8 research outputs found

    ChainRank, a chain prioritisation method for contextualisation of biological networks

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    Advances in high throughput technologies and growth of biomedical knowledge have contributed to an exponential increase in associative data. These data can be represented in the form of complex networks of biological associations, which are suitable for systems analyses. However, these networks usually lack both, context specificity in time and space as well as the distinctive borders, which are usually assigned in the classical pathway view of molecular events (e.g. signal transduction). This complexity and high interconnectedness call for automated techniques that can identify smaller targeted subnetworks specific to a given research context (e.g. a disease scenario)

    A Systems Medicine approach to multimorbidity. Towards personalised care for patients with Chronic Obstructive Pulmonary Disease

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    [eng] BACKGROUND: Multimorbidity (i.e. the presence of more than one chronic disease in the same patient) and comorbidity (i.e. the presence of more than one chronic disease in the presence of an index disease) are main sources of dysfunction in chronic patients and avoidable costs in conventional health systems worldwide. By affecting a majority of elderly population worldwide, multimorbidity prompts the need for revisiting the single disease approach followed by contemporary clinical practice and elaborate strategies that target shared mechanisms of associated diseases with the potential of preventing, decelerating or even halting multimorbid disease progression. However, our current understanding on disease interactions is rather limited, and although many disorders have been associated based on their shared molecular traits and their observed co-occurrence in different populations, no comprehensive approach has been outlined to translate this knowledge into clinical practice. The advent of novel measurement technologies (e.g. omics) and recent initiatives on digital health (e.g. registries, electronic health records) are facilitating access to an enormous amount of patient-related information from whole populations to molecular levels. State-of-the art computational models and machine learning tools demonstrate high potential for health prediction and together with systems biology are shaping the practicalities of systems medicine. Given the extremely long and expensive bench to clinics cycles of the biomedical sector, systems medicine promises a fast track approach where scientific evidence support clinical care, while simultaneously collected insights from daily clinical practice promote new scientific discoveries and optimize healthcare. The PhD thesis aims to explore multimorbidity from a systems medicine perspective on the concrete and practical use case of chronic obstructive pulmonary disease (COPD). COPD constitutes an ideal use case due to several factors, including: i) its high impact on healthcare and its ever-increasing burden; ii) its heterogeneous disease manifestations, and progress, often involving extra-pulmonary effects, including highly prevalent comorbidities (e.g. type 2 diabetes mellitus, cardiovascular disorders, anxiety-depression and lung cancer); and, iii) its well described systemic effects that are suggested associations with comorbidities in terms of underlying mechanisms. HYPOTHESIS: The central hypothesis of the PhD thesis builds on the emerging biological evidence that clustering of comorbid conditions, a phenomenon seen in complex chronic patients, could be due to shared abnormalities in relevant biological pathways (i.e. bioenergetics, inflammation and tissue remodelling). It is assumed that a systems understanding of the patient conditions may help to uncover the molecular mechanisms and lead to the design of preventive and targeted therapeutic strategies aiming at modulating patient prognosis. The PhD thesis focuses on non-pulmonary phenomena of COPD; that is, systemic effects and comorbidities, often observed in patients with COPD as a paradigm of complex chronic disease. OBJECTIVES: The general objective of the PhD thesis is threefold: i) to investigate molecular disturbances at body systems level that may lead to a better understanding of characteristic systemic effects and comorbidities of patients with COPD; ii) to analyse population level patterns of COPD comorbidities and investigate their role in the health risk of patients with COPD; and, iii) to explore technological strategies and tools that facilitate the transfer of the collected knowledge on comorbidity into clinical practice. MAIN FINDINGS: Firstly, the PhD thesis introduced a novel knowledge