Departamento de Promoção da Saúde e Prevenção de Doenças Não Transmissíveis
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Browsing Departamento de Promoção da Saúde e Prevenção de Doenças Não Transmissíveis by advisor "Antunes, Marília"
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- Biochemical and molecular characterisation of the dyslipidaemia in PortugalPublication . Costa, Cibelle Neiva Cavalcanti Mariano da; Bourbon, Mafalda; Antunes, MaríliaABSTRACT: Dyslipidaemia is one of the major modifiable independent risk factors for cardiovascular disease (CVD), with both genetic and environmental determinants. Although genetic risk factors are considered as non-modifiable, their CVD-associated risk can be prevented if early identified. The correct and early identification of dyslipidaemia is important for a better patient management and could definitely contribute to CVD prevention. This thesis intended the most complete characterisation of the dyslipidaemia in the Portuguese population, both biochemically and molecularly. Reference values based on population-specific percentiles for lipid and lipoprotein biomarkers were provided for the first time in the Portuguese population, namely total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), apolipoprotein A1 (apoA1), apolipoprotein B (apoB), small, dense LDL-C (sdLDL-C), lipoprotein(a) [Lp(a)], as well apoB/apoA1 and sdLDL-C/LDL-C ratios, and non-HDL-C and remnant cholesterol. To our knowledge, the sdLDL-C percentiles were the first to be established in an European population. The percentiles were estimated through a rigorous methodology and compared with other population percentiles by a very visual and feasible method, showing relevant differences. These newly determined reference values for lipid biomarkers were then used to characterise the dyslipidaemia in our population, and can now be used in the clinic for a better patient care and management. More than cholesterol per se, our study highlighted apoB and sdLDL-C as important biomarkers to be used in dyslipidaemia evaluation. Individuals presenting extreme phenotypes were further investigated to assess possible monogenic causes, and three individuals were found to have familial hypercholesterolemia (FH), the most common genetic dyslipidaemia and one of the most common disorders that confer an increased cardiovascular risk. Finally, in an attempt to explore the causes for the FH phenotype, a polygenic risk score was validated for the first time in the Portuguese population. A total of 289 index cases were identified with monogenic FH and other causes for their dyslipidaemia, and also 100 were identified with polygenic hypercholesterolaemia, representing 53.21% of the cohort. From the monogenic causes, 91.35% have a mutation in LDLR, 4.84% in APOB, 1.04% in PCSK9 and 2.08% had mutations in phenocopies genes (LIPA, APOE, ALB), suggesting that all those monogenic and polygenic causes should be always investigated for a better patient identification. This study provided the most complete characterisation of the dyslipidaemia in the Portuguese population, and important evidences for dyslipidaemia evaluation has been produced. The results obtained have application, not only for Portugal or a south European populations, but also might have an worldwide utility for the dyslipidaemia assessment. Together, the results obtained provide useful information on an important cardiovascular risk factor and should help to tackle and identify at risk situations that need urgent measures.
- Classification methods applied to familial hypercholesterolemia diagnosis in pediatric agePublication . Albuquerque, João David Ferreira de Castro; Antunes, Marília; Bourbon, MafaldaIntroduction: Familial Hypercholesterolemia (FH) is an inherited disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels. The resulting severe dyslipidemia leads to the early development of atherosclerosis, representing a major risk factor for cardiovascular disease (CVD). The early diagnosis of FH is associated with a significant reduction in CVD risk, supporting the introduction of precocious and more aggressive therapeutic measures. There are different clinical criteria available for the diagnosis of FH, although only genetic testing can confirm the diagnostic. Simon Broome (SB) criteria for FH diagnosis are among the most frequently used in clinical setting, and are based on family history, presence of physical signs, and LDLc and total cholesterol (TC) levels. When compared to genetic diagnosis results however, SB criteria present a high false positive rate, which constitutes a heavy burden in terms of healthcare costs, and limits the access to the genetic study of a larger universe of potential FH cases. Aim: The main purpose of this work was to develop alternative classification methods for FH diagnosis, based on different biochemical indicators, with improved ability to screen for FH cases in comparison to SB criteria. Two different models were developed for this purpose: a logistic regression (LR), and a decision tree (DT) model. Methods: Serum concentrations of TC, LDLc, high density lipoprotein cholesterol (HDLc), triglycerides (TG), apolipoproteins AI (apoAI) and B (apoB), and lipoprotein(a) (Lp(a)) were determined, and genetic diagnosis was performed, in a sample of 252 participants in the Portuguese FH Study, at pediatric age (2-17 years). All patients met the clinical criteria for dyslipidemia, and were not under hypolipidemic medication during the evaluation period. LR and DT models were fitted to sample data. For the LR model, two different cutoff points were defined, through receiver operating characteristics (ROC) curve analysis, following Yoden index and minimum p-value (min p) methods. The DT was built based on entropy reduction, or information gain measures. A modified version of the DT method was implemented, consisting in the sequential exclusion of predictor variables as they are introduced in the model. This allows producing a classification rule that uses single cutpoints for biomarkers, simplifying its interpretation. Different operating characteristics (OC) were estimated for all models: accuracy (Acc), sensitivity (Se), specificity (Spe), positive predictive value (PPV ) and negative predictive value (NPV ). These OC were calculated by generating a confusion matrix, considering molecular study results as the true state of the disease. The best performing LR and DT models were compared with SB biochemical criteria for FH diagnosis, through bootstrap resampling techniques. Median and mean values of the OC for 200 bootstrap samples were used for predictive performance comparison. Results: The logit function for the LR final model was expressed as g(π) = -7:083 + 0:086 X LDLc -0:041 X TG - 0:037X apoAI. The best performing DT model included the variables LDLc, TG, apoAI, apoB and HDLc, by descending order of importance. Between the different classification methods, Acc, Spe and PPV were higher in the DT model, followed by the LR model with the cut point value (c) defined by the min p method (c = 0:35). The lower values in these OC are found for SB criteria (p < 0:01). Higher Se and NPV on the other hand, are achieved by SB criteria, and the LR model with the cutpoint value calculated by Youden index (c = 0:17). However, the LR model using this cutpoint achieves significantly higher Acc, Spe and NPV than SB criteria (p < 0:01). Conclusions: Both LR and DT models seem to be a valid alternative to traditional clinical criteria for FH diagnosis. It seems possible to adjust the cutoff value in the LR model for similar Se levels as the ones observed in SB criteria, with significantly less false positive retention. To be validated by additional data, this would undoubtedly indicate this method as preferable between the two, and can have a very important impact in terms of cost-effectiveness. By avoiding the repetition of predictor variables, and providing single cutoff values for each biomarker, the modified DT model assumes a structure that typically resembles medical criteria, and can therefore be easily used in clinical practice. It seems that, in spite using different methodological approaches, both LR and DT models are able to divide the sample according to the most relevant biochemical characteristics for FH diagnosis. According to both classification methods, presence of FH is directly related to LDLc levels, and inversely related to TG and ApoAI concentrations, by this order of importance. The preferred classification model, as well as model specifications, may vary as a function of the OC that are considered more important, and context in which it is applied.
