Andrea Kwakowsky
Asheeta A. Prasad
Fernando Peña-Ortega
Sean Austin Ong Lim- 1Pharmacology and Therapeutics, School of Medicine, Galway Neuroscience Centre, Ollscoil na Gaillimhe - University of Galway, Galway, Ireland
- 2Department of Anatomy and Medical Imaging, Centre for Brain Research, Faculty of Medical and Health Science, University of Auckland, Auckland, New Zealand
- 3Faculty of Medicine and Health, School of Medical Sciences, University of Sydney, Sydney, NSW, Australia
- 4Departamento de Neurobiología del Desarrollo y Neurofisiología, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
- 5Neuroscience Program, College of Science and Health, DePaul University, Chicago, IL, United States
Editorial on the Research Topic
Neuronal network dysfunction in neurodegenerative disorders
The prevalence of neurodegenerative diseases is predicted to increase rapidly in the coming decades. There is a great need for therapies to prevent and/or slow the progression of these disorders as current therapies for most neurodegenerative diseases are symptomatic only. Neurodegenerative diseases such as Alzheimer's, Parkinson's, and Huntington's diseases as well as amyotrophic lateral sclerosis pose extraordinary challenges for drug development (Revi, 2020; Ferguson et al., 2022; Mead et al., 2022; Chopade et al., 2023). Several factors likely contribute to neurodegeneration, including oxidative stress, excitotoxicity, protein aggregation, vascular dysfunction, and neuroinflammation, and these processes culminate in the death of specific neuronal populations, leading to cognitive and/or motor impairments. The pathogenesis of neurodegenerative diseases is associated with significant dysfunction in multiple neurotransmitter systems, including altered levels of these neurotransmitters and the massive degeneration and remodeling of neuronal networks (Palop et al., 2006; Brichta et al., 2013; Ahmed et al., 2016; Govindpani et al., 2017; Kwakowsky et al., 2018; Yeung et al., 2021).
This editorial summarizes the contributions to the Frontiers Research Topic “Neuronal network dysfunction in neurodegenerative disorders.” The objective of this Research Topic was to bring together a cross-section of studies on the advances in human and non-human research focusing on deciphering the mechanisms of neuronal network dysfunction and exploring the use of new therapeutics with selected neuronal target specificity in neurodegenerative diseases.
For this Research Topic, we received a large number of submissions from which 10 articles by a total of 54 authors from 8 countries were published. The articles included 7 original research papers along with two systematic reviews and one multi-scale computational modeling study. These articles range from brain imaging studies performed on patients (Wei et al.; Zheng et al.) to studies exploring post-mortem anatomical changes (Mazumder et al.) and using in vitro human (Peppercorn et al.) and animal models to explore the role of neuronal networks in neurodegenerative diseases (Xie et al.) and critical review of a proposed therapeutic target (Wood et al.) and a suggested new model of disease mechanisms in PD (Muddapu et al.).
The selective loss of neurons and other mechanisms, such as abnormal expression and function of receptors and transporters, and mutations that affect their activity lead to dysfunctional network activity in neurodegenerative diseases. Importantly, the consequences of these alterations on neuronal network activity on behavior/cognition and/or motor function are not yet well-understood (Palop et al., 2006; Govindpani et al., 2017; Yeung et al., 2021; Elbasiouny, 2022). The underlying mechanisms of selective neuronal and regional vulnerability have been difficult to dissect (Surmeier et al., 2017; Giguere et al., 2018; Wang et al., 2020). Recent developments in whole-genome technologies, in vitro and in vivo disease models, and the extensive examination of anatomical, electrophysiological, and biochemical properties of vulnerable cell populations are beginning to elucidate these basic characteristics of neurodegenerative diseases. The collection of articles in this Research Topic showcases an array of tools applied to examine neuronal network dysfunction such as diffusion tensor imaging (DTI) (Huang et al.), functional and structural magnetic resonance imaging (MRI) (Wei et al.; Zheng et al.), multi-scale computational modeling (Muddapu et al.), optogenetics (Xie et al.), deep brain stimulation and post-mortem human brain analysis (Mazumder et al.), iPSc technology (Peppercorn et al.), RNA sequencing, and Sequential Window Acquisition of All Theoretical Fragment Ion Spectra-Mass Spectrometry (SWATH-MS) (Peppercorn et al.).
