Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study

doi:10.21203/rs.3.rs-1870271/v1

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Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study

https://doi.org/10.21203/rs.3.rs-1870271/v1

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published 17 Feb, 2023

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Heterogeneity in Parkinson’s disease (PD) presents a barrier to understanding disease mechanisms and developing new treatments. This challenge may be partially overcome by stratifying patients into clinically meaningful subtypes. A recent subtyping scheme classifies de novo PD patients into three subtypes: mild-motor predominant, intermediate, or diffuse-malignant, based on motor impairment, cognitive performance, REM-sleep behavior disorder, and autonomic function. We aimed to validate this approach in a large longitudinal cohort of early-stage PD (n=517). Furthermore, we assessed the influence of subtype on clinical motor phenotype and on one-year clinical disease progression. Diffuse-malignant patients (14%) differed from mild-motor predominant patients (48%) in three ways: involvement of more clinical domains, more diffuse hypokinetic-rigid symptoms (less lateralization, less hand/foot focality), and faster one-year progression. These findings extend the classification of diffuse-malignant and mild-motor predominant subtypes to early-stage PD and suggest that different pathophysiological mechanisms (focal versus diffuse cerebral propagation) may play a role.

Parkinson’s disease

subtype

clinical progression

longitudinal

Parkinson’s disease (PD) is a neurodegenerative disorder that is characterized by marked between-patient variability in clinical phenotype and prognosis^1,2. The cardinal motor symptoms involve bradykinesia, rigidity, and tremor, but many patients also have autonomic, psychiatric, and cognitive symptoms. Stratification of patient cohorts into clinically meaningful subtypes represents an important step towards accounting for such heterogeneity in future studies of PD-related etiology, treatment responsiveness, and biomarker detection^3,4. However, replication studies of subtype classifications in independent cohorts and at different disease stages are currently lacking, raising concerns over their usability in clinical research^5,6. In this study, we aimed to validate a set of clinical criteria that has recently been proposed for the subtyping of de novo PD patients⁷ by using them to investigate clinical heterogeneity in early-stage PD. We applied these previously published criteria to an independent large longitudinal cohort of early-stage PD patients (Personalized Parkinson Project, PPP⁸) to investigate subtype-specific differences in clinical baseline characteristics and disease progression.

Traditional subtyping approaches that focus on the presence or absence of a single motor symptom (e.g. tremor-dominant vs non-tremor PD), or on the expression of axial motor symptoms (postural instability and gait disorders, PIGD)^9–11 have the advantage that they can be individually applied to single patients, making them easy to use in clinical practice. However, these approaches fail to account for the wider range of motor and non-motor symptoms that characterizes PD. Modern data-driven approaches are able to accommodate this wider range of symptoms, but often require implementation at the cohort-level rather than at the level of individual patients, which limits their clinical usability. A recent study combined traditional and data-driven subtyping approaches to enable individual patient classification, while simultaneously accounting for both motor and non-motor symptoms⁷. A data-driven clustering analysis was applied to an extensive set of clinical measurements acquired from a cohort of de novo PD patients. This resulted in three subtypes, which were labelled as either mild-motor predominant, intermediate, or diffuse-malignant according to their clinical characteristics. A set of clinical criteria (henceforth referred to as the Mild-motor predominant – Intermediate - Diffuse-Malignant [MMP-IM-DM] criteria) was then derived that classifies individual patients as having one of the three subtypes based on motor impairment, cognitive impairment, REM-sleep behavior disorder, and autonomic function. Comparisons between subtypes defined from these criteria showed that the diffuse-malignant subtype was characterized by higher levels of impairment and faster progression across multiple clinical domains compared to the mild-motor predominant subtype.

Two studies have adapted the MMP-IM-DM criteria to retrospectively show that a diffuse-malignant subtype is associated with an increased risk of reaching clinically relevant disease milestones, such as dementia, care placement, or death^12,13. These findings support the notion that the MMP-IM-DM criteria may serve as a basis for the discovery of biomarkers that may increase the accuracy of clinical prognosis and improve our understanding of pathophysiological mechanisms underlying clinical heterogeneity in PD¹⁴. However, further validation and independent replication of these criteria is necessary to establish their usability in additional stages of PD.

In this study, we aimed to validate the MMP-IM-DM criteria for defining subtypes in PD by applying them to a large longitudinal cohort of early-stage PD patients (0–5 years disease duration) who participated in the Personalized Parkinson Project (PPP) in the Netherlands⁸. The PPP did not constitute a convenience sample, but rather aimed to include a cohort that represented real-life patients. Strict stratification criteria were applied to ensure a balanced inclusion of men and women, different age ranges (21–45; 46–55; 56–65; ≥66 years), and different disease durations (< 2.5 years; ≥2.5 years). We hypothesized that mild-motor predominant, intermediate, and diffuse-malignant subtypes could be replicated in this independent cohort. We predicted that these subtypes would differ in clinical characteristics beyond those that were used to implement the subtype classification and in one-year disease progression assessed across multiple clinical domains.

Subtyping

Subtype classification was performed in accordance with the MMP-IM-DM criteria⁷ after splitting the cohort patients at the median disease duration (33 months)¹⁵. This was done to ensure that disease duration did not constitute a major determinant of the subtype classification. In short, patients were classified based on percentiles of motor symptoms, cognitive function, REM-sleep behavior disorder, and autonomic function scores relative to the entire cohort. Out of 506 patients from the PPP who were included in this study, 63 (12%) lacked data from one or more measurements used for subtyping, owing to the fact that data collection and quality assurance procedures for the PPP has not yet been completed, and were therefore excluded from further analysis. The 443 remaining patients were classified into mild-motor predominant (n = 214, 48%), intermediate (n = 167, 38%), and diffuse-malignant (n = 62, 14%) subtypes. 422 patients returned for assessments at one-year follow-up, of whom 51 (12%) patients lacked a baseline subtype. Out of the remaining 371 patients, 179 (42%) were classified as mild-motor predominant, 144 (34%) as intermediate, and 48 (12%) as diffuse-malignant at baseline. Drop-out resulted primarily from cancellations or postponements of measurements owing to risks associated with the COVID-19 pandemic.

