Representative mass spectra of the MassArray reactions including the three genotypes (A: A/A; B: C/C; C: A/C) of SNP rs357565.

<p>The alleles and UEP (unextended primer) are indicated with thick horizontal arrows.</p

Distributions of the eight genetic polymorphisms in the genomic region of <i>PTCH1</i>.

<p>Red lines represent the SNPs genotyped; blue lines and arrow indicate all the 24 exons within <i>PTCH1</i>.</p

Bile acids concentrations (mean±SD) in dried blood spots of BA, neonatal jaundice and comparison infants.

<p>Bile acids concentrations (mean±SD) in dried blood spots of BA, neonatal jaundice and comparison infants.</p

Receiver operating charactristic curves to discriminate BA and comparison infants for concentrations of TC and total bile acids.

<p>The area under the curve was 0.82 (95% confidence interval: 0.72–0.92) for TC and 0.75 (95% confidence interval: 0.61–0.89) respectively, with p = 0.01976.</p

Sensitivity and specificity of TC concentration in prediction of BA.

<p>Sensitivity and specificity of TC concentration in prediction of BA.</p

Boxplot of total bile acids in dried blood spots of biliary atresia (n = 8), neonatal jaundice (n = 17) and comparison infants (n = 292).

<p>The level of total bile acids in BA was raised significantly compared to comparison infants, with p = 0.0162. BA: biliary atresia infants, Jaun: neonatal jaundice infants, NC: comparison infants.</p

Boxplots of GC (A), GCDC (B), TC (C) and TCDC (D) in dried blood spots of biliary atresia (n = 8), neonatal jaundice (n = 17) and comparison infants (n = 292).

<p>The concentrations of GC, GCDC, TC, and TCDC in BA were significantly higher than those of comparison infants (p<0.05). TC was also significantly elevated in BA compared to neonatal jaundice. No significant difference was observed between neonatal jaundice and comparison infants. BA: biliary atresia infants, Jaun: neonatal jaundice infants, NC: comparison infants.</p

Distinct Plasma Bile Acid Profiles of Biliary Atresia and Neonatal Hepatitis Syndrome

Biliary atresia (BA) is a severe chronic cholestasis disorder of infants that leads to death if not treated on time. Neonatal hepatitis syndrome (NHS) is another leading cause of neonatal cholestasis confounding the diagnosis of BA. Recent studies indicate that altered bile acid metabolism is closely associated with liver injury and cholestasis. In this study, we systematically measured the bile acid metabolome in plasma of BA, NHS, and healthy controls. Liver bile acids were also measured using biopsy samples from 48 BA and 16 NHS infants undergoing operative cholangiography as well as 5 normal adjacent nontumor liver tissues taken from hepatoblastoma patients as controls. Both BA and NHS samples had significantly elevated bile acid levels in plasma compared to normal controls. BA patients showed a distinct bile acid profile characterized by the higher taurochenodeoxycholic acid (TCDCA) level and lower chenodeoxycholic acid (CDCA) level than those in NHS patients. The ratio of TCDCA to CDCA in plasma was significantly higher in BA compared to healthy infants (<i>p</i> < 0.001) or NHS (<i>p</i> < 0.001). The area under receiver operating characteristic curve for TCDCA/CDCA to differentiate BA from NHS was 0.923 (95% CI: 0.862–0.984). These findings were supported by significantly altered expression levels of bile acid transporters and nuclear receptors in liver including farnesoid X receptor (FXR), small heterodimer partner (SHP), bile salt export pump (BSEP), and multidrug resistant protein 3 (MDR3) in BA compared to NHS. Taken together, the plasma bile acid profiles are distinct in BA, NHS, and normal infants, as characterized by the ratio of TCDCA/CDCA differentially distributed among the three groups of infants

Metabolomic Analysis Reveals Metabolic Disturbance in the Cortex and Hippocampus of Subchronic MK-801 Treated Rats

<div><p>Background</p><p>Although a number of proteins and genes relevant to schizophrenia have been identified in recent years, few are known about the exact metabolic pathway involved in this disease. Our previous proteomic study has revealed the energy metabolism abnormality in subchronic MK-801 treated rat, a well-established animal model for schizophrenia. This prompted us to further investigate metabolite levels in the same rat model to better delineate the metabolism dysfunctions and provide insights into the pathology of schizophrenia.</p> <p>Methods</p><p>Metabolomics, a high-throughput investigatory strategy developed in recent years, can offer comprehensive metabolite-level insights that complement protein and genetic findings. In this study, we employed a nondestructive metabolomic approach (1H-MAS-NMR) to investigate the metabolic traits in cortex and hippocampus of MK-801 treated rats. Multivariate statistics and ingenuity pathways analyses (IPA) were applied in data processing. The result was further integrated with our previous proteomic findings by IPA analysis to obtain a systematic view on our observations.</p> <p>Results</p><p>Clear distinctions between the MK-801 treated group and the control group in both cortex and hippocampus were found by OPLS-DA models (with R²X = 0.441, Q²Y = 0.413 and R²X = 0.698, Q²Y = 0.677, respectively). The change of a series of metabolites accounted for the separation, such as glutamate, glutamine, citrate and succinate. Most of these metabolites fell in a pathway characterized by down-regulated glutamate synthesis and disturbed Krebs cycle. IPA analysis further confirmed the involvement of energy metabolism abnormality induced by MK-801 treatment.</p> <p>Conclusions</p><p>Our metabolomics findings reveal systematic changes in pathways of glutamate metabolism and Krebs cycle in the MK-801 treated rats’ cortex and hippocampus, which confirmed and improved our previous proteomic observation and served as a valuable reference to the etiology research of schizophrenia.</p> </div

500 MHz CPMG 1H MAS NMR spectra (1–5 ppm).

<p>Top: hippocampus; bottom: rat cortex. Signals at 1.1–1.23 ppm & 3.62–3.7 ppm (labeled with “*”) correspond to ethanol, a contaminant from tool disinfection during sample preparation. These regions were absent from statistical analyses. Keys: 1, lactate; 2, N-acetylaspartate (NAA); 3, creatine; 4, acetate; 5,γ-Aminobutyric acid (GABA); 6, phophorylcholine (PC); 7, choline; 8, L-valine/L-leucine/L-isoleucine; 9, L-alanine; 10, L-glutamate; 11, L-aspartate; 12, myoinositol; 13, L-glutamine; 14, taurine; 15, succinate.</p