Prospective Investigation of Serum Metabolites, Coffee Drinking, Liver Cancer Incidence, and Liver Disease Mortality

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Combining multiple biomarkers linearly to minimize the Euclidean distance of the closest point on the receiver operating characteristic surface to the perfection corner in trichotomous settings

The performance of individual biomarkers in discriminating between two groups, typically the healthy and the diseased, may be limited. Thus, there is interest in developing statistical methodologies for biomarker combinations with the aim of improving upon the individual discriminatory performance. There is extensive literature referring to biomarker combinations under the two-class setting. However, the corresponding literature under a three-class setting is limited. In our study, we provide parametric and nonparametric methods that allow investigators to optimally combine biomarkers that seek to discriminate between three classes by minimizing the Euclidean distance from the receiver operating characteristic surface to the perfection corner. Using this Euclidean distance as the objective function allows for estimation of the optimal combination coefficients along with the optimal cutoff values for the combined score. An advantage of the proposed methods is that they can accommodate biomarker data from all three groups simultaneously, as opposed to a pairwise analysis such as the one implied by the three-class Youden index. We illustrate that the derived true classification rates exhibit narrower confidence intervals than those derived from the Youden-based approach under a parametric, flexible parametric, and nonparametric kernel-based framework. We evaluate our approaches through extensive simulations and apply them to real data sets that refer to liver cancer patients.

Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake

BACKGROUND

Metabolomics has the potential to enhance dietary assessment by revealing objective measures of many aspects of human food intake. Although metabolomics studies indicate that hundreds of metabolites are associated with dietary intake, correlations have been modest (e.g., r < 0.50), and few have been evaluated in controlled feeding studies.

OBJECTIVES

The aim of this study was to evaluate associations between metabolites and weighed food and beverage intake in a controlled feeding study of habitual diet.

METHODS

Healthy postmenopausal females from the Women's Health Initiative (N = 153) were provided with a customized 2-wk controlled diet designed to emulate their usual diet. Metabolites were measured by liquid chromatography tandem mass spectrometry in end-of-study 24-h urine and fasting serum samples (1293 urine metabolites; 1113 serum metabolites). We calculated partial Pearson correlations between these metabolites and intake of 65 food groups, beverages, and supplements during the feeding study. The threshold for significance was Bonferroni-adjusted to account for multiple testing (5.94 × 10-07 for urine metabolites; 6.91 × 10-07 for serum metabolites).

RESULTS

Significant diet-metabolite correlations were identified for 23 distinct foods, beverages, and supplements (171 distinct metabolites). Among foods, strong metabolite correlations (r ≥ 0.60) were evident for citrus (highest r = 0.80), dairy (r = 0.65), and broccoli (r = 0.63). Among beverages and supplements, strong correlations were evident for coffee (r = 0.86), alcohol (r = 0.69), multivitamins (r = 0.69), and vitamin E supplements (r = 0.65). Moderate correlations (r = 0.50-0.60) were also observed for avocado, fish, garlic, grains, onion, poultry, and black tea. Correlations were specific; each metabolite correlated with one food, beverage, or supplement, except for metabolites correlated with juice or multivitamins.

CONCLUSIONS

Metabolite levels had moderate to strong correlations with weighed intake of habitually consumed foods, beverages, and supplements. These findings exceed in magnitude those previously observed in population studies and exemplify the strong potential of metabolomics to contribute to nutrition research. The Women's Health Initiative is registered at clinicaltrials.gov as NCT00000611.

Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men

BACKGROUND

Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.

METHODS

We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.

FINDINGS

After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).

INTERPRETATION

This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.

FUNDING

National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].

Identification of pre-diagnostic lipid sets associated with liver cancer risk using untargeted lipidomics and chemical set analysis: A nested case-control study within the ATBC cohort

In pre-disposed individuals, a reprogramming of the hepatic lipid metabolism may support liver cancer initiation. We conducted a high-resolution mass spectrometry based untargeted lipidomics analysis of pre-diagnostic serum samples from a nested case-control study (219 liver cancer cases and 219 controls) within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Out of 462 annotated lipids, 158 (34.2%) were associated with liver cancer risk in a conditional logistic regression analysis at a false discovery rate (FDR) <0.05. A chemical set enrichment analysis (ChemRICH) and co-regulatory set analysis suggested that 22/28 lipid classes and 47/83 correlation modules were significantly associated with liver cancer risk (FDR <0.05). Strong positive associations were observed for monounsaturated fatty acids (MUFA), triacylglycerols (TAGs) and phosphatidylcholines (PCs) having MUFA acyl chains. Negative associations were observed for sphingolipids (ceramides and sphingomyelins), lysophosphatidylcholines, cholesterol esters and polyunsaturated fatty acids (PUFA) containing TAGs and PCs. Stearoyl-CoA desaturase enzyme 1 (SCD1), a rate limiting enzyme in fatty acid metabolism and ceramidases seems to be critical in this reprogramming. In conclusion, our study reports pre-diagnostic lipid changes that provide novel insights into hepatic lipid metabolism reprogramming may contribute to a pro-cell growth and anti-apoptotic tissue environment and, in turn, support liver cancer initiation.

Mechanism study of oleanolic acid derivative, K73-03, inducing cell apoptosis in hepatocellular carcinoma

Oleanolic acid (3β-hydroxyolean-12-en-28-oic acid, OA) is a kind of pentacyclic triterpene, which widely distributes in nature. OA possesses a powerful anti-cancer effect; however, its low solubility limits its bioavailability and application. In this study, a new OA derivative, K73-03, was used to determine its effect on liver cancer cells and detailed molecular mechanisms. Here, we show that K73-03 may lead to the disorder of mitochondria in HepG2 cells, leading to excessive ROS production and apoptosis in cells. Meanwhile, K73-03 could induce cell apoptosis by inhibiting JAK2/STAT3 pathway and NF-κB/P65 pathway. Collectively, this study may provide a preliminary basis for further cancer treatment of hepatocellular carcinoma.

Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration

Multiomics data including imaging radiomics and various types of molecular biomarkers have been increasingly investigated for better diagnosis and therapy in the era of precision oncology. Artificial intelligence (AI) including machine learning (ML) and deep learning (DL) techniques combined with the exponential growth of multiomics data may have great potential to revolutionize cancer subtyping, risk stratification, prognostication, prediction and clinical decision-making. In this article, we first present different categories of multiomics data and their roles in diagnosis and therapy. Second, AI-based data fusion methods and modeling methods as well as different validation schemes are illustrated. Third, the applications and examples of multiomics research in oncology are demonstrated. Finally, the challenges regarding the heterogeneity data set, availability of omics data, and validation of the research are discussed. The transition of multiomics research to real clinics still requires consistent efforts in standardizing omics data collection and analysis, building computational infrastructure for data sharing and storing, developing advanced methods to improve data fusion and interpretability, and ultimately, conducting large-scale prospective clinical trials to fill the gap between study findings and clinical benefits.

Unmet Needs in the Post-Direct-Acting Antiviral Era: Hepatocarcinogenesis After Hepatitis C Virus Eradication

Infection with chronic hepatitis C virus (HCV) is an important risk factor for hepatocellular carcinoma (HCC). Direct-acting antiviral therapy has transformed care for patients with HCV and reduces the risk of HCC. Despite HCV cure, a residual HCC risk remains in patients with advanced fibrosis and cirrhosis, with multiple mechanisms underlying subsequent hepatocarcinogenesis. Transcriptomic and proteomic signatures demonstrate the capacity for HCC risk stratification, and chemoprevention strategies are emerging. For now, pending more precise stratification, HCC surveillance of patients with cured HCV and advanced fibrosis or cirrhosis should continue.

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review

An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.

Dihydroartemisinin increased the abundance of Akkermansia muciniphila by YAP1 depression that sensitizes hepatocellular carcinoma to anti-PD-1 immunotherapy

The effect of anti-programmed cell death 1 (anti-PD-1) immunotherapy is limited in patients with hepatocellular carcinoma (HCC). Yes-associated protein 1 (YAP1) expression increased in liver tumor cells in early HCC, and Akkermansia muciniphila abundance decreased in the colon. The response to anti-PD-1 treatment is associated with A. muciniphila abundance in many tumors. However, the interaction between A. muciniphila abundance and YAP1 expression remains unclear in HCC. Here, anti-PD-1 treatment decreased A. muciniphila abundance in the colon, but increased YAP1 expression in the tumor cells by mice with liver tumors in situ. Mechanistically, hepatocyte-specific Yap1 knockout (Yap1LKO) maintained bile acid homeostasis in the liver, resulting in an increased abundance of A. muciniphila in the colon. Yap1 knockout enhanced anti-PD-1 efficacy. Therefore, YAP1 inhibition is a potential target for increasing A. muciniphila abundance to promote anti-PD-1 efficacy in liver tumors. Dihydroartemisinin (DHA), acting as YAP1 inhibitor, increased A. muciniphila abundance to sensitize anti-PD-1 therapy. A. muciniphila by gavage increased the number and activation of CD8+ T cells in liver tumor niches during DHA treatment or combination with anti-PD-1. Our findings suggested that the combination anti-PD-1 with DHA is an effective strategy for liver tumor treatment.

Coffee prevents IQ-induced liver damage by regulating oxidative stress, inflammation, endoplasmic reticulum stress, autophagy, apoptosis, and the MAPK/NF-κB signaling pathway in zebrafish

2-Amino-3-methylimidazole[4,5-f]quinoline (IQ), one of heterocyclic amines (HCAs) produced in proteinaceous foods upon heating, is recognized as a carcinogen. Previous studies have confirmed that IQ intake can cause liver damage in zebrafish. In the current study, we revealed the protective effects of coffee against IQ-induced liver damage. We exposed one-month-old wild-type zebrafish to IQ (80 ng/mL) and coffee at 50 mg/L, 100 mg/L, and 300 mg/L for 35 days. Markers of oxidative stress, inflammation, endoplasmic reticulum stress (ERS), autophagy, and apoptosis in the liver were assessed to explore the potential mechanisms of the protective effects. The results showed that coffee effectively improved IQ-induced liver damage by reducing ALT, AST, TC, TG, and LDL-C levels, increasing HDL-C level, and restoring hepatic morphology. Moreover, coffee showed an antioxidative effect by increasing GSH, GSH-Px, GST, CAT, and SOD levels and attenuating ROS and MDA contents. Additionally, coffee reduced the NO, iNOS, TNF-α, IL-6, IL-1β, and IL-12 expression levels, presenting an anti-inflammatory effect. Furthermore, coffee protected against ERS, autophagy dysfunction, and apoptosis by decreasing the GRP78, CHOP, and p62 while increasing the Atg5-Atg12, Beclin1, LC3-II, and Bcl-2 expression levels. TUNEL results showed that coffee rescued IQ-induced hepatocyte apoptosis. In addition, coffee interrupted the MAPK/NF-κB signaling pathway by suppressing the phosphorylation expressions of JNK, ERK, p38, p65, and IκB. These findings indicated that coffee prevents IQ-induced liver damage with antioxidative, anti-inflammatory, anti-ERS, anti-apoptotic, and pro-autophagic effects, thus to serve as a functional beverage with potential health benefits.

The role of the gut microbiome in the development of hepatobiliary cancers

Hepatobiliary cancers, including hepatocellular carcinoma and cancers of the biliary tract, share high mortality and rising incidence rates. They may also share several risk factors related to unhealthy western-type dietary and lifestyle patterns as well as increasing body weights and rates of obesity. Recent data also suggest a role for the gut microbiome in the development of hepatobiliary cancer and other liver pathologies. The gut microbiome and the liver interact bidirectionally through the "gut-liver axis," which describes the interactive relationship between the gut, its microbiota, and the liver. Here, we review the gut-liver interactions within the context of hepatobiliary carcinogenesis by outlining the experimental and observational evidence for the roles of gut microbiome dysbiosis, reduced gut barrier function, and exposure to inflammatory compounds as well as metabolic dysfunction as contributors to hepatobiliary cancer development. We also outline the latest findings regarding the impact of dietary and lifestyle factors on liver pathologies as mediated by the gut microbiome. Finally, we highlight some emerging gut microbiome editing techniques currently being investigated in the context of hepatobiliary diseases. Although much work remains to be done in determining the relationships between the gut microbiome and hepatobiliary cancers, emerging mechanistic insights are informing treatments, such as potential microbiota manipulation strategies and guiding public health advice on dietary/lifestyle patterns for the prevention of these lethal tumors.

Identification of Gut Microbial Lysine and Histidine Degradation and CYP-Dependent Metabolites as Biomarkers of Fatty Liver Disease

Numerous studies have described specific metabolites as biomarkers of severe liver diseases, but very few have measured gut microbiota (GM)-produced metabolites in fatty liver disease. We aimed at finding GM signatures and metabolite markers in plasma and feces related to high liver fat content. Based on imaging, we divided study participants into low (<5%, LF, n = 25) and high (>5%, HF, n = 39) liver fat groups. Fecal (LF n = 14, HF n = 25) and plasma (LF n = 11, HF n = 7) metabolomes of subsets of participants were studied using liquid chromatography/high resolution mass spectrometry. The GM were analyzed using 16S rRNA gene sequencing. Additionally, blood clinical variables and diet were studied. Dyslipidemia, higher liver enzymes and insulin resistance characterized the HF group. No major differences in diet were found between the groups. In the GM, the HF group had lower abundance of Bacteroides and Prevotellaceae NK3B31 group than the LF group after adjusting for metformin use or obesity. In feces, the HF group had higher levels of lysine and histidine degradation products, while 6-hydroxybetatestosterone (metabolized by CYP3A4) was low. Higher plasma levels of caffeine and its metabolites in the HF group indicate that the activity of hepatic CYP1A2 was lower than in the LF group. Our results suggest, that low fecal Prevotellaceae NK3B31 and Bacteroides abundance, and increased lysine and histidine degradation may serve as GM biomarkers of high liver fat. Altered plasma caffeine metabolites and lowered testosterone metabolism may specify decreased CYP activities, and their potential utility, as biomarkers of fatty liver disease. IMPORTANCE Because the high prevalence of nonalcoholic fatty liver disease sets diagnostic challenges to health care, identification of new biomarkers of the disease that in the future could have potential utility as diagnostic biomarkers of high liver fat content is important. Our results show that increased amino acid degradation products in the feces may be such biomarkers. In the blood, molecules that indicate defective hepatic metabolic enzyme activities were identified in individuals with high liver fat content.

