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Published in final edited form as: Neurobiol Aging. 2021 Feb 28;103:142.e1–142.e5. doi: 10.1016/j.neurobiolaging.2021.02.018

LRRK2 p.M1646T is associated with glucocerebrosidase activity and with Parkinson’s disease

Yuri L Sosero 1,2, Eric Yu 1,2, Lynne Krohn 1,2, Uladzislau Rudakou 1,2, Kheireddin Mufti 1,2, Jennifer A Ruskey 1,3, Farnaz Asayesh 1,3, Sandra B Laurent 3, Dan Spiegelman 1, Stanley Fahn 4, Cheryl Waters 4, S Pablo Sardi 5; International Parkinson Disease Genomics Consortium (IPDGC), Sara Bandres-Ciga 6, Roy N Alcalay 4,7, Ziv Gan-Or 1,2,3, Konstantin Senkevich 1,3,*
PMCID: PMC8178224  NIHMSID: NIHMS1688406  PMID: 33781610

Abstract

The LRRK2 p.G2019S Parkinson’s disease (PD) variant is associated with elevated glucocerebrosidase (GCase) activity in peripheral blood. We aimed to evaluate the association of other LRRK2 variants with PD and its association with GCase activity. LRRK2 and GBA were fully sequenced in 1,123 PD patients and 576 controls from the Columbia and PPMI cohorts, in which GCase activity was measured in dried blood spots by liquid chromatography-tandem mass spectrometry. LRRK2 p.M1646T was associated with increased GCase activity in the Columbia University cohort (β=1.58, p=0.0003), and increased but not significantly in the PPMI cohort (β=0.29, p=0.58). p.M1646T was associated with PD (OR=1.18, 95%CI=1.09-1.28, p=7.33E-05) in 56,306 PD patients and proxy-cases, and 1.4 million controls. Our results suggest that the p.M1646T variant is associated with risk of PD with a small effect and with increased GCase activity in peripheral blood.

Keywords: Parkinson’s disease, GBA, Glucocerebrosidase, LRRK2

1. Introduction

Parkinson’s disease (PD) is mostly caused by an interaction between genetic and environmental factors (Ascherio and Schwarzschild, 2016). Variants in GBA and LRRK2 are among the most common genetic risk factors of PD (Gan-Or et al., 2015; Ross et al., 2011). The frequency of these variants varies in different populations, with GBA variants found in 5-20% (Gan-Or et al., 2015) and LRRK2 variants reported in 1-40% of PD patients (Healy et al., 2008).

The activity of the enzyme encoded by GBA, β-glucocerebrosidase (GCase), is reduced in carriers of GBA variants, but also in a subset of PD patients without GBA variants (Alcalay, R. N. et al., 2015; Gegg et al., 2012). There are contradicting results regarding the effect of the LRRK2 p.G2019S variant on GCase activity. In peripheral blood, this variant was associated with an increased activity (Alcalay, R. N. et al., 2015), whereas in patient-derived dopaminergic neurons with LRRK2 variants GCase activity was reduced (Ysselstein et al., 2019). GCase protein level, as studied in dopaminergic neurons, was not affected in carriers of LRRK2 pathogenic variants (Ysselstein et al., 2019). A variant in TMEM175, p.T393M, has been associated with reduced GCase activity and, together with GBA variants and the LRRK2 p.G2019S variant, explain only 23% of the variance in GCase activity in peripheral blood (Krohn et al., 2020). These observations suggest that other genetic or environmental factors affect GCase activity.

In the current study, we performed full sequencing of LRRK2 and GBA and examined the effect of common LRRK2 variants on GCase activity in peripheral blood in two cohorts: from Columbia University and from the Parkinson's Progression Markers Initiative (PPMI). We further examined the association of LRRK2 variants identified through this analysis with risk of PD using data from the International Parkinson’s Disease Genomics Consortium (IPDGC), UK biobank and 23andMe, Inc. genome-wide association study (GWAS) meta-analysis (Nalls et al., 2019).

