Biology subjects

Jia, W.

Publications and source records attributed to Jia, W..

6 recordsLinked to original sources

bioRxiv2018

Flavor compounds in fermented Chinese alcoholic beverage alter gut microbiota and attenuate ethanol-induced liver

Alcoholic beverages which are consumed widely in most parts of the world have long been identified as a major risk factor for all liver diseases, particularly alcohol-induced liver disease (ALD). Recent compositional analyses suggest that Chinese Baijiu (CB), a clear alcoholic liquid distilled from fermented grains, contains large amounts of small molecule bioactive compounds in addition to a significant amount of ethanol. Here, in an experimental mouse model, we show that CB caused lower degrees of liver injury than pure ethanol by protecting against the decrease of the relative abundance of Akkermansia and increased relative abundance of Prevotella in the gut thereby preventing the destruction of the intestinal barrier. Furthermore, we demonstrated that ethanol-induced alteration of the gut microbiota profoundly affected the host metabolome. Compared with ethanol feeding, CB feeding resulted in higher concentrations of functional saturated LCFAs and SCFAs. Our results provide supporting evidence that ALD was profoundly influenced by host-gut microbiota metabolic interactions and that small molecule organic compounds in CB could attenuate ALD.

microbiology↗

bioRxiv2018

Altered Bile Acid Profile in Mild Cognitive Impairment and Alzheimer’s Disease: Relationship to Neuroimaging and CSF Biomarkers

IntroductionBile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimers disease (AD) including neuroinflammation and amyloid-{beta} deposition.\n\nMethodSerum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n=1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the \"A/T/N\" (Amyloid, Tau and Neurodegeneration) biomarkers for AD: CSF biomarkers, atrophy (MRI), and brain glucose metabolism ([18F]FDG-PET).\n\nResultsOf 23 BA and relevant calculated ratios, three BA signatures were associated with CSF A{beta}1-42 (\"A\") and three with CSF p-tau181 (\"T\") (corrected p<0.05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy (\"N\"), respectively (corrected p<0.05).\n\nConclusionThis is the first study to show serum-based BA metabolites are associated with \"A/T/N\" AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.

neuroscience↗

bioRxiv2018

Altered Bile Acid Profile Associates with Cognitive Impairment in Alzheimer’s Disease – An Emerging Role for Gut Microbiome

IntroductionIncreasing evidence suggests a role for the gut microbiome in central nervous system disorders and specific role for the gut-brain axis in neurodegeneration. Bile acids (BA), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer disease (AD).\n\nMethodsSerum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1,464 subjects including 370 cognitively normal older adults (CN), 284 with early mild cognitive impairment (MCI), 505 with late MCI, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for cofounders and multiple testing.\n\nResultsIn AD compared to CN, we observed significantly lower serum concentrations of a primary BA (cholic acid CA) and increased levels of the bacterially produced, secondary BA, deoxycholic acid (DCA), and its glycine and taurine conjugated forms. An increased ratio of DCA:CA, which reflects 7-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response related genes implicated in AD showed associations with BA profiles.\n\nConclusionWe report for the first time an association between altered BA profile, genetic variants implicated in AD and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut liver brain axis in the pathogenesis of AD.

neuroscience↗

bioRxiv2018

Metabolomics profile of umbilical cord blood is associated with maternal pre-pregnant obesity in a prospective multi-ethnic cohort displaying health disparities

Maternal obesity has become a growing global health concern that may predispose the offspring to medical conditions later in life. However, the metabolic link between maternal pre-pregnant obesity and healthy offspring has not yet been fully elucidated. In this study, we conducted a case-control study using coupled untargeted and targeted metabolomics approach, from the newborn cord blood metabolomes associated with a matched maternal pre-pregnant obesity cohort of 28 cases and 29 controls. The subjects were recruited from multi-ethnic populations in Hawaii, including rarely reported Native Hawaiian and other Pacific Islanders (NHPI). We found that maternal obesity was the most important factor contributing to differences in cord blood metabolomics. Using elastic net regularization based logistic regression model, we identified 29 metabolites as potential early-life biomarkers manifesting intrauterine effect of maternal obesity, with accuracy as high as 0.947 after adjusting for clinical confounding (maternal and paternal age and ethnicity, parity and gravidity). We validated the model results in a subsequent set of samples (N=30) with an accuracy of 0.822. Among the metabolites, six metabolites (galactonic acid, butenylcarnitine, 2-hydroxy-3-methylbutyric acid, phosphatidylcholine diacyl C40:3, 1,5-anhydrosorbitol, and phosphatidylcholine acyl-alkyl 40:3) were individually and significantly different between the maternal obese vs. norm-weight groups. Interestingly, Hydroxy-3-methylbutyric acid showed significnatly higher levels in cord blood from the NHPI group, compared to asian and caucasian groups. In summary, significant associations were observed between maternal pre-pregnant obesity and offspring metabolomics alternation at birth, revealing the inter-generational impact of maternal obesity.

bioinformatics↗

bioRxiv2017

ZmCOL3, a CCT-domain containing gene affects maize adaptation as a repressor and upstream of ZmCCT

Flowering time is a vital trait to control the adaptation of flowering plants to different environments. CCT-domain containing genes are considered to play an important role in plants flowering. Among 53 maize CCT family genes, 28 of them were located in the flowering time QTL regions and 16 genes were significant associated with flowering time based on candidate gene-based association mapping analysis. Furthermore, a CCT gene named as ZmCOL3 was validated to be a flowering repressor upstream of ZmCCT which is one of the key genes regulating maize flowering. The overexpressed ZmCOL3 could delay flowering time about 4 days whether in long day or short day conditions. The absent of one cytosine in 3UTR and the present of 551bp fragment in promoter regions are likely the causal polymorphisms which may contribute to the maize adaptation from tropical to temperate regions. ZmCOL3 could transactivate ZmCCT transcription or interfere circadian clock to inhibit flowering which was integrated in the modified model of maize photoperiod pathway.\n\nHighlightMaize CCT genes influence flowering time in different latitude environments and one of them named ZmCOL3 is a flowering time repressor which could transactivate ZmCCT transcription to delay flowering.

genetics↗

bioRxiv2017

GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies

MotivationLeft-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed.\n\nResultsWe have developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). We compared GSimp with other three imputation methods on two real-world targeted metabolomics datasets and one simulation dataset using our imputation evaluation pipeline. The results show that GSimp outperforms other imputation methods in terms of imputation accuracy, observation distribution, univariate and multivariate analyses, and statistical sensitivity.\n\nAvailability and implementationThe R code for GSimp, evaluation pipeline, vignette, real-world and simulated targeted metabolomics dataset are available on: https://github.com/WandeRum/GSimp.

bioinformatics↗