Post-traumatic stress disorder and childhood emotional abuse are markers of subthreshold bipolarity and worse treatment outcome in major depressive disorder

Post-traumatic stress disorder (PTSD) and childhood maltreatment (CMT: Parental neglect; emotional, physical and sexual abuse) have been linked to bipolar disorder but they are also common in major depressive disorder (MDD). Our objective was to investigate their association with the bipolar spectrum and antidepressant treatment outcome in 482 outpatients with DSM-IV MDD treated in the Combining Medications to Enhance Depression Outcomes trial for 28 weeks Bipolar spectrum score included age of onset <21 years, subthreshold hypomania (a period of elated or irritable mood with at least two concurrent hypomanic symptoms, which did not fulfill DSM criteria for hypomanic/manic episode) and depressive mixed state (DMX). PTSD subjects (n = 107; 22%) had more severe depression (P < 0.0001), work and social impairment (P = 0.0031), comorbid anxiety disorders (P < 0.0001) and increased suicidality (P = 0.0003). Bipolar spectrum score was higher with PTSD comorbidity (P = 0.0063) and childhood emotional abuse (P = 0.0001). PTSD comorbidity was associated with residual suicidality (P = 0.0218) after 6 weeks of antidepressant use whereas childhood emotional abuse [odds ratio (OR), 1.01-2.22], subthreshold hypomania (OR, 1.04-4.09) and DMX (OR, 1.00-4.19) were predictors of mood switch. These results corroborate the role of PTSD and childhood emotional abuse as markers of bipolar spectrum and prognostic factors during antidepressant treatment

Persistence of suicidal ideation within acute phase treatment of major depressive disorder: Analysis of clinical predictors

Suicidal ideation (SI) is common in major depressive disorder (MDD), and it is a risk factor for suicidal behaviour. Antidepressants are effective in reducing SI, but in some subjects, SI may persist for weeks. This study aimed to disentangle the contribution of baseline clinical characteristics in SI nonremission at week 6. Research involved 198 outpatients with MDD and SI collected within the Combining Medications to Enhance Depression Outcomes trial and treated with different antidepressant combinations. Although SI decreased from baseline to week 6 (P < 0.0001), 78 patients (39%) failed to achieve SI remission. Insomnia [OR, 0.72; 95% confidence interval (CI), 0.52-0.99], reduced need for sleep (OR, 0.75; 95% CI, 0.58-0.99), self-confidence (OR, 0.52; 95% CI, 0.32-0.82), cheerfulness (OR, 0.57; 95% CI, 0.33-0.98), and comorbid panic disorder (OR, 0.93; 95% CI, 0.87-0.99) at baseline were associated with lack of SI remission after controlling for baseline depression and SI scores. The combination of baseline SI and insomnia was moderately effective in predicting the lack of SI remission, with a specificity of 80% (95% CI, 72-87%) and an NPV of 68% (95% CI, 63-72%). In individuals with MDD and SI, the presence of insomnia and bipolar features should prompt a search for more effective treatment solutions in order to favour SI remission and prevent suicidal behaviour

Development, validation and application of an HPLC-MS/MS method to quantify urinary mercapturic acids