2. Materials and methods

2.1. Study population

To analyze the effects of LRRK2 variants on GCase activity, two cohorts were included: 1) The Columbia University cohort (n=1,229, PD=797, Controls=432) and 2) The PPMI cohort (n=470, PD=326, Controls=144). Both cohorts have been previously described (Alcalay, R. N. et al., 2015; Alcalay et al., 2020), and their demographic data is detailed in Table 1. The Columbia cohort consisted of patients and controls of mixed ethnicity (mainly of European origin, including 308 individuals of Ashkenazi Jewish descent). Data on the effect of the LRRK2 p.M1646T variant on risk of PD was extracted from the recent PD GWAS, including 37,688 PD patients, 18,618 UK Biobank proxy-cases and 1.4 million control (Nalls et al., 2019). All PD patients were diagnosed by movement disorder specialists according to the UK brain bank criteria (Hughes et al., 1992) or the MDS clinical diagnostic criteria (Postuma et al., 2015).

Table 1.

Demographic data of the cohorts to study LRRK2 effect on GCase activity.

Cohort PD Controls PD age
(mean, SD
in years)		 Controls
age (mean,
SD in years)		 PD males
(N,
percentage)		 Controls
males (N,
percentage)
Columbia 797 432 65.80 (11.04) 64.75 (9.94) 512 (64%) 116 (27%)
PPMI 326 144 60.12 (9.67) 61.37 (10.91) 216 (66%) 100 (69%)
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PD, Parkinson’s disease; SD, standard deviation; Columbia, cohort from Columbia University, NY; PPMI, Parkinson's Progression Markers Initiative cohort.

2.2. Standard Protocol Approvals, Registrations, and Patient Consents

The institutional review boards approved the study protocols, and informed consent was obtained from all participants before entering the study. 23andMe participants provided informed consent and participated in the research online, under a protocol approved by the external AAHRPP-accredited IRB, Ethical & Independent Review Services (E&I Review).

2.3. Genetic analysis

2.3.1. LRRK2 and GBA Sequencing in the Columbia University cohort

We performed full sequencing of LRRK2 and GBA in the Columbia University cohort using targeted sequencing with Molecular Inversion Probes (MIPs) and Sanger sequencing as previously described (Ouled Amar Bencheikh et al., 2018; Ross et al., 2016; Ruskey et al., 2019). The full protocol and the library of MIPs used for sequencing LRRK2 and GBA are available online (https://github.com/gan-orlab/MIP_protocol). A standard quality control protocol was performed as previously described (Rudakou et al., 2020), and the code is available at https://github.com/gan-orlab/MIPVar/.

2.3.2. Genetic data from PPMI and IPDGC

Due to the alignment difficulties with GBA, data on GBA variants in the PPMI cohort were extracted from combined data including whole genome sequencing data, whole exome sequencing data and RNA-seq as previously reported (Alcalay et al., 2020). Data on LRRK2 p.G2019S, p.M1646T, p.N551K-p.R1398H and p.N2081D were extracted from imputed GWAS data (Illumina Immunochip and NeuroX arrays) downloaded from the PPMI project website (https://ida.loni.usc.edu/). To examine the association of LRRK2 variants with PD, we extracted data from the recent PD GWAS meta-analysis (Nalls et al., 2019).

2.4. GCase activity

Dried blood spots (DBS) were obtained as previously described (Olivova et al., 2008; Reuser et al., 2011). DBS in the Columbia cohort were prepared from fresh blood (Alcalay, R. N. et al., 2015). GCase activity was measured in participants from Columbia University at Sanofi laboratories by liquid chromatography-tandem mass spectrometry (LC-MS/MS) from DBS, as a part of multiplex assay with four additional lysosomal enzymes as previously described (Alcalay, R. N. et al., 2015; Zhang et al., 2008). PPMI study participants donated blood on the first visit (baseline) and every year, which was frozen and stored in −80C freezer. Samples from the first three years of the cohort were thawed, and DBS were obtained. Activity was measured as previously described, using the mean GCase activity for each participant across all visits (Alcalay et al., 2020).