Between-subtype differences in baseline characteristics

Clinical measurements used to implement the MMP-IM-DM criteria. As expected, the three subtypes differed on the set of symptoms that were used to classify patients into subtypes (motor composite, cognitive composite, REM-sleep behavior disorder (RBDSQ), and autonomic dysfunction (SCOPA-AUT), see Fig. 1). Post-hoc tests of individual motor scores were used to explore which symptoms contributed most to between-subtype differences on the motor composite score. The diffuse-malignant subtype was associated with increased severity of overall impairment (MDS-UPDRS-III total [H(2) = 103, p < 0.001, η²_h = 0.23]), bradykinesia [H(2) = 98.1 p < 0.001, η²_h = 0.22], rigidity [H(2) = 44.2, p < 0.001, η²_h = 0.096], PIGD [H(2) = 96.2, p < 0.001, η²_h = 0.218], and self-reported motor symptoms (MDS-UPDRS-II total [H(2) = 117.9, p < 0.001, η²_h = 0.266]). There were no between-subtype differences in the severity of resting or action tremor. See Fig. 1A and Table 1.

Table 1

Demographic information and clinical characteristics.
	Mild-motor predominant (I)	Intermediate (II)	Diffuse-malignant (III)	p-value	Post-hoc
Demographics
Count (n)	214	167	62
Age	60.69 (9.02)	62.22 (8.69)	65.42 (7.13)	0.002	III > I (p = 0.001) III > II (p = 0.039)
Sex (F/M)	104/110	62/105	17/45	0.005
Disease duration (months)	30.44 (16.97)	32.94 (18.02)	32.45 (17.31)	0.58
Years education	17.43 (4.02)	17.11 (4.39)	16.58 (4.25)	0.13
Hoehn & Yahr-stage	27/174/13/0	13/140/13/1	0/37/21/4	< 0.001
LEDD	470.28 (253.28)	591.39 (366.75)	612.83 (335.61)	0.002	II > I (p = 0.029) III > I (p = 0.007)
Clinical scores used for subtype classification
Motor composite	11.30 (4.50)	13.69 (5.01)	21.77 (4.87)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
MDS-UPDRS-III total	26.63 (0.62)	30.21 (0.81)	44.62 (2.00)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
Bradykinesia	12.55 (0.38)	14.92 (0.51)	23.31 (1.34)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
Rigidity	4.85 (0.18)	5.32 (0.23)	7.55 (0.54)	< 0.001	II > I (p = 0.005) III > I (p < 0.001) III > II (p < 0.001)
PIGD	2.08 (0.10)	2.69 (0.11)	5.05 (0.20)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
Resting tremor	2.21 (0.17)	2.25 (0.20)	2.4 (0.33)	0.99
Action tremor	2.11 (0.13)	2.19 (0.15)	2.75 (0.25)	0.13
MDS-UPDRS-II total	5.71 (0.30)	8.66 (0.34)	14.65 (0.58)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
Cognitive composite ^a	0.30 (0.04)	-0.15 (0.59)	-0.45 (0.75)	< 0.001	I > II (p = 0.001) I > III (p < 0.001) II > III (p = 0.03)
RBDSQ	2.1 (1.68)	4.75 (3.38)	5.92 (3.62)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p = 0.012)
SCOPA-AUT	12.79 (5.33)	19.14 (8.23)	22.94 (7.71)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p = 0.016)
Note. Estimated marginal means (standard errors) adjusting for age, sex, and disease duration where appropriate. ^a z-score based on age-, education,- and/or sex-adjusted normative comparison; MDS-UPDRS = Movement Disorders Society Unified Parkinson Disease Rating Scale; F = Female; LEDD = Levodopa equivalent daily dose; M = Male; N = Number of participants; RBDSQ = REM sleep behavior disorder screening questionnaire; SCOPA-AUT = Scales for Outcomes in Parkinson’s Disease, autonomic section.

Clinical measurements withheld during subtype classification. Comparisons in clinical measurements beyond those that were used to implement the MMP-IM-DM criteria were conducted to test whether this subtyping approach captures variability in the wider clinical phenotype of PD patients. The diffuse-malignant subtype was associated with more severe oral motor dysfunction (ROMP [H(2) = 66.9, p < 0.001, η²_h = 0.15]), poorer overall cognitive function (MoCA [H(2) = 16.1, p < 0.001, η²_h = 0.032]) and more severe psychiatric problems, such as depression (BDI-II [H(2) = 73.1, p < 0.001, η²_h = 0.16]), anxiety (STAI trait [F(2) = 34.1, p < 0.001, η²_p = 0.14]; STAI state [F(2) = 25.8, p < 0.001, η²_p = 0.11]), impulse control disorder (QUIP [H(2) = 32.5, p < 0.001, η²_h = 0.07]), ophthalmologic problems (VIPD-Q [H(2) = 40.9, p < 0.001, η²_h = 0.09]), in combination with reduced quality of life (PDQ-39 [F(2) = 68.2, p < 0.001, η²_p = 0.24]). Furthermore, the diffuse-malignant subtype was characterized by older age [F(2) = 6.3, p = 0.002, η²_p = 0.03], increased medication use (LEDD [H(2) = 9.4, p = 0.009, η²_h = 0.019]), a higher proportion of men (sex [ꭓ²(2) = 10.8, p = 0.004]), and more severe stages of PD (Hoehn and Yahr-stage [ꭓ²(6) = 67.9, p < 0.001]). See Fig. 1A and Table 2.

