CINTHIA ELIM JANNES LEPSKI
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina
6 resultados
Resultados de Busca
Agora exibindo 1 - 6 de 6
- Cardiovascular disease onset in old people with severe hypercholesterolemia(2023) COUTINHO, Elaine R.; MINAME, Marcio H.; ROCHA, Viviane Z.; BITTENCOURT, Marcio S.; JANNES, Cinthia E.; KRIEGER, Jose E.; PEREIRA, Alexandre C.; SANTOS, Raul D.Background and aims: Familial hypercholesterolemia (FH) variants are associated with higher atherosclerotic cardiovascular disease risk (ASCVD) even when compared with other forms of severe hypercholesterolemia, especially in young people. Lipid lowering therapies (LLT) may change hypercholesterolemia natural history. This study aimed at evaluating factors associated with occurrence of ASCVD in old severe hypercholesterolemics diagnosed or not with FH and undergoing LLT.Methods: Hypercholesterolemic individuals >= 60 years participating on a genetic cascade screening for FH were divided in 4 groups (2 x 2) according to the presence (variant+) or not (variant-) of FH genetic variants and previous ASCVD (ASCVD+ and ASCVD-). Biomarkers associated with new incident ASCVD events were tested using Cox models. Continuous data shown as medians (%25; %75).Results: From 4,111 genotyped individuals, 377 (9.1%) were elderly [age 66 (63; 71) years], 28.9% males, 42.7% variant+, 32.1% with previous ASCVD, LLT duration 9 (5; 16) years, and on treatment LDL-cholesterol 144 (109; 200) mg/dL. After 4.8 (7; 3) years of follow up there were 47 incident events (12.4%, 2.7% patient/year). The annualized event rates were 0.8% (95% CI 0.36%; 1.70%), 2.3% (95% CI 1.3%; 4.1%), 5.2% (95% CI 2.8%; 9.7%) and 6.3% (95% CI 4.0%; 10.0%) respectively for groups variant-/ASCVD-, variant+/ASCVD-, variant-/ ASCVD+ and, variant+/ASCVD+ (p log rank p < 0.001). Only presence of previous ASCVD was independently associated with incident ASCVD [hazard ratio 3.236 (95%CI 1.497-6.993, p = 0.003)]. No interaction was found for previous ASCVD and variants.Conclusions: In old severe hypercholesterolemic individuals undergoing long-term LLT previous ASCVD was associated with incident events while FH causing variants were not.
conferenceObject RAPID PROGRESSION OF CORONARY ATHEROSCLEROSIS IN A PATIENT WITH AUTOSSOMAL RECESSIVE HYPERCHOLESTEROLEMIA(2023) MIZUTA, Marjorie Hayashida; AMORIM, Matheus; ROCHA, Viviane Zorzanelli; MINAME, Marcio Hiroshi; JANNES, Cinthia Elim; PEREIRA, Alexandre Costa; KRIEGER, Jose Eduardo; SANTOS, Raul; CHACRA, Ana Paula Marte- LDLR gene's promoter region hypermethylation in patients with familial hypercholesterolemia(2023) ZORZO, R. A.; SUEN, V. M. M.; SANTOS, J. E.; SILVA-JR, W. A.; SUAZO, V. K.; HONORATO, A. L. S. C.; SANTOS, R. D.; JANNES, C. E.; PEREIRA, A.; KRIEGER, J. E.; LIBERATORE, R. D. R.Familial hypercholesterolemia (FH) is characterized by high low-density lipoprotein cholesterol (LDL-C) levels and a high risk of early coronary heart disease. Structural alterations in the LDLR, APOB, and PCSK9 genes were not found in 20-40% of patients diagnosed using the Dutch Lipid Clinic Network (DCLN) criteria. We hypothesized that methylation in canonical genes could explain the origin of the phenotype in these patients. This study included 62 DNA samples from patients with a clinical diagnosis of FH according to the DCLN criteria, who previously tested negative for structural alterations in the canonical genes, and 47 DNA samples from patients with normal blood lipids (control group). All DNA samples were tested for methylation in the CpG islands of the three genes. The prevalence of FH relative to each gene was determined in both groups and the respective prevalence ratios (PRs) were calculated. The methylation analysis of APOB and PCSK9 was negative in both groups, showing no relationship between methylation in these genes and the FH phenotype. As the LDLR gene has two CpG islands, we analyzed each island separately. The analysis of LDLR-island1 showed PR = 0.982 (CI 0.33-2.95; chi(2) = 0.001; p = 0.973), also suggesting no relationship between methylation and the FH phenotype. Analysis of LDLR-island2 showed a PR of 4.12 (CI 1.43-11.88; chi(2) = 13,921; p = 0.00019), indicating a possible association between methylation on this island and the FH phenotype.
