Polygenic risk scores for the diagnosis and management of dyslipidemia
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review current progress in the use of polygenic risk scores for lipid traits and their use in the diagnosis and treatment of lipid disorders. RECENT FINDINGS: Inherited lipid disorders, including those causing extremes of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, or triglycerides were initially identified as monogenic traits, in which a single rare variant with large effect size is responsible for the phenotype. More recently, a polygenic basis for many lipid traits has also been identified. Patients with polygenic dyslipidemia can be identified through the use of polygenic risk scores (PRSs), which collapse information from a handful to several million genetic variants into a single metric. SUMMARY: PRSs for lipid traits may aid in the identification of the genetic basis for the lipid phenotype in individual patients, may provide additional information regarding the risk of cardiovascular disease, and could help in guiding therapeutic decision making.
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) | 0.000 | 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".