2.5. Statistical Analysis

Linear regression models were used to test for association between common LRRK2 variants with minor allele frequency (MAF) >1% and GCase activity in the Columbia and PPMI cohorts, adjusting for age, sex, PD status, GBA status and ethnicity. In the PPMI cohort additional adjustment for white blood cells count was performed as suggested previously (Alcalay et al., 2020). We then repeated the analysis after excluding LRRK2 p.G2019S, p.M1646T, protective haplotype carriers (tagged by p.R1398H) and GBA variants carriers in both Columbia and PPMI cohorts. In addition, to examine whether there are sex-specific effects, we performed additional analyses stratifying the cohorts by sex (code available at https://github.com/gan-orlab/LRRK2_GCase). Bonferroni correction for multiple comparisons was applied as needed. Finally, we evaluated differences in GCase activity between carriers and non-carriers of rare LRRK2 variants with MAF < 1% in the Columbia cohort. To test the association between GCase activity and LRRK2 rare variants, t-test was performed. The pathogenicity of such variants was estimated using ClinVar and Varsome annotation (Kopanos et al., 2019; Landrum et al., 2018). All statistical analyses were performed using R version 3.6.3 or PLINK version 1.9 (Chang et al., 2015; Purcell et al., 2007).

3. Results

In the Columbia University cohort, we identified 26 LRRK2 common variants with MAF >1% (Supplementary Table 1), including 9 nonsynonymous variants, 12 intronic variants and 5 synonymous variants.

The LRRK2 p.M1646T variant was associated with increased GCase activity compared to non-carriers (12.65 mmol/l/h vs. 11.38 mmol/l/h, respectively, β=1.58, p=0.0003, Table 2, Supplementary Table 1) in the Columbia University cohort. The effect of p.M1646T on GCase activity was stronger in PD (GCase=13.08 mmol/l/h, β=1.74, p=0.0011) and did not reach statistical significance in controls (GCase=11.96 mmol/l/h, β=1.37, p=0.068, Table 2, Supplementary Table 2-3). After exclusion of p.G2019S carriers, the association of p.M1646T with increased activity remained strong (GCase=12.64 mmol/l/h, β=1.73, p=6.24E-05, Supplementary Table 4-5). The LRRK2 p.G2019S variant was associated with increased GCase activity as previously described (Alcalay, R. N. et al., 2015). Two variants from the protective haplotype p.N551K-p.R1398H-p.K1423K were nominally associated with GCase activity, but this association was not statistically significant after Bonferroni correction (Table 2). When removing p.M1646T and p.G2019S from the analyses, we observed an increase both in the effect size and in the significance of the association between the protective haplotype and GCase activity (GCase=11.93 mmol/l/h, β=0.66, p=0.005, Supplementary Table 6), still not surpassing Bonferroni correction. Using data from the recent PD GWAS meta-analysis (Nalls et al., 2019), including 37,688 PD patients, 18,618 UK Biobank proxy-cases and 1.4 million controls, we then demonstrated that the LRRK2 p.M1646T variant was associated with PD (OR=1.18 95% CI=1.09-1.28, p=7.33E-05).

Table 2.

Impact of LRRK2 variants on GCase activity.

LRRK2 variants N of carriers Estimate SE p-value* GCase_mean Gcase_SD
Columbia cohort
PD + controls (N=1229)
p.R1398H 204 0.521 0.233 0.026 11.960 3.804
p.M1646T 58 1.578 0.431 0.0003 12.652 4.529
p.G2019S 61 1.370 0.438 0.0018 12.798 4.340
PD (N=797)
p.R1398H 123 0.495 0.298 0.097 11.776 3.863
p.M1646T 36 1.736 0.528 0.0011 13.078 4.600
p.G2019S 57 1.440 0.450 0.0014 12.877 4.471
Controls (N=432)
p.R1398H 81 0.755 0.383 0.050 12.240 3.720
p.M1646T 22 1.367 0.746 0.068 11.956 4.425
p.G2019S 4 −0.030 1.719 0.986 11.658 1.286
PPMI cohort
PD + controls (N=470)
p.R1398H 61 −0.724 0.340 0.034 10.936 2.961
p.M1646T 23 0.295 0.543 0.587 12.717 3.510
p.G2019S 6 0.004 1.050 0.997 11.453 2.648
PD (N=326)
p.R1398H 41 −0.893 0.406 0.028 10.445 3.045
p.M1646T 17 0.073 0.623 0.907 12.385 3.259
p.G2019S 6 −0.078 1.037 0.940 11.453 2.648
Controls (N=144)
p.R1398H 20 −0.240 0.622 0.701 11.941 2.564
p.M1646T 6 1.169 1.082 0.282 13.657 4.333
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SE, standard error; N, number; GCase_mean, mean glucocerebrosidase activity, μmol/l/h; SD, standard deviation; PD, Parkinson’s disease; Columbia, cohort from Columbia University, NY; PPMI, Parkinson's Progression Markers Initiative cohort

*

Bonferroni correction significance threshold for Columbia cohort (α=0.05/26=0.0019) and (α=0.05/5=0.01) for PPMI cohort.

