Metabolomics, proteomics, and genomics analyses provide profound insight into human biology and disease pathophysiology. In this thesis, we explored the methodological challenges facing these OMICs... Show moreMetabolomics, proteomics, and genomics analyses provide profound insight into human biology and disease pathophysiology. In this thesis, we explored the methodological challenges facing these OMICs technologies and illustrated their applications in epidemiological studies. In part one, we focused on some of the methodological challenges facing OMICs research. These challenges included handling missing data in metabolomics, measurement agreement between high throughput proteomic measurements with standard clinical measurements, and challenges in developing prediction models using metabolomic data. The second part of this thesis addressed various epidemiological research questions by utilizing genomic data and metabolomics measurements (Metabolon and Nightingale platforms) and using advanced data analysis methods. These studies provided important insights into the associations between metabolites and hepatic triglyceride content, the associations of between the size of cytosine-adenine-guanine nucleotide repeats in the huntingtin gene with metabolomic profile, and the associations of the man-made per- and polyfluoroalkyl substances (PFAS) with metabolite levels. Show less
A direct comparison of two methods for estimating the treated incidence of schizophrenia: the first-contact design (current standard) vs. an electronic psychiatric case-register (new method). The... Show moreA direct comparison of two methods for estimating the treated incidence of schizophrenia: the first-contact design (current standard) vs. an electronic psychiatric case-register (new method). The assumptions underlying the first-contact design are tested. The causes of 2 to 4-fold difference in estimates are conceptualized in a 3-dimensional model. The model is tested on the Norther European incidence literature. Show less
Ramspek, C.L.; Steyerberg, E.W.; Riley, R.D.; Rosendaal, F.R.; Dekkers, O.M.; Dekker, F.W.; Diepen, M. van 2021
Etiological research aims to uncover causal effects, whilst prediction research aims to forecast an outcome with the best accuracy. Causal and prediction research usually require different methods,... Show moreEtiological research aims to uncover causal effects, whilst prediction research aims to forecast an outcome with the best accuracy. Causal and prediction research usually require different methods, and yet their findings may get conflated when reported and interpreted. The aim of the current study is to quantify the frequency of conflation between etiological and prediction research, to discuss common underlying mistakes and provide recommendations on how to avoid these. Observational cohort studies published in January 2018 in the top-ranked journals of six distinct medical fields (Cardiology, Clinical Epidemiology, Clinical Neurology, General and Internal Medicine, Nephrology and Surgery) were included for the current scoping review. Data on conflation was extracted through signaling questions. In total, 180 studies were included. Overall, 26% (n = 46) contained conflation between etiology and prediction. The frequency of conflation varied across medical field and journal impact factor. From the causal studies 22% was conflated, mainly due to the selection of covariates based on their ability to predict without taking the causal structure into account. Within prediction studies 38% was conflated, the most frequent reason was a causal interpretation of covariates included in a prediction model. Conflation of etiology and prediction is a common methodological error in observational medical research and more frequent in prediction studies. As this may lead to biased estimations and erroneous conclusions, researchers must be careful when designing, interpreting and disseminating their research to ensure this conflation is avoided. Show less
Rodrigues, A.M.; Gouveia, N.; Costa, L.P. da; Eusebio, M.; Ramiro, S.; Machado, P.; ... ; EpiReumaPt Study Grp 2015
The content of this thesis is of two sorts: in one part, three topics about the early origins of adult disease are addressed, preceded by three related methodological studies which form the other... Show moreThe content of this thesis is of two sorts: in one part, three topics about the early origins of adult disease are addressed, preceded by three related methodological studies which form the other part. The thesis starts with a systematic review of the literature about the growth of infants born preterm. Next, three specific methodological issues related to early origins of adult disease studies are addressed. A: the most favorable regression model for analyzing and interpreting the effect of both prenatal and subsequent postnatal growth on adult health outcomes. B: the efficiency of reliability studies in the context of a multi-centre study. And C: the correct and clear assessment of reliability in case of log transformed outcomes. These methods are used ind the second part, in which three topics about the effects of prenatal and early postnatal growth on adult health outcomes are addressed, namely: A the association between birth weight and adult renal function in non-premature subjects. B: The association between birth weight and the adult metabolic syndrome, and its separate components in the same population. And finally, C: the association between early growth and adult body composition in subjects born very preterm. Show less
