Genetic Basis of the Negative Response to the Use of Triptans for the Treatment of Migraine—A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
INTRODUCTION: Migraine is a widespread and disabling neurological disorder, and triptans are a primary treatment for acute episodes. However, around 40% of patients are non-responsive. Genetic polymorphisms can influence drug effectiveness, and several association studies exist. This systematic review consolidates findings from etiological studies, which may provide greater certainty about their use in predicting the risk of low response to triptans. METHOD: This study followed COSMOS-E guidelines and employed databases like PubMed, Web of Science, and Embase until 2023. The Newcastle-Ottawa Scale (NOS) was used to assess quality, and statistical meta-analysis was performed. RESULTS: A comprehensive literature search identified 1421 articles from which 30 met eligibility for full-text review, and 9 studies were included in the final analysis. Although the overall analysis did not confirm a statistically significant association, subgroup analyses demonstrated significant relationships between SLC6A4, 5-HT1B, and COMT polymorphisms and triptan nonresponse, while CALCA and PRDM16 had moderate evidence, and GRIA1 and SCN1A polymorphisms exhibited limited evidence for non-response. While our analysis revealed that genetic polymorphisms are an essential cause of heterogeneity in response to triptans, the included studies showed substantial variability and methodological inconsistency. Polygenic risk scores (PRS) and combined genetic approaches, including prospective clinical trials and multi‑omics integration, can help stratify triptan nonresponders and inform decision‑making in precision and personalized medicine (PPM). CONCLUSIONS: These results underscore the potential utility of these genetic associations in tailored migraine therapy and reinforce the involvement of serotonergic and dopaminergic pathways in triptan efficacy. Future studies with larger and more homogeneous cohorts are essential to validate these associations. Still, clinical implementation of polygenic risk score (PRS) may offer a more effective pathway for applying PPM in migraine care.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".