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

Diabetes is a metabolic disease in which the body does not produce or properly respond to insulin, a hormone required to convert carbohydrates into energy for daily life. According to the American Diabetes Association, 23.6 million children and adults, approximately 7.8% of the population in the United States, have diabetes [1]. The cost of diabetes in 2007 was estimated to be $174 billion [1]. The micro- and macro-vascular complications of diabetes are the most common causes of renal failure, blindness and amputations leading to significant mortality, morbidity and poor quality of life; however, incomplete understanding of the causes of diabetic complications hinders the development of mechanism-based therapies.

In vivo and in vitro experiments implicate a number of enzymatic and non-enzymatic metabolic pathways in the initiation and progression of diabetic complications [2] including: (1) increased polyol pathway activity leading to sorbitol and fructose accumulation, NAD(P)-redox imbalances and changes in signal transduction; (2) non-enzymatic glycation of proteins yielding "advanced glycation end-products" (AGEs); (3) activation of protein kinase C (PKC), initiating a cascade of intracellular stress responses; and (4) increased hexosamine pathway flux [2, 3]. Only recently has a link among these pathways been established that provides a unified mechanism of tissue damage. Each of these pathways directly and indirectly leads to overproduction of reactive oxygen species (ROS) [2, 3].

ROS are highly reactive ions or small molecules including oxygen ions, free radicals and peroxides, formed as natural byproducts of cellular energy metabolism. ROS are implicated in multiple cellular pathways such as mitogen-activated protein kinase (MAPK) signaling, c-Jun amino-terminal kinase (JNK), cell proliferation and apoptosis [4–6]. Due to the highly reactive properties of ROS, excessive ROS may cause significant damage to proteins, DNA, RNA and lipids. All cells express enzymes capable of neutralizing ROS. In addition to the maintenance of antioxidant systems such as glutathione and thioredoxins, primary sensory neurons express two main detoxifying enzymes: superoxide dismutase (SOD) [7] and catalase [8]. SOD converts superoxide (O₂-) to H₂O₂, which is reduced to H₂O by glutathione and catalase [8]. SOD1 is the main form of SOD in the cytoplasm; SOD2 is located within the mitochondria. In neurons, SOD1 activity represents approximately 90% of total SOD activity and SOD2 approximately 10% [9]. Under diabetic conditions, this protective mechanism is overwhelmed due to the substantial increase in ROS, leading to cellular damage and dysfunction [10].

The idea that increased ROS and oxidative stress contribute to the pathogenesis of diabetic complications has led scientists to investigate different oxidative stress pathways [7, 11]. Inhibition of ROS or maintenance of euglycemia restores metabolic and vascular imbalances and blocks both the initiation and progression of complications [12, 13]. Despite the significant implications and extensive research into the role of ROS in diabetes, no comprehensive database regarding ROS-related genes or proteins is currently available.

In the present study, a comprehensive list of ROS- and diabetes-related targets (genes/proteins) was compiled from the biomedical literature through text mining technology. SciMiner, a web-based literature mining tool [14], was used to retrieve and process documents and identify targets from the text. SciMiner provides a convenient web-based platform for target-identification within the biomedical literature, similar to other tools including EBIMed [15], ALI BABA [16], and PolySearch [17]; however, SciMiner is unique in that it searches full text documents, supports free-text PubMed query style, and allows the comparison of target lists from multiple queries.

The ROS-diabetes targets collected by SciMiner were further tested against randomly selected non-ROS-diabetes literature to identify targets that are significantly over-represented in the ROS-diabetes literature. Functional enrichment analyses were performed on these targets to identify significantly over-represented biological functions in terms of Gene Ontology (GO) terms and pathways.

In order to confirm the biological relevance of the over-represented ROS-diabetes targets, the gene expression levels of nine selected targets were measured in dorsal root ganglia (DRG) from mice with and without diabetes. DRG contain primary sensory neurons that relay information from the periphery to the central nervous system (CNS) [7, 10, 18]. Unlike the CNS, DRG are not protected by a blood-nerve barrier, and are consequently vulnerable to metabolic and toxic injury [19]. We hypothesize that differential expression of identified targets in DRG would confirm their involvement in the pathogenesis of diabetic neuropathy.

Reactive oxygen species (ROS) are products of normal energy metabolism and play important roles in many other biological processes such as the immune response and signaling cascades [4–6]. As mediators of cellular damage, ROS are implicated in pathogenesis of multiple diseases including diabetic complications [27–30]. With the aid of literature mining technology, we collected 1,026 possible ROS-related targets from a set of biomedical literature indexed with both ROS and diabetes.

Fifty-three targets were significantly over-represented in the ROS-diabetes papers when compared against three background sets. Depending on how the background set is defined, the over-represented targets may vary widely. An ideal background set would be the entire PubMed set; however, this is not possible due to limited access to full texts and intense data processing. An alternative method would be to use only abstracts in PubMed, but this may not fully represent the literature. Using only the abstracts, our target identification method resulted in 21 (39%) of the 53 key ROS-diabetes targets (Additional File 12), suggesting the benefit of rich information in full text documents. In the present study, background documents were randomly selected from the same journal, volume, and issue of the 1,154 ROS-diabetes documents, which were not indexed with "Reactive Oxygen Species"[MeSH] nor "Diabetes Mellitus"[MeSH]. This approach maintained the background corpora not far from the ROS and diabetes context.

