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Abstract
Background and Objectives This study aimed to identify CSF proteomic signatures characteristic of Parkinson disease (PD) and evaluate their clinical utility.
Methods This observational study used data from the Parkinson's Progression Markers Initiative (PPMI), which enrolled patients with PD, healthy controls (HCs), and non-PD participants carrying GBA1, LRRK2, and/or SNCA pathogenic variants (genetic prodromals) at international sites. Study participants were chosen from PPMI enrollees based on the availability of aptamer-based CSF proteomic data, quantifying 4,071 proteins, and classified as patients with PD without GBA1, LRRK2, and/or SNCA pathogenic variants (nongenetic PD), HCs, patients with PD carrying the aforementioned pathogenic variants (genetic PD), or genetic prodromals. Differentially expressed protein (DEP) analysis and the least absolute shrinkage and selection operator (LASSO) were applied to the data from nongenetic PD and HCs. Signatures characteristics of nongenetic PD were quantified as a PD proteomic score (PD-ProS), validated internally and then externally using data of 1,556 CSF proteins from the LRRK2 Cohort Consortium (LCC). We further tested the PD-ProS in genetic PD and genetic prodromals and examined associations with clinical progression.
Results Data from 279 patients with nongenetic PD (mean ± SD, age 62.0 ± 9.6 years; male 67.7%) and 141 HCs (age 60.5 ± 11.9 years; male 64.5%) were used for PD-ProS derivation. From 23 DEPs, LASSO determined weights of 14 DEPs for the PD-ProS (area under the curve [AUC] 0.83, 95% CI 0.78–0.87), validated in an independent internal validation cohort of 71 patients with nongenetic PD and 35 HCs (AUC 0.81, 95% CI 0.73–0.90). In the LCC, only 5 of the 14 DEPs were also measured. Notably, these 5 DEPs still distinguished 34 patients with nongenetic PD from 31 HCs with the same weights (AUC 0.75, 95% CI 0.63–0.87). Furthermore, the PD-ProS distinguished 258 patients with genetic PD from 365 genetic prodromals. Finally, regardless of genetic status, the PD-ProS independently predicted both cognitive and motor decline in PD (dementia, adjusted hazard ratio in the highest quintile [aHR-Q5] 2.8 [95% CI 1.6–5.0]; Hoehn and Yahr stage IV, aHR-Q5 2.1 [95% CI 1.1–4.0]).
Discussion By integrating high-throughput proteomics with machine learning, we identified PD-associated CSF proteomic signatures crucial for PD development and progression.
Trial Registration Information ClinicalTrials.gov (NCT01176565). A link to the trial registry page is clinicaltrials.gov/ct2/show/NCT01141023.
Classification of Evidence This study provides Class II evidence that the CSF proteome contains clinically important information regarding the development and progression of Parkinson disease that can be deciphered by a combination of high-throughput proteomics and machine learning.
Glossary
- aHR=
- adjusted hazard ratio;
- AUC=
- area under the curve;
- DEP=
- differentially expressed protein;
- HC=
- healthy control;
- HR=
- hazard ratio;
- H&Y=
- Hoehn and Yahr;
- LASSO=
- least absolute shrinkage and selection operator;
- LCC=
- LRRK2 Cohort Consortium;
- LEDD=
- levodopa-equivalent daily dose;
- MCI=
- mild cognitive impairment;
- MJFF=
- Michael J. Fox Foundation;
- MS=
- mass spectrometry;
- NPV=
- negative predictive value;
- PD=
- Parkinson disease;
- PD-ProS=
- PD proteomic score;
- PPMI=
- Parkinson's Progression Markers Initiative;
- PPV=
- positive predictive value;
- PRS=
- polygenic risk score;
- SOMAers=
- slow off-rate modified aptamers
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
The initial draft of this manuscript was previously accessible on medRxiv with the DOI: 10.1101/2022.06.08.22276035. The current version contains several important enhancements compared to that earlier medRxiv version. Firstly, we've standardized the values in our differential protein analysis and adopted a more stringent cutoff value, changing it from q < 0.2 to q < 0.05. Secondly, we've adjusted the ratio of our derivation and internal validation cohorts to be more balanced. Most importantly, we've expanded our validation process to include an “external” validation cohort from an entirely different study, the LRRK2 Cohort Consortium, which used a different method for measuring proteins, namely mass spectrometry-based proteomics. As a result, the current version of our findings is significantly more reliable in terms of external validity compared to the preliminary version on medRxiv. This is crucial for any future clinical applications.
Submitted and externally peer reviewed. The handling editor was Associate Editor Peter Hedera, MD, PhD.
Editorial, page 595
Class of Evidence: NPub.org/coe
- Received January 8, 2023.
- Accepted in final form May 30, 2023.
- © 2023 American Academy of Neurology
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