management tool for targeted molecular analysis of underlying disease mechanisms of skeletal muscle dysfunction in patients with COPD. Second, a network analysis approach was outlined to further study this systemic effect, as well as the causes of abnormal adaptation of COPD muscle to exercise training. Furthermore, this work together with three other studies also aimed to reveal the general underlying causes of comorbidity clustering in COPD, using different modelling approaches. Overarching outcome of these studies indicates abnormalities in the complex co-regulation of core biological pathways (i.e. bioenergetics, inflammation, oxidative stress and tissue remodelling) both on muscle and body systems level (blood, lung), which paves the way for the development of novel pharmacological and non-pharmacological preventive interventions on non- pulmonary phenomena in patients with COPD. Furthermore, results indicated strong relation of muscle related dysregulations to aerobic capacity, in opposed to pulmonary severity of COPD. These findings have far reaching potential in COPD care, starting from defining the need for better characterization of exercise performance in the clinic practice and the promotion of physical activity from early stages of the disease. This PhD thesis also generated outcomes with respect to the risk of multimorbidity in patients with COPD using a population health approach. The thesis validated that patients with COPD are in increased risk to co-occur with other diseases compared to non-COPD patients, regardless of the population and healthcare system specificities of different regions (i.e. Catalonia, US). These findings indicated the potential role of multimorbidity as a risk factor for COPD, that was evaluated in the PhD thesis by constructing health risk assessment models to predict unexpected medical events in patients with COPD. The promising performance of the models and the prominent role of multimorbidity in these models presented a powerful argument for its role in clinical staging of the disease and their potential in clinical decision support. CONCLUSIONS: The PhD thesis achieved main points of the general objectives, namely: i) to perform a systems analysis of patients with COPD by investigating molecular disturbances at body systems level leading to a better understanding of characteristic systemic effects and comorbidities of patient with COPD; ii) to analyse population level patterns of COPD comorbidities and investigate their role in the health risk of patients with COPD; and iii) to explore technological strategies and tools that facilitate the transfer of the collected knowledge on comorbidity into clinical practice. Accordingly, the following conclusions arise: 1. Non-pulmonary manifestations in patients with Chronic Obstructive Pulmonary Disease (COPD) have a major negative impact on: highly relevant clinical events, use of healthcare resources and prognosis. Accordingly, the following indications were made: a. Actionable insights on non-pulmonary phenomena should be included in the clinical staging of these patients in an operational manner. b. Management of patients with COPD should be revisited to incorporate an integrative approach to non-pulmonary phenomena. c. Innovative cost-effective interventions, and pharmacological and non- pharmacological treatments targeting prevention of non-pulmonary manifestations in patients with COPD should be developed, and properly assessed. 2. Abnormal co-regulation of core biological pathways (i.e. bioenergetics, inflammation, tissue remodelling and oxidative stress), both in skeletal muscle and at body systems level, are common characteristics of patients with COPD, which potentially play a major role in comorbidity clustering. 3. Consistent relationships between cardiovascular health, skeletal muscle dysfunction and clinical outcomes in patients with COPD was identified, which makes it a priority to characterize patient exercise performance and physical activity in the clinic, and to adopt early cardiopulmonary rehabilitation strategies to modulate prognosis and prevent comorbidity clustering in these patients. 4. Multimorbidity is a strong predictor of unplanned medical events in patients with COPD and shows high potential to be used for personalized health risk prediction and service workflow selection. 5. Personalized health risk prediction was identified as a high potential tool for the integration and transfer of scientific evidence on multimorbidity to daily clinical practice. Limiting factors of its present applicability were explored and implementation strategies based on cloud computing solutions were proposed.