Table 2

Model-based predictions of clinical measurements at baseline.
	Mild-motor predominant (I)	Intermediate (II)	Diffuse-malignant (III)	p-value	Post-hoc
Clinical scores withheld from subtype classification
ROMP	9.63 (0.18)	11.36 (0.25)	13.30 (0.49)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
MoCA	27.23 (0.15)	26.81 (0.17)	26.25 (0.27)	< 0.001	I > II (p = 0.033) I > III (p < 0.001) II > III (p = 0.035
BDI-II	7.04 (0.39)	11.51 (0.45)	13.74 (0.75)	< 0.001	II > I (p < 0.001) III > I (p < 0.001)
STAI - Trait	31.91 (0.54)	38.07 (0.74)	40.76 (1.33)	< 0.001	II > I (p < 0.001) III > I (p < 0.001)
STAI - State	32.72 (0.52)	38.10 (0.70)	39.26 (1.19)	< 0.001	II > I (p < 0.001) III > I (p < 0.001)
QUIP	6.56 (0.68)	11.02 (0.78)	15 (1.31)	< 0.001	II > I (p < 0.001) III > I (p < 0.001)
PDQ-39	12.31 (0.48)	20.98 (0.92)	28.54 (2.14)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p < 0.001)
VIPD-Q	6.79 (0.51)	9.65 (0.59)	14.78 (1.01)	< 0.001	II > I (p < 0.001) III > I (p < 0.001) III > II (p = 0.001)
Motor symptom subscores relative to total MDS-UPDRS-III
Bradykinesia (%)	0.25 (0.006)	0.26 (0.007)	0.28 (0.012)	0.031	III > I (p = 0.03)
Rigidity (%)	0.23 (0.007)	0.23 (0.008)	0.22 (0.012)	0.7
PIGD (%)	0.12 (0.005)	0.12 (0.005)	0.17 (0.009)	< 0.001	III > I (p < 0.001) III > II (p < 0.001)
Resting tremor (%)	0.10 (0.006)	0.09 (0.006)	0.07 (0.012)	0.083	I > III (p = 0.085)
Action tremor (%)	0.11 (0.005)	0.10 (0.006)	0.10 (0.010)	0.6
Other (%)	0.14 (0.005)	0.15 (0.005)	0.14 (0.009)	0.31
Localization of bradykinesia-rigidity symptoms
Right vs. left	0.28 (0.012)	0.26 (0.014)	0.16 (0.023)	< 0.001	I > II (p = 0.059) I > III (p < 0.001) II > III (p < 0.001)
Arm vs. leg	0.28 (0.013)	0.26 (0.014)	0.16 (0.024)	< 0.001	I > III (p < 0.001) II > III (p < 0.001)
Note. Estimated marginal means (standard errors) of baseline score adjusting for age, sex, and disease duration. PIGD = Postural instability and gait disturbance; ROMP = Radboud Oral Inventory for Parkinson’s Disease; MoCA = Montreal Cognitive Assessment; BDI = Beck’s Depression Index; STAI = State-Trait Anxiety Inventory; QUIP = Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease; PDQ = Parkinson’s Disease Questionnaire; VIPD-Q = Visual Impairment in Parkinson’s Disease Questionnaire.

Partitioning of overall motor symptom severity. Percentages of motor symptom subscore severity relative to overall motor severity were compared to test whether subtypes differed in the relative dominance of certain motor symptoms. The motor phenotype of the diffuse-malignant subtype consisted of more bradykinesia [F(2) = 3.5, p = 0.031, η²_p = 0.02] and PIGD [H(2) = 19.8, p < 0.001, η²_h = 0.04] and showed a trend towards less resting tremor [H(2) = 4.97, p = 0.083, η²_h = 0.007]. See Fig. 1B and Table 2. An exploration of resting tremor revealed that 10 out of 62 (16%) diffuse-malignant patients showed considerable resting tremor (MDS-UPDRS-III resting tremor score of ≥ 2 for at least one arm¹⁶). In comparison, 40 out of 214 (19%) mild-motor predominant patients had considerable resting tremor. This suggests that the presence of marked resting tremor is not necessarily a demarcating feature of a benign, mild-motor predominant subtype.

Localization of bradykinesia-rigidity symptoms. Between-subtype differences in the localization of bradykinesia-rigidity symptoms was assessed by comparing right versus left lateralization and arm versus leg focality. The diffuse-malignant subtype was associated with more diffusely distributed motor symptoms (right-left lateralization [H(2) = 41.9, p < 0.001, η²_h = 0.092] and arm-leg focality [H(2) = 21.3, p < 0.001, η²_h = 0.045]). See Fig. 1C and Table 2.

