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Several genetic and environmental factors have been reported in progressive supranuclear palsy (PSP), although none were identified as a definitive cause. We aimed to explore potential gene-environment interactions in PSP. Two hundred and ninety two PSP cases and 292 controls matched for age, sex, and race from the ENGENE-PSP were analyzed to determine the association between PSP and minor alleles of 5 single nucleotide polymorphisms (SNPs) in 4 genes (MAPT, MOBP, EIF2AK3, and STX6), which were previously associated with PSP risk. Interactions between these SNPs and environmental factors, including previously reported occupational and agricultural risk factors for PSP, were assessed for PSP odds and age of symptom onset. Minor alleles of MAPTrs242557 and EIF2AK3rs7571971 were individually associated with increased odds; MAPTrs8070723 minor alleles were associated with lower PSP odds. There were several gene-environment interactions for PSP odds and age of symptom onset, however, they did not remain significant after FDR-correction. Larger scale studies are required to determine potential interactions.

BackgroundThe Parkinson's Progression Markers Initiative (PPMI) is an ongoing observational, longitudinal cohort study of participants with Parkinson's disease, healthy controls, and carriers of the most common Parkinson's disease-related genetic mutations, which aims to define biomarkers of Parkinson's disease diagnosis and progression. All participants are assessed annually with a battery of motor and non-motor scales, 123-I Ioflupane dopamine transporter (DAT) imaging, and biological variables. We aimed to examine whether non-manifesting carriers of LRRK2 and GBA mutations have prodromal features of Parkinson's disease that correlate with reduced DAT binding.MethodsThis cross-sectional analysis is based on assessments done at enrolment in the subset of non-manifesting carriers of LRRK2 and GBA mutations enrolled into the PPMI study from 33 participating sites worldwide. The primary objective was to examine baseline clinical and DAT imaging characteristics in non-manifesting carriers with GBA and LRRK2 mutations compared with healthy controls. DAT deficit was defined as less than 65% of putamen striatal binding ratio expected for the individual's age. We used t tests, χ2 tests, and Fisher's exact tests to compare baseline demographics across groups. An inverse probability weighting method was applied to control for potential confounders such as age and sex. To account for multiple comparisons, we applied a family-wise error rate to each set of analyses. This study is registered with ClinicalTrials.gov, number NCT01141023.FindingsBetween Jan 1, 2014, and Jan 1, 2019, the study enrolled 208 LRRK2 (93% G2019S) and 184 GBA (96% N370S) non-manifesting carriers. Both groups were similar with respect to mean age, and about 60% were female. Of the 286 (73%) non-manifesting carriers that had DAT imaging results, 18 (11%) LRRK2 and four (3%) GBA non-manifesting carriers had a DAT deficit. Compared with healthy controls, both LRRK2 and GBA non-manifesting carriers had significantly increased mean scores on the Movement Disorders Society Unified Parkinson's Disease Rating Scale (total score 4·6 [SD 4·4] healthy controls vs 8·4 [7·3] LRRK2 vs 9·5 [9·2] GBA, p

Importance We observed a significant correlation between cerebrospinal fluid (CSF) levels of tau proteins and α-synuclein, but not β-amyloid 1-42 (Aβ1-42), and lower concentration of CSF biomarkers, as compared with healthy controls, in a cohort of entirely untreated patients with Parkinson disease (PD) at the earliest stage of the disease studied so far. Objective To evaluate the baseline characteristics and relationship to clinical features of CSF biomarkers (Aβ1-42, total tau [T-tau], tau phosphorylated at threonine 181 [P-tau 181 ], and α-synuclein) in drug-naive patients with early PD and demographically matched healthy controls enrolled in the Parkinson’s Progression Markers Initiative (PPMI) study. Design, Setting, and Participants Cross-sectional study of the initial 102 research volunteers (63 patients with PD and 39 healthy controls) of the PPMI cohort. Main Outcomes and Measures The CSF biomarkers were measured by INNO-BIA AlzBio3 immunoassay (Aβ1-42, T-tau, and P-tau 181 ; Innogenetics Inc) or by enzyme-linked immunosorbent assay (α-synuclein). Clinical features including diagnosis, demographic characteristics, motor, neuropsychiatric, and cognitive assessments, and DaTscan were systematically assessed according to the PPMI study protocol. Results Slightly, but significantly, lower levels of Aβ1-42, T-tau, P-tau 181 , α-synuclein, and T-tau/Aβ1-42 were seen in subjects with PD compared with healthy controls but with a marked overlap between groups. Using multivariate regression analysis, we found that lower Aβ1-42 and P-tau 181 levels were associated with PD diagnosis and that decreased CSF T-tau and α-synuclein were associated with increased motor severity. Notably, when we classified patients with PD by their motor phenotypes, lower CSF Aβ1-42 and P-tau 181 concentrations were associated with the postural instability–gait disturbance–dominant phenotype but not with the tremor-dominant or intermediate phenotype. Finally, we found a significant correlation of the levels of α-synuclein with the levels of T-tau and P-tau 181 . Conclusions and Relevance In this first report of CSF biomarkers in PPMI study subjects, we found that measures of CSF Aβ1-42, T-tau, P-tau 181 , and α-synuclein have prognostic and diagnostic potential in early-stage PD. Further investigations using the entire PPMI cohort will test the predictive performance of CSF biomarkers for PD progression.

The Parkinson Progression Marker Initiative (PPMI) is a comprehensive observational, international, multi-center study designed to identify PD progression biomarkers both to improve understanding of disease etiology and course and to provide crucial tools to enhance the likelihood of success of PD modifying therapeutic trials. The PPMI cohort will comprise 400 recently diagnosed PD and 200 healthy subjects followed longitudinally for clinical, imaging and biospecimen biomarker assessment using standardized data acquisition protocols at twenty-one clinical sites. All study data will be integrated in the PPMI study database and will be rapidly and publically available through the PPMI web site- www.ppmi-info.org. Biological samples including longitudinal collection of blood, cerebrospinal fluid (CSF) and urine will be available to scientists by application to an independent PPMI biospecimen review committee also through the PPMI web site. PPMI will rely on a partnership of government, PD foundations, industry and academics working cooperatively. This approach is crucial to enhance the potential for success of this ambitious strategy to develop PD progression biomarkers that will accelerate research in disease modifying therapeutics.