Health Benefits of Coffee Consumption for Cancer and Other Diseases and Mechanisms of Action

Coffee is one of the most widely consumed beverages worldwide, and epidemiology studies associate higher coffee consumption with decreased rates of mortality and decreased rates of neurological and metabolic diseases, including Parkinson's disease and type 2 diabetes. In addition, there is also evidence that higher coffee consumption is associated with lower rates of colon and rectal cancer, as well as breast, endometrial, and other cancers, although for some of these cancers, the results are conflicting. These studies reflect the chemopreventive effects of coffee; there is also evidence that coffee consumption may be therapeutic for some forms of breast and colon cancer, and this needs to be further investigated. The mechanisms associated with the chemopreventive or chemotherapeutic effects of over 1000 individual compounds in roasted coffee are complex and may vary with different diseases. Some of these mechanisms may be related to nuclear factor erythroid 2 (Nrf2)-regulated pathways that target oxidative stress or pathways that induce reactive oxygen species to kill diseased cells (primarily therapeutic). There is evidence for the involvement of receptors which include the aryl hydrocarbon receptor (AhR) and orphan nuclear receptor 4A1 (NR4A1), as well as contributions from epigenetic pathways and the gut microbiome. Further elucidation of the mechanisms will facilitate the potential future clinical applications of coffee extracts for treating cancer and other inflammatory diseases.

A novel classification of HCC basing on fatty-acid-associated lncRNA

Aberrant long noncoding RNA (lncRNA) expression and fatty acid signaling dysfunction both contribute to hepatocellular carcinoma (HCC) occurrence and development. However, the relationship and interaction mechanism between lncRNAs and fatty acid signaling in HCC remain unclear. Data regarding RNA expression and clinical outcomes for patients with HCC were obtained from The Cancer Genome Atlas (TCGA), HCCDB, and the Gene Expression Omnibus (GEO) databases. Hallmark pathways were identified using the single-sample gene set enrichment analysis (ssGSEA) method. ConsensusClusterPlus was used to establish a consistency matrix for classifying samples into three subtypes. A risk signature was established, and predictive values for key lncRNAs related to prognosis were evaluated using Kaplan-Meier analysis and receiver operating characteristic curves. The ESTIMATE algorithm, MCP-Counter, and ssGSEA were used to evaluate the characteristics of the tumor immune microenvironment. The CTRP2.0 and PRISM were used to analyze drug sensitivity in HCC subtypes. We discovered seven fatty-acid-associated lncRNAs with predictive prognostic capabilities, including TRAF3IP2-AS1, SNHG10, AL157392.2, LINC02641, AL357079.1, AC046134.2, and A1BG-AS. Three subtypes were obtained, which presented with differences in prognosis, clinical information, mutation features, pathway traits, immune characteristics, and drug sensitivity. The seven key lncRNAs identified in this study might serve as promising biomarkers for predicting prognosis in patients with HCC, and the three HCC subtypes classified according to lncRNA expression profiles could improve HCC classification.

The association between plasma metabolites and future risk of all-cause mortality

BACKGROUND

Metabolite profiles provide snapshots of the overall effect of numerous exposures accumulated over life courses, which may lead to health outcomes in the future.

OBJECTIVE

We hypothesized that the risk of all-cause mortality is linked to alterations in metabolism earlier in life, which are reflected in plasma metabolite profiles. We aimed to identify plasma metabolites associated with future risk of all-cause mortality.

METHODS

Through metabolomics, 110 metabolites were measured in 3833 individuals from the Malmö Diet and Cancer-Cardiovascular Cohort (MDC-CC). A total of 1574 deaths occurred within an average follow-up time of 22.2 years. Metabolites that were significantly associated with all-cause mortality in MDC-CC were replicated in 1500 individuals from Malmö Preventive Project re-examination (MPP), among whom 715 deaths occurred within an average follow-up time of 11.3 years.

RESULTS

Twenty two metabolites were significantly associated with all-cause mortality in MDC-CC, of which 13 were replicated in MPP. Levels of trigonelline, glutamate, dimethylglycine, C18-1-carnitine, C16-1-carnitine, C14-1-carnitine, and 1-methyladenosine were associated with an increased risk, while levels of valine, tryptophan, lysine, leucine, histidine, and 2-aminoisobutyrate were associated with a decreased risk of all-cause mortality.

CONCLUSION

We used metabolomics in two Swedish prospective cohorts and identified replicable associations between 13 metabolites and future risk of all-cause mortality. Novel associations between five metabolites-C18-1-carnitine, C16-1-carnitine, C14-1-carnitine, trigonelline, and 2-aminoisobutyrate-and all-cause mortality were discovered. These findings suggest potential new biomarkers for the prediction of mortality and provide insights for understanding the biochemical pathways that lead to mortality.

Antitumor effect and metabonomics of niclosamide micelles

Polymer micelles now have promising applications in the treatment of cancer, increasing the water solubility and bioavailability of drugs. Previous studies have found that micelles of niclosamide have good anti‐liver cancer effect. In view of the poor water solubility of niclosamide (NIC), we decided to prepare niclosamide micelles. However, its therapeutic mechanism is not clear, so this paper conducted a preliminary study on its vitro anti‐tumour mechanism and metabonomics to find out its impact. It was found that the drug‐loaded micelles (PEG_2K‐FIbu/NIC) had an inhibitory effect on HepG2 cells. Moreover, it can promote apoptosis of HepG2 cells and block S and G2/M phase of cell cycle. The plasma and liver metabolomics of mice in normal group, model group and administration group were studied by UPLC‐MS and ¹H‐NMR. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS‐DA) were used to process the data and find the relevant metabolites. metaboanalyst 5.0 was used to integrate the relevant metabolites to find the main related metabolic pathways. Thus, the anti‐tumour mechanism of PEG_2K‐FIbu/NIC was analysed. Fifty‐one biomarkers were detected in plasma, and 43 biomarkers were detected in liver. After comprehensive biomarker and metabolic pathway analysis, it was found that PEG_2K‐FIbu/NIC micelles could affect the changes of many metabolites, mainly affecting amino acid metabolism. This article is an in‐depth study based on the published Preparation and pharmacodynamics of niclosamide micelles (DOI: 10.1016/j.jddst.2021.103088).

