Genetically-proxied anti-diabetic drug target perturbation and risk of cancer: a Mendelian randomization analysis
Authors: Yarmolinsky James , Bouras Emmanouil , Constantinescu Andrei , Burrows Kimberley , Bull Caroline J , Vincent Emma E , Martin Richard M , Dimopoulou Olympia , Lewis Sarah J , Moreno Victor , Vujkovic Marijana , Chang Kyong-Mi , Voight Benjamin F , Tsao Philip S , Gunter Marc J , Hampe Jochen , Lindblom Annika , Pellatt Andrew J , Pharoah Paul D P , Schoen Robert E , Gallinger Steven , Jenkins Mark A , Pai Rish K ,   the PRACTICAL consortium,   VA Million Veteran Program, Gill Dipender , Tsilidis Kostas K 
Published: October 2022

Aims/hypothesis

Epidemiological studies have generated conflicting findings on the relationship between anti-diabetic medication use and cancer risk. Naturally occurring variation in genes encoding anti-diabetic drug targets can be used to investigate the effect of their pharmacological perturbation on cancer risk.

Methods

We developed genetic instruments for three anti-diabetic drug targets (peroxisome proliferator activated receptor gamma, PPARG; sulfonylurea receptor 1, ABCC8; glucagon-like peptide 1 receptor, GLP1R) using summary genetic association data from a genome-wide association study (GWAS) of type 2 diabetes in 69,869 cases and 127,197 controls in the Million Veteran Program. Genetic instruments were constructed usingcis-acting genome-wide significant (P<5×10−8) single-nucleotide polymorphisms (SNPs) permitted to be in weak linkage disequilibrium (r2<0.20). Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), prostate (79,148 cases, 61,106 controls), and overall (i.e. site-combined) cancer (27,483 cases, 372,016 controls). Inverse-variance weighted random-effects models adjusting for linkage disequilibrium were employed to estimate causal associations between genetically-proxied drug target perturbation and cancer risk. Colocalisation analysis was employed to examine robustness of findings to violations of Mendelian randomization (MR) assumptions. A Bonferroni correction was employed as a heuristic to define associations from MR analyses as “strong” and “weak” evidence.

Results

In Mendelian randomization analysis, genetically-proxied PPARG perturbation was weakly associated with higher risk of prostate cancer (OR for PPARG perturbation equivalent to a 1 unit decrease in inverse-rank normal transformed HbA1c: 1.75, 95% CI 1.07-2.85,P=0.02). In histological subtype-stratified analyses, genetically-proxied PPARG perturbation was weakly associated with lower risk of ER+ breast cancer (OR 0.57, 95% CI 0.38-0.85;P=6.45 × 10−3). In colocalisation analysis however, there was little evidence of shared causal variants for type 2 diabetes liability and cancer endpoints in thePPARGlocus, though these analyses were likely underpowered. There was little evidence to support associations of genetically-proxied PPARG perturbation with colorectal or overall cancer risk or genetically-proxied ABCC8 or GLP1R perturbation with risk across cancer endpoints.

Conclusions/interpretation

Our drug-target MR analyses did not find consistent evidence to support an association of genetically-proxied PPARG, ABCC8 or GLP1R perturbation with breast, colorectal, prostate or overall cancer risk. Further evaluation of these drug targets using alternative molecular epidemiological approaches may help to further corroborate the findings presented in this analysis.

Research in context

What is already known about this subject?

Anti-diabetic medication use is variably linked to both increased and decreased cancer risk in conventional epidemiological studies

It is unclear whether these associations represent causal relationships

What is the key question?

What is the association of genetically-proxied perturbation of three anti-diabetic drug targets (PPARG, ABCC8, GLP1R) with risk of breast, colorectal, prostate and overall cancer risk?

What are the new findings?

Genetically-proxied PPARG perturbation was weakly associated with higher risk of prostate cancer and lower risk of ER+ breast cancer

There was little evidence that liability to type 2 diabetes and these cancer endpoints shared one or more causal variants in thePPARGlocus, a necessary precondition to infer causality between PPARG perturbation and cancer risk

How might this impact on clinical practice in the foreseeable future?

Our drug-target Mendelian randomization analyses did not find consistent evidence to support a link between genetically-proxied perturbation of PPARG, ABCC8, and GLP1R and risk of breast, colorectal, prostate and overall cancer risk

These findings suggest that on-target effects of PPARG agonists, sulfonylureas, and GLP1R agonists are unlikely to confer large effects on breast, colorectal, prostate, or overall cancer risk