Machine learning for prediction of schizophrenia based on identifying the primary and interaction effects of minor physical anomalies.

In the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) are considered neurodevelopmental markers of schizophrenia. To date, there has been no research to evaluate the interaction between MPAs. Our study built and used a machine learning model to predict the risk of schizophrenia based on measurements of MPA items and to investigate the potential primary and interaction effects of MPAs. The study included 470 patients with schizophrenia and 354 healthy controls. The models used are classical statistical model, Logistic Regression (LR), and machine leaning models, Decision Tree (DT) and Random Forest (RF). We also plotted two-dimensional scatter diagrams and three-dimensional linear/quadratic discriminant analysis (LDA/QDA) graphs for comparison with the DT dendritic structure. We found that RF had the highest predictive power for schizophrenia (Full-training AUC = 0.97 and 5-fold cross-validation AUC = 0.75). We identified several primary MPAs, such as the mouth region, high palate, furrowed tongue, skull height and mouth width. Quantitative MPA analysis indicated that the higher skull height and the narrower mouth width, the higher the risk of schizophrenia. In the interaction, we further identified that skull height and mouth width, furrowed tongue and skull height, high palate and skull height, and high palate and furrowed tongue, showed significant two-item interactions with schizophrenia. A weak three-item interaction was found between high palate, skull height, and mouth width. In conclusion, we found that the two machine learning methods showed good predictive ability in assessing the risk of schizophrenia using the primary and interaction effects of MPAs.

Discrepancy of social cognition between bipolar disorders and major depressive disorders.

BACKGROUND: The research landscape examining social cognition (SC) impairment in patients with major depressive disorders (MDD) and bipolar disorders (BD) is notably scarce. Presently, assessments predominantly rely on static stimuli and self-reported measures, which may not capture the dynamic dimensions of social cognition. OBJECTIVES: This study aimed to validate the Chinese version of Movie Assessment of Social Cognition (MASC-CH) and to investigate whether MDD and BD exhibit distinct patterns of SC impairments, shedding light on potential differences between these two mood disorders. METHODS: The study encompassed 197 participants, aged 18-65, distributed as follows: 21 BD, 20 MDD, and 156 healthy controls (HC). We focused on examining "cognitive" and "emotional" SC scores and "undermentalizing" and "overmentalizing" error patterns, with nonsocial inference as a control. Additional assessments included the Reading Mind in the Eyes Test (RMET) and the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). We also explored the association between depression severity (measured by the Hamilton Depressive Rating Scale, HDRS) and distinct SC dimensions between MDD and BD. RESULTS: The MASC-CH exhibited strong validity and reliability for SC assessment. In group comparisons, BD participants scored significantly lower on MASC-CH, while the MDD group scores were not significantly different from HC. Specifically, BD individuals had notably lower cognitive SC scores and made more undermentalizing and absence of mentalizing errors than MDD and HC. Additionally, a negative correlation between HDRS score and overmentalizing was observed in BD, not in the MDD. CONCLUSIONS: The findings indicate that depression severity scores in BD were inversely related to MASC-CH scores. In contrast, this relationship was not observed in the MDD group. These results underscore the importance of SC impairments as distinguishing characteristics of both BD and MDD. It provides valuable insights into the distinct social-cognitive profiles of both mood disorders.

DNA methylation signature aberration as potential biomarkers in treatment-resistant schizophrenia: Constructing a methylation risk score using a machine learning method.

Treatment-resistant schizophrenia (TRS) is defined as a non-response to at least two trials of antipsychotic medication with an adequate dose and duration. We aimed to evaluate the discriminant abilities of DNA methylation probes and methylation risk score between treatment-resistant schizophrenia and non-treatment-resistant schizophrenia. This study recruited 96 schizophrenia patients (TRS and non-TRS) and 56 healthy controls (HC). Participants were divided into a discovery set and a validation set. In the discovery set, we conducted genome-wide methylation analysis (human MethylationEPIC 850K BeadChip) on the subject's blood DNA and discriminated significant methylation signatures, then verified these methylation signatures in the validation set. Based on genome-wide scans of TRS versus non-TRS, thirteen differentially methylated probes were identified at FDR <0.05 and >20% differences in DNA methylation ß-values. Next, we selected six probes within gene coding regions (LOC404266, LOXL2, CERK, CHMP7, and SLC17A9) to conduct verification in the validation set using quantitative methylation-specific PCR (qMSP). These six methylation probes showed satisfactory discrimination between TRS patients and non-TRS patients, with an AUC ranging from 0.83 to 0.92, accuracy ranging from 77.8% to 87.3%, sensitivity ranging from 80% to 90%, and specificity ranging from 65.6% to 85%. This methylation risk score model showed satisfactory discrimination between TRS patients and non-TRS patients, with an accuracy of 88.3%. These findings support that methylation signatures may be used as an indicator of TRS vulnerability and provide a model for the clinical use of methylation to identify TRS.

Development and validation of a web-based prediction tool on minor physical anomalies for schizophrenia.

In support of the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) have been suggested as biomarkers and potential pathophysiological significance for schizophrenia. However, an integrated, clinically useful tool that used qualitative and quantitative MPAs to visualize and predict schizophrenia risk while characterizing the degree of importance of MPA items was lacking. We recruited a training set and a validation set, including 463 schizophrenia patients and 281 healthy controls to conduct logistic regression and the least absolute shrinkage and selection operator (Lasso) regression to select the best parameters of MPAs and constructed nomograms. Two nomograms were built to show the weights of these predictors. In the logistic regression model, 11 out of a total of 68 parameters were identified as the best MPA items for distinguishing between patients with schizophrenia and controls, including hair whorls, epicanthus, adherent ear lobes, high palate, furrowed tongue, hyperconvex fingernails, a large gap between first and second toes, skull height, nasal width, mouth width, and palate width. The Lasso regression model included the same variables of the logistic regression model, except for nasal width, and further included two items (interpupillary distance and soft ears) to assess the risk of schizophrenia. The results of the validation dataset verified the efficacy of the nomograms with the area under the curve 0.84 and 0.85 in the logistic regression model and lasso regression model, respectively. This study provides an easy-to-use tool based on validated risk models of schizophrenia and reflects a divergence in development between schizophrenia patients and healthy controls ( https://www.szprediction.net/ ).

Impairment in Emotional Intelligence May Be Mood-Dependent in Bipolar I and Bipolar II Disorders.

Background: An emotional intelligence (EI) deficit has been noticed in euthymic bipolar spectrum disorder (BD) patients. However, whether this deficit is affected by mood or subtype is unclear. Objectives:The aim of this study was to investigate whether an EI deficit is mood-dependent, and which mood symptoms have more impact on EI in BD. Methods: Two hundred and thirty participants aged between 18 and 65 years old were recruited [130 BD patients (51 bipolar I disorder (BDI) and 79 bipolar II disorder (BDII): 39.2% males; 91 healthy controls (HCs): 48.4% males)]. The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), which contains experiential and strategic EI ratings, was used to assess social cognition. The Hamilton Depression Rating Scale (HDRS) and the Young's Mania Rating Scale (YMRS) were used for evaluating the severity [HAMD and YMRS scores ≦7 were euthymic (BDeut) and HAMD YMRS sores ≧8 were episodic (BDepi)]. Analyses of covariance (ANCOVA) were performed, with adjustment for background information between the BD patients and HCs. Results: The results showed that, compared to the HCs, the BDeut patients showed no difference in any MSCEIT measures, while the BDepi patients showed lower scores in all MSCEIT measures, except for perceiving emotions. In addition, a main effect of mood state instead of BD subtype was found for the managing emotions branch (p < 0.0007). Regression analyses showed that the duration of illness and HDRS scores were correlated with the scores in the strategic area of the MSCEIT, while age and YMRS scores were more relevant to the scores in the experiential area of the MSCEIT. Conclusion: The results confirm that an EI deficit is mood-dependent in BD patients. In addition, a depressive mood is more related to the strategic EI area, while a manic mood is correlated with the experiential EI area. Understanding the different domains of EI deficits in BD patients may be helpful for developing interventions for BD.

Effects of mood episodes and comorbid anxiety on neuropsychological impairment in patients with bipolar spectrum disorder.

