Back

Large-scale functional annotation establishes a reference framework for human LRRK2 variants

Cheung, A.; Pratuseviciute, N.; Black, K.; Lis, P.; Phung, T.; Cavin, M.; Morel, G.; Saari MacDonald, A.; Huin, V.; Zittel-Dirks, S.; Tonelli, F.; Riebenbauer, B.; Gasser, T.; Ruiz-Martinez, J.; Global Parkinsons Genetics Program (GP2), ; Morris, H. R.; Lange, L. M.; Dilliott, A. A.; Goldstein, O.; Shani, S.; Arnaud, L.; Zimprich, A.; Pirker, W.; Klein, C.; Alcalay, R.; Lohmann, K.; Alessi, D. R.; Sammler, E.

2026-06-26 neurology
10.64898/2026.06.17.26355034 medRxiv
Show abstract

Pathogenic variants in leucine-rich repeat kinase 2 (LRRK2) 1 are among the most frequent monogenic causes of Parkinson's disease (PD) and act through a gain-of-function mechanism of increased kinase activity. LRRK2-targeted therapies are in clinical development, but interpretation of the rapidly expanding catalogue of rare LRRK2 variants remains a barrier to translation. Here, we present functionally annotated data on more than 350 LRRK2 variants using a standardized cellular assay with Rab10 phosphorylation as a readout of kinase activity and integrated these data with curated genetic and clinical annotations from the Movement Disorders Society Genetic Mutation Database (MDSGene). Variants differed in activation magnitude, ranging from modest increases (e.g., p.G2019S) to strongly activating substitutions such as p.Y1699C or p.L1795F. Activating variants occurred across the full length of LRRK2, although the largest effects clustered within the ROC-COR regulatory hub, where structural analysis identified subdomains forming an allosteric scaffold controlling kinase output. All known/established pathogenic variants showed increased activity, whereas benign and likely benign variants remained within the wild-type range. Functional effect sizes correlated with pathway activation in patient-derived immune cells, altogether providing a framework for ACMG-based variant interpretation in which kinase activation can support PS3 functional evidence for reclassification of variants.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Brain
168 papers in training set
Top 0.1%
19.2%
2
Movement Disorders
71 papers in training set
Top 0.1%
15.6%
3
npj Parkinson's Disease
105 papers in training set
Top 0.2%
13.4%
4
Nature Communications
5641 papers in training set
Top 20%
8.2%
50% of probability mass above
5
Acta Neuropathologica
58 papers in training set
Top 0.3%
5.3%
6
Annals of Neurology
64 papers in training set
Top 0.4%
3.3%
7
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 19%
2.8%
8
Brain Communications
166 papers in training set
Top 2%
2.2%
9
eBioMedicine
183 papers in training set
Top 2%
1.8%
10
Acta Neuropathologica Communications
89 papers in training set
Top 1%
1.6%
11
Journal of Neurology, Neurosurgery & Psychiatry
30 papers in training set
Top 0.4%
1.6%
12
Neuron
337 papers in training set
Top 4%
1.2%
13
Science Advances
1243 papers in training set
Top 24%
1.2%
14
Communications Biology
993 papers in training set
Top 20%
1.2%
15
Scientific Reports
3612 papers in training set
Top 63%
1.2%
16
Nature Medicine
125 papers in training set
Top 2%
1.2%
17
Molecular Neurodegeneration
55 papers in training set
Top 1%
1.1%
18
Journal of Parkinson's Disease
13 papers in training set
Top 0.2%
1.1%
19
PLOS Pathogens
820 papers in training set
Top 8%
1.1%
20
Neurology Genetics
15 papers in training set
Top 0.2%
1.0%
21
Nature Genetics
286 papers in training set
Top 4%
1.0%
22
Genome Medicine
183 papers in training set
Top 5%
0.9%
23
PLOS ONE
5266 papers in training set
Top 63%
0.6%
24
Cell Reports
1498 papers in training set
Top 30%
0.5%
25
Molecular Systems Biology
162 papers in training set
Top 4%
0.5%