Lovastatin regulates hypercholesterolemia and type II diabetes via BIRC2, LDLR, APOB, CASP3, CASP6, CASP9, XIAP and APAF1 genes:

A System Pharmacology approach

 

Suganya M¹, Usha Raja Nanthini¹, Smruti Sudha Nayak², Vino S², Sajitha Lulu S³*

¹Department of Biotechnology, Mother Teresa Women's University, Kodaikanal, Tamilnadu, India – 624101.

²Department of Bio-Sciences, School of Bio Sciences and Technology, Vellore Institute of Technology,

Vellore, Tamilnadu, India – 632014.

³Department of Biotechnology School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, India – 632014.

 

ABSTRACT:

Cardiovascular diseases are considered a major causative factor for the increasing rate of global mortality rate. Rendering to an approximation of the World Health Organization (WHO), 17.9 million people worldwide were affected by cardiovascular diseases. The behavioral risk factors such as tobacco use, unhealthy diet, obesity, physical inactivity, and harmful use of alcohol were found to play a significant role in the onset of cardiovascular diseases. Hypertension, diabetes, and hyperlipidemia are considered clinical factors associated with the prevalence of cardiovascular diseases. Among these clinical factors hyperlipidemia, which is characterized by increased levels of serum cholesterol, is highly related to the pathophysiological mechanism associated with cardiovascular diseases. Several medications are available for lowering abnormal serum cholesterol levels. Lovastatin, which belongs to the class of statins aids in lowering cholesterol levels by inhibiting hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, a significant enzyme required for cholesterol biosynthesis. Lovastatin is also involved in regulating the pathogenesis of type 2 diabetes. In this study, we explored the association between Lovastatin interacting genes in Hypercholesterolemia pathways with genes associated with Type 2 Diabetes mellitus by employing systems biology approach. Our studies identified the significance of key genes such as BIRC2, LDLR, APOB, CASP3, CASP6, CASP9, XIAP, and APAF1 in the regulation of hypercholesterolemia and type 2 diabetes.

 

 

 

 

INTRODUCTION: 

Cholesterol is considered one of the significant components of cell membranes and steroid hormones. A major part of the required cholesterol is being synthesized by the body and the remaining portion comes through diet. It is interactable in blood and generates lipoprotein complexes like high-density lipoproteins (HDL-C), low-density lipoproteins (LDL-C), very low-density lipoproteins (VLDL-C), and chylomicrons with proteins and phospholipids¹. LDL-C levels beyond a certain threshold have been linked to an increase in cardiovascular mortality with LDL reduction².

 

Lovastatin relates to the statins class of drugs and was the second agent identified in this class discovered by Alfred Alberts and his team at Merck in 1978^3–5, which inhibits the (3S)-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase⁶. It has been stated that the global prevalence of statin use has grown over time⁷. Studies are pointing out the side effects during the medication period that due to its lipophilic nature^8,9, it could penetrate extrahepatic cell membranes such as beta cells, adipocytes, and skeletal muscles¹⁰. Hence, it could have comorbidities like myopathy, systemic inflammation, hemorrhagic stroke, cognitive decline, peripheral neuropathy, diabetes, insomnia, tendinitis, arthralgia, arthritis, and cataract¹¹. Moreover, there are few recent studies discussing the significant increases in the risk of diabetes-related to statin therapy¹², even though the defined mechanism for statin-induced diabetes remains unclear¹³.

 

Inhibiting theformation of ubiquinone (CoQ 10) synthesis leads to mitochondrial oxidative stress and β cell apoptosis^14–16. Hence, statins activate inflammasome NLRP3 from adipocytes in the presence of endotoxins leading to interleukin-1β-mediated insulin resistance¹⁷. Statin also results in reducing the expression of GLUT4 in adipocytes causing impaired glucose tolerance associated with type 2 diabetes¹⁸.

