• Nirosen Vijiaratnam, Michael Lawton, Amanda J Heslegrave, Tong Guo, Manuela Tan, Edwin Jabbari, Raquel Real, John Woodside, Katherine Grosset, Viorica Chelban, Dilan Athauda, Christine Girges, Roger A Barker, John Hardy, Nicholas Wood, Henry Houlden, Nigel Williams, Yoav Ben-Shlomo, Henrik Zetterberg, Donald G Grosset, Thomas Foltynie, Huw R Morris, and PRoBaND clinical consortium.
• Department of Clinical and Movement Neurosciences, University College London, UCL Queen Square Institute of Neurology, London, UK.
• J. Neurol. Neurosurg. Psychiatr. 2022 May 16; 93 (7): 707715707-15.

BackgroundPatients with Parkinson's disease (PD) have variable rates of progression. More accurate prediction of progression could improve selection for clinical trials. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be further improved by blood biomarkers.ObjectiveTo determine if blood biomarkers (serum neurofilament light (NfL) and genetic status (glucocerebrosidase, GBA and apolipoprotein E (APOE))) are useful in addition to clinical measures for prognostic modelling in PD.MethodsWe evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients' genetic (GBA and APOE) status. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model, and explored how blood biomarkers compared with clinical variables in distinguishing prognostic phenotypes .Results291 patients were assessed in this study. Baseline serum NfL was associated with baseline cognitive status. Nfl predicted a shorter time to dementia, postural instability and death (dementia-HR 2.64; postural instability-HR 1.32; mortality-HR 1.89) whereas APOEe4 status was associated with progression to dementia (dementia-HR 3.12, 95% CI 1.63 to 6.00). NfL levels and genetic variables predicted unfavourable progression to a similar extent as clinical predictors. The combination of clinical, NfL and genetic data produced a stronger prediction of unfavourable outcomes compared with age and gender (area under the curve: 0.74-age/gender vs 0.84-ALL p=0.0103).ConclusionsClinical trials of disease-modifying therapies might usefully stratify patients using clinical, genetic and NfL status at the time of recruitment.© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

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