Higher Urine bis(Monoacylglycerol)Phosphate Levels in LRRK2 G2019S Mutation Carriers: Implications for Therapeutic Development
Bibliographic record
Abstract
BACKGROUND: LRRK2 mutations are a common cause of dominantly inherited PD. Previous studies showed decreases in urine levels of didocohexaenoyl (22:6) bis(monoacylglycerol)phosphate in LRRK2-knockout mice and in non-human primates treated with LRRK2 kinase inhibitors. We hypothesized that urine levels of bis(monoacylglycerol)phosphate isoforms will be higher in individuals with a PD-causing gain-of-kinase function mutation, LRRK2 G2019S. The objective of this study was to investigate alterations in urinary phospholipids as biomarkers of LRRK2 mutations and Parkinson's disease status/phenotypes. METHODS: Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to assess 54 bioactive phospholipids in urine from the LRRK2 Cohort Consortium (n = 80). To confirm and extend the findings, urine from an independent LRRK2 cohort from Columbia University Irving Medical Center (n = 116) was used. Both cohorts were composed of LRRK2 G2019S carriers and non-carriers with and without PD. RESULTS: In each cohort, 4 bis(monoacylglycerol)phosphate isoforms (di-18:1-bis[monoacylglycerol]phosphate, didocohexaenoyl [22:6] bis[monoacylglycerol] phosphate, 2,2'-di-22:6-bis[monoacylglycerol]phosphate, and 2,2'-di-18:1-bis[monoacylglycerol]phosphate) were significantly higher (2.5- to 4.3-fold) in G2019S carriers compared with non-carriers. Interestingly, 2,2'-di-18:1-bis(monoacylglycerol)phosphate levels were marginally higher in LRRK2 carriers with PD than in those without PD (P = 0.045). Moreover, increased 2,2' and total di-22:6-bis(monoacylglycerol)phosphate were associated with worse cognitive status assessed by the Montreal Cognitive Assessment (P = 0.0033 and 0.0144, respectively). CONCLUSIONS: The observed association of bis(monoacylglycerol)phosphate isoforms with LRRK2 G2019S mutation, PD status among G2019S carriers, and correlation with cognitive decline suggest the potential use of urinary bis(monoacylglycerol)phosphate isoforms as biomarkers for clinical trials of LRRK2-targeted therapies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".