Literature-based discovery of diabetes- and ROS-related targets

Reactive oxygen species in biological systems: Pathways, associated diseases, and potential inhibitors-A review

Reactive oxygen species (ROS) are produced under normal physiological conditions and may have beneficial and harmful effects on biological systems. ROS are involved in many physiological processes such as differentiation, proliferation, necrosis, autophagy, and apoptosis by acting as signaling molecules or regulators of transcription factors. In this case, maintaining proper cellular ROS levels is known as redox homeostasis. Oxidative stress occurs because of the imbalance between the production of ROS and antioxidant defenses. Sources of ROS include the mitochondria, auto-oxidation of glucose, and enzymatic pathways such as nicotinamide adenine dinucleotide phosphate reduced (NAD[P]H) oxidase. The possible ROS pathways are NF-κB, MAPKs, PI3K-Akt, and the Keap1-Nrf2-ARE signaling pathway. This review covers the literature pertaining to the possible ROS pathways and strategies to inhibit them. Additionally, this review summarizes the literature related to finding ROS inhibitors.

Graph embedding-based link prediction for literature-based discovery in Alzheimer's Disease

OBJECTIVE

We explore the framing of literature-based discovery (LBD) as link prediction and graph embedding learning, with Alzheimer's Disease (AD) as our focus disease context. The key link prediction setting of prediction window length is specifically examined in the context of a time-sliced evaluation methodology.

METHODS

We propose a four-stage approach to explore literature-based discovery for Alzheimer's Disease, creating and analyzing a knowledge graph tailored to the AD context, and predicting and evaluating new knowledge based on time-sliced link prediction. The first stage is to collect an AD-specific corpus. The second stage involves constructing an AD knowledge graph with identified AD-specific concepts and relations from the corpus. In the third stage, 20 pairs of training and testing datasets are constructed with the time-slicing methodology. Finally, we infer new knowledge with graph embedding-based link prediction methods. We compare different link prediction methods in this context. The impact of limiting prediction evaluation of LBD models in the context of short-term and longer-term knowledge evolution for Alzheimer's Disease is assessed.

RESULTS

We constructed an AD corpus of over 16 k papers published in 1977-2021, and automatically annotated it with concepts and relations covering 11 AD-specific semantic entity types. The knowledge graph of Alzheimer's Disease derived from this resource consisted of ∼11 k nodes and ∼394 k edges, among which 34% were genotype-phenotype relationships, 57% were genotype-genotype relationships, and 9% were phenotype-phenotype relationships. A Structural Deep Network Embedding (SDNE) model consistently showed the best performance in terms of returning the most confident set of link predictions as time progresses over 20 years. A huge improvement in model performance was observed when changing the link prediction evaluation setting to consider a more distant future, reflecting the time required for knowledge accumulation.

CONCLUSION

Neural network graph-embedding link prediction methods show promise for the literature-based discovery context, although the prediction setting is extremely challenging, with graph densities of less than 1%. Varying prediction window length on the time-sliced evaluation methodology leads to hugely different results and interpretations of LBD studies. Our approach can be generalized to enable knowledge discovery for other diseases.

AVAILABILITY

Code, AD ontology, and data are available at https://github.com/READ-BioMed/readbiomed-lbd.

Metformin: A Potential Candidate for Targeting Aging Mechanisms

Aging is a universal phenomenon in all biological organisms, defined by the loss of reproductive capacity and a progressive decline in fitness. In humans, aging is further associated with an increased incidence of disease conditions. The current aging population has become a primary public burden of the 21^st century. Therefore, to delay the aging process and maintain fitness in the aging population, the discovery of novel anti-aging drugs remains an urgent need. In recent years, metformin, a widely used hypoglycemic drug, has attracted growing attention in the field of anti-aging research. Reportedly, numerous studies have indicated that metformin regulates aging-related pathways, possibly delaying the aging process by modulating these pathways. The elucidation of these anti-aging effects may provide insights into the age-retarding potential of metformin. The present review focuses on the predominant molecular mechanisms associated with aging, as well as the anti-aging effects of metformin.

