Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

O’Connor, Lois; O’Connor, B; Lim, Su Bin; Lo, Chih Hung

doi:10.1016/j.jpha.2023.06.011

Cited by 34 publications

(13 citation statements)

References 250 publications

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“…The RNA-sequencing (RNA-seq) transcriptomic dataset GSE173955 [36] was obtained from the Gene Expression Omnibus (GEO) database [37]. The 10 healthy control (HC) and 8 AD samples are from the hippocampus region of post-mortem brains with the age of the HC samples at 77.00 ± 8.50 years and AD samples at 91.75 ± 6.08 years.…”

Section: Methodsmentioning

confidence: 99%

Defective lysosomal acidification contributes to TNFR1 mediated neuronal necroptosis in Alzheimer’s disease

Lo,

Zeng,

Loi

et al. 2023

Preprint

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Background: Tumor necrosis factor (TNF) receptor 1 (TNFR1) signaling mediates neuronal necroptosis in Alzheimer's disease (AD). Interaction of TNFR1 signaling axis with autolysosomal pathway and the accumulation of necrosome molecules in impaired lysosomes have been shown to lead to necroptotic neuronal death. This has been attributed to the terminal failure of the autophagic process, primarily due to lysosomal degradation dysfunction. Being the final and determining step of the autolysosomal pathway, lysosomes with sufficient acidification as maintained by functional vacuolar (H+)-ATPase (V-ATPase) are required to achieve complete autophagic degradation of toxic cellular components. Here, we aim to investigate the role of defective lysosomal acidification in mediating TNFR1 induced neuronal necroptosis in AD. Methods: Neuropathological analysis of human post-mortem AD brains was performed to examine the correlation between TNFR1 induced neuronal necroptosis and autolysosomal dysfunction. Specifically, we probed for the level of V-ATPase subunits in AD brains to determine the extent of lysosomal acidification and function. Cell-based assays were conducted to understand the effect of TNFR1 activation in driving lysosomal acidification defect, autophagic impairment, mitochondrial dysfunction, and neuronal death in SH-SY5Y neuroblastoma cells. Furthermore, we applied lysosome-acidifying nanoparticles (AcNPs) to determine whether restoration of lysosomal acidification can rescue neuronal necroptosis in both TNF-treated SH-SY5Y cells and APP-NL-G-F knock-in mouse model of AD. Results: We revealed that TNFR1 activated neuronal necroptosis correlates with autolysosomal dysfunction as characterized by downregulation of V-ATPase subunits and accumulation of autophagy receptor p62 in human AD brains. In cell culture, we showed for the first time that lysosomal acidification is only impaired in cells treated with TNF and not with other cytokines, contributing to inhibition of autophagic degradation in SH-SY5Y cells. We also illustrated that there is defective mitochondrial turnover, together with reduced mitochondrial functions and elevated reactive oxygen species, leading to neuronal death in SH-SY5Y cells. Importantly, we demonstrated that AcNPs restore lysosomal acidification, autophagic activity, and mitochondrial function, as well as rescue neuronal necroptosis in both TNF-treated SH-SY5Y cells and APP-NL-G-F mice. Conclusions: Defective lysosomal acidification plays a key role in TNFR1 mediated neuronal necroptosis. This opens avenues for new therapeutic strategies to target lysosomal acidification dysfunction in AD.

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Section: Methodsmentioning

confidence: 99%

Defective lysosomal acidification contributes to TNFR1 mediated neuronal necroptosis in Alzheimer’s disease

Lo,

Zeng,

Loi

et al. 2023

Preprint

Self Cite

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“…The cytome can be defined as the entire collection of dynamic cellular processes, incorporating both structural and functional parameters, that form the basis of all biochemical and physiological processes in the body [ 436 , 437 , 438 ]. In the field of neurological and neuromuscular disorders, this would be a strategic step forward to evolve evidence-based medicine to the next level of stratified approaches and establish personalized medical therapies via translational neuroscience [ 439 ].…”

Section: The Pathoproteomic Profiling Of Duchenne Muscular Dystrophymentioning

confidence: 99%

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

Dowling,

Trollet,

Negroni

et al. 2024

Proteomes

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This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

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“…The future of omics analysis lies at the interface of multi-omics integration, where genomics, transcriptomics, proteomics, metabolomics, lipidomics, as well as spatial omics can be utilized simultaneously [ 180 ]. One of the main challenges of integrative approaches concerns increased dimensionality due to the increased complexity of the omics datasets associated with the biological systems.…”

Section: Summary and Future Perspectivesmentioning

confidence: 99%

“…One of the main challenges of integrative approaches concerns increased dimensionality due to the increased complexity of the omics datasets associated with the biological systems. An integrative analysis, such as independent biological integration or unsupervised machine learning, will enable the reconstruction of biological systems, with a holistic understanding of gene and protein regulation at different omic levels for translational applications [ 180 , 181 ]. Multi-omics data integration would provide a more sophisticated and accurate analysis for early disease detection (e.g., lysosomal dysfunction [ 182 , 183 ]), as well as increase precision phenotyping and personalized medicine [ 184 , 185 , 186 , 187 ].…”

Section: Summary and Future Perspectivesmentioning

confidence: 99%

Data Mining of Microarray Datasets in Translational Neuroscience

O’Connor,

Zeng

et al. 2023

Brain Sciences

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Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

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Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Cited by 34 publications

References 250 publications

Defective lysosomal acidification contributes to TNFR1 mediated neuronal necroptosis in Alzheimer’s disease

Defective lysosomal acidification contributes to TNFR1 mediated neuronal necroptosis in Alzheimer’s disease

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

Data Mining of Microarray Datasets in Translational Neuroscience

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