As a replication for GCase activity, we used data from the PPMI cohort, and analyzed the association of p.R1398H (representing the protective haplotype), p.M1646T, p.G2019S and p.N2081D with GCase activity (Table 2, Supplementary Table 8). The p.M1646T variant showed the same direction of effect and similar average GCase activity value as observed in the Columbia cohort, but did not reach statistical significance, possibly due to the small number of carriers (n=23), compared to non-carriers (12.72 mmol/l/h vs. 11.84 mmol/l/h, respectively, β=0.29, p=0.59; Table 2). Only six carriers of the LRRK2 p.G2019S variant were included in the PPMI cohort, and the association of this variant with GCase activity, as well as of the protective haplotype, were not statistically significant after Bonferroni correction (Table 2, Supplementary Table 8). Stratified analysis by sex did not identify sex differences in GCase activity in both cohorts (Supplementary Table 7,8).

We have found 32 rare nonsynonymous variants in the LRRK2 gene with MAF < 1% in the Columbia cohort (Supplementary table 9), none of which were reported as pathogenic. The rare variant p.E334K was associated with a decreased GCase activity (GCase=10.61±0.53 mmol/l/h, p=0.007; Supplementary Table 9). Among the three carriers of this variant, two were PD patients. This variant has uncertain significance as reported in ClinVar. We further studied the association of GCase activity in carriers of all rare variants versus non carriers and did not find any statistically significant difference (Supplementary Table 9).

4. Discussion

In the current study, we show that the LRRK2 p.M1646T variant is associated with PD and with increased GCase activity in peripheral blood. The association of this variants with PD has been previously suggested (Heckman et al., 2013; Ross et al., 2011) and we confirmed this association in a larger European cohort. Although the p-value did not reach the GWAS level of statistical significance (Nalls et al., 2019), the association between p.M1646T and PD replicated in different cohorts suggests that this variant is a risk factor of PD. Despite its smaller effect on PD risk compared to the LRRK2 p.G2019S variant, the effect of p.M1646T on GCase activity was larger than the effect of p.G2019S. However, since the results on GCase activity did not fully replicate in the PPMI cohort, additional studies are required to understand the associations between LRRK2 variants, GCase activity and PD risk.

In a recent study, the LRRK2 pathogenic variants p.G2019S, p.R1441G, and p.R1441C were associated with reduced GCase activity in patient-derived dopaminergic neurons, and correction of these variants resulted in normalization of GCase activity (Ysselstein et al., 2019). Conversely, in the current study, deleterious LRRK2 variants (p.G2019S and p.M1646T) were associated with increased GCase activity in peripheral blood. There are several potential explanations for these differences in the direction of effects on GCase activity, including: a) different effects of LRRK2 variants in the central nervous system vs. peripheral blood, b) the possibility that iPSC-derived dopaminergic neurons, which are young cells, are different than patient tissues, due to the natural aging process, and c) the different methods used to measure GCase activity.

Considering the study suggesting that LRRK2 variants are associated with reduced GCase activity (Ysselstein et al., 2019), drugs targeting LRRK2 activity could be repurposed for GBA-PD, and drugs that target GCase activity could be used for LRRK2-PD. However, this potential association between LRRK2, GBA and GCase activity should be carefully studied further, since other data suggests that LRRK2 variants are not associated with reduced GCase activity. Patients with GBA-PD (and thus, reduced GCase activity) have a more severe phenotype with faster disease progression and cognitive decline, depression and anxiety, compared to sporadic PD (Cilia et al., 2016; Liu et al., 2016; Swan et al., 2016). In contrast, LRRK2 variants carriers have a milder phenotype with slower disease progression and lower frequency of cognitive symptoms compared to sporadic PD (Alcalay, Roy N. et al., 2015; Piredda et al., 2020). Moreover, two independent studies demonstrated that carriers of both LRRK2 and GBA variants seem to have a benign phenotype, similar to those who carry LRRK2 variants only (Omer et al., 2020; Yahalom et al., 2019) . If indeed LRRK2 variants lead to reduced GCase activity as suggested (Ysselstein et al., 2019), we would expect that patients with both LRRK2 and GBA variants would have a severe phenotype. Instead, their phenotype is milder (Omer et al., 2020; Yahalom et al., 2019), which may raise the hypothesis that the increased GCase activity we observed in peripheral blood may have some protective effect on PD phenotype. This hypothesis requires additional studies in human cohorts and disease models.

