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Network-medicine approach for the identification of genetic association of parathyroid adenoma with cardiovascular disease and type-2 diabetes.
Imam, Nikhat; Alam, Aftab; Siddiqui, Mohd Faizan; Veg, Akhtar; Bay, Sadik; Khan, Md Jawed Ikbal; Ishrat, Romana.
Afiliação
  • Imam N; Institute of Computer Science and Information Technology, Department of Mathematics, Magadh University, Bodh Gaya, Bihar India.
  • Alam A; Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi India.
  • Siddiqui MF; Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi India.
  • Veg A; International Medical Faculty, Osh State University, Osh City, 723500, Kyrgyz Republic Kyrgyzstan.
  • Bay S; Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi India.
  • Khan MJI; Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University; Istanbul Türkiye.
  • Ishrat R; Institute of Computer Science and Information Technology, Department of Mathematics, Magadh University, Bodh Gaya, Bihar India.
Brief Funct Genomics ; 22(3): 250-262, 2023 05 18.
Article em En | MEDLINE | ID: mdl-36790356
ABSTRACT
Primary hyperparathyroidism is caused by solitary parathyroid adenomas (PTAs) in most cases (⁓85%), and it has been previously reported that PTAs are associated with cardiovascular disease (CVD) and type-2 diabetes (T2D). To understand the molecular basis of PTAs, we have investigated the genetic association amongst PTAs, CVD and T2D through an integrative network-based approach and observed a remarkable resemblance. The current study proposed to compare the PTAs-associated proteins with the overlapping proteins of CVD and T2D to determine the disease relationship. We constructed the protein-protein interaction network by integrating curated and experimentally validated interactions in humans. We found the $11$ highly clustered modules in the network, which contain a total of $13$ hub proteins (TP53, ESR1, EGFR, POTEF, MEN1, FLNA, CDKN2B, ACTB, CTNNB1, CAV1, MAPK1, G6PD and CCND1) that commonly co-exist in PTAs, CDV and T2D and reached to network's hierarchically modular organization. Additionally, we implemented a gene-set over-representation analysis over biological processes and pathways that helped to identify disease-associated pathways and prioritize target disease proteins. Moreover, we identified the respective drugs of these hub proteins. We built a bipartite network that helps decipher the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drug combinations or drug-repurposing approaches will improve the clinical conditions in comorbidity, enhance the potency of a few drugs and give a synergistic effect with better outcomes. This network-based analysis opens a new horizon for more personalized treatment and drug-repurposing opportunities to investigate new targets and multi-drug treatment and may be helpful in further analysis of the mechanisms underlying PTA and associated diseases.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias das Paratireoides / Doenças Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudo: Diagnostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias das Paratireoides / Doenças Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudo: Diagnostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article