Mingming Su

Salivary metabolite signatures of oral cancer and leukoplakia

Oral cancer, one of the six most common human cancers with an overall 5‐year survival rate of <50%, is often not diagnosed until it has reached an advanced stage. The aim of the current study is to explore salivary metabolomics as a disease diagnostic and stratification tool for oral cancer and leukoplakia and evaluate the potential of salivary metabolome for detection of oral squamous cell carcinoma (OSCC). Saliva metabolite profiling for a group of 37 OSCC patients, 32 oral leukoplakia (OLK) patients and 34 healthy subjects was performed using ultraperformance liquid chromatography coupled with quadrupole/time‐of‐flight mass spectrometry in conjunction with multivariate statistical analysis. The OSCC, OLK and healthy control groups demonstrate characteristic salivary metabolic signatures. A panel of five salivary metabolites including γ‐aminobutyric acid, phenylalanine, valine, n‐eicosanoic acid and lactic acid were selected using OPLS‐DA model with S‐plot. The predictive power of each of the five salivary metabolites was evaluated by receiver operating characteristic curves for OSCC. Valine, lactic acid and phenylalanine in combination yielded satisfactory accuracy (0.89, 0.97), sensitivity (86.5% and 94.6%), specificity (82.4% and 84.4%) and positive predictive value (81.6% and 87.5%) in distinguishing OSCC from the controls or OLK, respectively. The utility of salivary metabolome diagnostics for oral cancer is successfully demonstrated in this study and these results suggest that metabolomics approach complements the clinical detection of OSCC and stratifies the two types of lesions, leading to an improved disease diagnosis and prognosis.

Circulating Unsaturated Fatty Acids Delineate the Metabolic Status of Obese Individuals

Background Obesity is not a homogeneous condition across individuals since about 25–40% of obese individuals can maintain healthy status with no apparent signs of metabolic complications. The simple anthropometric measure of body mass index does not always reflect the biological effects of excessive body fat on health, thus additional molecular characterizations of obese phenotypes are needed to assess the risk of developing subsequent metabolic conditions at an individual level. Methods To better understand the associations of free fatty acids (FFAs) with metabolic phenotypes of obesity, we applied a targeted metabolomics approach to measure 40 serum FFAs from 452 individuals who participated in four independent studies, using an ultra-performance liquid chromatograph coupled to a Xevo G2 quadruple time-of-flight mass spectrometer. Findings FFA levels were significantly elevated in overweight/obese subjects with diabetes compared to their healthy counterparts. We identified a group of unsaturated fatty acids (UFAs) that are closely correlated with metabolic status in two groups of obese individuals who underwent weight loss intervention and can predict the recurrence of diabetes at two years after metabolic surgery. Two UFAs, dihomo-gamma-linolenic acid and palmitoleic acid, were also able to predict the future development of metabolic syndrome (MS) in a group of obese subjects. Interpretation These findings underscore the potential role of UFAs in the MS pathogenesis and also as important markers in predicting the risk of developing diabetes in obese individuals or diabetes remission after a metabolic surgery.

Enhanced Fructose Utilization Mediated by SLC2A5 Is a Unique Metabolic Feature of Acute Myeloid Leukemia with Therapeutic Potential

Rapidly proliferating leukemic progenitor cells consume substantial glucose, which may lead to glucose insufficiency in bone marrow. We show that acute myeloid leukemia (AML) cells are prone to fructose utilization with an upregulated fructose transporter GLUT5, which compensates for glucose deficiency. Notably, AML patients with upregulated transcription of the GLUT5-encoding gene SLC2A5 or increased fructose utilization have poor outcomes. Pharmacological blockage of fructose uptake ameliorates leukemic phenotypes and potentiates the cytotoxicity of the antileukemic agent, Ara-C. In conclusion, this study highlights enhanced fructose utilization as a metabolic feature of AML and a potential therapeutic target.

