Using association rule mining to jointly detect clinical features and differentially expressed genes related to chronic inflammatory diseases

Autor(es)

Veroneze, Rosana ; Cruz Tfaile Corbi, Samia ; Roque da Silva, Barbara ; de S. Rocha, Cristiane ; V. Maurer-Morelli, Claudia ; Perez Orrico, Silvana Regina ; Cirelli, Joni A. ; Von Zuben, Fernando J. ; Mantuaneli Scarel-Caminaga, Raquel

• Tipo de documento: Artigo Científico
• Fonte: PLoS One; v. 15, n. 10, p. 22-pg., 2020-10-02.

Resumo

Objective It is increasingly common to find patients affected by a combination of type 2 diabetes mellitus (T2DM), dyslipidemia (DLP) and periodontitis (PD), which are chronic inflammatory diseases. More studies able to capture unknown relationships among these diseases will contribute to raise biological and clinical evidence. The aim of this study was to apply association rule mining (ARM) to discover whether there are consistent patterns of clinical features (CFs) and differentially expressed genes (DEGs) relevant to these diseases. We intend to reinforce the evidence of the T2DM-DLP-PD-interplay and demonstrate the ARM ability to provide new insights into multivariate pattern discovery. Methods We utilized 29 clinical glycemic, lipid and periodontal parameters from 143 patients divided into five groups based upon diabetic, dyslipidemic and periodontal conditions (including a healthy-control group). At least 5 patients from each group were selected to assess the transcriptome by microarray. ARM was utilized to assess relevant association rules considering: (i) only CFs; and (ii) CFs+DEGs, such that the identified DEGs, specific to each group of patients, were submitted to gene expression validation by quantitative polymerase chain reaction (qPCR). Results We obtained 78 CF-rules and 161 CF+DEG-rules. Based on their clinical significance, Periodontists and Geneticist experts selected 11 CF-rules, and 5 CF+DEG-rules. From the five DEGs prospected by the rules, four of them were validated by qPCR as significantly different from the control group; and two of them validated the previous microarray findings. Conclusions ARM was a powerful data analysis technique to identify multivariate patterns involving clinical and molecular profiles of patients affected by specific pathological panels. ARM proved to be an effective mining approach to analyze gene expression with the advantage of including patient's CFs. A combination of CFs and DEGs might be employed in modeling the patient's chance to develop complex diseases, such as those studied here. (AU)

• Processo FAPESP: 16/25418-6 - Investigação da associação de haplótipo no gene IL8 com suscetibilidade à doença periodontal crônica e Diabetes Mellitus tipo 2
• Beneficiário: Bárbara Roque da Silva
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
• Processo FAPESP: 09/16233-9 - Avaliação do efeito da descompensação do Diabetes Mellitus sobre a expressão de genes do sistema imune e sobre lesões no DNA em pacientes com periodontite crônica.
• Beneficiário: Sâmia Cruz Tfaile Corbi
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 10/10882-2 - Expressão gênica em indivíduos portadores de Diabetes mellitus tipo 2, dislipidemia e doença periodontal: avaliação por microarray
• Beneficiário: Raquel Mantuaneli Scarel Caminaga
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/21174-8 - Algoritmos enumerativos para biclusterização: expandindo e explorando seu potencial em bioinformática e em neurociência
• Beneficiário: Rosana Veroneze
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 14/16148-0 - Investigação do transcriptoma e do proteoma salivar e plasmático em indivíduos acometidos por diabetes mellitus tipo 2, dislipidemia e doença periodontal crônica
• Beneficiário: Sâmia Cruz Tfaile Corbi
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 07/08362-8 - Avaliação da correlação entre peroxidação lipídica e o perfil de marcadores inflamatórios em pacientes portadores de diabetes mellitus tipo 2 com periodontite crônica
• Beneficiário: Silvana Regina Perez Orrico
• Modalidade de apoio: Auxílio à Pesquisa - Regular