[cat] INTRODUCCIÓ: Tant la multimorbiditat (la presència de més d'una malaltia crònica en el mateix pacient), com la comorbiditat (la presència de més d'una malaltia crònica quan hi ha una malaltia de referència) són una font important de disfuncions en l’atenció sanitària dels pacients crònics i generen importants despeses evitables en sistemes de salut arreu del món. La multimorbiditat/comorbiditat afecta la majoria de població de més de 65 anys. El seu gran impacte sanitari i social fa necessària la revisió d’aspectes essencials de la pràctica mèdica convencional, molt enfocada al tractament de cada malaltia de forma aïllada. En aquest sentit, cal elaborar estratègies que considerin els mecanismes biològics comuns entre patologies, per tal de prevenir, retardar o fins i tot aturar la progressió del fenomen. Malauradament, el poc coneixement dels mecanismes biològics que modulen les interaccions entre malalties és un factor limitant important. Hi ha estudis sobre els mecanismes moleculars comuns entre malalties i s’han realitzat anàlisis poblacionals de la multimorbiditat, però no existeix encara una aproximació holística per tal de traduir aquest coneixement a la pràctica clínica. L’aparició de noves tecnologies òmiques, així com iniciatives recents en l’àmbit de la salut digital, han facilitat l'accés a una quantitat enorme d'informació dels pacients, tant a nivell poblacional com a nivell molecular. A més, les eines computacionals i d'aprenentatge automàtic existents estan demostrant un gran potencial predictiu que, conjuntament amb les metodologies de la biologia de sistemes, estan conformant els aspectes pràctics del desplegament de la medicina de sistemes. De forma progressiva, aquesta última esdevé una via efectiva per accelerar el rol de l’evidència científica com a suport a la atenció clínica. De forma recíproca, la digitalització sistemàtica de la pràctica clínica diària, permet la generació de noves descobertes científiques i la optimització de l’assistència sanitària. Aquesta tesis doctoral pretén explorar la multimorbiditat des d’una perspectiva de medicina de sistemes, considerant com a cas d'ús concret i pràctic la malaltia pulmonar obstructiva crònica (MPOC). La MPOC constitueix un cas d'ús ideal a causa de diversos factors: i) el seu alt impacte a nivell sanitari; ii) la heterogeneïtat en quant a manifestacions i progrés, sovint amb efectes extra-pulmonars, incloent de forma freqüent comorbiditats com la diabetis mellitus tipus 2, trastorns cardiovasculars, l'ansietat-depressió i el càncer de pulmó; i, iii) els efectes sistèmics de la malaltia pulmonar, que podrien presentar mecanismes biològics comuns a algunes comorbiditats. HIPÒTESIS: La hipòtesi central d’aquesta tesis doctoral considera que la multimorbiditat podria explicar-se per alteracions en les xarxes de regulació de mecanismes biològics rellevants com la bioenergètica, inflamació i remodelació de teixits. En aquest sentit, l’anàlisi holística del problema podria millorar la comprensió dels mecanismes moleculars que modulen les associacions entre malalties i, per tant, facilitar el disseny d'estratègies terapèutiques preventives i dirigides a modular el pronòstic dels pacients. Aquesta tesis doctoral estudia els fenòmens extra-pulmonars de la MPOC; és a dir, efectes sistèmics (disfunció del múscul esquelètic) i comorbiditats, com a paradigma de malalties cròniques complexes. OBJECTIUS: L'objectiu general d’aquesta tesis doctoral és triple: i) l’anàlisi holístic de pacients amb MPOC amb focus en la disfunció muscular i les comorbiditats; ii) avaluar el paper de les comorbiditats en el risc de salut dels pacients amb MPOC, tant a nivell poblacional com individual; i, iii) explorar estratègies tecnològiques i eines de salut digital que facilitin la transferència de coneixement a la pràctica clínica diària. RESULTATS: El primer manuscrit de la tesi descriu una nova eina de gestió del coneixement per l’anàlisi molecular dels mecanismes de disfunció del múscul esquelètic en pacients amb MPOC. També dins el primer objectiu de la tesi, s’efectua un anàlisi de xarxes orientat a la identificació de mòduls biològics explicatius de la disfunció muscular i de l’adaptació anòmala d’aquests malalts a l’entrenament físic, tal com es descriu en el segon manuscrit. Els tres articles següents exploren, des de diferents perspectives, l’impacte i mecanismes de les comorbiditats en els pacients amb MPOC. Els principals resultats d'aquests estudis indiquen una complexa i anormal regulació de vies biològiques principals, com es el cas de la bioenergètica, inflamació, estrès oxidatiu i remodelació de teixits, tant a nivell del múscul com a nivell sistèmic (sang, pulmó). Aquests resultats obren noves vies per a intervencions preventives, tant farmacològiques com no farmacològiques, sobre els fenòmens no pulmonars que presenten els pacients amb MPOC. Els resultats indiquen una associació de les