摘要
AIM: To identify plasma metabolites used as biomarkers in order to distinguish cirrhotics from controls and encephalopathics.METHODS: A clinical study involving stable cirrhotic patients with and without overt hepatic encephalopathy was designed. A control group of healthy volunteers was used. Plasma from those patients was analysed using 1H- nuclear magnetic resonance spectroscopy. We used the Carr Purcell Meiboom Gill sequence to process the sample spectra at ambient probe temperature. We used a gated secondary irradiation field for water signal suppression. Samples were calibrated and referenced using the sodium trimethyl silyl propionate peak at 0.00 ppm. For each sample 128 transients(FID's) were acquired into 32 K complex data points over a spectral width of 6 KHz. 30 degree pulses were applied with an acquisition time of 4.0 s in order to achieve better resolution, followed by a recovery delay of 12 s, to allow for complete relaxation and recovery of the magnetisation. A metabolic profile was created for stable cirrhotic patients without signs of overt hepatic encephalopathy and encephalopathic patients as well as healthy controls. Stepwise discriminant analysis was then used and discriminant factors were created to differentiate between the three groups.RESULTS: Eighteen stabled cirrhotic patients, eighteen patients with overt hepatic encephalopathy and seventeen healthy volunteers were recruited. Patients with cirrhosis had significantly impaired ketone body metabolism, urea synthesis and gluconeogenesis. This was demonstrated by higher concentrations of acetoacetate(0.23 ± 0.02 vs 0.05 ± 0.00, P < 0.01), and b-hydroxybutarate(0.58 ± 0.14 vs 0.08 ± 0.00, P < 0.01), lower concentrations of glutamine(0.44 ± 0.08 vs 0.63 ± 0.03, P < 0.05), histidine(0.16 ± 0.01 vs 0.36 ± 0.04, P < 0.01) and arginine(0.08 ± 0.01 vs 0.14 ± 0.02, P < 0.03) and higher concentrations of glutamate(1.36 ± 0.25 vs 0.58 ± 0.04, P < 0.01), lactate(1.53 ± 0.11 vs 0.42 ± 0.05, P < 0.01), pyruvate(0.11 ± 0.02 vs 0.03 ± 0.00, P < 0.01) threonine(0.39 ± 0.02 vs 0.08 ± 0.01, P < 0.01) and aspartate(0.37 ± 0.03 vs 0.03 ± 0.01). A five metabolite signature by stepwise discriminant analysis could separate between controls and cirrhotic patients with an accuracy of 98%. In patients with encephalopathy we observed further derangement of ketone body metabolism, impaired production of glycerol and myoinositol, reversal of Fischer's ratio and impaired glutamine production as demonstrated by lower b-hydroxybutyrate(0.58 ± 0.14 vs 0.16 ± 0.02, P < 0.0002), higher acetoacetate(0.23 ± 0.02 vs 0.41 ± 0.16, P < 0.05), leucine(0.33 ± 0.02 vs 0.49 ± 0.05, P < 0.005) and isoleucine(0.12 ± 0.02 vs 0.27 ± 0.02, P < 0.0004) and lower glutamine(0.44 ± 0.08 vs 0.36 ± 0.04, P < 0.013), glycerol(0.53 ± 0.03 vs 0.19 ± 0.02, P < 0.000) and myoinositol(0.36 ± 0.04 vs 0.18 ± 0.02, P < 0.010) concentrations. A four metabolite signature by stepwise discriminant analysis could separate between encephalopathic and cirrhotic patients with an accuracy of 87%.CONCLUSION: Patients with cirrhosis and patients with hepatic encephalopathy exhibit distinct metabolic abnormalities and the use of metabonomics can select biomarkers for these diseases.
AIM To identify plasma metabolites used as biomarkersin order to distinguish cirrhotics from controls and encephalopathics.METHODS： A clinical study involving stable cirrhoticpatients with and without overt hepatic encephalopathywas designed. A control group of healthy volunteers wasused. Plasma from those patients was analysed using1H - nuclear magnetic resonance spectroscopy. Weused the Carr Purcell Meiboom Gill sequence to processthe sample spectra at ambient probe temperature. Weused a gated secondary irradiation field for water signalsuppression. Samples were calibrated and referencedusing the sodium trimethyl silyl propionate peak at0.00 ppm. For each sample 128 transients （FID＇s）were acquired into 32 K complex data points over aspectral width of 6 KHz. 30 degree pulses were appliedwith an acquisition time of 4.0 s in order to achievebetter resolution, followed by a recovery delay of 12s, to allow for complete relaxation and recovery ofthe magnetisation. A metabolic profile was created forstable cirrhotic patients without signs of overt hepaticencephalopathy and encephalopathic patients as wellas healthy controls. Stepwise discriminant analysis wasthen used and discriminant factors were created todifferentiate between the three groups.RESULTS： Eighteen stabled cirrhotic patients, eighteenpatients with overt hepatic encephalopathy and seventeenhealthy volunteers were recruited. Patients with cirrhosishad significantly impaired ketone body metabolism, ureasynthesis and gluconeogenesis. This was demonstratedby higher concentrations of acetoacetate （0.23 ± 0.02vs 0.05 ± 0.00, P 〈 0.01）, and b-hydroxybutarate （0.58± 0.14 vs 0.08 ± 0.00, P 〈 0.01）, lower concentrationsof glutamine （0.44 ± 0.08 vs 0.63 ± 0.03, P 〈 0.05）,histidine （0.16 ± 0.01 vs 0.36 ± 0.04, P 〈 0.01） andarginine （0.08 ± 0.01 vs 0.14 ± 0.02, P 〈 0.03） andhigher concentrations of glutamate （1.36 ± 0.25 vs0.58 ± 0.04, P 〈 0.01）, lactate （1.53 ± 0.11 vs 0.42± 0.05, P 〈 0.01）, pyruvate （0.11 ± 0.02 vs 0.03 ±0.00, P 〈 0.01） threonine （0.39 ± 0.02 vs 0.08 ± 0.01,P 〈 0.01） and aspartate （0.37 ± 0.03 vs 0.03 ± 0.01）.A five metabolite signature by stepwise discriminantanalysis could separate between controls and cirrhoticpatients with an accuracy of 98%. In patients withencephalopathy we observed further derangementof ketone body metabolism, impaired production ofglycerol and myoinositol, reversal of Fischer＇s ratio andimpaired glutamine production as demonstrated bylower b-hydroxybutyrate （0.58 ± 0.14 vs 0.16 ± 0.02, P〈 0.0002）, higher acetoacetate （0.23 ± 0.02 vs 0.41 ±0.16, P 〈 0.05）, leucine （0.33 ± 0.02 vs 0.49 ± 0.05, P〈 0.005） and isoleucine （0.12 ± 0.02 vs 0.27 ± 0.02, P〈 0.0004） and lower glutamine （0.44 ± 0.08 vs 0.36 ±0.04, P 〈 0.013）, glycerol （0.53 ± 0.03 vs 0.19 ± 0.02,P 〈 0.000） and myoinositol （0.36 ± 0.04 vs 0.18 ± 0.02,P 〈 0.010） concentrations. A four metabolite signatureby stepwise discriminant analysis could separatebetween encephalopathic and cirrhotic patients with anaccuracy of 87%.CONCLUSION： Patients with cirrhosis and patientswith hepatic encephalopathy exhibit distinct metabolicabnormalities and the use of metabonomics can selectbiomarkers for these diseases.
