Frequency of Loss of Function Variants in <i>LRRK2</i> in Parkinson Disease
Bibliographic record
Abstract
Importance: Pathogenic variants in LRRK2 are a relatively common genetic cause of Parkinson disease (PD). Currently, the molecular mechanism underlying disease is unknown, and gain and loss of function (LOF) models of pathogenesis have been postulated. LRRK2 variants are reported to result in enhanced phosphorylation of substrates and increased cell death. However, the double knockout of Lrrk2 and its homologue Lrrk1 results in neurodegeneration in a mouse model, suggesting that disease may occur by LOF. Because LRRK2 inhibitors are currently in development as potential disease-modifying treatments in PD, it is critical to determine whether LOF variants in LRRK2 increase or decrease the risk of PD. Objective: To determine whether LRRK1 and LRRK2 LOF variants contribute to the risk of developing PD. Design, Setting, and Participants: To determine the prevailing mechanism of LRRK2-mediated disease in human populations, next-generation sequencing data from a large case-control cohort (>23 000 individuals) was analyzed for LOF variants in LRRK1 and LRRK2. Data were generated at 5 different sites and 5 different data sets, including cases with clinically diagnosed PD and neurologically normal control individuals. Data were collected from 2012 through 2017. Main Outcomes and Measures: Frequencies of LRRK1 and LRRK2 LOF variants present in the general population and compared between cases and controls. Results: Among 11 095 cases with PD and 12 615 controls, LRRK1 LOF variants were identified in 0.205% of cases and 0.139% of controls (odds ratio, 1.48; SE, 0.571; 95% CI, 0.45-4.44; P = .49) and LRRK2 LOF variants were found in 0.117% of cases and 0.087% of controls (odds ratio, 1.48; SE, 0.431; 95% CI, 0.63-3.50; P = .36). All association tests suggested lack of association between LRRK1 or LRRK2 variants and PD. Further analysis of lymphoblastoid cell lines from several heterozygous LOF variant carriers found that, as expected, LRRK2 protein levels are reduced by approximately half compared with wild-type alleles. Conclusions and Relevance: Together these findings indicate that haploinsufficiency of LRRK1 or LRRK2 is neither a cause of nor protective against PD. Furthermore, these results suggest that kinase inhibition or allele-specific targeting of mutant LRRK2 remain viable therapeutic strategies in PD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".