Dysregulated hepatic bile acids collaboratively promote liver carcinogenesis

Dysregulated bile acids (BAs) are closely associated with liver diseases and attributed to altered gut microbiota. Here, we show that the intrahepatic retention of hydrophobic BAs including deoxycholate (DCA), taurocholate (TCA), taurochenodeoxycholate (TCDCA), and taurolithocholate (TLCA) were substantially increased in a streptozotocin and high fat diet (HFD) induced nonalcoholic steatohepatitis‐hepatocellular carcinoma (NASH‐HCC) mouse model. Additionally chronic HFD‐fed mice spontaneously developed liver tumors with significantly increased hepatic BA levels. Enhancing intestinal excretion of hydrophobic BAs in the NASH‐HCC model mice by a 2% cholestyramine feeding significantly prevented HCC development. The gut microbiota alterations were closely correlated with altered BA levels in liver and feces. HFD‐induced inflammation inhibited key BA transporters, resulting in sustained increases in intrahepatic BA concentrations. Our study also showed a significantly increased cell proliferation in BA treated normal human hepatic cell lines and a down‐regulated expression of tumor suppressor gene CEBPα in TCDCA treated HepG2 cell line, suggesting that several hydrophobic BAs may collaboratively promote liver carcinogenesis.

A panel of free fatty acid ratios to predict the development of metabolic abnormalities in healthy obese individuals.

Increasing evidences support that metabolically healthy obese (MHO) is a transient state. However, little is known about the early markers associated with the development of metabolic abnormalities in MHO individuals. Serum free fatty acids (FFAs) profile is highlighted in its association with obesity-related insulin resistance, type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD). To examine the association of endogenous fatty acid metabolism with future development of metabolic abnormalities in MHO individuals, we retrospectively analyzed 24 [product FFA]/[precursor FFA] ratios in fasting sera and clinical data from 481 individuals who participated in three independent studies, including 131 metabolic healthy subjects who completed the 10-year longitudinal Shanghai Diabetes Study (SHDS), 312 subjects cross-sectionally sampled from the Shanghai Obesity Study (SHOS), and 38 subjects who completed an 8-week very low carbohydrate diet (VLCD) intervention study. Results showed that higher baseline level of oleic acid/stearic acid (OA/SA), and lower levels of stearic acid/palmitic acid (SA/PA) and arachidonic acid/dihomo-γ-linolenic acid (AA/DGLA) ratios were associated with higher rate of MHO to MUO conversion in the longitudinal SHDS. Further, the finding was validated in the cross-sectional and interventional studies. This panel of FFA ratios could be used for identification and early intervention of at-risk obese individuals.

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student’s t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics (https://metabolomics.cc.hawaii.edu/software/MetImp/).

Factors affecting separation and detection of bile acids by liquid chromatography coupled with mass spectrometry in negative mode

AbstractBile acids (BAs) are cholesterol metabolites with important biological functions. They undergo extensive host-gut microbial co-metabolisms during the enterohepatic circulation, creating a vast structural diversity and resulting in great challenges to separate and detect them. Based on the bioanalytical reports in the past decade, this work developed three chromatographic gradient methods to separate a total of 48 BA standards on an ethylene-bridged hybrid (BEH) C18 column and high-strength silica (HSS) T3 column and accordingly unraveled the factors affecting the separation and detection of them by liquid chromatography coupled with mass spectrometry (LC-MS). It was shown that both the acidity and ammonium levels in mobile phases reduced the electrospray ionization (ESI) of BAs as anions of [M−H]−, especially for those unconjugated ones without 12-hydroxylation. It was also found that the retention of taurine conjugates on the BEH C18 column was sensitive to the strength of formic acid and ammonium in mobile phases. By using the volatile buffers with an equivalent ammonium level as mobile phases, we comprehensively demonstrated the effects of the elution pH value on the retention behaviors of BAs on both the BEH C18 column and HSS T3 column. Based on the retention data acquired on a C18 column, we presented the ionization constants (pKa) of various BAs with the widest coverage beyond those of previous reports. When we made attempts to establish the structure-retention relationships (SRRs) of BAs, the lack of discriminative structural descriptors for BA stereoisomers emerged as the bottleneck problem. The methods and results presented in this work are especially useful for the development of reliable, sensitive, high-throughput, and robust LC-MS bioanalytical protocols for the quantitative metabolomic studies. Graphical AbstractNonlinear curve fitting of capacity factors and elution pH value for the separation of common unconjugated bile acids.

