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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Aging Neurosci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Aging Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Aging Neurosci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1663-4365</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnagi.2025.1655660</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Gamma-aminobutyric acid associated research in Parkinson&#x2019;s disease: an exploratory trends analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Zhou</surname> <given-names>Sheng-Qiang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author"><name><surname>Liu</surname> <given-names>Fang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2400841"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Chen</surname> <given-names>Yan-Jun</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3239668"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Xie</surname> <given-names>Ming-Rong</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3049059"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label><institution>National TCM Master Liu Zuyi Inheritance Studio, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine)</institution>, <city>Changsha</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Graduate School of Hunan University of Chinese Medicine</institution>, <city>Changsha</city>, <country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>The First Clinical College of Nanjing University of Chinese Medicine</institution>, <city>Nanjing</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Ming-Rong Xie, <email xlink:href="mailto:zhousq23@stu.hnucm.edu.cn">xiemingrong1@njzyydx4.wecom.work</email>; Yan-Jun Chen <email xlink:href="mailto:msliufang23@126.com">chenyanjunyj@126.com</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-27">
<day>27</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>17</volume>
<elocation-id>1655660</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>06</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>19</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>12</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Zhou, Liu, Chen, and Xie.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Zhou, Liu, Chen, and Xie</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-27">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Parkinson&#x2019;s disease (PD) is a neurodegenerative disease characterized by the progressive loss of dopaminergic neurons. Gamma-aminobutyric acid (GABA), as a key inhibitory neurotransmitter, participates in physiological processes such as cognition and motor control by regulating the balance of neuronal excitability. Related studies have found that the GABAergic signaling abnormalities in the basal ganglia and thalamocortical circuits are closely associated with the motor dysfunction and non-motor symptoms of PD. This study aimed to analyze GABA and PD research literature to further identify hotspots, frontiers, and development directions.</p>
</sec>
<sec>
<title>Method</title>
<p>Data were obtained from the Web of Science, Scopus, and PubMed databases. VOSviewer and CiteSpace were used to visualize and perform quantitative analyses.</p>
</sec>
<sec>
<title>Results</title>
<p>From 2001 to 2024, a total of 630 publications related to GABA and PD were identified, and the annual publication count fluctuated with an overall upward trend. The United States and China contributed a large number of publications. Karolinska Institute was the leading research institution. <italic>Neuroscience</italic> published the most papers related to GABA and PD. Dr. Morari, Michele was the most prolific author. The keywords with high frequency focused on the core pathological mechanisms and the imbalance of neurotransmitters, the neural anatomical structure and functional circuits, the main research methods and models, and the treatment strategies. In recent years, &#x03B1;-synuclein, oxidative stress, and anxiety have emerged as research topics with higher burst intensity.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>This study delineates a comprehensive knowledge structure of GABA and PD research. Enhanced collaboration among authors across institutions and countries is pivotal to advancing the field. The mechanism of GABA in the basal ganglia region is a focus of current research. The detrimental effects of &#x03B1;-synuclein and oxidative stress on the GABAergic system and the non-motor symptom of anxiety are likely to be the frontiers of future research.</p>
</sec>
</abstract>
<kwd-group>
<kwd>basal ganglia</kwd>
<kwd>gamma-aminobutyric acid</kwd>
<kwd>oxidative stress</kwd>
<kwd>Parkinson&#x2019;s disease</kwd>
<kwd>&#x03B1;-synuclein</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>Natural Science Foundation Project of Changsha City</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp1">kq2208144</award-id>
</award-group>
<award-group id="gs2">
<funding-source id="sp2">
<institution-wrap>
<institution>Scientific Research Project of Hunan Provincial Health Commission</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp2">D202319019427</award-id>
</award-group>
<award-group id="gs3">
<funding-source id="sp3">
<institution-wrap>
<institution>Academic Inheritance and Communication Project of China Academy of Chinese Medical Sciences</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp3">CI2022E014XB</award-id>
</award-group>
<award-group id="gs4">
<funding-source id="sp4">
<institution-wrap>
<institution>Postgraduate Research Innovation Project of Hunan Province</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp4">CX20251165</award-id>
</award-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the 2nd Lushan Xinglin Talent Project of Hunan Academy of Chinese Medicine in 2025 (Document No. 5 [2025], Personnel Department of the Academy), The 2nd Zhaoyang Talent Project of Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine in 2024, and Hunan Furong Program&#x2014;Young Health Professionals Talent (Document No. 8 [2025], Hunan Provincial Talent Office), and the Postgraduate Research Innovation Project of Hunan Province (Grant No. CX20251165).</funding-statement>
</funding-group>
<counts>
<fig-count count="6"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="38"/>
<page-count count="10"/>
<word-count count="5740"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Cellular and Molecular Mechanisms of Brain-aging</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>Parkinson&#x2019;s disease (PD) is a neurodegenerative disorder characterized by the degeneration of dopaminergic neurons and a significant reduction in dopamine (DA) levels (<xref ref-type="bibr" rid="ref15">Kalia and Lang, 2015</xref>).</p>
<p>The motor symptoms of PD include resting tremor, rigidity, and postural instability, accompanied by non-motor symptoms such as depression, insomnia, and cognitive impairment (<xref ref-type="bibr" rid="ref2">Bloem et al., 2021</xref>). Currently, although DA replacement therapy can alleviate some symptoms, it cannot halt disease progression. Consequently, exploring novel therapeutic targets has become a research focus.</p>
<p>Gamma-aminobutyric acid (GABA), a vital inhibitory neurotransmitter, maintains the excitation-inhibition balance within neural networks by activating ionotropic GABA<sub>A</sub> receptors and metabotropic GABA<sub>B</sub> receptors (<xref ref-type="bibr" rid="ref10">Farrant and Nusser, 2005</xref>). Under physiological conditions, the GABAergic system plays a key role in regulating motor coordination, emotional stability, the sleep&#x2013;wake cycle, and cognitive memory (<xref ref-type="bibr" rid="ref11">Gerfen and Surmeier, 2011</xref>; <xref ref-type="bibr" rid="ref18">M&#x00F6;hler, 2012</xref>; <xref ref-type="bibr" rid="ref24">Saper et al., 2005</xref>; <xref ref-type="bibr" rid="ref4">Buzs&#x00E1;ki and Wang, 2012</xref>). Under pathological conditions, abnormal GABA signaling is closely associated with PD, epilepsy, Alzheimer&#x2019;s disease, and depression (<xref ref-type="bibr" rid="ref36">Wong et al., 2003</xref>; <xref ref-type="bibr" rid="ref25">Shetty and Bates, 2016</xref>).</p>
<p>Related studies have shown that GABA is implicated in the pathogenesis and symptom progression of PD. Autopsy studies of PD patients revealed degeneration of GABAergic neurons in the basal ganglia, accompanied by markedly reduced GABA levels (<xref ref-type="bibr" rid="ref12">Gerlach et al., 1996</xref>). PET imaging in early PD patients demonstrated GABAergic dysfunction in the putamen and cortical regions (<xref ref-type="bibr" rid="ref30">Takashima et al., 2022</xref>). Degeneration of dopaminergic neurons in PD leads to an imbalance within the basal ganglia-thalamocortical circuit. Within this circuit, the GABAergic system modulates the overactivity of the indirect pathway in the basal ganglia, thereby suppressing excitatory output from the thalamus to the cortex. This suppression is thought to exacerbate bradykinesia and rigidity in PD (<xref ref-type="bibr" rid="ref22">Obeso et al., 2008</xref>). Targeting GABA receptors or enhancing GABA synthesis may restore inhibitory tone and ameliorate motor symptoms. Investigating the relationship between GABA and PD could provide novel insights into the disease&#x2019;s pathogenesis and the development of targeted therapeutic strategies, potentially delaying PD progression.</p>
<p>Bibliometrics, a discipline involving the quantitative analysis of academic literature using statistical methods, reveals the developmental trajectory, research hotspots, collaboration networks, and knowledge structure of a specific field by mining information such as keywords, authors, institutions, citation networks, and temporal trends within publication data. Applying bibliometrics to explore the relationship between GABA and PD can intuitively present research focus, identify research gaps, trace collaboration networks, and provide direction for interdisciplinary research.</p>
</sec>
<sec sec-type="methods" id="sec2">
<label>2</label>
<title>Methods</title>
<sec id="sec3">
<label>2.1</label>
<title>Data search</title>
<p>Data were obtained from the Web of Science (WoS), Scopus, and PubMed databases. The search strategy employed was as follows: (i) WoS: ((TS&#x202F;=&#x202F;(gamma-aminobutyric acid)) OR TS&#x202F;=&#x202F;(4-Aminobutyric acid)) AND TS&#x202F;=&#x202F;(Parkinson&#x2019;s disease). (ii) Scopus: (([TITLE-ABS-KEY](gamma-aminobutyric acid)) OR ([TITLE-ABS-KEY]((4-Aminobutyric acid))) AND ([TITLE-ABS-KEY](Parkinson&#x2019;s disease)). (iii) PubMed: ((gamma-aminobutyric acid[Title/Abstract]) OR (4-Aminobutyric acid[Title/Abstract])) AND (Parkinson&#x2019;s disease[Title/Abstract]). The inclusion criteria were as follows: (i) Publication date from January 1, 2001, to December 31, 2024; (ii) Publication type restricted to articles and reviews; (iii) Language restricted to English. The exclusion criteria were: (i) The EndNote software eliminated duplicate publications by the same author. (ii) Exclusion of publications irrelevant to the research topic. Following the application of these criteria, 630 publications relevant to GABA and PD were identified (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Literature search and selection flowchart.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Flowchart detailing the publication selection process. Identification: 366 from Web of Science, 2,998 from Scopus, 324 from PubMed, totaling 3,688. After removing 1,968 irrelevant items, 1,720 were screened. Timeframe: January 1, 2001, to December 31, 2024; English-language articles and reviews. Screening results: 771 sought for retrieval. Endnote excluded 141 duplicates. Ultimately, 630 publications were included in the study.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec4">
<label>2.2</label>
<title>Data analysis</title>
<p>We employed the software tools VOSviewer (1.6.18) and CiteSpace (6.2.R3) to analyze annual publication trends, countries, institutions, journals, authors, and keywords. This approach is consistent with methodologies established in prior literature (<xref ref-type="bibr" rid="ref6">Chen et al., 2025</xref>). CiteSpace is a specialized tool for visualizing and mapping knowledge domains within scientific literature. It facilitates the identification of emerging research frontiers, evolutionary trends, and the dynamic patterns of disciplinary development (<xref ref-type="bibr" rid="ref5">Chen, 2004</xref>). VOSviewer is widely recognized for its intuitive visualization of co-occurrence networks. It utilizes color clustering and density views to illustrate the association strength among elements such as keywords and authors, enabling the efficient construction of data networks (<xref ref-type="bibr" rid="ref31">van Eck and Waltman, 2010</xref>).</p>
</sec>
</sec>
<sec sec-type="results" id="sec5">
<label>3</label>
<title>Results</title>
<sec id="sec6">
<label>3.1</label>
<title>Publication trends</title>
<p>A total of 630 publications related to GABA and PD were obtained. Annual publication numbers exhibited an upward fluctuation (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). Research on GABA in PD accounted for a relatively small proportion of all published PD research (<xref ref-type="fig" rid="fig2">Figure 2B</xref>). The research on GABA in PD accounted for a relatively small proportion of the PD-related studies listed in the WoS (95,413 publications) (<xref ref-type="fig" rid="fig2">Figure 2B</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Analysis of publication trends. <bold>(A)</bold> Annual number of publications on GABA and PD. <bold>(B)</bold> Proportion of research topics in PD publications.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g002.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Graph A shows the annual number of publications from 2001 to 2024, peaking at 41 in 2024. Graph B is a stacked area chart showing research areas related to Parkinson&#x2019;s disease over the same period. The dominant area from 2014 onward is Parkinson's disease, indicated in orange. Other areas such as those involving gamma-aminobutyric acid and phenolic compounds are smaller.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec7">
<label>3.2</label>
<title>Country distribution</title>
<p>The world map indicated that GABA-PD publications were concentrated in Asia and North America, with relatively few publications from South America and Africa (<xref ref-type="fig" rid="fig3">Figure 3A</xref>). In the country collaboration network, node size corresponds to publication volume, and line thickness indicates collaboration strength (<xref ref-type="fig" rid="fig3">Figure 3B</xref>). The United States and China have made significant contributions to GABA-PD research. The United States was the most active country (184 publications), followed by China (128 publications) and Italy (54 publications) (<xref ref-type="table" rid="tab1">Table 1</xref>).</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Country analysis. <bold>(A)</bold> Geographic distribution of publications. <bold>(B)</bold> International collaborative network map. The size of the nodes represents the number of publications from each country, and the lines represent the collaboration between countries.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g003.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Map in section A shows countries color-coded with numbers representing data points. Section B is a network graph showing connections between countries like USA, China, and India, with varying line thicknesses indicating interaction strength.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>The top 10 countries.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Country</th>
<th align="center" valign="top">Number of publications</th>
<th align="center" valign="top">Citations</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">1</td>
<td align="left" valign="top">USA</td>
<td align="center" valign="top">184</td>
<td align="center" valign="top">4,152</td>
</tr>
<tr>
<td align="left" valign="top">2</td>
<td align="left" valign="top">China</td>
<td align="center" valign="top">128</td>
<td align="center" valign="top">1,475</td>
</tr>
<tr>
<td align="left" valign="top">3</td>
<td align="left" valign="top">Italy</td>
<td align="center" valign="top">54</td>
<td align="center" valign="top">769</td>
</tr>
<tr>
<td align="left" valign="top">4</td>
<td align="left" valign="top">United Kingdom</td>
<td align="center" valign="top">50</td>
<td align="center" valign="top">1764</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Germany</td>
<td align="center" valign="top">41</td>
<td align="center" valign="top">1,029</td>
</tr>
<tr>
<td align="left" valign="top">6</td>
<td align="left" valign="top">France</td>
<td align="center" valign="top">39</td>
<td align="center" valign="top">699</td>
</tr>
<tr>
<td align="left" valign="top">7</td>
<td align="left" valign="top">Japan</td>
<td align="center" valign="top">36</td>
<td align="center" valign="top">663</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Canada</td>
<td align="center" valign="top">35</td>
<td align="center" valign="top">1,376</td>
</tr>
<tr>
<td align="left" valign="top">9</td>
<td align="left" valign="top">India</td>
<td align="center" valign="top">34</td>
<td align="center" valign="top">498</td>
</tr>
<tr>
<td align="left" valign="top">10</td>
<td align="left" valign="top">Sweden</td>
<td align="center" valign="top">29</td>
<td align="center" valign="top">215</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec8">
<label>3.3</label>
<title>Research institutions</title>
<p>Karolinska Institute was the most active institution (21 publications), followed by the University of Ferrara (16 publications) and Emory University (14 publications). The top 10 institutions represented three continents: North America, Europe, and Asia, encompassing six countries (<xref ref-type="table" rid="tab2">Table 2</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>The top nine institutions.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Institution</th>
<th align="center" valign="top">Documents</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">1</td>
<td align="left" valign="top">Karolinska Institute</td>
<td align="center" valign="top">21</td>
</tr>
<tr>
<td align="left" valign="top">2</td>
<td align="left" valign="top">University of Ferrara</td>
<td align="center" valign="top">16</td>
</tr>
<tr>
<td align="left" valign="top">3</td>
<td align="left" valign="top">Emory University</td>
<td align="center" valign="top">14</td>
</tr>
<tr>
<td align="left" valign="top">4(tie)</td>
<td align="left" valign="top">Xi&#x2019;an Jiaotong University</td>
<td align="center" valign="top">12</td>
</tr>
<tr>
<td align="left" valign="top">4(tie)</td>
<td align="left" valign="top">University of Toronto</td>
<td align="center" valign="top">12</td>
</tr>
<tr>
<td align="left" valign="top">6(tie)</td>
<td align="left" valign="top">Qingdao University</td>
<td align="center" valign="top">5</td>
</tr>
<tr>
<td align="left" valign="top">6(tie)</td>
<td align="left" valign="top">Shandong University</td>
<td align="center" valign="top">5</td>
</tr>
<tr>
<td align="left" valign="top">6(tie)</td>
<td align="left" valign="top">Tianjin University</td>
<td align="center" valign="top">5</td>
</tr>
<tr>
<td align="left" valign="top">6(tie)</td>
<td align="left" valign="top">University of Manchester</td>
<td align="center" valign="top">5</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec9">
<label>3.4</label>
<title>Journals</title>
<p>According to Bradford&#x2019;s law, we identified 17 core journals relevant to the topic (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). Within PD research, studies on GABA have not yet achieved wide interdisciplinary integration; the field remains predominantly centered within neurology. <italic>Neuroscience</italic> published the most articles (23 publications), followed by <italic>Movement Disorders</italic> (22 publications) and <italic>Neuropharmacology</italic> (21 publications) (<xref ref-type="fig" rid="fig4">Figure 4B</xref> and <xref ref-type="table" rid="tab3">Table 3</xref>).</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Journal analysis. <bold>(A)</bold> Core journal. <bold>(B)</bold> Journal network diagram.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g004.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Panel A shows a Bradford's Law graph illustrating core sources, with a steep decline from over 20 to 5 articles. Panel B is a colorful network map displaying interconnected scientific journal names, depicting relationships among various neuroscience-related publications.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>The top 10 journals.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Source</th>
<th align="center" valign="top">Documents</th>
<th align="center" valign="top">Citations</th>
<th align="center" valign="top">Average number of citations</th>
<th align="center" valign="top">IF</th>
<th align="center" valign="top">JCR</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">1</td>
<td align="left" valign="top">Neuroscience</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">371</td>
<td align="char" valign="top" char=".">16.13</td>
<td align="char" valign="top" char=".">2.9</td>
<td align="center" valign="top">Q2</td>
</tr>
<tr>
<td align="left" valign="top">2</td>
<td align="left" valign="top">Movement Disorders</td>
<td align="center" valign="top">22</td>
<td align="center" valign="top">356</td>
<td align="char" valign="top" char=".">16.18</td>
<td align="char" valign="top" char=".">7.4</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">3</td>
<td align="left" valign="top">Neuropharmacology</td>
<td align="center" valign="top">21</td>
<td align="center" valign="top">202</td>
<td align="char" valign="top" char=".">9.62</td>
<td align="char" valign="top" char=".">4.6</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">4</td>
<td align="left" valign="top">Journal of Neuroscience</td>
<td align="center" valign="top">17</td>
<td align="center" valign="top">391</td>
<td align="char" valign="top" char=".">23.00</td>
<td align="char" valign="top" char=".">4.4</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Experimental Neurology</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">168</td>
<td align="char" valign="top" char=".">12.00</td>
<td align="char" valign="top" char=".">4.6</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Journal of Neurochemistry</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">125</td>
<td align="char" valign="top" char=".">8.93</td>
<td align="char" valign="top" char=".">4.2</td>
<td align="center" valign="top">Q2</td>
</tr>
<tr>
<td align="left" valign="top">7</td>
<td align="left" valign="top">Neurobiology of Disease</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">332</td>
<td align="char" valign="top" char=".">27.67</td>
<td align="char" valign="top" char=".">5.1</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Brain Research</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">46</td>
<td align="char" valign="top" char=".">4.18</td>
<td align="char" valign="top" char=".">2.7</td>
<td align="center" valign="top">Q3</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Neuroscience Letters</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">207</td>
<td align="char" valign="top" char=".">18.82</td>
<td align="char" valign="top" char=".">2.5</td>
<td align="center" valign="top">Q3</td>
</tr>
<tr>
<td align="left" valign="top">10</td>
<td align="left" valign="top">Brain</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">438</td>
<td align="char" valign="top" char=".">43.80</td>
<td align="char" valign="top" char=".">11.7</td>
<td align="center" valign="top">Q1</td>
</tr>
<tr>
<td align="left" valign="top">10</td>
<td align="left" valign="top">PLoS One</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">246</td>
<td align="char" valign="top" char=".">24.60</td>
<td align="char" valign="top" char=".">2.9</td>
<td align="center" valign="top">Q2</td>
</tr>
<tr>
<td align="left" valign="top">10</td>
<td align="left" valign="top">European Journal of Neuroscience</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">343</td>
<td align="char" valign="top" char=".">34.30</td>
<td align="char" valign="top" char=".">2.7</td>
<td align="center" valign="top">Q3</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>IF, Impact Factor; JCR, Journal Citation Reports.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec10">
<label>3.5</label>
<title>Authors</title>
<p>Highly productive authors constitute a dominant force in this research field. In the author collaboration network, node size corresponds to publication volume (<xref ref-type="fig" rid="fig5">Figure 5</xref>). Dr. Morari, Michele was the most productive author (13 publications), followed by Dr. Jian Liu (12 publications) and Dr. Kjell Fuxe (10 publications) (<xref ref-type="table" rid="tab4">Table 4</xref>). These prolific authors have contributed significantly to the advancement of the field.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Author collaboration network.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g005.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Network graph depicting connections between various individuals represented as labeled nodes. Nodes are grouped by color, indicating clusters of related individuals, with lines showing the relationships. Names such as "brotchie, jonathan m." and "wang, y." appear prominently, suggesting central figures in their respective clusters.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>The top 10 authors.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Author</th>
<th align="left" valign="top">Documents</th>
<th align="left" valign="top">Country</th>
<th align="left" valign="top">Institution</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">1</td>
<td align="left" valign="top">Dr. Morari, Michele</td>
<td align="left" valign="top">13</td>
<td align="left" valign="top">Italy</td>
<td align="left" valign="top">University of Ferrara</td>
</tr>
<tr>
<td align="left" valign="top">2</td>
<td align="left" valign="top">Dr. Jian, Liu</td>
<td align="left" valign="top">12</td>
<td align="left" valign="top">China</td>
<td align="left" valign="top">Xi&#x2019;an Jiaotong University</td>
</tr>
<tr>
<td align="left" valign="top">3</td>
<td align="left" valign="top">Dr. Fuxe, Kjell</td>
<td align="left" valign="top">10</td>
<td align="left" valign="top">Italy</td>
<td align="left" valign="top">University of Ferrara</td>
</tr>
<tr>
<td align="left" valign="top">4</td>
<td align="left" valign="top">Dr. Wichmann, Thomas</td>
<td align="left" valign="top">9</td>
<td align="left" valign="top">USA</td>
<td align="left" valign="top">Emory University</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Dr. Brotchie, Jonathan M.</td>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Canada</td>
<td align="left" valign="top">Toronto Western Hospital</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Dr. Smith, Yoland</td>
<td align="left" valign="top">8</td>
<td align="left" valign="top">USA</td>
<td align="left" valign="top">Emory University</td>
</tr>
<tr>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Dr. Savasta, Marc</td>
<td align="left" valign="top">8</td>
<td align="left" valign="top">France</td>
<td align="left" valign="top">Inserm</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Dr. Kumar, Puneet</td>
<td align="left" valign="top">7</td>
<td align="left" valign="top">India</td>
<td align="left" valign="top">Maharaja Ranjit Singh Punjab Technical University</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Dr. Di Paolo, Therese</td>
<td align="left" valign="top">7</td>
<td align="left" valign="top">Canada</td>
<td align="left" valign="top">Laval University</td>
</tr>
<tr>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Dr. Singh, Shamsher</td>
<td align="left" valign="top">7</td>
<td align="left" valign="top">India</td>
<td align="left" valign="top">ISF College of Pharmacy</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec11">
<label>3.6</label>
<title>Keywords</title>
<p>High-frequency keywords reflect current research focus and enable researchers to rapidly identify core topics. Besides GABA (540 times) and PD (475 times), high-frequency keywords included animals (186 times), male (179 times), DA (174 times), glutamate (140 times), basal ganglia (131 times), metabolism (127 times), substantia nigra (98 times), subthalamic nucleus (92 times), neurons (92 times), globus pallidus (71 times), deep brain stimulation (46 times) (<xref ref-type="fig" rid="fig6">Figure 6A</xref>). Cluster #0 aged, #1: middle-aged, #2: disease model, #7: basal ganglia, #9: oxidative stress reflected the core background and pathophysiology of PD. Cluster #3: patch clamp, #4: acetylcholine, #5: 4-aminobutyric acid receptor, #8: microdialysis, #11: serotonin 1b receptor reflected the detailed research methods and complex neurotransmitter interactions. Cluster #6: levodopa, #10: safinamide, #12: gut microbiota reflected the transition from traditional treatment to cutting-edge exploration in PD (<xref ref-type="fig" rid="fig6">Figure 6B</xref>). Keyword burst refers to the sudden and significant increase in a keyword at a specific time. &#x201C;&#x03B1;-synuclein&#x201D; (2019&#x2013;2024, strength&#x202F;=&#x202F;4.92), &#x201C;anxiety&#x201D; (2020&#x2013;2024, strength&#x202F;=&#x202F;5.23), and &#x201C;oxidative stress&#x201D; (2021&#x2013;2024, strength&#x202F;=&#x202F;6.84) have exhibited high burst intensity in recent GABA-PD research (<xref ref-type="fig" rid="fig6">Figure 6C</xref> and <xref ref-type="table" rid="tab5">Table 5</xref>).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Keywords analysis. <bold>(A)</bold> Keywords network diagram. <bold>(B)</bold> Keywords cluster analysis. <bold>(C)</bold> Keywords with the strongest citation bursts.</p>
</caption>
<graphic xlink:href="fnagi-17-1655660-g006.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Diagram with three parts: A shows a network of research terms related to neuroscience, grouped by color; B displays a timeline visualization of keywords, color-coded by relevance; C lists keywords with associated years and strengths in a chart format.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Burst keywords with example citations in recent years.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Burst keywords</th>
<th align="left" valign="top">Citations</th>
</tr>
</thead>
<tbody>
<tr>
<td/>
<td align="left" valign="top">1. Cellular milieu imparts distinct pathological &#x03B1;-synuclein strains in &#x03B1;-synucleinopathies</td>
</tr>
<tr>
<td align="left" valign="top">&#x03B1;-synuclein</td>
<td align="left" valign="top">2. Trial of prasinezumab in early-stage Parkinson&#x2019;s disease</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">3. Discriminating &#x03B1;-synuclein strains in Parkinson&#x2019;s disease and multiple system atrophy</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">1. Blockade of pre- and post-synaptic GABAB receptors in the anteroventral bed nucleus of stria terminalis produces anxiolytic-like and anxiety-like effects in parkinsonian rats, respectively</td>
</tr>
<tr>
<td align="left" valign="top">anxiety</td>
<td align="left" valign="top">2. Nuclear localization of alpha-synuclein induces anxiety-like behavior in mice by decreasing hippocampal neurogenesis and pathologically affecting amygdala circuits</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">3. Blockade of pre-synaptic and post-synaptic GABAB receptors in the lateral habenula produces different effects on anxiety-like behaviors in 6-hydroxydopamine hemiparkinsonian rats</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">1. Role of GABA pathway in motor and non-motor symptoms in Parkinson&#x2019;s disease: a bidirectional circuit</td>
</tr>
<tr>
<td align="left" valign="top">oxidative stress</td>
<td align="left" valign="top">2. L-Theanine ameliorated rotenone-induced parkinsonism-like symptoms in rats</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">3. Inhibition of NADPH oxidase within midbrain periaqueductal gray decreases pain sensitivity in Parkinson&#x2019;s disease via GABAergic signaling pathway</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="sec12">
<label>4</label>
<title>Discussion</title>
<sec id="sec13">
<label>4.1</label>
<title>General information</title>
<p>From 2001 to 2024, a total of 630 publications related to GABA and PD were identified. The annual publication count exhibited an upward trend with fluctuations. The United States and China have allocated substantial funding to neuroscience and Parkinson&#x2019;s disease research, which has directly facilitated investigations into the GABAergic system. As leading contributors in the field, these nations frequently serve as central hubs in large-scale international collaborative networks, thereby reinforcing their prominent roles. Regarding global cooperation, the successful model of the Parkinson&#x2019;s Progression Markers Initiative could be leveraged to establish an international &#x201C;GABA-PD Alliance.&#x201D; Such an alliance could enable the sharing of patient biospecimen repositories with GABA-related pathological data and support multicenter, longitudinal clinical studies to elucidate dynamic changes in the GABAergic system throughout PD progression. Karolinska Institute was the leading research institution. <italic>Neuroscience</italic> published the most papers on GABA and PD. Dr. Michele Morari was the most prolific author.</p>
</sec>
<sec id="sec14">
<label>4.2</label>
<title>Hotspots and frontiers</title>
<p>High-frequency keywords directly reflect topics of widespread concern within a field and reveal current research focus. In addition to GABA and PD, high-frequency keywords included animals, male, DA, glutamate, basal ganglia, metabolism, substantia nigra (SN), subthalamic nucleus, neurons, globus pallidus (GP), and deep brain stimulation (DBS). The basal ganglia constitute a complex neural network responsible for motor control, learning, emotion regulation, and other functions. Its core nuclei include the striatum, GP, SN, and STN. These nuclei interact through both direct (promoting movement) and indirect (inhibiting movement) pathways to maintain motor balance (<xref ref-type="bibr" rid="ref38">Yelnik, 2002</xref>). The core pathology of PD involves the degeneration of dopaminergic neurons in the SN pars compacta and reduced DA levels, leading to an imbalance between the indirect and direct pathways of the basal ganglia. Excessive activity within the indirect pathway, primarily mediated by GABAergic neurons, is an important mechanism underlying the development of motor symptoms in PD (<xref ref-type="bibr" rid="ref21">Obeso et al., 2008</xref>). Glutamate, as an excitatory neurotransmitter, participates in PD progression (<xref ref-type="bibr" rid="ref1">Blandini et al., 1996</xref>). In PD, decreased GABAergic inhibition and increased glutamatergic excitation form a vicious cycle, resulting in excessive inhibition of the basal ganglia output nuclei (GPi/SNr) on the thalamus and consequent movement disorders (<xref ref-type="bibr" rid="ref34">Windels et al., 2003</xref>). DBS is an established clinical treatment for PD, and its mechanism of action may involve modulation of the STN-GPe network (<xref ref-type="bibr" rid="ref20">Noor et al., 2024</xref>).</p>
<p>Keywords such as &#x03B1;-synuclein oxidative stress and anxiety have shown a high burst intensity in recent GABA and PD research. This trend highlights the most active and highly focused core directions and emerging focus in current PD research. &#x03B1;-Synuclein is the core pathological hallmark of PD; its aggregation propagation and toxicity are central to PD pathogenesis (<xref ref-type="bibr" rid="ref37">Yaribash et al., 2025</xref>). Oxidative stress results from an imbalance between the production and clearance of reactive oxygen species within cells and is considered a key driver of neuronal death in PD (<xref ref-type="bibr" rid="ref14">Jenner, 2003</xref>). Anxiety is a common non-motor symptom in PD patients and its pathophysiological mechanisms are closely linked to neurotransmitter dysregulation and neural circuit dysfunction associated with PD (<xref ref-type="bibr" rid="ref32">Walsh and Bennett, 2001</xref>). Abnormal aggregation and propagation of &#x03B1;-synuclein can directly or indirectly induce oxidative stress which in turn exacerbates &#x03B1;-synuclein aggregation and toxicity forming a vicious cycle. The core pathological process of &#x03B1;-synuclein and oxidative stress extensively damages brain neurons and neural circuits (<xref ref-type="bibr" rid="ref29">Surmeier et al., 2017</xref>). The basal ganglia-thalamocortical circuit and GABAergic interneurons and projection neurons within the limbic system are particularly vulnerable to this damage. Dysfunction of GABAergic signaling in these circuits is regarded as a key mechanism contributing to neuropsychiatric symptoms such as anxiety in PD (<xref ref-type="bibr" rid="ref16">Li et al., 2024</xref>). These foci reflect an in-depth exploration of PD&#x2019;S pathological mechanisms. The attention paid to anxiety as a non-motor symptom indicates that it has become a clinically significant research direction in the field of PD studies. The GABAergic system plays a pivotal role in this context acting as a key link connecting upstream core pathology with downstream key clinical symptoms.</p>
</sec>
<sec id="sec15">
<label>4.3</label>
<title>Clinical research</title>
<p>In the evaluation of clinical trials targeting the GABAergic system for PD interventions, studies vary in efficacy, methodology, and clinical translational potential. A clinical trial of nabilone (<italic>n</italic> =&#x202F;7) showed that it significantly alleviated levodopa-induced dyskinesia. The mechanism may involve inhibition of GABA reuptake in the GP and enhancement of inhibitory transmission; however, this trial had a small sample size, did not assess core motor symptoms, and lacked long-term safety data (<xref ref-type="bibr" rid="ref26">Sieradzan et al., 2001</xref>). A study on the GABA<sub>A</sub> receptor antagonist flumazenil (<italic>n</italic> =&#x202F;16) reported improved motor flexibility, although without significant improvement in UPDRS-III scores. Limitations included the short duration of the single-dose effect, lack of long-term safety data, and the common adverse drug reaction of dizziness (<xref ref-type="bibr" rid="ref23">Ondo and Silay, 2006</xref>). The Zonisamide study (<italic>n</italic> =&#x202F;389) demonstrated that 50&#x202F;mg/day significantly reduced &#x201C;off&#x201D; time without increasing the risk of dyskinesia or hallucinations. However, limitations remain: Zonisamide&#x2019;s multi-target mechanism (MAO-B inhibition, calcium channel regulation) makes it difficult to attribute effects solely to a single GABAergic pathway, and the inclusion of patients already receiving combined treatments such as dopamine agonists may have weakened the observed effect (<xref ref-type="bibr" rid="ref19">Murata et al., 2015</xref>). A 4-month randomized controlled trial of the NKCC1 inhibitor bumetanide (<italic>n</italic> =&#x202F;44) showed that improvement in UPDRS-III scores during the OFF period did not differ significantly between the bumetanide and placebo groups. Furthermore, tolerance was poor, possibly due to insufficient brain penetration of the drug and systemic side effects (<xref ref-type="bibr" rid="ref7">Damier et al., 2024</xref>). A randomized, double-blind trial of probiotic-M8 combined with conventional drugs for PD treatment (<italic>n</italic> =&#x202F;82) reported significant synergistic benefits in improving non-motor symptoms and some motor functions (UPDRS-III score), with good safety. However, limitations include a small sample size, high dropout rate, inadequate analysis of the primary motor endpoint, and methodological constraints resulting in a relatively low level of evidence (<xref ref-type="bibr" rid="ref28">Sun et al., 2022</xref>). A clinical trial investigating DBS for PD provided direct neurochemical evidence for the role of the GP in human memory processing. The findings revealed the complex and specific regulatory patterns of basal ganglia circuits across different cognitive functions. In the enrolled PD patients, changes in GABA concentration within the GP were closely associated with the type of memory task performed: GABA levels increased during implicit memory tasks but decreased during explicit memory tasks (<xref ref-type="bibr" rid="ref3">Buchanan et al., 2015</xref>). However, this study had several limitations, including a small sample size (<italic>n</italic> =&#x202F;2) and the constrained temporal resolution of microdialysis technology. In a study conducted on PD patients undergoing STN-DBS treatment, brain chemical measurements revealed a significant decrease in GABA concentration in the thalamus (<xref ref-type="bibr" rid="ref27">Stefani et al., 2011</xref>). The decrease in GABA concentration reduces the inhibitory effect on the thalamus, and is considered a key event for restoring motor function and achieving clinical efficacy. Overall, current clinical evidence for GABA-targeted therapy is generally of low quality (small sample sizes, short study durations). Strategies directly targeting GABA receptors or transporters have demonstrated limited efficacy and are associated with tolerance issues. In contrast, approaches indirectly modulating the GABAergic pathway (such as probiotics regulating neurotransmitter metabolism via the microbiota-gut-brain axis) show potential for improving non-motor symptoms, but alleviation of core motor deficits still requires optimization. Future research should integrate large-sample RCTs, targeted drug delivery technologies, and multi-omics mechanistic studies to clarify the precise therapeutic role of GABAergic modulation in PD.</p>
</sec>
<sec id="sec16">
<label>4.4</label>
<title>Correlation between GABA and PD</title>
<p>GABAergic dysfunction contributes to motor symptoms in PD primarily through an imbalance in the basal ganglia&#x2019;s direct/indirect pathways, leading to excessive inhibition of GPi/SNr output (<xref ref-type="bibr" rid="ref8">DeLong and Wichmann, 2007</xref>). The successful application of GPi-targeted DBS is the most direct therapeutic manifestation of this mechanism (<xref ref-type="bibr" rid="ref33">Wichmann and DeLong, 2016</xref>). The role of GABAergic interneurons within cortical-basal ganglia-thalamus circuit microcircuits, particularly in the generation of pathological oscillations, is under active investigation. Beyond the main output nuclei, numerous GABAergic interneurons are present within basal ganglia circuits (such as striatum, GPe, and STN) as well as in related cortical and thalamic regions. These interneurons play a crucial role in fine-tuning information flow and synchronizing neuronal activities, such as the generation of &#x03B2; oscillations in local microcircuits (<xref ref-type="bibr" rid="ref9">Devergnas et al., 2014</xref>). In PD, DA deficiency may disrupt the normal function of these interneurons, leading to local network excitation-inhibition imbalance and pathological oscillations, which are closely associated with bradykinesia and rigidity (<xref ref-type="bibr" rid="ref13">Gittis et al., 2011</xref>). The specific mechanisms of the GABA system in non-motor symptoms of PD (such as depression, anxiety, cognitive impairment, sleep disorders, and comorbidities) remain insufficiently studied. GABA, as the primary inhibitory neurotransmitter in the central nervous system, is widely distributed in brain regions involved in emotion, cognition, and sleep regulation (<xref ref-type="bibr" rid="ref17">Luscher et al., 2011</xref>; <xref ref-type="bibr" rid="ref35">Winsky-Sommerer, 2009</xref>). GABAergic dysfunction (such as loss of GABAergic neurons, altered receptor expression, and abnormal signal transduction) may significantly contribute to these non-motor symptoms. An in-depth exploration of how GABAergic changes in the cortex, limbic system, and brainstem contribute to specific non-motor symptoms is crucial for developing novel therapies targeting these aspects.</p>
</sec>
<sec id="sec17">
<label>4.5</label>
<title>Challenge and opportunity</title>
<p>In GABA and PD research, challenges and opportunities coexist. GABAergic neurons in the basal ganglia are distributed across multiple nuclei, and their complex interactions complicate the precise localization of functional abnormalities. DA depletion leads to overactivity of the indirect pathway, which may exacerbate motor inhibition via GABAergic neurons; however, the specific mechanisms are not fully understood. Furthermore, animal models may not fully recapitulate changes in the human GABA system. Poor blood&#x2013;brain barrier penetration, receptor tolerance, and long-term side effects limit the clinical application of GABAergic drugs. Future validation of drug safety and efficacy requires large-scale, multi-center clinical trials. Despite the complexity of the GABA system in PD posing research challenges, emerging technologies offer broad opportunities for precision therapy development. Gene-editing technologies or viral vectors could modulate GABAergic transmission and potentially repair aberrant circuits. Combining imaging (such as PET/fMRI) or molecular markers to identify PD patient subgroups could facilitate personalized treatment.</p>
</sec>
<sec id="sec18">
<label>4.6</label>
<title>Limitations</title>
<p>In this study, only English-language publications were included during the literature search and screening process. Although this approach is common in bibliometric research to ensure data source consistency and reproducibility, it inevitably introduces a certain degree of language bias. The excluded non-English literature accounted for 8.21% of the retrieved records. Consequently, the findings and analyses presented herein primarily reflect the research landscape of GABA in PD from the perspective of international English-language journals and may not fully represent the global situation in this field. Future studies could provide a more globally representative analysis by incorporating literature from multilingual databases.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec19">
<label>5</label>
<title>Conclusion</title>
<p>This study provides a visual analysis of the role of GABA in PD research. Strengthening collaboration among institutions and countries will help advance this field. Research primarily focuses on the mechanisms and interventions related to neural circuit dysfunction in PD. &#x03B1;-synuclein, oxidative stress, and anxiety are likely to represent key research directions in the coming years.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec20">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="author-contributions" id="sec21">
<title>Author contributions</title>
<p>S-QZ: Methodology, Software, Writing &#x2013; original draft. FL: Software, Visualization, Writing &#x2013; review &#x0026; editing. Y-JC: Writing &#x2013; review &#x0026; editing, Supervision. M-RX: Writing &#x2013; review &#x0026; editing, Supervision.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors are grateful to all researchers who have published articles related to Parkinson&#x2019;s disease and gamma-aminobutyric acid research.</p>
</ack>
<sec sec-type="COI-statement" id="sec22">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec23">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec24">
<title>Publisher&#x2019;s note</title>
<p>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.</p>
</sec>
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<fn-group>
<fn fn-type="custom" custom-type="edited-by" id="fn0002">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/474954/overview">Jorge Busciglio</ext-link>, University of California, Irvine, United States</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0003">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/50042/overview">Sunil Dutt Shukla</ext-link>, Government Meera Girls College, Udaipur, India</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3102523/overview">Paul-Stefan Panaitescu</ext-link>, Iuliu Ha&#x021B;ieganu University of Medicine and Pharmacy, Romania</p>
</fn>
</fn-group>
<fn-group>
<fn fn-type="abbr" id="abbrev1">
<label>Abbreviations:</label>
<p>PD, Parkinson&#x2019;s disease; DA, Dopamine; GABA, Gamma-aminobutyric acid; WoS, Web of Science; STN, Subthalamic nucleus; SN, Substantia nigra; GP, Globus pallidus; DBS, Deep brain stimulation; avBNST, Anteroventral bed nucleus of stria terminalis.</p>
</fn>
</fn-group>
</back>
</article>