Sulfur-containing amino acids and risk of schizophrenia.

BACKGROUND: Schizophrenia is a chronic and complex severe psychiatric disorder. Male and female are different in their risks for schizophrenia for the biologic and sociocultural reasons. Homocysteine (Hcy), Cysteine (Cys), and methionine (Met) play important roles in metabolism, and the three amino acids may also be involved in pathogenesis of schizophrenia. OBJECTIVE: This study aimed to test the associations between sulfur-containing amino acid blood levels and risk of schizophrenia, evaluating the different risk in male and female. METHODS: We organized a case-control study on 876 individuals with schizophrenia and 913 age- and sex-matched healthy subjects as control group. The concentrations of Hcy, Cys and Met were measured by liquid chromatography-tandem mass spectrometry technology. Subsequently, restricted cubic spline was applied to explore full-range associations of these amino acids with schizophrenia. Interactions between levels of the three amino acids and sex on additive scale were also tested. RESULTS: Hcy levels at ≤29 µmol/L were associated with sharply increased risk of schizophrenia, inversely, Met was associated with sharply decreased risk of schizophrenia at levels ≤22 µmol/L. Increased Cys levels were associated with decreased risk of schizophrenia. Almost inverse associations were observed between Cys/Hcy and Met/Hcy ratios and schizophrenia. Significant synergistic interactions between levels of all the three amino acids and sex were discovered on an additive scale. CONCLUSIONS: Our study suggests a close association between sulfur-containing amino acids and schizophrenia with different risk in male and female. Future studies are demanded to clarify the pathogenic role of Hcy, Cys and Met in schizophrenia.

Metabolite biomarker discovery for human gastric cancer using dried blood spot mass spectrometry metabolomic approach.

As one of the most common malignancies, gastric cancer (GC) is the third leading cause of cancer-related deaths in China. GC is asymptomatic in early stages, and the majority of GC mortality is due to delayed symptoms. It is an urgent task to find reliable biomarkers for the identification of GC in order to improve outcomes. A combination of dried blood spot sampling and direct infusion mass spectrometry (MS) technology was used to measure blood metabolic profiles for 166 patients with GC and 183 healthy individuals, and 93 metabolites including amino acids, carnitine/acylcarnitines and their derivatives, and related ratios were quantified. Multiple algorithms were used to characterize the changes of metabolic profiles in patients with GC compared to healthy individuals. A biomarker panel was identified in training set, and assessed by tenfold cross-validation and external test data set. After systematic selection of 93 metabolites, a biomarker panel consisting of Ala, Arg, Gly, Orn, Tyr/Cit, Val/Phe, C4-OH, C5/C3, C10:2 shows the potential to distinguish patients with GC from healthy individuals in tenfold cross-validation model (sensitivity: 0.8750, specificity: 0.9006) and test set (sensitivity: 0.9545, specificity: 0.8636). This metabolomic analysis makes contribution to the identification of disease-associated biomarkers and to the development of new diagnostic tools for patients with GC.

A metabolomics strategy to identify potential biomarkers associated with human laryngeal cancer based on dried blood spot mass spectrometry approach.

ABSTRACT: Laryngeal cancer (LC) as one of common malignant tumors in the head and neck region accounted for 1% to 5% of new cancer cases and was ranked as the third otolaryngology cancer. However, some patients with LC were diagnosed at the advanced stage, which can cause delayed diagnosis and treatment. It is an urgent task to seek effective biomarkers for the early diagnosis of LC aimed at alleviating suffering.A combination of dried blood spot sampling and direct infusion mass spectrometry technology was applied to 39 patients with LC and 53 healthy individuals. Multiple algorithms towards 93 metabolites including amino acids and carnitine/acylcarnitines were run for selecting differential metabolites. Furthermore, leave-one-out cross-validation method was used to evaluate diagnostic performance of selected metabolite biomarkers.A biomarker panel consisting of arginine, proline, hexacosanoic carnitine, ornithine /citrulline, and 3-hydroxy-octadecenoylcarnitine exhibited potential to distinguish patients with LC from healthy individuals, with a sensitivity of 0.8974 and a specificity of 0.8302 in leave-one-out cross-validation model.The metabolomic analysis of LC patients is beneficial to screen disease-associated biomarkers and develop new diagnostic approaches.