Ethanol-metabolizing activities and isozyme protein contents of alcohol and aldehyde dehydrogenases in human liver: phenotypic traits of the ADH1B*2 and ALDH2*2 variant gene alleles.

OBJECTIVE: Alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) are principal enzymes responsible for the metabolism of ethanol. East Asian populations are unique in that they carry both a prevalent ADH1B*2 and a dominant-negative ALDH2*2 allele. A systematic investigation of ethanol-metabolizing activities in normal livers correlated with the corresponding functional allelic variations and protein contents of the relevant isozymes in respective enzyme families has been lacking. MATERIALS AND METHODS: To obtain a reasonable sample size encompassing all possible genetic allelotypes of the ADH1B and ALDH2, 141 surgical liver specimens from adult Han Chinese were studied. Expression patterns and activities of ADH and ALDH were determined with stratification of the genetic phenotypes. Absolute protein contents as well as cellular localization of the activity and protein of ADH/ALDH isozymes were also investigated. RESULTS: The activities of ADH1B*1/*2 and ADH1B*2/*2 allelic phenotypes were 5-6-fold those of the ADH1B*1/*1, suggesting that ADH1B*2 allele-encoded subunits are dominant over expression of hepatic ADH activity. The activities of the ALDH2-active phenotype were 90% higher than those of the ALDH2-inactive phenotype. Sex and age did not significantly influence the hepatic ADH and ALDH activities with specified genetic phenotypes. The isozyme protein contents were as follows in decreasing order: ADH1, ADH2, ALDH1A1, ALDH2, and ADH3. Both ADH1, but not ADH2/3, and ALDH1A1/2 showed a preferential expression in perivenular hepatocytes. CONCLUSION: Functional correlations of ADH1B*2 and ALDH2*2 variant alleles in the liver provide a biochemical genetic basis suggesting their contribution toward variability in ethanol metabolism as well as susceptibility to alcoholism and alcohol-related diseases in East Asians.

Steady-state metabolism of ethanol in perfused rat livers treated with cyanamide: quantitative analysis of acetaldehyde effects on the metabolic flux rates.

BACKGROUND: Alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) are principal enzymes responsible for metabolism of ethanol in mammals. The steady-state metabolic flux of ethanol has been poorly understood. METHODS: We investigated flux rates of the individual steps of ethanol metabolism in perfused rat livers treated with ALDH inactivator cyanamide as an attempt to mimic human ALDH2 deficiency commonly seen in East Asians. The net rates of ethanol oxidation, acetaldehyde oxidation, and acetate activation were determined with a set of defined equations, based on the set influx rates of ethanol and the measured efflux rates of ethanol, acetaldehyde, and acetate. RESULTS: After intraperitoneal injections of 0.2 and 1.5 mg/kg cyanamide, hepatic activities of mitochondrial ALDH2 and cytoplasmic ALDH1A1 decreased to a similar degree, that is, 51 to 57% and 69 to 74%, compared with the corresponding controls, respectively, whereas cytoplasmic ADH1 activity remained unchanged. At infusing 2 mM ethanol, acetaldehyde oxidation rate well matched (99%) the net ethanol oxidation rate in control liver. Both the ethanol and acetaldehyde oxidation rates were significantly decreased after cyanamide treatments. At 10 mM ethanol, the efflux acetaldehyde was significantly higher than that infusing 2 mM ethanol in both control and cyanamide groups. Seventy-eight percent of the oxidized ethanol released as efflux acetate. At 2 mM ethanol, the apparent flux control coefficients of ADH1 were assessed to be 0.78, 0.54, and 0.39, respectively, in control, low, and high cyanamide-treated livers. Kinetic simulations revealed that inhibition by acetaldehyde may largely account for the observed reduction of ADH1 oxidation rates after cyanamide treatment. CONCLUSIONS: Our results provide the first flux evidence that ADH and ALDH are steps influencing steady-state metabolism of ethanol in rat livers with inactivated ALDHs.

Dominance of the inactive Asian variant over activity and protein contents of mitochondrial aldehyde dehydrogenase 2 in human liver.

