Trace Amine-Associated Receptors as Novel Therapeutic Targets for Immunomodulatory Disorders
Bibliographic record
Abstract
Trace amines and their receptors (trace amine-associated receptors; TAARs) are an emerging pharmacological target for the treatment of human disorders. While most studies have focused on their therapeutic potential for neurologic and psychiatric disorders, TAARs are also expressed throughout the periphery, including prominent expression in human leukocytes. Furthermore, recent independent, unbiased metabolomic studies have consistently identified one or more TAAR ligands as potential etiologic factors in inflammatory bowel disease (IBD). The putative role of TAARs in diseases such as IBD that are associated with hyperactive immune responses has not, however, previously been systematically addressed. Here, we review the current state of the knowledge of the effects of TAARs on leukocyte function, in particular in the context of mucosal epithelial cells that interface with the environment; developing a model whereby TAARs may be considered as a novel therapeutic target for disorders associated with dysregulated immune responses to environmental factors. In this model, we hypothesize that altered trace amine homeostasis results in hyperactivity of the immune system. Such loss of homeostasis can occur through many different mechanisms including TAAR polymorphisms and altered trace amine load due to changes in host synthesis and/or degradative enzymes, diet, or microbial dysbiosis. The resulting alterations in TAAR functioning can then lead to a loss of homeostasis of leukocyte chemotaxis, differentiation, and activation, as well as an altered ability of members of the microbiota to adhere to and penetrate the epithelial cell layers. Such changes would generate a pro-inflammatory state at mucosal epithelial barrier layers that can manifest as clinical symptomatology such as that seen in IBD. These alterations may also have the potential to induce systemic effects, which could possibly contribute to immunomodulatory disorders in other systems, including neurological diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".