11/11 – SEMINÁRIO DE QUALIFICAÇÃO (Doutorado)

11 de novembro de 2024 – 10h30min

SEMINÁRIO DE QUALIFICAÇÃO (Doutorado)

FABYANNE GUIMARÃES DE OLIVEIRA

Clinical-epidemiological profile of congenital heart anomalies in reference hospitals in southern Brazil, with a bioinformatics approach

Orientadora: Dra. Lavínia Schüler Faccini

Coorientadora: Dra. Thayne Woycinck Kowalski

Banca Examinadora: Dra. Giovanna Câmara Giudicelli e Dr. Fabiano de Oliveira Poswar

11 de novembro de 2024 (segunda-feira)

10h30min

Presencial: Anfiteatro do Departamento de Genética da UFRGS (Campus do Vale, prédio 43312)

Sala virtual: https://mconf.ufrgs.br/webconf/ppgbm

Abstract

Congenital heart diseases (CHD) are structural anomalies of the heart and large intrathoracic vessels present at birth, affecting 0.8-1 per 100 live births, and are one of the major causes of infant mortality. Its can be diagnosed as isolated defects or associated with genetic syndromes and congenital defects. Approximately 70% of CHD cases have multifactorial etiologies and can be influenced by environmental factors (diabetes, obesity, medications) and genetic factors. This study aims to evaluate the types of CHD diagnosed in a hospital sample in Rio Grande do Sul. Also with a bioinformatics approach, we aim to identify and characterize candidate genes involved in cardiogenesis and metabolic pathways related to the development of CHD. We performed a descriptive analyses on 381 cases of CHD, divided into 235 cases of isolated CHD (iCHD) and 146 cases of associated CHD (aCHD), where the most prevalent CHD was Atrial Septal Defect (107 cases (33.2%) for iCHD and 68 (33.2%) for aCHD). Trisomy 21 was the most common syndrome in 33 cases (50.0%). For the second objective, we looked for differentially expressed genes involved in CHD development through bioinformatics pipelines. We analyzed experimental datasets available in genomic databases, using transcriptome, gene enrichment, and systems biology strategies. Network analysis based on genetic and phenotypic ontologies revealed that EP300, CALM3, and EGFR genes facilitate rapid information flow, while NOTCH1, TNNI3, and SMAD4 are significant mediators within the network. Differential gene expression (DGE) analysis identified 2,513 genes across three study types: 1) Tetralogy of Fallot (ToF); 2) Hypoplastic Left Heart Syndrome (HLHS); and 3) Trisomy 21/CHD, with LYVE1, PLA2G2A, and SDR42E1 genes found in three of the six studies. This study was submitted to the International Journal of Molecular Sciences.