Metabolic changes preceding bladder cancer occurrence among Korean men: a nested case-control study from the KCPS-II cohort

BACKGROUND

Bladder cancer (BLCA) research in Koreans is still lacking, especially in focusing on the prediction of BLCA. The current study aimed to discover metabolic signatures related to BLCA onset and confirm its potential as a biomarker.

METHODS

We designed two nested case-control studies using Korean Cancer Prevention Study (KCPS)-II. Only males aged 35-69 were randomly selected and divided into two sets by recruitment organizations [set 1, BLCA (n = 35) vs. control (n = 35); set 2, BLCA (n = 31) vs. control (n = 31)]. Baseline serum samples were analyzed by non-targeted metabolomics profiling, and OPLS-DA and network analysis were performed. Calculated genetic risk score (GRS) for BLCA from all KCPS participants was utilized for interpreting metabolomics data.

RESULTS

Critical metabolic signatures shown in the BLCA group were dysregulation of lysine metabolism and tryptophan-indole metabolism. Furthermore, the prediction model consisting of metabolites (lysine, tryptophan, indole, indoleacrylic acid, and indoleacetaldehyde) reflecting these metabolic signatures showed mighty BLCA predictive power (AUC: 0.959 [0.929-0.989]). The results of metabolic differences between GRS-high and GRS-low groups in BLCA indicated that the pathogenesis of BLCA is associated with a genetic predisposition. Besides, the predictive ability for BLCA on the model using GRS and five significant metabolites was powerful (AUC: 0.990 [0.980-1.000]).

CONCLUSION

Metabolic signatures shown in the present research may be closely associated with BLCA pathogenesis. Metabolites involved in these could be predictive biomarkers for BLCA. It could be utilized for early diagnosis, prognostic diagnosis, and therapeutic targets for BLCA.

Non-invasive biomarkers for early diagnosis of pancreatic cancer risk: metabolite genomewide association study based on the KCPS-II cohort

BACKGROUND

Pancreatic cancer is a lethal disease with a high mortality rate. The difficulty of early diagnosis is one of its primary causes. Therefore, we aimed to discover non-invasive biomarkers that facilitate the early diagnosis of pancreatic cancer risk.

METHODS

The study subjects were randomly selected from the Korean Cancer Prevention Study-II and matched by age, sex, and blood collection point [pancreatic cancer incidence (n = 128) vs. control (n = 256)]. The baseline serum samples were analyzed by non-targeted metabolomics, and XGBoost was used to select significant metabolites related to pancreatic cancer incidence. Genomewide association study for the selected metabolites discovered valuable single nucleotide polymorphisms (SNPs). Moderation and mediation analysis were conducted to explore the variables related to pancreatic cancer risk.

RESULTS

Eleven discriminant metabolites were selected by applying a cut-off of 4.0 in XGBoost. Five SNP presented significance in metabolite-GWAS (p ≤ 5 × 10-6) and logistic regression analysis. Among them, the pair metabolite of rs2370981, rs55870181, and rs72805402 displayed a different network pattern with clinical/biochemical indicators on comparison with allelic carrier and non-carrier. In addition, we demonstrated the indirect effect of rs59519100 on pancreatic cancer risk mediated by γ-glutamyl tyrosine, which affects the smoking status. The predictive ability for pancreatic cancer on the model using five SNPs and four pair metabolites with the conventional risk factors was the highest (AUC: 0.738 [0.661-0.815]).

CONCLUSIONS

Signatures involving metabolites and SNPs discovered in the present research may be closely associated with the pathogenesis of pancreatic cancer and for use as predictive biomarkers allowing early pancreatic cancer diagnosis and therapy.

Plasma Metabolome Analysis Suggests That L-Arginine Supplementation Affects Microbial Activity Resulting in a Decrease in Trimethylamine N-oxide-A Randomized Controlled Trial in Healthy Overweight Adults with Cardiometabolic Risk Factors

Background

The effects of supplementation with L-arginine (L-arg), the precursor of nitric oxide (NO), on vascular and cardiometabolic health have largely been explored. Whether other mechanisms of the action of L-arg exist remains unknown, as arginine metabolism is complicated.

Objective

We aimed to characterize the effect of low dose L-arg supplementation on overall human metabolism both in a fasting state and in response to an allostatic stress.

Methods

In a randomized, double-blind, crossover study, 32 healthy overweight adults (mean age 45 y) with cardiometabolic risk (fasting plasma triglycerides >150 mg/dL; waist circumference >94 cm [male] or >80 cm [female]) were treated with 1.5 g sustained-release L-arg 3 times/d (4.5 g/d) or placebo for 4 wk. On the last day of treatment, volunteers consumed a high-fat meal challenge (900 kcal, 80% as fat, 13% as carbohydrate, and 7% as protein). Plasma was collected at fasting, 2, 4, and 6 h after the challenge, and the metabolome was analyzed by high-resolution liquid chromatography-mass spectrometry. Metabolic profiles were analyzed using linear mixed models-principal component analysis.

Results

The challenge meal explained most of the changes in the metabolome. The overall effect of L-arg supplementation significantly explained 0.5% of the total variance, irrespective of the response to the challenge meal (P < 0.05). Among the metabolites that explain most of the L-arg effect, we found many amino acids, including branched-chain amino acids, that were decreased by L-arg supplementation. L-arg also decreased trimethylamine N-oxide (TMAO). Other changes suggest that L-arg increased methyl demand.

Conclusions

Analysis of the effect of 4 wk of L-arg supplementation on the metabolome reveals important effects on methyl balance and gut microbiota activity, such as a decrease in TMAO. Further studies are needed to investigate those mechanisms and the implications of these changes for long-term health.This trial was registered at clinicaltrials.gov as NCT02354794.