Literature DB >> 31942999

Disruption of a RAC1-centred network is associated with Alzheimer's disease pathology and causes age-dependent neurodegeneration.

Masataka Kikuchi1, Michiko Sekiya2,3, Norikazu Hara4, Akinori Miyashita4, Ryozo Kuwano4,5, Takeshi Ikeuchi4, Koichi M Iijima2,3, Akihiro Nakaya1.   

Abstract

The molecular biological mechanisms of Alzheimer's disease (AD) involve disease-associated crosstalk through many genes and include a loss of normal as well as a gain of abnormal interactions among genes. A protein domain network (PDN) is a collection of physical bindings that occur between protein domains, and the states of the PDNs in patients with AD are likely to be perturbed compared to those in normal healthy individuals. To identify PDN changes that cause neurodegeneration, we analysed the PDNs that occur among genes co-expressed in each of three brain regions at each stage of AD. Our analysis revealed that the PDNs collapsed with the progression of AD stage and identified five hub genes, including Rac1, as key players in PDN collapse. Using publicly available as well as our own gene expression data, we confirmed that the mRNA expression level of the RAC1 gene was downregulated in the entorhinal cortex (EC) of AD brains. To test the causality of these changes in neurodegeneration, we utilized Drosophila as a genetic model and found that modest knockdown of Rac1 in neurons was sufficient to cause age-dependent behavioural deficits and neurodegeneration. Finally, we identified a microRNA, hsa-miR-101-3p, as a potential regulator of RAC1 in AD brains. As the Braak neurofibrillary tangle (NFT) stage progressed, the expression levels of hsa-miR-101-3p were increased specifically in the EC. Furthermore, overexpression of hsa-miR-101-3p in the human neuronal cell line SH-SY5Y caused RAC1 downregulation. These results highlight the utility of our integrated network approach for identifying causal changes leading to neurodegeneration in AD.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2020        PMID: 31942999      PMCID: PMC7191305          DOI: 10.1093/hmg/ddz320

Source DB:  PubMed          Journal:  Hum Mol Genet        ISSN: 0964-6906            Impact factor:   6.150


  82 in total

1.  Incipient Alzheimer's disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses.

Authors:  Eric M Blalock; James W Geddes; Kuey Chu Chen; Nada M Porter; William R Markesbery; Philip W Landfield
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-09       Impact factor: 11.205

2.  INstruct: a database of high-quality 3D structurally resolved protein interactome networks.

Authors:  Michael J Meyer; Jishnu Das; Xiujuan Wang; Haiyuan Yu
Journal:  Bioinformatics       Date:  2013-04-18       Impact factor: 6.937

Review 3.  Innate immunity in Alzheimer's disease.

Authors:  Michael T Heneka; Douglas T Golenbock; Eicke Latz
Journal:  Nat Immunol       Date:  2015-03       Impact factor: 25.606

Review 4.  Metazoan MicroRNAs.

Authors:  David P Bartel
Journal:  Cell       Date:  2018-03-22       Impact factor: 41.582

5.  Crystal structure of the Rac1-RhoGDI complex involved in nadph oxidase activation.

Authors:  S Grizot; J Fauré; F Fieschi; P V Vignais; M C Dagher; E Pebay-Peyroula
Journal:  Biochemistry       Date:  2001-08-28       Impact factor: 3.162

6.  MicroRNA-101 targets MAPK phosphatase-1 to regulate the activation of MAPKs in macrophages.

Authors:  Qing-Yuan Zhu; Qin Liu; Jian-Xia Chen; Ke Lan; Bao-Xue Ge
Journal:  J Immunol       Date:  2010-11-10       Impact factor: 5.422

7.  Labelling and optical erasure of synaptic memory traces in the motor cortex.

Authors:  Akiko Hayashi-Takagi; Sho Yagishita; Mayumi Nakamura; Fukutoshi Shirai; Yi I Wu; Amanda L Loshbaugh; Brian Kuhlman; Klaus M Hahn; Haruo Kasai
Journal:  Nature       Date:  2015-09-09       Impact factor: 49.962

8.  Genes associated with the progression of neurofibrillary tangles in Alzheimer's disease.

Authors:  A Miyashita; H Hatsuta; M Kikuchi; A Nakaya; Y Saito; T Tsukie; N Hara; S Ogishima; N Kitamura; K Akazawa; A Kakita; H Takahashi; S Murayama; Y Ihara; T Ikeuchi; R Kuwano
Journal:  Transl Psychiatry       Date:  2014-06-10       Impact factor: 6.222

9.  Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Authors:  Yingyao Zhou; Bin Zhou; Lars Pache; Max Chang; Alireza Hadj Khodabakhshi; Olga Tanaseichuk; Christopher Benner; Sumit K Chanda
Journal:  Nat Commun       Date:  2019-04-03       Impact factor: 14.919

10.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease.

