Abstract

Background:There are currently no treatments that stop or slow the progression of Parkinson’s disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression.Methods:We analyzed 3 large longitudinal cohorts: Tracking Parkinson’s, Oxford Discovery, and the Parkinson’s Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington’s disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis.Results:There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ɛ4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10 −6).Conclusions:We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ɛ4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed.

Highlights

  • We examined the associations for this single-nucleotide polymorphism (SNP) in the previous progression GWAS18; rs35950207 was not significantly associated with binomial analysis of Hoehn and Yahr stage 3 or more at baseline

  • We used a new method of analyzing clinical progression in Parkinson’s disease (PD) by combining multiple assessments in a data-driven principal components analysis (PCA) to derive scores of composite, motor, and cognitive progression in large clinical cohorts

  • We showed that associations at the top signals strengthened when using the combined motor and cognitive progression scores compared with using the scales separately

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Summary

Introduction

These scores were analyzed in GWASs to identify variants associated with composite (cross-domain), motor, and cognitive progression in PD. We classified patients as carrying a pathogenic GBA variant, including Gaucher’s disease variants and variants associated with PD but excluding novel variants, using previous studies.[15,16] We analyzed GBA status in relation to the progression scores using linear regression, adjusting for cohort and the first 5 genetic principal components.

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