Trimethylamine N-oxide, choline and its metabolites are associated with the risk of non-alcoholic fatty liver disease.

It is inconclusive whether trimethylamine N-oxide (TMAO) and choline and related metabolites, namely trimethylamine (TMA), l-carnitine, betaine and dimethylglycine (DMG), are associated with non-alcoholic fatty liver disease (NAFLD). Our objective was to investigate these potential associations. Additionally, we sought to determine the mediating role of TMAO. In this 1:1 age- and sex-matched case-control study, a total of 150 pairs comprising NAFLD cases and healthy controls were identified. According to the fully adjusted model, after the highest tertile was compared with the lowest tertile, the plasma TMAO concentration (OR = 2·02 (95 % CI 1·04, 3·92); P trend = 0·003), l-carnitine concentration (OR = 1·79 (1·01, 3·17); P trend = 0·020) and DMG concentration (OR = 1·81 (1·00, 3·28); P trend = 0·014) were significantly positively associated with NAFLD incidence. However, a significantly negative association was found for plasma betaine (OR = 0. 50 (0·28, 0·88); P trend = 0·001). The restricted cubic splines model consistently indicated positive dose-response relationships between exposure to TMAO, l-carnitine, and DMG and NAFLD risk, with a negative association being observed for betaine. The corresponding AUC increased significantly from 0·685 (0·626, 0·745) in the traditional risk factor model to 0·769 (0·716, 0·822) when TMAO and its precursors were included (l-carnitine, betaine and choline) (P = 0·032). Mediation analyses revealed that 14·7 and 18·6 % of the excess NAFLD risk associated with l-carnitine and DMG, respectively, was mediated by TMAO (the P values for the mediating effects were 0·021 and 0·036, respectively). These results suggest that a higher concentration of TMAO is associated with increased NAFLD risk among Chinese adults and provide evidence of the possible mediating role of TMAO.

Enzymatic cascade reactors on carbon nanotube transistor detecting trace prostate cancer biomarker.

Biosensors based on carbon nanotube field-effect transistors (CNT-FETs) have shown great potential in biomarker detection due to their high sensitivity because of appreciable semiconducting electrical properties. However, background signal interferences in complex mediums may results in low signal-to-noise ratio, which may impose challenges for precise biomarker detection in physiological fluids. In this work, we develop an enzymatic CNT-FET, with scalable production at wafer scale, for detection of trace sarcosine that is a biopsy-correlated biomarker of prostate cancer. Enzymatic cascade rectors are constructed on the CNT to improve the reaction efficiency, thereby, enhancing the signal transduction. As such, a limit of detection as low as 105 zM is achieved in buffer solution. Owing to the enhanced reaction efficiency, the testing of clinical serum samples yields significant signal difference to discriminate the prostate cancer (PCa) samples from the benign prostatic hyperplasia (BPH) samples (P = 1.07 × 10-5), demonstrating immense potential in practical applications.

Serum betaine and dimethylglycine in mid-pregnancy and the risk of gestational diabetes mellitus: a case-control study.

PURPOSE: To investigate the associations of choline, betaine, dimethylglycine (DMG), L-carnitine, and Trimethylamine-N-oxide (TMAO) with the risk of Gestational diabetes mellitus (GDM) as well as the markers of glucose homeostasis. METHODS: We performed a case-control study including 200 diagnosed GDM cases and 200 controls matched by maternal age (±2 years) and gestational age (±2 weeks). Concentrations of serum metabolites were measured by the high-performance liquid chromatography - tandem mass spectrometry (HPLC-MS/MS). RESULTS: Compared to the control group, GDM group had significantly lower serum betaine concentration and betaine/choline ratio, and higher DMG concentration. Furthermore, decreased betaine concentration and betaine/choline ratio, increased DMG concentration showed significant association with the risk of GDM. In addition, serum betaine concentrations were negatively associated with blood glucose levels at 1-h post-glucose load (OGTT-1h), and both betaine and L-carnitine concentrations were positively associated with 1,5-anhydroglucitol levels. Betaine/choline ratio was negatively associated with OGTT-1h and blood glucose levels at 2-h post-glucose load (OGTT-2h) and serum choline concentrations were negatively associated with fasting blood glucose and positively associated with OGTT-2h. CONCLUSION: Decreased serum betaine concentrations and betaine/choline ratio, and elevated DMG concentrations could be significant risk factors for GDM. Furthermore, betaine may be associated with blood glucose regulation and short-term glycemic fluctuations.

Changes in Isoleucine, Sarcosine, and Dimethylglycine During OGTT as Risk Factors for Diabetes.

CONTEXT: Current metabolomics studies in diabetes have focused on the fasting state, while only a few have addressed the satiated state. OBJECTIVE: We combined the oral glucose tolerance test (OGTT) and metabolomics to examine metabolite-level changes in populations with different glucose tolerance statuses and to evaluate the potential risk of these changes for diabetes. METHODS: We grouped participants into those with normal glucose tolerance (NGT), impaired glucose regulation (IGR), and newly diagnosed type 2 diabetes (NDM). During the OGTT, serum was collected at 0, 30, 60, 120, and 180 minutes. We evaluated the changes in metabolite levels during the OGTT and compared metabolic profiles among the 3 groups. The relationship between metabolite levels during the OGTT and risk of diabetes and prediabetes was analyzed using a generalized estimating equation (GEE). The regression results were adjusted for sex, body mass index, fasting insulin levels, heart rate, smoking status, and blood pressure. RESULTS: Glucose intake altered metabolic profile and induced an increase in glycolytic intermediates and a decrease in amino acids, glycerol, ketone bodies, and triglycerides. Isoleucine levels differed between the NGT and NDM groups and between the NGT and IGR groups. Changes in sarcosine levels during the OGTT in the diabetes groups were opposite to those in glycine levels. GEE analysis revealed that during OGTT, isoleucine, sarcosine, and acetic acid levels were associated with NDM risks, and isoleucine and acetate levels with IGR risks. CONCLUSION: Metabolic profiles differ after glucose induction in individuals with different glucose tolerance statuses. Changes in metabolite levels during OGTT are potential risk factors for diabetes development.