Bibliographic record
Abstract
Asthma is a chronic disorder causing inflammation and reversible airway obstruction that affects approximately 300 million individuals worldwide. The incidence of asthma has nearly doubled in the past three decades resulting in higher rates of morbidity, mortality and health care costs. Despite the availability of several classes of asthma medications such as beta-agonists, leukotriene modifiers and corticosteroids, up to 50% of asthmatics do not benefit from one or more of these drugs. Studies have shown that asthma and drug response phenotypes such as forced expiratory volume in one second (FEV(1)) are heritable traits, indicating a genetic component of variable response to asthma drugs. This review summarizes the findings of pharmacogenetic investigations on the three main classes of asthma medications. In addition, the limitations of these genetic studies are discussed and future research avenues are proposed to identify novel genetic factors. Although numerous genes have been associated with variable response to common asthma drugs, results are often contradictory across different studies, and remain to be confirmed in larger replication cohorts. Nevertheless, literature in asthma pharmacogenetics demonstrates that genetic variants influence response to asthma treatments and may be used for predictive testing prior to drug administration to avoid adverse reactions and increase drug efficacy.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".