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Record W4408207574 · doi:10.1093/braincomms/fcaf103

<i>LRRK2</i> -associated parkinsonism with and without <i>in vivo</i> evidence of alpha-synuclein aggregates: longitudinal clinical and biomarker characterization

2025· article· en· W4408207574 on OpenAlexafffund
Lana M. Chahine, David-Erick Lafontant, Seung Ho Choi, Hirotaka Iwaki, Cornelis Blauwendraat, Andrew Singleton, Michael C. Brumm, Roy N. Alcalay, Kelly Nudelman, Alain Dagher, Andrew Vo, Charles S. Venuto, Karl Kieburtz, Kathleen L. Poston, Susan Bressman, Paulina González-Latapí, Brian Avants, Christopher S. Coffey, Danna Jennings, Eduardo Tolosa, Andrew Siderowf, Kenneth Marek, Tatyana Simuni, Kenneth Marek, Caroline M. Tanner, Tanya Simuni, Douglas Galasko, Roseanne D. Dobkin, Tatiana M. Foroud, Brit Mollenhauer, Dan Weintraub, Ethan Brown, Mark Frasier, Todd Sherer, Sohini Chowdhury, Aleksandar Videnović, Duygu Tosun, Werner Poewe, Jan Hammer, Raymond James, Ekemini Riley, John Seibyl, Leslie M. Shaw, David G. Standaert, Sneha Mantri, Nabila Dahodwala, Michael A. Schwarzschild, Connie Marras, Hubert Fernandez, Ira Shoulson, Helen Rowbotham, Paola Casalin, Claudia Trenkwalder, Jamie L. Eberling, Katie Kopil, Maggie Kuhl, L. Kirsch, Emily Flagg, Bridget McMahon, Craig Stanley, Kim Fabrizio, Dixie Ecklund, Trevis Huff, Laura Heathers, Christopher Hobbick, Gena Antonopoulos, Chelsea Caspell‐Garcia, Arthur W. Toga, Karen Crawford, Doug Galasko, Andrew Singleton, Thomas J. Montine, Monica Korell, Charles Adler, Amy W. Amara, Paolo Barone, Bastiaan R. Bloem, Kathrin Brockmann, Norbert Brüggemann, Kelvin L. Chou, Alberto J. Espay, Stewart A. Factor, Michelle Fullard, Robert Hauser, Penelope Hogarth, Shu-Ching Hu, Stuart Isaacson, Christine Klein, Rejko Krüger, Mark Lew, Zoltan Mari, María José Martí, Nikolaus R. McFarland, Tiago Mestre, Emile Moukheiber, Alastair J. Noyce, Wolfgang H. Oertel, Njideka Okubadejo, Rajesh Pahwa, Nicola Pavese, Ron Postuma, Giulietta Riboldi, Lauren Ruffrage, Javier Ruiz‐Martínez, David A. Russell, Marie Saint‐Hilaire, Nancy Dos Santos, Wesley Schlett, Ruth B. Schneider, Holly A. Shill, David Shprecher, Leonidas Stefanis, Yen Tai, Arjun Tarakad

Bibliographic record

VenueBrain Communications · 2025
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute on AgingAvid RadiopharmaceuticalsH. Lundbeck A/SServierVoyager TherapeuticsUnion Chimique BelgeBristol-Myers SquibbAligning Science Across Parkinson’sNeurocrine BiosciencesCerevel TherapeuticsJazz PharmaceuticalsTakeda Pharmaceuticals U.S.A.Denali CommissionAbbVieJanssen BiotechTeva Pharmaceutical IndustriesVerily Life SciencesAmathus TherapeuticsBiohaven PharmaceuticalsCelgenePfizerBiogenRocheMichael J. Fox Foundation for Parkinson's ResearchSanofiWeston Family FoundationMerck
KeywordsParkinsonismBiomarkerAlpha-synucleinIn vivoLRRK2Parkinson's diseaseNeuroscienceMedicineChemistryPsychologyPathologyBiologyDiseaseBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Among LRRK2-associated parkinsonism cases with nigral degeneration, over two-thirds demonstrate evidence of pathologic alpha-synuclein, but many do not. Understanding the clinical phenotype and underlying biology in such individuals is critical for therapeutic development. Our objective was to compare clinical and biomarker features, and rate of progression over 4 years of follow-up, among LRRK2-associated parkinsonism cases with and without in vivo evidence of alpha-synuclein aggregates. Data were from the Parkinson’s Progression Markers Initiative, a multicentre prospective cohort study. The sample included individuals diagnosed with Parkinson disease with pathogenic variants in LRRK2. Presence of CSF alpha-synuclein aggregation was assessed with seed amplification assay. A range of clinician- and patient-reported outcome assessments were administered. Biomarkers included dopamine transporter scan, CSF amyloid-beta1-42, total tau, phospho-tau181, urine bis(monoacylglycerol)phosphate levels and serum neurofilament light chain. Linear mixed-effects (LMMs) models examined differences in trajectory in CSF-negative and CSF-positive groups. A total of 148 LRRK2 parkinsonism cases (86% with G2019S variant), 46 negative and 102 positive for CSF alpha-synuclein seed amplification assay, were included. At baseline, the negative group was older than the positive group [median (inter-quartile range) 69.1 (65.2–72.3) versus 61.5 (55.6–66.9) years, P < 0.001] and a greater proportion were female [28 (61%) versus 43 (42%), P = 0.035]. Despite being older, the negative group had similar duration since diagnosis and similar motor rating scale [16 (11–23) versus 16 (10–22), P = 0.480] though lower levodopa equivalents. Only 13 (29%) of the negative group were hyposmic, compared with 75 (77%) of the positive group. The negative group, compared with the positive group, had higher per cent-expected putamenal dopamine transporter binding for their age and sex [0.36 (0.29–0.45) versus 0.26 (0.22–0.37), P < 0.001]. Serum neurofilament light chain was higher in the negative group compared with the positive group [17.10 (13.60–22.10) versus 10.50 (8.43–14.70) pg/mL; age-adjusted P-value = 0.013]. In terms of longitudinal change, the negative group remained stable in functional rating scale score in contrast to the positive group who had a significant increase (worsening) of 0.729 per year (P = 0.037), but no other differences in trajectory were found. Among individuals diagnosed with Parkinson disease with pathogenic variants in the LRRK2 gene, we found clinical and biomarker differences in cases without versus with in vivo evidence of CSF alpha-synuclein aggregates. LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates as a group exhibit less severe motor manifestations and decline. The underlying biology in LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates requires further investigation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.065
GPT teacher head0.363
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations17
Published2025
Admission routes2
Has abstractyes

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