 

In this study, we use a network-based system biology approach to understand the cross-talk between Lovastatin interacting genes¹⁹ in Hypercholesterolemia pathways with genes associated with Type 2 Diabetes mellitus. We have extracted almost all the lovastatin interacting genes in Hypercholesterolemia related pathways using database searches and an extensive literature survey. We have also predicted the connection with additional genes, proteins, transcription factors, pathways, and associated diseasesrelated to diabetes. Thus this analysis provides a deeper understanding of the interconnecting cross-talks between molecules in Hypercholesteraemic and Type 2 diabetes pathways.

 

MATERIALS AND METHODS:

Retrieval of target genes:

Retrieval of target genes interacting with lovastatin was accomplished by performing an extensive literature search as well as database exploration. Databases such as STITCH, Binding Database as well as Drug Bank were explored for the identification of target genes. STITCH database incorporates significant information about interactions from metabolic pathways, crystal structures, binding experiments, and drug target relationships²⁰ while Binding Database consists of experimentally derived binding affinities of protein-ligand complexes extracted from scientific literature²¹. Drugbank is a publicly accessible database possessing 13,570 drug records including 2629 approved small molecule drugs, 1377 permitted biologics, 131 nutraceuticals, and 6373 experimental drugs (www.drugbank.ca).

 

Prediction of Interacting Partners (IPs):

The interacting partners associated with the target genes were identified from the STRING database. The STRING database predicts protein-protein interactions as well as functional associations based on systematic co-expression analysis, and the discovery of common selective signals across genomes, including automated text mining of scientific literature²². The IPs for target genes were predicted by fixing a Tanimoto coefficient > 0.9.

 

Network construction:

The protein (target gene) - protein (IP) interactions were visualized by constructing a network using Cytoscape (v3.3.0) (www.cytoscape.org) which is a computational software for analyzing complex associations between biomolecules. In a protein-protein interaction network, the target genes and IPs are denoted as nodes while interactions between nodes represent edges. To elucidate the significance of nodes and their respective edges we calculated network topology parameters such as degree, Betweenness centrality, Closeness, MCC, MCODE using the cyto Hubba plugin of Cytoscape software. The calculation of network topology parameters results in the prediction of closely associated genes (hub genes).

 

Gene enrichment analysis:

Functional enrichment analysis of the reported hub genes from the network was performed by extracting information from the Kyoto Encyclopaedia of Genes and Genomes (KEGG), which is a database that aids in the comprehensive understanding of biological functions by integrating molecular-level information. KEGG provides detailed information regarding molecular functions, biological functions, and localization of the hub genes²³.

 

Regulatory network construction:

The construction of regulatory networks requires information regarding transcription factors associated with key genes (hub genes). Hence, transcription factors associated with hub genes were identified using the iRegulon plugin of Cytoscape software, which aids in the identification of regulons using motif and track discovery in a set of co-regulated genes.

 

RESULTS:

Target fishing and functional Interacting Partners (IPs) prediction:

An extensive literature survey, as well as database exploration, aided us in the identification of 19 target genes for lovastatin. The target genes identified were obtained by conducting the literature survey and from various databases such as STITCH, Binding Database as well as drug bank. The functional IPs for each target gene were predicted using the STRING database by fixing the Tanimoto coefficient as 0.9 and by the literature survey. A total of 84 genes were predicted as Interacting partners and with a crucial role in Hypercholesterolemia and related pathways.

 

Network analysis of gene protein interactions:

Gene protein interactions for identified target genes and IPs related to Lovastatin were constructed using Cytoscape (v3.3.0) software. The lovastatin-target genes network (26 nodes, 25 edges) was also constructed using Cytoscape. The molecular functions of genes interacting with lovastatin are provided in Table 1. Lovastatin. Subnetworks for target gene – IP networks were delineated by analyzing network topological parameters such as degree, betweenness centrality, closeness, MCC, and MCODE using the Cytohubba plugin of Cytoscape software. The comprehensive analysis of subnetworks revealed 8 genes called Hub genes with the highest scores for thetopological parameters of interest. The hub genes are provided in Figure 1. These highly connected genes were Baculoviral IAP repeat-containing protein 2 (BIRC2), Low-density lipoprotein receptor (LDLR), Apolipoprotein B-100 (APOB), Caspase-3 (CASP3), Caspase-6 (CASP6), Caspase-9 (CASP9), E3 ubiquitin-protein ligase XIAP (XIAP) and Apoptotic protease-activating factor 1 (APAF1). The target gene-disease network (95 nodes, 87 edges) is provided in Figure 2. Out of 69 diseases identified, 14 were related to hypercholesterolemia and 4 were related to type 2 diabetes.

