From Bibliometrics to Preliminary Clinical Evidence: TRP Channel-Mediated Neuroimmune Crosstalk in Temperature-Sensitive Airway Hyperresponsiveness

Abstract

Introduction

Temperature variability is a critical environmental trigger for airway hyperresponsiveness (AHR); however, the specific neuroimmune mechanisms linking thermal stress to respiratory inflammation remain underexplored.

Methods

We integrated a macroscopic bibliometric analysis of the global literature (1925–2024) with an exploratory clinical validation. To corroborate emergent bibliometric trends, nasal mucosal biopsies were collected from patients with temperature-sensitive AHR (n=9) and normal controls (NC, n=9). The localized expression of transient receptor potential (TRP) channels (TRPV1, TRPM8, and TRPA1) was evaluated using reverse transcription-quantitative PCR (RT-qPCR) and semi-quantitative immunohistochemistry (IHC). Furthermore, local neuroimmune interactions were assessed by evaluating the spatial co-localization of TRP channels with substance P (SP) via immunofluorescence (IF) and semi-quantitative analysis.

Results

Bibliometric mapping revealed a progressive paradigm shift from broad epidemiological associations toward specific molecular mechanisms, identifying TRP channels as central research hotspots. In the exploratory clinical cohort, both RT-qPCR and IHC analyses confirmed that TRPV1, TRPM8, and TRPA1 were significantly upregulated in the nasal mucosa of AHR patients compared to controls (all FDR-adjusted q < 0.05, supported by large effect sizes). Additionally, IF imaging demonstrated robust spatial co-localization of these overexpressed TRP channels with SP, structurally supporting the presence of local neurogenic inflammation.

Conclusion

By bridging bibliometric trends with experimental corroboration, this study highlights TRP channels as pivotal “thermosensory switches” in AHR neuroimmune crosstalk. These findings provide preliminary clinical evidence that TRP-mediated pathways may drive the transition from external thermal fluctuations to mucosal inflammatory cascades. Given the exploratory nature of the current cohort size, our results offer a targeted biomolecular framework for future large-scale investigations into climate-sensitive respiratory diseases.

Introduction

Environmental thermal variability is increasingly recognized as a major determinant of global respiratory morbidity.¹ While prolonged exposure to climatic extremes has well-documented systemic impacts, acute temperature fluctuations act as specific environmental stressors that disrupt airway homeostasis. Given the escalating frequency of erratic climate events, delineating the exact respiratory risks of thermal stress is a clinical imperative.

Exposure to temperatures outside the physiological thermoneutral zone routinely triggers or exacerbates respiratory pathology, particularly in susceptible populations. This is highly evident in conditions defined by airway hyperresponsiveness (AHR)—including bronchial asthma (BA), allergic rhinitis (AR), and vasomotor rhinitis (VMR).² These disorders share a core pathophysiological trait: an exaggerated local response to thermal stimuli that presents as bronchoconstriction, nasal congestion, and mucosal hypersecretion.³ Yet, despite clear epidemiological links between temperature shifts and AHR exacerbations, the specific neuroimmune trajectories bridging physical thermal sensing to mucosal inflammation remain incompletely characterized.⁴

Within the upper respiratory tract, this thermal sensitivity typically manifests as nasal hyperreactivity (NHR). Provocation with cold dry air (CDA) serves as a validated diagnostic standard for this phenotype,^5,6 while instruments like the Subjective Cold Hyperresponsiveness (SCH) questionnaire are used to quantify patient-specific severity. Recent molecular investigations, utilizing a combination of TRP mRNA quantification, neuropeptide profiling, and functional calcium imaging, have confirmed altered TRP channel expression and sensory nerve activation in patients with NHR.⁷ Temperature-induced AHR is now understood not as a simple physical reflex, but as a coordinated response mediated by discrete “neuroimmune units” at mucosal barriers. Thermosensitive Transient Receptor Potential (TRP) channels operate as the primary transducers at this interface, converting environmental thermal cues into active biological signals.⁸

Once activated, TRP channels trigger the local release of potent neuropeptides, including Substance P (SP), calcitonin gene-related peptide (CGRP), and neuromedin U (NMU). NMU, in particular, directly activates group 2 innate lymphoid cells (ILC2s) to amplify allergic airway inflammation, illustrating the extensive downstream reach of this neuroimmune crosstalk.^9–11 Translating these molecular sensors into viable therapeutics, however, has proven difficult. The TRPV1 antagonist SB-705498 successfully inhibited capsaicin-induced NHR but failed to show clinical efficacy in seasonal allergic rhinitis trials.^12–14 TRPM8 currently lacks successful clinical validation in airway disease, though the novel TRPA1 inhibitor GDC-0334 has demonstrated promising target engagement in early-phase studies.¹⁵ This stark divergence between robust molecular target validation and stalled clinical translation highlights a critical knowledge gap. Because the existing literature on these neuroimmune pathways is vast yet highly fragmented, piecing together a holistic understanding of temperature-sensitive AHR remains a major challenge.

To systematically map this conceptual landscape, we applied a bibliometric approach to evaluate global research trajectories in temperature-sensitive AHR. Rather than relying exclusively on macroscopic literature trends, we anchored these computational findings with orthogonal molecular (RT-qPCR) and structural (immunofluorescence) data derived from a strictly phenotyped, non-allergic clinical cohort. By bridging in silico thematic mapping with targeted ex vivo observations, this study provides preliminary evidence supporting the local upregulation of TRP-mediated neuroimmune units. Ultimately, these localized structural and transcriptional insights offer a grounded baseline to guide future definitive functional investigations.

Materials and Methods

Data Retrieval Strategy

In strict accordance with the Bibliometric and Scientometric Evaluation in Research (BIBLIO) reporting guidelines, we performed a comprehensive literature search within the Web of Science Core Collection (WoSCC), specifically utilizing the SCI-E and SSCI databases. To preclude data discrepancies arising from continuous index updates, all retrievals were executed on a single day (December 31, 2024). Our strategy captured the intersection of AHR and thermal stress using the following comprehensive query: ALL=(“Airway Hyperreactivity” OR “Asthma” OR “Exercise-induced asthma” OR “Exercise-Induced Bronchoconstriction” OR “Nonspecific nasal hyperreactivity” OR “Allergic Rhinitis” OR “Non-Allergic Rhinitis” OR “Vasomotor Rhinitis” OR “Cold-air inducing rhinitis” OR “Climate and Respiratory Health” OR “Cough” OR “Cold-Induced Cough” OR “Sneezing” OR “Temperature-triggered sneezing”) AND ALL=(“Temperature change” OR “Temperature variations” OR “Cold dry air” OR “Cold stimulation” OR “Heat exposure” OR “Environmental temperature” OR “Cold-induced bronchoconstriction” OR “Temperature-induced airway response” OR “Thermal stress” OR “Temperature sensitivity” OR “Cold air exposure”).

Following initial data acquisition, two investigators manually screened the abstracts and full texts. To ensure stringent screening accuracy, any discrepancies during the dual-review process were immediately discussed and resolved via joint consensus, with complex cases adjudicated by the senior author. Because all disagreements were resolved in real-time to reach a 100% unified consensus, a post-hoc inter-rater reliability statistic (such as Cohen’s κ) was not calculated. This rigorous, consensus-based triage yielded a final cohort of 4115 valid documents, as detailed in a PRISMA-style flow diagram (Supplementary Figure 1).

