Associations between PCSK9 gene missense variants, blood glucose and type 2 diabetes

Zhanna Balkhiyarova; Yinglai Qi; Vincent Pascat; Yevhenia Sharhorodksa; Alessia David; Ben Jones; Inga Prokopenko; Chioma Izzi-Engbeaya

doi:10.1530/endoabs.109.OC6.4

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Endocrine Abstracts (2025) 109 OC6.4 | DOI: 10.1530/endoabs.109.OC6.4

SFEBES2025 Oral Communications Metabolism, Obesity and Diabetes (6 abstracts)

Associations between PCSK9 gene missense variants, blood glucose and type 2 diabetes

Zhanna Balkhiyarova ¹ , Yinglai Qi ² , Vincent Pascat ² , Yevhenia Sharhorodksa ¹ , Alessia David ² , Ben Jones ² , Inga Prokopenko ¹ & Chioma Izzi-Engbeaya ²

Author affiliations

¹University of Surrey, Guilford, United Kingdom; ²Imperial College London, London, United Kingdom

Background: Lipid-lowering medication has dramatically reduced cardiovascular events and associated mortality. Statins (HMG-CoA reductase (HMGCR) inhibitors), the most widely used class of lipid-lowering medication, are associated with an increased risk of new onset type 2 diabetes. Similarly, inactivating mutations in HMGCR are associated with an increased risk of new onset type 2 diabetes. Medications that inhibit the activity or production of proprotein convertase subtilisin/kexin type 9 (PCSK9) are novel agents that potently lower cholesterol. Conflicting data about reduced PCSK9 activity and the risk of developing type 2 diabetes have been reported in the literature. Exploring genetic factors may provide additional insights and inform clinical practice.

Aim: To evaluate the relationship between genetic variants in PCSK9 and type 2 diabetes.

Methods: Using the UK Biobank dataset, we performed single-variant analyses and utilised regression (PLINK), Burden, SKAT, SKAT-O tests and hierarchical clustering to test for associations between PCSK9 missense SNPs and metabolic traits (LDL cholesterol, random glucose and type 2 diabetes) in 469,835 individuals with whole-exome sequencing data.

Results: Single-variant association analysis revealed associations between rs374014696 (Ala242Val, OR [95% CI] 0.51 [0.40-0.65], P = 1.022×10⁻⁷) and rs773660398 (Ala44Thr, OR: 1.50 [1.26-1.78], P = 6.735×10⁻⁶) alternative alleles and higher random glucose values. Clustering and burden tests highlighted three distinct clusters of PCSK9 missense variants. Cluster 1 variants were associated with lower LDL and higher glucose levels. Cluster 2 variants were associated with lower risk of type 2 diabetes. Cluster 3 variants were associated with lower LDL levels, higher glucose levels and higher risk of type 2 diabetes.

Conclusions: Our data suggest that a proportion of coding missense PCSK9 gene variants are associated with lower cholesterol levels, higher random glucose levels and increased risk of type 2 diabetes. Further research is required to determine if similar risks are present in more diverse populations.