Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein-protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug-disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors.

BACKGROUND: Dengue fever can progress to dengue hemorrhagic fever (DHF), a more serious and occasionally fatal form of the disease. Indicators of serious disease arise about the time the fever begins to reduce (typically 3 to 7 days following symptom onset). There are currently no effective antivirals available. Drug repurposing is an emerging drug discovery process for rapidly developing effective DHF therapies. Through network pharmacology modeling, several US Food and Drug Administration (FDA)-approved medications have already been researched for various viral outbreaks.
OBJECTIVE: We aimed to identify potentially repurposable drugs for DHF among existing FDA-approved drugs for viral attacks, symptoms of viral fevers, and DHF.
METHODS: Using target identification databases (GeneCards and DrugBank), we identified human-DHF virus interacting genes and drug targets against these genes. We determined hub genes and potential drugs with a network-based analysis. We performed functional enrichment and network analyses to identify pathways, protein-protein interactions, tissues where the gene expression was high, and disease-gene associations.
RESULTS: Analyzing virus-host interactions and therapeutic targets in the human genome network revealed 45 repurposable medicines. Hub network analysis of host-virus-drug associations suggested that aspirin, captopril, and rilonacept might efficiently treat DHF. Gene enrichment analysis supported these findings. According to a Mayo Clinic report, using aspirin in the treatment of dengue fever may increase the risk of bleeding complications, but several studies from around the world suggest that thrombosis is associated with DHF. The human interactome contains the genes prostaglandin-endoperoxide synthase 2 (PTGS2), angiotensin converting enzyme (ACE), and coagulation factor II, thrombin (F2), which have been documented to have a role in the pathogenesis of disease progression in DHF, and our analysis of most of the drugs targeting these genes showed that the hub gene module (human-virus-drug) was highly enriched in tissues associated with the immune system (P=7.29 × 10-24) and human umbilical vein endothelial cells (P=1.83 × 10-20); this group of tissues acts as an anticoagulant barrier between the vessel walls and blood. Kegg analysis showed an association with genes linked to cancer (P=1.13 × 10-14) and the advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications (P=3.52 × 10-14), which indicates that DHF patients with diabetes and cancer are at risk of higher pathogenicity. Thus, gene-targeting medications may play a significant part in limiting or worsening the condition of DHF patients.
CONCLUSIONS: Aspirin is not usually prescribed for dengue fever because of bleeding complications, but it has been reported that using aspirin in lower doses is beneficial in the management of diseases with thrombosis. Drug repurposing is an emerging field in which clinical validation and dosage identification are required before the drug is prescribed. Further retrospective and collaborative international trials are essential for understanding the pathogenesis of this condition.

The liver harbors a diverse array of immune cells during both health and disease. The specific roles of these cells in nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC) remain unclear. Using a systems immunology approach, we demonstrate that reciprocal cell-cell communications function through dominant-subdominant pattern of ligand-receptor homeostatic pathways. In the healthy control, hepatocyte-dominated homeostatic pathways induce local immune responses to maintain liver homeostasis. Chronic intake of a Western diet (WD) alters hepatocytes and induces hepatic stellate cell (HSC), cancer cell and NKT cell-dominated interactions during NAFLD. During HCC, monocytes, hepatocytes, and myofibroblasts join the dominant cellular interactions network to restore liver homeostasis. Dietary correction during NAFLD results in nonlinear outcomes with various cellular rearrangements. When cancer cells and stromal cells dominate hepatic interactions network without inducing homeostatic immune responses, HCC progression occurs. Conversely, myofibroblast and fibroblast-dominated network orchestrates monocyte-dominated HCC-preventive immune responses. Tumor immune surveillance by 75% of immune cells successfully promoting liver homeostasis can create a tumor-inhibitory microenvironment, while only 5% of immune cells manifest apoptosis-inducing functions, primarily for facilitating homeostatic liver cell turnover rather than direct tumor killing. These data suggest that an effective immunotherapy should promote liver homeostasis rather than direct tumor killing.