alteracions musculars amb la capacitat aeròbica, i no pas amb la gravetat de la malaltia pulmonar. Aquestes troballes tenen un gran potencial en la millora de la gestió dels pacients amb MPOC, començant per la necessitat d’una millor caracterització de la capacitat aeròbica en la pràctica clínica i la promoció d'activitat física des de les primeres etapes de la malaltia. La tesi també ha generat resultats d’interès en relació amb el risc de multimorbiditat en pacients amb MPOC, mitjançant un enfocament de salut poblacional. Els resultats evidencien que els pacients amb MPOC presenten un risc mes elevat de comorbiditat que els pacients sense MPOC, independentment de les especificitats de la població i del sistema sanitari de les àrees analitzades (Catalunya, EUA). La tesi també demostra el paper de la multimorbiditat com a factor modulador del risc clínic dels pacients amb MPOC. Aquests resultats indiquen l’interès de l’ús de la multimobiditat en l’estadiatge dels pacients amb MPOC i en l’elaboració d’eines de suport al procés de decisió clínica. CONCLUSIONS: Aquesta tesi doctoral ha assolit els objectius generals plantejats i proposa les següents conclusions: 1. Les manifestacions no pulmonars en els pacients amb malaltia pulmonar obstructiva crònica (MPOC) tenen un impacte negatiu respecte a esdeveniments de gran rellevància clínica, ús de recursos sanitaris i pronòstic. En conseqüència, es fan les següents recomanacions: a. Els fenòmens no pulmonars de la MPOC s’haurien d’incloure de manera operativa en l’estadiatge d'aquests pacients. b. S’hauria de redefinir la gestió clínica dels pacients amb MPOC tot incorporant un enfocament holístic dels fenòmens no pulmonars. c. S’haurien de desenvolupar i avaluar correctament noves intervencions, farmacològiques i no farmacològiques, per a la prevenció de les manifestacions no pulmonars en pacients amb MPOC. 2. Les alteracions de la regulació de vies biològiques rellevants com la bioenergètica, inflamació, estrès oxidatiu i la remodelació de teixits a nivell del múscul esquelètic, i també a nivell sistèmic, s’observa en els pacients amb MPOC i pot tenir un paper important en les co-morbiditats. 3. Les relacions entre alteracions cardiovasculars, disfunció del múscul esquelètic i altres aspectes clínics dels pacients amb MPOC, indiquen la necessitat de caracteritzar la capacitat aeròbica i els nivells d'activitat física en la pràctica clínica, així com la implementació d’estratègies de rehabilitació cardiopulmonar en les primeres etapes de la malaltia, per tal de modular la prognosis dels malalts i prevenir l’aparició de comorbiditats. 4. La multimorbiditat és un bon predictor d’esdeveniments clínics rellevants en pacients amb MPOC i mostra un gran potencial per a personalitzar l’estimació de risc i la selecció de serveis. 5. La predicció de risc de forma personalitzada s’ha identificat com una eina amb molt potencial per a la gestió de la multimorbiditat en la pràctica clínica diària. S’han explorat els factors limitants de la seva aplicabilitat i s’han proposat estratègies d'implementació d’eines predictives adients, basades en solucions de computació en el núvol.[spa] INTRODUCCIÓN: Tanto la multimorbilidad (la presencia de más de una enfermedad crónica en un mismo paciente) como la comorbilidad (la presencia de más de una enfermedad crónica en presencia de una enfermedad de referencia) son una fuente importante de disfunciones en la atención sanitaria de los pacientes crónicos y generan importantes costes evitables en los sistemas de salud de todo el mundo. La multimorbilidad/comorbilidad afecta a la mayoría de la población de más de 65 años. Debido a su gran impacto sanitario y social, resulta necesaria la revisión de aspectos esenciales de la práctica médica convencional, muy enfocada en el tratamiento de cada enfermedad de forma aislada. En este sentido, es necesario elaborar estrategias que consideren mecanismos biológicos comunes entre patologías, con el fin de prevenir, retrasar o incluso detener la progresión del fenómeno. Desgraciadamente, el escaso conocimiento de los mecanismos biológicos que modulan las interacciones entre enfermedades es un factor limitante importante. Existen estudios sobre los mecanismos moleculares comunes entre enfermedades y se han realizados análisis poblaciones de la multimorbilidad, pero no existe aún una aproximación holística que permita traducir este conocimiento a la práctica clínica. La aparición de nuevas tecnologías ómicas, así como recientes iniciativas en el ámbito de la salud digital, han facilitado el acceso a una cantidad enorme de información sobre los pacientes, tanto a nivel poblacional como a nivel molecular. Además, las herramientas computacionales y de aprendizaje automático existentes demuestran un gran potencial predictivo