Untargeted plasma metabolomics for risk prediction of hepatocellular carcinoma: A prospective study in two Chinese cohorts

Characterization of metabolic perturbation prior to hepatocellular carcinoma (HCC) may deepen the understanding of causal pathways and identify novel biomarkers for early prevention. We conducted two 1:1 matched nested case-control studies (108 and 55 pairs) to examine the association of plasma metabolome (profiled using LC-MS) with the risk of HCC based on two prospective cohorts in China. Differential metabolites were identified by paired t-tests and orthogonal partial least-squares discriminant analysis (OPLS-DA). Weighted gene co-expression network analysis (WGCNA) was performed to classify metabolites into modules for identifying biological pathways involved in hepatocarcinogenesis. We assessed the risk predictivity of metabolites using multivariable logistic regression models. Among 612 named metabolites, 44 differential metabolites were identified between cases and controls, including 12 androgenic/progestin steroid hormones, 8 bile acids, 10 amino acids, 6 phospholipids, and 8 others. These metabolites were associated with HCC in the multivariable logistic regression analyses, with odds ratios ranging from 0.19 (95% CI: 0.11-0.35) to 5.09 (95% CI: 2.73-9.50). WGCNA including 612 metabolites showed 8 significant modules related to HCC risk, including those representing metabolic pathways of androgen and progestin, primary and secondary bile acids, and amino acids. A combination of 18 metabolites of independent effects showed the potential to predict HCC risk, with an AUC of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.93) in the training and validation sets, respectively. In conclusion, we identified a panel of plasma metabolites that could be implicated in hepatocellular carcinogenesis and have the potential to predict HCC risk.

Impact of coffee preparation on total phenolic content in brewed coffee extracts and their contribution to the body's antioxidant status

Although coffee has been reported as a major contributor to antioxidants in the diet, there are limited studies assessing how brewing methods and types of coffee affect antioxidant capacity of coffee consumers. This study was aimed to investigate the impact of coffee preparation on total phenolic content in brewed coffee extracts and their contribution to antioxidant status. We examined how the different brewing methods affect total phenolic content and antioxidant capacity in brewed coffee extracts, then assessed the antioxidant status of coffee consumers after drinking coffee. Results showed that consuming capsule versus French press coffee provides a higher total phenolic content and drinking capsule coffee leads to greater antioxidant status as shown by the higher total antioxidant capacity in urine. Further studies can expand on this by using a broader range of brewing methods to evaluate the contribution of brewing methods of coffee to antioxidant status.

A prospective investigation of serum bile acids with risk of liver cancer, fatal liver disease, and biliary tract cancer

Bile acids (BAs), major regulators of the gut microbiota, may play an important role in hepatobiliary cancer etiology. However, few epidemiologic studies have comprehensively examined associations between BAs and liver or biliary tract cancer. In the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study, we designed 1:1 matched, nested, case-control studies of primary liver cancer (n = 201 cases), fatal liver disease (n = 261 cases), and primary biliary tract cancer (n = 138 cases). Using baseline serum collected ≤30 years before diagnosis or death, we measured concentrations of 15 BAs with liquid chromatography-tandem mass spectrometry. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) using multivariable conditional logistic regression models, adjusted for age, education, diabetes status, smoking, alcohol intake, and body mass index. We accounted for multiple comparisons using a false discovery rate (FDR) correction. Comparing the highest to the lowest quartile, seven BAs were positively associated with liver cancer risk, including taurocholic acid (TCA) (OR, 5.62; 95% CI, 2.74-11.52; Q trend < 0.0001), taurochenodeoxycholic acid (TCDCA) (OR, 4.77; 95% CI, 2.26-10.08; Q trend < 0.0001), and glycocholic acid (GCA) OR, 5.30; 95% CI, 2.41-11.66; Q trend < 0.0001), and 11 were positively associated with fatal liver disease risk, including TCDCA (OR, 9.65; 95% CI, 4.41-21.14; Q trend < 0.0001), TCA (OR, 7.45; 95% CI, 3.70-14.97; Q trend < 0.0001), and GCA (OR, 6.98; 95% CI, 3.32-14.68; Q trend < 0.0001). For biliary tract cancer, associations were generally >1 but not significant after FDR correction. Conjugated BAs were strongly associated with increased risk of liver cancer and fatal liver disease, suggesting mechanistic links between BA metabolism and liver cancer or death from liver disease.

Prediagnostic alterations in circulating bile acid profiles in the development of hepatocellular carcinoma

Bile acids (BAs) play different roles in cancer development. Some are carcinogenic and BA signaling is also involved in various metabolic, inflammatory and immune-related processes. The liver is the primary site of BA synthesis. Liver dysfunction and microbiome compositional changes, such as during hepatocellular carcinoma (HCC) development, may modulate BA metabolism increasing concentration of carcinogenic BAs. Observations from prospective cohorts are sparse. We conducted a study (233 HCC case-control pairs) nested within a large observational prospective cohort with blood samples taken at recruitment when healthy with follow-up over time for later cancer development. A targeted metabolomics method was used to quantify 17 BAs (primary/secondary/tertiary; conjugated/unconjugated) in prediagnostic plasma. Odd ratios (OR) for HCC risk associations were calculated by multivariable conditional logistic regression models. Positive HCC risk associations were observed for the molar sum of all BAs (ORdoubling  = 2.30, 95% confidence intervals [CI]: 1.76-3.00), and choline- and taurine-conjugated BAs. Relative concentrations of BAs showed positive HCC risk associations for glycoholic acid and most taurine-conjugated BAs. We observe an association between increased HCC risk and higher levels of major circulating BAs, from several years prior to tumor diagnosis and after multivariable adjustment for confounders and liver functionality. Increase in BA concentration is accompanied by a shift in BA profile toward higher proportions of taurine-conjugated BAs, indicating early alterations of BA metabolism with HCC development. Future studies are needed to assess BA profiles for improved stratification of patients at high HCC risk and to determine whether supplementation with certain BAs may ameliorate liver dysfunction.

Metabolomic analysis of serum alpha-tocopherol among men in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study

BACKGROUND/OBJECTIVES

The role of vitamin E in chronic disease risk remains incompletely understood, particularly in an un-supplemented state, and evidence is sparse regarding the biological actions and pathways involved in its influence on health outcomes. Identifying vitamin-E-associated metabolites through agnostic metabolomics analyses can contribute to elucidating the specific associations and disease etiology. This study aims to investigate the association between circulating metabolites and serum α-tocopherol concentration in an un-supplemented state.

SUBJECTS/METHODS

Metabolomic analysis of 4,294 male participants was conducted based on pre-supplementation fasting serum in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study. The associations between 1,791 known metabolites measured by ultra-high-performance LC-MS/GC-MS and HPLC-determined α-tocopherol concentration were estimated using multivariable linear regression. Differences in metabolite levels per unit difference in α-tocopherol concentration were calculated as standardized β-coefficients and standard errors.

RESULTS

A total of 252 metabolites were associated with serum α-tocopherol at the Bonferroni-corrected p value (p < 2.79 × 10^-5). Most of these metabolites were of lipid and amino acid origin, with the respective subclasses of dicarboxylic fatty acids, and valine, leucine, and isoleucine metabolism, being highly represented. Among lipids, the strongest signals were observed for linoleoyl-arachidonoyl-glycerol (18:2/20:4)[2](β = 0.149; p = 8.65 × 10^-146) and sphingomyelin (D18:2/18:1) (β = 0.035; p = 1.36 × 10^-30). For amino acids, the strongest signals were aminoadipic acid (β = 0.021; p = 5.01 × 10^-13) and l-leucine (β = 0.007; p = 1.05 × 10^-12).

