org/annual-meeting/easd-2023.html

Keywords

  • Multimorbidity
  • GWAS
  • CKD
  • Diabetes
  • T2DM
  • UK Biobank
  • Biomarker
  • Biomarker Discovery

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