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Browsing by Author "Medeiros, Ana M."

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  • Comparison of the mutation spectrum and association with pre and post treatment lipid measures of children with heterozygous familial hypercholesterolaemia (FH) from eight European countries
    Publication . Futema, Marta; Ramaswami, Uma; Tichy, Lukas; Bogsrud, Martin P.; Holven, Kirsten B.; Roeters van Lennep, Jeanine; Wiegman, Albert; Descamps, Olivier S.; De Leener, Anne; Fastre, Elodie; Vrablik, Michal; Freiberger, Tomas; Esterbauer, Harald; Dieplinger, Hans; Greber-Platzer, Susanne; Medeiros, Ana M.; Bourbon, Mafalda; Mollaki, Vasiliki; Drogari, Euridiki; Humphries, Steve E.
    Background and aims: Familial hypercholesterolaemia (FH) is commonly caused by mutations in the LDLR, APOB or PCSK9 genes, with untreated mean low density lipoprotein-cholesterol (LDL-C) concentrations being elevated in APOB mutation carriers, even higher in LDLR mutation and highest in those with a PCSK9 mutation. Here we examine this in children with FH from Norway, UK, The Netherlands, Belgium, Czech Republic, Austria, Portugal and Greece. Methods: Differences in characteristics and pre- and post-treatment lipid concentrations in those with different molecular causes were compared by standard statistical tests. Results: Data were obtained from 2866 children, of whom 2531 (88%) carried a reported LDLR/APOB/PCSK9 variant. In all countries, the most common cause of FH was an LDLR mutation (79% of children, 297 different), but the prevalence of the APOB p.(Arg3527Gln) mutation varied significantly (ranging from 0% in Greece to 39% in Czech Republic, p < 2.2 × 10-16). The prevalence of a family history of premature CHD was significantly higher in children with an LDLR vs APOB mutation (16% vs 7% p=0.0005). Compared to the LDLR mutation group, mean (±SD) concentrations of pre-treatment LDL-C were significantly lower in those with an APOB mutation (n = 2260 vs n = 264, 4.96 (1.08)mmol/l vs 5.88 (1.41)mmol/l, p < 2.2 × 10-16) and lowest in those with a PCSK9 mutation (n = 7, 4.71 (1.22)mmol/l). Conclusions: The most common cause of FH in children from eight European countries was an LDLR mutation, with the prevalence of the APOB p.(Arg3527Gln) mutation varying significantly across countries. In children, LDLR-FH is associated with higher concentrations of LDL-C and family history of CHD compared to those with APOB-FH.
    2021-01-12Journal article Restricted access Show more
  • Estudo Português de Hipercolesterolemia Familiar: 1999-2020
    Publication . Medeiros, Ana M.; Alves, Ana C.; Chora, Joana R.; Bourbon, Mafalda
    A Hipercolesterolemia Familiar (FH) é uma doença genética do metabolismo dos lípidos, para a qual existem métodos de diagnóstico e tratamentos eficazes disponíveis. Em Portugal estima-se que existam entre 20 000–33 000 pessoas com FH (prevalência 1:500–1:300). Indivíduos com FH possuem um elevado risco de desenvolver uma doença cardiovascular prematura (DCV), pois apresentam valores de colesterol elevados desde a nascença. O diagnóstico genético inclui o estudo de 3 genes associados à FH: LDLR, APOB, PCSK93. O Estudo Português de Hipercolesterolemia Familiar teve início em 1999 e tem como objetivo identificar a causa da genética da hipercolerolemia em indivíduos com critérios clínicos de FH.
    2021-05Conference object Restricted access Show more
  • Single versus Multiple Imputation Methods Applied to Classify Dyslipidemic Patients Concerning Statin Usage: a Comparative Performance Study
    Publication . Albuquerque, João; Alves, Ana C.; Medeiros, Ana M.; Bourbon, Mafalda; Antunes, Marília
    Introduction: One ofthe greatest challenges when working with clinical datasetsisto decide howto deal withmissing values. Removing observations with any missing values priorto data analysis, a process defined aslistwise deletion, is the standard default procedure in most statistical software packages, but may lead to great loss of valuable information [1]. The use of robust imputation methods may provide accurate estimates for missing values, allowing to include these observations into the analysis. The imputation strategy to adopt depends on the amount and type of missing information, and also on the relation between variables, allying statistical expertise with clinical understanding of the data. The main purpose of this work was to compare the performance oftwo differentmethods ofimputationto overcomemissingness on dyslipidemic patients regarding statin usage.
    2020-10Conference object Open access Show more