Dataset Information

Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.

ABSTRACT: Various studies suggest a comorbid association between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) indicating that there could be shared underlying pathophysiological mechanisms.This study aims to systematically model relevant knowledge at the molecular level to find a mechanistic rationale explaining the existing comorbid association between AD and T2DM.We have used a knowledge-based modeling approach to build two network models for AD and T2DM using Biological Expression Language (BEL), which is capable of capturing and representing causal and correlative relationships at both molecular and clinical levels from various knowledge resources.Using comparative analysis, we have identified several putative "shared pathways". We demonstrate, at a mechanistic level, how the insulin signaling pathway is related to other significant AD pathways such as the neurotrophin signaling pathway, PI3K/AKT signaling, MTOR signaling, and MAPK signaling and how these pathways do cross-talk with each other both in AD and T2DM. In addition, we present a mechanistic hypothesis that explains both favorable and adverse effects of the anti-diabetic drug metformin in AD.The two computable models introduced here provide a powerful framework to identify plausible mechanistic links shared between AD and T2DM and thereby identify targeted pathways for new therapeutics. Our approach can also be used to provide mechanistic answers to the question of why some T2DM treatments seem to increase the risk of AD.

SUBMITTER: Karki R

PROVIDER: S-EPMC5611890 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.

Karki Reagon R Kodamullil Alpha Tom AT Hofmann-Apitius Martin M

Journal of Alzheimer's disease : JAD 20170101 2

<h4>Background</h4>Various studies suggest a comorbid association between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) indicating that there could be shared underlying pathophysiological mechanisms.<h4>Objective</h4>This study aims to systematically model relevant knowledge at the molecular level to find a mechanistic rationale explaining the existing comorbid association between AD and T2DM.<h4>Method</h4>We have used a knowledge-based modeling approach to build two network mode ...[more]

PMID: 28922161

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Project description:BackgroundSarcopenia is characterized by the age-associated loss of skeletal muscle mass and strength that develops progressively and plays an important role in the disability of the elderly. It has received growing attention over the last decade and has been implicated as both a cause and consequence of type 2 diabetes mellitus (T2DM). The existence of T2DM could increase the risk of developing sarcopenia through multiple mechanisms including advanced glycation end-product accumulation. Meanwhile, sarcopenia would alter glucose disposal and may contribute to the development and progression of T2DM due to reduced muscle mass.MethodsWe implemented transcriptomic analysis of skeletal muscle biopsy specimens in sarcopenia patients and proliferating myoblasts or differentiated myotubes from individuals with T2DM. Related microarray data were selected from Gene Expression Omnibus (GEO) to screen the genes, which were differentially expressed for sarcopenia and T2DM. Multiple combinatorial statistical methods and bioinformatics tools were used to analyze the common DEGs. Meanwhile, functional enrichment analysis was also carried out. Furthermore, we constructed the protein-protein interaction (PPI), as well as transcription factor (TF)-gene interactions network and TF-miRNA coregulatory network. Finally, based on the common DEGs, drug compounds were speculated using the Drug Signatures database (DSigDB).ResultsA total of 1765 and 2155 DEGs of sarcopenia and T2DM were screened, respectively. 15 common genes (LXN, CIB2, PEA15, KANK2, FGD1, NMRK1, PLCB1, SEMA4G, ADARB1, UPF3A, CSTB, COL3A1, CD99, ETV3, FJX1) correlated with sarcopenia and T2DM simultaneously were then identified, and 3 genes (UPF3A, CSTB and PEA15) of them were regarded as hub genes. Functional enrichment analysis revealed several shared pathways between two diseases. In addition, according to the TF-gene interactions network and TF-miRNA coregulatory network, part of TF and miRNA may be identified as key regulator in sarcopenia and T2DM at the same time (e.g., CREM and miR-155). Notably, drug compounds for T2DM and sarcopenia were also suggested, such as coenzyme Q10.ConclusionThis study revealed that sarcopenia and T2DM may share similar pathogenesis and provided new biological targets and ideas for early diagnosis and effective treatment of sarcopenia and T2DM.

Project description:PurposeThe pancreatic islet specific microRNA-375 (miR-375) is overexpressed in type 2 diabetes mellitus (T2DM) patients suppressing the glucose-induced insulin secretion. Thus, miR-375 may serve as a biomarker for the early prediction of T2DM among high-risk individuals. We conducted this clinical study to assess the significance of miR-375 among type 2 diabetes mellitus (T2DM) patients and their first-degree relatives.Patients and methodsWe included 56 Han Chinese individuals (N: NGT = 21, T2DM = 10, FD-NGT =13 and FD-T2DM = 12) who received medical health check-ups from January 2018 to September 2018 at The Third Hospital of Yunnan Province, China. They were categorized as normal glucose tolerance (NGT), T2DM, first-degree relatives with normal glucose tolerance (FD-NGT) and first-degree relatives with T2DM (FD-T2DM). OGTT, C-peptide and Insulin tests were performed to confirm the diagnosis. The miR-375 levels were determined by Quantitative real-time RT-PCR (qRT-PCR).ResultsThe OGTT test showed a significant difference in T2DM and FD-T2DM groups compared with NGT and FD-NGT (p< 0.05). Similar results were observed during C-peptide and insulin tests. Interestingly, the 2-hour insulin test showed FD-NGT group having a significantly higher mean ± standard error of (64.240 ± 12.775) compared to NGT (28.836 ± 10.875). Assessment of miR-375 expression levels in 4 groups showed a significant up-regulation in T2DM and FD-T2DM compared with NGT and FD-NGT groups. A slight increase in miRNA expression was observed in FD-NGT compared with NGT group but was not statistically significant.ConclusionThe OGTT, C-peptide and insulin tests revealed a statistically significant difference in T2DM and FD-T2DM compared with NGT and FD-NGT groups. A significantly higher miR-375 expression was also observed in T2DM and FD-T2DM groups compared with NGT and FD-NGT and thus, miR-375 may serve as a stable biomarker for the early prediction of T2DM among high-risk individuals.

Dataset Information

Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.

Publications

Comorbidity Analysis between Alzheimer's Disease and Type 2 Diabetes Mellitus (T2DM) Based on Shared Pathways and the Role of T2DM Drugs.

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