Between-subtype differences in one-year clinical progression

Comparisons of one-year disease progression were conducted to assess whether the subtypes were differentially susceptible to the worsening of symptoms. The diffuse-malignant subtype was associated with faster progression of motor subscores (Δbradykinesia [F(2) = 3.14, p = 0.043, η²_p = 0.018], ΔPIGD [F(2) = 4.1, p = 0.017, η²_p = 0.023]), cognitive impairment (ΔMoCA [F(2) = 9.6, p < 0.001, η²_p = 0.052]), trait anxiety (ΔSTAI trait [F(2) = 5.9, p = 0.003, η²_p = 0.034]), impulse control disorder (ΔQUIP [F(2) = 6.6, p = 0.001, η²_p = 0.044]), quality of life (ΔPDQ-39 F(2) = 3.4, p = 0.033, η²_p = 0.02), and autonomic dysfunction (ΔSCOPA-AUT [F(2) = 4.5, p = 0.011, η²_p = 0.028]). In addition, the diffuse-malignant subtype showed an increased proportion of PIGD (ΔPIGD proportion [F(2) = 4.4, p = 0.012, η²_p = 0.026]). The diffuse-malignant subtype also showed trends toward faster progression of medication titration (ΔLEDD F(2) = 2.6, p = 0.077, η²_p = 0.016), depression (ΔBDI-II [F(2) = 2.9, p = 0.054, η²_p = 0.019]), and state anxiety (ΔSTAI state F(2) = 2.4, p = 0.09, η²_p = 0.015). See Fig. 2 and Table 3.

Table 3

Model-based predictions of 1-year progression on clinical measurements.
	Mild-motor predominant (I)	Intermediate (II)	Diffuse-malignant (III)	p-value	Post-hoc	% imputed data
Motor symptoms
ΔLEDD	81.67 (15.11)	132.09 (16.67)	102.91 (30.15)	0.077	II > I (p = 0.067)	20.8
ΔMotor composite	0.82 (0.29)	1.11 (0.30)	1.83 (0.62)	0.37		24.6
ΔMDS-UPDRS-III total	2.15 (0.65)	2.73 (0.69)	4.3 (1.33)	0.38		17.4
ΔBradykinesia	0.70 (0.40)	1.14 (0.43)	3.12 (0.83)	0.043	III > I (p = 0.031) III > II (p = 0.082)	17.4
ΔRigidity	0.62 (0.19)	0.68 (0.22)	0.68 (0.38)	0.88		17.8
ΔPIGD	-0.29 (0.11)	0.10 (0.12)	0.36 (0.24)	0.017	II > I (p = 0.035) III > I (P = 0.059)	25.3
ΔResting tremor	0.38 (0.15)	0.25 (0.17)	0.18 (0.28)	0.76		18.5
ΔAction tremor	-0.04 (0.11)	-0.03 (0.12)	0.29 (0.20)	0.32		18.5
ΔMDS-UPDRS-II total	-0.08 (0.28)	0.51 (0.29)	0.73 (0.58)	0.3		24.2
ΔROMP	-0.18 (0.17)	0.004 (0.18)	0.22 (0.33)	0.5		24.2
Motor symptom subscores relative to total MDS-UPDRS-III
ΔBradykinesia (%)	0.00 (0.01)	0.00 (0.01)	0.00 (0.01)	0.77		18.3
ΔRigidity (%)	0.01 (0.01)	0.00 (0.01)	-0.01 (0.01)	0.61		17.6
ΔPIGD (%)	-0.02 (0.00)	-0.01 (0.01)	0.01 (0.01)	0.012	III > I (p = 0.01)	17.8
ΔResting tremor (%)	0.00 (0.01)	0.00 (0.01)	0.00 (0.01)	0.77		18.5
ΔAction tremor (%)	-0.01 (0.00)	-0.01 (0.01)	-0.01 (0.01)	0.82		18.1
ΔOther (%)	0.01 (0.00)	0.01 (0.01)	0.01 (0.01)	0.84		18.1
Diffusivity of bradykinesia-rigidity symptoms
ΔRight vs. left	-0.03 (0.01)	-0.03 (0.01)	-0.04 (0.02)	0.82		18.7
ΔArm vs. leg	-0.02 (0.01)	-0.02 (0.01)	− 0.01 (0.02)	0.84		17.8
Non-motor symptoms
ΔMoCA	-0.28 (0.16)	-0.79 (0.17)	-1.72 (0.28)	< 0.001	I > II (p = 0.073) I > III (p < 0.001) II > III (p = 0.013)	17
ΔBDI-II	-0.59 (0.31)	-0.08 (0.34)	1.03 (0.57)	0.054	III > I (p = 0.043)	23.5
ΔSTAI - Trait	-1.44 (0.44)	0.43 (0.49)	1.45 (0.80)	0.003	II > I (p = 0.017) III > I (p = 0.007)	23.7
ΔSTAI - State	-1.33 (0.45)	-0.65 (0.52)	0.79 (0.84)	0.09	III > I (p = 0.075)	23.3
ΔQUIP	-1.35 (0.58)	-0.85 (0.65)	3.30 (1.12)	0.001	III > I (p < 0.001) III > II (p = 0.004)	24.8
ΔPDQ-39	-0.70 (0.55)	0.33 (0.58)	2.5 (1.05)	0.033	III > I (p = 0.025)	24.9
ΔRBDSQ	0.00 (0.14)	0.32 (0.16)	0.04 (0.27)	0.28		23
ΔSCOPA-AUT	-0.14 (0.39)	0.46 (0.43)	2.47 (0.74)	0.011	III > I (p = 0.008) III > II (p = 0.037)	22.9
ΔVIPD-Q	0.21 (0.47)	0.73 (0.53)	1.55 (0.90)	0.39		24.4
Note. Estimated marginal means (standard errors) of 1-year progression adjusting for age, sex, disease duration and baseline score. Δ = Delta (follow-up – baseline).

Sensitivity analyses

Analyses on imputed versus non-imputed data sets. Comparisons of progression were re-performed on non-imputed data. All results reported above remained significant. In addition, the trend towards faster progression of depression became significant in the analysis of non-imputed data (ΔBDI-II [F(2) = 3.1, p = 0.048, η²_p = 0.02]).