BACKGROUND: Liver and heart are two important organs in the human body, whose function strongly affects other organs. On the other hand, these two main organs affect each other due to common metabolic pathways. Therefore, a disorder in any of them can lead to disease in other organs. Today, using the network medicine perspective, these complex connections can be easily mapped and discovered. From the Persian medicine viewpoint, links are formed based on the material causes of diseases, while from the conventional medicine viewpoint, they are mostly formed due to metabolites, genes, and pathways.
METHODS: In this article, we first investigated the recent articles of conventional medicine that examine the relationship between heart and liver in the important databases. Then, we checked out the sources of Persian medicine and finally, using the RStudio software used in network medicine for text mining, we drew the communication network centered on heart and liver and their mutual causes from the perspective of Persian Medicine.
RESULTS: Examining the network connection between the heart and the liver showed that the definitions based on Persian medicine, which are based on the material causes of diseases, are very compatible with the genes, metabolites and pathways between these two organs.
CONCLUSIONS: Understanding these concepts can be helpful in detecting the co-occurrence of diseases of these two organs, as well as predicting the possible occurrence of related diseases between the heart and liver, and ultimately in better treatment.

Alcoholic liver disease (ALD) is characterized by high morbidity and mortality, and mainly results from prolonged and excessive alcohol use. Amomum villosum Lour. (A. villosum), a well-known traditional Chinese medicine (TCM), has hepatoprotective properties. However, its ability to combat alcohol-induced liver injury has not been fully explored. The objective of this study was to investigate the hepatoprotective effects of A. villosum in a rat model of alcohol-induced liver disease, thereby establishing a scientific foundation for the potential preventive use of A. villosum in ALD. We established a Chinese liquor (Baijiu)-induced liver injury model in rats. Hematoxylin and eosin (HE) staining, in combination with biochemical tests, was used to evaluate the protective effects of A. villosum on the liver. The integration of network medicine analysis with experimental validation was used to explore the hepatoprotective effects and potential mechanisms of A. villosum in rats. Our findings showed that A. villosum ameliorated alcohol-induced changes in body weight, liver index, hepatic steatosis, inflammation, blood lipid metabolism, and liver function in rats. Network proximity analysis was employed to identify 18 potentially active ingredients of A. villosum for ALD treatment. These potentially active ingredients in the blood were further identified using mass spectrometry (MS). Our results showed that A. villosum plays a hepatoprotective role by modulating the protein levels of estrogen receptor 1 (ESR1), anti-nuclear receptor subfamily 3 group C member 1 (NR3C1), interleukin 6 (IL-6), and tumor necrosis factor-α (TNF-α). In conclusion, the results of the current study suggested that A. villosum potentially exerts hepatoprotective effects on ALD in rats, possibly through regulating the protein levels of ESR1, NR3C1, IL-6, and TNF-α.

BACKGROUND: Drunkenness and alcoholic liver disease (ALD) are critical public health issues associated with significant morbidity and mortality due to chronic overconsumption of alcohol. Traditional remedies, such as bear bile powder, have been historically acclaimed for their hepatoprotective properties. This study assessed the efficacy of a biotransformed bear bile powder known as golden bile powder (GBP) in alleviating alcohol-induced drunkenness and ALD.
METHODS: A murine model was engineered to simulate alcohol drunkenness and acute hepatic injury through the administration of a 50% ethanol solution. Intervention with GBP and its effects on alcohol-related symptoms were scrutinized, by employing an integrative approach that encompasses serum metabolomics, network medicine, and gut microbiota profiling to elucidate the protective mechanisms of GBP.
RESULTS: GBP administration significantly delayed the onset of drunkenness and decreased the duration of ethanol-induced inebriation in mice. Enhanced liver cell recovery was indicated by increased hepatic aldehyde dehydrogenase levels and superoxide dismutase activity, along with significant decreases in the serum alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, triglyceride, and total cholesterol levels (P < 0.05). These biochemical alterations suggest diminished hepatic damage and enhanced lipid homeostasis. Microbiota analysis via 16S rDNA sequencing revealed significant changes in gut microbial diversity and composition following alcohol exposure, and these changes were effectively reversed by GBP treatment. Metabolomic analyses demonstrated that GBP normalized the alcohol-induced perturbations in phospholipids, fatty acids, and bile acids. Correlation assessments linked distinct microbial genera to serum bile acid profiles, indicating that the protective efficacy of GBP may be attributable to modulatory effects on metabolism and the gut microbiota composition. Network medicine insights suggest the prominence of two active agents in GBP as critical for addressing drunkenness and ALD.
CONCLUSIONS: GBP is a potent intervention for alcohol-induced pathology and offers hepatoprotective benefits, at least in part, through the modulation of the gut microbiota and related metabolic cascades.