que, conjuntamente con las metodologías de biología de sistemas, están conformando los aspectos prácticos de la medicina de sistemas. De manera progresiva esta última se está convirtiendo en una vía efectiva para acelerar el papel de la evidencia científica como soporte a la atención clínica. De forma recíproca, la digitalización sistemática de la práctica clínica diaria permite la generación de nuevos descubrimientos científicos y la optimización de la asistencia sanitaria. Esta tesis doctoral pretende explorar la multimorbilidad desde una perspectiva de medicina de sistemas, considerando como caso de uso concreto y práctico la enfermedad pulmonar obstructiva crónica (EPOC). La EPOC constituye un caso de uso ideal debido a diversos factores: i) su alto impacto a nivel sanitario; ii) la heterogeneidad en cuanto a manifestaciones y progreso, a menudo con efectos extra pulmonares, incluyendo de forma frecuente comorbilidades como la diabetes mellitus tipo 2, trastornos cardiovasculares, la ansiedad-depresión y el cáncer de pulmón; y, iii) los efectos sistémicos de la enfermedad pulmonar, que podrían presentar mecanismos biológicos comunes a algunas comorbilidades. HIPÓTESIS: La hipótesis central de esta tesis doctoral considera que la multimorbilidad podría explicarse por alteraciones en las redes de regulación de mecanismos biológicos relevantes como la bioenergética, inflamación y remodelación de tejidos. En este sentido, el análisis holístico del problema podría mejorar la comprensión de los mecanismos moleculares que modulan las asociaciones entre enfermedades y, por tanto, facilitar el diseño de estrategias terapéuticas preventivas y dirigidas a modular el pronóstico de los pacientes. Esta tesis doctoral estudia los fenómenos extra pulmonares de la EPOC; es decir, efectos sistémicos (disfunción del músculo esquelético) y comorbilidades, como paradigma de enfermedades crónicas complejas. OBJETIVOS: El objetivo general de esta tesis doctoral es triple: i) el análisis holístico de pacientes con EPOC focalizando en la disfunción muscular y la comorbilidades; ii) evaluar el papel de las comorbilidades en el riesgo de salud de los pacientes con EPOC, tanto a nivel poblacional como individual; y, iii) explorar estrategias tecnológicas y herramientas de salud digital que faciliten la transferencia de conocimiento a la práctica clínica diaria. RESULTADOS: El primer manuscrito de la tesis describe una nueva herramienta de gestión del conocimiento para el análisis molecular de los mecanismos de disfunción del músculo esquelético en pacientes con EPOC. Incluido en el primer objetivo de la tesis, se efectúa un análisis de redes orientado a la identificación de módulos biológicos que explican la disfunción muscular y la adaptación anómala de estos pacientes al entrenamiento físico, tal y cómo se describe en el segundo manuscrito. Los tres artículos siguientes exploran, desde perspectivas diferentes, el impacto y mecanismos de las comorbilidades en los pacientes con EPOC. Los principales resultados de estos estudios indican una compleja y anormal regulación de vías biológicas principales, como es el caso de la bioenergética, inflamación, estrés oxidativo y remodelación de tejidos, tanto a nivel del músculo como a nivel sistémico (sangre, pulmón). Estos resultados abren nuevas vías para intervenciones preventivas, tanto farmacológicas como no farmacológicas, sobre los fenómenos no pulmonares que presentan los pacientes con E

    Informing epidemic (research) responses in a timely fashion by knowledge management - a Zika virus use case

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    The response of pathophysiological research to emerging epidemics often occurs after the epidemic and, as a consequence, has little to no impact on improving patient outcomes or on developing high-quality evidence to inform clinical management strategies during the epidemic. Rapid and informed guidance of epidemic (research) responses to severe infectious disease outbreaks requires quick compilation and integration of existing pathophysiological knowledge. As a case study we chose the Zika virus (ZIKV) outbreak that started in 2015 to develop a proof-of-concept knowledge repository. To extract data from available sources and build a computationally tractable and comprehensive molecular interaction map we applied generic knowledge management software for literature mining, expert knowledge curation, data integration, reporting and visualization. A multi-disciplinary team of experts, including clinicians, virologists, bioinformaticians and knowledge management specialists, followed a pre-defined workflow for rapid integration and evaluation of available evidence. While conventional approaches usually require months to comb through the existing literature, the