Pregnancy and newborns disorders followed by urine metabolomics

Chapter 1 introduces the scope of the work by identifying the clinically relevant prenatal disorders and presently available diagnostic methods. The methodology followed in this work is presented, along with a brief account of the principles of the analytical and statistical tools employed. A thorough description of the state of the art of metabolomics in prenatal research concludes the chapter, highlighting the merit of this novel strategy to identify robust disease biomarkers. The scarce use of maternal and newborn urine in previous reports enlightens the relevance of this work. Chapter 2 presents a description of all the experimental details involved in the work performed, comprising sampling, sample collection and preparation issues, data acquisition protocols and data analysis procedures. The proton Nuclear Magnetic Resonance (NMR) characterization of maternal urine composition in healthy pregnancies is presented in Chapter 3. The urinary metabolic profile characteristic of each pregnancy trimester was defined and a 21-metabolite signature found descriptive of the metabolic adaptations occurring throughout pregnancy. 8 metabolites were found, for the first time to our knowledge, to vary in connection to pregnancy, while known metabolic effects were confirmed. This chapter includes a study of the effects of non-fasting (used in this work) as a possible confounder. Chapter 4 describes the metabolomic study of 2nd trimester maternal urine for the diagnosis of fetal disorders and prediction of later-developing complications. This was achieved by applying a novel variable selection method developed in the context of this work. It was found that fetal malformations (FM) (and, specifically those of the central nervous system, CNS) and chromosomal disorders (CD) (and, specifically, trisomy 21, T21) are accompanied by changes in energy, amino acids, lipids and nucleotides metabolic pathways, with CD causing a further deregulation in sugars metabolism, urea cycle and/or creatinine biosynthesis. Multivariate analysis models´ validation revealed classification rates (CR) of 84% for FM (87%, CNS) and 85% for CD (94%, T21). For later-diagnosed preterm delivery (PTD), preeclampsia (PE) and intrauterine growth restriction (IUGR), it is found that urinary NMR profiles have early predictive value, with CRs ranging from 84% for PTD (11-20 gestational weeks, g.w., prior to diagnosis), 94% for PE (18-24 g.w. pre-diagnosis) and 94% for IUGR (2-22 g.w. pre-diagnosis). This chapter includes results obtained for an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) study of pre-PTD samples and correlation with NMR data. One possible marker was detected, although its identification was not possible. Chapter 5 relates to the NMR metabolomic study of gestational diabetes mellitus (GDM), establishing a potentially predictive urinary metabolic profile for GDM, 2-21 g.w. prior to diagnosis (CR 83%). Furthermore, the NMR spectrum was shown to carry information on individual phenotypes, able to predict future insulin treatment requirement (CR 94%). Chapter 6 describes results that demonstrate the impact of delivery mode (CR 88%) and gender (CR 76%) on newborn urinary profile. It was also found that newborn prematurity, respiratory depression, large for gestational age growth and malformations induce relevant metabolic perturbations (CR 82-92%), as well as maternal conditions, namely GDM (CR 82%) and maternal psychiatric disorders (CR 91%). Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the value of maternal or newborn urine metabolomics for pregnancy monitoring and disease prediction, towards the development of new early and non-invasive diagnostic methods.

