Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis
Authors: Yarmolinsky James , Robinson Jamie W , Mariosa Daniela , Karhunen Ville , Huang Jian , Dimou Niki , Murphy Neil , Burrows Kimberley , Bouras Emmanouil , Smith-Byrne Karl , Lewis Sarah J , Galesloot Tessel E , Kiemeney Lambertus A , Vermeulen Sita , Martin Paul , Albanes Demetrius , Hou Lifang , Newcomb Polly A , White Emily , Wolk Alicja , Wu Anna H , Marchand Loïc Le , Phipps Amanda I , Buchanan Daniel D ,   the International Lung Cancer Consortium,   the PRACTICAL consortium, Zhao Sizheng Steven , Gill Dipender , Chanock Stephen J , Purdue Mark P , Smith George Davey , Brennan Paul , Herzig Karl-Heinz , Jarvelin Marjo-Riitta , Dehghan Abbas , Johansson Mattias , Gunter Marc J , Tsilidis Kostas K , Martin Richard M 
Published: May 2023

Background

Tumour-promoting inflammation is a “hallmark” of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear.

Methods

We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combinedcis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,162 cancer cases and up to 824,556 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P< 5.0 x 10-8)cis-acting SNPs (i.e. in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2< 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-correctedP-value (“q-value”) < 0.05 was used as a threshold to define “strong evidence” to support associations and 0.05 ≤q-value < 0.20 to define “suggestive evidence”. A colocalisation posterior probability (PPH4) > 70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes.

Results

We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR 1.19, 95% CI 1.10-1.29,q-value=0.033, PPH4=84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR 1.42, 95% CI 1.20-1.69,q-value=0.055, PPH4=73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR 0.66, 95% CI 0.53-0.81,q-value=0.067, PPH4=81.8%), macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR 1.14, 95% CI 1.05-1.23,q-value=0.072, PPH4=76.1%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR 0.92, 95% CI 0.88-0.97,q-value=0.15), PPH4=85.6%). For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥ 0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk.

Conclusion

Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 5 circulating inflammatory markers in risk of 5 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.