Abstract Liquid chromatography (LC) combined with mass spectrometry (MS) is a powerful tool for qualitative and quantitative analytics of organic molecules from various matrices, and the use of this hyphenated technique is very common in bioanalytical laboratories. In this study, LC/MS methods and the required sample preparation applications were developed for plant flavonoid and drug metabolism studies. The main focus was in developing methods to be used during cytochrome P450 (CYP) -specific drug interaction studies. Traditional high performance liquid chromatography (HPLC) and new, more efficient and faster ultra-performance liquid chromatography (UPLC) were utilized together with time-of-flight (TOF) and triple quadrupole (QqQ) mass spectrometry. In the flavonoid study, collision-induced radical cleavage of flavonoid glycosides was tested and observed to be a suitable tool for the structure elucidation of the 15 flavonol glycosides extracted from the medicinal plant Rhodiola rosea. Ten of these glycosides were previously unreported in the plant. Several unreported in vivo bupropion metabolites were identified from human urine when developing the method for the new and more extensive in vitro and in vivo N-in-one interaction cocktail assays. The qualified analysis methods developed here enable faster analysis for the N-in-one cocktail assays, in turn enabling a more efficient screening of drugs that affect CYP-enzyme activities. In the case of the human in vitro cocktail assay, fourteen compounds were analyzed using a single LC/MS/MS run. The method has proven to be very reliable and has been used in several interaction studies utilizing different sample matrices. The in vivo cocktail assay that was developed enables totally non-invasive sample collection from the patients, the urine sample being sufficient for the UPLC/MS/MS analysis of all target compounds. The last part of the study consisted of developing a specific and very sensitive UPLC/MS/MS method for the analysis of one of the in vivo cocktail analytes, the antidiabetic drug repaglinide, from human placenta perfusates. / Tiivistelmä Nestekromatografia (LC) yhdistettynä massaspektrometriaan (MS) on tehokas työväline kvalitatiivisessa ja kvantitatiivisessa analytiikassa, ja tätä tekniikkaa käytetään erityisesti bioalan laboratorioissa. Tässä väitöskirjatyössä kehitettiin ja sovellettiin LC/MS- ja näytteenkäsittelymenetelmiä kasvien flavonoidimetabolian ja lääkeaineiden metaboliatuotteiden tutkimukseen keskittyen erityisesti sytokromi P450 (CYP) -entsyymispesifisten lääkeaineiden interaktiotutkimuksiin tarvittaviin menetelmiin. Työssä hyödynnettiin perinteistä korkean erotuskyvyn nestekromatografiaa (HPLC) ja uutta, suorituskyvyltään vielä tehokkaampaa ja nopeampaa nestekromatografiaa (UPLC) yhdessä lentoaika- (TOF) ja kolmoiskvadrupolimassaspektrometrian (QqQ) kanssa. Tutkimustyön flavonoidimetaboliaan keskittyneessä osuudessa havaittiin törmäyksen aiheuttaman (CID) radikaalipilkkoutumisen soveltuvan lääkinnällisenä kasvina käytetystä ruusujuuresta (Rhodiola rosea) uutettujen viidentoista flavonoliglykosidin rakennemääritykseen. Kymmentä näistä löydetyistä glykosideista ei oltu aiemmin raportoitu ruusujuuresta. Tutkimustyön keskeisimpänä tavoitteena kehitettiin kvalifioidut LC/MS -analyysimenetelmät käytettäväksi aikaisempaa kattavampien in vitro ja in vivo -olosuhteiden N-in-one -tyyppisten CYP-entsyymi-interaktiotutkimusten analyyttisenä työkaluna. Näitä analyysimenetelmiä kehitettäessä löydettiin ja tunnistettiin ihmisen virtsasta aiemmin raportoimattomia metaboliitteja CYP2B6 -entsyymin malliaineena käytetyn bupropionin annostelun jälkeen. Kyseisten kehitettyjen analyysimenetelmien avulla CYP-entsyymien toimintaan vaikuttavien lääkeaineiden tutkiminen on aiempaa nopeampaa ja antaa yhdellä kertaa samasta tutkimuksesta entistä laaja-alaisempaa tietoa. In vitro -tutkimusta varten kehitetty LC/MS/MS -analyysimenetelmä on osoittautunut erittäin käyttökelpoiseksi lukuisissa interaktiotutkimuksissa, ja in vivo -tutkimusta varten kehitetty UPLC/MS/MS -analyysimenetelmä mahdollistaa täysin ei-invasiivisen näytteenoton potilaista. Tutkimustyön viimeisessä vaiheessa kehitettiin erittäin herkkä ja spesifinen UPLC/MS/MS -analyysimenetelmä CYP2C8-entsyymin toiminnan malliaineena käytetyn repaglinidin analysoimiseksi koejärjestelystä, jossa tutkitaan yhdisteiden kulkeutumista raskausaikana äidin ja sikiön verenkierron välillä istukan kautta.

Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Cocaine is a stimulant that features a strong ability to cause dependence. Often adulterants are added to this drug in order to mimic its action or minimize its adverse effects. When there are other pharmacologically active components in the drug composition, severe problems can occur to users’ health, such as intoxication symptoms. Thus, the aim of this study was to develop a method for the determination of the main adulterants of cocaine (caffeine, levamisole, lidocaine, phenacetin, diltiazem, and hydroxyzine) in human urine. The high-performance liquid chromatography with a photodiode array detector and the dispersive liquid-liquid microextraction based on solidification of floating organic drop were used as analysis technique and as sample preparation technique, respectively. The reversed-phase chromatographic separation was obtained with a C18 column (250 x 4.6 mm; 5 μm; 80 Å) in gradient elution mode using acetonitrile-trifluoroacetic acid 0.026% (v/v) at 1 mL min-1 as mobile phase, at 25°C, and detection at 235 nm. The analysis time was 25 min. Under optimum conditions, human urine samples were alkalized with 0.5 mol.L-1 sodium phosphate buffer (pH 10) and added sodium chloride (20% m/v). Acetonitrile (150 μL) and 1-dodecanol (30 μL) were used as dispersive and extraction solvent, respectively. The method presented linear range of 312.5 – 3125 ng.mL−1 for caffeine and levamisole and 187.5 – 1875 ng.mL−1 for lidocaine, phenacetin, diltiazem, and hydroxyzine, with limit of quantification of 187.5 ng.mL-1 to lidocaine, phenacetin, diltiazem, and hydroxyzine and 312.5 ng.mL-1 for caffeine and levamisole. Recovery mean values were between 6.0 and 42.6%. The method showed good precision and accuracy, with within- and between-run relative standard deviation and relative error less than 15%. The samples were stable after freeze-thaw cycle and short-term room temperature stability tests. Additionally, this method was applied in samples of urine of five cocaine users and at least one adulterant was identified in all samples. It is expected that this method will contribute to the precision in the diagnosis of cocaine adulterants’ intoxication and to the proper planning of therapeutic measures. / A cocaína é uma droga estimulante que apresenta capacidade de causar dependência. Frequentemente são adicionados a esta droga adulterantes com o intuito de mimetizar sua ação ou minimizar seus efeitos adversos. Quando há nessa droga outros componentes farmacologicamente ativos, agravos à saúde dos usuários podem ocorrer, como quadros de intoxicação. Assim, o objetivo deste trabalho foi desenvolver um método de determinação dos principais adulterantes da cocaína (cafeína, levamisol, lidocaína, fenacetina, diltiazem e hidroxizina) em urina humana. A cromatografia líquida de alta eficiência com detector de arranjo de fotodiodos foi utilizada como técnica de análise e a microextração líquido-líquido dispersiva com solidificação da gota orgânica flutuante, como técnica de preparo das amostras. A separação cromatográfica dos analitos em fase reversa foi obtida em uma coluna C18 (250 x 4,6 mm; 5 μm; 80 Å) em modo gradiente e usando acetonitrila-ácido trifluoroacético 0,026% (v/v) a 1 mL.min-1 como fase móvel (25°C e detecção a 235 nm). O tempo de análise foi de 25 min. Para o preparo da amostra, a urina foi alcalinizada com tampão fosfato de sódio 0,5 mol.L-1 (pH 10) e adicionada de cloreto de sódio (20% m/v). Acetonitrila (150 μL) e 1-dodecanol (30 μL) foram utilizados como solvente dispersor e extrator, respectivamente. O método apresentou intervalos lineares de concentração de 312,5 – 3125 ng.mL−1 para cafeína e levamisol e de 187,5 – 1875 ng.mL−1 para lidocaína, fenacetina, diltiazem e hidroxizina, com limite de quantificação de 187,5 ng.mL-1 para lidocaína, fenacetina, diltiazem e hidroxizina e 312,5 ng.mL-1 para cafeína e levamisol. Os valores médios de recuperação variaram de 6,0 a 42,6%. O método mostrou boa precisão e exatidão intra e intercorrida com coeficientes de variação e erros relativos menores que 15%. As amostras apresentaram-se estáveis após ciclos de congelamento-descongelamento e após serem mantidas por 24h em temperatura ambiente. Ainda, o método foi aplicado em cinco amostras de urina de usuários de cocaína e pelo menos um adulterante foi identificado em todas as amostras. Espera-se que este método possa contribuir para a precisão no diagnóstico das intoxicações por adulterantes da cocaína e para o adequado planejamento das medidas terapêuticas.

