Study of the Relationship Between Astrocytes and Alzheimer’s Disease by Gene Set Enrichment Analysis Based on Single-cell RNA Sequence

doi:10.13523/j.cb.2112014

China Biotechnology

2022, Vol. 42

Issue (5): 18-26 DOI: 10.13523/j.cb.2112014

Study of the Relationship Between Astrocytes and Alzheimer’s Disease by Gene Set Enrichment Analysis Based on Single-cell RNA Sequence

QIAO Long¹,LIAO Ya-jin²,PAN Rui-yuan²,YUAN Zeng-qiang^1,^2,^**(

)

1 School of Basic Medicine, Anhui Medical University, Hefei 230032,China
2 Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China

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Abstract

Objective: To analyze the glucose metabolism pathway associated with astrocytes in Alzheimer’s disease (AD) by the bioinformatics method, and to provide a theoretical basis for revealing the glycolysis metabolism of astrocytes in the brains of AD patients. Methods: Firstly, the single-cell transcriptome data from AD patients and healthy persons were analyzed with t-distributed stochastic neighbor embedding (t-SNE); secondly, the genes differently expressed in astrocytes from AD patients and healthy persons were analyzed by Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA); lastly, the transcription cofactors related to AD were analyzed by the transcriptional regulatory network. Results: The t-SNE analysis indicated that the ratio of excitatory neurons and astrocytes was decreased in the brains of AD patients. In addition, the decreased astrocytes were characterized with RASGEF1B⁺SLC26A3⁺ or NRGN⁺CALM1⁺; GO analysis showed that differentially expressed genes were mainly related to axongenesis, neuronal migration, glial cell differentiation, zinc homeostasis, positive regulation of synaptic transmission and vascular transport. KEGG analysis showed that the differentially expressed genes were mainly related to PI3K-Akt signaling pathway, AMPK signaling pathway and calcium signaling pathway. GSEA analysis results showed that the differentially regulated genes in AD patients were enriched in glycolysis and gluconeogenesis pathway. In addition, PKM, PFKL, ACSS1 and LDHB were down-regulated in astrocytes from AD patients.Transcriptional regulatory network analysis showed that PKM,SOX2 and SOX9 were down-regulated in astrocytes from AD patients. SREBF1 and BCL6 were up-regulated in astrocytes of AD patients. Conclusion: The reduction of excitatory neurons and astrocytes in the brains of AD patients, as well as the down-regulation of the glycolysis pathway in astrocytes from the brains of AD patients, suggest that the impaired glycolysis in astrocytes could be one of the mechanisms underlying the development of AD.

Key words： PKM Alzheimer’s disease(AD) Astrocyte Glycolysis

Received: 07 December 2021 Published: 17 June 2022

ZTFLH:

Q811.4

Corresponding Authors: Zeng-qiang YUAN E-mail: zyuan620@yahoo.com

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Cite this article:

QIAO Long,LIAO Ya-jin,PAN Rui-yuan,YUAN Zeng-qiang. Study of the Relationship Between Astrocytes and Alzheimer’s Disease by Gene Set Enrichment Analysis Based on Single-cell RNA Sequence. China Biotechnology, 2022, 42(5): 18-26.

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https://manu60.magtech.com.cn/biotech/10.13523/j.cb.2112014 OR https://manu60.magtech.com.cn/biotech/Y2022/V42/I5/18

Fig.1 Cell type of identification,distribution of various cell types and heat maps of cell marker genes (a)Cell type of identification (b)Heat maps of cell marker genes

Fig.2 Distribution of various cell types and percentage of each cell type (a)Distribution of cell types in normal and Alzheimer disease patients (b)Overall cell type distribution in normal and in Alzheimer disease patients (c)Percentage of each cell type

Table1 Differential gene expression of various cell types

Fig.3 Pathway enrichment information of differential genes in astrocyte (a)Distribution of astrocytes in normal and patients with Alzheimer disease (b)Heat map of differential genes in astrocyte subsets (c)Gene ontology analysis of differential genes in astrocyte (d)Functional enrichment analysis of differential genes in astrocyte (e)Gene set enrichment analysis of differential genes in astrocyte (f)Expression levels of enriched genes

Fig.4 Transcriptional regulatory cofactors in astrocytes and their expression levels (a)Heat map of transcriptional regulators in astrocytes (b)Expression levels of transcriptional regulatory factors


[1]	Cai Z Y, Wan C Q, Liu Z. Astrocyte and Alzheimer’s disease. Journal of Neurology, 2017, 264(10): 2068-2074. doi: 10.1007/s00415-017-8593-x

[2]	Wakabayashi K, Miki Y. Deposition and clearance of β-amyloid in the brain. Brain and Nerve, 2013, 65(12): 1433-1444.

[3]	Choi S S, Lee S R, Lee H J. Neurorestorative role of stem cells in Alzheimer’s disease: astrocyte involvement. Current Alzheimer Research, 2016, 13(4): 419-427. doi: 10.2174/156720501304160314162812

[4]	Tarczyluk M A, Nagel D A, Rhein Parri H, et al. Amyloid β 1-42 induces hypometabolism in human stem cell-derived neuron and astrocyte networks. Journal of Cerebral Blood Flow and Metabolism, 2015, 35(8): 1348-1357. doi: 10.1038/jcbfm.2015.58 pmid: 25853906

[5]	Stipursky J, Romão L, Tortelli V, et al. Neuron-Glia signaling: implications for astrocyte differentiation and synapse formation. Life Sciences, 2011, 89(15-16): 524-531. doi: 10.1016/j.lfs.2011.04.005 pmid: 21569780

