Background

There is inconsistent evidence for the causal role of serum insulin-like growth factor-1 (IGF-1) concentration in the pathogenesis of human age-related diseases such as type 2 diabetes (T2D). Here, we investigated the association between IGF-1 and T2D using (clustered) Mendelian randomization (MR) analyses in the UK Biobank.

Methods

We conducted Cox proportional hazard analyses in 451 232 European-ancestry individuals of the UK Biobank (55.3% women, mean age at recruitment 56.6 years), among which 13 247 individuals developed type 2 diabetes during up to 12 years of follow-up. In addition, we conducted two-sample MR analyses based on independent single nucleotide polymorphisms (SNPs) associated with IGF-1. Given the heterogeneity between the MR effect estimates of individual instruments (P-value for Q statistic = 4.03e-145), we also conducted clustered MR analyses. Biological pathway analyses of the identified clusters were performed by over-representation analyses.

Results

In the Cox proportional hazard models, with IGF-1 concentrations stratified in quintiles, we observed that participants in the lowest quintile had the highest relative risk of type 2 diabetes [hazard ratio (HR): 1.31; 95% CI: 1.23-1.39). In contrast, in the two-sample MR analyses, higher genetically influenced IGF-1 was associated with a higher risk of type 2 diabetes. Based on the heterogeneous distribution of MR effect estimates of individual instruments, six clusters of genetically determined IGF-1 associated either with a lower or a higher risk of type 2 diabetes were identified. The main clusters in which a higher IGF-1 was associated with a lower risk of type 2 diabetes consisted of instruments mapping to genes in the growth hormone signalling pathway, whereas the main clusters in which a higher IGF-1 was associated with a higher risk of type 2 diabetes consisted of instruments mapping to genes in pathways related to amino acid metabolism and genomic integrity.

Conclusions

The IGF-1-associated SNPs used as genetic instruments in MR analyses showed a heterogeneous distribution of MR effect estimates on the risk of type 2 diabetes. This was likely explained by differences in the underlying molecular pathways that increase IGF-1 concentration and differentially mediate the effects of IGF-1 on type 2 diabetes.

© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.