Analyses on subtype classifications based on cognitive composite scores versus binary MCI. Subtype classifications were re-performed after replacing the cognitive composite score with a binary variable indicating the presence or absence of mild cognitive impairment (MCI). This led to the classification of an additional 32 patients who lacked a cognitive composite score, leading to a total sample size of 475 patients. 206 (43%) were classified as mild-motor predominant, 199 (42%) as intermediate, and 70 (15%) as diffuse-malignant. Subtype counts did not differ between cognitive composite-based and MCI-based classifications (p = 0.31). Agreement between these two classifications was substantial (k = 0.76, 86%). Comparisons of baseline measurements between MCI-based subtypes led to no change in the significance of the results reported above. Comparisons of progression also yielded highly consistent results, with the exception that the intermediate subtype showed a larger increase in LEDD compared to the mild-motor predominant one (ΔLEDD F(2) = 3.4, p = 0.036, η²_p = 0.02).

Subtype conversions

Subtype conversions relative to baseline cohort-level scores. Subtype classification was conducted for both sessions relative to baseline cohort-level scores. Agreement between classifications at baseline and follow-up was weak-to-moderate (k = 0.46, 66%). Out of 362 patients, 122 (34%) converted to another classification from baseline to follow-up assessment. However, subtype conversions were not random, and tended to occur more often from benign to severe subtypes, than the other way around (trend towards an effect of time on subtype counts [χ²(2) = 5.51, p = 0.063]). That is, 79 (22%) patients converted to a more severe subtype, while 43 (12%) converted to a more benign subtype. More specifically, in the mild-motor group, 55 patients converted to intermediate and 9 patients converted to diffuse-malignant. In the intermediate group, 27 patients converted to mild-motor and 24 patients converted to diffuse-malignant. In the diffuse-malignant group, 0 patients converted to mild-motor and 16 patients converted to intermediate. See Fig. 3.

Subtype conversions relative to session-specific cohort-level scores. Subtype classification was conducted for both sessions relative to session-specific cohort-level scores. Agreement between classifications at baseline and follow-up was weak-to-moderate (k = 0.44, 66%). Again, subtype conversions tended to occur more often from benign to severe subtypes, than the other way around [trend towards a significant effect of time on subtype counts(χ²(2) = 4.82, p = 0.089)]. Out of 362 patients, 125 (35%) converted to another classification from baseline to follow-up assessment. Overall, 78 (22%) patients converted to a more severe subtype and 47 (13%) converted to a more benign subtype. In the mild-motor group, 50 patients converted to intermediate and 7 patients converted to diffuse-malignant. In the intermediate group, 27 patients converted to mild-motor and 21 patients converted to diffuse-malignant. In the diffuse-malignant group, 1 patient converted to mild-motor and 19 patients converted to intermediate. See Fig. 3.

We employed the clinical subtyping strategy of Fereshtehnejad and colleagues (the MMP-IM-DM criteria)⁷ to classify patients in a large longitudinal cohort-study of early-stage PD. The proportion of subtypes, baseline clinical characteristics, and progression rates were largely consistent with findings in de novo and mid-to-late-stage PD^7,12,13, thereby validating the use of the MMP-IM-DM criteria, but now for early-stage PD.

Application of the MMP-IM-DM criteria led to three groups that were characterized by increasingly severe motor symptoms, cognitive impairment, REM-sleep behavior disorder, and autonomic dysfunction. A diffuse-malignant subtype showed relatively high symptom severity in all four domains, followed by an intermediate subtype, while a mild-motor predominant subtype showed the least severe symptoms, indicating that subtype classification was successful. We were able to confirm that these differences extended to a diverse set of clinical measurements beyond those that were used to implement the subtype classification, thereby corroborating previous findings in de novo PD⁷. Our study adds to these findings by providing a more extensive analysis of motor symptoms, showing that the diffuse-malignant subtype is characterized by motor symptoms that are less lateralized, less confined to the upper extremities, and consist of relatively more bradykinesia and PIGD. Moreover, we show that the diffuse-malignant subtype is associated with faster progression in both motor and non-motor domains, which has previously only been described for de novo and mid-to-late-stage PD^7,12,13. In the motor domain, progression differences between subtypes were primarily confined to bradykinesia and PIGD. We also show that comparisons between subtypes that were classified based on a cognitive composite score or a binary variable indicating MCI yielded highly comparable results with respect to clinical differences at baseline and in progression.

Traditional subtyping approaches in PD research often classify patients based on the presence or absence of tremor and PIGD symptoms¹⁷. The presence of tremor has been linked to a more benign PD phenotype that resembles a mild-motor predominant subtype, whereas the absence of tremor in combination with the presence of PIGD has been linked to a more aggressive PD phenotype that resembles a diffuse-malignant subtype^17–19. In our study, the motor phenotype of the diffuse-malignant subtype was characterized by more bradykinesia and PIGD symptoms. There was also a trend towards a reduction in the percentage of resting tremor relative to overall motor severity for this subtype compared to the mild-motor predominant subtype. This suggests a link between the subtyping approach used in this study and more traditional ones that rely on tremor and PIGD. However, the two approaches are unlikely to overlap completely. For example, we observed that the proportions of patients with considerable resting tremor¹⁶ was comparable between diffuse-malignant and mild-motor predominant subtypes. A previous study found that tremor-PIGD subtyping was less sensitive to progression differences between subtypes compared to the MMP-IM-DM criteria¹². The improved sensitivity of the MMP-IM-DM criteria may result from having accounted for a wider clinical phenotype consisting of both motor and non-motor symptoms.