 

Table I: Illustrates details regarding genes interacting with lovastatin

Sl. No	Lovastatin interacting genes	gene name	Molecular functions	Reference
I	APOB	Apolipoprotein B	Carriescholesteroland triglycerides from the liver and gut to utilization and storage sites.	24
II	LDLR	Low density lipoprotein receptor	Cholesterol transport	25
III	APOE	Apolipoprotein E	regulate plasma cholesterol homeostasis	26
IV	WWOX	WW domain containing oxidoreductase	plays a role in apoptosis	27
V	ABCA1	ATP binding cassette subfamily A member	Efflux of intracellular cholesterol to apolipoproteins	28
VI	APOA1	Apolipoprotein A1	Transport of cholesterol from tissues	29
VII	APOE	Apolipoprotein	Lipid transport between organs via the plasma and interstitial fluids	30
VIII	APP	Amyloid-beta precursor protein	Neurite growth, neuronal adhesion, and axonogenesis	31
IX	MAPK1	Mitogen-activated protein kinase 1	Cell growth, adhesion, survival and differentiation	32
X	CASP3	Caspase 3	Apoptosis execution	33
XI	CASP9	Caspase 9	Apoptosis execution	34
XII	KRAS	Kirsten rat sarcoma viral oncogene	Cell proliferation	35
XIII	NRAS	NeuroblastomaRAS viral oncogene	Intrinsic GTPase activity	36
XIV	HMGCR	3-hydroxy-3-methylglutaryl-coenzyme A reductase	Cholesterol biosynthesis	37
XV	LMNA	Lamin A	Nuclear assembly, chromatin organization, nuclear membrane and telomere dynamics	38
XVI	LDLRAP1	LowDensity Lipoprotein ReceptorAdaptor Protein 1	endocytosis of the LDL receptor	39
XVII	RAF1	Rapidly Accelerated Fibrosarcoma proto oncogene	Proliferation, differentiation, apoptosis, survival, and oncogenic transformation	40
XVIII	FZD4	Frizzled class Receptor 4	Receptor for Wnt proteins	41
XIX	TMPO	Thymopoietin	Structural organization of the nucleus	42

 

 

Figure 1: Hub genes in green color (green color indicates hub genes and red color indicates targets and interacting partners)

 

Figure 2: Target gene-disease network. (The target genes related to hypercholesterolemia and diabetes are represented in yellow color)

 

Gene enrichment analysis:

Gene enrichment analysis on hub genes revealed the biological functions as well as cytosolic locations of hub genes. BIRC2 gene located in the cytoplasm encodes a protein responsible for modulating inflammatory signaling and immunity, mitogenic kinase signaling, cell proliferation, cell invasion, and metastasis⁴³. The LDLR gene family consists of cell surface proteins that play a role in receptor-mediated endocytosis of specific ligands. Low-density lipoprotein (LDL) is generallycoupled at the cell membrane and carried into the cell, eventually ending up in lysosomes where the protein is degraded and the cholesterol is made accessible for suppression of microsomal enzymes. And 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase, is the rate-limiting step in cholesterol synthesis⁴⁴. Apolipoprotein B is an apolipoprotein of chylomicrons and low-density lipoproteins (LDL) responsible for the cellular binding and internalization of LDL particles by the apoB/E receptor⁴⁵. Caspase family proteins are encoded by the cysteine-aspartic gene encodes a protein that regulates the modulation of inflammatory signaling and immunity, copper homeostasis, mitogenic kinase signaling, cell proliferation, as well as cell invasion and metastasis⁴⁶. APAF1 gene encodes a cytoplasmic protein responsible for the initiation of apoptosis.