BACKGROUND: It has been well documented that a variant allele of mitochondrial aldehyde dehydrogenase 2 (ALDH2), ALDH2*2, commonly occurs in East Asians but rarely in other ethnic populations. This unique allelic variation significantly influences drinking behavior and susceptibility to development of alcoholism. Previous structural, functional, and cellular studies indicate that the resulting variant polypeptide subunit K (Lys-487) exerts dominance of null activity and shorter half-life over the tetrameric enzyme molecules in distinct manners. However, the in vivo evidence for the proposed dominance mechanisms remains lacking. METHODS: To address this question, we investigated 33 surgical liver samples identified to be normal homozygous ALDH2*1/*1 (n = 17), heterozygous ALDH2*1/*2 (n = 13), and variant homozygous ALDH2*2/*2 (n = 3). The ALDH2 activity was determined at a sufficient low acetaldehyde concentration (3 µM) and the isozyme protein amount by immunotitration using purified class-specific antibodies. RESULTS: The tissue ALDH2 activity in heterozygotes was 17% that of the ALDH2*1/*1 genotype (p < 0.001), whereas the activity of ALDH2*2/*2 was too low to be precisely determined. The protein amounts of tissue ALDH2 in variant homozygotes and heterozygotes were similar but only 30 to 40% that of normal homozygotes (p < 0.01). Linear regression analyses show that ALDH2 activities were significantly correlated with the protein contents in normal homozygotes and heterozygotes, respectively (p < 0.005). The specific activity of ALDH2 per enzyme protein in ALDH2*1/*2 was 38% that of ALDH2*1/*1 (p < 0.001). CONCLUSIONS: These results are in good agreement with those predicted by the model studies, thus providing in vivo evidence for differential impairments of hepatic acetaldehyde oxidation with alcohol metabolism in individuals carrying ALDH2*1/*2 and ALDH2*2/*2 genotypes.

Comparing the sensitivity of fatigue and sleep disturbance assessment tools in women with advanced cancer undergoing chemotherapy.

Objective: This study aims to investigate the variations in fatigue and sleep disturbances among female patients with advanced lung cancer (ALC) and advanced breast cancer (ABC) during chemotherapy. Methods: A total of 36 female patients with ALC and 36 with ABC, all of whom had completed their first cycle of chemotherapy, were included. Fatigue was assessed using the General Fatigue Scale (GFS), and sleep disturbances were evaluated using the Pittsburgh Sleep Quality Index (PSQI) at designated time points throughout the chemotherapy process. Results: Linear regression analysis indicated that variables such as age, education level, employment status, cancer type, clinical stage, and symptom distress had no significant correlation with either fatigue or sleep disturbances. The GFS significantly discriminated fatigue among the ALC, ABC, and combined groups, while the PSQI demonstrated a significant distinction in sleep disturbance only within the ALC and combined groups. Conclusions: In summary, when considering the findings of both assessments in this study, the GFS score exhibited greater sensitivity in detecting fatigue than the PSQI score did for identifying sleep disturbances in advanced cancer patients undergoing chemotherapy.

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees.

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann-Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence. CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence.

The role of ALDH2 and ADH1B polymorphism in alcohol consumption and stroke in Han Chinese.