Clinical differences between PD subtypes may be partially explained by heterogeneity in neural mechanisms and pathological processes²⁰. Neuroimaging studies employing the MMP-IM-DM criteria have shown that the diffuse-malignant subtype is characterized by heightened excitability and decreased plasticity in the primary motor cortex¹⁴, disrupted functional connectivity patterns, reduced basal ganglia tissue integrity²¹, and more structural atrophy⁷. These findings support the hypothesis that subtypes may differ with respect to underlying pathological processes, such as the accumulation and spread of ɑ-synuclein^20,22−24. Recent evidence suggests that PD-related ɑ-synucleinopathy may spread bi-directionally between the central and peripheral nervous system²⁵, and that the specific direction of this spread may be associated with different clinical phenotypes of PD^20,22,23. It has been proposed that a peripheral initiation of ɑ-synuclein accumulation may be associated with older age-at-onset, diffuse symptomatology, and faster clinical progression. In contrast, a cortex-based initiation of ɑ-synuclein accumulation, which is more common in younger patients, may lead to a more focal onset of motor symptoms, targeting primarily one arm or leg, owing to a process of retrograde nigral degeneration that follows the somatotopic organization of descending corticostriatal projections^22,24. We observed that the diffuse-malignant subtype was characterized by more severe motor and non-motor symptoms, older age, and faster progression, which matches the clinical phenotype of a peripheral-first type of ɑ-synucleinopathy. Conversely, the characteristics we observed for the mild-motor predominant subtype, especially with respect to the lateralization and focality of motor symptoms, overlap with the clinical phenotype of a central-first type of ɑ-synucleinopathy. Further research is required to investigate the relationship between clinically defined subtypes and subtypes defined by ɑ-synuclein propagation.

Previous research has shown that subtypes may not be stable over time^12,26−30. Subtype conversions could result from disease progression such that all patients converge towards a diffuse-malignant phenotype in late-stage PD¹³. Consistent with this hypothesis, we show that a majority of convertors were classified with a more severe subtype at follow-up, with conversions primarily occurring between neighboring subtypes, and not between subtypes at each end of the spectrum. However, we also found that some patients (12%) were classified with a more benign subtype at follow-up, which has previously been found also in a notable proportion of patients with de novo PD (23%)²⁶. Given the progressive nature of PD, it is unlikely that these improvements reflect a remission of symptoms. These improvements, and the resulting conversions to more benign subtypes, may rather be attributed to sources of sampling error, such as test-retest and assessor variability, and the relatively short follow-up period of one year that was employed in this study. Furthermore, initiation of treatment may explain why some symptoms improved with follow-up, leading to more benign subtype classification.

The subtyping approach proposed by Fereshtehnejad and colleagues⁷ includes the option to replace the cognitive composite score with a binary variable indicating MCI, which is regularly assessed in a clinical setting with measurements such as the MoCA. We found that the MCI-based classification yielded proportions of subtypes that showed high agreement with the original classification that relied on cognitive composite scores. The MCI-based classification also led to highly consistent between-subtype differences in baseline measurements and disease progression. This suggests that MCI, as defined by a single measure of global cognitive function, may be a reliable substitute in cases where the calculation of a composite score across multiple cognitive domains is not feasible. However, it should be noted that composite scores constitute more precise measurements of cognitive performance and will likely lead to more accurate and meaningful classifications.

Our study included patients with a range of disease durations from 0 to 5 years, which may have influenced subtype classifications^15,30. To account for this, we split the cohort at the median disease duration and applied separate classifications to the two resulting groups. There was no difference in disease duration between subtypes after combining the two groups. Our results are therefore not attributable to differences in disease duration. It may be argued that splitting the cohort at the median disease duration could influence the distribution of subtype counts. However, the proportions of patients assigned to each subtype was almost identical in the two groups. Furthermore, these proportions are consistent with previous findings^7,12,13, indicating that the median split did not bias subtype classification in favor of any one subtype.

Two concerns can be raised with respect to our analysis of progression. First, one year is a relatively short follow-up time for symptoms to worsen in PD. Second, progression was estimated based on two timepoints, potentially confounding change over time with sampling error. Both concerns are partially diminished by our large sample size, which provides adequate power to detect small changes over time while simultaneously ensuring that estimates of change are resistant to sampling error. However, further studies with longer follow-up times and additional timepoints will be required to establish the reliability of the between-subtype differences in progression that we observed.

We applied a set of recently proposed clinical criteria⁷ (referred to here as the MMP-IM-DM criteria) to classify early-stage PD patients from a large longitudinal cohort-study into mild-motor predominant, intermediate, or diffuse-malignant subtypes. Consistent with previous findings in de novo and mid-to-late-stage PD^7,12,13, subtypes differed in baseline symptom severity and rates of clinical progression across multiple clinical domains. In addition, we found that subtypes showed varying levels of motor symptom lateralization and focality, which may suggest differences in underlying pathophysiological mechanisms. These results confirm that the MMP-IM-DM criteria yield clinically meaningful subtypes in to early-stage PD.

Participants

Baseline and one-year follow-up data from 517 individuals with early-stage PD were extracted from the PPP database in November 2021. The PPP is an ongoing single-center longitudinal cohort study conducted at Radboud University Medical Center (Nijmegen, The Netherlands) where PD patients are followed for at least two years⁸. Data collection began at the end of 2017 and is currently ongoing. Here, we focused on the completed one-year progression data. Written informed consent was obtained for all participants. The study protocol was approved by a medical ethical committee (METC Oost-Nederland, formerly CMO Arnhem-Nijmegen; #2016–2934). Patients were eligible for the study if they were diagnosed with idiopathic PD by a certified neurologist, had 0–5 years disease duration, were ≥ 18 years of age, able to read and understand Dutch, able to comply with all aspects of the study protocol, and could provide informed consent. Exclusion criteria included co-morbidities severe enough to impair interpretation of parkinsonian disability, contraindications to magnetic resonance imaging, pregnancy or breastfeeding, and nickel allergy. During baseline assessments, the diagnoses of 11 participants were re-evaluated from PD to Parkinsonism (n = 8) or other (n = 3). These participants were excluded from further analyses. Further details can be found in the primary study protocol of the PPP⁸. Demographic information can be found in Table 1.

