Genetic subtraction reveals divergent pathways and targets in anxiety-related and anxiety-independent TMD.

Overview

1. Faculty of Dentistry, National University of Singapore, Singapore, 119085 Singapore
2. Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Nanjing University, 30 Zhongyang Road, Nanjing, 210008 China
3. Department of Stomatology, Medical School of Nantong University, Affiliated Hospital of Nantong University, Nantong, 226001 China

Abstract

Background: Temporomandibular disorders (TMD) show substantial clinical and genetic overlap with anxiety, yet it remains unclear whether TMD risk reflects shared anxiety-related liability or distinct anxiety-independent genetic mechanisms. Disentangling these components is essential for understanding TMD heterogeneity beyond symptom-based classifications.

Methods: We applied GWAS-by-subtraction using genome-wide summary statistics for TMD (20,799 cases and 479,549 controls; FinnGen Release 12) and anxiety disorders (74,973 cases and 400,243 controls), partitioning TMD heritability into two orthogonal latent components: an anxiety-dependent factor (FAnxiety) and an anxiety-independent factor (FNon-Anxiety). To delineate the mechanisms underlying each component, we integrated fine-mapping, transcriptome- and proteome-wide association analyses, genetic colocalization, brain imaging–genetics, and single-cell RNA sequencing from human embryonic temporomandibular joint tissue.

Results: Anxiety showed significant genetic correlation with TMD (rg = 0.4417, p = 1.98 × 10− 1 9) and accounted for 19.50% of TMD heritable variance. FAnxiety yielded multiple genome-wide significant loci (CNTNAP5, PCLO, PRSS16, BTN1A1, RAB27B), whereas FNon-Anxiety produced a single independent signal near GPNMB, demonstrating sharply divergent genetic architectures. Multi-omic integration identified RAB27B as a driver of the anxiety-related pathway, implicating synaptic vesicle trafficking and neuroimmune regulation, while GPNMB and KLHL7 supported anxiety-independent pathways involving musculoskeletal remodeling and peripheral inflammation. BrainXcan analyses showed that FAnxiety predominantly affected limbic and external capsule microstructure, whereas FNon-Anxiety mapped to thalamic–sensorimotor white matter networks. Single-cell mapping further revealed distinct enrichment patterns of RAB27B, KLHL7, and GPNMB across TMJ cell types.

Conclusion: These findings demonstrate that TMD genetic liability comprises separable anxiety-related and anxiety-independent dimensions with distinct molecular, neurostructural, and cellular signatures. Rather than defining clinical subtypes, these latent components represent associative dimensions of genetic risk at the population level. This integrative framework clarifies the genetic architecture underlying TMD heterogeneity and provides a foundation for future studies integrating individual-level phenotyping to assess clinical relevance and causal mechanisms.

Supplementary Information: The online version contains supplementary material available at 10.1186/s10194-026-02304-3.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper says that its authors' code is available on request: it was not published with the paper, so there is nothing to verify.

Code availability

All analyses were conducted using established, publicly available software packages, including tools for GWAS-by-subtraction, TWAS, PWAS, colocalization, BrainXcan analysis, and single-cell RNA-seq processing. No new software or computational methods were developed in this study. The analyses followed standard implementations and recommended workflows provided by the original software developers, which are available through the respective project websites and repositories. Custom code used in this study is available upon reasonable request.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• figshare:32031606, at figshare; found in DataCite
• geo:GSE308079, at NCBI GEO; found in “Data availability”

Data Availability Statement

The summary-level GWAS data sets analyzed in this study are publicly available. TMD GWAS data were obtained from the FinnGen consortium (Release 12, https://www.finngen.fi/en). GWAS summary statistics for anxiety were obtained from a previously published study (10.6084/m9.figshare.23659653.v1). All summary statistics generated in this study, along with the complete fine-mapping and colocalization results, are available in a publicly accessible repository (DOI: 10.5281/zenodo.18765836). Variant annotation resources included dbSNP build 157 (https://ncbiinsights.ncbi.nlm.nih.gov/2025/03/18/dbsnp-release-157/) and the 1000 Genomes Project Phase 3 reference panel (https://www.internationalgenome.org/category/phase-3/). Transcriptome-wide association analyzes were performed using GTEx v8 reference transcriptomic data and pre-trained FUSION expression weights (http://gusevlab.org/projects/fusion/). Colocalization analyzes were conducted using fastENLOC (https://github.com/xqwen/fastenloc). Single-cell transcriptomic data were obtained from the Gene Expression Omnibus under accession number GSE308079 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE308079). Proteome-wide association analyzes (PWAS) used BLISS models publicly released by Chongwu Lab (https://huggingface.co/data sets/chongwulab/BLISS-models).

All analyses were conducted using established, publicly available software packages, including tools for GWAS-by-subtraction, TWAS, PWAS, colocalization, BrainXcan analysis, and single-cell RNA-seq processing. No new software or computational methods were developed in this study. The analyses followed standard implementations and recommended workflows provided by the original software developers, which are available through the respective project websites and repositories. Custom code used in this study is available upon reasonable request.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 11 authors, 6 keywords, 6 MeSH terms, 63 references.

Cite

This paper

Cao, Y., Yang, X., Svensson, P., Chung Wen, R. W., Han Sng, T. J., Islam, I., Han, W., Feng, X., Hou, B., Li, Y., & Zheng, L. (2026). Genetic subtraction reveals divergent pathways and targets in anxiety-related and anxiety-independent TMD. The journal of headache and pain, 27(1), 105. https://doi.org/10.1186/s10194-026-02304-3

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