The genes encoding the enzymes for metabolising alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2) - exhibit genetic polymorphism and ethnic variations. Although the ALDH2*2 variant allele has been widely accepted as protecting against the development of alcoholism in Asians, the association of the ADH1B*2 variant allele with drinking behaviour remains inconclusive. The goal of this study was to determine whether the polymorphic ADH1B and ALDH2 genes are associated with stroke in male Han Chinese with high alcohol consumption. Sixty-five stroke patients with a history of heavy drinking (HDS) and 83 stroke patients without such a history (NHDS) were recruited for analysis of the ADH1B and ALDH2 genotypes from the stroke registry in the Tri-Service General Hospital, Taipei, Taiwan, between January 2000 and December 2001. The allelotypes of ADH1B and ALDH2 were determined using the polymerase chain reaction-restriction fragment length polymorphism method. The HDS patients (3 per cent) showed a significantly lower ALDH2*2 allele frequency than NHDS patients (27 per cent) (p < 0.001). After controlling for age, patients with HDS were associated with a significantly higher occurrence of cigarette smoking (p < 0.01) and liver dysfunction (p < 0.01). Multiple logistic regression analyses revealed that the ALDH2*2 variant allele was an independent variable exhibiting strong protection (odds ratio 0.072; 95 per cent confidence interval 0.02-0.26) against HDS after adjustment for hypertension, diabetes mellitus, smoking status and liver dysfunction. By contrast, allelic variations in ADH1B exerted no significant effect on HDS. The present study indicated that, unlike ALDH2*2, ADH1B*2 appears not to be a significant negative risk factor for high alcohol consumption in male Han Chinese with stroke.

Chemotherapy agents induce tartrate-resistant acid phosphatase 5a contributing to the symptom distress in lung cancer patients.

Tartrate-resistant acid phosphatase 5a (TRACP5a) is mainly secreted by activated macrophages in chronic inflammation. Serum TRACP5a is associated with symptom distress in lung cancer patients during chemotherapy. Therefore, this study aimed to investigate whether chemotherapy drugs modulate TRACP5a as an inducible marker for symptom distress in lung cancer patients during chemotherapy. In clinical analysis, lung cancer participants completely received the six-cycle chemotherapy process (n = 42). Clinical determinations for TRACP5a, C-reactive protein (CRP), interleukin-6 (IL-6), white blood cells, monocytes, and hemoglobin were analyzed at six time points: BL, C1d8, C2d1, C4d1, C4d8, and Ed28. Meanwhile, five questionnaires for fatigue, sleep disturbance, pain, depression, and confusion were finished before drug treatment. For monocyte-to-macrophage differentiation, THP-1 cells were treated with phorbol 12-myristate 13-acetate (PMA). TRACP5a secretion in THP-1 cells was determined at the following days up to 6 days after 1-day incubation of chemotherapy drugs by dot blotting. Clinical analysis revealed that TRACP5a significantly increased at C1d8 and C4d8, but dropped at C2d1 and Ed28. CRP and IL-6 displayed a broad-range variation, resulting in no significant difference among the assessment time points. In contrast, monocytes decreased at C1d8 and C4d8, but rose again at C2d1 and Ed28. In symptom distress, the changes only in fatigue and sleep disturbance were positively associated with the trend in TRACP5a. In PMA-treated THP-1 cells, TRACP5a significantly increased after stimulation with gemcitabine and paclitaxel. Taken together, induction of TRACP5a by chemotherapy drugs might be generated from monocyte-differentiated macrophages, further causing clinical symptom distress in lung cancer patients.

The Relationship Between Inflammatory Biomarkers and Symptom Distress in Lung Cancer Patients Undergoing Chemotherapy.

BACKGROUND: Symptom distress often occurs in lung cancer patients undergoing chemotherapy. However, a biomarker has not been identified to reflect the severity of their symptom distress. OBJECTIVE: The aim of this study was to investigate the relationship between symptom distress and serum inflammatory biomarkers in lung cancer patients undergoing chemotherapy. METHODS: A longitudinal, repeated-measures design was used to assess subjective symptoms (fatigue, sleep disturbance, pain, depression, and confusion), serum biomarkers (tartrate-resistant acid phosphatase 5a [TRACP5a], interleukin 6 [IL-6], IL-8, and C-reactive protein), and white blood cells in 62 lung cancer patients recruited from a single medical center at 3 time points: T1 was the baseline, T2 was the eighth day after the first chemotherapy cycle, and T3 was prior to the second cycle. Symptom distress was measured individually by 5 questionnaires (General Fatigue Scale, Pittsburgh Sleep Quality Index, Brief Pain Inventory, Profile of Mood States-Depressive, and Confusion). RESULTS: The trend of TRACP5a was positively correlated to the trend of the patients' symptom distress. However, the trends of IL-6 and IL-8 did not correlate. CONCLUSIONS: Serum TRACP5a was associated with symptom distress in lung cancer patients. Therefore, TRACP5a might be a potential biomarker to assess symptom distress of lung cancer patients undergoing chemotherapy. IMPLICATIONS FOR PRACTICE: Oncology nurses may be able to apply TRACP5a expression to predict or monitor multiple distress symptoms in lung cancer patients undergoing chemotherapy. Furthermore, nurses can use these study findings to better understand the patients who need more attention to improve their quality of life.