OBJECTIVES: Cases of patients with bipolar disorder (BD) having neuropsychological impairment have been reported, although inconsistently. The possibility of comorbidity with anxiety disorder (AD) has been suggested. The association between mood episodes and AD comorbidity on neuropsychological performance is unclear and thus was investigated in the current study. METHODS: All participants were informed about and agreed to participate in this study. Patients with BD were recruited from outpatient and inpatient settings, and healthy controls (HCs) were recruited as a comparison group. Six hundred and twenty-eight participants (175 HCs and 453 BD-56 BDI and 397 BDII) were studied based on their current mood episode, namely, depressive (BDd ), manic/hypomanic (BDm), mixed (BDmix), and euthymic (BDeu), compared with/without AD comorbidity (164 with AD). RESULTS: Compared to HCs, all BD groups had significantly more impaired neuropsychological profiles, but the BDeu group was found to have less impairment in memory and executive function than the episodic BD groups. The percentage of AD comorbidity in BDd, BDm, BDmix, and BDeu was 33.9%, 40.3%, 33.0%, and 35.6%, respectively (χ2  = 1.61, p > .05). The results show that AD plays a different role in neuropsychological impairment across various mood episodes in BD. CONCLUSION: Memory impairment and executive dysfunction may be state-like cognitive phenotypes and are affected by AD comorbidity during mixed and depressive episodes in BD, while sustained attention deficiencies are more like trait markers, regardless of mood episodes, and persist beyond the course of the illness. The AD comorbidity effect on attentional deficit is greater when suffering from a manic episode.

The OXTR Polymorphism Stratified the Correlation of Oxytocin and Glucose Homeostasis in Non-Diabetic Subjects.

OBJECTIVE: Previous animal studies have shown that the oxytocin system might affect glucose homeostasis through the hypothalamus-pituitary-adrenal (HPA) axis and peripheral organs. Moreover, whether the effect is stratified by the polymorphism of oxytocin receptor gene (OXTR) remains unclear. METHODS: In this study, we recruited 89 non-diabetic participants. Their plasma oxytocin and serum insulin profiles were obtained, and the polymorphism of OXTR rs53576 was genotyped. RESULTS: There were significant correlations between the oxytocin level and fasting glucose level (r = -0.29, P <0.01), insulin level (r = -0.26, P = 0.01), and homeostasis model assessment-estimated insulin resistance (HOMA-IR) (r = -0.25, P = 0.01), when adjusted for age, gender, and body mass index (BMI). When further considering the stratification effects of OXTR variation, we found that the oxytocin level was significantly correlated with the fasting glucose level (r = -0.25, P = 0.04), insulin level (r = -0.35, P = 0.03), and HOMA-IR (r = -0.35, P < 0.01) in subjects with the OXTR A allele (n = 75) after adjustment for age, gender, and BMI. In addition, the oxytocin level in those with the GG genotype of OXTR was significantly negatively correlated with the leptin level (n = 14, r = -0.66, P = 0.02). CONCLUSION: The results demonstrated that the polymorphism of OXTR plays an important role in individual differences in the correlation of oxytocin and glucose homeostasis in non-diabetic subjects.

Memory Impairment and Plasma BDNF Correlates of the BDNF Val66Met Polymorphism in Patients With Bipolar II Disorder.

Studies suggest that a functional polymorphism of brain-derived neurotrophic factor (BDNF), polymorphism BDNF Val66Met affects cognitive functions, however, the effect is unclear in bipolar II (BD-II) disorder. We used the Wechsler Memory Scale-third edition (WMS-III), the presence of the BDNF Val66Met polymorphism, and plasma concentrations of BDNF to investigate the association between memory impairment and BDNF in BD-II disorder. We assessed the memory functions of 228 BD-II patients and 135 healthy controls (HCs). BD-II patients had significantly lower scores on five of the eight WMS-III subscales. In addition to education, the BDNF polymorphism were associated with the following subscales of WMS-III, auditory delayed memory, auditory delayed recognition memory and general memory scores in BD-II patients, but not in HC. Moreover, BD-II patients with the Val-homozygote scored significantly higher on the visual immediate memory subscale than did those with the Met/Met and Val/Met polymorphisms. The significantly positive effect of the Val-homozygote did not have a significantly positive effect on memory in the HC group, however. We found no significant association between BDNF polymorphisms and plasma concentrations of BDNF. The plasma BDNF was more likely to be associated with clinical characteristics than it was with memory indices in the BD-II group. The impaired memory function in BD-II patients might be dependent upon the association between the BDNF Val66Met polymorphism and peripheral BDNF levels.