Although databases like Scopus offer broader citation coverage for non-English clinical literature, we strategically restricted our analysis to the WoSCC. This constraint was essential to maintain the standardized metadata compatibility required for CiteSpace’s high-fidelity co-citation and burst detection algorithms—effectively bypassing the technical artifacts and data attrition inherent to merging disparate database formats.

Bibliometric Analysis and Visualization

Eligible records were exported with complete bibliographic metadata and cited references. For scientometric mapping and data visualization, we integrated CiteSpace (version 6.2.R4) with the bibliometrix package in R. CiteSpace was primarily deployed to model multi-level collaborative networks—spanning countries, institutions, and authors—and to execute co-citation and keyword co-occurrence analyses.

To guarantee methodological reproducibility, we strictly standardized the CiteSpace configurations. Parameters included 1-year time slices, a g-index node selection criterion (with scaling factor κ= 25), and a default burst detection γ threshold of 1.0, with network topologies streamlined via the “Pathfinder” and “pruning sliced networks” algorithms. Together, these computational frameworks delineated the conceptual structure and evolutionary trajectory of the field.^16,17 Annual publication dynamics were subsequently quantified using Microsoft Excel, capturing the historical expansion of research at the intersection of thermal stress and AHR.

Targeted Literature Review

Relying exclusively on raw citation metrics inherently skews literature selection toward older canonical studies, risking the omission of critical recent advancements. To circumvent this chronological bias and address the limitations of pure bibliometrics, we adopted a hybrid curation strategy. To systematically capture recent high-impact work, we manually queried PubMed and Scopus (2019–2024) using targeted inclusion criteria focusing on “TRP channel antagonists”, “clinical trials”, and “multimodal nasal hyperreactivity”. Articles were included if they provided direct clinical or translational evidence regarding TRP-mediated airway disease. By integrating seminal bibliometric milestones with these manually selected contemporary studies, we captured both established paradigms and the current clinical vanguard. Accordingly, recent pivotal investigations—such as the multimodal clinical profiling of nasal hyperreactivity and early-phase TRP inhibitor trials—were systematically incorporated.^7,18 This balanced synthesis seamlessly bridges historical foundations with cutting-edge therapeutic developments, providing a robust theoretical framework to contextualize our experimental hypothesis.

Experimental Validation

Study Participants and Ethical Approval

A total of 18 adult subjects (aged 18–70 years) were enrolled and stratified equally into a temperature-sensitive AHR cohort (n = 9) and a normal control (NC) group (n = 9).

Inclusion Criteria: Eligibility for the AHR cohort required a minimum 12-week history of chronic nasal symptoms directly provoked by thermal fluctuations. Diagnostic thresholds mandated a Total Nasal Symptom Score (TNSS) ≥6, accompanied by at least two primary complaints (rhinorrhea, paroxysmal sneezing, nasal congestion, or pruritus). To rigorously exclude atopic confounders, all AHR patients had to demonstrate negative profiles on both skin prick tests and serum allergen-specific IgE assays. Furthermore, phenotypic sensitivity to cold air was quantified using the Subjective Cold Hyperresponsiveness (SCH) questionnaire^19,20 (Supplementary Table 1). The NC cohort comprised individuals undergoing concurrent structural nasal surgeries (eg, septoplasty or nasal bone fracture reduction) who possessed an unremarkable history of allergic or respiratory pathologies, corroborated by negative specific-IgE profiles. To minimize the potential confounding effects of acute surgical trauma or structural inflammation on local TRP expression, all control mucosal biopsies were meticulously harvested from macroscopically healthy, non-inflamed regions distant from the primary site of structural deviation or fracture.

Exclusion Criteria: To mitigate baseline confounding, individuals were excluded from either cohort if they presented with: (1) acute rhinitis or sinusitis within 30 days prior to screening; (2) chronic rhinosinusitis or asthma; (3) severe systemic, autoimmune, or psychiatric comorbidities; or (4) current pregnancy or lactation.

Ethical Considerations: The study protocol (ID: 2022/YX/236) was approved by the Institutional Review Board of the Second Hospital of Shanxi Medical University, adhering strictly to the Declaration of Helsinki. All participants were fully informed of the study’s purpose and procedures prior to providing their written informed consent.

RNA Extraction and Reverse Transcription-Quantitative PCR (RT-qPCR)

To validate the molecular expression of TRP channels, total RNA was extracted from freshly collected nasal mucosal biopsies using TRIzol reagent (Invitrogen, USA) according to the manufacturer’s instructions. RNA concentration and purity were assessed using a NanoDrop ND-2000 spectrophotometer (Thermo, USA). Subsequently, 1 μg of total RNA was reverse-transcribed into cDNA using PrimeScript RT Master Mix (TaKaRa, China). Quantitative PCR was performed on an ABI PRISM 7500 Sequence Detection System (Applied Biosystems) using SYBR Premix Ex Taq (TaKaRa, China). Relative mRNA expression levels of TRPV1, TRPM8, and TRPA1 were normalized to the endogenous control gene 18S and calculated using the 2^−ΔΔCt method. All reactions were performed in triplicate, and target genes along with 18S were assayed within distinct wells. The RT-qPCR primers used in this study were designed and synthesized by Sangon Biotech (Shanghai, China) and underwent specificity validation via the NCBI Basic Local Alignment Search Tool (BLAST). The specific primer sequences (5’→3’) are detailed in Supplementary Table 2.

Histopathological and Immunofluorescence Evaluations

To evaluate the spatial expression profiles of thermosensitive channels (TRPV1, TRPM8, and TRPA1), immunohistochemical (IHC) staining was performed on fixed, paraffin-embedded nasal mucosal biopsies (4μm sections). Following deparaffinization and rehydration, specific antigen retrieval and sequential IHC visualization procedures were executed following our previously established protocols.²¹ To ensure reproducibility, specific primary antibodies for TRPV1 (Catalog # SAB5700857, Sigma-Aldrich, St. Louis, MO, USA; RRID: AB_3683649; dilution 1:200), TRPM8 (Catalog # SAB2104241, Sigma-Aldrich, St. Louis, MO, USA; RRID: AB_10668145; dilution 1:500), TRPA1 (Catalog # SAB2105082, Sigma-Aldrich, St. Louis, MO, USA; RRID: AB_10670056; dilution 1:500) were utilized.^22,23 Negative controls were routinely incorporated in all staining batches. This was achieved by substituting the primary antibody with phosphate-buffered saline (PBS), which consistently yielded a complete absence of immunoreactivity (Supplementary Figure 2A). To ensure objectivity, the average optical density (AOD) of the staining was quantified using ImageJ software (NIH, Bethesda, MD, USA) by two independent pathologists who were strictly blinded to the subjects’ clinical groupings. Any discrepancies in the initial evaluations were resolved through joint review and consensus to establish the final AOD values.