CONCLUSIONS

The large number of metabolites, particularly lipid and amino acid compounds associated with serum α-tocopherol provide leads regarding potential mechanisms through which vitamin E influences human health, including its role in cardiovascular disease and cancer.

Targeted Inhibition of LPL/FABP4/CPT1 fatty acid metabolic axis can effectively prevent the progression of nonalcoholic steatohepatitis to liver cancer

Rationale: Nonalcoholic steatohepatitis (NASH), as one of the key stages in the development of nonalcoholic fatty liver disease (NAFLD), can directly progress to HCC, but the underlying mechanism is not fully understood.

Methods: Differentially expressed genes (DEGs) in each stage of disease development were studied through a GEO dataset deriving from a Stelic Animal Model (STAM), which can simulate the evolution of NAFLD/NASH to HCC in humans. GSVA analysis was performed to analyze the differentially expressed oncogenic signatures in each stage. A human NAFLD-related dataset from GEO database was utilized for gene expression verification and further validated in the protein level in STAM mice. Small molecule inhibitors were applied to STAM mice for investigating whether inhibition of the LPL/FABP4/CPT1 axis could prevent the occurrence of NASH-related HCC in vivo. Microsphere formation and clonal formation assays in vitro were applied to study if inhibition of the LPL/FABP4/CPT1 axis can reduce the viability of liver cancer stem cells (LCSCs).

Results: We found that upregulation of the LPL/FABP4/CPT1 molecular axis, as a fatty acid metabolic reprogramming process, occurred specifically during the NASH phase. GSVA analysis showed widespread activation of a large number of oncogenic signals, which may contribute to malignant transformation during NASH. Furthermore, inhibition of the LPL/FABP4/CPT1 axis could effectively delay the tumor growth in STAM mice. Cell assays revealed inhibitors targeting this axis can significantly reduce the sphere-forming, proliferation, and clonality of LCSCs.

Conclusion: These results suggest that activation of the LPL/FABP4/CPT1 axis is essential for LCSCs maintenance, which acts synergistically with a variety of up-regulated oncogenic signals that drive the hepatocyte-LCSCs transdifferentiation during NASH to HCC progression. Thus, targeting the LPL/FABP4/CPT1 axis may provide a potential direction for NASH-related HCC prevention.

Clinical Significance of Screening Differential Metabolites in Ovarian Cancer Tissue and Ascites by LC/MS

Tumor cells not only show a vigorous metabolic state, but also reflect the disease progression and prognosis from their metabolites. To judge the progress and prognosis of ovarian cancer is generally based on the formation of ascites, or whether there is ascites recurrence during chemotherapy after ovarian cancer surgery. To explore the relationship between the production of ascites and ovarian cancer tissue, metabolomics was used to screen differential metabolites in this study. The significant markers leading to ascites formation and chemoresistance were screened by analyzing their correlation with the formation of ascites in ovarian cancer and the clinical indicators of patients, and then provided a theoretical basis. The results revealed that nine differential metabolites were screened out from 37 ovarian cancer tissues and their ascites, among which seven differential metabolites were screened from 22 self-paired samples. Sebacic acid and 20-COOH-leukotriene E4 were negatively correlated with the high expression of serum CA125. Carnosine was positively correlated with the high expression of serum uric acid. Hexadecanoic acid was negatively correlated with the high expression of serum γ-GGT and HBDH. 20a,22b-Dihydroxycholesterol was positively correlated with serum alkaline phosphatase and γ-GGT. In the chemotherapy-sensitive and chemotherapy-resistant ovarian cancer tissues, the differential metabolite dihydrothymine was significantly reduced in the chemotherapy-resistant group. In the ascites supernatant of the drug-resistant group, the differential metabolites, 1,25-dihydroxyvitamins D3-26, 23-lactonel and hexadecanoic acid were also significantly reduced. The results indicated that the nine differential metabolites could reflect the prognosis and the extent of liver and kidney damage in patients with ovarian cancer. Three differential metabolites with low expression in the drug-resistant group were proposed as new markers of chemotherapy efficacy in ovarian cancer patients with ascites.

Novel Biomarkers of Habitual Alcohol Intake and Associations With Risk of Pancreatic and Liver Cancers and Liver Disease Mortality

BACKGROUND

Alcohol is an established risk factor for several cancers, but modest alcohol-cancer associations may be missed because of measurement error in self-reported assessments. Biomarkers of habitual alcohol intake may provide novel insight into the relationship between alcohol and cancer risk.

METHODS

Untargeted metabolomics was used to identify metabolites correlated with self-reported habitual alcohol intake in a discovery dataset from the European Prospective Investigation into Cancer and Nutrition (EPIC; n = 454). Statistically significant correlations were tested in independent datasets of controls from case-control studies nested within EPIC (n = 280) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC; n = 438) study. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations of alcohol-associated metabolites and self-reported alcohol intake with risk of pancreatic cancer, hepatocellular carcinoma (HCC), liver cancer, and liver disease mortality in the contributing studies.

RESULTS

Two metabolites displayed a dose-response association with self-reported alcohol intake: 2-hydroxy-3-methylbutyric acid and an unidentified compound. A 1-SD (log2) increase in levels of 2-hydroxy-3-methylbutyric acid was associated with risk of HCC (OR = 2.54, 95% CI = 1.51 to 4.27) and pancreatic cancer (OR = 1.43, 95% CI = 1.03 to 1.99) in EPIC and liver cancer (OR = 2.00, 95% CI = 1.44 to 2.77) and liver disease mortality (OR = 2.16, 95% CI = 1.63 to 2.86) in ATBC. Conversely, a 1-SD (log2) increase in questionnaire-derived alcohol intake was not associated with HCC or pancreatic cancer in EPIC or liver cancer in ATBC but was associated with liver disease mortality (OR = 2.19, 95% CI = 1.60 to 2.98) in ATBC.

CONCLUSIONS

2-hydroxy-3-methylbutyric acid is a candidate biomarker of habitual alcohol intake that may advance the study of alcohol and cancer risk in population-based studies.

Metabolites Associated with Coffee Consumption and Incident Chronic Kidney Disease

BACKGROUND AND OBJECTIVES

Moderate coffee consumption has been associated with lower risk of CKD; however, the exact biologic mechanisms underlying this association are unknown. Metabolomic profiling may identify metabolic pathways that explain the association between coffee and CKD. The goal of this study was to identify serum metabolites associated with coffee consumption and examine the association between these coffee-associated metabolites and incident CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using multivariable linear regression, we identified coffee-associated metabolites among 372 serum metabolites available in two subsamples of the Atherosclerosis Risk in Communities study (ARIC; n=3811). Fixed effects meta-analysis was used to pool the results from the two ARIC study subsamples. Associations between coffee and metabolites were replicated in the Bogalusa Heart Study (n=1043). Metabolites with significant associations with coffee in both cohorts were then evaluated for their prospective associations with incident CKD in the ARIC study using Cox proportional hazards regression.

