Aim
To examine the association between depressive symptoms and plasma amino acid related metaboli in older adults.
Methods
A total of 152 older adults aged ≥65 years, residing in Niigata, Japan, were used for analysis. We evaluated depressive symptoms using the Geriatric Depression Scale‐15, which has been validated in older community‐dwelling individuals, and used a cut off score of ≥5 to classify participants as having depressive symptoms. We used high‐performance liquid chromatography‐electrospray ionization mass spectrometry to measure the concentrations of plasma amino acid‐related metabolites, and carried out logistic regression analysis to assess the association between depressive symptoms and plasma amino acid‐related metabolites.
Results
Of the 119 older adults (mean age 76.3 years) included in the analysis, 22 were classified as having depressive symptoms (depressive group). There were no significant differences in physical and cognitive impairments between participants in the depressive and non‐depressive groups. The plasma α‐aminobutyric acid (AABA) level was significantly lower in the depressive group than in the non‐depressive group (P < 0.001). Logistic regression analysis showed the best‐fit model, which included AABA, leucine, threonine, hydroxyl proline and histidine levels (area under the receiver operating characteristic curve 0.8346; 95% confidence interval 0.7365–0.9326). In particular, the plasma AABA level was strongly associated with depressive symptoms.
Conclusions
Plasma AABA level is significantly associated with depression symptoms in older community‐dwelling adults in Japan. Thus, plasma AABA might serve as a potential marker of depression in older adults aged ≥65 years. Geriatr Gerontol Int 2019; 19: 254–258.
A simplified method for analyzing tryptophan (Trp) and its metabolites in human plasma was developed using liquid chromatography-electrospray ionization tandem mass spectrometry. Trp and its metabolites have various chemical properties but have no common functional group for derivatization. Using a reversed-phase pentafluorophenyl (PFP) column for liquid chromatography separation, Trp and its 15 metabolites (3-hydroxyanthranilic acid, 3-hydroxy-kynurenine, 3-indoleacetic acid, 5-hydroxyindole-3-acetic acid, 5-hydroxy-L-tryptophane, anthranilic acid, indole-3-lactic acid, kynurenine, kynurenic acid, melatonin, nicotinic acid, picolinic acid, quinolinic acid, serotonin, and xanthurenic acid were successfully separated within 15 min without derivatization. Neopterin which is known as a biomarker for inflammation and is often evaluated with Trp metabolites in several reports could also be simultaneously analyzed. With this method, Trp and its metabolites were detected with good sensitivity and selectivity without derivatization and solid-phase extraction. The method was validated in this study, showing that the relative standard deviation of 14 Trp metabolites was <15%, and accuracy was within 100% ± 20%, with the exception of nicotinic acid. The quantification range was optimized to 0.0150-100 µM covering the concentration of Trp metabolites in human plasma. Overall, 12 Trp metabolites in healthy human plasma were quantified with good precision and accuracy.
Proteinogenic amino acids are natural nutrients ingested daily from standard foods. Commercially manufactured amino acids are added to a wide range of nutritional products, including dietary supplements and regular foods. Currently, the regulatory risk management of amino acids is conducted by means of setting daily maximum limits of intake. However, there have been no reported adverse effects of amino acid overdosing, while impurities in low-quality amino acids have been identified as causative agents in several health hazard events. This paper reviews the analytical chemistry of impurities in amino acids and highlights major variations in the purity of commercial products. Furthermore, it examines the international standards and global regulatory risk assessment of amino acids utilized in dietary supplements and foods, recommending (1) further research on analytical methods that can comprehensively separate impurities in amino acids, and (2) re-focusing on the regulatory risk management of amino acids to the analytical chemistry of impurities.
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