Feasibility of using urinary N7-(2-carbamoyl-2-hydroxyethyl) Guanine as a biomarker for acrylamide exposed workers.

Acrylamide (AA), a probable human carcinogen, is a widely-used industrial chemical but is also present in tobacco smoke and carbohydrate-rich foods processed at high temperatures. AA is metabolized to glycidamide (GA) to cause the formation of DNA adducts. N7-(2-carbamoyl-2-hydroxyethyl) guanine (N7-GAG), the most abundant DNA adduct induced by GA, was recently detected in urine of smokers and non-smokers. In this study, we assessed the variability of AA exposure and biomarkers of AA exposure in urine samples repeatedly collected from AA-exposed workers and explored the half-life of N7-GAG. A total of 8 AA-exposed workers and 36 non-exposed workers were recruited. Pre-shift and post-shift urine samples were collected from the exposed group in parallel with personal sampling for eight consecutive days and from the control group on day 1 of the study. Urinary N7-GAG and the mercapturic acids of AA and GA, namely N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) and N-(R,S)-acetyl-S-(1-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA) were analyzed using on-line solid phase extraction-liquid chromatography-electrospray ionization/tandem mass spectrometry methods. We found that N7-GAG levels in urine were significantly higher in exposed workers than in controls and that N7-GAG level correlated positively with AAMA and GAMA levels. Results from this study showed that AAMA and GAMA possibly remain the more preferred biomarkers of AA exposure and that N7-GAG levels could be elevated by occupational exposures to AA and serve as a biomarker of AA-induced genotoxicity for epidemiological studies.

Potential Association of Urinary N7-(2-Carbamoyl-2-hydroxyethyl) Guanine with Dietary Acrylamide Intake of Smokers and Nonsmokers.

Acrylamide (AA), a rodent carcinogen, is widely used in industry and present in cigarette smoke as well as in foods processed at high temperatures. The metabolic activation of AA to glycidamide (GA) could be critical for AA carcinogenicity since GA causes DNA adduct formation in vivo. N7-(2-carbamoyl-2-hydroxyethyl) guanine (N7-GAG), the most abundant DNA adduct of AA, is subjected to spontaneous and enzymatic depurination and excreted through urine. Urinary N7-GAG analysis can confirm AA genotoxicity and identify active species of AA metabolites in humans, thereby serving as a risk-associated biomarker for molecular epidemiology studies. This study aimed to develop an isotope-dilution solid-phase extraction liquid chromatography tandem mass spectrometry method to comparatively analyze urinary N7-GAG levels in nonsmokers and smokers. Urinary N-acetyl-S-(propionamide)-cysteine (AAMA), a metabolite of AA, was also analyzed as a biomarker for current AA exposure. Urinary N7-GAG was quantified by monitoring m/z 239 → 152 for N7-GAG and m/z 242 → 152 for (13)C3-labeled N7-GAG under positive electron spray ionization and multiple reaction mode. The median urinary N7-GAG level was 0.93 µg/g creatinine in nonsmokers (n = 33) and 1.41 µg/g creatinine in smokers (n = 30). Multiple linear regression analysis of data revealed that N7-GAG levels were only significantly associated with AAMA levels. These results demonstrate that urinary N7-GAG of nonsmokers and smokers is significantly associated with a very low level of dietary AA intake, assessed by analyzing urinary AAMA.

Cognitive performance in older elderly men with late-life depression and cardiovascular comorbidities: symptomatological correlation.