RESULTS

In the ARIC study, mean (SD) age was 54 (6) years, 56% were daily coffee drinkers, and 32% drank >2 cups per day. In the Bogalusa Heart Study, mean (SD) age was 48 (5) years, 57% were daily coffee drinkers, and 38% drank >2 cups per day. In a meta-analysis of two subsamples of the ARIC study, 41 metabolites were associated with coffee consumption, of which 20 metabolites replicated in the Bogalusa Heart Study. Three of these 20 coffee-associated metabolites were associated with incident CKD in the ARIC study.

CONCLUSIONS

We detected 20 unique serum metabolites associated with coffee consumption in both the ARIC study and the Bogalusa Heart Study, and three of these 20 candidate biomarkers of coffee consumption were associated with incident CKD. One metabolite (glycochenodeoxycholate), a lipid involved in primary bile acid metabolism, may contribute to the favorable kidney health outcomes associated with coffee consumption. Two metabolites (O-methylcatechol sulfate and 3-methyl catechol sulfate), both of which are xenobiotics involved in benzoate metabolism, may represent potential harmful aspects of coffee on kidney health.

An investigation of cross-sectional associations of a priori-selected dietary components with circulating bile acids

BACKGROUND

A growing body of literature suggests chronically higher bile acid (BA) concentrations may be associated with multiple health conditions. Diet may affect BA metabolism and signaling; however, evidence from human populations is lacking.

OBJECTIVES

We systematically investigated cross-sectional associations of a priori-selected dietary components (fiber, alcohol, coffee, fat) with circulating BA concentrations.

METHODS

We used targeted, quantitative LC-MS/MS panels to measure 15 circulating BAs in a subset of the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC; n = 2224) and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO; n = 986) comprising Finnish male smokers and United States men and women, respectively. We used multivariable linear regression to estimate associations of each dietary component with log-transformed BAs; exponentiated coefficients estimate proportional differences. We included the median of the dietary component quartile in linear regression models to test for trend.

RESULTS

In ATBC, fiber was inversely associated with multiple circulating BAs. The proportional difference was -10.09% (95% CI: -19.29 to 0.16; P-trend = 0.04) when comparing total BAs among those in the highest relative to the lowest fiber quartile. Alcohol, trans fat, and polyunsaturated fat were positively associated with BAs in ATBC. The proportional difference comparing total BAs among those in the highest relative to the lowest alcohol quartile was 8.76% (95% CI: -3.10 to 22.06; P-trend = 0.03). Coffee and monounsaturated fat were inversely associated with BAs. The proportional difference comparing total BAs among those in the highest relative to the lowest coffee quartile was -24.03% (95% CI: -31.57 to -15.66; P-trend < 0.0001). In PLCO, no dietary components were associated with BAs except fiber, which was inversely associated with tauroursodeoxycholic acid.

CONCLUSIONS

Alcohol, coffee, certain fat subtypes, and fiber were associated with circulating concentrations of multiple BAs among Finnish male smokers. Given the potential role of BAs in disease risk, further investigation of the effects of diet on BAs in humans is warranted.

Reproducibility, Temporal Variability, and Concordance of Serum and Fecal Bile Acids and Short Chain Fatty Acids in a Population-Based Study

BACKGROUND

Bile acid (BA) and short chain fatty acid (SCFA) production is affected by diet and microbial metabolism. These metabolites may play important roles in human carcinogenesis.

METHODS

We used a fully quantitative targeted LC-MS/MS system to measure serum and fecal BA and SCFA concentrations in 136 Costa Rican adults at study baseline and 6-months. We randomly selected 50 participants and measured their baseline samples in duplicate. Our objective was to evaluate: Technical reproducibility; 6-month temporal variability; and concordance between sample type collected from the same individual at approximately the same time.

RESULTS

Technical reproducibility was excellent, with intraclass correlation coefficients (ICC) ≥0.83 for all BAs except serum tauroursodeoxycholic acid (ICC = 0.72) and fecal glycolithocholic acid (ICC = 0.66) and ICCs ≥0.81 for all SCFAs except serum 2-methylbutyric acid (ICC = 0.56) and serum isobutyric acid (ICC = 0.64). Temporal variability ICCs were generally low, but several BAs (i.e., deoxycholic, glycoursodeoxycholic, lithocholic, taurocholic, and tauroursodeoxycholic acid) and SCFAs (i.e., 2-methylbutyric, butyric, propionic, and valeric acid) had 6-month ICCs ≥0.44. The highest degree of concordance was observed for secondary and tertiary BAs.

CONCLUSIONS

Serum and fecal BAs and SCFAs were reproducibly measured. However, 6-month ICCs were generally low, indicating that serial biospecimen collections would increase statistical power in etiologic studies. The low concordance for most serum and fecal metabolites suggests that consideration should be paid to treating these as proxies.

IMPACT

Our findings will inform the design and interpretation of future human studies on associations of BAs, SCFAs, and potentially other microbial metabolites, with disease risk.

Neonatal heel prick mass spectrometry identifies metabolic predictors of AML latency

Ongoing research efforts that consider cancer as a disease of dramatically altered cellular metabolism have accelerated interest in snapshot metabolomics in various human tissues. In this issue of Leukemia Research, Petrick et al performed metabolomic analysis on newborn blood spots and found a number of unexpected ceramide and sphingolipid compounds that may play a role in the development and latency of pediatric acute myeloid leukemia (AML). The chemical complexity and range of cellular metabolites massively exceeds the relatively limited building blocks of the transcriptome or the proteome and has high potential to find novel leukemia-specific macromolecular synthesis pathways, metabolic vulnerabilities and biomarkers.

Association between Pre-Diagnostic Serum Bile Acids and Hepatocellular Carcinoma: The Singapore Chinese Health Study

Hepatocellular carcinoma (HCC) is a commonly diagnosed malignancy with poor prognosis. Rising incidence of HCC may be due to rising prevalence of metabolic dysfunction-associated fatty liver disease, where altered bile acid metabolism may be implicated in HCC development. Thirty-five bile acids were quantified using ultra-performance liquid chromatography triple-quadrupole mass spectrometry assays in pre-diagnostic serum of 100 HCC cases and 100 matched controls from the Singapore Chinese Health Study. Conditional logistic regression was used to assess associations for bile acid levels with risk of HCC. Conjugated primary bile acids were significantly elevated whereas the ratios of secondary bile acids over primary bile acids were significantly lower in HCC cases than controls. The respective odds ratios and 95% confidence intervals of HCC were 6.09 (1.75-21.21) for highest vs. lowest tertile of cholic acid species and 30.11 (5.88-154.31) for chenodeoxycholic acid species. Doubling ratio of taurine-over glycine-conjugated chenodeoxycholic acid was associated significantly with 40% increased risk of HCC whereas doubling ratio of secondary over primary bile acid species was associated with 30-40% reduced risk of HCC. In conclusion, elevated primary bile acids and taurine over glycine-conjugated ratios were strongly associated with HCC risk whereas the ratios of secondary bile acids over primary bile acids were inversely associated with HCC risk.