Metabonomics of human amniotic fluid for prenatal diagnostics

O trabalho apresentado nesta tese teve como principais objectivos contribuir para o conhecimento da composição do líquido amniótico humano (LA), colhido no 2º trimestre de gravidez, assim como investigar possíveis alterações na sua composição devido à ocorrência de patologias pré-natais, recorrendo à metabonómica e procurando, assim, definir novos biomarcadores de doenças da grávida e do feto. Após uma introdução descrevendo o estado da arte relacionado com este trabalho (Capítulo 1) e os princípios das metodologias analíticas usadas (Capítulo 2), seguida de uma descrição dos aspectos experimentais associados a esta tese (Capítulo 3), apresentam-se os resultados da caracterização da composição química do LA (gravidez saudável) por espectroscopia de ressonância magnética nuclear (RMN), assim como da monitorização da sua estabilidade durante o armazenamento e após ciclos de congelamento-descongelamento (Capítulo 4). Amostras de LA armazenadas a -20°C registaram alterações significativas, tornando-se estas menos pronunciadas (mas ainda mensuráveis) a -70°C, temperatura recomendada para o armazenamento de LA. Foram também observadas alterações de composição após 1-2 ciclos de congelamento-descongelamento (a ter em conta aquando da reutilização de amostras), assim como à temperatura ambiente (indicando um período máximo de 4h para a manipulação e análise de LA). A aquisição de espectros de RMN de 1H de alta resolução e RMN acoplado (LC-NMR/MS) permitiu a detecção de 75 compostos no LA do 2º trimestre, 6 dos quais detectados pela primeira vez no LA. Experiências de difusão (DOSY) permitiram ainda a caracterização das velocidades de difusão e massas moleculares médias das proteínas mais abundantes. O Capítulo 5 descreve o estudo dos efeitos de malformações fetais (FM) e de cromossomopatias (CD) na composição do LA do 2º trimestre de gravidez. A extensão deste trabalho ao estudo dos efeitos de patologias no LA que ocorrem no 3º trimestre de gravidez é descrita no Capítulo 6, nomeadamente no que se refere ao parto pré-termo (PTD), pré-eclampsia (PE), restrição do crescimento intra-uterino (IUGR), ruptura prematura de membranas (PROM) e diabetes mellitus gestacional (GDM). Como complemento a estes estudos, realizou-se uma análise preliminar da urina materna do 2º trimestre para o estudo de FM e GDM, descrita no Capítulo 7. Para interpretação dos dados analíticos, obtidos por espectroscopia RMN de 1H, cromatografia líquida de ultra eficiência acoplada a espectrometria de massa (UPLC-MS) e espectroscopia do infravermelho médio (MIR), recorreu-se à análise discriminante pelos métodos dos mínimos quadrados parciais e o método dos mínimos quadrados parciais ortogonal (PLS-DA e OPLS-DA) e à correlação espectral. Após análise por validação cruzada de Monte-Carlo (MCCV), os modelos PLS-DA de LA permitiram distinguir as FM dos controlos (sensibilidades 69-85%, especificidades 80-95%, taxas de classificação 80-90%), revelando variações metabólicas ao nível do metabolismo energético, dos metabolismos dos aminoácidos e glícidos assim como possíveis alterações ao nível do funcionamento renal. Observou-se também um grande impacto das FM no perfil metabólico da urina materna (medido por UPLC-MS), tendo no entanto sido registados modelos PLS-DA com menor sensibilidade (40-60%), provavelmente devido ao baixo número de amostras e maior variabilidade da composição da urina (relativamente ao LA). Foram sugeridos possíveis marcadores relacionados com a ocorrência de FM, incluindo lactato, glucose, leucina, valina, glutamina, glutamato, glicoproteínas e conjugados de ácido glucurónico e/ou sulfato e compostos endógenos e/ou exógenos (<1 M) (os últimos visíveis apenas na urina). No LA foram também observadas variações metabólicas devido à ocorrência de vários tipos de cromossomopatias (CD), mas de menor magnitude. Os perfis metabólicos de LA associado a pré- PTD produziram modelos que, apesar do baixo poder de previsão, sugeriram alterações precoces no funcionamento da unidade fetoplacentária, hiperglicémia e stress oxidativo. Os modelos obtidos para os grupos pré- IUGR pré- PE, pré- PROM e pré-diagnóstico GDM (LA e urina materna) registaram baixo poder de previsão, indicando o pouco impacto destas condições na composição do LA e/ou urina do 2º trimestre. Os resultados obtidos demonstram as potencialidades da análise dos perfis metabólicos do LA (e, embora com base em menos estudos, da urina materna) do 2º trimestre para o desenvolvimento de novos e complementares métodos de diagnóstico, nomeadamente para FM e PTD.

Salivary proteomics and peptidomics of type 1 diabetes Mellitus

A Diabetes Mellitus (DM) compreende um conjunto de desordens metabólicas comuns caracterizadas por hiperglicemia, que afeta diferentes órgãos do organismo. Ao longo do tempo, ocorrem danos microvasculares no glomérulo renal, retina e nervos periféricos, bem como doença macrovascular nas artérias. A composição da saliva também é afetada pela DM, com consequências na homeostasia oral. No entanto, o proteoma e o peptidoma salivar têm sido pouco explorados na DM tipo 1 e nas suas complicações crónicas. Tendo em conta o crescente interesse na saliva como fluido diagnóstico, o objetivo principal deste trabalho foi avaliar os eventos proteolíticos subjacentes à DM tipo 1 e às suas complicações microvasculares, bem como, caracterizar as alterações induzidas pela DM tipo 1 no proteoma e peptidoma salivar. A DM tipo 1 e particularmente as complicações microvasculares associadas modulam o perfil proteolítico dos fluidos biológicos, com diferenças significativas de atividade observadas na urina e saliva, atribuídas principalmente ao complexo Metaloproteinase da Matriz (MMP)-9/lipocalina associada à gelatinase de neutrófilos, aminopeptidase N, azurocidina e calicreína 1. O aumento da atividade proteolítica observado na saliva total dos diabéticos resultou no aumento da percentagem de péptidos, principalmente de um número acrescido de fragmentos de colagénio do tipo I, refletindo possivelmente um estado inflamatório crónico dos tecidos orais e periodontais. O peptidoma também corrobora uma maior suscetibilidade das proteínas salivares, especificamente, das proteínas ricas em prolina básicas (bPRP) 1, bPRP2 e proteínas ricas em prolina ácidas (aPRP) à proteólise, evidenciando a geração de fragmentos de proteínas associadas à ligação a bactérias. A análise do proteoma salivar baseada em iTRAQ mostrou uma sobre-expressão de L-plastina, fator do adenocarcinoma do pâncreas e das proteínas S100-A8 e S100-A9, enfatizando a importância do sistema imune inato na patogénese da DM tipo 1 e das complicações microvasculares associadas. A análise integrada de todas as proteínas expressas diferencialmente entre os pacientes diabéticos com ou sem complicações microvasculares e indivíduos saudáveis foi realizada com o STRING, onde se observam três conjuntos funcionalmente ligados, um compreende a interação entre o colagénio tipo I, colagénio tipo II e MMP-9, um segundo conjunto envolve a MMP-2 e o colagénio de tipo I e um terceiro conjunto composto por proteínas salivares e inflamatórias. Estes conjuntos estão associados com as vias Kegg de interação recetor-matriz extracelular, de adesão focal e migração transendotelial dos leucócitos. Por outro lado, a análise do proteoma e peptidoma salivar destacou potenciais biomarcadores para o diagnóstico e prognóstico da DM tipo 1 e das suas complicações.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