 

Regulatory network construction:

The transcription factors regulating hub genes were predicted using the iRegulon plugin of Cytoscape software. FOXO1 was identified as a significant transcription factor regulating the BIRC2 hub gene, which plays a significant role in the progression of insulin resistance and type2 diabetes⁴⁷. The regulatory network depicting the FOXO transcription factor regulating hub genes is represented in Figure 3. The depiction of the mechanism of the FOXO transcription factor along with the hub genes in regulating hypercholesterolemia and type 2 diabetes is given in Figure 4. The hub genes identified by analyzing network topology features were mapped to a type 2 diabetes pathway. Hub genes such as BIRC2, LDLR, APOB, CASP3, CASP6, CASP9, XIAP, and APAF1 were discovered to have a significant role in the development and progression of type 2 diabetes. Out of 8 hub genes identified, the expression of BIRC2 and XIAP inhibits the onset of the disease while the expression of LDLR, APOB, CASP3, CASP6, CASP9, and APAF1 activates the type 2 diabetes pathway and contributes to the onset of disease. The cross talks between hub genes identified and transcription factors like regulating these hub genes like FOXO1 for lovastatin with hypercholesteremia and type 2 diabetes are depicted in Figure 5.

 

Figure 3: FOXO1 interacting with major hub genes constructed using iRegulon of Cytoscape  (Purple color indicates Target genes

 

Figure 4: Establishing the mode of action of FOXO1 transcription factor

 

Figure 5: Involvement of identified hub genes and their transcription factors regulating hypercholesterolemia and type 2 diabetes.

 

DISCUSSION AND CONCLUSION:

We have explored the role of identified hub genes in the pathogenesis of insulin resistance and type 2 diabetes. BIRC2 regulates type 2 diabetes by making functional associations with NF-Kappa-B inhibitor alpha (IKBα). The nuclear factor NF-Kappa-B (NFKB) releases pro-inflammatory cytokines in the nucleus leading to the onset of Type 2 Diabetes. IKBα inhibits NF-Kβ by masking nuclear localization signals of NFKB proteins and keeping them in an inactive state. The protein encoded by BIRC2 interacts with IKBα via its ring domain for triggering proteasomal degradation through ubiquitin editing preventing the entry of NFKB into the nucleus⁴⁸. The protein encoded by XIAP also inhibits NFKB activation. The proteins encoded by LDLR and APOB are related to hypercholesteremia⁴⁹. The accumulation of lipids directs to the elevated production of Reactive Oxygen Species (ROS) leading to the prevalence of oxidative stress responsible for the B cell dysfunction and insulin resistance. The proteins encoded by the caspase family are responsible for insulin resistance which leads to hyperglycemia. The enhanced production of ROS triggers the upregulated activity of caspase proteins which leads to the loss of B cell mass⁵⁰.

 

The FOXO1 transcription factor was identified as a key regulator of BIRC2 protein. The FOXO1 transcription factor, abundant in pancreatic cells is responsible for the onset of type 2 diabetes⁵¹. The enhanced oxidative stress triggers dysregulation of FOXO1 leading to the release of proinflammatory cytokines and the onset of type 2 diabetes. Hence, the lovastatin-mediated regulation of type 2 diabetes is explained by its interaction with the FOXO1 transcription factor and BIRC2 protein. Similarly, the hub genes APOB, as well as LDLR involved in hypercholesterolemia are related to pancreatic beta-cell dysfunction and the onset of type 2 diabetes via interacting with the FOXO1 transcription factor.

 

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

 

ACKNOWLEDGMENTS:

The authors are grateful to the management of the Vellore Institute of Technology for providing the facilities to carry out this research investigation.

 

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Accepted on 30.01.2023          © RJPT All right reserved

Research J. Pharm. and Tech 2023; 16(9):4058-4064.