The gene expression levels of nine targets selected from the 53 over-represented ROS-diabetes targets were measured in diabetic and non-diabetic DRG. Our laboratory is particularly interested in deciphering the underlying mechanisms of diabetic neuropathy, a major complication of diabetes. Data published by our laboratory both in vitro and in vivo confirm the negative impact of oxidative stress in complication-prone neuron tissues like DRG [7, 10, 18, 31]. In an effort to obtain diabetic neuropathy specific targets, SciMiner was employed to further analyze a subset of the ROS-diabetes papers (data not shown). Nerve growth factor (NGF) was identified as the most over-represented target in this subset when compared to the full ROS-diabetes set; however, NGF did not have statistical significance (BH adjusted p-value = 0.06). The relatively small numbers of papers and associated targets may have contributed to this non-significance. Therefore, the candidate targets for gene expression validation were selected from among the 53 over-represented ROS-diabetes targets derived from the full ROS-diabetes corpus.

Among the tested genes, the expression levels of Cat, Sod1, Sod2, Prkca, and Nos1 were decreased, while the expression levels of Ncf1, Xdh, and Cyba were increased under diabetic conditions. Cat, Sod1, and Sod2 are responsible for protecting cells from oxidative stress by destroying superoxides and hydrogen peroxides [8–11]. Decreased expression of these genes may result in oxidative stress [32]. Increased expression of Cyba and Ncf1, subunits of superoxide-generating nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex [30], also supports enhanced oxidative stress. Xdh and its inter-convertible form, Xanthine oxidase (Xod), showed increased activity in various rat tissues under oxidative stress conditions with diabetes [33], and also showed increased expression in diabetic DRG in the current study.

Unlike the above concordant genes, protein kinase C and nitric oxide synthases did not exhibit predicted expression changes in diabetes. Protein kinase C activates NADPH oxidase, further promoting oxidative stress in the cell [34, 35]. Decreased expression of Prkca in our diabetic DRG is not parallel with expression levels of other enzymes expected to increase oxidative stress. Between the two nitric oxide synthases tested in the present study, Nos1 (neuronal) expression was significantly decreased (p-value < 0.001) in diabetes, while Nos3 (endothelial) expression was not significant (p-value = 0.06). The neuronal Nos1 is expected to play a major role in producing nitric oxide, another type of highly reactive free radical. Thus, with some exceptions, the majority of the differentially expressed genes in DRG show parallel results to the known activities of these targets in diabetes, suggesting enhanced oxidative stress in the diabetic DRG.

Assessment of antioxidant enzyme expression in diabetes has yielded a variety of results [36–40] depending upon the duration of diabetes, the tissue studied and other factors. In diabetic mice and rats, it is commonly reported that superoxide dismutases are down-regulated [37–40], where data regarding catalase are variable [36, 40]. PKC is activated in diabetes, but most papers that examined mRNA demonstrated that its expression is largely unchanged [41].

Among the 53 over-represented ROS-diabetes targets, SOD1 was the most over-represented and was differentially expressed under diabetic and non-diabetic conditions. To the best of our knowledge, no published study has investigated the role of SOD1 in the onset and/or progression of diabetic neuropathy. Mutations of SOD1 have long been associated with the inherited form of amyotrophic lateral sclerosis (ALS) [42] and the theory of oxidative stress-based aging [43]. Early reports indicate that knockout of the SOD1 gene does not affect nervous system development [44], although recovery following injury is slow and incomplete [45, 46]. With respect to diabetes, SOD1 KO accelerates the development of diabetic nephropathy [47] and cataract formation [48]. Thus, examining the SOD1 KO mouse as a model of diabetic neuropathy would be a reasonable follow-up study.

One limitation of the current approach using literature mining technology is incorrect or missed identification of the mentioned targets within the literature. Based on a performance evaluation using a standard text set BioCreAtIvE (Critical Assessment of Information Extraction systems in Biology) version 2 [49], SciMiner achieved 87.1% recall (percentage identification of targets in the given text), 71.3% precision (percentage accuracy of identified target) and 75.8% F-measure (harmonious average of recall and precision = (2 × recall × precision)/(recall + precision)) before manual revision [14]. In order to improve the accuracy of SciMiner's results, each target was manually reviewed and corrected by checking the sentences in which each target was identified. Approximately, 120 targets (~10% of the initially identified targets from the ROS-diabetes papers) were removed during the manual review process. The overall accuracy is expected to improve through the review process; however, the review process did not address targets missed by SciMiner, since we did not thoroughly review individual papers. Instead, 5 missed targets, whose associations with ROS-diabetes literature were available in the NCBI Gene2PubMed database, were added to the final ROS-diabetes target list (Additional File 2).

The present approach enabled us to collect a comprehensive list of ROS and diabetes related targets and led us to confirm the biological relevance to diabetic neuropathy of the selected ROS-diabetes targets. Using SciMiner to identify significantly enriched targets is applicable to other disease topics of interest by providing a more focused subset of literature for review and by highlighting targets common to multiple manuscripts.