Clinical measurements

Motor symptoms were assessed in an off-medicated state (> 12h withdrawal) with the Movement Disorders Society Unified Parkinson Disease Rating Scale (MDS-UPDRS)³¹ part III by a trained assessor. Subscores of the MDS-UPDRS-III were defined for bradykinesia (11 scores, items 4–9 and 14), rigidity (5 scores, item 3), resting tremor (5 scores, items 17–18, jaw/lip tremor score excluded), action tremor (4 scores, items 15–16), and postural instability and gait disturbance (PIGD; 5 scores, MDS-UPDRS-III items 10–12 and MDS-UPDRS-II items 12–13)^9,32. Self-evaluation of motor symptoms was assessed using the MDS-UPDRS-II. Oral motor symptoms were assessed with the Radboud Oral Motor Inventory for Parkinson’s Disease (ROMP)³³. Cognitive performance was assessed with the Montreal Cognitive Assessment (MoCA)³⁴ as a measure of overall cognition, the Benton Judgement of Line Orientation (Benton JLO)³⁵ as a test of visuospatial perception, the Brixton Spatial Anticipation Test (Brixton)³⁶ that assesses executive function, the Semantic Fluency Test (SFT; 1-minute animal naming)³⁷ as a measure of verbal fluency, the Symbol Digit Modalities Test (SDMT, 90 seconds, oral version)³⁸ measuring processing speed, Letter-Number Sequencing (LNS) from the Wechsler Adult Intelligence Test – Fourth Edition³⁹ as an index of working memory, and the Rey Auditory Verbal Learning Test (RAVLT)^37,40 as a test of episodic memory. Autonomic function was assessed with the Scales for Outcomes in Parkinson’s disease (SCOPA-AUT)⁴¹. REM-sleep behavior was assessed with the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ)⁴². Neuropsychiatric symptoms were assessed with the Beck Depression Inventory (BDI-II)⁴³, State-Trait Anxiety Inventory (STAI)⁴⁴, and Questionnaire for Impulsive-Compulsive Disorders in PD (QUIP)⁴⁵. Quality of life was assessed with the Parkinson’s Disease Questionnaire-39 (PDQ-39)^46,47. Ophthalmologic problems were assessed with the Visual Impairment in Parkinson’s Disease Questionnaire (VIPD-Q)⁴⁸. Progression was defined for each clinical measurement as between-session difference scores (deltas; follow-up – baseline).

Subtype classification

Implementation of the MMP-IM-DM criteria depends on assessments of four clinical domains: motor symptoms, cognitive function, REM-sleep behavior disorder, and autonomic function⁷. In accordance with the original classification, motor symptoms were measured using the total scores of MDS-UPDRS-II and III together with the PIGD subscore, REM-sleep behavior disorder was measured using the RBDSQ total score, and autonomic function was measured using the SCOPA-AUT total score. Cognitive function was assessed with a battery of neuropsychological tests that included the Benton JLO, Brixton, SFT, SDMT, LNS, and an average across subscores of the RAVLT (trials 1–5, delayed recall, delayed recognition). Scores from measurements of cognitive function were transformed into age-, education- and sex-adjusted z-scores using extensive normative data^49,50. In the motor and cognitive domains, composite scores were calculated by averaging across the scores available within each domain (3 scores for the motor composite and 6 scores for the cognitive composite). Cohort-level means and standard deviations were calculated for each domain. These cohort-level summary statistics were used to calculate participant-specific z-scores (individual mean – cohort mean / cohort standard deviation). This resulted in four z-scores per participant that reflected the severity of symptoms within each domain relative to the entire cohort. Within each domain, participant-specific z-scores were transformed into percentiles to which the MMP-IM-DM criteria could be applied. Patients with all scores below the 75th percentile were classified as mild-motor predominant. Patients with composite motor scores and at least one non-motor score above the 75th percentile, or with all three non-motor scores above the 75th percentile, were classified as diffuse-malignant. The remaining patients were classified as intermediate. Patients with missing data in one or more domains were classified as an undefined subtype and were excluded from further analysis. The influence of disease duration on subtype classification was accounted for by splitting the cohort at the median disease duration (33 months since diagnosis) and performing separate classifications for each of the two groups following the procedure above¹⁵. The two groups were then merged into a single cohort before further analysis. This ruled out the possibility that inter-individual differences in disease duration (and hence disease severity) determined the subtype classification rather than clinical phenotype.

Classification yielded highly similar proportions of subtypes above and below the median disease duration split. At baseline, 218 (50%) patients had a disease duration above the median (104 mild-motor predominant, 87 intermediate, and 27 diffuse-malignant) and 218 (50%) had a disease duration below the median (109 mild-motor predominant, 78 intermediate, and 31 diffuse-malignant). At follow-up, 178 (49%) patients had a disease duration above the median (83 mild-motor predominant, 75 intermediate, and 20 diffuse-malignant) and 187 (51%) had a disease duration below the median (95 mild-motor predominant, 67 intermediate, 25 diffuse-malignant).

Subtype conversions

Subtype classifications were performed separately at baseline and at one-year follow-up to assess longitudinal changes in subtype classification. For both baseline and follow-up classifications, the cognitive composite measure was exchanged for a binary variable indicating mild cognitive impairment (MCI), defined as education-adjusted scores below 26 on the MoCA⁵¹. Separate classifications were performed based on baseline z-scores to characterize subtype changes relative to baseline and session-specific z-scores to characterize subtype changes relative to peers.

