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. 2018 Dec;89(12):1279-1287.
doi: 10.1136/jnnp-2018-318337. Epub 2018 Jul 25.

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression

Michael Lawton  1 , Yoav Ben-Shlomo  2 , Margaret T May  2 , Fahd Baig  3   4 , Thomas R Barber  3   4 , Johannes C Klein  3   4 , Diane M A Swallow  5 , Naveed Malek  6 , Katherine A Grosset  6 , Nin Bajaj  7 , Roger A Barker  8 , Nigel Williams  9 , David J Burn  10 , Thomas Foltynie  11 , Huw R Morris  12 , Nicholas W Wood  13 , Donald G Grosset #  6 , Michele T M Hu #  3   4
Affiliations

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression

Michael Lawton et al. J Neurol Neurosurg Psychiatry. 2018 Dec.

Abstract

Objectives: To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly diagnosed with this condition.

Methods: 1601 and 944 patients with idiopathic PD, from Tracking Parkinson's and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models.

Results: We identified four clusters: (1)  fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and  poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson's at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1-1.1). In Tracking Parkinson's, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%.

Conclusions: We have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.

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Conflict of interest statement

Competing interests: NB has received payment for advisory board attendance from UCB, Teva Lundbeck, Britannia, GSK, Boehringer and honoraria from UCB Pharma, GE Healthcare, Lily Pharma and Medtronic. He has received research grant support from GE Healthcare, Wellcome Trust, MRC and Parkinson’s UK and royalties from Wiley. RAB received grants from Parkinson’s UK, NIHR, Cure Parkinson’s Trust, Evelyn Trust, Rosetrees Trust, MRC and EU along with payment for advisory board attendance from Oxford Biomedica and LCT, and honoraria from Wiley and Springer. DJB received grants from NIHR, Wellcome Trust, GlaxoSmithKline Ltd, Parkinson’s UK and Michael J Fox Foundation. TF received payment for advisory board meetings for Abbvie and Oxford Biomedica, and honoraria for presentations at meetings sponsored by Medtronic, St Jude Medical, Britannia and Teva pharmaceuticals. HRM has received grants from Parkinson’s UK, grants from Medical Research Council UK, during the conduct of the study; grants from Welsh Assembly Government, personal fees from Teva, personal fees from Abbvie, personal fees from Teva, personal fees from UCB, personal fees from Boerhinger-Ingelheim, personal fees from GSK, non-financial support from Teva, grants from Ipsen Fund, non-financial support from Medtronic, grants from MNDA, grants from PSP Association, grants from CBD Solutions, grants from Drake Foundation and personal fees from Acorda, outside the submitted work. In addition, HRM has a patent and is a co-applicant on a patent application related to C9ORF72—Method for diagnosing a neurodegenerative disease (PCT/GB2012/052140) pending. DGG received payment for advisory board attendance from AbbVie and honoraria from UCB Pharma, GE Healthcare and Acorda.

Figures

Figure 1
Figure 1
Important salient clinical features of the four clusters across the two cohorts where the percentages within each cluster are from the Tracking Parkinson’s cohort.
Figure 2
Figure 2
Within cluster means of the standardised variables for the four k-means cluster solution in both cohorts along with the 95% CI for the mean. Positive (above the dotted line) is worse than average and negative better than average. For laterality, positive is more bilateral than average and negative more unilateral than average. Note that hallucinations, constipation and urinary are categorical variables and were standardised using a slightly different method (see online supplementary appendix 1). In Tracking Parkinson’s, cluster 1 n=493 patients, cluster 2 n=459, cluster 3 n=336 and cluster 4 n=313, while in Discovery, cluster 1 n=218, cluster 2 n=319, cluster 3 n=196 and cluster 4 n=211. BP, blood pressure; RBD, rapid eye movement sleep behaviour disorder.
Figure 3
Figure 3
Longitudinal follow-up in MDS-UPDRS part III by cohort. Difference between clusters progression rates p<0.001 in Tracking Parkinson’s and p=0.007 in Discovery. Changed denominator where 80% or more of questions were answered. Observed data were split into yearly bins (0–1, 1–2, 2–3, 3–4 and 4–5 years) and the means plotted. MDS, Movement Disorders Society; UPDRS, Unified Parkinson’s Disease Rating Scale.
Figure 4
Figure 4
Longitudinal follow-up in Montreal Cognitive Assessment (MoCA) by cohort. Difference between cluster progression rates p=0.04 in Tracking Parkinson’s and p=0.41 in Discovery. Changed denominator where 80% or more of questions were answered. Observed data were split into yearly bins (0–1, 1–2, 2–3, 3–4 and 4–5 years) and the means plotted.
See this image and copyright information in PMC

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