BACKGROUND: Whether depression or cardiovascular disease would have a greater effect on worsening cognitive impairment in the burgeoning older elderly population is uncertain. Which disorder causes greater cognitive impairment was investigated. METHODS: A cross section of 207 cognitively impaired older elderly (≥75 years old) men was recruited from outpatient clinics in southern Taiwan between 2004 and 2008. Their medical charts were reviewed for their history of medical illnesses, and those undergoing a current major depressive episode were screened using the Mini-International Neuropsychiatric Interview. Four groups of men were enrolled: 33 healthy controls (HC), 101 cognitively impaired patients with cardiovascular comorbidities (CVCs), 34 patients with late-life depression (LLD), and 49 patients with LLD and cardiovascular comorbidities (LLD + CVC). Several neuropsychological tests (e.g., Mini-Mental State Examination (MMSE), WCST, and Trail Making Test (TMT) parts A and B) were used to assess the participants. RESULTS: Cognitive function scores were highest in the HC group and lowest in the LLD + CVC group. There were no significant differences between the two groups with LLD comorbidity, and LLD was mostly associated with cognitive performance. LLD + CVC group members had the lowest recall memory, but their overall MMSE score was not significantly different. Moreover, this group had a higher but nonsignificantly different perseverative error than did the LLD group. Similarly, the LLD + CVC group was nonsignificantly slower at the TMT-A and TMT-B tasks than was the LLD group. CONCLUSIONS: LLD worsens neuropsychological function more than cardiovascular comorbidities do.

Symptomatological and cognitive correlates of vascular comorbidity in older-elderly (at least 75 years old) men with major depressive disorder.

Depression is a common geriatric psychiatric disorder increasing with age among elderly people (≥ 75 years old), especially those with medical comorbidities. They have higher suicide rates than younger men, but these are paid less attention. Elderly men (n=141) who were newly admitted residents of the Veterans' Home in Tainan, Taiwan from 2004 to 2006 were recruited and screened for major depression. Specialist physicians obtained past histories of medical illnesses through chart reviews, interview, and health examinations. Fifty-nine of the 141 elderly people had major depression and participated in this study. Thirty-nine men in the group with vascular comorbidities (VC), and 20 in the group without (NVC) vascular comorbidities were compared. The VC group had more time-orientation impairment, greater psychomotor retardation, and diminished concentration/decision-making than did the NVC group. Psychomotor retardation and other cognitive function impairments (e.g., concentration and decision-making) are characteristic manifestations among patients with major depression and vascular comorbidity compared with those without vascular comorbidity.

The interaction between BDNF and DRD2 in bipolar II disorder but not in bipolar I disorder.

Bipolar I (BP-I) and bipolar II (BP-II) disorders are the two most common subtypes of bipolar disorder. However, most studies have not differentiated bipolar disorder into BP-I and BP-II groups, for which the underlying etiology differentiating these two subtypes remains unclear. The genetic association between both subtypes is essential for improving our understanding. The dopamine D2 receptor/ankyrin repeat and kinase domain containing 1 (DRD2/ANKK1), one of the dopaminergic pathways, as well as the brain-derived neurotrophic factor (BDNF) gene, were reported as candidate genes in the etiology of bipolar disorder. Therefore, we examined the contribution of the BDNF and DRD2/ANKK1 genes and their interaction to the differentiation of BP-I and BP-II. Seven hundred ninety-two participants were recruited: 208 with BP-I, 329 with BP-II, and 255 healthy controls. The genotypes of the BDNF and DRD2/ANKK1 Taq1A polymorphisms were determined using polymerase chain reactions plus restriction fragment length polymorphism analysis. A significant main effect for the Val/Val genotype of the BDNF Val66Met polymorphism predicted BP-II patients. The significant interaction effect for the Val/Val genotype of the BDNF Val66Met polymorphism and A1/A2 genotype of DRD2/ANKK1 Taq1A polymorphism was found only in BP-II patients. We provide initial evidence that the BDNF Val66Me and DRD2/ANKK1 Taq1A polymorphisms interact only in BP-II disorder and that BP-I and BP-II are genetically distinct.

Comparative analysis of urinary N7-(2-hydroxyethyl)guanine for ethylene oxide- and non-exposed workers.

