scholarly journals Functional analysis of a common BAG3 allele associated with protection from heart failure

2021 ◽  
Author(s):  
Juan A Perez-Bermejo ◽  
Luke M Judge ◽  
Christina L Jensen ◽  
Kenneth Wu ◽  
Annie Truong ◽  
...  
Keyword(s):  
Heart Failure ◽  
Protein Interaction ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Interaction Network ◽  
Dependent Manner ◽  
Protein Variant ◽  
Preferential Binding ◽  
Induced Pluripotent ◽  
Immortalized Cell

AbstractMultiple genetic association studies have correlated a common allelic block linked to the BAG3 gene with a decreased incidence of heart failure, but the molecular mechanism for such protection remains elusive. One of the variants in this allele block is coding, changing cysteine to arginine at position 151 of BAG3 (rs2234962-BAG3C151R). Here, we use induced pluripotent stem cells (iPSC) to test if the BAG3C151R variant alters protein and cellular function in human cardiac myocytes. Quantitative protein interaction network analysis identified specific changes in BAG3C151R protein interaction partners in cardiomyocytes but not in iPSCs or an immortalized cell line. Knockdown of BAG3 interacting factors in cardiomyocytes followed by myofibrillar analysis revealed that BAG3C151R associates more strongly with proteins involved in the maintenance of myofibrillar integrity. Finally, we demonstrate that cardiomyocytes expressing the BAG3C151R variant have improved response to proteotoxic stress in an allele dose-dependent manner. This study suggests that the BAG3C151R variant increases cardiomyocyte protection from stress by enhancing the recruitment of factors critical to the maintenance of myofibril integrity, hinting that this variant could be responsible for the cardioprotective effect of the haplotype block. By revealing specific changes in preferential binding partners of the BAG3C151R protein variant, we also identify potential targets for the development of novel cardioprotective therapies.

scholarly journals Heterogeneous Network Model to Identify Potential Associations Between Plasmodium vivax and Human Proteins

2020 ◽  
Vol 21 (4) ◽  
pp. 1310
Author(s):  
Apichat Suratanee ◽  
Kitiporn Plaimas
Keyword(s):  
Plasmodium Vivax ◽  
Network Model ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Heterogeneous Network ◽  
Drug Targets ◽  
Association Studies ◽  
Interaction Network ◽  
Biomedical Science ◽  
Human Malaria

Integration of multiple sources and data levels provides a great insight into the complex associations between human and malaria systems. In this study, a meta-analysis framework was developed based on a heterogeneous network model for integrating human-malaria protein similarities, a human protein interaction network, and a Plasmodium vivax protein interaction network. An iterative network propagation was performed on the heterogeneous network until we obtained stabilized weights. The association scores were calculated for qualifying a novel potential human-malaria protein association. This method provided a better performance compared to random experiments. After that, the stabilized network was clustered into association modules. The potential association candidates were then thoroughly analyzed by statistical enrichment analysis with protein complexes and known drug targets. The most promising target proteins were the succinate dehydrogenase protein complex in the human citrate (TCA) cycle pathway and the nicotinic acetylcholine receptor in the human central nervous system. Promising associations and potential drug targets were also provided for further studies and designs in therapeutic approaches for malaria at a systematic level. In conclusion, this method is efficient to identify new human-malaria protein associations and can be generalized to infer other types of association studies to further advance biomedical science.

scholarly journals Antagonism of GluK1-containing Kainate Receptors Reduces Ethanol Consumption by Modulating Ethanol Reward and Withdrawal

2021 ◽  
Author(s):  
Natalia Quijano-Carde' ◽  
Erika E. Perez ◽  
Richard Feinn ◽  
Henry R. Kranzler ◽  
Mariella De Biasi
Keyword(s):  
Association Studies ◽  
Genetic Association Studies ◽  
Ethanol Consumption ◽  
In Vivo Microdialysis ◽  
Ethanol Withdrawal ◽  
Kainate Receptors ◽  
Dependent Manner ◽  
Receptor System ◽  
Acute Ethanol

Alcohol use disorder (AUD) is a neuropsychiatric condition affecting millions of people worldwide. Topiramate (TPM) is an antiepileptic drug that has been shown to reduce ethanol drinking in humans. However, TPM is associated with a variety of adverse effects due to its interaction with many receptor systems and intracellular pathways. Thus, a better understanding of the role of TPM's main molecular targets in AUD could yield better therapeutic tools. GluK1-containing kainate receptors (GluK1*KARs) are non-selectively inhibited by TPM, and genetic association studies suggest that this receptor system could be targeted to reduce drinking in AUD patients. We examined the efficacy of LY466195, a selective inhibitor of GluK1*KAR, in reducing ethanol consumption in the intermittent two-bottle choice paradigm in mice. The effect of LY466195 on various ethanol-related phenotypes was investigated by quantification of alcohol intake, physical signs of withdrawal, conditioned place preference (CPP) and in vivo microdialysis in the nucleus accumbens. Selective GluK1*KAR inhibition reduced ethanol intake and preference in a dose-dependent manner. LY466195 treatment attenuated the physical manifestations of ethanol withdrawal and influenced the rewarding properties of ethanol. Interestingly, LY466195 injection also normalized changes in dopamine levels in response to acute ethanol in ethanol-dependent mice, but had no effect in ethanol-naive mice, suggesting ethanol state-dependent effects. The data point to GluK1*KARs as an attractive pharmacological target for the treatment of AUD.

scholarly journals Association Study based on Topological Constraints of Protein-Protein Interaction Networks

2020 ◽  
Author(s):  
Hao-Bo Guo ◽  
Hong Qin
Keyword(s):  
Association Study ◽  
Protein Interaction ◽  
Association Studies ◽  
Interaction Network ◽  
Molecular Networks ◽  
Topological Constraints ◽  
Protein Protein Interaction ◽  
Gene Sets ◽  
Z Scores ◽  
Empirical Networks

AbstractThe non-random interaction pattern of a protein-protein interaction network (PIN) is biologically informative but its potentials have not been fully utilized in omics studies. Here, we propose a network-permutation-based association study (NetPAS) method that gauges the observed interactions between two sets of genes based on the comparison between permutation null models and the empirical networks. This enables NetPAS to evaluate relationships, constrained by network topology, between gene sets related to different phenotypes. We demonstrated the utility of NetPAS in 50 well-curated gene sets and comparison of association studies using Z-scores, p-values or overrepresentations. Using NetPAS, a weighted human disease network was generated from the association scores of 19 gene sets from OMIM. We also applied NetPAS in gene sets derived from gene ontology and pathway annotations and showed that NetPAS uncovered functional terms missed by DAVID and other network-based enrichment tools. Overall, we show that NetPAS can take topological constraints of molecular networks into account and offer new perspectives than existing methods.

Sign in / Sign up

Export Citation Format

Share Document