P376: Microdeletion and microduplication of 15q11.2-q13 share a neurodevelopmental phenotype
Bibliographic record
Abstract
Introduction: Interpatient variability in response to pharmacotherapy can significantly affect treatment outcomes and the management of cardiovascular events.Commonly used antiplatelet agents such as clopidogrel (Plavix), prasugrel (Effient), and ticagrelor (Brilinta) help reduce thrombotic events.Clopidogrel, in particular, requires activation via the CYP2C19 enzyme, which is responsible for metabolizing approximately 10% of all drugs, including clopidogrel and prasugrel.Genetic variations in CYP2C19, such as the *2 or *3 alleles, can result in a loss-of-function phenotype, leading to a diminished response to clopidogrel.This reduced efficacy is associated with an increased risk of adverse cardiovascular events.In contrast, CYP2C19 variants do not decrease the effectiveness of prasugrel, which is a more potent antiplatelet agent compared to clopidogrel, though it carries a higher risk of bleeding.Both CYP2C19 and CYP3A4 enzymes play crucial roles in determining the effectiveness of these antiplatelet agents.While clopidogrel and prasugrel are primarily influenced by CYP2C19 metabolism, ticagrelor, a newer class of antiplatelet drug, is predominantly metabolized by CYP3A4, which can also impact its therapeutic response.Methods: PMC Diagnostics (PMCDx) utilizes pharmacogenetic (PGx) testing as a tool to personalize the management of cardiovascular disease, particularly in the context of antiplatelet medications.We have conducted PGx testing on 54 participants from diverse ethnic backgrounds, including, but not limited to, White, African American, and Asian populations.The pharmacogenetic responses to three antiplatelet medications-clopidogrel (Plavix), prasugrel (Effient), and ticagrelor (Brilinta)were evaluated by analyzing the metabolic activity of the CYP2C19 and CYP3A4 enzymes.Clinical management guidelines based on PGx findings for these medications have been established by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 7 and PharmGKB.Results: PMCDx studied 54 clinical samples.The results showed that 3 patients showed poor metabolizers, and 15 patients showed intermediate metabolizers, a total of 33% of patients have an increased risk of pharmacotherapy failure.Clopidogrel should be avoided to these patients.There are 10 cases, 18.5% of the patients in this study showed one or two decreased function alleles detected in CYP3A4.Ticagrelor (Brilinta) may present with higher plasma concentrations of the active medication, thus an increased risk of side effects may occur.This medication should be either avoided or the patient's medication response should be monitored to the guide dosing.Conclusion: Implementing population-wide screening for CYP2C19 and CYP3A4 variants not only identifies individuals who are poor or intermediate metabolizers but also facilitates tailored treatment strategies.The significance of the pharmacogenetics testing lies in its potential to enhance medication adherence, optimize therapeutic regimens, and ultimately improve patient outcomes while reducing healthcare costs associated with adverse drug reactions and ineffective therapies.Integrating pharmacogenetics into routine clinical practice represents a crucial advancement in the precision medicine landscape, promising enhanced efficacy in cardiovascular disease management.The use of pharmacogenetic testing can serve as a foundational element in developing a more personalized and effective approach to treating cardiovascular disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".