[6]	Carter S F, Herholz K, Rosa-Neto P, et al. Astrocyte biomarkers in Alzheimer’s disease. Trends in Molecular Medicine, 2019, 25(2): 77-95. doi: 10.1016/j.molmed.2018.11.006

[7]	Mathys H, Davila-Velderrain J, Peng Z, et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature, 2019, 570 (7761): 332-337. doi: 10.1038/s41586-019-1195-2

[8]	Zhou Y, Song W M, Andhey P S, et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nature Medicine, 2020, 26 (1): 131-142. doi: 10.1038/s41591-019-0695-9

[9]	Zhang X X, Lan Y J, Xu J Y, et al. CellMarker: a manually curated resource of cell markers in human and mouse. Nucleic Acids Research, 2018, 47(D1): D721-D728. doi: 10.1093/nar/gky900

[10]	Weise C M, Chen K W, Chen Y H, et al. Left lateralized cerebral glucose metabolism declines in amyloid-β positive persons with mild cognitive impairment. NeuroImage: Clinical, 2018, 20: 286-296. doi: 10.1016/j.nicl.2018.07.016

[11]	Croteau E, Castellano C A, Fortier M, et al. A cross-sectional comparison of brain glucose and ketone metabolism in cognitively healthy older adults, mild cognitive impairment and early Alzheimer’s disease. Experimental Gerontology, 2018, 107: 18-26. doi: S0531-5565(17)30228-0 pmid: 28709938

[12]	Arnold S E, Arvanitakis Z, Macauley-Rambach S L, et al. Brain insulin resistance in type 2 diabetes and Alzheimer disease: concepts and conundrums. Nature Reviews Neurology, 2018, 14(3): 168-181. doi: 10.1038/nrneurol.2017.185

[13]	Butterfield D A, di Domenico F, Barone E. Elevated risk of type 2 diabetes for development of Alzheimer disease: a key role for oxidative stress in brain. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, 2014, 1842(9): 1693-1706. doi: 10.1016/j.bbadis.2014.06.010

[14]	Neth B J, Craft S. Insulin resistance and Alzheimer’s disease: bioenergetic linkages. Frontiers in Aging Neuroscience, 2017, 9: 345. doi: 10.3389/fnagi.2017.00345

[15]	Haughey N J, Mattson M P. Alzheimer’s amyloid beta-peptide enhances ATP/gap junction-mediated calcium-wave propagation in astrocytes. Neuromolecular Medicine, 2003, 3(3): 173-180. pmid: 12835512

[16]	Siracusa R, Fusco R, Cuzzocrea S. Astrocytes: role and functions in brain pathologies. Frontiers in Pharmacology, 2019, 10: 1114. doi: 10.3389/fphar.2019.01114 pmid: 31611796

[17]	Siino V, Jensen P, James P, et al. Obesogenic diets cause alterations on proteins and theirs post-translational modifications in mouse brains. Nutrition and Metabolic Insights, 2021, 14: 11786388211012405.

[18]	Sultana R, Boyd-Kimball D, Cai J, et al. Proteomics analysis of the Alzheimer’s disease hippocampal proteome. Journal of Alzheimer’s Disease: JAD, 2007, 11(2): 153-164.

[19]	Meier-Ruge W, Iwangoff P, Reichlmeier K. Neurochemical enzyme changes in Alzheimer’s and Pick’s disease. Archives of Gerontology and Geriatrics, 1984, 3(2): 161-165. pmid: 6089677

[20]	Kim J, Han J, Jang Y, et al. High-capacity glycolytic and mitochondrial oxidative metabolisms mediate the growth ability of glioblastoma. International Journal of Oncology, 2015, 47(3): 1009-1016. doi: 10.3892/ijo.2015.3101

[21]	Wang F, Xu C S, Chen W H, et al. Identification of blood-based glycolysis gene associated with Alzheimer’s disease by integrated bioinformatics analysis. Journal of Alzheimer’s Disease: JAD, 2021, 83(1): 163-178.

[22]	Shindyapina A V, Komarova T V, Sheshukova E V, et al. The antioxidant cofactor alpha-lipoic acid may control endogenous formaldehyde metabolism in mammals. Frontiers in Neuroscience, 2017, 11: 651. doi: 10.3389/fnins.2017.00651 pmid: 29249928

[23]	Sathe G, Na C H, Renuse S, et al. Quantitative proteomic profiling of cerebrospinal fluid to identify candidate biomarkers for Alzheimer’s disease. PROTEOMICS - Clinical Applications, 2019, 13(4): 1800105. doi: 10.1002/prca.201800105

[24]	El Kadmiri N, Slassi I, El Moutawakil B, et al. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and Alzheimer’s disease. Pathologie-biologie, 2014, 62(6): 333-336. doi: 10.1016/j.patbio.2014.08.002

[25]	Rahman M R, Islam T, Shahjaman M, et al. Discovering biomarkers and pathways shared by Alzheimer’s disease and ischemic stroke to identify novel therapeutic targets. Medicina (Kaunas, Lithuania), 2019, 55(5): 191.

[26]	Shen L M, Chen C, Yang A C, et al. Redox proteomics identification of specifically carbonylated proteins in the hippocampi of triple transgenic Alzheimer’s disease mice at its earliest pathological stage. Journal of Proteomics, 2015, 123: 101-113. doi: 10.1016/j.jprot.2015.04.005

[27]	Butterfield D A, Halliwell B. Oxidative stress, dysfunctional glucose metabolism and Alzheimer disease. Nature Reviews Neuroscience, 2019, 20 (3): 148-160. doi: 10.1038/s41583-019-0132-6 pmid: 30737462

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