Pancreatic cancer cell apoptosis is induced by a proteoglycan extracted from Ganoderma lucidum

The Traditional Chinese Medicine, Ganoderma lucidum, has been widely used for its immunity-related and anti-cancer effects. Fudan-Yueyang-Ganoderma lucidum (FYGL) is a proteoglycan, extracted from Ganoderma lucidum, that has shown safe anti-diabetic activity in vivo. The present study demonstrated that FYGL could selectively inhibit the viability of PANC-1 and BxPC-3 pancreatic cancer cells in a dose dependent manner, but not in Mia PaCa-2 pancreatic cancer cells and HepG2 liver cancer cells. In addition, FYGL could inhibit migration and colony formation, and promote apoptosis in PANC-1 cells, but not in Mia PaCa-2 cells. Further investigation into the underlying mechanism revealed that FYGL could inhibit the expression level of the Bcl-2 protein in PANC-1 cells, but not in Mia PaCa-2 cells, leading to an increase in reactive oxygen species (ROS) and a reduction in the mitochondrial membrane potential and cell apoptosis. The increased ROS also promoted the formation of autophagosomes, along with an increase in the microtubule-associated protein light chain 3 II/I ratio. However, FYGL halted autophagy by preventing the autophagosomes from entering the lysosomes. The inhibition of autophagy increased the accumulation of defective mitochondria, as well as the production of ROS. Taken together, the processes of ROS regulation and autophagy inhibition promoted apoptosis of PANC-1 cells through the caspase-3/cleaved caspase-3 cascade. These results indicated that FYGL could be potentially used as an anti-cancer agent in the treatment of pancreatic cancer.

The Role of Reactive Oxygen Species in Acute Myeloid Leukaemia

Acute myeloid leukaemia (AML) is an aggressive haematological malignancy with a poor overall survival. Reactive oxygen species (ROS) have been shown to be elevated in a wide range of cancers including AML. Whilst previously thought to be mere by-products of cellular metabolism, it is now clear that ROS modulate the function of signalling proteins through oxidation of critical cysteine residues. In this way, ROS have been shown to regulate normal haematopoiesis as well as promote leukaemogenesis in AML. In addition, ROS promote genomic instability by damaging DNA, which promotes chemotherapy resistance. The source of ROS in AML appears to be derived from members of the “NOX family” of NADPH oxidases. Most studies link NOX-derived ROS to activating mutations in the Fms-like tyrosine kinase 3 (FLT3) and Ras-related C3 botulinum toxin substrate (Ras). Targeting ROS through either ROS induction or ROS inhibition provides a novel therapeutic target in AML. In this review, we summarise the role of ROS in normal haematopoiesis and in AML. We also explore the current treatments that modulate ROS levels in AML and discuss emerging drug targets based on pre-clinical work.

A systematic review on literature-based discovery workflow

As scientific publication rates increase, knowledge acquisition and the research development process have become more complex and time-consuming. Literature-Based Discovery (LBD), supporting automated knowledge discovery, helps facilitate this process by eliciting novel knowledge by analysing existing scientific literature. This systematic review provides a comprehensive overview of the LBD workflow by answering nine research questions related to the major components of the LBD workflow (i.e., input, process, output, and evaluation). With regards to the input component, we discuss the data types and data sources used in the literature. The process component presents filtering techniques, ranking/thresholding techniques, domains, generalisability levels, and resources. Subsequently, the output component focuses on the visualisation techniques used in LBD discipline. As for the evaluation component, we outline the evaluation techniques, their generalisability, and the quantitative measures used to validate results. To conclude, we summarise the findings of the review for each component by highlighting the possible future research directions.