With respect to network dysfunction in Parkinson's Disease (PD), Muddapu et al. developed a computational model of cortico-basal ganglia networks that are strongly implicated in levodopa-induced dyskinesia (LID). The model also considers the scale at the level of oxidative stress and calcium-driven excitotoxicity. Collectively, their model proposes that neuronal cell loss in the substantia nigra pars compacta is affected differently at the terminals compared to the soma. Brain imaging techniques have also provided more insight into clinical PD. Wei et al. specifically looked at network connectivity in different presentations of PD. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has demonstrable success in improving motor symptoms in PD. The study by Zheng et al. helps to explain the neurological bases of clinical differences between the two motor subtypes of PD. Using optogenetic strategies, Xie et al. demonstrate that STN manipulation exerts behavioral effects at the level of locomotion and abnormal involuntary movements in 6-OHDA treated rats. Mazumder et al. provide evidence that DBS in humans does not exert its therapeutic benefit through minimizing neuronal cell loss, changes in astroglial cell numbers, or levels of alpha-synuclein. These studies work to highlight the circuitry involved in DBS.
Secreted amyloid precursor protein alpha (sAPPα) is a cleavage product of APP and is involved in modulating learning and memory. Previous studies proposed that it has the potential as a therapy for preventing, delaying, or even reversing Alzheimer's disease (AD). Peppercorn et al. identified a set of genes affected by sAPPα, which will aid further investigation into the mechanism of action of this neuroprotective protein. The excitatory amino acid transporter 2 (EAAT2) also appears to be a promising therapeutic target for AD. EAAT2 is the main glutamatergic transporter in the human brain and is a key regulator of normal glutamatergic metabolism and maintenance of the excitatory/inhibitory balance and network function. The systematic review by Wood et al. demonstrates that while the findings implicate EAAT2 expressional and functional alterations as key processes in AD progression, they also highlight the need for further studies to characterize EAAT2's involvement in normal physiology and disease in human tissue and to identify compounds that can act as EAAT2 neuromodulators.
Cheng et al. explored the pathophysiological mechanism of freezing of gait (FOG) in multiple system atrophy (MSA) using RS-fMRI and found that FOG is associated with centrality of the impaired thalamus network. The examination of behavioral associations and thalamocortical connectivity suggests that the non-motor circuit plays a compensatory role in MSA.
By retrospectively analyzing DTI parameters Huang et al. report that different neuroanatomical structures are affected differently by idiopathic normal pressure hydrocephalus (INPH) related to their positions in neuronal networks and characteristics, which affects the presentation of clinical symptoms and the prognosis of shunt surgery.
A systematic review by Yap et al. on spinocerebellar ataxia type 3 (SCA3) highlights the importance of evaluating the progressive changes regarding functional connectivity of the cerebellar-cerebral neuronal networks in patients. Importantly, the clinical data show that rather than individual brain regions, the connectivity between different brain regions in distributed networks may be responsible for motor and neurocognitive function in SCA3.
Recently the focus has shifted toward therapeutics which target multiple aspects of neurodegeneration to ensure future treatment success, and the targeting of specific neuronal networks offers many potential therapeutic targets (Brichta et al., 2013; Cao et al., 2018; Stoker and Barker, 2020; Ferguson et al., 2022; Mead et al., 2022). Drug designs have also shifted from treating neurodegenerative diseases at later stages of disease progression to focusing on preventive strategies at early stages of disease development (Cao et al., 2018; Stoker and Barker, 2020; Ferguson et al., 2022). Targeting neuronal dysfunction at early stages of these disorders might offer novel and more effective therapeutic options, and understanding the neuronal network dysfunction in neurodegenerative disorders will open new insights into the fundamental processes of brain circuit function and remodeling to help uncover the etiology of these intractable neurological disorders.
In conclusion, this collection of reviews and original research for this Research Topic provides new perspectives on neuronal network changes and insights toward the value of tools which can be applied to studying neurodegeneration.
Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.
Funding
We acknowledge funding support from the Alzheimer's New Zealand Charitable Trust (370836), Alzheimer's Zealand (3718869), and Freemasons New Zealand (3719321) to AK. AP was supported by the National Health and Medical Research Council to AP (APP1160412). FP-O was supported by Pappit-UNAM (IG200521) and by CONACyT (A1-S-7540).
