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Systems Pharmacology Approach to Identify Potential Therapeutic Small‐Molecules for Treatment of Diabetic Peripheral Neuropathy
Author(s) -
McGregor Brett A.,
Porter James E.,
Feldman Eva L.,
Hur Junguk
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.1270.1
Subject(s) - microarray analysis techniques , diabetic neuropathy , peripheral neuropathy , diabetes mellitus , gene , computational biology , microarray , drug repositioning , metformin , bioinformatics , dna microarray , gene regulatory network , medicine , biology , gene expression , pharmacology , genetics , endocrinology , drug
Diabetic peripheral neuropathy (DPN) is one of the most common complications of diabetes. Despite extensive research the underlying mechanisms leading to this complication are not fully understood, and there are no specific treatments or means to predict DPN onset or progression. In this study, we employed a systems pharmacology approach to identify DPN‐related transcriptional networks and pathways conserved across various animal models and species, to identify drug‐candidates with therapeutic potentials. From our Diabetic Neuropathy Microarray Knowledge‐Base (DNMKB), we selected DPN‐related microarray data performed in sciatic nerve samples from type 1 diabetes (streptozotocin‐treated) and type 2 diabetes ( db / db , ob / ob , high‐fat diet fed) murine models and human subjects with non‐progressive and progressive DPN. Differentially expressed genes (DEGs) were identified between non‐diabetic and diabetic samples in murine models, and between non‐progressive and progressive samples in human. Our in‐house literature mining program, SciMiner, was used to construct a transcriptional network for each DEG set, based on the sentence‐level gene‐gene co‐citation information in the complete PubMed abstracts. These networks were then compared using a network‐comparison program TALE (tool for approximate large graph matching) to identify overlapping relations between networks. These comparisons indicated that genes involved in the reelin signaling pathway, matrix metalloproteinases inhibition, and proliferation regulation to be differentially expressed and conserved between datasets. The genes that demonstrate the most dramatic fold change while overlapping across species and various DPN models were defined as the representative gene expression signature of DPN. This DPN signature was searched against the drug‐perturbed gene expression profile data from the Library of Integrated Network‐based Cellular Signatures (LINCS) database. LINCS, aiming to create a network‐based understanding of gene expression when cells are exposed to different perturbing agents, have extensively profiled the transcriptomic perturbations of over 20,000 small‐molecules in various cell lines and primary cells. Our expression profile‐based comparison analysis identified over 50 potential small‐molecule compounds with potential of reversing the direction of expression changes identified in the central pathways involved in our DPN networks. The top candidates included methyltransferase inhibitors and metabotropic glutamate inhibitors. A systems pharmacology approach, integrating of multiple bio/chem‐informatics analyses, identified DPN‐associated pathways that are highly conserved across various murine models and across species, as well as potential small‐molecules for DPN. Support or Funding Information The study was supported by the Diabetic Complications Consortium (DiaComp) Pilot & Feasiblity Grant (to J.H.), and the American Diabetes Association (to E.L.F).