Transcriptional networks of progressive diabetic peripheral neuropathy in the db/db mouse model of type 2 diabetes: An inflammatory story

Diabetic peripheral neuropathy is the most common complication of diabetes and a source of considerable morbidity. Numerous molecular pathways are linked to neuropathic progression, but it is unclear whether these pathways are altered throughout the course of disease. Moreover, the methods by which these molecular pathways are analyzed can produce significantly different results; as such it is often unclear whether previously published pathways are viable targets for novel therapeutic approaches. In the current study we examine changes in gene expression patterns in the sciatic nerve (SCN) and dorsal root ganglia (DRG) of db/db diabetic mice at 8, 16, and 24 weeks of age using microarray analysis. Following the collection and verification of gene expression data, we utilized both self-organizing map (SOM) analysis and differentially expressed gene (DEG) analysis to detect pathways that were altered at all time points. Though there was some variability between SOM and DEG analyses, we consistently detected altered immune pathways in both the SCN and DRG over the course of disease. To support these results, we further used multiplex analysis to assess protein changes in the SCN of diabetic mice; we found that multiple immune molecules were upregulated at both early and later stages of disease. In particular, we found that matrix metalloproteinase-12 was highly upregulated in microarray and multiplex data sets suggesting it may play a role in disease progression.

New Horizons in Diabetic Neuropathy: Mechanisms, Bioenergetics, and Pain

Pre-diabetes and diabetes are a global epidemic, and the associated neuropathic complications create a substantial burden on both the afflicted patients and society as a whole. Given the enormity of the problem and the lack of effective therapies, there is a pressing need to understand the mechanisms underlying diabetic neuropathy (DN). In this review, we present the structural components of the peripheral nervous system that underlie its susceptibility to metabolic insults and then discuss the pathways that contribute to peripheral nerve injury in DN. We also discuss systems biology insights gleaned from the recent advances in biotechnology and bioinformatics, emerging ideas centered on the axon-Schwann cell relationship and associated bioenergetic crosstalk, and the rapid expansion of our knowledge of the mechanisms contributing to neuropathic pain in diabetes. These recent advances in our understanding of DN pathogenesis are paving the way for critical mechanism-based therapy development.

ARN: analysis and prediction by adipogenic professional database

Adipogenesis is the process of cell differentiation by which mesenchymal stem cells become adipocytes. Extensive research is ongoing to identify genes, their protein products, and microRNAs that correlate with fat cell development. The existing databases have focused on certain types of regulatory factors and interactions. However, there is no relationship between the results of the experimental studies on adipogenesis and these databases because of the lack of an information center. This information fragmentation hampers the identification of key regulatory genes and pathways. Thus, it is necessary to provide an information center that is quickly and easily accessible to researchers in this field. We selected and integrated data from eight external databases based on the results of text-mining, and constructed a publicly available database and web interface (URL: http://210.27.80.93/arn/ ), which contained 30873 records related to adipogenic differentiation. Then, we designed an online analysis tool to analyze the experimental data or form a scientific hypothesis about adipogenesis through Swanson's literature-based discovery process. Furthermore, we calculated the "Impact Factor" ("IF") value that reflects the importance of each node by counting the numbers of relation records, expression records, and prediction records for each node. This platform can support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.

Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury

Objective

Mild traumatic brain injury (mTBI) has high prevalence in the military, among athletes, and in the general population worldwide (largely due to falls). Consequences can include a range of neuropsychological disorders. Unfortunately, such neural injury often goes undiagnosed due to the difficulty in identifying symptoms, so the discovery of an effective biomarker would greatly assist diagnosis; however, no single biomarker has been identified. We identify several body substances as potential components of a panel of biomarkers to support the diagnosis of mild traumatic brain injury.

Methods

Our approach to diagnostic biomarker discovery combines ideas and techniques from systems medicine, natural language processing, and graph theory. We create a molecular interaction network that represents neural injury and is composed of relationships automatically extracted from the literature. We retrieve citations related to neurological injury and extract relationships (semantic predications) that contain potential biomarkers. After linking all relationships together to create a network representing neural injury, we filter the network by relationship frequency and concept connectivity to reduce the set to a manageable size of higher interest substances.