Concentration of tumor biomarkers using aqueous biphasic systems

According to the World Health Organization, around 8.2 million people die each year with cancer. Most patients do not perform routine diagnoses and the symptoms, in most situations, occur when the patient is already at an advanced stage of the disease, consequently resulting in a high cancer mortality. Currently, prostate cancer is the second leading cause of death among males worldwide. In Portugal, this is the most diagnosed type of cancer and the third that causes more deaths. Taking into account that there is no cure for advanced stages of prostate cancer, the main strategy comprises an early diagnosis to increase the successful rate of the treatment. The prostate specific antigen (PSA) is an important biomarker of prostate cancer that can be detected in biological fluids, including blood, urine and semen. However, the commercial kits available are addressed for blood samples and the commonly used analytical methods for their detection and quantification requires specialized staff, specific equipment and extensive sample processing, resulting in an expensive process. Thus, the aim of this MSc thesis consisted on the development of a simple, efficient and less expensive method for the extraction and concentration of PSA from urine samples using aqueous biphasic systems (ABS) composed of ionic liquids. Initially, the phase diagrams of a set of aqueous biphasic systems composed of an organic salt and ionic liquids were determined. Then, their ability to extract PSA was ascertained. The obtained results reveal that in the tested systems the prostate specific antigen is completely extracted to the ionic-liquid-rich phase in a single step. Subsequently, the applicability of the investigated ABS for the concentration of PSA was addressed, either from aqueous solutions or urine samples. The low concentration of this biomarker in urine (clinically significant below 150 ng/mL) usually hinders its detection by conventional analytical techniques. The obtained results showed that it is possible to extract and concentrate PSA, up to 250 times in a single-step, so that it can be identified and quantified using less expensive techniques.

Concentration of tumor biomarkers using aqueous biphasic systems

According to the World Health Organization, around 8.2 million people die each year with cancer. Most patients do not perform routine diagnoses and the symptoms, in most situations, occur when the patient is already at an advanced stage of the disease, consequently resulting in a high cancer mortality. Currently, prostate cancer is the second leading cause of death among males worldwide. In Portugal, this is the most diagnosed type of cancer and the third that causes more deaths. Taking into account that there is no cure for advanced stages of prostate cancer, the main strategy comprises an early diagnosis to increase the successful rate of the treatment. The prostate specific antigen (PSA) is an important biomarker of prostate cancer that can be detected in biological fluids, including blood, urine and semen. However, the commercial kits available are addressed for blood samples and the commonly used analytical methods for their detection and quantification requires specialized staff, specific equipment and extensive sample processing, resulting in an expensive process. Thus, the aim of this MSc thesis consisted on the development of a simple, efficient and less expensive method for the extraction and concentration of PSA from urine samples using aqueous biphasic systems (ABS) composed of ionic liquids. Initially, the phase diagrams of a set of aqueous biphasic systems composed of an organic salt and ionic liquids were determined. Then, their ability to extract PSA was ascertained. The obtained results reveal that in the tested systems the prostate specific antigen is completely extracted to the ionic-liquid-rich phase in a single step. Subsequently, the applicability of the investigated ABS for the concentration of PSA was addressed, either from aqueous solutions or urine samples. The low concentration of this biomarker in urine (clinically significant below 150 ng/mL) usually hinders its detection by conventional analytical techniques. The obtained results showed that it is possible to extract and concentrate PSA, up to 250 times in a single-step, so that it can be identified and quantified using less expensive techniques.