Genetics of Lithium Response in Bipolar Disorder
Bibliographic record
Abstract
INTRODUCTION: Lithium remains the best-established long-term treatment for bipolar disorder because of its efficacy in maintaining periods of remission and reducing the risk of suicide. Not all patients successfully respond to lithium treatment, and the individual response, including the occurrence of side effects, is highly variable and not easy to predict. The genetic basis of lithium response is supported by the fact that the response clusters in families. Likewise, recent high-throughput genomic analyses have shed light on its genetic architecture. METHODS: This nonsystematic review summarizes the main results obtained in genetic association studies using lithium response as target trait. RESULTS: These studies suggest that several genetic loci might modulate the way a patient responds to lithium maintenance treatment. Further studies to fully characterize the genetic architecture of lithium response are warranted. DISCUSSION: The identification of genetic factors associated with lithium response will be important for (1) better understanding of lithium's mode of action and (2) development of a predictive model for optimization of long-term treatment of bipolar disorder.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".