Results

99,437 relevant citations yielded 26,441 unique relations. 18,085 of these contained a potential biomarker as subject or object with a total of 6246 unique concepts. After filtering by graph metrics, the set was reduced to 1021 relationships with 49 unique concepts, including 17 potential biomarkers.

Conclusion

We created a network of relationships containing substances derived from 99,437 citations and filtered using graph metrics to provide a set of 17 potential biomarkers. We discuss the interaction of several of these (glutamate, glucose, and lactate) as the basis for more effective diagnosis than is currently possible. This method provides an opportunity to focus the effort of wet bench research on those substances with the highest potential as biomarkers for mTBI.

[Acatalasemia and type 2 diabetes mellitus]

The catalase enzyme decomposes the toxic concentrations of hydrogen peroxide into oxygen and water. Hydrogen peroxide is a highly reactive small molecule and its excessive concentration may cause significant damages to proteins, deoxyribonucleic acid, ribonucleic acid and lipids. Acatalasemia refers to inherited deficiency of the catalase enzyme. In this review the authors discuss the possible role of the human catalase enzyme, the metabolism of hydrogen peroxide, and the phenomenon of hydrogen peroxide paradox. In addition, they review data obtained from Hungarian acatalasemic patients indicating an increased frequency of type 2 diabetes mellitus, especially in female patients, and an early onset of type 2 diabetes in these patients. There are 10 catalase gene variants which appear to be responsible for decreased blood catalase activity in acatalasemic patients with type 2 diabetes. It is assumed that low levels of blood catalase may cause an increased concentration of hydrogen peroxide which may contribute to the pathogenesis of type 2 diabetes mellitus.

High glucose forces a positive feedback loop connecting Akt kinase and FoxO1 transcription factor to activate mTORC1 kinase for mesangial cell hypertrophy and matrix protein expression

High glucose-induced Akt acts as a signaling hub for mesangial cell hypertrophy and matrix expansion, which are recognized as cardinal signatures for the development of diabetic nephropathy. How mesangial cells sustain the activated state of Akt is not clearly understood. Here we show Akt-dependent phosphorylation of the transcription factor FoxO1 by high glucose. Phosphorylation-deficient, constitutively active FoxO1 inhibited the high glucose-induced phosphorylation of Akt to suppress the phosphorylation/inactivation of PRAS40 and mTORC1 activity. In contrast, dominant negative FoxO1 increased the phosphorylation of Akt, resulting in increased mTORC1 activity similar to high glucose treatment. Notably, FoxO1 regulates high glucose-induced protein synthesis, hypertrophy, and expression of fibronectin and PAI-1. High glucose paves the way for complications of diabetic nephropathy through the production of reactive oxygen species (ROS). We considered whether the FoxO1 target antioxidant enzyme catalase contributes to sustained activation of Akt. High glucose-inactivated FoxO1 decreases the expression of catalase to increase the production of ROS. Moreover, we show that catalase blocks high glucose-stimulated Akt phosphorylation to attenuate the inactivation of FoxO1 and PRAS40, resulting in the inhibition of mTORC1 and mesangial cell hypertrophy and fibronectin and PAI-1 expression. Finally, using kidney cortices from type 1 diabetic OVE26 mice, we show that increased FoxO1 phosphorylation is associated with decreased catalase expression and increased fibronectin and PAI-1 expression. Together, our results provide the first evidence for the presence of a positive feedback loop for the sustained activation of Akt involving inactivated FoxO1 and a decrease in catalase expression, leading to increased ROS and mesangial cell hypertrophy and matrix protein expression.

Simulation of Swanson's literature-based discovery: anandamide treatment inhibits growth of gastric cancer cells in vitro and in silico

Swanson's literature-based discovery focus on resurrecting previously published but neglected knowledge. In this study, we propose a two-step model of the discovery process and generate a hypothesis between anandamide and gastric cancer. Further, the potential relationship was confirmed by follow-up experimentation. The anandamide treatment resulted in cell cycle redistribution of gastric cancer cells. Most importantly, the variation of cell cycle was mediated by some genes from the B-terms of the closed discovery, indicating the potential role of the B-terms. Swanson's literature-based discovery not only collates data for possible interactions, but also provides the potential to observe the larger background behind these direct links and is an invaluable discovery tool for investigators.