Circulating amino acids and amino acid-related metabolites and risk of breast cancer among predominantly premenopausal women

Known modifiable risk factors account for a small fraction of premenopausal breast cancers. We investigated associations between pre-diagnostic circulating amino acid and amino acid-related metabolites (N = 207) and risk of breast cancer among predominantly premenopausal women of the Nurses' Health Study II using conditional logistic regression (1057 cases, 1057 controls) and multivariable analyses evaluating all metabolites jointly. Eleven metabolites were associated with breast cancer risk (q-value < 0.2). Seven metabolites remained associated after adjustment for established risk factors (p-value < 0.05) and were selected by at least one multivariable modeling approach: higher levels of 2-aminohippuric acid, kynurenic acid, piperine (all three with q-value < 0.2), DMGV and phenylacetylglutamine were associated with lower breast cancer risk (e.g., piperine: ORadjusted (95%CI) = 0.84 (0.77-0.92)) while higher levels of creatine and C40:7 phosphatidylethanolamine (PE) plasmalogen were associated with increased breast cancer risk (e.g., C40:7 PE plasmalogen: ORadjusted (95%CI) = 1.11 (1.01-1.22)). Five amino acids and amino acid-related metabolites (2-aminohippuric acid, DMGV, kynurenic acid, phenylacetylglutamine, and piperine) were inversely associated, while one amino acid and a phospholipid (creatine and C40:7 PE plasmalogen) were positively associated with breast cancer risk among predominately premenopausal women, independent of established breast cancer risk factors.

Untargeted metabolomics of newborn dried blood spots reveals sex-specific associations with pediatric acute myeloid leukemia

The etiology of pediatric acute myeloid leukemia (AML) is largely unknown, but evidence for mutations in utero and long latency periods suggests that environmental factors play a role. Therefore, we used untargeted metabolomics of archived newborn dried blood spots (DBS) to investigate neonatal exposures as potential causal risk factors for AML. Untargeted metabolomics profiling was performed on DBS punches from 48 pediatric patients with AML and 46 healthy controls as part of the California Childhood Leukemia Study (CCLS). Because sex disparities are suggested by differences in AML incidence rates, metabolite features associated with AML were identified in analyses stratified by sex. There was no overlap between the 16 predictors of AML in females and 15 predictors in males, suggesting that neonatal metabolomic profiles of pediatric AML risk are sex-specific. In females, four predictors of AML were putatively annotated as ceramides, a class of metabolites that has been linked with cancer cell proliferation. In females, two metabolite predictors of AML were strongly correlated with breastfeeding duration, indicating a possible biological link between this putative protective risk factor and childhood leukemia. In males, a heterogeneous metabolite profile of AML predictors was observed. Replication with larger participant numbers is required to validate findings.

Validation of soy isoflavone intake and its health effects: a review of the development of exposure biomarkers

BACKGROUND/OBJECTIVES

It is difficult to consistently demonstrate the health effects of soy isoflavones owing to the multitude of factors contributing to their bioavailability. To accurately verify these health effects, dietary isoflavone intake should be measured using a biologically active dose rather than an intake dose. This concept has been expanded to the development of new exposure biomarkers in nutrition research. This review aims to provide an overview of the development of exposure biomarkers and suggest a novel research strategy for identifying the health effects of soy isoflavone intake.

MATERIALS/METHODS

We cover recent studies on the health effects of soy isoflavones focusing on isoflavone metabolites as exposure biomarkers.

RESULTS

Compared to non-fermented soy foods, fermented soy foods cause an increased concentration of isoflavones in the biofluid immediately following ingestion. The correlation between exposure biomarkers in blood and urine and the food frequency questionnaire was slightly lower than that of corresponding 24-h dietary recalls. Urinary and blood isoflavone levels did not show a consistent association with chronic disease and cancer risk.

CONCLUSION

It is crucial to understand the variable bioavailabilities of soy isoflavones, which may affect evaluations of soy isoflavone intake in health and disease. Further studies on the development of valid exposure biomarkers are needed to thoroughly investigate the health effects of isoflavone.

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

Longitudinal change of metabolite profile and its relation to multiple risk factors for the risk of developing hepatitis B-related hepatocellular carcinoma

Despite considerable knowledge of viral pathogenesis, the pathophysiological changes related to the multifactorial, multistep process of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) development remains unclear. Longitudinal metabolomics study can reveal biological process for disease progression. We performed metabolite profiling with longitudinal prediagnostic plasma samples from two nested case-control studies of hepatitis B surface antigen carriers participating in ultrasound screening for HCC, one within a government employee cohort (870 samples from 109 HCC cases and 107 controls) and the other within a hospital-based cohort (266 samples from 63 HCC cases and 114 controls). Of the 34 measured metabolites, tyrosine, isoleucine, and glutamine were consistently associated with HCC. In analyses combining longitudinal data, a high metabolic risk score based on the three amino acids was robustly associated with increased risk of HCC (OR = 3.71, 95% confidence interval: 2.53-5.42), even after adjustment for clinical factors, or when assessed for different times up to ≥8 years before diagnosis. Similar association was observed in an independent, prospective analysis comprising 633 randomly selected individuals of the government employee cohort. More importantly, this metabolite signature was longitudinally influenced by HBV-infection phase and involved in gradual progression to liver fibrosis and cirrhosis. Furthermore, mediation analysis showed that the score mediated substantial proportions of the associations of key viral factors, insulin resistance, and diabetes status with HCC risk. Our results suggest that an amino-acid dysregulation metabotype may play a role in HBV-related HCC development, and may also be linked to common pathways that mediate increased HCC risks.

Prediagnostic concentrations of circulating bile acids and hepatocellular carcinoma risk: REVEAL-HBV and HCV studies

Hepatocellular carcinoma (HCC) is the dominant histologic type of liver cancer, accounting for 75% of cases. Growing evidence suggests that the cross-talk between the gut microbiome and metabolome (ie, gut-liver axis) are related to the development of hepatic inflammation, and ultimately, HCC. Bile acids are metabolites, derived from cholesterol and synthesized in the liver, which may have a critical role in regulation of the gut-liver axis. We investigated whether prediagnostic circulating bile acids were associated with HCC risk, using the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer (REVEAL)-Hepatitis B Virus (HBV) and REVEAL-Hepatitis C Virus (HCV) cohorts from Taiwan. Fifteen bile acids were quantitated using liquid chromatography, from 185 cases and 161 matched controls in REVEAL-HBV and 96 cases and 96 matched controls in REVEAL-HCV. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between bile acid levels and HCC were calculated using multivariable-adjusted logistic regression. Higher levels of glycine and taurine conjugated primary bile acids were associated with a 2- to 8-fold increased risk of HBV- (eg, glycocholic acid OR_Q4vsQ1 = 3.38, 95% CI: 1.48-7.71, P_trend < .003) and HCV-related HCC (eg, OR = 8.16, 95% CI: 2.21-30.18, P_trend < .001). However, higher levels of the secondary bile acid deoxycholic acid were inversely associated with HBV-related HCC risk (OR = 0.41, 95% CI: 0.19-0.88, P_trend = .02). Our study provides evidence that higher concentrations of bile acids-specifically, conjugated primary bile acids-are associated with increased HCC risk. However, our study does not support the hypothesis that higher levels of secondary bile acids increase liver cancer risk; indeed, deoxycholic acid may be associated with a decreased HCC risk.