- Development and Validation of Screening Methods Applied to Familial Hypercholesterolemia DiagnosisPublication . Albuquerque, João; Antunes, Marília; Antunes, Marília; Bourbon, Mafalda; Soares, RaquelFamilial hypercholesterolemia (FH) is an inherited disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels. If untreated, the severe dyslipidemia from birth leads to the early development of atherosclerosis, representing a major risk factor for cardiovascular disease (CVD). The early diagnosis of FH is associated with a signi cant reduction in CVD risk, supporting the introduction of risk mitigation strategies, such as cascade screening of rst degree relatives, and adequate lipid lowering therapy (LLT) as precociously as possible. The importance of genetic testing is emphasized by evidence that individuals with a con rmed pathogenic variant possess a signi cant increase in the risk of CVD when compared to subjects with FH-like phenotype for whom a causative variant is not detected. Nevertheless, molecular testing is still not available as a rst line diagnosis tool, and previous selection and strati cation of subjects to undergo this procedure should be made. Currently used clinical criteria, typically based on LDLc levels, family history of hypercholesterolemia and/ or premature CVD and presence of physical signs like tendon xanthomas, present the limitation of retaining a high number of false positive cases. This may constitute a heavy burden in terms of healthcare costs, and limits the access to the genetic study of a larger universe of true FH cases. The main purpose of this work was to develop alternative classi cation methods for FH diagnosis, based on di erent biochemical and clinical indicators, with improved ability to screen for FH cases in comparison to traditional clinical criteria. The metrics used for comparison range from the areas under the receiver operating characteristics (AUROC) and precision-recall (AUPRC) curves, to several operating characteristics (OC), to agreement tests, among others
- System biology approach for Cardiovascular MedicinePublication . Costa, Cibelle Neiva Cavalcanti Mariano da; Bourbon, Mafalda; Antunes, MaríliaCardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. The common forms of CVD have a complex aetiology in which interactions between multiple genetic and environmental factors play an important role. Of many independent cardiovascular risk factors that have been identified, namely, dyslipidaemia, arterial hypertension, diabetes, sedentarism, overweight/obesity, inadequate diet and smoking, all have a common link: all could be modifiable. In contrast, genetic risk factors are considered non-modifiable, but the associated risk can be prevented if early identified, making genetic studies a priority in cardiovascular genetics research. This research project proposes the study of interactions between biological, including genetics, and environmental factors that give rise to the cardiovascular risk profile as well as to characterise the genetic cardiovascular risk profile of the Portuguese population. It is also proposed to study the differential expression pattern between a control and disease (premature myocardial infarction) population in order to identify novel biomarkers for the early identification of at risk subjects. Overall 1700 individuals (men and women aged between 18 and 79), from e_COR project, involving Lisboa, Porto, Centro, Algarve and Alentejo regions will be included. Lipid profile will be analysed and percentiles defined and adjusted according to the lipid-lowering drugs. The different genes expression patterns will be analysed by RNA-Seq in 50 patients with premature myocardial infarction (pMI) and in 50 controls, without cardiovascular risk factors or CHD, from e_COR study. A combination of genomics and transcriptomics approaches will be performed to establish genotype/phenotype co-relation between known genetic markers and CVD disorders, as well as to investigate novel potential biomarkers. Statistical analysis will be performed with SPSS and R. The integration analysis of the effects of non-genetic risk factors and epigenetic variation, with knowledge of DNA sequence determinants and with the enormous quantities of information produced by the high-throughput technologies used to sequence the human genome, has the potential to improve the understanding of the aetiology, prediction and stratification of CVD, by connecting biological information in disease-specific network. This project will contribute for a better knowledge of the interactions between biological and/or environmental factors that give rise to cardiovascular risk, as well as determining the cardiovascular risk profile of the Portuguese population. With all the data collected it will also be possible to establish reference values for biomarkers of lipid metabolism. The results should have a high impact on the definition of criteria for identifying individuals at high risk for developing CVD.