Effects of triple antioxidant therapy on measures of cardiovascular autonomic neuropathy and on myocardial blood flow in type 1 diabetes: a randomised controlled trial

AIMS/HYPOTHESIS

We evaluated the effects of a combination triple antioxidant therapy on measures of cardiovascular autonomic neuropathy (CAN) and myocardial blood flow (MBF) in patients with type 1 diabetes.

METHODS

This was a randomised, parallel, placebo-controlled trial. Participants were allocated to interventions by sequentially numbered, opaque, sealed envelopes provided to the research pharmacist. All participants and examiners were masked to treatment allocation. Participants were evaluated by cardiovascular autonomic reflex testing, positron emission tomography with [(11)C]meta-hydroxyephedrine ([(11)C]HED) and [(13)N]ammonia, and adenosine stress testing. Markers of oxidative stress included 24 h urinary F2-isoprostanes. Diabetic peripheral neuropathy (DPN) was evaluated by symptoms, signs, electrophysiology and intra-epidermal nerve fibre density. Randomised participants included 44 eligible adults with type 1 diabetes and mild-to-moderate CAN, who were aged 46 ± 11 years and had HbA1c 58 ± 5 mmol/mol (7.5 ± 1.0%), with no evidence of ischaemic heart disease. Participants underwent a 24-month intervention, consisting of antioxidant treatment with allopurinol, α-lipoic acid and nicotinamide, or placebo. The main outcome was change in the global [(11)C]HED retention index (RI) at 24 months in participants on the active drug compared with those on placebo.

RESULTS

We analysed data from 44 participants (22 per group). After adjusting for age, sex and in-trial HbA1c, the antioxidant regimen was associated with a slight, but significant worsening of the global [(11)C]HED left ventricle RI (-0.010 [95% CI -0.020, -0.001] p = 0.045) compared with placebo. There were no significant differences at follow-up between antioxidant treatment and placebo in the global MBF, coronary flow reserve, or in measures of DPN and markers of oxidative stress. The majority of adverse events were of mild-to-moderate severity and did not differ between groups

CONCLUSIONS/INTERPRETATION

In this cohort of type 1 diabetes patients with mild-to-moderate CAN, a combination antioxidant treatment regimen did not prevent progression of CAN, had no beneficial effects on myocardial perfusion or DPN, and may have been detrimental. However, a larger study is necessary to assess the underlying causes of these findings.

Identification of epigenetically altered genes in sporadic amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a terminal disease involving the progressive degeneration of motor neurons within the motor cortex, brainstem and spinal cord. Most cases are sporadic (sALS) with unknown causes suggesting that the etiology of sALS may not be limited to the genotype of patients, but may be influenced by exposure to environmental factors. Alterations in epigenetic modifications are likely to play a role in disease onset and progression in ALS, as aberrant epigenetic patterns may be acquired throughout life. The aim of this study was to identify epigenetic marks associated with sALS. We hypothesize that epigenetic modifications may alter the expression of pathogenesis-related genes leading to the onset and progression of sALS. Using ELISA assays, we observed alterations in global methylation (5 mC) and hydroxymethylation (5 HmC) in postmortem sALS spinal cord but not in whole blood. Loci-specific differentially methylated and expressed genes in sALS spinal cord were identified by genome-wide 5mC and expression profiling using high-throughput microarrays. Concordant direction, hyper- or hypo-5mC with parallel changes in gene expression (under- or over-expression), was observed in 112 genes highly associated with biological functions related to immune and inflammation response. Furthermore, literature-based analysis identified potential associations among the epigenes. Integration of methylomics and transcriptomics data successfully revealed methylation changes in sALS spinal cord. This study represents an initial identification of epigenetic regulatory mechanisms in sALS which may improve our understanding of sALS pathogenesis for the identification of biomarkers and new therapeutic targets.