An environmental mixture is composed of multiple environmental exposures. Quantifying this joint effect on health outcomes mirrors what occurs in nature, offering significant benefits to environmental epidemiological research. However, analyzing the impact of an environmental mixture poses numerous statistical and inferential challenges. Motivated by the Strong Heart Study (SHS), a prospective cohort study of cardiovascular disease (CVD) outcomes among three American Indian communities where urine samples were collected at three visits and analyzed for concentrations of various metal exposures, this dissertation aims to improve our ability to analyze the effect of multiple, continuous, and correlated exposures with complex relationships on a health outcome using observational study data, such as the metal mixture exposure in the SHS. The contributions of this dissertation address two challenges inherent in environmental mixture analyses: modeling methods and the transportability of estimated effects. In the first project presented in this dissertation, our goal was to evaluate the performance of available modeling methods for estimating the impact of an environmental mixture on survival outcomes. While survival time outcomes (also known as time-to-event outcomes) are very common in epidemiological studies, little attention has been given to examining the performance of existing modeling methods when estimating the effect of an environmental mixture on a survival outcome. In this chapter, we identified applicable and readily available modeling methods, assessed their performance through simulations replicating various real-world scenarios, and applied the selected methods to estimate the effect of a metal mixture on CVD incidence in the SHS. We examined proportional hazards (PH) based models as well as more flexible, machine learning-style models. Our simulations found that, when the PH assumption held, the effect estimates via flexible models had higher bias and variance compared to PH methods. However, when the PH assumption was violated, this discrepancy between the methods decreased and the more flexible methods achieved higher coverage. These simulation findings underscore the importance of demonstrating the robustness of findings across various modeling approaches in environmental epidemiology. In the SHS analysis, all methods found a significant, harmful effect of the metal mixture on incident CVD. However, the more flexible approaches found larger point estimates with wider confidence bands. The second and third projects of this dissertation focus on constructing a framework for transporting an environmental mixture effect across populations. Numerous methods exist for analyzing environmental mixture effects within a population where sample data is available for. However, being able to adjust these effects based on the exposure/covariate distribution of a different target population would enable more precise estimation of the mixture effect in that population. This, in turn, allows for more accurate estimation of effects for populations distinct from those sampled. This broadens available data sources and provides significant advantages to researchers and policymakers interested in specific populations. The second project leverages causal inference concepts to formally extend the transportability literature to the environmental mixtures context. We defined a relevant intervention with favorable properties concerning the exposure concentration positivity assumption and explicitly outline the assumptions needed to transport its effect across two observational studies. To assess whether the target population is well represented in the study population sample, which is required for the positivity of population membership assumption, a matching algorithm is proposed. Subject's environmental mixture exposure profiles are incorporated into subject matching on exposures and covariates between the two populations. Simulation results demonstrate that the matching algorithm effectively detects non-overlap across populations, with well-overlapped populations yielding minimally biased transported effect estimates, while those with insufficient overlap exhibit greater bias. Applying this framework, we estimated the effects of a metal mixture on coronary artery calcification (CAC) in the SHS cohort by transporting the effects observed in the Multi-Ethnic Study of Atherosclerosis (MESA). Although CAC was not directly measured in the SHS, its importance as a subclinical indicator of advanced atherosclerosis and its link to elevated cardiovascular risk underscore the significance of exploring its relationship with metal exposures in the SHS. Despite larger effects observed in the MESA population, significant effects persisted within the SHS, providing insights for innovative strategies in preventing and treating atherosclerosis progression among American Indian populations. In the third project, we turned our focus to violations of internal and external validity exchangeability assumptions. We proposed the use of a negative control exposure analysis modeled with Bayesian Kernel Machine Regression with hierarchical variable selection to identify unmeasured confounding in the context of multiple, continuous, and correlated exposures when exposures are measured at various time points. Additionally, we developed a novel method for detecting violations of transportability assumptions by assessing the transportability of an effect within a study population. If the internal validity assumptions are plausible, then the inability to transport an effect within a study population suggests the presence of unmeasured effect modification in the study sample. Through simulations, we demonstrated the efficacy of these methods in detecting unmeasured confounding and effect modification. We applied these methods to assess the robustness of the estimated effect of a metal mixture on fasting blood glucose levels in the SHS to violations of transportability assumptions and found evidence of both unmeasured confounding and effect modification. However, the internal effect estimate remained significant and robust to unmeasured confounding.