Aims/hypothesis
Diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN) are two common microvascular complications of type 1 and type 2 diabetes mellitus that are associated with a high degree of morbidity. In this study, using a variety of systems biology approaches, our aim was to identify common and distinct mechanisms underlying the pathogenesis of these two complications.
Methods
Our previously published transcriptomic datasets of peripheral nerve and kidney tissue, derived from murine models of type 1 diabetes (streptozotocin-injected mice) and type 2 diabetes (BKS-db/db mice) and their respective controls, were collected and processed using a unified analysis pipeline so that comparisons could be made. In addition to looking at genes and pathways dysregulated in individual datasets, pairwise comparisons across diabetes type and tissue type were performed at both gene and transcriptional network levels to complete our proposed objective.
Results
Gene-level analysis identified exceptionally high levels of concordant gene expression in DN (94% of 2,433 genes), but not in DPN (55% of 1,558 genes), between type 1 diabetes and type 2 diabetes. These results suggest that common pathogenic mechanisms exist in DN across diabetes type, while in DPN the mechanisms are more distinct. When these dysregulated genes were examined at the transcriptional network level, we found that the Janus kinase (JAK)–signal transducer and activator of transcription (STAT) pathway was significantly dysregulated in both complications, irrespective of diabetes type.
Conclusions/interpretation
Using a systems biology approach, our findings suggest that common pathogenic mechanisms exist in DN across diabetes type, while in DPN the mechanisms are more distinct. We also found that JAK–STAT signalling is commonly dysregulated among all datasets. Using such approaches, further investigation is warranted to determine whether the same changes are observed in patients with diabetic complications.
Diabetic peripheral neuropathy (DPN) is one of the most common complications of diabetes. In this study, we employed a systems biology approach to identify DPN-related transcriptional pathways conserved across human and various murine models. Eight microarray datasets on peripheral nerve samples from murine models of type 1 (streptozotocin-treated) and type 2 (db/db and ob/ob) diabetes of various ages and human subjects with non-progressive and progressive DPN were collected. Differentially expressed genes (DEGs) were identified between non-diabetic and diabetic samples in murine models, and non-progressive and progressive human samples using a unified analysis pipeline. A transcriptional network for each DEG set was constructed based on literature-derived gene-gene interaction information. Seven pairwise human-vs-murine comparisons using a network-comparison program resulted in shared sub-networks including 46 to 396 genes, which were further merged into a single network of 688 genes. Pathway and centrality analyses revealed highly connected genes and pathways including LXR/RXR activation, adipogenesis, glucocorticoid receptor signalling, and multiple cytokine and chemokine pathways. Our systems biology approach identified highly conserved pathways across human and murine models that are likely to play a role in DPN pathogenesis and provide new possible mechanism-based targets for DPN therapy.
The US Toxicology Testing in the 21st Century (Tox21) program was established to develop more efficient and human-relevant toxicity assessment methods. The Tox21 program screens >10,000 chemicals using quantitative high-throughput screening (qHTS) of assays that measure effects on toxicity pathways. To date, more than 70 assays have yielded >12 million concentration-response curves. The patterns of activity across assays can be used to define similarity between chemicals. Assuming chemicals with similar activity profiles have similar toxicological properties, we may infer toxicological properties based on its neighbourhood. One approach to inference is chemical/biological annotation enrichment analysis. Here, we present Tox21 Enricher, a web-based chemical annotation enrichment tool for the Tox21 toxicity screening platform. Tox21 Enricher identifies over-represented chemical/biological annotations among lists of chemicals (neighbourhoods), facilitating the identification of the toxicological properties and mechanisms in the chemical set.
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