Affective phenotypes in heterozygous LRRK2 R1441G knock-in mice
Bibliographic record
Abstract
Several missense mutations in the LRRK2 gene are linked to familial Parkinson’s disease (PD). Although LRRK2 mutant mouse models typically lack gross motor impairments, their contribution to non-motor PD symptoms remains largely underexplored. In this study, we showed that the R1441G missense mutation promoted behavioural despair in the forced swim test (FST) and led to anhedonia, reflected in reduced sucrose preference, while the typical expression of helplessness in avoidance learning, induced by undermining locus of control, was unaffected. Notably, these depressive phenotypes emerged predominantly in heterozygous R1441G knock-in (KI) mice, and a similar dominant negative phenotype was evident in the elevated plus maze, with heterozygous mutants exhibiting lower anxiety than wild-type (WT) mice. Together, these results suggest that the R1441G mutation may impact select dimensions of affective function in prodromal adult mice, irrespective of sex. In contrast, no overt behavioural phenotypes were detected in cognitive, social, or motor domains, including associative learning, hippocampus-dependent spatial learning, sensorimotor gating, social interaction, motor coordination, grip strength, or spontaneous locomotor activity. Further investigation is warranted to dissect the mechanisms underlying the domain-specific and seemingly dominant-negative behavioural effects of the R1441G mutation, especially in comparison to the behavioural phenotypes associated with other models of LRRK2 mutations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".