Dataset Information

MiR-129-5p Inhibits Adipogenesis through Autophagy and May Be a Potential Biomarker for Obesity.

ABSTRACT: Introduction:Obesity has an unclear pathogenesis. MicroRNAs (miRNAs) may function as biologically active molecules for obesity through regulating adipocyte differentiation. This study aimed to identify how miR-129-5p (a specific miRNA) regulates adipogenesis in vitro and explore its possible role in the pathogenesis of obesity in humans. Materials and Methods:The miR-129-5p expression was detected in obese mouse models. The effect of miR-129-5p on adipocyte differentiation was observed, and the adipose markers were analyzed. Bioinformatics and dual-luciferase reporter assay were applied to predict and confirm the target genes of miR-129-5p. The human serum samples were detected and analyzed. Results:miR-129-5p is highly expressed in adipose tissues of db/db mice. Gain- and loss-of-function studies show that miR-129-5p could significantly inhibit adipocyte differentiation and white adipocyte browning in vitro and decreases the level of specific markers, such as FABP4, UCP1, and PPAR?, in mature white and brown adipocytes. miR-129-5p directly targets ATG7 which is predicted with bioinformatics and confirmed by dual-luciferase reporter assay. Serum miR-129-5p level was evidently elevated in patients with simple obesity (p < 0.01) and correlates with obesity indices, including BMI (r?=?0.407, p < 0.029) and fat percentage (r?=?0.394, p < 0.038). Conclusion:miR-129-5p might target on the ATG7-related autophagy signaling network that regulates white and brown adipogenesis. Importantly, the aforementioned results suggest serum miR-129-5p might be a potential biomarker and therapeutic target for obesity.

SUBMITTER: Fu X

PROVIDER: S-EPMC6875017 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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miR-129-5p Inhibits Adipogenesis through Autophagy and May Be a Potential Biomarker for Obesity.

Fu Xue X Jin Lina L Han Luyu L Yuan Yini Y Mu Qian Q Wang Hui H Yang Jian J Ning Guang G Zhou Donglei D Zhang Zhiguo Z

International journal of endocrinology 20191106

<h4>Introduction</h4>Obesity has an unclear pathogenesis. MicroRNAs (miRNAs) may function as biologically active molecules for obesity through regulating adipocyte differentiation. This study aimed to identify how miR-129-5p (a specific miRNA) regulates adipogenesis in vitro and explore its possible role in the pathogenesis of obesity in humans.<h4>Materials and methods</h4>The miR-129-5p expression was detected in obese mouse models. The effect of miR-129-5p on adipocyte differentiation was obs ...[more]

PMID: 31781210

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Project description:Osteoporosis is a frequently occurring bone disease in middle-aged and aged men and women. However, current therapies on this disease are still not ideal. MicroRNAs (miRNAs) are a class of endogenous non-protein-coding RNA with a length of 18-25 nucleotides. miRNAs have been identified as important regulators for development, metabolism, carcinogenesis, and bone formation. miR-129-5p has been reported as a regulator of cancer and neuroscience, whereas studies about its function on bone formation is still limited. In this study, we investigated the function and mechanism of miR-129-5p on osteoblast differentiation and bone formation. We have assessed the expression of miRNAs in bone mesenchymal stem cells from aging and menopause osteoporosis C57BL6 mice. The expression of miR-129-5p was altered in all osteoporosis models. Besides, the expression of miR-129-5p was negatively correlated with osteoblastic differentiation markers in the femur tissues of C57BL/6 mice of different ages. We further demonstrated that overexpression of miR-129-5p inhibited osteoblast differentiation in MC3T3-E1 cell line, as well as bone formation of C57BL/6 mice. On the other hand, down-regulation of miR-129-5p enhanced osteoblast differentiation and bone formation. We also found that miR-129-5p inhibited Wnt/β-catenin pathway in osteoblast. The target gene of miR-129-5p has been forecasted and proved as Tcf4. We further found that plasmid containing Tcf4-3' UTR sequence enhanced osteoblast differentiation, as well as Wnt/β-catenin pathway in MC3T3-E1 cells. To further investigate the rescue effect of miR-129-5p inhibitor, we manufactured bioengineered novel recombinant miR-129-5p inhibitor through Escherichia coli system and then tested its function. The results showed that the novel recombinant miR-129-5p inhibitor promoted osteoblast differentiation and greatly ameliorated menopause osteoporosis in C57BL6 mice. In conclusion, we have discovered miR-129-5p as an inhibitor of bone formation. miR-129-5p inhibited downstream transcription factors of Wnt/β-catenin pathway through targeting Tcf4. Moreover, novel recombinant miR-129-5p inhibitor showed rescue effect on osteoporosis. This study has revealed a new mechanism of osteogenic differentiation and provided novel therapeutic strategies for treatment of skeletal disorders.

Project description:BackgroundAlzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers.MethodsWe performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification.ResultsNetwork analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs.ConclusionsIntegrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Project description:BackgroundAlzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers.MethodsWe performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification.ResultsNetwork analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules, and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and apoE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs.ConclusionsIntegrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Dataset Information

MiR-129-5p Inhibits Adipogenesis through Autophagy and May Be a Potential Biomarker for Obesity.

Publications

miR-129-5p Inhibits Adipogenesis through Autophagy and May Be a Potential Biomarker for Obesity.

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