For the assessment of neuroimmune co-localization, immunofluorescence (IF) assays were conducted. Serial 5μm mucosal sections were fixed in 4% paraformaldehyde for 15 min at room temperature. Following the blockade of non-specific binding sites using normal goat serum (10 min at 37°C in a humidified chamber), the samples were incubated overnight at 4°C with target-specific primary antibodies against SP (Catalog # ab14184, Abcam, Cambridge, MA, USA; RRID: AB_300971; dilution 1:500) and the respective TRP channels. After rigorous washing with PBS, the sections were incubated with Alexa Fluor 488- and Alexa Fluor 594-conjugated secondary antibodies for 2 h at room temperature, protected from light. To rigorously rule out spectral bleed-through artifacts and tissue autofluorescence, both no-primary-antibody controls and single-stain controls were processed in parallel and imaged under identical exposure parameters (Supplementary Figure 2B). Nuclear counterstaining and slide mounting were accomplished using a DAPI-containing medium (Invitrogen, P36962). To quantify the degree of co-localization, Pearson’s correlation coefficient (PCC), Mander’s overlap coefficients (M1 and M2), and Spearman’s rank correlation coefficient were calculated using a custom pipeline implemented in Python (version 3.12) with OpenCV (version 4.11) and SciPy libraries. Costes’ automatic thresholding was applied to distinguish true co-localized signals from background noise, and statistical significance was assessed through iterative randomization (100 iterations).

Statistical Methods

Data analysis and visualization were conducted utilizing GraphPad Prism (v9.0) and IBM SPSS Statistics (v20.0). Continuous variables were initially assessed for normality using the Shapiro–Wilk test. Parametric baseline clinical characteristics are presented as mean ± standard deviation (SD) and were evaluated via independent Student’s t-tests. However, given the sample size (n=9 per group) and the skewed distribution characteristics of specific datasets (including clinical symptom scores, relative mRNA expression, and semi-quantitative IHC), these results are presented as medians with interquartile ranges (IQR) and were analyzed using the non-parametric Mann–Whitney U-test.

To ensure statistical rigor, we applied several additional parameters. First, to account for multiple comparisons across primary outcomes, P-values were adjusted using the Benjamini-Hochberg False Discovery Rate (FDR) procedure. Second, effect sizes were calculated to estimate the magnitude of differences, utilizing Cohen’s d for parametric data and the rank-biserial correlation for non-parametric datasets. Third, 95% confidence intervals (CIs) for the differences are reported alongside the test statistics. Finally, a post-hoc power analysis was incorporated, confirming that the current cohort size provided adequate statistical power (>80%, alpha=0.05) to detect the substantial differences observed in our orthogonal validations. A two-sided P-value (or FDR-adjusted Q-value) < 0.05 was considered statistically significant.

Results

General Data and Annual Output

Our WoSCC retrieval yielded 4115 articles matching the inclusion criteria for temperature-sensitive AHR between 1925 and 2024. Publication volume surged notably from 2019 to a peak of 315 articles in 2021 (Figure 1C), reflecting an intensifying academic mandate to decode how thermal fluctuations drive airway hyperreactivity.

Figure 1.

Global Trends and Collaborations in AHR and Temperature Variations Research. (A) The national distribution density map. (B) The country collaboration map. (C) Annual trends in the number of new publications. Note: The apparent decline in 2024 is an artifact of incomplete database indexing up to our retrieval date (December 31, 2024). (D) Co-operation among countries. (E) Cumulative annual number of published research articles by the top five contributing countries.

Country/Region Distribution and Cooperation Network

Original research dominated the retrieved corpus (n = 3700, 89.92%), supplemented primarily by review articles and conference proceedings (Supplementary Table 3). Geographically, the United States emerged as the principal contributor (n = 1756, 38.67%), followed by China (14.17%), the United Kingdom (8.09%), Canada (4.91%), and Australia (4.89%) (Figure 1A). The historical publication trajectories of these top five nations underscore their sustained dominance and expanding output in this domain (Figure 1E).

Mapping global collaboration generated a network of 135 nodes and 1066 links (density = 0.1179; Figure 1B). Within this framework, the United States (0.71), China (0.20), and Australia (0.13) exhibited the highest centrality scores, functioning as essential conduits for transnational research. Beyond the particularly robust bilateral ties between the US and China, a broader consortium of critical hubs—including the UK, Italy, South Korea, Germany, and India—sustains a highly active and integrated worldwide research partnership (Figure 1D).

Research Contributions and Collaboration Dynamics

At the institutional level, Harvard University emerged as the most prolific contributor (n = 120, 2.92%), closely followed by the University of California System (n = 94, 2.28%). The remainder of the top ten—predominantly concentrated across North America and Europe—each produced fewer than 65 articles, individually representing under 2% of the total corpus (Supplementary Table 4). Institutional collaboration mapping (811 nodes, 1616 links; density = 0.0049) highlighted Harvard (centrality = 0.11), the University of London (0.06), and the UC System (0.04) as central bridging hubs that orchestrate global research networks (Figure 2A). Among individual authors, Dan Norbäck led the field with 44 publications, preceding Chan Lu (n = 28) and E.R. McFadden (n = 24) (Supplementary Table 5). The corresponding co-authorship network (1406 nodes, 1717 links; density = 0.0017) delineates the distinct collaborative clusters anchored by these prominent investigators (Figure 2B).

Figure 2.

Co-operation networks among institutions and authors. (A) Network visualization of institutional collaborations. (B) Network visualization of author collaborations. The size of the nodes represents the publication volume (or frequency of co-occurrence). The connecting lines between nodes indicate collaborative relationships, while the colors correspond to different publication timeframes.

Journals and Dual-Overlay Map of Journals

Publication outlet analysis identified the European Respiratory Journal as the leading venue (n = 81, 1.97%), flanked tightly by Science of the Total Environment (n = 79, 1.92%) and Environmental Research (n = 77, 1.87%). Collectively, the ten most active journals—each publishing over 50 articles—serve as the primary platforms disseminating research in this domain (Supplementary Table 6).

A dual-map overlay visually captures the interdisciplinary complexity of temperature-AHR research (Figure 3), revealing six principal citation trajectories. These pathways are fundamentally anchored in veterinary/animal sciences, environmental science, molecular biology, immunology, and clinical medicine. Yellow trajectories delineate the intersection of environmental and animal sciences, contextualizing the broad ecological footprint of thermal stress. More critically, orange pathways connecting molecular biology, immunology, and genetics underscore a profound mechanistic pivot toward identifying the cellular transducers of temperature-induced AHR. Meanwhile, green trajectories bridge environmental science with clinical medicine, emphasizing the direct translational impact of climate variability on respiratory outcomes. Ultimately, these citation dynamics illustrate the field’s maturation into a highly integrated discipline that seamlessly merges macroscopic environmental exposures with microscopic molecular mechanisms.

Figure 3.