Ethylene oxide (EO), a direct alkylating agent and a carcinogen, can attack the nucleophilic sites of DNA bases to form a variety of DNA adducts. The most abundant adduct, N7-(2-hydroxyethyl)guanine (N7-HEG), can be depurinated spontaneously or enzymatically from DNA backbone to form abasic sites. Molecular dosimetry of the excised N7-HEG in urine can serve as an EO exposure and potential risk-associated biomarker. This study was to analyze N7-HEG in urine collected from 89 EO-exposed and 48 nonexposed hospital workers and 20 exposed and 10 nonexposed factory workers by using our newly developed on-line solid-phase extraction isotope-dilution LC-MS/MS method. Statistical analysis of data shows that the exposed factory workers excreted significantly greater concentrations of N7-HEG than both the nonexposed factory workers and hospital workers. Multiple linear regression analysis reveals that the EO-exposed factory workers had a significantly greater post-shift urinary N7-HEG than their nonexposed coworkers and hospital workers. These results demonstrate that analysis of urinary N7-HEG can serve as a biomarker of EO exposure for future molecular epidemiology studies to better understand the role of the EO-induced DNA adduct formation in EO carcinogenicity and certainly for routine surveillance of occupational EO exposure for the study of potential health impacts on workers.

The application of mass spectrometry in molecular dosimetry: ethylene oxide as an example.

Mass spectrometry plays an increasingly important role in the search for and quantification of novel chemically specific biomarkers. The revolutionary advances in mass spectrometry instrumentation and technology empower scientists to specifically analyze DNA and protein adducts, considered as molecular dosimeters, derived from reactions of a carcinogen or its active metabolites with DNA or protein. Analysis of the adducted DNA bases and proteins can elucidate the chemically reactive species of carcinogens in humans and can serve as risk-associated biomarkers for early prediction of cancer risk. In this article, we review and compare the specificity, sensitivity, resolution, and ease-of-use of mass spectrometry methods developed to analyze ethylene oxide (EO)-induced DNA and protein adducts, particularly N7-(2-hydroxyethyl)guanine (N7-HEG) and N-(2-hydroxyethyl)valine (HEV), in human samples and in animal tissues. GC/ECNCI-MS analysis after HPLC cleanup is the most sensitive method for quantification of N7-HEG, but limited by the tedious sample preparation procedures. Excellent sensitivity and specificity in analysis of N7-HEG can be achieved by LC/MS/MS analysis if the mobile phase, the inlet (split or splitless), and the collision energy are properly optimized. GC/ECNCI-HRMS and GC/ECNCI-MS/MS analysis of HEV achieves the best performance as compared with GC/ECNCI-MS and GC/EI-MS. In conclusion, future improvements in high-throughput capabilities, detection sensitivity, and resolution of mass spectrometry will attract more scientists to identify and/or quantify novel molecular dosimeters or profiles of these biomarkers in toxicological and/or epidemiological studies.

Biological monitoring for occupational acrylamide exposure from acrylamide production workers.

OBJECTIVE: We conducted a repeated-measurement study to (1) investigate the correlation between occupational exposure to airborne acrylamide (AA) and the time-dependent behavior of urinary AAMA, GAMA2, and GAMA3 and (2) calculate the estimated biological exposure index at the permissible exposure limit (PEL) level of 30 µg/m(3). METHODS: Forty-four workers were recruited--8 were AA-exposed and 36 were controls. Pre- and post-shift urine samples were collected from the exposed group in parallel with personal sampling for 8 consecutive days and only 1 day for the control group and analyzed using liquid chromatography-electrospray ionization/tandem mass spectrometry (LC-ESI-MS/MS). RESULTS: Post-shift urinary AAMA level was significantly associated with personal AA exposure (p < 0.001), indicating that urinary AAMA was a better AA exposure biomarker. The estimated urinary excretion of AAMA was 3.0 mg/g creatinine for nonsmoking workers exposed to the PEL of 30 µg/m(3). The median GAMA (the sum of GAMA2 and GAMA3)/AAMA ratio for exposed workers was 0.03 (range, 0.005-0.14), relatively lower than that of the nonoccupational group. CONCLUSIONS: Although sample size in this study was small, the repeated-measurement data provide useful reference for future studies related to biological monitoring of occupational exposure to AA.

