Dataset Information

Autophagy in cardiovascular biology.

ABSTRACT: Cardiovascular disease is the leading cause of death worldwide. As such, there is great interest in identifying novel mechanisms that govern the cardiovascular response to disease-related stress. First described in failing hearts, autophagy within the cardiovascular system has been widely characterized in cardiomyocytes, cardiac fibroblasts, endothelial cells, vascular smooth muscle cells, and macrophages. In all cases, a window of optimal autophagic activity appears to be critical to the maintenance of cardiovascular homeostasis and function; excessive or insufficient levels of autophagic flux can each contribute to heart disease pathogenesis. In this Review, we discuss the potential for targeting autophagy therapeutically and our vision for where this exciting biology may lead in the future.

SUBMITTER: Lavandero S

PROVIDER: S-EPMC4382263 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Autophagy in cardiovascular biology.

Lavandero Sergio S Chiong Mario M Rothermel Beverly A BA Hill Joseph A JA

The Journal of clinical investigation 20150102 1

Cardiovascular disease is the leading cause of death worldwide. As such, there is great interest in identifying novel mechanisms that govern the cardiovascular response to disease-related stress. First described in failing hearts, autophagy within the cardiovascular system has been widely characterized in cardiomyocytes, cardiac fibroblasts, endothelial cells, vascular smooth muscle cells, and macrophages. In all cases, a window of optimal autophagic activity appears to be critical to the mainte ...[more]

PMID: 25654551

Similar Datasets

Project description:The mechanisms of the control and activity of the autophagy-lysosomal protein degradation machinery are emerging as an important theme for neurodevelopment and neurodegeneration. However, the underlying regulatory and functional networks of known genes controlling autophagy and lysosomal function and their role in disease are relatively unexplored. We performed a systems biology-based integrative computational analysis to study the interactions between molecular components and to develop models for regulation and function of genes involved in autophagy and lysosomal function. Specifically, we analyzed transcriptional and microRNA-based post-transcriptional regulation of these genes and performed functional enrichment analyses to understand their involvement in nervous system-related diseases and phenotypes. Transcriptional regulatory network analysis showed that binding sites for transcription factors, SREBP1, USF, AP-1 and NFE2, are common among autophagy and lysosomal genes. MicroRNA enrichment analysis revealed miR-130, 98, 124, 204 and 142 as the putative post-transcriptional regulators of the autophagy-lysosomal pathway genes. Pathway enrichment analyses revealed that the mTOR and insulin signaling pathways are important in the regulation of genes involved in autophagy. In addition, we found that glycosaminoglycan and glycosphingolipid pathways also make a major contribution to lysosomal gene regulation. The analysis confirmed the known contribution of the autophagy-lysosomal genes to Alzheimer and Parkinson diseases and also revealed potential involvement in tuberous sclerosis, neuronal ceroidlipofuscinoses, sepsis and lung, liver and prostatic neoplasms. To further probe the impact of autophagy-lysosomal gene deficits on neurologically-linked phenotypes, we also mined the mouse knockout phenotype data for the autophagylysosomal genes and found them to be highly predictive of nervous system dysfunction. Overall this study demonstrates the utility of systems biology-based approaches for understanding the autophagy-lysosomal pathways and gaining additional insights into the potential impact of defects in these complex biological processes.

Dataset Information

Autophagy in cardiovascular biology.

Publications

Autophagy in cardiovascular biology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets