Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach

Ni, Qi; Su, Xiuqin; Chen, Jingqi; Tian, Weidong

doi:10.1155/2015/432012

Cited by 8 publications

(5 citation statements)

References 45 publications

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“…alh-12 is an aldehyde dehydrogenase, which is upregulated in long-lived C. elegans mutants [ 60 ]. The human homologue, ALDH9A1, has not been experimentally linked with HD, however a meta-analysis of pathways affected in HD predicted that ALDH9A1 is important for HD as it is involved in multiple metabolic pathways that are affected in HD [ 61 ].…”

Section: Discussionmentioning

confidence: 99%

Targeting Mitochondrial Network Disorganization is Protective in C. elegans Models of Huntington’s Disease

Machiela¹,

Rudich²,

Traa³

et al. 2021

Aging and disease

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Huntington’s disease (HD) is an adult-onset neurodegenerative disease caused by a trinucleotide CAG repeat expansion in the HTT gene. While the pathogenesis of HD is incompletely understood, mitochondrial dysfunction is thought to be a key contributor. In this work, we used C. elegans models to elucidate the role of mitochondrial dynamics in HD. We found that expression of a disease-length polyglutamine tract in body wall muscle, either with or without exon 1 of huntingtin, results in mitochondrial fragmentation and mitochondrial network disorganization. While mitochondria in young HD worms form elongated tubular networks as in wild-type worms, mitochondrial fragmentation occurs with age as expanded polyglutamine protein forms aggregates. To correct the deficit in mitochondrial morphology, we reduced levels of DRP-1, the GTPase responsible for mitochondrial fission. Surprisingly, we found that disrupting drp-1 can have detrimental effects, which are dependent on how much expression is decreased. To avoid potential negative side effects of disrupting drp-1 , we examined whether decreasing mitochondrial fragmentation by targeting other genes could be beneficial. Through this approach, we identified multiple genetic targets that rescue movement deficits in worm models of HD. Three of these genetic targets, pgp-3, F25B5.6 and alh-12 , increased movement in the HD worm model and restored mitochondrial morphology to wild-type morphology. This work demonstrates that disrupting the mitochondrial fission gene drp-1 can be detrimental in animal models of HD, but that decreasing mitochondrial fragmentation by targeting other genes can be protective. Overall, this study identifies novel therapeutic targets for HD aimed at improving mitochondrial health.

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Section: Discussionmentioning

confidence: 99%

Targeting Mitochondrial Network Disorganization is Protective in C. elegans Models of Huntington’s Disease

Machiela¹,

Rudich²,

Traa³

et al. 2021

Aging and disease

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“…Studies included HD cells and brains harvested from mouse models and postmortem HD brain tissues (6,(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33). Several studies have characterized transcriptional dysregulation in HD from the network perspective (34)(35)(36)(37)(38)(39). More recently, changes in the microRNA class of noncoding RNAs have been evaluated (29,36,(40)(41)(42)(43).…”

Section: Introductionmentioning

confidence: 99%

Transcriptome sequencing reveals aberrant alternative splicing in Huntington's disease

et al. 2016

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Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by a CAG expansion in the gene-encoding Huntingtin (HTT). Transcriptome dysregulation is a major feature of HD pathogenesis, as revealed by a large body of work on gene expression profiling of tissues from human HD patients and mouse models. These studies were primarily focused on transcriptional changes affecting steady-state overall gene expression levels using microarray based approaches. A major missing component, however, has been the study of transcriptome changes at the post-transcriptional level, such as alternative splicing. Alternative splicing is a critical mechanism for expanding regulatory and functional diversity from a limited number of genes, and is particularly complex in the mammalian brain. Here we carried out a deep RNA-seq analysis of the BA4 (Brodmann area 4) motor cortex from seven human HD brains and seven controls to systematically discover aberrant alternative splicing events and characterize potential associated splicing factors in HD. We identified 593 differential alternative splicing events between HD and control brains. Using two expanded panels with a total of 108 BA4 tissues from patients and controls, we identified four splicing factors exhibiting significantly altered expression levels in HD patient brains. Moreover, follow-up molecular analyses of one splicing factor PTBP1 revealed its impact on disease-associated splicing patterns in HD. Collectively, our data provide genomic evidence for widespread splicing dysregulation in HD brains, and suggest the role of aberrant alternative splicing in the pathogenesis of HD.

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“…Path length between nodes has been used as a method to understand the interaction between nodes in biological networks, such as in cases of metabolic genes’ shortest path lengths to disease genes being a good marker of the likelihood that the gene is a biomarker for the disease(Ni et al 2015). In this study, path length was used as the basis to group microbes based on and identify differences in hallmarks by comparing the group sizes.…”

Section: Methodsmentioning

confidence: 99%

MoMA: Large scale network model of Microbes, Metabolites and Aging hallmarks

Menon,

Bapatdhar,

Kumar

et al. 2023

Preprint

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The gut microbiome is known to be a driver of age-related health decline. Various studies have shone light on the role of the gut microbiome as a marker as well as modulator of aging processes. However, the mechanisms by which the microbiome affects aging are still unclear. We have developed a Microbiome Metabolite Aging (MMA) fusion network by building upon a metabolic interaction network of gut microbiota to develop associations with the hallmarks of aging. The MMA, consisting of 238 metabolite-aging hallmark interactions serves as a tool to investigate the mammalian (and in particular human) gut microbiome as an effector of aging at a systems-level. The network further identifies 249 microbes that unequivocally affect the hallmarks of aging. The results highlight how the underlying biology of microbial metabolite mediated interactions, in conjunction with the topological properties at a network level, differentially regulate the aging hallmarks. This detailed microbial and metabolite association to the hallmarks of aging provides a foundational model which is envisaged to be instrumental in advancing our knowledge of the physiology of aging, and for the development of novel therapeutic tools.

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Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach

Cited by 8 publications

References 45 publications

Targeting Mitochondrial Network Disorganization is Protective in C. elegans Models of Huntington’s Disease

Targeting Mitochondrial Network Disorganization is Protective in C. elegans Models of Huntington’s Disease

Transcriptome sequencing reveals aberrant alternative splicing in Huntington's disease

MoMA: Large scale network model of Microbes, Metabolites and Aging hallmarks

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