The blood metabolome of incident kidney cancer: A case–control study nested within the MetKid consortium

Abstract

Background Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). Methods and findings We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case–control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some—but not all—metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. Conclusions This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI—the principal modifiable risk factor of kidney cancer.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition

“…An inverse association was previously reported between lysoPC a C18:2 with T2D in different studies 7,46 as well as with risks of breast, colorectal and prostate cancers in the pan-cancer analysis conducted in the EPIC Heidelberg study 25 . Our results regarding the three clusters of phosphatidylcholines were in line with many previously reported inverse associations between cancer and phosphatidylcholines 11,12,15,16,20,47 . Besides, we identified a positive association between the cluster that included PC aa C28:1 and cancer risk across all studied cancer types.…”

“…Glutamine was inversely associated with overall cancer risk in our analysis, while glutamate, a metabolite of glutamine, was positively related to the risk of all cancer types except for breast cancer. Although prior studies of the French E3N and SU.VI.MAX cohorts reported a positive association between glutamine and premenopausal breast cancer 51,52 , our results regarding glutamine and glutamate were consistent with those of many previous studies that reported inverse associations between glutamine and risk of colorectal cancer 18 , HCC 19,53 and T2D 7,54 , and positive associations between glutamate and risk of premenopausal breast cancer 52 , kidney cancer 15 , HCC 19,53 , as well as T2D 7 . Lower serum levels of glutamine were also observed in kidney cancer 55 and ovarian cancer 56 cases compared to controls.…”

“…As a result, metabolomics may facilitate the identification of biological mechanisms involved in the development of chronic diseases. For example, prior metabolomics studies have identified metabolites associated with the risk of various chronic conditions, including type-2 diabetes (T2D) [5][6][7] , cardiovascular diseases (CVD) [8][9][10] , and different site-specific cancers, including cancers of the breast 11 , prostate 12,13 , endometrium 14 , kidney 15 , colorectum [16][17][18] , hepatocellular carcinoma (HCC) 19 , and others 20,21 .…”

“…In this work, we extended this concept by leveraging targeted metabolomics data available within nested case-control studies on eight cancer types (breast, colorectal, endometrial, gallbladder and biliary tract, kidney, localized prostate and advanced prostate cancers, and HCC) previously acquired in the European Prospective Investigation into Cancer and Nutrition (EPIC) 11,12,14,15,19 . The data shared lasso [26][27][28] , a penalized multivariate approach specifically designed for the investigation of a set of shared risk factors across different disease outcomes, was used to carry out a multivariate pan-cancer analysis to identify mutually adjusted metabolites associated with cancer risk and to identify those metabolites with consistent or heterogeneous patterns of associations across the eight cancer types.…”

Epidemiology and Prevention of Renal Cell Carcinoma

“…Sensitivity and specificity of the clinical stage prediction model were 88.5% and 75.4%, respectively, with an AUC of 0.837 [ 135 ]. Guida et al, studied the first comprehensive metabolomics analysis of incident RCC to be conducted using a prospective design, using pre-diagnostic blood samples from up to 1305 RCC case–control pairs from five prospective cohort studies [ 136 ]. In this study, 25 metabolites were found to be robustly associated with risk after 1416 metabolites associated with the development of RCC were analyzed.…”