Introduction Mercapturic acids are metabolic end products of some occupational and environmental toxicants such as volatile organic compounds. They are metabolites formed by the conjugation of an electrophilic compound with glutathione. These electrophilic metabolic intermediates are believed to be the active species able to react with DNA and responsible for the genotoxicity associated with parent compounds [1]. Mercapturates can be found in urine and, therefore, they can be considered useful non-invasive biomarkers of exposure. Although several analytical methods were reported for the analysis of single or small groups of mercapturates [2], only two papers describes the analysis of several mercapturates [3,4]. The aim of this work was to set up a LC-MS/MS method able to determine mercapturic acids derived from different toxicants. Experimental For the preparation of standard solution, the majority of standard compounds were purchased from Toronto Research Chemicals (Ontario, Canada), along with relative isotopically labelled standards. The complete list of analytes is reported in Table 1. The simple sample preparation developed includes dilution with formic acids (0.2 M), addition of an internal standard mixture of 16 deuterated analogs and filtration with 0.45 \u3bcm regenerated cellulose membrane filter (Agilent Technologies, Santa Clara, California). Analysis were carried out using a hybrid triple quadrupole/linear ion trap mass spectrometer (QTRAP 5500, AB Sciex, Monza, Italy) interfaced with an ultrahigh pressure liquid chromatograph (UHPLC, Agilent 1220, Cernusco sul Naviglio, Italy) equipped with a Betasil C18 column (150 x2.1 mm, 5 \u3bcm; Thermo Fisher Scientific, Rodano, Italy) and a pre-column BETASIL C18 (10 x 2,1 mm, 5\u3bc; Thermo Fisher Scientific, Rodano, Italy). Chromatographic separation was performed using a linear gradient with an aqueous mobile phase composed by an aqueous solution of ammonium formiate 5 mM and 0.1% formic acid and an organic mobile phase composed by acetonitrile. A complete validation was carried out: linearity, sensitivity, accuracy, precision, selectivity, matrix effect, recovery and process efficiency were evaluated according to both FDA guidelines and the considerations reported in the review written by Gonz\ue1lez and co-workers [5,6]. The method was then applied to the analysis of urine samples from adult subjects with different smoking habits: non-smokers, electronic cigarette smokers, and traditional tobacco smokers. Results Results from linearity assays showed that correlation coefficients (R2) were close to 1 for most of compounds, demonstrating optimal linear responses for the considered concentrations ranges, although a polynomial regression was necessary for AAMA since it showed a saturation at high concentrations. Limits of quantitation (LOQ) values were between 0.15 and 1 \u3bcg/L, except for HEMA and AAMA (1.93 and 1.30 \u3bcg/L respectively). Precision, evaluated as relative standard deviations (RDS), was below 15% for most analytes in both intra-day and inter-day tests. Accuracy was between 85 and 110 % of expected values, with few exceptions exceeding 120% at the lowest concentrations. Selectivity was verified by injection of a blank sample (synthetic urine) showing no chromatographic peak having an area at 20% of LOQ at the relative retention time and mass transition of compounds of interest. The same condition was verified analysing a blank sample immediately after the injection of the standard mixture at the highest concentration of the calibration curve, indicating the absence of carry-over. Results from the matrix effect, recovery and process efficiency tests were suitable in most of the cases, with some exceptions that were partially corrected using the internal standards. Results from urine samples of individuals with different smoking habit showed significant differences between smokers and non-smokers: 11 different mercapturic acids were significantly higher (P-value 640.005) in traditional tobacco smokers than in non-smokers (an example is illustrated in Figure 1). Conclusion In this work, we developed a method useful to quantify mercapturic acids in urine samples. The method was subjected to a complete validation and showed to be suitable for most of the considered analytes. Despite some critical issues with some analytes (in particular HEMA), it demonstrated to be an useful tool for fast determination of mercapturates. The first application carried out using human urine samples suggests that mercapturic acids are suitable biomarkers for toxicants in tobacco smoke. References 1. B.M. De Rooij, J.N.M. Commandeur, N.P.E; Biomarkers, 3 (1998), pp 239-303. 2. P.I. Mathias, C. B'hymer; Biomarkers, 21 (2016), pp 293-315. 3. K.U. Alwis, B.C. Blount, A.S. Britt, D. Patel, D.L. Ashley; Analytica Chimica Acta, 750 (2012), pp 152-160. 4. N. Pluym, G. Gilch, G. Scherer, M. Scherer; Analytical and Bioanalytical Chemistry, 407 (2015), pp 5463-5476. 5. FDA. Guidance for Industry - Bioanalytical Method Validation. (2013) Available at: https://www.fda.gov/downloads/Drugs/Guidances/ucm368107.pdf 6. O. Gonz\ue1lez, M.E. Blanco, G. Iriarte, L. Bartolom\ue9, M.I. Maguregui, R.M. Alonso; Journal of Chromatography A, 1353 (2014), pp10-27

Untargeted metabolomics in urine to investigate smoking exposure

Background: Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Methods: Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. Results: One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, of which we were able to putatively annotate about half. The identification of the mercapturic acids of acrolein, 1,3-butadiene, and crotonaldeide, chemicals known to be present in tobacco smoke, supports the validity of the proposed approach. With a lower level of confidence, we annotated the glucuronide conjugated of 3-hydroxycotinine and the sulfate conjugate of methoxyphenol; finally, with the lowest degree of confidence, several other sulfate conjugates of small molecules were annotated. Short discussion/conclusions: The proposed approach seems to be useful for the investigation of exposure to toxicants in humans

Investigation of urine metabolites related to tobacco smoke chemicals using an untargeted metabolomic approach

Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, for which we were able to putatively annotate about half. Among these, the identification of the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach. Furthermore, several metabolites, mostly as sulfate conjugates, derived from chemicals known to be present in tobacco smoke, were annotated, among which the metabolite of methoxyphenol, acrolein, 1,3-butadiene, and crotonaldeide

A workflow for data integration, analysis, and metabolite annotation for untargeted metabolomics

Metabolomics is the youngest of the \u201comics\u201d disciplines and it is regarded as a promising approach to understand the metabolic changes that can occur in particular conditions and to identify new biomarkers. We present here a workflow for data integration, analysis, and metabolite annotation to be applied to untargeted metabolomic experiments. Data acquired with LC-MS/MS, operating in data dependent mode, are processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The data-table obtained is elaborated and submitted to statistical analysis using the on-line software MetaboAnalyst. Multivariate analysis, in particular principal component and partial least squares discriminant analysis are performed for data visualization. Univariate analysis, in particular T-test for pairwise and ANOVA for multi-groups comparison, are performed to detect significant features among groups. The software BEAMS, developed by the University of Birmingham, is then implemented for grouping adducts and isotopes, and to perform a first annotation. Metabolite annotation is finally completed by comparing the fragmentation pattern obtained from each parent ion corresponding to a significant feature with data stored in on-line databases as Metlin, and with the help of the software MS-FINDER, which performs in-silico fragmentation. We applied this workflow to an untargeted metabolomic experiment performed on 67 urine samples obtained from adult subjects with different smoking habits: non-smokers, electronic cigarette smokers, and traditional tobacco smokers. 117 features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites. We were able to putatively annotate compound classes of most of the significant metabolites (level 3 according to the \u201cProposed minimum reporting standards\u201d; Sumner et al., 2007) and to putatively annotate some of them (level 2). Among them, the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach

Abitudine al fumo di sigaretta e profilo di escrezione di acidi mercapturici urinari : confronto tra tabacco e sigaretta elettronica

Introduzione. Nel fumo di sigaretta sono presenti moltissime molecole, centinaia delle quali riconosciute cancerogene per l\u2019uomo. Il contenuto del fumo di sigaretta elettronica \ue8 meno noto e sulla sua pericolosit\ue0 per la salute umana \ue8 in corso un acceso dibattito. Molte sostanze cancerogene contenute nel fumo di tabacco, dopo assorbimento nel nostro organismo, subiscono biotrasfomazione a dare composti elettrofili che sono ritenuti responsabili della loro genotossicit\ue0/cancerogenicit\ue0. In molti casi questi intermedi reattivi vengono eliminati nelle urine come acidi mercapturici. Scopo. Scopo di questo lavoro \ue8 stato verificare se l\u2019abitudine al fumo di tabacco e la sigaretta elettronica rappresentano sorgenti di esposizione a composti elettrofili, eliminati nell\u2019urine come acidi mercapturici (MA). Metodo. Sono stati raccolti campioni di urina di soggetti adulti con diversa abitudine al fumo di sigaretta: 22 soggetti fumatori (FT) di sigaretta tradizionale, 7 soggetti fumatori di sigaretta elettronica (FE) e 38 soggetti non fumatori (NF). Nei campioni di urina \ue8 stata ricercata la presenza di 18 acidi mercapturici derivati dalla biotrasformazione di acroleina, acrilamide, acrilonitrile, benzene, 1,3-butadiene, crotonaldeide, N,N-dimetilformammide, etilene, ossido di etilene, cloruro di vinile, ossido di propilene, stirene, toluene nonch\ue9 agenti metilanti ed etilanti. Le determinazioni sono state eseguite con un metodo basato sulla cromatografia liquida accoppiata a spettrometria di massa. Risultati. Dal confronto dei livelli di MA nei soggetti con diverse abitudini al fumo sono state evidenziate differenze significative tra fumatori e non fumatori: 11 diversi acidi mercapturici erano significativamente pi\uf9 alti (valore p 640.005) nei fumatori tradizionali rispetto ai non fumatori. I livelli mediani di MA sono risultati variare tra

