Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

: Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and Results An lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score ≥1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups <0.0001); however, subjects with FH/M- and lp(a) score ≥1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level ≥190 mg/dL (or from 68% to 50%, considering a more conservative formula). Conclusions Our study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

Refinement of the diagnostic approach for the identification of children and adolescents affected by familial hypercholesterolemia: Evidence from the LIPIGEN study

Background and aims: We aimed to describe the limitations of familiar hypercholesterolemia (FH) diagnosis in childhood based on the presence of the typical features of FH, such as physical sings of cholesterol accumulation and personal or family history of premature cardiovascular disease or hypercholesterolemia, comparing their prevalence in the adult and paediatric FH population, and to illustrate how additional information can lead to a more effective diagnosis of FH at a younger age.Methods: From the Italian LIPIGEN cohort, we selected 1188 (>= 18 years) and 708 (<18 years) genetically-confirmed heterozygous FH, with no missing personal FH features. The prevalence of personal and familial FH features was compared between the two groups. For a sub-group of the paediatric cohort (N = 374), data about premature coronary heart disease (CHD) in second-degree family members were also included in the evaluation.Results: The lower prevalence of typical FH features in children/adolescents vs adults was confirmed: the prevalence of tendon xanthoma was 2.1% vs 13.1%, and arcus cornealis was present in 1.6% vs 11.2% of the cohorts, respectively. No children presented clinical history of premature CHD or cerebral/peripheral vascular disease compared to 8.8% and 5.6% of adults, respectively. The prevalence of premature CHD in first-degree relatives was significantly higher in adults compared to children/adolescents (38.9% vs 19.7%). In the sub-cohort analysis, a premature CHD event in parents was reported in 63 out of 374 subjects (16.8%), but the percentage increased to 54.0% extending the evaluation also to second-degree relatives.Conclusions: In children, the typical FH features are clearly less informative than in adults. A more thorough data collection, adding information about second-degree relatives, could improve the diagnosis of FH at younger age

Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and ResultsAn lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score >= 1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups <0.0001); however, subjects with FH/M- and lp(a) score >= 1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level >= 190 mg/dL (or from 68% to 50%, considering a more conservative formula). ConclusionsOur study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

Refinement of the diagnostic approach for the identification of children and adolescents affected by familial hypercholesterolemia: Evidence from the LIPIGEN study

Background and aims: We aimed to describe the limitations of familiar hypercholesterolemia (FH) diagnosis in childhood based on the presence of the typical features of FH, such as physical sings of cholesterol accumulation and personal or family history of premature cardiovascular disease or hypercholesterolemia, comparing their prevalence in the adult and paediatric FH population, and to illustrate how additional information can lead to a more effective diagnosis of FH at a younger age. Methods: From the Italian LIPIGEN cohort, we selected 1188 (≥18 years) and 708 (<18 years) genetically-confirmed heterozygous FH, with no missing personal FH features. The prevalence of personal and familial FH features was compared between the two groups. For a sub-group of the paediatric cohort (N = 374), data about premature coronary heart disease (CHD) in second-degree family members were also included in the evaluation. Results: The lower prevalence of typical FH features in children/adolescents vs adults was confirmed: the prevalence of tendon xanthoma was 2.1% vs 13.1%, and arcus cornealis was present in 1.6% vs 11.2% of the cohorts, respectively. No children presented clinical history of premature CHD or cerebral/peripheral vascular disease compared to 8.8% and 5.6% of adults, respectively. The prevalence of premature CHD in first-degree relatives was significantly higher in adults compared to children/adolescents (38.9% vs 19.7%). In the sub-cohort analysis, a premature CHD event in parents was reported in 63 out of 374 subjects (16.8%), but the percentage increased to 54.0% extending the evaluation also to second-degree relatives. Conclusions: In children, the typical FH features are clearly less informative than in adults. A more thorough data collection, adding information about second-degree relatives, could improve the diagnosis of FH at younger age