initial ZIKV KnowledgeBase (ZIKA KB) was completed within a few weeks. Recently we updated the ZIKA KB with additional curated data from the large amount of literature published since 2016 and made it publicly available through a web interface together with a step-by-step guide to ensure reproducibility of the described use case. In addition, a detailed online user manual is provided to enable the ZIKV research community to generate hypotheses, share knowledge, identify knowledge gaps, and interactively explore and interpret data. A workflow for rapid response during outbreaks was generated, validated and refined and is also made available. The process described here can be used for timely structuring of pathophysiological knowledge for future threats. The resulting structured biological knowledge is a helpful tool for computational data analysis and generation of predictive models and opens new avenues for infectious disease research. ZIKV Knowledgebase is available at www.zikaknowledgebase.eu

    Exploring the interactions between neuron degeneration and RNA homeostasis through biological network analysis

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    Tese de mestrado em Bioquímica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016A esclerose lateral amiotrófica (ALS) e a atrofia muscular espinal (SMA) são caracterizadas pela degeneração dos neurónios motores (MN) e são comummente conhecidas como doenças neuromusculares, ou mais especificamente doenças do neurónio motor (MND). A morte dos neurónios motores está diretamente envolvida na perda da inervação muscular e na consequente atrofia muscular. Para além da convergência fenotípica, estas doenças também partilham grandes semelhanças moleculares. A perda de função dos genes que codificam as proteínas FUS, TDP43, SETX e SOD1 são as causas mais conhecidas de ALS. No caso da SMA, a doença é provocada pela produção de formas não funcionais da proteína SMN. Sabe-se que as proteínas FUS, TDP43, SMN e SETX (FTSS) interagem fisicamente e, além disso, são conhecidas por estarem envolvidas num conjunto de funções semelhantes, muitas das quais estão relacionados com os processos de metabolismo do RNA. Esta observação levou a hipótese de que a ALS e a SMA são fenótipos patológicos que, apesar de diferentes, derivam de mecanismos moleculares semelhantes, possivelmente associados a perturbação da hemóstase do RNA. No entanto, é muito intrigante como eventos transversais a todos os tipos celulares podem induzir a morte específica dos neurónios motores. A fim de resolver estas questões nos propomos uma abordagem de biologia de sistemas para descrever a estrutura interactomica e funcional da degeneração dos neurónios motores. A biologia de sistemas (systems biology) baseia-se no pressuposto de que "o todo é mais do que a soma das partes". Utiliza uma abordagem holística para decifrar a complexidade dos sistemas biológicos e para isso integra muitas disciplinas cientificas como a biologia, ciências computacionais, estatística e matemática. A biologia de sistemas concebe as entidades biológicas como sistemas complexos de elementos interrelacionados. Deste modo, uma boa maneira de entender as suas propriedades e representando-as como redes (networks). A biologia de redes (networks biology) e um subcampo da biologia de sistemas que explora os princípios da teoria de redes para inferir informação biológica. Da mesma forma, as doenças são o resultado fenotípico de perturbações interrelacionadas e assim também podem ser representadas como redes biológicas. A medicina de redes e, por sua vez, focalizada na obtenção de conhecimento biomédico a partir da biologia de redes. O nosso principal objetivo e, em primeiro lugar, identificar os elementos mais centrais numa rede de interação proteína-proteína contendo os genes associados a ALS e a SMA. Estes elementos serão parte de mecanismos patológicos hipoteticamente envolvidos na degeneração dos neurónios motores. Considerando a hipótese de que as proteínas FTSS são elementos centrais nas MNDs, realizamos primeiramente uma analise exploratória para desvendar as funções mais influentes entre as proteínas FTSS. Para isso foi construída uma rede de interações proteína-proteína (PPI) constituída pelos interactores mais próximos as proteínas FTSS, o que nos permite identificar as funções mais sobre-representadas dentro da rede. Embora, sabendo que as proteínas FTSS não são as únicas proteínas associadas as MNDs, também realizamos uma exploração mais integrativa incluindo todos os DAGs (genes associados a doença) conhecidos para a ALS e SMA e aplicando um método de priorização de DAGs para prever os elementos mais centrais a ligar as duas patologias. Contudo, depois de fazer extensa uma pesquisa bibliográfica, não encontramos nenhum método