Acknowledgments
We deeply thank all the authors and reviewers for their contribution to this Research Topic.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Ahmed, R. M., Devenney, E. M., Irish, M., Ittner, A., Naismith, S., Ittner, L. M., et al. (2016). Neuronal network disintegration: common pathways linking neurodegenerative diseases. J Neurol. Neurosurg. Psychiatry 87, 1234–1241. doi: 10.1136/jnnp-2014-308350
Brichta, L., Greengard, P., and Flajolet, M. (2013). Advances in the pharmacological treatment of Parkinson's disease: targeting neurotransmitter systems. Trends Neurosci. 36, 543–554. doi: 10.1016/j.tins.2013.06.003
Cao, J., Hou, J., Ping, J., and Cai, D. (2018). Advances in developing novel therapeutic strategies for Alzheimer's disease. Mol. Neurodegener. 13, 64. doi: 10.1186/s13024-018-0299-8
Chopade, P., Chopade, N., Zhao, Z., Mitragotri, S., Liao, R., and Chandran Suja, V. (2023). Alzheimer's and Parkinson's disease therapies in the clinic. Bioeng. Transl. Med. 8, e10367. doi: 10.1002/btm2.10367
Elbasiouny, S. M. (2022). Motoneuron excitability dysfunction in ALS: pseudo-mystery or authentic conundrum? J. Physiol. 600, 4815–4825. doi: 10.1113/JP283630
Ferguson, M. W., Kennedy, C. J., Palpagama, T. H., Waldvogel, H. J., Faull, R. L. M., and Kwakowsky, A. (2022). Current and possible future therapeutic options for Huntington's disease. J. Cent. Nerv. Syst. Dis. 14, 11795735221092517. doi: 10.1177/11795735221092517
Giguere, N., Burke Nanni, S., and Trudeau, L. E. (2018). On cell loss and selective vulnerability of neuronal populations in Parkinson's disease. Front. Neurol. 9, 455. doi: 10.3389/fneur.2018.00455
Govindpani, K., Calvo-Flores Guzman, B., Vinnakota, C., Waldvogel, H. J., Faull, R. L., and Kwakowsky, A. (2017). Towards a better understanding of GABAergic remodeling in Alzheimer's disease. Int. J. Mol. Sci. 18, 1813. doi: 10.3390/ijms18081813
Kwakowsky, A., Calvo-Flores Guzman, B., Govindpani, K., Waldvogel, H. J., and Faull, R. L. (2018). Gamma-aminobutyric acid A receptors in Alzheimer's disease: highly localized remodeling of a complex and diverse signaling pathway. Neural Regen. Res. 13, 1362–1363. doi: 10.4103/1673-5374.235240
Mead, R. J., Shan, N., Reiser, H. J., Marshall, F., and Shaw, P. J. (2022). Amyotrophic lateral sclerosis: a neurodegenerative disorder poised for successful therapeutic translation. Nat. Rev. Drug Discov. 1–28. doi: 10.1038/s41573-022-00612-2
Palop, J. J., Chin, J., and Mucke, L. (2006). A network dysfunction perspective on neurodegenerative diseases. Nature 443, 768–773. doi: 10.1038/nature05289
Revi, M. (2020). Alzheimer's disease therapeutic approaches. Adv. Exp. Med. Biol. 1195, 105–116. doi: 10.1007/978-3-030-32633-3_15
Stoker, T. B., and Barker, R. A. (2020). Recent developments in the treatment of Parkinson's disease. F1000Res 9, F1000 Faculty Rev-862. doi: 10.12688/f1000research.25634.1
Surmeier, D. J., Obeso, J. A., and Halliday, G. M. (2017). Selective neuronal vulnerability in Parkinson's disease. Nat. Rev. Neurosci. 18, 101–113. doi: 10.1038/nrn.2016.178
Wang, Z. T., Zhang, C., Wang, Y. J., Dong, Q., Tan, L., and Yu, J. T. (2020). Selective neuronal vulnerability in Alzheimer's disease. Ageing Res. Rev. 62, 101114. doi: 10.1016/j.arr.2020.101114
Keywords: neurodegeneration, neurotransmitter, neurodegenerative diseases, neuronal network remodeling, neuronal network dysfunction
Citation: Kwakowsky A, Prasad AA, Peña-Ortega F and Lim SAO (2023) Editorial: Neuronal network dysfunction in neurodegenerative disorders. Front. Neurosci. 17:1151156. doi: 10.3389/fnins.2023.1151156
Received: 25 January 2023; Accepted: 08 February 2023;
Published: 24 February 2023.
Edited by:
Victor Tapias, Cornell University, United StatesReviewed by:
Carmen Castro, Universidad de Cádiz, SpainSavina Apolloni, University of Rome Tor Vergata, Italy
Copyright © 2023 Kwakowsky, Prasad, Peña-Ortega and Lim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Andrea Kwakowsky, 
YS5rd2Frb3dza3kmI3gwMDA0MDthdWNrbGFuZC5hYy5ueg==