conferenceObject Cardiovascular Disease Progression in Children With Homozygous Familial Hypercholesterolemia Despite Early Diagnosis on a Genetic Cascade Screening Program(2022) JULIANI, Fabiana C.; CHACRA, Ana Paula M.; MINAME, Marcio H.; SALGADO FILHO, Wilson; MIZUTA, Marjorie H.; JANNES, Cinthia E.; KRIEGER, Jose E.; MARANHAO, Raul C.; SANTOS, Raul D.; ROCHA, Viviane Z.- Identification of pathogenic variants in the Brazilian cohort with Familial hypercholesterolemia using exon-targeted gene sequencing(2023) BORGES, Jessica Bassani; OLIVEIRA, Victor Fernandes; DAGLI-HERNANDEZ, Carolina; FERREIRA, Glaucio Monteiro; BARBOSA, Thais Kristini Almendros Afonso; MARCAL, Elisangela da Silva Rodrigues; LOS, Bruna; MALAQUIAS, Vanessa Barbosa; BORTOLIN, Raul Hernandes; FREITAS, Renata Caroline Costa; MORI, Augusto Akira; BASTOS, Gisele Medeiros; GONCALVES, Rodrigo Marques; ARAUJO, Daniel Branco; ZATZ, Henry; BERTOLAMI, Adriana; FALUDI, Andre Arpad; BERTOLAMI, Marcelo Chiara; SOUZA, Amanda Guerra de Moraes Rego; FRANCA, Joao Italo Dias; THUROW, Helena Strelow; HIRATA, Thiago Dominguez Crespo; NAKAYA, Helder Takashi Imoto; JANNES, Cinthia Elim; PEREIRA, Alexandre da Costa; SILBIGER, Vivian Nogueira; LUCHESSI, Andre Ducati; ARAUJO, Jessica Nayara Goes; NAKAZONE, Marcelo Arruda; CARMO, Tayanne Silva; SOUZA, Doroteia Rossi Silva; MORIEL, Patricia; WANG, Jaqueline Yu Ting; NASLAVSKY, Michel Satya; GORJAO, Renata; PITHON-CURI, Tania Cristina; CURIO, Rui; FAJARDO, Cristina Moreno; WANG, Hui-Tzu Lin; GAROFALO, Adriana Regina; CERDA, Alvaro; SAMPAIO, Marcelo Ferraz; HIRATA, Rosario Dominguez Crespo; HIRATA, Mario HiroyukiFamilial hypercholesterolemia (FH) is a monogenic disease characterized by high plasma low-density lipoprotein cholesterol (LDL-c) levels and increased risk of premature atherosclerotic cardiovascular disease. Mutations in FH-related genes account for 40% of FH cases worldwide. In this study, we aimed to assess the pathogenic variants in FH-related genes in the Brazilian FH cohort FHBGEP using exon-targeted gene sequencing (ETGS) strategy. FH patients (n = 210) were enrolled at five clinical sites and peripheral blood samples were obtained for laboratory testing and genomic DNA extraction. ETGS was performed using MiSeq platform (Illumina). To identify deleterious variants in LDLR, APOB, PCSK9, and LDLRAP1, the long-reads were subjected to Burrows -Wheeler Aligner (BWA) for alignment and mapping, followed by variant calling using Genome Analysis Tool -kit (GATK) and ANNOVAR for variant annotation. The variants were further filtered using in-house custom scripts and classified according to the American College Medical Genetics and Genomics (ACMG) guidelines. A total of 174 variants were identified including 85 missense, 3 stop-gain, 9 splice-site, 6 InDel, and 71 in regu-latory regions (3 & PRIME;UTR and 5 & PRIME;UTR). Fifty-two patients (24.7%) had 30 known pathogenic or likely pathogenic variants in FH-related genes according to the American College Medical and Genetics and Genomics guidelines. Fifty-three known variants were classified as benign, or likely benign and 87 known variants have shown un-certain significance. Four novel variants were discovered and classified as such due to their absence in existing databases. In conclusion, ETGS and in silico prediction studies are useful tools for screening deleterious variants and identification of novel variants in FH-related genes, they also contribute to the molecular diagnosis in the FHBGEP cohort.
- Generation and validation of a classification model to diagnose familial hypercholesterolaemia in adults(2023) ALBUQUERQUE, Joao; MEDEIROS, Ana Margarida; ALVES, Ana Catarina; JANNES, Cinthia Elim; MANCINA, Rosellina M.; PAVANELLO, Chiara; CHORA, Joana Rita; MOMBELLI, Giuliana; CALABRESI, Laura; PEREIRA, Alexandre da Costa; KRIEGER, Jose Eduardo; ROMEO, Stefano; BOURBON, Mafalda; ANTUNES, MariliaBackground and aims: The early diagnosis of familial hypercholesterolaemia is associated with a significant reduction in cardiovascular disease (CVD) risk. While the recent use of statistical and machine learning algorithms has shown promising results in comparison with traditional clinical criteria, when applied to screening of potential FH cases in large cohorts, most studies in this field are developed using a single cohort of patients, which may hamper the application of such algorithms to other populations. In the current study, a logistic regression (LR) based algorithm was developed combining observations from three different national FH cohorts, from Portugal, Brazil and Sweden. Independent samples from these cohorts were then used to test the model, as well as an external dataset from Italy.Methods: The area under the receiver operating characteristics (AUROC) and precision-recall (AUPRC) curves was used to assess the discriminatory ability among the different samples. Comparisons between the LR model and Dutch Lipid Clinic Network (DLCN) clinical criteria were performed by means of McNemar tests, and by the calculation of several operating characteristics.Results: AUROC and AUPRC values were generally higher for all testing sets when compared to the training set. Compared with DLCN criteria, a significantly higher number of correctly classified observations were identified for the Brazilian (p < 0.01), Swedish (p < 0.01), and Italian testing sets (p < 0.01). Higher accuracy (Acc), G mean and F1 score values were also observed for all testing sets.Conclusions: Compared to DLCN criteria, the LR model revealed improved ability to correctly classify observations, and was able to retain a similar number of FH cases, with less false positive retention. Generalization of the LR model was very good across all testing samples, suggesting it can be an effective screening tool if applied to different populations.