com um objectivo semelhante, pelo que construímos um método novo com base em teoria de redes para prever os nos que ligam especificamente os DAGs associados a um par de doenças. O método S2B foi concebido a partir do pressuposto de que as proteínas que interagem com um DAG são provavelmente relacionadas com a mesma doença (constituindo módulos de doenças na rede) e também que os DAGs são propensos a ser associados a mais do que uma doença (os módulos de doenças podem sobrepor-se). Assim, o método S2B está focado na medição dum tipo particular de medida de centralidade (S2B betweenness). O betweeness e uma medida de centralidade popular em biologia de redes que conta as vezes que um no está envolvido num caminho mais curto (shortest path) numa rede. Geralmente o betweeneess standard é medido para todos os possíveis caminhos mais curtos entre quaisquer nos enquanto que o S2B betweenness apenas considera os caminhos mais curtos entre pares de DAGs. Portanto, o método S2B só prioriza a centralidade dos elementos ligando genes causativos de duas doenças. Alem disso, sabendo que os nos altamente conectados (hubs) são mais propensos a aparecer por acaso num caminho mais curto entre DAGs, o algoritmo do S2B também utiliza dois algoritmos estatísticos baseados em aleatorizações da rede com os quais mede a especificidade dos hubs no contexto das doenças em estudo. As proteínas resultantes da priorização realizada pelo S2B foram enriquecidas funcionalmente. Os resultados da análise de enriquecimento foram comparados com os resultados obtidos na análise da rede particular para as proteínas FTSS para assim, explorar qual e o papel do metabolismo do RNA e outros mecanismos moleculares hipotéticos na degeneração dos neurónios motores. No conjunto das várias abordagens seguidas, este trabalho levou a descoberta de novos processos biológicos candidatos a mecanismos moleculares comuns entre a ALS e a SMA, mas também confirmou alguns processos já conhecidos simultaneamente envolvidos na ALS e na SMA. Globalmente, os nossos resultados sugerem cinco vias moleculares principais em comum nas duas patologias: 1) danos no DNA e apoptose induzidos pela desregulação da formação de “R-loops”, 2) inflamação e neuro degeneração induzida por uma hipersensibilidade imunológica, 3) desregulação da cromatina e genotoxicidade produzida pela perturbação da biogénese de histonas, 4) alteração dos padrões de “splicing” e genotoxicidade criada pela falha da formação do spliceossoma e 5) desregulação de processos relacionados com microtubulos que levam a problemas morfológicos na formação de axónios e sinapses. As vias identificadas sugerem novas hipóteses que podem ser experimentalmente testadas. Assim, esta investigação pode ajudar a melhorar a compreensão dos mecanismos envolvidos na morte dos neurónios motores e também ajudar eventualmente ao desenho de alvos terapêuticos e biomarcadores para as MNDs. Alem disso, também fornecemos um novo método para a priorização de DAGs candidatos a ligar os mecanismos moleculares de duas doenças relacionadas. Tal como no caso das MNDs, esperamos que este método ajude a comunidade a estudar outros tipos de doenças complexas.Amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) are characterized by motor neuron (MN) degeneration and commonly referred as motor neuron diseases (MND). MN degeneration leads to the loss of muscle innervation and subsequent muscular atrophy. In addition to phenotypic similarity, they also share molecular overlaps. Genes that codify FUS, TDP43, SETX and SOD1 proteins are the best-known causative genes of ALS and SMN dysfunction is the cause of SMA. FUS, TDP43, SMN and SETX (FTSS) proteins are known to physically interact and are involved in similar functions, many of which related to RNA metabolism processes. This supports the hypothesis that ALS and SMA are different pathophenotypic results derived from related molecular origins, in particular from RNA homeostasis perturbation. However, it is very intriguing how such critical events could specifically induce motor neuron perturbation. Besides, RNA metabolism is not the only function described for MND associated genes, indeed FTSS proteins are highly multifunctional which hinders the identification of the most relevant functions in this context. In order to solve these questions we followed a systems biology approach exploring the interactomic and functional framework of MN degeneration. Under the hypothesis that FTSS proteins are central elements in MN degeneration, we performed a local network analysis to unravel the most influential functions among FTSS proteins. We constructed a protein-protein interaction (PPI) network constituted by FTSS proteins' common interactors to identify the most over represented functions within this FTSS-focused