Planning of quinone compounds with trypanocidal activity

Desde a identificação do vírus da imunodeficiência humana (HIV, do inglês Human Immunodeficiency Virus) como agente causador da Síndrome da Imunodeficiência Adquirida (AIDS ? do inglês Acquired Immunodeficiency Syndrome), a busca para tratamentos seguros e eficazes contra o HIV transformou-se no principal foco para a descoberta de uma nova droga em todo o mundo. A AIDS aparece como um dos principais problemas de saúde pública para as próximas décadas, onde será o maior determinante de mortalidade na faixa etária entre 20 e 50 anos em praticamente todos os países do mundo. Tendo como objetivo relacionar a atividade de compostos biflavonóides anti-HIV-1 com algumas de suas propriedades moleculares, serão utilizados métodos de Mecânica Molecular e Química Quântica. O método de cálculo semi-empírico AM1 foi empregado para calcular um conjunto de propriedades moleculares dos 14 compostos biflavonóides com atividade anti-HIV-1. A seguir utilizar-se-á métodos estatísticos com a finalidade de separar os 14 compostos em duas classes, ativos e não ativos, de forma que se relacione qual as propriedades, dentre as calculadas, são responsáveis pela atividade dos compostos biflavonóides estudados. As técnicas estatísticas utilizadas foram a Análise de Componentes Principais (PCA: Principal Components Analysis), Análise Hierárquica de Agrupamentos (HCA: Hierarquical Clusters Analysis) e Análise de Discriminates por Passos (SDA: Stepwise Discriminant Analysis). Os estudos com PCA, HCA, e SDA mostraram que as variáveis HOMO (Highest Occupied Molecular Orbital - Orbital Molecular Ocupado de Maior Energia), LUMO (Lowest Unoccupied Molecular Orbital ? Orbital Molecular Desocupado de Menor Energia), e Área superficial são responsáveis pela separação dos compostos com alta e baixa atividade anti-HIV-1. O comportamento destas três propriedades pode ser útil na tentativa de se obter outros compostos biflavonóides com elevada atividade inibidora anti-HIV-1.A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the Density Functional Theory (DFT) method in order to calculate electronic atomic and molecular properties to be correlated with the biological activity. The chemometric methods Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Stepwise Discriminant Analysis (SDA), Kth nearest neighbor (KNN) and Soft Independent Modeling of Class Analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and predict the anti-trypanocidal activity of new quinone compounds from a test set. Four descriptors were responsible for the separation between the active and inactive compounds: T5 (torsion angle), HOMO-1 (energy of the first molecular orbital below HOMO), QTS1 (sum of absolute values of the atomic charges) and VOLS2 (volume of the substituent at region B). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new quinone compounds by using the PCA, HCA, SDA, KNN and SIMCA. Beside the five chemometric methods, the neural network method was used by employing the backpropagation algorithm. The four variables (T5, QTS1, VOLS2 and HOMO-1) were employed to validate the models constructed previously. The architecture of networks consisting of four neurons at input layers, ten neurons at intermediary layers and two neurons at output layers was adopted to observe the root mean square error between the true and desired output over the entire training set. The percentage of correct classification was 87.5%, and only one compound was predicted wrong in the test set, which indicates that the model is robust and could be able to make predictions. The docking studies were carried out with two different programs in the approach of ligands: the Autodock and FlexX. The docking results on trypanothione reductase enzyme showed that all studied compounds stay at second hydrophobic pocket in the outer region of the active site called the Z-site. The residues that could be specifically involved in the binding of ligands are Lys62, Thr66, Thr397, Thr463, Leu399, Ser464, Glu466 and Glu467, where the residues Thr66, Thr463 and Leu399 are conserved in different trypanothiones and could be used for the development of selective inhibitors against to the parasite enzyme

Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity

In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico CNPqConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Funda ao de Amparo a Pesquisa do Estado de Sao Paulo Fapesp (Brazilian Granting Agencies)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CAPESConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)CNPqFAPESPFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP