The interaction effect of metals exposure and dietary habit on cognitive function in Chinese older adult cohort.

BACKGROUND: As the important factors in cognitive function, dietary habits and metal exposures are interactive with each other. However, fewer studies have investigated the interaction effect of them on cognitive dysfunction in older adults. METHODS: 2,445 registered citizens aged 60-85 years from 51 community health centers in Luohu District, Shenzhen, were recruited in this study based on the Chinese older adult cohort. All subjects underwent physical examination and Mini-cognitive assessment scale. A semi quantitative food frequency questionnaire was used to obtain their food intake frequency, and 21 metal concentrations in their urine were measured. RESULTS: Elastic-net regression model, a machine learning technique, identified six variables that were significantly associated with cognitive dysfunction in older adults. These variables included education level, gender, urinary concentration of arsenic (As) and cadmium (Cd), and the frequency of monthly intake of egg and bean products. After adjusting for multiple factors, As and Cd concentrations were positively associated with increased risk of mild cognitive impairment (MCI) in the older people, with OR values of 1.19 (95% CI: 1.05-1.42) and 1.32 (95% CI: 1.01-1.74), respectively. In addition, older adults with high frequency of egg intake (≥30 times/month) and bean products intake (≥8 times/month) had a reduced risk of MCI than those with low protein egg intake (<30 times/month) and low bean products intake (<8 times/month), respectively. Furthermore, additive interaction were observed between the As exposure and egg products intake, as well as bean products. Cd exposure also showed additive interactions with egg and bean products intake. CONCLUSIONS: The consumption of eggs and bean products, as well as the levels of exposure to the heavy metals Cd and As, have been shown to have a substantial influence on cognitive impairment in the elderly population.

A dataset of branched fatty acid esters of hydroxy fatty acids diversity in foods.

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) are a class of bioactive lipids that show therapeutic potential for diabetes, anti-cancer and inflammation. These FAHFAs can be obtained through dietary intake, potentially improving human health. However, there is currently inadequate knowledge regarding the presence and variety of FAHFAs in different foods. Herein, we profile FAHFAs from 12 typical food samples and 4 medicinal food samples with the aid of our previous established chemical isotope labeling-assisted liquid chromatography-mass spectrometry method and build a comprehensive dataset of FAHFA diversity. The dataset comprised a total of 1207 regioisomers belonging to 298 different families, with over 100 families being newly discovered for the first time. Therefore, our findings contribute valuable insights into the molecular diversity and presence of FAHFA in a range of foods. This dataset serves as a foundation for further exploration of the nutritional and medicinal functions of FAHFAs.

Correlating metal exposures and dietary habits with hyperuricemia in a large urban elderly cohort by artificial intelligence.

Epidemiological studies using conventional statistical methods have reported an association between individual metal exposure and hyperuricemia (HUA). There is also evidence that diet may influence HUA development, although the available data are inconsistent. We therefore used an elastic net regression (ENR) model to screen the usefulness of various environmental and dietary factors as predictors of HUA in a large sample cohort. This study included 6217 subjects drawn from the Shenzhen Aging Related Disorder Cohort. We obtained information on the subjects' dietary habits via face-to-face interviews and used inductively coupled plasma mass spectrometry (ICP-MS) to measure the urinary concentrations of 24 metals to which elderly persons in large urban areas may be exposed. An elastic net regression (ENR) model was generated to screen the utility of the metals and dietary factors as predictors of HUA, and we demonstrated the superiority of the ENR model by comparing it to a traditional logistic regression model. The identified predictors were used to create a clinically usable nomogram for identifying patients at risk of developing HUA. The area under curve (AUC) value of the final model was 0.692 for the training set and 0.706 for the test set. Important predictors of HUA were Zn, As, V, and Fe as well as consumption of wheat, beans, and rice; the corresponding estimated odds ratios and 95% confidence intervals were 1.091 (0.932,1.251), 1.190 (1.093,1.286), 0.924 (0.793,1.055), 0.704 (0.626,0.781), 0.998 (0.996,1.001), 0.993 (0.989,0.998), and 1.001 (0.998,1.002), respectively. In contrast to previous studies, we found that both urinary metal concentrations and dietary habits are important for predicting HUA risk. Exposure to specific metals and consumption of specific foods were identified as important predictors of HUA, indicating that the incidence of this disease could be reduced by reducing exposure to these metals and promoting improved dietary habits.

A strategy for screening and identification of new amino acid-conjugated bile acids with high coverage by liquid chromatography-mass spectrometry.

Bile acids (BAs) are a class of vital gut microbiota-host cometabolites, and they play an important role in maintaining gut microbiota-host metabolic homeostasis. Very recently, a new mechanism of BA anabolic metabolism mediated by gut microbiota (BA-amino acid conjugation) has been revealed, which provides a perspective for the research on BA metabolism and gut metabolome. In this study, we established a polarity-switching multiple reaction monitoring mass spectrometry-based screening method to mine amino acid-conjugated bile acids (AA-BAs) derived from host-gut microbiota co-metabolism. In addition, a retention time-based annotation strategy was further proposed to identify the AA-BA isomers and epimers. Using the developed methods, we successfully screened 118 AA-BA conjugates from mouse and human feces, 28 of them were confirmed by standards, and 62 putatively identified based on their predicted retention times. Moreover, we observed that the levels of most AA-BAs were significantly downregulated in the feces of chronic sleep deprivation mice, suggesting that the AA-BA metabolism was closely related to the physiological state of the host.

Alternating Dual-Collision Energy Scanning Mass Spectrometry Approach: Discovery of Novel Microbial Bile-Acid Conjugates.

Bile acids (BAs) are a type of gut microbiota-host cometabolites with abundant structural diversity, and they play critical roles in maintaining host-microbiota homeostasis. In this study, we developed a new N-(4-aminomethylphenyl) pyridinium (AMPP) derivatization-assisted alternating dual-collision energy scanning mass spectrometry (AMPP-dual-CE MS) method for the profiling of BAs derived from host-gut microbiota cometabolism in mice. Using the proposed method, we discovered two new types of amino acid conjugations (alanine conjugation and proline conjugation) and acetyl conjugation with host BAs, for the first time, from mouse intestine contents and feces. Additionally, we also determined and identified nine new leucine- and phenylalanine-conjugated BAs. These findings broaden our knowledge of the composition of the BA pool and provide insight into the mechanism of host-gut microbiota cometabolism of BAs.

Preparation of cotton wool modified with boric acid functionalized titania for selective enrichment of glycopeptides.

An effective enrichment technique is a prerequisite to enable comprehensive analysis of protein glycosylation. In this work, a method was developed for modifying cotton wool with boric acid-functionized titania nanomaterial. The modified cotton wool was used for the preparation of solid phase extraction pipette tips for glycopeptide enrichment. Owing to the unique properties of this novel solid phase material, an enrichment protocol was proposed by using a mixed-mode of hydrophilic interaction liquid chromatography, titania affinity chromatography and boronate affinity chromatography. The performance of the tips was assessed by capturing glycopeptides from tryptic digests of horse radish peroxidase (HRP) and human immunoglobulin G. Modified cotton wool tips allowed the remove of most nonglycosylated peptides. 26 glycopeptides were detected from the HRP digest. The detection limit for glycopeptide determined by MALDI-TOF MS was below 5 fmol. The developed tips are particularly convenient tools for sample pretreatment and show a great potential in glycosylation analysis.