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Applying Proteomics and Integrative "Omics" Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis.
Tracz, Joanna; Luczak, Magdalena.
Afiliação
  • Tracz J; European Centre for Bioinformatics and Genomics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.
  • Luczak M; European Centre for Bioinformatics and Genomics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.
Int J Mol Sci ; 22(14)2021 Jul 13.
Article em En | MEDLINE | ID: mdl-34299112
ABSTRACT
Patients with chronic kidney disease (CKD) are at increased risk of atherosclerosis and premature mortality, mainly due to cardiovascular events. However, well-known risk factors, which promote "classical" atherosclerosis are alone insufficient to explain the high prevalence of atherosclerosis-related to CKD (CKD-A). The complexity of the molecular mechanisms underlying the acceleration of CKD-A is still to be defied. To obtain a holistic picture of these changes, comprehensive proteomic approaches have been developed including global protein profiling followed by functional bioinformatics analyses of dysregulated pathways. Furthermore, proteomics surveys in combination with other "omics" techniques, i.e., transcriptomics and metabolomics as well as physiological assays provide a solid ground for interpretation of observed phenomena in the context of disease pathology. This review discusses the comprehensive application of various "omics" approaches, with emphasis on proteomics, to tackle the molecular mechanisms underlying CKD-A progression. We summarize here the recent findings derived from global proteomic approaches and underline the potential of utilizing integrative systems biology, to gain a deeper insight into the pathogenesis of CKD-A and other disorders.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Genômica / Proteômica / Insuficiência Renal Crônica / Aterosclerose / Metabolômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Genômica / Proteômica / Insuficiência Renal Crônica / Aterosclerose / Metabolômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article