Dual-map overlay of journals illustrating the interdisciplinary knowledge flow in temperature-sensitive AHR research. To easily interpret this map: (1) The left side represents the citing journals (active research fronts), indicating the disciplines where the current articles are published. (2) The right side represents the cited journals (intellectual base), indicating the foundational disciplines from which the references are drawn. (3) The colored curves in the middle are citation paths, visually tracing the trajectory of knowledge flow from foundational fields (right) to current active research (left). (4) The size of the nodes (ellipses) reflects the volume of publications or citations within that specific discipline. For instance, the prominent thick paths (eg, yellow and green lines) demonstrate that current clinical and molecular studies (left) draw heavily upon foundational knowledge from genetics, biology, and health sciences (right).

Keyword Trends and Research Clusters

Keyword Co-Occurrence and Cluster

Co-occurrence analysis of 7255 unique keywords identified 855 terms meeting the visualization threshold (frequency≥25; Figure 4A). Prominent terms—such as “asthma”, “air pollution”, “exposure”, and “climate change”—substantiate the profound impact of environmental thermal fluctuations on AHR pathology. Thematic mapping bifurcated the literature into two primary domains (Figure 4C): an air pollution cluster (anchored by “mortality”, “association”, and “particulate matter”) and an asthma cluster (defined by “exposure”, “children”, “temperature”, and “prevalence”).

Figure 4.

Keyword co-occurrence and clustering analysis in temperature-sensitive AHR research. (A) Keyword co-occurrence network generated by CiteSpace. The node size is proportional to the keyword frequency, and the concentric tree-ring colors indicate the chronological distribution of the publications. (B) Cluster view of the co-occurrence network (CiteSpace). Keywords are grouped into distinct thematic clusters (labeled #0 to #8) represented by different colors, highlighting major research domains. (C) Network visualization of keyword clustering. The spatial proximity and link thickness between nodes indicate the strength of co-occurrence, with distinct colors denoting specific thematic modules (eg, purple for environmental exposures, blue for pediatric asthma). (D) Time-zone view of the keyword co-occurrence network (CiteSpace). This chronological layout maps the evolutionary trajectory of research hotspots over time (from left to right), illustrating how fundamental concepts have branched into emerging contemporary focus areas (eg, machine learning).

Network clustering further isolated six distinct thematic modules (Figure 4B), ranging from air pollution (#0) to house dust mites (#5). Projected temporally (Figure 4D), these clusters reveal a clear evolutionary trajectory: whereas early studies predominantly investigated macroscopic epidemiological associations, recent efforts have decisively pivoted toward molecular mechanisms. Notably, thermosensitive TRP channels (eg, TRPV1, TRPA1, and TRPM8) and neuroimmune crosstalk have crystallized as the definitive contemporary frontiers.

Burst Keywords

Burst detection (Figure 5) captured sudden citation spikes, mapping dynamic shifts in research priorities. These emergent terms highlight a sustained interest in specific environmental and pathophysiological triggers, evidenced by robust bursts in “exercise-induced asthma”, “histamine”, “heat”, and “ambient temperature”. Concurrently, terms like “PM2.5” and “pulmonary function” reflect a broadening scope encompassing global air quality.

Figure 5.

Top 80 keywords with the strongest citation bursts in temperature-sensitive AHR research. The “Strength” column indicates the intensity of the sudden surge in a keyword’s frequency, reflecting a rapid accumulation of academic attention. The teal line represents the entire timeline (1990–2024), while the red segments highlight the specific active duration (from “Begin” to “End” year) of the burst for each keyword. This chronological visualization traces the dynamic evolution of research frontiers, illustrating a distinct paradigm shift from early physiological and diagnostic focuses (eg, “bronchoconstriction”, “histamine”) to recent environmental and interdisciplinary concerns (eg, “ambient temperature”, “pm2.5”, “machine learning”).

Beyond biological triggers, these temporal dynamics closely mirror major external disruptions and methodological advances. The abrupt surge in “COVID-19” and “airborne transmission” underscores the pandemic’s profound reconfiguration of respiratory research. Similarly, the recent emergence of “machine learning” signals a critical methodological transition, emphasizing the growing reliance on artificial intelligence and advanced analytics for predictive AHR modeling.

Keywords Co-Word Network Based on 51 Publications

Co-word network analysis of the 51 core publications revealed a distinct structural hierarchy (Figure 6). While macroscopic environmental exposures (eg, temperature variation, climate change) and clinical AHR phenotypes (eg, asthma, allergic rhinitis) clustered into peripheral modules, the biomolecular mechanisms linking them emerged as central bridging hubs. These mechanistic nodes segregated into three interconnected pathways: TRP family ion channels, classical immunogenic cascades (involving the epithelium, mast cells, and histamine), and sensory-driven neurogenic inflammation. In alignment with recent comprehensive reviews, this network topology quantitatively confirms, rather than discovers, the field’s established conceptual framework. It positions TRP-dependent neuroimmune pathways as the critical interface between thermal stress and downstream airway pathology, serving as a macroscopic roadmap for our subsequent experimental design.

Figure 6.

Keyword co-occurrence network based on the 51 core publications. Each node represents a keyword, with its size proportional to the frequency of occurrence. The color gradient of the nodes and their rings (from purple/dark red to yellow) indicates the chronological evolution of the keywords from 2015 to 2025. Spatially, the network visualizes a clear mechanistic hierarchy from left to right: macroscopic environmental exposures (eg, extreme temperature, cold air), central biomolecular mechanisms (eg, TRP channels, neurogenic inflammation, calcium influx), and downstream clinical phenotypes (eg, allergic rhinitis, asthma).

Building upon this foundation, and to circumvent the chronological bias inherent to relying solely on highly cited historical literature, we employed a hybrid targeted review strategy (Table 1). This integrated cohort—spanning seminal foundational studies and recent translational milestones, including multi-modal NHR investigations and early-phase TRP inhibitor trials—identified three dominant mechanistic themes (Supplementary Table 7). These comprise TRPV1-centric pathology models, TRPM8/TRPA1-mediated cold-sensing pathways, and the therapeutic targeting of polymodal TRP systems in airway remodeling. The thematic evolution within this synthesized literature highlights a decisive shift from basic channel characterization toward translational intervention, directly informing the hypothesis for our subsequent ex vivo clinical validation.

Table 1.

Overview of the Hybrid Targeted Review Strategy, Summarizing Key Literature Across Foundational Neuroimmune Mechanisms and Translational Milestones