ETS exposure and PAH body burden in nonsmoking Italian adults

Active smoking is associated with increased body burden of polycyclic aromatic hydrocarbons (PAHs); the aim of this study was to assess whether environmental tobacco smoking (ETS) increases the internal dose of PAHs. In 344 nonsmoking Italian adults, out of 497 individuals selected as representative of the population of the town of Modena, ETS exposure was evaluated by a self-administered questionnaire and by the measurement of urinary cotinine (COT-U). PAH exposure was assessed by the measurement of urinary 1-hydroxypyrene (1-OHPYR) and of ten urinary PAHs. In all subjects, median (5th-95th percentile) COT-U was 0.47 (<0.1-3.91) mu g/L. While 58 subjects reported to be ETS exposed (ETSQUEST), 38 individuals were identified as ETS exposed on the basis of a COT-U value of 1.78 (90% confidence interval 1.75-1.80) mu g/L, previously derived as an upper reference value in not ETS exposed Italian adults (ETSCOT). Median COT-U levels were 1.38 (<0.1-9.06) and 3.63 (1.80-17.39) mu g/L in ETSQUEST and in ETSCOT subjects, respectively. Significant correlations between COT-U and 1-OHPYR, and urinary anthracene, fluoranthene, pyrene, and chrysene were found among all subjects. Significantly higher levels of 1-OHPYR, and urinary fluorene, anthracene, and pyrene were found in ETSCOT individuals. The results of multiple linear regression analyses, taking into consideration diet and other sources of PAHs exposures such as the residence area/characteristics and traffic, confirmed that 1-OHPYR and urinary fluorene were affected by ETS exposure, even if ETS played a minor role

Un approccio metabolomico non mirato per indagare l&apos;esposizione a sostanze tossiche nel fumo di sigaretta

Introduzione: Nel fumo di sigaretta siano state identificate migliaia di diverse sostanze chimiche pericolose; ci\uf2 nonostante la caratterizzazione dei metaboliti urinari di queste sostanze a seguito di esposizione nell'uomo \ue8 stata effettuata sono parzialmente. Obiettivo: Lo studio si propone di applicare un approccio metabolomico non mirato all'analisi di campioni di urina di soggetti con diversa abitudine al fumo, allo scopo di identificare i metaboliti derivanti da sostanze tossiche associati. Metodi: Sono stati raccolti campioni estemporanei di urina da 67 soggetti suddivisi in tre gruppi sulla base della loro abitudine al fumo: 38 soggetti erano non fumatori, 7 erano fumatori di sigaretta elettronica e 22 erano fumatori di tabacco. I campioni sono stati analizzati utilizzando la cromatografia liquida accoppiata ad uno spettrometro di massa con tempo di volo, raccogliendo i segnali degli ioni negativi. I dati sono stati processati utilizzando i pacchetti R IPA e MXCMS per correggere i tempi di ritenzione ed effettuare l'allineamento tra i cromatogrammi. Il test ANOVA \ue8 stato utilizzato per identificare gli elementi caratteristici che distinguono tra loro i gruppi. Il software BEAMS, sviluppato dall'universit\ue0 di Birmingham, \ue8 stato applicato per raggruppare gli addotti e gli isotopi riferiti ad una stessa sostanza ed effettuare una prima annotazione dei picchi. L'annotazione \ue8 stata completata confrontando gli spettri di frammentazione ottenuti da standard puri e con il database Metlin, usando il software MS-FINDER Risultati: Nei cromatogrammi ottenuti sono stati identificati complessivamente 3613 segnali, di cui 117 sono risultati diversi nei gruppi studiati. Questi segnali sono stati attribuiti a circa 80 diversi metaboliti, dei quali siamo riusciti ad annotarne putativamente circa la met\ue0. L\u2019identificazione, con un grado di confidenza pari a 1, degli acidi mercapturici dell\u2019acroleina, del 1,3-butadiene, e della crotonaldeide, sostanze risaputamene presenti nel fumo di tabacco, supportano la validit\ue0 dell\u2019approccio adottato (il grado di confidenza 1 si attribuisce alle molecole identificate con certezza per confronto con lo standard puro). Con un grado di confidenza minore (pari a 2) sono state identificati: il coniugato glucuronide della 3-idrossicotinina e il coniugato solfato del metossifenolo. Infine, con un grado di confidenza 3, sono state identificate numerose altre piccole molecole, escrete come coniugati solfati. Conclusione: L\u2019approccio proposto sembra utile per indagare l\u2019esposizione a miscele di sostanze tossiche nell\u2019uomo. Dato che l\u2019esposizione a miscele di sostanze chimiche, piuttosto che a singoli composti, \ue8 una caratteristica peculiare di molti ambienti di lavoro, si reputa che questo approccio apra interessanti prospettive per la medicina del lavoro