Connecting the dots between PubMed abstracts

Background

There are now a multitude of articles published in a diversity of journals providing information about genes, proteins, pathways, and diseases. Each article investigates subsets of a biological process, but to gain insight into the functioning of a system as a whole, we must integrate information from multiple publications. Particularly, unraveling relationships between extra-cellular inputs and downstream molecular response mechanisms requires integrating conclusions from diverse publications.

Methodology

We present an automated approach to biological knowledge discovery from PubMed abstracts, suitable for “connecting the dots” across the literature. We describe a storytelling algorithm that, given a start and end publication, typically with little or no overlap in content, identifies a chain of intermediate publications from one to the other, such that neighboring publications have significant content similarity. The quality of discovered stories is measured using local criteria such as the size of supporting neighborhoods for each link and the strength of individual links connecting publications, as well as global metrics of dispersion. To ensure that the story stays coherent as it meanders from one publication to another, we demonstrate the design of novel coherence and overlap filters for use as post-processing steps.

Conclusions

We demonstrate the application of our storytelling algorithm to three case studies: i) a many-one study exploring relationships between multiple cellular inputs and a molecule responsible for cell-fate decisions, ii) a many-many study exploring the relationships between multiple cytokines and multiple downstream transcription factors, and iii) a one-to-one study to showcase the ability to recover a cancer related association, viz. the Warburg effect, from past literature. The storytelling pipeline helps narrow down a scientist's focus from several hundreds of thousands of relevant documents to only around a hundred stories. We argue that our approach can serve as a valuable discovery aid for hypothesis generation and connection exploration in large unstructured biological knowledge bases.

Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

Background

Vaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for Brucella, the causative agent of brucellosis in humans and animals.

Results

The VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 Brucella vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to Brucella vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated Brucella vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines. These genes included known protective antigens, virulence factors, and genes closely related to Brucella vaccines. These VO-interacting Brucella genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of Brucella vaccines and genes were identified. The asserted and inferred VO hierarchies provide semantic support for inferring novel knowledge of association of vaccines and genes from the retrieved data. New hypotheses were generated based on this analysis approach.

Conclusion

VO-SciMiner can be used to improve the efficiency for PubMed searching in the vaccine domain.

Eryptosis and oxidative damage in type 2 diabetic mellitus patients with chronic kidney disease

It has been suggested that oxidative stress may participate in the progression of diabetes and its complications. Long-term complications of type 2 diabetes mellitus (T2DM) include retinopathy, atherosclerosis, shortened life span of erythrocytes, nephropathy, and chronic kidney disease (CKD). Oxidative damage has been associated with erythrocyte apoptosis induction in other pathological conditions. Our aim was to study the presence of eryptosis and its possible relationship with oxidative damage in patients with T2DM without CKD (T2DM/CKD(-)) and in patients with T2DM and CKD (T2DM/CKD(+)).Oxidative damage of lipids erythrocytes were increased in diabetic patients. The highest lipoperoxidation was found in T2DM/CKD(+). Likewise, the lower plasma total antioxidant capacity, GSH/GSSG ratio, and GSH in erythrocytes were found in T2DM/CKD(+) patients. A negative correlation was found between plasma total antioxidant capacity and oxidative damage. Phosphatidylserine (PS) externalization was measured in erythrocytes to evaluate eryptosis. Annexin binding in erythrocytes of T2DM/CKD(+) patients was higher than in healthy subjects and T2DM/CKD(-) patients. A positive correlation between lipoperoxidation and PS externalization in erythrocytes was found. This work showed that the erythrocytes of diabetic patients have increased oxidative damage, a reduction of antioxidant systems and more erythrocyte PS externalization. The duration of diabetes and the presence of CKD increase both oxidative damage and eryptosis. It is possible that a longer time of evolution induces an increase in erythrocyte oxidative damage and the consumption of blood antioxidant systems, adding to the osmotic stress in CKD and so contributes to an increase in PS externalization in diabetic patients.