Risk analysis of colorectal cancer incidence by gene expression analysis.

BACKGROUND: Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. OBJECTIVE: Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples. METHODS: We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues. RESULTS: Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method. CONCLUSIONS: Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

Validity and Reliability of the Taiwanese Version of the General Fatigue Scale in Cancer Patients.

BACKGROUND: Fatigue has been described as the most frequent and distressing problem of cancer patients undergoing chemotherapy. OBJECTIVE: The aim of this study is to evaluate the validity and reliability of the Taiwanese version of the General Fatigue Scale (GFS-T) and to evaluate the severity of the fatigue among breast cancer patients in Taiwan. METHODS: A cross-sectional research design was used, recruiting breast cancer patients from 2 medical centers in Taiwan. Patients completed the scale exploring their GFS-T, the Brief Fatigue Inventory-Taiwan Form, and the Eastern Cooperative Oncology Group Performance Status. The data were collected between the day before the first chemotherapy (T1) and 1 week after the first chemotherapy (T2). RESULTS: A total of 171 patients participated in this study. Cronbach's α for the GFS-T at both time points both were .94. Factor analysis generated 1 factor that accounted for 73.7% of variance in participants' fatigue. The receiver operating characteristic curve analyses suggested that the GFS-T cut-point of 24 had an adequate combination of sensitivity and specificity to distinguish high and low performance status. The receiver operating characteristic curve is 0.67 (95% confidence interval, 0.59-0.75). CONCLUSIONS: The GFS-T is a reliable and valid instrument for assessing fatigue among cancer patients. Further research is needed to better understand predictors of cancer-related fatigue. IMPLICATIONS FOR PRACTICE: The GFS-T can provide clinical nurses with a useful measure to assess fatigue in cancer patients.

Verification of gene expression profiles for colorectal cancer using 12 internet public microarray datasets.

AIM: To verify gene expression profiles for colorectal cancer using 12 internet public microarray datasets. METHODS: Logistic regression analysis was performed, and odds ratios for each gene were determined between colorectal cancer (CRC) and controls. Twelve public microarray datasets of GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105, which included 519 cases of adenocarcinoma and 88 normal mucosa controls, were pooled and used to verify 17 selective genes from 3 published studies and estimate the external generality. RESULTS: We validated the 17 CRC-associated genes from studies by Chang et al (Model 1: 5 genes), Marshall et al (Model 2: 7 genes) and Han et al (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray datasets as well as the external validation. The goodness-of-fit test of Hosmer-Lemeshow (H-L) showed statistical significance (P = 0.044) for Model 2 of Marshall et al in which observed event rates did not match expected event rates in subgroups of the model population. Expected and observed event rates in subgroups were similar, which are called well calibrated, in Models 1, 3 and 4 with non-significant P values of 0.460, 0.194 and 1.000 for H-L tests, respectively. A 7-gene model of CPEB4, EIF2S3, MGC20553, MS4A1, ANXA3, TNFAIP6 and IL2RB was pairwise selected, which showed the best results in logistic regression analysis (H-L P = 1.000, R (2) = 0.951, areas under the curve = 0.999, accuracy = 0.968, specificity = 0.966 and sensitivity = 0.994). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.

Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees.

BACKGROUND: Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0). METHODS: Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. RESULTS: The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. CONCLUSION: We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

Gene expression profile of peripheral blood in colorectal cancer.

