Abstract Background Lysosomal dysfunction plays a crucial role in the pathogenesis of Parkinson’s disease (PD), particularly among GBA1 mutation carriers. Beyond GBA1 , genes such as TMEM175 , SCARB2 , and CTSB identified in genome-wide association studies (GWAS) are also implicated in lysosomal pathways contributing to PD risk, although their functional effects in patients remain unclear. Proteins encoded by these lysosome-related genes have been explored as potential therapeutic targets in experimental models. Biomarker profiles, including clinical measures, α-syn seeding activity, lysosomal proteins, and sphingolipids, may facilitate patient stratification and support therapeutic monitoring in future clinical trials. Aim The aim of this study is to investigate the impact of genetic variants of three lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) on biomarker profiles in PD with and without GBA1 variants. Cross-sectional data from two German cohorts: the Tuebingen Parkinson Cohort (TUEPAC) and the DESCRIBE PD cohort of the German Center for Neurodegenerative Diseases were used as explorative cohorts, and data from Accelerating Medicines Partnership® Parkinson’s Disease (AMP-PD) were used as a validation cohort. The ultimate goal is to provide new data for patient stratification based on genetics, which might serve as a readout for target engagement and treatment efficiency assessment. Methods Three cohorts were analyzed: TUEPAC, DESCRIBE PD, and AMP-PD. TUEPAC and DESCRIBE PD were combined into a single German discovery cohort (TUEPAC-DESCRIBE-PD), while AMP-PD served as an independent validation cohort. Within each cohort, for subgroup analyses, PD patients were classified as the overall PD cohort (PD all ), and further stratified by GBA1 mutation status into PD patients without GBA1 mutations (PD GBA1 _wildtype ), and PD patients carrying GBA1 mutations (PD GBA1 ). We evaluated cognitive and motor function, as well as depression using the Montreal Cognitive Assessment (MoCA), Unified Parkinson Disease Rating Scale-part I II (UPDRS III), and Beck Depression Inventory-II(BDI-II) scales. Analyzed biomarkers included CSF α-syn seeding activity using seed amplification assay (SAA), CSF lysosomal protein levels of lysosomal integral membrane protein 2 (LIMP2), also known as SCARB2, cathepsin B (CTSB) and lysosome-associated membrane protein 2 (LAMP2), blood-based enzyme activity of the lysosomal glucocerebrosidase (GCase), and CSF sphingolipid profiles. PD patients carrying risk alleles in TMEM175 , SCARB2 , and CTSB were compared to non-carriers. Results Genotype-phenotype correlation analysis in TUEPAC-DESCRIBE-PD and AMP-PD revealed: (1) In PD all , the TMEM175 p.M393T risk variant was nominally associated with decreased cognitive function when adjusted for GBA1 mutation status in TUEPAC-DESCRIBE-PD; this association could not be replicated, although a similar trend was observed in the slightly smaller, but multicentric AMP-PD cohort; TMEM175 p.M393T was not significantly associated with BDI-I I or UPDRS-III scores in either cohort. (2) In PD GBA1 _wildtype , GCase activity was significantly lower in PD patients with SCARB2 rs6812193 risk allele in TUEPAC-DESCRIBE-PD, while a similar but non-significant trend was observed in AMP-PD; (3) In PD all , CSF levels of CTSB were nominally lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; in PD GBA1 _wildtype , LAMP2 was significantly lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; (4) In PD all , TMEM175 p.M393T risk allele was nominally associated with altered sphingolipid profiles across both TUEPAC-DESCRIBE-PD and AMP-PD cohorts. Conclusion These findings demonstrate that genetic variants in lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) have a functional impact on biomarker profiles in PD patients. Integrating genetic characterization with biochemical profiling provides a framework for patient stratification and may serve as a translational strategy to monitor target engagement and evaluate treatment efficacy in future clinical trials.
Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers
Background: Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson’s disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. Objective: To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. Methods: We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). Results: We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60–0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. Conclusion: Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.
Genomewide Association Studies of
LRRK2
Modifiers of Parkinson's Disease
Objective The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age‐at‐onset of Parkinson's disease. Methods We performed the first genomewide association study of penetrance and age‐at‐onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non‐cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age‐at‐onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age‐at‐onset in LRRK2 mutation carriers. Results A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E‐08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co‐immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E‐07; age‐at‐onset top variant: p value = 9.3E‐07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age‐at‐onset. Interpretation This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82–94
The Mutation Matters:
CSF
Profiles of
GCase
, Sphingolipids, α‐Synuclein in
PD