Dataset Information

Glomerular expression pattern of long non-coding RNAs in the type 2 diabetes mellitus BTBR mouse model.

ABSTRACT: The prevalence of type 2 diabetes mellitus (T2DM) and by association diabetic nephropathy (DN) will continuously increase in the next decades. Nevertheless, the underlying molecular mechanisms are largely unknown and studies on the role of new actors like long non-coding RNAs (lncRNAs) barely exist. In the present study, the inherently insulin-resistant mouse strain "black and tan, brachyuric" (BTBR) served as T2DM model. While wild-type mice do not exhibit pathological changes, leptin-deficient diabetic animals develop a severe T2DM accompanied by a DN, which closely resembles the human phenotype. We analyzed the glomerular expression of lncRNAs from wild-type and diabetic BTBR mice (four, eight, 16, and 24 weeks) applying the "GeneChip Mouse Whole Transcriptome 1.0 ST" array. This microarray covered more lncRNA gene loci than any other array before. Over the observed time, our data revealed differential expression patterns of 1746 lncRNAs, which markedly differed from mRNAs. We identified protein-coding and non-coding genes, that were not only co-located but also co-expressed, indicating a potentially cis-acting function of these lncRNAs. In vitro-experiments strongly suggested a cell-specific expression of these lncRNA-mRNA-pairs. Additionally, protein-coding genes, being associated with significantly regulated lncRNAs, were enriched in various biological processes and pathways, that were strongly linked to diabetes.

SUBMITTER: Reichelt-Wurm S

PROVIDER: S-EPMC6611801 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Glomerular expression pattern of long non-coding RNAs in the type 2 diabetes mellitus BTBR mouse model.

Reichelt-Wurm Simone S Wirtz Tobias T Chittka Dominik D Lindenmeyer Maja M Reichelt Robert M RM Beck Sebastian S Politis Panagiotis P Charonis Aristidis A Kretz Markus M Huber Tobias B TB Liu Shuya S Banas Bernhard B Banas Miriam C MC

Scientific reports 20190705 1

The prevalence of type 2 diabetes mellitus (T2DM) and by association diabetic nephropathy (DN) will continuously increase in the next decades. Nevertheless, the underlying molecular mechanisms are largely unknown and studies on the role of new actors like long non-coding RNAs (lncRNAs) barely exist. In the present study, the inherently insulin-resistant mouse strain "black and tan, brachyuric" (BTBR) served as T2DM model. While wild-type mice do not exhibit pathological changes, leptin-deficient ...[more]

PMID: 31278342

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Project description:The relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) is so strong that scientists called it "brain diabetes". According to several studies, the critical factor in this relationship is brain insulin resistance. Due to the rapid global spread of both diseases, overcoming this cross-talk has a significant impact on societies. Long non-coding RNAs (lncRNAs), on the other hand, have a substantial impact on complex diseases due to their ability to influence gene expression via a variety of mechanisms. Consequently, the regulation of lncRNA expression in chronic diseases permits the development of innovative therapeutic techniques. However, developing a new drug requires considerable time and money. Recently repurposing existing drugs has gained popularity due to the use of low-risk compounds, which may result in cost and time savings. in this study, we identified drug repurposing candidates capable of controlling the expression of common lncRNAs in the cross-talk between DM and AD. We also utilized drugs that interfered with this cross-talk. To do this, high degree common lncRNAs were extracted from microRNA-lncRNA bipartite network. The drugs that interact with the specified lncRNAs were then collected from multiple data sources. These drugs, referred to as set D, were classified in to positive (D+) and negative (D-) groups based on their effects on the expression of the interacting lncRNAs. A feature selection algorithm was used to select six important features for D. Using a random forest classifier, these features were capable of classifying D+ and D- with an accuracy of 82.5%. Finally, the same six features were extracted for the most recently Food and Drug Administration (FDA) approved drugs in order to identify those with the highest likelihood of belonging to D+ or D-. The most significant FDA-approved positive drugs, chromium nicotinate and tapentadol, were presented as repurposing candidates, while cefepime and dihydro-alpha-ergocryptine were recommended as significant adverse drugs. Moreover, two natural compounds, curcumin and quercetin, were recommended to prevent this cross-talk. According to the previous studies, less attention has been paid to the role of lncRNAs in this cross-talk. Our research not only did identify important lncRNAs, but it also suggested potential repurposed drugs to control them.

Dataset Information

Glomerular expression pattern of long non-coding RNAs in the type 2 diabetes mellitus BTBR mouse model.

Publications

Glomerular expression pattern of long non-coding RNAs in the type 2 diabetes mellitus BTBR mouse model.

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