Review Domain	Reference	Journal & Citation Impact	Targeted TRP Channels	Associated Respiratory Conditions	Downstream Signaling Pathways	Translational Significance
Foundational Mechanisms	Geppetti P et al (2006)24	Eur J Pharmacol (Citations: 151)	TRPV1	Asthma; COPD; chronic cough	Ca2+; SP; NKA; CGRP; PKC/PKA; NGF; neurogenic inflammation	This foundational review established TRPV1 as a polymodal nociceptive sensor whose activation drives neurogenic airway inflammation, cough, bronchoconstriction, and hypersecretion, framing TRPV1 antagonism as a candidate therapeutic strategy for asthma and COPD.
Foundational Mechanisms	Jia Y et al (2007)25	Biochim Biophys Acta (Citations: 109)	TRPV1; TRPV4	Asthma; chronic cough	Ca2+; tachykinins (SP/NKA); CGRP; PGE2; bradykinin	This review delineated how TRPV1- and TRPV4-mediated Ca2+ influx and sensory neuropeptide release, together with sensitization by prostaglandins and bradykinin, regulate airway tone and contribute to airway hyperreactivity and cough.
Foundational Mechanisms	Sabnis AS et al (2008)26	Am J Physiol Lung Cell Mol Physiol (Citations: 78)	TRPM8 (variant)	Cold-induced airway inflammation; asthma-relevant	Ca2+; IL-1α/β; IL-4; IL-6; IL-8; IL-13; GM-CSF; TNF-α; LTs	This experimental study showed that cold activates a TRPM8 variant in human lung epithelial cells to upregulate proinflammatory cytokine and chemokine gene transcription, providing a molecular basis for cold-induced airway inflammation and a potential role in asthma.
Foundational Mechanisms	Li M et al (2011)27	J Allergy Clin Immunol (Citations: 107)	TRPM8	COPD; cold-air-induced mucin hypersecretion	Ca2+; PLC; PIP2; MARCKS; MUC5AC	This study demonstrated that TRPM8 expression is increased in COPD airway epithelium and that cold induces MUC5AC mucin hypersecretion through a Ca2+-PLC-PIP2-MARCKS pathway, directly linking cold air exposure to mucus hypersecretion in COPD.
Foundational Mechanisms	Banner KH et al (2011)28	Pharmacol Ther (Citations: 120)	TRPC; TRPM; TRPV; TRPA1	Asthma; COPD; chronic cough	Ca2+	This comprehensive review synthesized evidence that multiple TRP channel families regulate Ca2+-dependent airway sensory-neural and inflammatory signaling, identifying TRP channels as emerging therapeutic targets across major respiratory diseases.
Foundational Mechanisms	Knowlton WM et al (2011)29	Curr Pharm Biotechnol (Citations: 61)	TRPM8	Cold-induced asthma (discussed); primary focus on cold sensing, pain, and cancer	Ca2+; PLC; PIP2	This review integrated TRPM8 biology from cold sensing to pain and cancer, and noted that TRPM8 activation by cold air in respiratory tissues may contribute to asthma-like airway symptoms, highlighting its pharmacological relevance.
Foundational Mechanisms	Bonvini SJ et al (2015)30	Naunyn Schmiedebergs Arch Pharmacol (Citations: 68)	TRPV1; TRPA1; TRPV4; TRPM8	Chronic cough	Ca2+	This bench-to-bedside review profiled TRPV1, TRPA1, TRPV4, and TRPM8 in cough neurobiology, documented the clinical limitations of TRPV1 antagonists, and advanced alternative TRP channels as antitussive drug targets.
Foundational Mechanisms	Du Q et al (2019)31	Front Physiol (Citations: 113)	TRPV1	Asthma; other respiratory, digestive, and cardiovascular diseases	Ca2+; inflammatory mediators	This cross-systems review consolidated evidence that TRPV1-mediated Ca2+ signaling contributes to asthma and other common digestive, cardiovascular, and respiratory diseases, reinforcing TRPV1 as a disease-relevant therapeutic target.
Translational Milestones	Deng L et al (2020)32	Environ Pollut (Citations: 93)	TRPA1; TRPM8; TRPV1	Asthma (OVA-induced mouse model)	IgE; IL-4; IL-1β; IL-6; TNF-α; IFN-γ	This experimental study demonstrated that both low (10°C) and high (40°C) ambient temperatures aggravate OVA-induced allergic airway inflammation in mice with temperature-dependent TRPA1/TRPM8/TRPV1 expression, providing mechanistic evidence for temperature-triggered asthma exacerbations.
Translational Milestones	Balestrini A et al (2021)18	J Exp Med (Citations: 132)	TRPA1	Asthma	SP; NKA; CGRP; neurogenic inflammation; Ca2+	This translational study showed that the selective oral TRPA1 antagonist GDC-0334 suppresses neurogenic inflammation and airway contraction preclinically and achieves target engagement in a Phase 1 healthy-volunteer study, providing clinical rationale for TRPA1 inhibition in asthma.
Translational Milestones	Backaert W et al (2024)7	Rhinology (Citations: 5)	TRPV1; TRPM8; TRPA1	Allergic rhinitis; chronic rhinosinusitis with nasal polyps (CRSwNP)	Histamine; SP; CGRP; NKA; IL-33	This clinical study linked cold-dry-air nasal hyperreactivity in allergic rhinitis and CRSwNP to TRPV1/TRPM8 neuronal expression, neuropeptide release, and IL-33, and showed that histamine sensitizes TRPV1/TRPA1, revealing a neurogenic axis in upper-airway hyperreactivity.

Notes: Citation counts were retrieved from Crossref on 17 August 2026 (is-referenced-by-count field), reflecting the number of times each paper had been cited by Crossref-indexed publications at that date.

Abbreviations: TRP, transient receptor potential; COPD, chronic obstructive pulmonary disease; SP, substance P; CGRP, calcitonin gene-related peptide; PKC, protein kinase C; TRPV1, transient receptor potential vanilloid 1; TRPV4, transient receptor potential vanilloid 4; TRPM8, transient receptor potential melastatin 8; TRPA1, transient receptor potential ankyrin 1; NKA, neurokinin A; NGF, nerve growth factor; PLC, phospholipase C; PIP2, phosphatidylinositol 4,5-bisphosphate; MARCKS, myristoylated alanine-rich C kinase substrate; MUC5AC, mucin 5AC; IL, interleukin; IL-33, interleukin-33; GM-CSF, granulocyte-macrophage colony-stimulating factor; TNF-α, tumor necrosis factor-α; IFN-γ, interferon-γ; IgE, immunoglobulin E; AR, allergic rhinitis; CRSwNP, chronic rhinosinusitis with nasal polyps; OVA, ovalbumin.

Differences in TRP-Related Indicators in Human Nasal Mucosal Tissue Validation

Comparison of Clinical Characteristics Between the Two Groups

A total of 18 subjects were enrolled in this study, comprising 9 patients with temperature-sensitive AHR and 9 healthy controls. Baseline demographic profiles—including age, gender distribution, and smoking status—were highly comparable between the two cohorts (Table 2). Furthermore, no significant intergroup disparities were observed in systemic allergic indicators, specifically total serum IgE levels and peripheral eosinophil (Eos) counts. Clinically, however, the AHR cohort exhibited a profound phenotypic sensitivity to thermal fluctuations. Upon exposure to temperature changes, these patients recorded significantly higher localized symptom scores (ie, rhinorrhea, nasal itching, sneezing, and nasal congestion) and markedly elevated SCH scores compared to the healthy controls (P < 0.05).

Table 2.

