Reduced RNA adenosine-to-inosine editing in hippocampus vasculature associated with Alzheimer’s disease

Crooke, Philip S.; Tossberg, John T.; Heinrich, Rachel M.; Porter, Krislyn P.; Aune, Thomas M.

doi:10.1093/braincomms/fcac238

Cited by 4 publications

(2 citation statements)

References 71 publications

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“…Interestingly, in both sub-GRNs, the number of TGs that each TF controls varies to an important degree, exhibiting a scale-free like topology. The analysis of the top-10 TFs controlling the highest number of TGs, has revealed that most of these TFs have been found associated to Alzheimer disease in previous studies [ 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 ], as reported in Table 4 . The full lists of TFs belonging to both communities are reported in Table A1 .…”

Section: Resultsmentioning

confidence: 92%

Gene Self-Expressive Networks as a Generalization-Aware Tool to Model Gene Regulatory Networks

Peignier

Calevro

2023

Biomolecules

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Self-expressiveness is a mathematical property that aims at characterizing the relationship between instances in a dataset. This property has been applied widely and successfully in computer-vision tasks, time-series analysis, and to infer underlying network structures in domains including protein signaling interactions and social-networks activity. Nevertheless, despite its potential, self-expressiveness has not been explicitly used to infer gene networks. In this article, we present Generalizable Gene Self-Expressive Networks, a new, interpretable, and generalization-aware formalism to model gene networks, and we propose two methods: GXN•EN and GXN•OMP, based respectively on ElasticNet and OMP (Orthogonal Matching Pursuit), to infer and assess Generalizable Gene Self-Expressive Networks. We evaluate these methods on four Microarray datasets from the DREAM5 benchmark, using both internal and external metrics. The results obtained by both methods are comparable to those obtained by state-of-the-art tools, but are fast to train and exhibit high levels of sparsity, which make them easier to interpret. Moreover we applied these methods to three complex datasets containing RNA-seq informations from different mammalian tissues/cell-types. Lastly, we applied our methodology to compare a normal vs. a disease condition (Alzheimer), which allowed us to detect differential expression of genes’ sub-networks between these two biological conditions. Globally, the gene networks obtained exhibit a sparse and modular structure, with inner communities of genes presenting statistically significant over/under-expression on specific cell types, as well as significant enrichment for some anatomical GO terms, suggesting that such communities may also drive important functional roles.

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Section: Resultsmentioning

confidence: 92%

Gene Self-Expressive Networks as a Generalization-Aware Tool to Model Gene Regulatory Networks

Peignier

Calevro

2023

Biomolecules

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“…Conversely, ADARB1 + neurons are our only population not previously identified among AD vulnerable neurons. However, reduction in ADARB1 expression is associated with AD 58 . On the other hand, we do not find a significant reduction in total number of other neuronal subpopulations previously identified as vulnerable in AD, such as CUX2 + , PCP4 + , GPC5 + and SST + neurons 7,35,47 .…”

Section: Discussionmentioning

confidence: 98%

Intra-cellular accumulation of amyloid is a marker of selective neuronal vulnerability in Alzheimer’s disease

Caramello,

Fancy,

Tournerie

et al. 2023

Preprint

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Characterisation of vulnerable neurons that die earliest with Alzheimer’s disease (AD) could provide rationale treatment targets to slow or prevent neurodegeneration. We used imaging mass cytometry to identify the neuronal sub-types lost earliest in AD and explored associated mechanisms with paired single nuclear transcriptomics inpost-mortemmiddle temporal gyri from diseased donors. We found L5-6 RORB+and L3-6 GAD1+neurons show the greatest loss in AD. These neuronal subtypes also accumulated β-amyloids intracellularly. By contrast, pTau+tangles progressively formed in a distinct L3 RORB+GPC5+subtype that appeared resilient. Both astrocytes and microglia expressed reactive phenotype markers with AD and reactive microglia were spatially associated with vulnerable neurons. RORB+neuronal sub-types accumulating either amyloids or pTau showed increased expression of autophagy-related genes. In conclusion, we identified layer- and neuronal subtype-specific loss with AD that suggest intrinsic autophagy-related defects associated with intracellular accumulation of β-amyloids, rather than pTau, may initiate early neurodegeneration.

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Fabrication of a polymer brush-functionalized porphyrin-based covalent organic framework for enrichment of N-glycopeptides

Wang,

Zhang,

Hua

et al. 2023

Microchim Acta

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Reduced RNA adenosine-to-inosine editing in hippocampus vasculature associated with Alzheimer’s disease

Cited by 4 publications

References 71 publications

Gene Self-Expressive Networks as a Generalization-Aware Tool to Model Gene Regulatory Networks

Gene Self-Expressive Networks as a Generalization-Aware Tool to Model Gene Regulatory Networks

Intra-cellular accumulation of amyloid is a marker of selective neuronal vulnerability in Alzheimer’s disease

Fabrication of a polymer brush-functionalized porphyrin-based covalent organic framework for enrichment of N-glycopeptides

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