In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Type 2 diabetes (T2D) and hypertension are global public health concerns and major metabolic disorders in humans. Experimental evidence indicates considerable hereditary influences on the etiology of T2D and hypertension, but the molecular basis of these diseases is still limited. Thus, the current study analyzed 185 (132 T2D and 53 hypertension) GWAS catalog datasets and identified 83 common genes linked to T2D and hypertension pathogenesis. These genes were further examined using various bioinformatics approaches to elucidate their molecular mechanisms underlying the pathophysiology of T2D and hypertension. Gene ontology (GO) analysis revealed the biological, cellular, and molecular functions of these genes, which were also linked to different T2D and hypertension pathways. Specifically, seven genes were found to be crucial for T2D, and nine were directly associated with hypertension. Protein-protein interaction (PPI) analysis identified 28 candidate genes and seven hub genes through 11 topological methods. Among 231 miRNAs, seven were significant in interacting with the hub genes, and nine transcription factors (TFs) out of 36 were linked to these hub genes. Additionally, two of the seven hub genes were downregulated by 43 FDA-approved drugs. These findings elucidate the molecular processes underlying T2D and hypertension, suggesting that targeting these genes could lead to future drug development and therapeutic strategies to treat T2D and hypertension.

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Journal
Heliyon
Published
2024-08-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e36546
Citations
1
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.23
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article

In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Md. Golam Rabby, Md Sakib Hasan, Md. Numan Islam, Md Suzauddula et al.
1 citations
Heliyon
Bioinformatics and Genomic Networks
0.23
article

In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Md. Golam Rabby, Md Sakib Hasan, Md. Numan Islam, Md Suzauddula, Mahbubur Alam Dewan
article en
1 citations

Abstract

Type 2 diabetes (T2D) and hypertension are global public health concerns and major metabolic disorders in humans. Experimental evidence indicates considerable hereditary influences on the etiology of T2D and hypertension, but the molecular basis of these diseases is still limited. Thus, the current study analyzed 185 (132 T2D and 53 hypertension) GWAS catalog datasets and identified 83 common genes linked to T2D and hypertension pathogenesis. These genes were further examined using various bioinformatics approaches to elucidate their molecular mechanisms underlying the pathophysiology of T2D and hypertension. Gene ontology (GO) analysis revealed the biological, cellular, and molecular functions of these genes, which were also linked to different T2D and hypertension pathways. Specifically, seven genes were found to be crucial for T2D, and nine were directly associated with hypertension. Protein-protein interaction (PPI) analysis identified 28 candidate genes and seven hub genes through 11 topological methods. Among 231 miRNAs, seven were significant in interacting with the hub genes, and nine transcription factors (TFs) out of 36 were linked to these hub genes. Additionally, two of the seven hub genes were downregulated by 43 FDA-approved drugs. These findings elucidate the molecular processes underlying T2D and hypertension, suggesting that targeting these genes could lead to future drug development and therapeutic strategies to treat T2D and hypertension.

HeliyonVol. 10(16)
University of Nebraska–Lincoln (US), National Chung Hsing University (TW)
Zero hunger
Openalex Percentile: Top 43%
Bioinformatics and Genomic Networks
0.23
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In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension — Md. Golam Rabby, Md Sakib Hasan, et al. · Heliyon (2024) | TGRS Research Map | TGRS