Rapid and sensitive on-line liquid chromatographic/tandem mass spectrometric determination of an ethylene oxide-DNA adduct, N7-(2-hydroxyethyl)guanine, in urine of nonsmokers.

Ethylene oxide (EtO) is classified as a known human carcinogen. The formation of EtO-DNA adducts is considered as an important early event in the EtO carcinogenic process. An isotope-dilution on-line solid-phase extraction and liquid chromatography coupled with tandem mass spectrometry method was then developed to analyze one of the EtO-DNA adducts, N7-(2-hydroxyethyl)guanine (N7-HEG), in urine of 46 nonsmokers with excellent accuracy, sensitivity and specificity. The merits of this method include small sample volume (only 120 microL urine required), automated sample cleanup, and short total run time (12 minutes per sample). This method demonstrates its high-throughput capacity for future molecular epidemiology studies on the potential health effects resulting from the low-dose EtO exposure.

Simultaneous analysis of urinary 4,4'-methylenebis(2-chloroaniline) and N-acetyl 4,4'-methylenebis(2-chloroaniline) using solid-phase extraction and liquid chromatography/tandem mass spectrometry.

Analysis of 4,4'-methylenebis(2-cholroaniline) (MOCA) or its metabolites in urine has been considered as the appropriate method to assess MOCA exposures through inhalation and skin absorption. MOCA and its metabolite, N-acetyl 4,4'-methylenebis(2-chloroaniline) (acetyl-MOCA), are analyzed using methods either limited by sensitivity or sample preparation. Therefore, a solid-phase extraction (SPE) and liquid chromatography/tandem mass spectrometry (LC/MS/MS) method was developed to simultaneously analyze MOCA and acetyl-MOCA in urine to serve as biomarkers for MOCA exposure. Protein was precipitated by using acetonitrile, and SPE were applied to clean up samples to eliminate the matrix effect and to improve the recovery. The limit of quantitation of this method was at 1.0 ng/mL for MOCA and 0.03 ng/mL for acetyl-MOCA (signal-to-noise (S/N) ratio = 10). Urinary MOCA and acetyl-MOCA levels in MOCA-exposed workers were analyzed and quantitated to be 191.9 +/- 373.2 (mean +/- standard deviation (SD)) and 11.79 +/- 23.8 ng/mL (N = 54) with the median values 38.6 and 1.8 ng/mL, respectively. MOCA concentrations are significantly correlated with their corresponding acetyl-MOCA levels in urine (Spearman correlation coefficient r = 0.916, p < 0.001). These results show that this method has been successfully developed and provides high-throughput potential to analyze MOCA and acetyl-MOCA to serve as exposure biomarkers for future study of the potential health effects associated with MOCA exposures.

Analysis of urinary N-acetyl-S-(propionamide)-cysteine as a biomarker for the assessment of acrylamide exposure in smokers.

Acrylamide, classified by the IARC as a probable human carcinogen (Group 2A), is present in cigarette mainstream smoke and also some high-temperature-processed foods, thus smokers and consumers of certain foods are at risk of acrylamide exposure. The objectives of this study were to analyze N-acetyl-S-(propionamide)-cysteine (NASPC), an acrylamide metabolite, in the urine of smokers and nonsmokers, and to investigate the association between acrylamide exposure and urinary NASPC levels in smokers and nonsmokers in order to validate NASPC as a biomarker for the assessment of acrylamide exposure. Urine samples from 63 male military officers were collected as well as background personal information and smoking habits using questionnaires. Acrylamide exposure from tobacco smoke was represented by self-reported daily cigarette consumption and urinary cotinine levels. NASPC and cotinine were analyzed using our newly developed liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) methods. Our results reveal a statistically significant linear relationship between urinary NASPC and cotinine levels for smokers (Spearman correlation coefficient r=0.402, P=0.028), but insignificantly so for nonsmokers. These results verify our suggestion that urinary NASPC could serve as a sensitive, specific, noninvasive, and easily accessible biomarker for low-dose acrylamide exposure as also exposure to carcinogens in tobacco smoke. Routine monitoring of urinary NASPC could be used to assess human exposures to acrylamide in the living environment and the workplace.