Pharmacology of human trace amine-associated receptors: Therapeutic opportunities and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The discovery in 2001 of a G protein-coupled receptor family, subsequently termed trace amine-associated receptors (TAAR), triggered a resurgence of interest in so-called trace amines. Initial optimism quickly faded, however, as the TAAR family presented a series of challenges preventing the use of standard medicinal chemistry and pharmacology technologies. Consequently the development of basic tools for probing TAAR and translating findings from model systems to humans has been problematic. Despite these challenges the last 5years have seen considerable advances, in particular with respect to TAAR1, which appears to function as an endogenous rheostat, maintaining central neurotransmission within defined physiological limits, in part through receptor heterodimerization yielding biased signaling outputs. Regulation of the dopaminergic system is particularly well understood and clinical testing of TAAR1 directed ligands for schizophrenia and psychiatric disorders have begun. In addition, pre-clinical animal models have identified TAAR1 as a novel target for drug addiction and metabolic disorders. Growing evidence also suggests a role for TAARs in regulating immune function. This review critically discusses the current state of TAAR research, highlighting recent developments and focussing on human TAARs, their functions, and clinical implications. Current gaps in knowledge are identified, along with the research reagents and translational tools still required for continued advancement of the field. Through this, a picture emerges of an exciting field on the cusp of significant developments, with the potential to identify new therapeutic leads for some of the major unmet medical needs in the areas of neuropsychiatry and metabolic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it