AIM: Optimal molecular markers for detecting colorectal cancer (CRC) in a blood-based assay were evaluated. METHODS: A matched (by variables of age and sex) case-control design (111 CRC and 227 non-cancer samples) was applied. Total RNAs isolated from the 338 blood samples were reverse-transcribed, and the relative transcript levels of candidate genes were analyzed. The training set was made of 162 random samples of the total 338 samples. A logistic regression analysis was performed, and odds ratios for each gene were determined between CRC and non-cancer. The samples (n = 176) in the testing set were used to validate the logistic model, and an inferred performance (generality) was verified. By pooling 12 public microarray datasets(GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105), which included 519 cases of adenocarcinoma and 88 controls of normal mucosa, we were able to verify the selected genes from logistic models and estimate their external generality. RESULTS: The logistic regression analysis resulted in the selection of five significant genes (P < 0.05; MDM2, DUSP6, CPEB4, MMD, and EIF2S3), with odds ratios of 2.978, 6.029, 3.776, 0.538 and 0.138, respectively. The five-gene model performed stably for the discrimination of CRC cases from controls in the training set, with accuracies ranging from 73.9% to 87.0%, a sensitivity of 95% and a specificity of 95%. In addition, a good performance in the test set was obtained using the discrimination model, providing 83.5% accuracy, 66.0% sensitivity, 92.0% specificity, a positive predictive value of 89.2% and a negative predictive value of 73.0%. Multivariate logistic regressions analyzed 12 pooled public microarray data sets as an external validation. Models that provided similar expected and observed event rates in subgroups were termed well calibrated. A model in which MDM2, DUSP6, CPEB4, MMD, and EIF2S3 were selected showed the result in logistic regression analysis (H-L P = 0.460, R2= 0.853, AUC = 0.978, accuracy = 0.949, specificity = 0.818 and sensitivity = 0.971). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.

The beneficial effect of ST-36 (Zusanli) acupressure on postoperative gastrointestinal function in patients with colorectal cancer.

PURPOSE/OBJECTIVES: To evaluate the effectiveness of ST-36 (Zusanli) acupressure on recovery of postoperative gastrointestinal function in patients with colorectal cancer. DESIGN: A longitudinal, randomized, controlled trial design. SETTING: An urban medical center in Taiwan. SAMPLE: 60 patients with colorectal cancer who had undergone abdominal surgery. METHODS: Patients were randomly assigned to two groups, the ST-36 acupressure group (n = 30) and a sham acupressure group (n = 30). Patients in the ST-36 group received an acupressure procedure in a three-minute cycle performed three times per day during the five days after surgery. Patients in the control group received routine postoperative care and sham acupressure. Generalized estimating equations (GEEs) were used to gauge longitudinal effects of the two groups of patients. MAIN RESEARCH VARIABLES: Frequency of bowel sounds, the time to first flatus passage, first liquid intake, solid intake, and defecation. FINDINGS: Patients who received acupressure had significantly earlier flatus passage and time to liquid intake as compared to patients in the control group. Other main variables, including the first time to solid intake and defecation, did not show significant difference between the two groups. The GEE method revealed that all patients had increasing bowel sounds over time, and the experimental group had greater improvement of bowel motility than the control group within the period of 2-3 days postoperatively. CONCLUSIONS: ST-36 acupressure was able to shorten the time to first flatus passage, oral liquid intake, and improve gastrointestinal function in patients after abdominal surgery. IMPLICATIONS FOR NURSING: ST-36 acupressure can be integrated into postoperative adjunct nursing care to assist patients' postoperative gastrointestinal function. KNOWLEDGE TRANSLATION: Few studies have explored the effectiveness of acupressure techniques on promoting bowel sounds. Evidence from this study suggests stimulation of the ST-36 acupressure point can increase bowel sound frequency for patients with colorectal cancer in the first three days after surgery. Application of this technique may improve a patient's comfort after surgery.

Establishment of steady-state metabolism of ethanol in perfused rat liver: the quantitative analysis using kinetic mechanism-based rate equations of alcohol dehydrogenase.

Alcohol dehydrogenase (ADH) catalyzes oxidation of ingested ethanol to acetaldehyde, the first step in hepatic metabolism. The purpose of this study was to establish an ex vivo rat liver perfusion system under defined and verified steady states with respect to the metabolites and the metabolic rates, and to quantitatively correlate the observed rates with simulations based on the kinetic mechanism-based rate equations of rat liver ADH. Class I ADH1 was isolated from male Sprague-Dawley rats and characterized by steady-state kinetics in the Krebs-Ringer perfusion buffer with supplements. Nonrecirculating liver perfusion with constant input of ethanol at near physiological hepatic blood flow rate was performed in situ. Ethanol and the related metabolites acetaldehyde, acetate, lactate, and pyruvate in perfusates were determined. Results of the initial velocity, product, and dead-end inhibition studies showed that rat ADH1 conformed to the Theorell-Chance Ordered Bi Bi mechanism. Steady-state metabolism of ethanol in the perfused liver maintained up to 3h as evidenced by the steady-state levels of ethanol and metabolites in the effluent, and the steady-state ethanol disappearance rates and acetate production rates. The changes of the metabolic rates were qualitatively and in general quantitatively correlated to the results from simulations with the kinetic rate equations of ADH1 under a wide range of ethanol, in the presence of competitive inhibitor 4-methylpyrazole and of uncompetitive inhibitor isobutyramide. Preliminary flux control analysis estimated that apparent C(ADH)(J) in the perfused liver may approximate 0.7 at constant infusion with 1-2 mM ethanol, suggesting that ADH plays a major but not the exclusive role in governing hepatic ethanol metabolism. The reported steady-state rat liver perfusion system may potentially be applicable to other drug or drug-ethanol interaction studies.

Functional assessment of human alcohol dehydrogenase family in ethanol metabolism: significance of first-pass metabolism.

BACKGROUND: Alcohol dehydrogenase (ADH) is the principal enzyme responsible for ethanol metabolism in mammals. Human ADH constitutes a unique complex enzyme family with no equivalent counterpart in experimental rodents. This study was undertaken to quantitatively assess relative contributions of human ADH isozymes and allozymes to hepatic versus gastric metabolism of ethanol in the context of the entire family. METHODS: Kinetic parameters for ethanol oxidation for recombinant human class I ADH1A, ADH1B1, ADH1B2, ADH1B3, ADH1C1, and ADH1C2; class II ADH2; class III ADH3; and class IV ADH4 were determined in 0.1 M sodium phosphate at pH 7.5 over a wide range of substrate concentrations in the presence of 0.5 mM NAD+. The composite numerical formulations for organ steady-state ethanol clearance were established by summing up the kinetic equations of constituent isozymes/allozymes with the assessed contents in livers and gastric mucosae with different genotypes. RESULTS: In ADH1B*1 individuals, ADH1B1 and ADH1C allozymes were found to be the major contributors to hepatic-alcohol clearance; ADH2 made a significant contribution only at high ethanol levels (> 20 mM). ADH1B2 was the major hepatic contributor in ADH1B*2 individuals. ADH1C allozymes were the major contributor at low ethanol (< 2 mM), whereas ADH1B3 the major form at higher levels (> 10 mM) in ADH1B*3 individuals. For gastric mucosal-alcohol clearance, the relative contributions of ADH1C allozymes and ADH4 were converse as ethanol concentration increased. It was assessed that livers with ADH1B*1 may eliminate approximately 95% or more of single-passed ethanol as inflow sinusoidal alcohol reaches approximately 1 mM and that stomachs with different ADH1C genotypes may remove 20% to 30% of single-passed alcohol at the similar level in mucosal cells. CONCLUSIONS: This work provides just a model, but a strong one, for quantitative assessments of ethanol metabolism in the human liver and stomach. The results indicate that the hepatic-alcohol clearance of ADH1B*2 individuals is higher than that of the ADH1B*1 and those of the ADH1B*3 versus the ADH1B*1 vary depending on sinusoidal ethanol levels. The maximal capacity for potential alcohol first-pass metabolism in the liver is greater than in the stomach.