Demographic and Clinical Characteristics of the AHR and Normal Control Groups

Characteristics	AHR (n=9)	NC (n=9)	Effect Size	95% CI of Difference	p-value	FDR q-value
Age (years)	40.00 ± 11.49	41.00 ± 14.77	Cohen’s d = −0.08	−14.22 to 12.22	0.875	—
Sex, (m/f)	4/5	5/4	—	—	ns	—
Smoking, n	3	3	—	—	ns	—
tIgE	44.90 ± 26.04	58.10 ± 49.23	Cohen’s d = −0.34	−52.55 to 26.16	0.487	—
Eos count (×109/L)	0.15 ± 0.12	0.14 ± 0.13	Cohen’s d = 0.07	−0.11 to 0.13	0.880	—
Nasal congestion	8.00 (5.00–8.00)	2.00 (2.00–4.00)	Rank-biserial r = 0.83	2.00 to 6.00	0.002	0.002
Sneezing	6.00 (3.00–6.00)	1.00 (1.00–2.00)	Rank-biserial r = 0.84	2.00 to 5.00	0.001	0.002
Runny nose	6.00 (6.00–8.00)	1.00 (0.00–1.00)	Rank-biserial r = 0.99	4.00 to 7.00	<0.001	<0.001
Itchy nose	6.00 (4.00–6.00)	1.00 (0.00–1.00)	Rank-biserial r = 0.99	3.00 to 6.00	<0.001	<0.001
Overall score	23.00 (20.00–28.00)	5.00 (3.00–7.00)	Rank-biserial r = 1.00	13.00 to 23.00	<0.001	<0.001
SCH	2.00 (2.00–3.00)	0.00 (0.00–1.00)	Rank-biserial r = 0.93	1.00 to 3.00	<0.001	<0.001

Notes: Data are presented as Mean ± SD for baseline continuous variables (Age, tIgE, EOS) and analyzed using the independent Student’s t-test. Clinical symptom scores are presented as Median (IQR) and analyzed using the exact Mann–Whitney U-test. * Effect Size: Calculated using Cohen’s d for parametric data and rank-biserial correlation (r) for non-parametric data. ** FDR q-value: Calculated using the Benjamini-Hochberg procedure to correct for multiple comparisons among the six primary clinical symptom outcomes. Baseline descriptors were not subjected to this correction (indicated by “—”).

Abbreviations: AHR, airway hyperreactivity; NC, normal control; SD, standard deviation; IQR, interquartile range; CI, confidence interval; FDR, false discovery rate; EOS, eosinophils; tIgE, total immunoglobulin E.

Upregulation of TRP Channels in Nasal Mucosa

To validate the biomolecular framework identified in our bibliometric analysis, we assessed the local expression of thermosensitive TRP channels in nasal mucosal biopsies. IHC profiling revealed a marked upregulation of TRPV1, TRPM8, and TRPA1 in the AHR cohort relative to the healthy controls (Figure 7A, D and G). Semi-quantitative analysis—performed by independent pathologists blinded to the clinical groupings—confirmed these elevations to be statistically significant (Figure 7B, E and H). Specifically, the positive staining area in the AHR group was markedly higher than that in the NC group for: TRPV1 (Median [IQR]: 1.85 (1.13, 2.14) vs 0.48 (0.30, 1.20); p = 0.02, FDR-adjusted q = 0.02, rank-biserial r = 0.65, 95% CI: 0.14 to 1.85); TRPM8 (Median [IQR]: 2.50 (2.33, 3.90) vs 0.87 (0.69, 1.71); p < 0.001, FDR-adjusted q = 0.001, rank-biserial r = 0.93, 95% CI: 0.79 to 3.28); and TRPA1 (Median [IQR]: 0.96 (0.74, 1.53) vs 0.39 (0.30, 0.54); p < 0.001, FDR-adjusted q = 0.001, rank-biserial r = 0.90, 95% CI: 0.33 to 1.23).

Figure 7.

Enhanced expression and neuroimmune co-localization of TRP channels in the nasal mucosa of patients with AHR. (A, D and G) Representative IHC images illustrating the spatial distribution and upregulated protein expression of TRPV1, TRPM8, and TRPA1 in the AHR group compared to the NC group. Scale bars = 30 μm. (B, E and H) Semi-quantitative analysis of the IHC positive staining area for each channel. (C, F and I) Orthogonal validation using RT-qPCR to quantify the relative mRNA expression levels of the respective TRP channels. For all dot plots, data are presented as individual values (dots) superimposed with the median and interquartile range (IQR) (n=9 per group). Statistical significance was determined using the non-parametric Mann–Whitney U-test (*p < 0.05, **p < 0.01, ***p < 0.001). (J–L) Representative immunofluorescence images demonstrating the anatomical co-localization of TRP channels (green) with the sensory neuropeptide SP (red) in mucosal biopsies. Nuclei were counterstained with DAPI (blue). The merged panels reveal robust spatial overlap, supporting the structural basis for TRP-mediated neurogenic inflammation (quantitative co-localization metrics are detailed in the main text). Scale bars = 20 μm.

Orthogonal Validation of TRP Channel Upregulation via RT-qPCR

To orthogonally confirm our semi-quantitative protein-level observations, we evaluated the mRNA expression of TRPV1, TRPM8, and TRPA1 in the expanded clinical cohort (n = 9 per group). Consistent with the immunohistochemical trends, RT-qPCR analysis revealed a robust transcriptional upregulation of all three targets (Figure 7C, F and I). Specifically, the relative mRNA expression in the AHR group was significantly elevated compared to the NC group for: TRPV1 (Median [IQR]: 9.78 (4.56, 12.77) vs 0.91 (0.59, 1.44); p = 0.01, FDR-adjusted q = 0.01, rank-biserial r = 0.70, 95% CI: 0.87 to 12.48); TRPM8 (Median [IQR]: 2.20 (1.57, 4.94) vs 1.00 (0.86, 1.18); p = 0.001, FDR-adjusted q = 0.002, rank-biserial r = 0.85, 95% CI: 0.47 to 4.08); andTRPA1 (Median [IQR]: 3.65 (1.42, 4.04) vs 1.00 (0.96, 1.36); p = 0.01, FDR-adjusted q = 0.01, rank-biserial r = 0.70, 95% CI: 0.33 to 3.66). This solid transcriptional alignment, supported by large effect sizes, strictly substantiates the molecular reliability of the observed TRP channel overexpression.

Anatomical Co-Distribution of TRP Channels and SP

To explore the structural basis for neuroimmune interactions, IF assays were performed to evaluate the spatial relationship between TRP channels and the neuropeptide SP. Addressing potential concerns regarding spectral bleed-through and tissue autofluorescence, negative controls lacking primary antibodies, alongside single-stain controls, were routinely employed to ensure signal specificity (Supplementary Figure 2B). Furthermore, to move beyond qualitative visual assessment, we conducted rigorous quantitative co-localization analysis using Costes auto-thresholding, and selected representative optical sections from each group to present key metrics (Figure 7J–L).

For TRPV1 and SP, colocalization analysis showed that 48.2% of TRPV1 (green) signal overlapped with SP (red) signal (Mander’s M2 = 0.482), whereas only 16.9% of SP signal overlapped with TRPV1 (M1 = 0.169), suggesting a broader distribution of TRPV1. Within the bright colocalized regions, the fluorescence intensities exhibited a strong positive correlation (Costes-thresholded Pearson’s r = 0.655, Spearman’s rho = 0.527). For TRPM8 and SP, the image revealed that 14.3% of TRPM8 (green) signal overlapped with SP (red) signal (M2 = 0.143), while 92.2% of SP signal was located within TRPM8-positive areas (M1 = 0.922). Intensity correlation analysis after Costes threshold correction showed a strong positive correlation (Costes-thresholded Pearson’s r = 0.587, Spearman’s rho = 0.523). Similarly, for TRPA1 and SP, 92.1% of TRPA1 (green) signal overlapped with SP (red) signal (M2 = 0.921), and 76.4% of SP signal overlapped with TRPA1 (M1 = 0.764), also exhibiting a highly symmetrical co-distribution pattern. Intensity correlation analysis revealed a strong positive correlation (Costes-thresholded Pearson’s r = 0.782, Spearman’s rho = 0.578)(Supplementary Figure 2C-E).

Collectively, all three TRP channels displayed varying degrees of anatomical co-localization with SP. TRPM8 and TRPA1 demonstrated the highest degree of spatial overlap, characterized by highly symmetrical co-distribution patterns, whereas TRPV1 exhibited a relatively lower, yet still definitive, positive spatial correlation. These findings confirm the structural proximity between TRP channels and SP in the nasal mucosa, providing a robust morphological baseline for TRP-mediated neurogenic inflammation. However, consistent with the inherent limitations of static histological snapshots, these structural associations do not equate to dynamic molecular interactions. Future functional validations—such as in vivo calcium imaging or electrophysiological blockade—remain essential to definitively confirm active neuroimmune crosstalk in this temperature-sensitive phenotype.

Discussion

Our results align with recent review detailing a distinct paradigm shift in airway research toward TRP channels.⁸ The upregulation of TRPV1, TRPM8, and TRPA1 observed in the nasal mucosa of our temperature-sensitive AHR cohort closely mirrors established profiles in idiopathic rhinitis, CRSwNP, and cold-aggravated asthma models.^32,33 Moreover, the anatomical co-localization of these channels with SP not only offers biological plausibility but is also heavily substantiated by the emerging framework of localized “neuronal-immune cell units” at barrier surfaces.³⁴

General Information and Thematic Shift

Historically, the relationship between climatic stressors and AHR was treated predominantly as an epidemiological phenomenon. Despite long-standing clinical evidence that temperature fluctuations exacerbate rhinitis and asthma, underlying mechanistic investigations remained notably sparse. Our bibliometric analysis captures a definitive evolutionary trajectory: since the turn of the 21st century, scientific momentum has decisively pivoted toward decoding the cellular mechanics of airway thermal sensing, positioning neuroimmune interactions as the central drivers.

Informed by these in silico trends, our translational focus converged on the TRP channel family—a rapidly emerging mechanistic hotspot. Crucially, our clinical data provide direct ex vivo validation of these macroscopic patterns. By demonstrating the profound spatial upregulation of thermosensory TRP channels alongside their neuroimmune co-localization with SP in hyperreactive mucosa, this study successfully bridges the traditional gap between global epidemiological observations and targeted molecular pathology.

Global Contributions and the Evolution of Institutional Paradigms

Geospatial mapping reveals a progressive evolution in research leadership. While historically dominated by North American and European institutions, the recent surge in publication output from China signals a shifting global dynamic, ostensibly catalyzed by mounting regional environmental pressures.

Tracking institutional contributions further illuminates the field’s conceptual maturation. Early foundational work—championed by centers like Harvard University—established the physiological basis of temperature-induced AHR by demonstrating temperature-dependent cholinergic contractility and quantifying cooling-proportional FEV1 declines. Building on these classical models, contemporary hubs such as the University of Wisconsin-Madison have advanced the discipline into the systems biology era. By employing multimodal approaches, these groups have broadened the investigative lens from isolated airway remodeling to systemic neuro-affective networks. This paradigm shift underscores the immense complexity of airway neuroimmune circuitry; more importantly, it provides the vital theoretical scaffolding needed to understand how localized mucosal phenomena—such as the TRP-mediated hyperreactivity observed in our clinical cohort—might ultimately integrate into broader systemic reflexes.

Macroscopic Environmental Triggers and the Shift Toward Molecular Transducers

Consistent with prevailing epidemiological models, our thematic analysis indicates that thermal variability rarely acts in isolation. Rather, it synergizes with ambient irritants (eg, PM_2.5, NO₂, and allergens) to alter the local airway microenvironment, effectively lowering the threshold for AHR.³⁵ This environmental interplay is further underscored by the recent bibliometric surge in COVID-19-related keywords, illustrating how climatic stressors exacerbate pre-existing airway vulnerabilities during public health crises.³⁶

Beyond mapping the established epidemiological triad of temperature, pollution, and pathogens, current research has increasingly focused on the underlying molecular mechanisms. Identifying the biomolecular sensors that transduce these environmental stimuli into neurogenic inflammation has become a priority. This mechanistic shift provides a clear rationale for our experimental focus on TRP channels as primary thermosensors.

Mechanisms of TRP Channel-Mediated Neuroimmune Interactions in Temperature-Sensitive AHR

Neuroimmune Crosstalk as a Proposed Primary Driver

Although our clinical data firmly establish the structural overexpression and anatomical co-localization of TRP channels with SP in the nasal mucosa, capturing their dynamic functional engagement remains beyond the scope of static histological assays. Consequently, to contextualize these findings, we integrate our structural observations with established mechanistic frameworks.

Beyond classical immunological pathways, our bibliometric synthesis underscores a critical paradigm shift: neuroimmune (N-I) crosstalk is increasingly recognized as a central regulatory mechanism in temperature-sensitive AHR 4,22.^4,22,37 Inherent to this specific AHR subtype are thermosensitive TRP channels.⁹ Functioning as polymodal sensors, members such as TRPV1, TRPM8, and TRPA1 integrate environmental thermal fluctuations with local chemical and mechanical stimuli.^38,39,

Current literature suggests that the thermal activation of these channels—expressed on both sensory nerve fibers and non-neural cells (eg, airway epithelium, CD4⁺ T cells)—can circumvent the traditional allergen-sIgE-mast cell axis. This activation likely triggers a dual inflammatory cascade: an immediate neurogenic response mediated by rapid neuropeptide release (eg, SP, CGRP), followed by an immunogenic phase driven by subsequent cytokine surges (eg, IL-33, IL-6, IL-13).⁴⁰ Ultimately, the robust spatial co-distribution of TRP channels and SP observed in our patient cohort provides a compelling structural foundation for this localized N-I cascade (Figure 8).

Figure 8.

Schematic overview of TRP channel-mediated neuroimmune interactions in temperature-sensitive airway hyperreactivity. The diagram illustrates the tripartite mechanism contributing to AHR: (1) Neurogenic inflammation triggered by the activation of temperature-sensitive TRP channels (TRPV1, TRPM8, TRPA1) on sensory nerve endings, leading to the release of neuropeptides (eg, SP, CGRP); (2) Type 2 inflammation propagated by complex neuroimmune crosstalk involving mast cells, Th2 cells, and ILC2s; and (3) Barrier defect characterized by the disruption of tight junction proteins (ZO-1, OCC) in the airway epithelium.

Polymodal TRP Sensors: Translating Thermal Stress to Peripheral Inflammation

To contextualize our findings, we must distinguish our structural data (TRP channel overexpression and SP co-localization) from functional signaling mechanisms. Based on established literature, TRPV1 classically transduces heat (>43°C), yet winter cold paradoxically sensitizes it, exacerbating rhinitis. Activated TRPV1 drives SP and CGRP release, promoting mucosal edema and adaptive immune responses.²⁸ While local capsaicin desensitization and early experimental blockade (SB-705498) showed promise in specific hyperreactive models,¹² clinical translation has proven difficult. Notably, large-scale clinical trials evaluating the TRPV1 antagonist SB-705498 for allergic rhinitis failed to demonstrate efficacy over placebo.^13,14 This translational failure indicates that TRP activation operates within a highly redundant neuroimmune network, where singular receptor blockade is insufficient.

Our TRPM8 and TRPA1 structural findings similarly parallel established cold-transduction frameworks. Previous functional studies indicate that cold-triggered Ca²⁺ influx via TRPM8 activates MAPK/NF-κB pathways, driving Th2 cytokine and histamine release.^20,41 Furthermore, TRPA1 depolarizes trigeminal neurons, triggering neuropeptide release and mast cell degranulation.⁴² Although our anatomical co-distribution data support the plausibility of these cascades in our temperature-sensitive cohort, definitive confirmation requires future real-time functional assays (eg, calcium imaging).

Beyond neurogenic inflammation, thermal stress physically impairs the airway epithelial barrier. Consistent with our previous preliminary data, environmental triggers induce calcium influx via epithelial TRPV1, directly downregulating tight junction proteins (ZO-1, occludin).²¹ When compounded by cold-impaired mucociliary clearance or ambient pollutants, this barrier dysfunction facilitates allergen penetration, synergistically amplifying pro-inflammatory cytokine release.^35,43

Beyond the Periphery: Central Sensitization and the Nasal/Lung-Brain Axes as Future Perspectives

Ultimately, the implications of peripheral TRP-mediated neuroimmune interactions may extend beyond local airway remodeling. Emerging literature has conceptualized the “lung-brain” and “nose-brain” axes to describe how peripheral respiratory inflammation might drive central sensitization and affective comorbidities via vagal and trigeminal afferents.^44–46 However, it is imperative to acknowledge that our current investigation relies exclusively on peripheral nasal mucosal biopsies and lacks CNS data. Consequently, our localized findings cannot directly substantiate brain-level processes or systemic central sensitization.

Instead, the local TRP channel upregulation and neuroimmune co-localization observed in our cohort are best interpreted as the potential peripheral sensory starting point-the afferent arm-of these proposed theoretical axes. Viewed from a forward-looking perspective, mapping this peripheral mucosal initiation provides a vital theoretical rationale for exploring the broader brain-immune interface. While our study does not directly test a brain-axis hypothesis, it underscores the necessity for future comprehensive investigations. Subsequent multidisciplinary studies incorporating functional neuroimaging, epigenetic profiling, and specific neural circuit mapping will be instrumental in bridging the gap between peripheral TRP activation and the central nervous system in temperature-sensitive airway diseases.

Limitations of the Study

Several limitations warrant consideration. First, restricting our bibliometric analysis to the WoSCC ensured CiteSpace compatibility but excluded broader databases (eg, Scopus) and may obscure recent breakthroughs due to citation latency. Second, while we provided robust structural and transcriptional evidence, the absence of real-time functional assays (eg, in vitro calcium imaging) necessitates future dynamic validation. Third, utilizing surgical patients as normal controls introduces potential confounding from localized surgical trauma or latent inflammation, despite sampling macroscopically healthy mucosa. Finally, the generalizability of these specific TRP profiles requires further confirmation through large-scale, multicenter functional studies that parallelly assess classic allergen-driven AR or broader asthmatic cohorts.

Conclusion

By bridging macroscopic bibliometric trends with targeted ex vivo investigations, this study provides preliminary evidence supporting the role of thermosensitive TRP channels in temperature-sensitive AHR. Our bibliometric analysis, which identified TRP channels as an emergent mechanistic frontier, directly generated our experimental hypothesis. We corroborated this by demonstrating the significant transcriptional and structural upregulation of TRPV1, TRPM8, and TRPA1, alongside their anatomical co-distribution with SP, in the nasal mucosa of AHR patients. While this fixed-tissue co-localization reflects static spatial proximity rather than dynamic functional crosstalk, it successfully maps the essential peripheral afferent arm of proposed neuroimmune pathways (eg, the “nose-brain” axis).

Clinically, translating these localized neuroimmune signatures remains complex; the lack of efficacy in prior TRPV1 antagonist trials underscores the redundancy of these networks, suggesting singular receptor blockade is insufficient. To transition from these preliminary structural observations to definitive clinical validation, future investigations must prioritize real-time functional assays (eg, in vitro calcium imaging) combined with large-scale, multicenter cohorts to confirm active signaling crosstalk and advance precision neuroimmune therapies.

Funding Statement

This research was financially supported by the National Key R & D Program of China (NO. 2023YFC2507900), the National Natural Science Foundation of China (NO. 82171119, 82201263, 82301287), and the Basic Research Project of Shanxi Province (Exploration Category) (NO. 202203021222390).

Abbreviations

Ach, acetylcholine; CGRP, calcitonin gene-related peptide; SP, substance P; VIP, vasoactive intestinal peptide; NMU, neuromedin U; NMUR1, neuromedin U receptor 1; NA, noradrenaline; TRPV1, transient receptor potential vanilloid 1; TRPM8, transient receptor potential melastatin 8; TRPA1, transient receptor potential ankyrin 1; IL, interleukin; TSLP, thymic stromal lymphopoietin; LT, leukotriene; PG, prostaglandin; ZO-1, zonula occludens-1; OCC, occludin; EpiC, epithelial cell; GC, goblet cell; CNS, central nervous system.

Data Sharing Statement

The bibliometric datasets analyzed during the current study are derived from public domain resources (Web of Science Core Collection). The clinical and experimental data that support the findings of this study are available from the corresponding author, CQZ, upon reasonable request. The raw clinical data are not publicly available due to privacy and ethical restrictions regarding human research participants.

Author Contributions

Yanjie Wang: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Writing-original draft. Qianru Zhao: Conceptualization, Writing-original draft. Haoxiang Zhang: Investigation, Formal analysis, Writing-original draft. Xueping Qi: Formal analysis, Writing-review & editing. Fengli Cheng: Formal analysis, Writing-review & editing. Sirui Fu: Investigation, Data curation, Formal analysis, Writing-review & editing. Qi Zhang: Investigation, Data curation, Formal analysis, Writing-review & editing. Luyao Wang: Investigation, Data curation, Formal analysis, Writing-review & editing. Xiaojia Zhu: Investigation, Data curation, Formal analysis, Writing-review & editing. Danni Xu: Data curation, Formal analysis, Writing-original draft. Muze Liu: Data curation, Formal analysis, Writing-original draft. Changqing Zhao: Conceptualization, Supervision, Investigation, Formal analysis, Writing-review & editing. Yanjie Wang had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare not to have any conflicts of interest that may be considered to influence directly or indirectly the content of the article.

The authors declare that the work was not completely produced with the help of any artificial intelligence software or tool.