network. We also performed a PPI network analysis including all the known MND associated genes. For that purpose we developed a new method, S2B (double specific betweenness) to prioritize nodes specifically linking a pair of diseases. While standard betweenness is measured for all possible shortest paths between any nodes, S2B only considers those shortest paths involving Disease Associated Genes (DAGs) from one disease as initial nodes and DAGs from the other disease as final nodes. Therefore, S2B method only prioritizes proteins linking MND causative genes. Moreover, knowing that highly connected nodes (hubs) are more likely found by chance in a shortest paths involving DAGs, S2B method also performs two network randomization-based statistics to filter out proteins that link MND DAGs non specifically. Finally we functionally enriched the prioritized candidates and compared against the functional set obtained with FTTS-focused network in other to explore the role of RNA metabolism and other putative molecular mechanisms on MN degeneration. The combined approaches used in this work provided novel biological processes simultaneously involved in ALS and SMA diseases and confirmed the relevance of known related processes. Globally, our results suggest five pathways in common between ALS and SMA: 1) DNA damage and apoptosis induced by R-loop deregulation, 2) inflammation and neurodegeneration induced by immune hyper-sensitivity, 3) chromatin deregulation and genotoxicity produced by histone biogenesis perturbation, 4) splicing patterns alteration and genotoxicity produced by spliceosome assembly failure and 5) deregulation of microtubule related processes leading to morphological problems in axon and synapse formation. Besides the new hypothesis of common pathomechanisms in MNDs, our work also supplies a new network-based DAG prioritization method, S2B, to identify disease-disease linking candidates we expect to contribute to the study of various complex diseases

    The molluscan shell secretome : unlocking calcium pathways in a changing world

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    How do molluscs build their shells? Despite hundreds of years of human fascination, the processes underpinning mollusc shell production are still considered a black box. We know molluscs can alter their shell thickness in response to environmental factors, but we do not have a mechanistic understanding of how the shell is produced and regulated. In this thesis I used a combination of methodologies - from traditional histology, to shell damage-repair experiments and ‘omics technologies - to better understand the molecular mechanisms which control shell secretion in two species, the Antarctic clam Laternula elliptica and the temperate blunt-gaper clam Mya truncata. The integration of different methods was particularly useful for assigning putative biomineralisation functions to genes with no previous annotation. Each chapter of this thesis found reoccurring evidence for the involvement of vesicles in biomineralisation and for the duplication and subfunctionalisation of tyrosinase paralogues. Shell damage-repair experiments revealed biomineralisation in L. elliptica was variable, transcriptionally dynamic, significantly affected by age and inherently entwined with immune processes. The high amount of transcriptional variation across 78 individual animals was captured in a single mantle regulatory gene network, which was used to predict the regulation of “classic” biomineralisation genes, and identify novel biomineralisation genes. There were some general shared patterns in the molecular control of biomineralisation between the two species investigated in this thesis, but overall, the comparative work in this thesis, coupled to the growing body of literature on the evolution of molluscan biomineralisation, suggests that biomineralisation mechanisms are surprisingly divergent

    ChainRank, a chain prioritisation method for contextualisation of biological networks

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    Advances in high throughput technologies and growth of biomedical knowledge have contributed to an exponential increase in associative data. These data can be represented in the form of complex networks of biological associations, which are suitable for systems analyses. However, these networks usually lack both, context specificity in time and space as well as the distinctive borders, which are usually assigned in the classical pathway view of molecular events (e.g. signal transduction). This complexity and high interconnectedness call for automated techniques that can identify smaller targeted subnetworks specific to a given research context (e.g. a disease scenario)
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