Our study has several limitations. In our cohorts, difference in sex between PD patients and controls was significant. To address this limitation, we adjusted the regression model with sex as covariate, as well as other covariates. The Columbia cohort differed from the PPMI cohort in terms of ethnicity. The PPMI cohort is predominantly European, while the Columbia cohort included individuals of mixed ethnicity, mainly of European and Ashkenazi Jewish ancestry. This was addressed adjusting the regression models for ethnicity. Due to ethnical differences, the total number of carriers of LRRK2 variants in PPMI cohort was relatively low comparing to the Columbia cohort. Another limitation is that GCase activity was measured in blood, which does not necessarily reflect GCase activity in the brain. There were also technical differences in sample preparation: in the Columbia cohort GCase activity was measured in DBS prepared from fresh blood and in the PPMI cohort DBS was prepared from frozen blood. These differences between the cohorts may explain the lack of replication of some of the results.

To conclude, we demonstrated that the LRRK2 p.M1646T variant is associated with increased GCase activity in peripheral blood and with increased risk of PD. The interplay between LRRK2, GBA and GCase activity should be studied in additional cohorts and relevant disease models.

Supplementary Material

1

5. Acknowledgements

Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database (www.ppmiinfo.org/data). For up-to-date information on the study, visit www.ppmiinfo.org.” “PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including (list the full names of all of the PPMI funding partners found at www.ppmiinfo.org/fundingpartners). We would also like to thank the research participants and employees of 23andMe for making this work possible. The full GWAS summary statistics for the 23andMe discovery data set will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. Please visit research.23andme.com/collaborate/ for more information and to apply to access the data. We would like to also thank all members of the International Parkinson Disease Genomics Consortium (IPDGC). For a complete overview of members, acknowledgements and funding, please see http://pdgenetics.org/partners. ZGO is supported by the Fonds de recherche du Québec - Santé (FRQS) Chercheurs-boursiers award, in collaboration with Parkinson Quebec, and by the Young Investigator Award by Parkinson Canada. The access to part of the participants for this research has been made possible thanks to the Quebec Parkinson’s Network (http://rpq-qpn.ca/en/). KS is supported by a post-doctoral fellowship from the Canada First Research Excellence Fund (CFREF), awarded to McGill University for the Healthy Brains for Healthy Lives initiative (HBHL). We thank Daniel Rochefort, Hélène Catoire, Clotilde Degroot and Vessela Zaharieva for their assistance.

7. Funding Sources

This study was financially supported by grants from the Michael J. Fox Foundation, the Canadian Consortium on Neurodegeneration in Aging (CCNA), the Canada First Research Excellence Fund (CFREF), awarded to McGill University for the Healthy Brains for Healthy Lives initiative (HBHL), and Parkinson Canada. The Columbia University cohort is supported by the Parkinson’s Foundation, the National Institutes of Health (K02NS080915, and UL1 TR000040) and the Brookdale Foundation. This research was supported in part by the Intramural Research Program of the NIH, National institute on Aging.

Footnotes

6.

Relevant conflicts of interest/financial disclosures:

SF received consulting fees/honoraria for board membership from Retrophin Inc., Sun Pharma Advanced Research Co., LTD and Kashiv Pharma. CHW received research support from Sanofi, Biogen, Roche, consulting fees/honoraria from Amneal, Adamas, Impel, Kyowa, Mitsubishi, Neurocrine, US World Meds, Acadia, Acorda. RNA received consultation fees from Biogen, Denali, Genzyme/Sanofi and Roche. ZGO received consultancy fees from Lysosomal Therapeutics Inc. (LTI), Idorsia, Prevail Therapeutics, Inceptions Sciences (now Ventus), Ono Therapeutics, Denali and Deerfield. Rest of the authors have nothing to report.

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