Authors:  J C Lambert; C A Ibrahim-Verbaas; D Harold; A C Naj; R Sims; C Bellenguez; A L DeStafano; J C Bis; G W Beecham; B Grenier-Boley; G Russo; T A Thorton-Wells; N Jones; A V Smith; V Chouraki; C Thomas; M A Ikram; D Zelenika; B N Vardarajan; Y Kamatani; C F Lin; A Gerrish; H Schmidt; B Kunkle; M L Dunstan; A Ruiz; M T Bihoreau; S H Choi; C Reitz; F Pasquier; C Cruchaga; D Craig; N Amin; C Berr; O L Lopez; P L De Jager; V Deramecourt; J A Johnston; D Evans; S Lovestone; L Letenneur; F J Morón; D C Rubinsztein; G Eiriksdottir; K Sleegers; A M Goate; N Fiévet; M W Huentelman; M Gill; K Brown; M I Kamboh; L Keller; P Barberger-Gateau; B McGuiness; E B Larson; R Green; A J Myers; C Dufouil; S Todd; D Wallon; S Love; E Rogaeva; J Gallacher; P St George-Hyslop; J Clarimon; A Lleo; A Bayer; D W Tsuang; L Yu; M Tsolaki; P Bossù; G Spalletta; P Proitsi; J Collinge; S Sorbi; F Sanchez-Garcia; N C Fox; J Hardy; M C Deniz Naranjo; P Bosco; R Clarke; C Brayne; D Galimberti; M Mancuso; F Matthews; S Moebus; P Mecocci; M Del Zompo; W Maier; H Hampel; A Pilotto; M Bullido; F Panza; P Caffarra; B Nacmias; J R Gilbert; M Mayhaus; L Lannefelt; H Hakonarson; S Pichler; M M Carrasquillo; M Ingelsson; D Beekly; V Alvarez; F Zou; O Valladares; S G Younkin; E Coto; K L Hamilton-Nelson; W Gu; C Razquin; P Pastor; I Mateo; M J Owen; K M Faber; P V Jonsson; O Combarros; M C O'Donovan; L B Cantwell; H Soininen; D Blacker; S Mead; T H Mosley; D A Bennett; T B Harris; L Fratiglioni; C Holmes; R F de Bruijn; P Passmore; T J Montine; K Bettens; J I Rotter; A Brice; K Morgan; T M Foroud; W A Kukull; D Hannequin; J F Powell; M A Nalls; K Ritchie; K L Lunetta; J S Kauwe; E Boerwinkle; M Riemenschneider; M Boada; M Hiltuenen; E R Martin; R Schmidt; D Rujescu; L S Wang; J F Dartigues; R Mayeux; C Tzourio; A Hofman; M M Nöthen; C Graff; B M Psaty; L Jones; J L Haines; P A Holmans; M Lathrop; M A Pericak-Vance; L J Launer; L A Farrer; C M van Duijn; C Van Broeckhoven; V Moskvina; S Seshadri; J Williams; G D Schellenberg; P Amouyel
Journal:  Nat Genet       Date:  2013-10-27       Impact factor: 38.330

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  9 in total

1.  Artificial Intelligence and Circulating Cell-Free DNA Methylation Profiling: Mechanism and Detection of Alzheimer's Disease.

Authors:  Ray O Bahado-Singh; Uppala Radhakrishna; Juozas Gordevičius; Buket Aydas; Ali Yilmaz; Faryal Jafar; Khaled Imam; Michael Maddens; Kshetra Challapalli; Raghu P Metpally; Wade H Berrettini; Richard C Crist; Stewart F Graham; Sangeetha Vishweswaraiah
Journal:  Cells       Date:  2022-05-25       Impact factor: 7.666

2.  A Study on the Correlation Between Age-Related Macular Degeneration and Alzheimer's Disease Based on the Application of Artificial Neural Network.

Authors:  Meng Zhang; Xuewu Gong; Wenhui Ma; Libo Wen; Yuejing Wang; Hongbo Yao
Journal:  Front Public Health       Date:  2022-06-30

3.  Pharmacological Modulators of Small GTPases of Rho Family in Neurodegenerative Diseases.

Authors:  William Guiler; Addison Koehler; Christi Boykin; Qun Lu
Journal:  Front Cell Neurosci       Date:  2021-05-12       Impact factor: 5.505

4.  miR‑375 affects the hedgehog signaling pathway by downregulating RAC1 to inhibit hepatic stellate cell viability and epithelial‑mesenchymal transition.

Authors:  Zhiwei Liang; Jian Li; Longshuan Zhao; Yilei Deng
Journal:  Mol Med Rep       Date:  2021-01-05       Impact factor: 2.952

5.  Artificial intelligence-based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer's disease.

Authors:  Shingo Tsuji; Takeshi Hase; Ayako Yachie-Kinoshita; Taiko Nishino; Samik Ghosh; Masataka Kikuchi; Kazuro Shimokawa; Hiroyuki Aburatani; Hiroaki Kitano; Hiroshi Tanaka
Journal:  Alzheimers Res Ther       Date:  2021-05-03       Impact factor: 6.982

6.  Identification of Ferroptosis-Related Genes in Alzheimer's Disease Based on Bioinformatic Analysis.

Authors:  Ying Wang; Guohua Chen; Wei Shao
Journal:  Front Neurosci       Date:  2022-02-07       Impact factor: 4.677

7.  Application of weighted co-expression network analysis and machine learning to identify the pathological mechanism of Alzheimer's disease.

Authors:  Keping Chai; Xiaolin Zhang; Shufang Chen; Huaqian Gu; Huitao Tang; Panlong Cao; Gangqiang Wang; Weiping Ye; Feng Wan; Jiawei Liang; Daojiang Shen
Journal:  Front Aging Neurosci       Date:  2022-07-13       Impact factor: 5.702

Review 8.  Drosophila as a Model Organism to Study Basic Mechanisms of Longevity.

Authors:  Anna A Ogienko; Evgeniya S Omelina; Oleg V Bylino; Mikhail A Batin; Pavel G Georgiev; Alexey V Pindyurin
Journal:  Int J Mol Sci       Date:  2022-09-24       Impact factor: 6.208

Review 9.  GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease.

Authors:  Hanne Leysen; Deborah Walter; Bregje Christiaenssen; Romi Vandoren; İrem Harputluoğlu; Nore Van Loon; Stuart Maudsley
Journal:  Int J Mol Sci       Date:  2021-12-13       Impact factor: 5.923

  9 in total

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