Urinary metabolic insights into host-gut microbial interactions in healthy and IBD children

AIM To identify metabolic signatures in urine samples from healthy and inflammatory bowel disease (IBD) children. METHODS We applied liquid chromatography and gas chromatography coupled to targeted mass spectrometry (MS)-based metabolite profiling to identify and quantify bile acids and host-gut microbial metabolites in urine samples collected from 21 pediatric IBD patients monitored three times over one year (baseline, 6 and 12 mo), and 27 age- and gender-matched healthy children. RESULTS urinary metabolic profiles of IBD children differ significantly from healthy controls. Such metabolic differences encompass central energy metabolism, amino acids, bile acids and gut microbial metabolites. In particular, levels of pyroglutamic acid, glutamic acid, glycine and cysteine, were significantly higher in IBD children in the course of the study. This suggests that glutathione cannot be optimally synthesized and replenished. Whilst alterations of the enterohepatic circulation of bile acids in pediatric IBD patients is known, we show here that non-invasive urinary bile acid profiling can assess those altered hepatic and intestinal barrier dysfunctions. CONCLUSION The present study shows how non-invasive sampling of urine followed by targeted MS-based metabonomic analysis can elucidate and monitor the metabolic status of children with different GI health/disease status.

Serum stearic acid/palmitic acid ratio as a potential predictor of diabetes remission after Roux-en-Y gastric bypass in obesity

Endogenous fatty acid metabolism that results in elongation and desaturation lipid products is thought to play a role in the development of type 2 diabetes mellitus (T2DM). In this study, we evaluated the potential of estimated elongase and desaturase activities for use as predictive markers for T2DM remission after Roux‐en‐Y gastric bypass (RYGB). The results of a targeted metabolomics approach from 2 independent studies were used to calculate 24 serum FA concentration ratios (product/precursor). Gene expression data from an open public data set was also analyzed. In a longitudinal study of 38 obese diabetic patients with RYGB, we found higher baseline stearic acid/palmitic acid (S/P) ratio. This ratio reflects an elovl6‐encoded elongase enzyme activity that has been found to be associated with greater possibility for diabetes remission after RYGB [odds ratio, 2.16 (95% CI 1.10–4.26)], after adjustment for age, gender, body mass index, diabetes duration, glycosylated hemoglobin A1c, and fasting C‐peptide. Our results were validated by examination of postsurgical elovl6 gene expression in morbidly obese patients. The association of S/P with the metabolic status of obese individuals was further validated in a cross‐sectional cohort of 381 participants. In summary, higher baseline S/P was associated with greater probability of diabetes remission after RYGB and may serve as a diagnostic marker in preoperative patient assessment. —Zhao, L., Ni, Y., Yu, H., Zhang, P., Zhao, A., Bao, Y., Liu, J., Chen, T., Xie, G., Panee, J., Chen, W., Rajani, C., Wei, R., Su, M., Jia, W., Jia, W. Serum stearic acid/palmitic acid ratio as a potential predictor of diabetes remission after Roux‐en‐Y gastric bypass in obesity. FASEB J. 31, 1449–1460 (2017) www.fasebj.org

Metabotypes Related to Meat and Vegetable Intake Reflect Microbial, Lipid and Amino Acid Metabolism in Healthy People

SCOPE The objective of this study is to develop a new methodology to identify the relationship between dietary patterns and metabolites indicative of food intake and metabolism. METHODS AND RESULTS Plasma and urine samples from healthy Swiss subjects (n = 89) collected over two time points are analyzed for a panel of host-microbial metabolites using GC- and LC-MS. Dietary intake is evaluated using a validated food frequency questionnaire. Dietary pattern clusters and relationships with metabolites are determined using Non-Negative Matrix Factorization (NNMF) and Sparse Generalized Canonical Correlation Analysis (SGCCA). Use of NNMF allows detection of latent diet clusters in this population, which describes a high intake of meat or vegetables. SGCCA associates these clusters to i) diet-host microbial and lipid associated bile acid metabolism, and ii) essential amino acid metabolism. CONCLUSION This novel application of NNMF and SGCCA allows detection of distinct metabotypes for meat and vegetable dietary patterns in a heterogeneous population. As many of the metabolites associated with meat or vegetable intake are the result of host-microbiota interactions, the findings support a role for microbiota mediating the metabolic imprinting of different dietary choices.