Partitioning of overall motor symptom severity

Proportions were calculated for bradykinesia, rigidity, tremor, PIGD, and other remaining items of the MDS-UPDRS-III by first dividing each motor subscore by the number of items that was used to calculate them (see above). This scaled each subscore to a range from 0 to 4³². Each subscore was divided by the sum of all scaled subscores to express each subscore as a percentage.

Localization of bradykinesia-rigidity symptoms

Motor symptoms associated with PD may be lateralized, with one side being more affected than the other, and focal, with the upper extremities being more affected than the lower ones. Given that the diffuse-malignant subtype is characterized by diffuse involvement of motor and non-motor symptoms, we tested the hypothesis that this subtype is also characterized by a more diffuse distribution of motor symptom severity, which is defined here as reduced lateralization and focality of motor symptoms²². Assessments of lateralization and focality assumes the presence of motor symptoms. This assumption held for bradykinesia and rigidity, which were present in all included patients. In contrast, resting and action tremor were absent in a large proportion of patients (resting tremor, n = 151 [38%]; action tremor, n = 99 [22%]), rendering these symptoms relatively uninformative for assessments of lateralization and focality. Tremor was therefore excluded from further analyses of motor symptom lateralization and focality. For each participant, the lateralization of bradykinesia and rigidity was calculated for MDS-UPDRS-III items that encoded side (right vs. left) whereas focality was calculated for items that encoded limb (arm vs. leg). Right-left lateralization was calculated as the absolute difference between the severity of symptoms associated with each side divided by their summed severity (|right - left|/right + left). Arm-leg focality was calculated in the same way (|arm - leg|/arm + leg). This resulted in lateralization and focality scores ranging from 0 to 1 where 0 indicated an even distribution of severity across sides or limbs and 1 indicated that severity was focused entirely on one side or limb. Lateralization and focality scores were calculated separately for bradykinesia and rigidity. These were combined as a weighted sum weighted based on the number of items that each symptom consisted of (10 for bradykinesia and 4 for rigidity).

Statistical analysis

Data preparation and imputation of missing data. All data preparation and statistical analysis were conducted in R (https://www.r-project.com). Values of dependent variables above or below 3 standard deviations from the mean were treated as missing values. Participants with missing baseline data were excluded from further analysis. Multiple imputation involving predictive mean matching was implemented with the to correct for drop-out in analyses of progression⁵². For analyses of progression, the number of imputed data sets were calculated as the percentage of missing data (see Table 3) times 5. Each imputation was iterated 10 times.

Between-subtype comparisons of clinical phenotype and progression. One-way analyses of covariance (ANCOVAs) with SUBTYPE (mild-motor predominant, intermediate, diffuse-malignant) as a between-subjects factor were used to assess differences in baseline characteristics and one-year progression between PD subtypes. Analyses of baseline characteristics were conducted on the original data set following list-wise deletion of missing values and included age⁵³, sex⁵⁴, and disease duration³⁰ as covariates of no interest. Dependent variables were log-transformed if possible. Kruskal-Wallis rank sum tests followed by pairwise Wilcoxon rank sum tests were used to assess baseline characteristics whenever ANCOVA assumptions were not met. Analyses of progression were conducted on imputed data sets and included the baseline as an additional covariate of no interest⁵⁵. Pairwise comparisons of estimated marginal means were conducted as post-hoc tests, adjusting for multiple comparisons using a multivariate t-distribution. Sensitivity analyses of progression were conducted on non-imputed data sets following list-wise deletion of missing values. Comparisons were re-performed using the classification where the cognitive composite score was replaced with MCI to assess the potential difference in sensitivity between these two options. Chi-square tests were used to assess the effect of TIME (baseline, one-year follow-up) on subtype counts. Agreement between classifications at baseline and one-year follow-up was assessed with Cohen’s kappa.

Funding: The Michael J. Fox Foundation for Parkinson’s Research. The Center of Expertise for Parkinson & Movement Disorders was supported by a center of excellence grant of the Parkinson’s Foundation.

Acknowledgements

We thank the patients who participated in the Personalized Parkinson Project, the assessors who performed data collection during this project, and the technical team from ‘Polymorphic encryption and pseudonymization for personalized healthcare’ who made it possible to extract the data analyzed in the current study. The current study was funded in part by the Michael J. Fox Foundation (grant ID #15581 to RCH).

Author contributions

NML, MEJ, and RCH contributed to the design of the study, statistical analysis, and interpretation of the data. MEJ and NML conducted the statistical analyses under the supervision of RCH. MEJ drafted the manuscript. RPCK assisted in statistical analyses. RPCK and BRB contributed to interpretation of the data and revisions of the manuscript. All authors revised and approved the submitted manuscript.

Competing interests

Nothing to declare.

Correspondence

Correspondence and requests for materials should be addressed to Martin E. Johansson.

Data availability

The clinical dataset analyzed during the current study will be made publicly available upon the completion of the Personalized Parkinson Project.

Code availability

The analyses in the current study were conducted using publicly available ‘R’-packages. Rmarkdown files containing the analysis code can be made available upon request.

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Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study

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Abstract

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Introduction

Results

Subtyping

Between-subtype differences in baseline characteristics

Between-subtype differences in one-year clinical progression

Sensitivity analyses

Subtype conversions

Discussion

Conclusion

Methods

Participants

Clinical measurements

Subtype classification

Subtype conversions

Partitioning of overall motor symptom severity

Localization of bradykinesia-rigidity symptoms

Statistical analysis

Declarations

References

Additional Declarations

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