Mobeen Ahmed, Joshi Sweta, Fatima Firdaus, Bhargav Anasuya, Arif Yusra, Faruq Mohammed, Ramachandran Srinivasan
CSIR Institute of Genomics & Integrative Biology, Sukhdev Vihar, New Delhi, 110025 India.
Department of Food Technology, SIST, Jamia Hamdard, New Delhi, 110062 India.
3 Biotech. 2025 Feb;15(2):47. doi: 10.1007/s13205-024-04202-4. Epub 2025 Jan 20.
Insulin resistance is major factor in the development of metabolic syndrome and type 2 diabetes (T2D). We extracted 430 genes from literature associated with both insulin resistance and inflammation. The highly significant pathways were Toll-like receptor signaling, PI3K-Akt signaling, cytokine-cytokine receptor interaction, pathways in cancer, TNF signaling, and NF-kappa B signaling. Among the 297 common genes in all datasets of various T2D patients' tissues including blood, muscle, liver, pancreas, and adipose tissues, 71% and 60% of these genes were differentially expressed in pancreas (GSE25724) and liver (GSE15653), respectively. A total of 169 genes contain highly conserved motifs for various transcription factors involved in immune response, thereby suggesting coordinated expression. Through co-expression analysis, we obtained three modules. The respective modules had 78, 158, and 55 genes, and , , and as hub genes. Further, we used the BioNSi pathways simulation tool and identified the following five KEGG pathways perturbed in four or more tissues, namely Toll-like receptor signaling pathway, RIG-1-like receptor signaling pathway, pathways in cancer, NF-kappa B signaling pathway, and insulin resistance pathway. The genes and are common to all these five pathways. In addition, using the NF-κB computational activation model, we identified that the reversal of NF-κB constitutive activation through overexpression of NFKB1 (P50 homodimer), PPARG, PIAS3 could reduce insulin resistance by almost half of its original value. To conclude, co-expression studies, gene expression network simulation, and NF-κB computational modeling substantiate the causal role of NF-κB pathway in insulin resistance. These results taken together with other published evidence suggests that the TNF-TRAF2-IKBKB-NF-κB axis could be explored as a potential target in combination with available metabolic targets in the management of insulin resistance.
The online version contains supplementary material available at 10.1007/s13205-024-04202-4.
胰岛素抵抗是代谢综合征和2型糖尿病(T2D)发展的主要因素。我们从与胰岛素抵抗和炎症相关的文献中提取了430个基因。高度显著的通路有Toll样受体信号通路、PI3K - Akt信号通路、细胞因子 - 细胞因子受体相互作用、癌症通路、TNF信号通路和NF - κB信号通路。在包括血液、肌肉、肝脏、胰腺和脂肪组织在内的各种T2D患者组织的所有数据集中的297个共同基因中,这些基因分别有71%和60%在胰腺(GSE25724)和肝脏(GSE15653)中差异表达。共有169个基因包含参与免疫反应的各种转录因子的高度保守基序,从而表明存在协同表达。通过共表达分析,我们获得了三个模块。各个模块分别有78、158和55个基因,并且 、 和 作为枢纽基因。此外,我们使用BioNSi通路模拟工具,确定了在四个或更多组织中受到干扰的以下五条KEGG通路,即Toll样受体信号通路、RIG - 1样受体信号通路、癌症通路、NF - κB信号通路和胰岛素抵抗通路。基因 和 在所有这五条通路中都存在。此外,使用NF - κB计算激活模型,我们确定通过过表达NFKB1(P50同二聚体)、PPARG、PIAS3来逆转NF - κB组成性激活可将胰岛素抵抗降低近一半。总之,共表达研究、基因表达网络模拟和NF - κB计算建模证实了NF - κB通路在胰岛素抵抗中的因果作用。这些结果与其他已发表的证据一起表明,TNF - TRAF2 - IKBKB - NF - κB轴可作为与可用代谢靶点联合治疗胰岛素抵抗的潜在靶点进行探索。
在线版本包含可在10.1007/s13205 - 024 - 04202 - 4获取的补充材料。