Dietary Protein, Fiber and Coffee Are Associated with Small Intestine Microbiome Composition and Diversity in Patients with Liver Cirrhosis

The gut microbiome is a key factor in chronic liver disease progression. In prior research, we found that the duodenal microbiome was associated with sex, ethnicity, and cirrhosis complications. Here, we examined the association between diet and the duodenal microbiome in patients with liver cirrhosis. This study included 51 participants who completed a detailed food frequency questionnaire and donated duodenal biopsies for microbiome characterization by 16S ribosomal RNA gene sequencing. Data were analyzed for alpha diversity, beta diversity, and association of taxa abundance with diet quality and components using QIIME 2 pipelines. Diet quality was assessed through calculation of the Healthy Eating Index 2010. Participants with higher adherence to protein recommendations exhibited increased microbial richness and evenness (p = 0.03) and a different microbial profile compared to those with lower adherence (p = 0.03). Prevotella-9 and Agathobacter were increased in association with increased protein adherence. Fiber consumption was also associated with the duodenal microbial profile (p = 0.01), with several taxa exhibiting significantly decreased or increased abundance in association with fiber intake. Coffee drinking was associated with microbial richness and evenness (p = 0.001), and there was a dose–response association between coffee drinking and relative abundance of Veillonella (p = 0.01). We conclude that protein, fiber, and coffee are associated with diversity and composition of the duodenal microbiome in liver cirrhosis.

Physical Activity and Risk of Hepatocellular Carcinoma Among U.S. Men and Women

Mounting evidence indicates a potential beneficial effect of vigorous-intensity physical activity on hepatocellular carcinoma (HCC). However, the association between moderate-intensity physical activity, such as brisk walking, and the risk of HCC remains largely unknown. Two prospective cohorts of 77,535 women from the Nurses' Health Study and 44,540 men from the Health Professionals Follow-up Study were included. Weekly time spent on physical activities were updated biennially. The Cox proportional hazard regression model was used to calculate multivariable hazard ratios (HR) and 95% confidence intervals (95% CI). After an average 23-year follow-up, we identified 138 incident HCC cases. A higher amount of total physical activity was not significantly associated with a reduced risk of HCC (top tertile vs. bottom tertile; HR = 0.78; 95% CI, 0.51-1.18; P _trend = 0.33). For the same comparison, there was an inverse association between moderate-intensity activity and HCC risk (HR = 0.60; 95% CI, 0.38-0.94; P _trend = 0.04), whereas no statistically significant association with vigorous-intensity activity (HR = 0.88; 95% CI, 0.56-1.37; P _trend = 0.74). Engaging in brisk walking was significantly associated with a lower risk of HCC (over 1 hour/week vs. non-brisk walking; HR = 0.50; 95% CI, 0.31-0.78; P _trend = 0.006). The association between brisk walking and HCC risk was generally present across all subgroups, including age, body mass index, type 2 diabetes mellitus, smoking status, aspirin use, and alcohol consumption (all P _interaction ≥ 0.05). In conclusion, moderate-intensity activity, especially brisk walking, was associated with reduced risk of HCC among U.S. men and women. If confirmed, brisk walking might serve a feasible way for HCC prevention.

Metabolomics identified new biomarkers for the precise diagnosis of pancreatic cancer and associated tissue metastasis

Pancreatic cancer (PC) is one of the most aggressive malignancies with high mortality due to a complex and latent pathogenesis leading to the severe lack of early diagnosis methods. To improve clinical diagnosis and enhance therapeutic outcome, we employed the newly developed precision-targeted metabolomics method to identify and validate metabolite biomarkers from the plasma samples of patients with pancreatic cancer that can sensitively and efficiently diagnose the onsite progression of the disease. Many differential metabolites have the capacity to markedly distinguish patients with pancreatic cancer (n = 60) from healthy controls (n = 60). To further enhance the specificity and selectivity of metabolite biomarkers, a dozen tumor tissues from PC patients and paired normal tissues were used to clinically validate the biomarker performance. We eventually verified five new metabolite biomarkers in plasma (creatine, inosine, beta-sitosterol, sphinganine and glycocholic acid), which can be used to readily diagnose pancreatic cancer in a clinical setting. Excitingly, we proposed a panel biomarker by integrating these five individual metabolites into one pattern, demonstrating much higher accuracy and specificity to precisely diagnose pancreatic cancer than conventional biomarkers (CA125, CA19-9, CA242 and CEA); moreover, this plasma panel biomarker used for PC diagnosis is also quite convenient to implement in clinical practice. Using the same metabolomics method, we characterized succinic acid and gluconic acid as having a great capability to monitor the progression and metastasis of pancreatic cancer at different stages. Taken together, this metabolomics method was used to identify and validate metabolite biomarkers that can precisely and sensitively diagnose the onsite progression and metastasis of pancreatic cancer in a clinical setting. Furthermore, such effort should leave clinicians with the correct time frame to facilitate early and efficient therapeutic interventions, which could largely improve the five-year survival rate of PC patients by significantly lowering clinical mortality.

Diet and liver cancer risk: a narrative review of epidemiological evidence

Primary liver cancer is the third leading cause of cancer-related death worldwide. Most patients are diagnosed at late stages with poor prognosis; thus, identification of modifiable risk factors for primary prevention of liver cancer is urgently needed. The well-established risk factors of liver cancer include chronic infection with hepatitis B virus (HBV) or hepatitis C virus (HCV), heavy alcohol consumption, metabolic diseases such as obesity and diabetes, and aflatoxin exposure. However, a large proportion of cancer cases worldwide cannot be explained by current known risk factors. Dietary factors have been suspected as important, but dietary aetiology of liver cancer remains poorly understood. In this review, we summarised and evaluated the observational studies of diet including single nutrients, food and food groups, as well as dietary patterns with the risk of developing liver cancer. Although there are large knowledge gaps between diet and liver cancer risk, current epidemiological evidence supports an important role of diet in liver cancer development. For example, exposure to aflatoxin, heavy alcohol drinking and possibly dairy product (not including yogurt) intake increase, while intake of coffee, fish and tea, light-to-moderate alcohol drinking and several healthy dietary patterns (e.g. Alternative Healthy Eating Index) may decrease liver cancer risk. Future studies with large sample size and accurate diet measurement are warranted and need to consider issues such as the possible aetiological heterogeneity between liver cancer subtypes, the influence of chronic HBV or HCV infection, the high-risk populations (e.g. cirrhosis) and a potential interplay with host gut microbiota or genetic variations.

Coffee and digestive cancers-what do we know, and where do we go?

Coffee drinking has been inversely associated with liver cancer consistently in prospective studies. Yet, the specific compounds underlying this association, and whether associations vary by preparation method, are unknown. Associations with other sites within the gastrointestinal tract are also unclear. A recent study by Tran et al. leverages the resources of the UK Biobank to begin answering these questions, and suggests important avenues for future work.

Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.