BACKGROUND: The ability to identify early epigenetic signatures underlying the inheritance of cardiovascular risk, including trans- and intergenerational effects, may help to stratify people before cardiac symptoms occur.
METHODS: Prospective and retrospective cohorts and case-control studies focusing on DNA methylation and maternal/paternal effects were searched in Pubmed from 1997 to 2023 by using the following keywords: DNA methylation, genomic imprinting, and network analysis in combination with transgenerational/intergenerational effects.
RESULTS: Maternal and paternal exposures to traditional cardiovascular risk factors during critical temporal windows, including the preconceptional period or early pregnancy, may perturb the plasticity of the epigenome (mainly DNA methylation) of the developing fetus especially at imprinted loci, such as the insulin-like growth factor type 2 (IGF2) gene. Thus, the epigenome is akin to a \"molecular archive\" able to memorize parental environmental insults and predispose an individual to cardiovascular diseases onset in later life. Direct evidence for human transgenerational epigenetic inheritance (at least three generations) of cardiovascular risk is lacking but it is supported by epidemiological studies. Several blood-based association studies showed potential intergenerational epigenetic effects (single-generation studies) which may mediate the transmittance of cardiovascular risk from parents to offspring.
CONCLUSIONS: In this narrative review, we discuss some relevant examples of trans- and intergenerational epigenetic associations with cardiovascular risk. In our perspective, we propose three network-oriented approaches which may help to clarify the unsolved issues regarding transgenerational epigenetic inheritance of cardiovascular risk and provide potential early biomarkers for primary prevention.

The conventional method of one drug being used for one target has not yielded therapeutic solutions for Lewy body dementia (LBD), which is a leading progressive neurological disorder characterized by significant loss of neurons. The age-related disease is marked by memory loss, hallucinations, sleep disorder, mental health deterioration, palsy, and cognitive impairment, all of which have no known effective cure. The present study deploys a network medicine pipeline to repurpose drugs having considerable effect on the genes and proteins related to the diseases of interest. We utilized the novel SAveRUNNER algorithm to quantify the proximity of all drugs obtained from DrugBank with the disease associated gene dataset obtained from Phenopedia and targets in the human interactome. We found that most of the 154 FDA-approved drugs predicted by SAveRUNNER were used to treat nervous system disorders, but some off-label drugs like quinapril and selegiline were interestingly used to treat hypertension and Parkinson\'s disease (PD), respectively. Additionally, we performed gene set enrichment analysis using Connectivity Map (CMap) and pathway enrichment analysis using EnrichR to validate the efficacy of the drug candidates obtained from the pipeline approach. The investigation enabled us to identify the significant role of the synaptic vesicle pathway in our disease and accordingly finalize 8 suitable antidepressant drugs from the 154 drugs initially predicted by SAveRUNNER. These potential anti-LBD drugs are either selective or non-selective inhibitors of serotonin, dopamine, and norepinephrine transporters. The validated selective serotonin and norepinephrine inhibitors like milnacipran, protriptyline, and venlafaxine are predicted to manage LBD along with the affecting symptomatic issues.

UNASSIGNED: The increasing knowledge about multiple sclerosis (MS) pathophysiology has reinforced the need for an improved description of disease phenotypes, connected to disease biology. Growing evidence indicates that complex diseases constitute phenotypical and genetic continuums with \"simple,\" monogenic disorders, suggesting shared pathomechanisms.
UNASSIGNED: The objective of this study was to depict a novel MS phenotypical framework leveraging shared physiopathology with Mendelian diseases and to identify phenotype-specific candidate drugs.
UNASSIGNED: We performed an enrichment testing of MS-associated variants with Mendelian disorders genes. We defined a \"MS-Mendelian network,\" further analyzed to define enriched phenotypic subnetworks and biological processes. Finally, a network-based drug screening was implemented.
UNASSIGNED: Starting from 617 MS-associated loci, we showed a significant enrichment of monogenic diseases (p < 0.001). We defined an MS-Mendelian molecular network based on 331 genes and 486 related disorders, enriched in four phenotypic classes: neurologic, immunologic, metabolic, and visual. We prioritized a total of 503 drugs, of which 27 molecules active in 3/4 phenotypical subnetworks and 140 in subnetwork pairs.
UNASSIGNED: The genetic architecture of MS contains the seeds of pathobiological multiplicities shared with immune, neurologic, metabolic and visual monogenic disorders. This result may inform future classifications of MS endophenotypes and support the development of new therapies in both MS and rare diseases.

BACKGROUND: It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation.
METHODS: The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.
RESULTS: The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.
CONCLUSIONS: The implemented workflow could be used for other multifactorial diseases.